system

Abstract

Provide a system. A method for receiving additional information about a network location from a user; means for transmitting the received additional information to a server; means for analyzing the received additional information and generating data necessary to update the management table and the network configuration diagram; means for updating the management table using the generated data; means for updating the network configuration diagram using the generated data; means for outputting the updated management table and network configuration diagram to a user; A system including:

Description

[Technical Field]

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

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

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

[0004] In network management, adding new base stations is a time-consuming and labor-intensive process. Manually entering base station names, line details, and router parameters (such as IP addresses) and updating management tables and network diagrams is particularly prone to human error and is inefficient. Furthermore, if the data in the management tables and diagrams does not match, troubleshooting can become difficult later. To solve these problems, an efficient and accurate management method is needed. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means. A means is provided for a user to input information about a network location to be added from a terminal and for that information to be sent to a server. The server validates the received information and further analyzes it using an AI engine. A means is provided for generating data necessary for updating the management table and network configuration diagram based on the analyzed data. A means is provided for automatically updating the management table and network configuration diagram using the generated data and outputting the updated information to the user. This makes the process of adding network locations more efficient, reduces human error, and enables accurate and rapid management.

[0006] A "network location" is a geographical or logical location for data communications within a network.

[0007] "Additional information" is a general term for various data that need to be newly input, such as the site name, line details, and router parameters related to the network site.

[0008] "User" means an individual or entity that utilizes the system to enter and verify network location information.

[0009] A "terminal" is an electronic device that a user operates and uses to input information about a network location.

[0010] A "server" is a computer system that processes and analyzes additional information received from a user.

[0011] "Validation" is the process of ensuring that received data is in the correct format and contains all required information.

[0012] An "AI engine" is a program that uses artificial intelligence technology to analyze received data and generate the data necessary for management tables and network configuration diagrams.

[0013] A "management table" is a database or data structure for recording and managing detailed information about network locations (location names, line details, IP addresses, etc.).

[0014] A "network configuration diagram" is a diagram that visually shows network locations and their connections.

[0015] A "node" is a unit that represents a specific network location in a network configuration diagram.

[0016] A "data store" is a storage device or database system for storing data on management tables and network configuration diagrams.

[0017] "Output" is the process of displaying or returning the results of processing on the server to the user. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The system for implementing this invention aims to easily and accurately manage information about new network locations added by users, and automatically update management tables and network configuration diagrams. This system transmits information entered by users from their terminals to a server, which analyzes it using an AI engine, thereby achieving automatic generation and updating of data.

[0040] First, the user enters additional information about the network site (site name, line details, router IP address, etc.) into the terminal. For example, the user enters information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" into the form. The terminal then sends this information to the server.

[0041] The server validates the received information to ensure it is in the correct format and is complete. If all validations are met, the server passes the data to the AI ​​engine and begins analysis. The AI ​​engine generates the data necessary to update the management table and network diagram. For example, if the AI ​​engine receives the information "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it will generate a "management table entry" and a "diagram node" for the update.

[0042] The server then uses the generated data to update the management table, which is a database that records and manages information about all nodes in the network, and adds an entry for the new node. This entry includes the node name, line details, IP address, and so on. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0043] Finally, the server outputs and displays the updated management table and network configuration diagram on the user's terminal, allowing the user to immediately check the information about the newly added base.

[0044] For example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives and validates this information. Next, the AI ​​engine analyzes the information and adds the "Tokyo Office" location to the management table and adds it as a new node to the network configuration diagram. The server then outputs this updated information to the user's device, where the user can view it.

[0045] In this way, the system provides accurate and efficient network management with minimal user intervention.

[0046] The processing flow will be explained below.

[0047] Step 1:

[0048] The user enters information about a new network site into the terminal. Specifically, the user enters information such as the site name, line details, and router IP address into the input form. For example, the user enters information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1."

[0049] Step 2:

[0050] The device sends the input information to the server as an HTTP request in JSON format.

[0051] Step 3:

[0052] The server receives the HTTP request and analyzes the data sent. Specifically, it parses the request body in JSON format and obtains each key and value.

[0053] Step 4:

[0054] The server validates the data it receives, checking that it is formatted correctly and that all required fields are filled in. If the data is invalid, it returns an error.

[0055] Step 5:

[0056] The server passes the data that has passed validation to the AI ​​engine, which then begins analysis. Specifically, the AI ​​engine generates the data necessary to update the management table and network configuration diagram based on the site name, line details, and router IP address.

[0057] Step 6:

[0058] The server updates the management table using the data returned from the AI ​​engine, specifically by inserting new records into the management table database or updating existing records.

[0059] Step 7:

[0060] The server also uses the generated data to update the network diagram, specifically adding new nodes to the network diagram database and setting connection information.

[0061] Step 8:

[0062] The server saves the updated management tables and network diagrams, writes them to the necessary data stores, and also performs checks to ensure data consistency and integrity.

[0063] Step 9:

[0064] The server generates a response indicating that the update is complete and sends it to the terminal, which includes the updated management table and details of the network topology diagram.

[0065] Step 10:

[0066] The terminal receives the response from the server and displays the updated results to the user. Specifically, it visually displays the updated management table and network configuration diagram, allowing the user to check the new location information.

[0067] Example 1

[0068] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0069] With existing network management systems, it is time-consuming to manually update management tables and network diagrams with additional information about network locations, which can lead to inaccuracies. Therefore, there is a need for a method to easily and accurately manage network location information and automatically update management tables and network diagrams.

[0070] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0071] In this invention, the server includes means for validating the additional information for the network site and confirming that it is in the correct format and complete, means for analyzing the received additional information and passing the data to an AI engine to generate data necessary for updating the management table and network configuration diagram, and means for updating the management table using the generated data. This makes it possible to automatically update the management table and network configuration diagram accurately and efficiently based on the network site information entered by the user.

[0072] "Network location" means a physical or logical location connected to a network, including the equipment and infrastructure for data transfer and communications.

[0073] "Additional information" refers to detailed data about a network site, including the site name, line details, router IP address, etc.

[0074] "User" means an individual or organization that uses the system to enter, manage, and review information about a network location.

[0075] "Terminal" refers to a device used by a user, such as a computer, tablet, or smartphone, and is a device for inputting and displaying information.

[0076] "Server" refers to a centralized computer system that provides services over a network, processes data received from users, and updates management tables and network diagrams.

[0077] "Validation" refers to the process of verifying data to ensure it is accurate and complete, including format and content checks.

[0078] "Analysis" refers to the process of using an AI engine to generate the necessary information based on the received data.

[0079] An "AI engine" refers to a system that uses artificial intelligence technology to analyze data and automatically generate management table entries and network configuration diagram nodes.

[0080] "Management table" refers to a database that records and manages information on all locations within a network.

[0081] A "network configuration diagram" refers to a diagram that visually shows each location within a network and their connection relationships.

[0082] "Generated data" refers to the management table entries and network diagram nodes that are analyzed and generated by the AI ​​engine.

[0083] This invention is a system that allows users to easily and accurately manage information about newly added network locations and automatically update management tables and network configuration diagrams. This system sends information entered by users to a terminal to a server, analyzes it using an AI engine, and automatically generates and updates data.

[0084] Hardware and software used

[0085] The system includes the following hardware and software:

[0086] Device: A computer, tablet, smartphone, etc. that a user operates.

[0087] Server: A centralized computer system.

[0088] AI Engine: An artificial intelligence system that performs data analysis and automatic generation.

[0089] Database: A database system for storing management tables.

[0090] Internet connection: Allows data communication between the device and the server.

[0091] Specific operation of the system

[0092] The user accesses the terminal and enters additional information about the network site (e.g., "site name," "line details," "router IP address," etc.). For example, the user enters "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1." The terminal then sends this information to the server.

[0093] The server validates the received information, checking whether the location name, line details, and router IP address are entered in a valid format. If validation is successful, the server passes the data to the AI ​​engine to begin analysis.

[0094] The AI ​​engine generates the data necessary to update the management table and network diagram. For example, it analyzes information on "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" to generate a "management table entry" and a "diagram node."

[0095] The server uses the generated data to update the management table, which records and manages information about all nodes in the network, and adds entries for new nodes. This includes the node name, line details, IP address, etc.

[0096] The server also updates the network diagram based on the generated data, adding new locations as nodes and visually showing their connections with other network elements.

[0097] Finally, the server outputs the updated management table and network configuration diagram to the terminal, allowing the user to immediately check them.

[0098] Specific examples

[0099] For example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," validation occurs when the server receives this information. The AI ​​engine then generates a "management table entry" and a "configuration diagram node" and returns them to the server. The server then updates the management table and network configuration diagram using the updated data and outputs this information to the user's device. The user can immediately view the new information.

[0100] Prompt Sentence Examples

[0101] An example of a prompt to be input to the generative AI model is as follows:

[0102] Input information: {

[0103] "Office Name": "Tokyo Office",

[0104] "Line details": "Fiber 1Gbps",

[0105] "Router IP Address": "192.168.3.1"

[0106] }

[0107] Use this information to generate and update management table entries and network diagram nodes.

[0108] In this way, the system provides accurate and efficient network management with minimal user intervention.

[0109] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0110] Step 1:

[0111] The user accesses the terminal and enters additional information about the network site. Specifically, the user enters the "site name," "line details," and "router IP address" into the input form. For example, the user might enter "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," and click the "Submit" button. The entered information is then imported into the terminal's system.

[0112] Step 2:

[0113] The device sends the additional information received from the user to the server. Specifically, the device sends the information entered in the form to the server as an HTTP POST request. This request contains data in JSON format. The sent information reaches the specified endpoint on the server.

[0114] Step 3:

[0115] The server validates the additional information it has received. Specifically, the server checks whether the site name, line details, and router IP address have been entered in the correct format. At this stage, it checks the format of the entered information (for example, whether the IP address format is correct) and whether all required fields have been filled in. If invalid data is found, it generates an error message and returns it to the terminal as an HTTP response. If validation is successful, it proceeds to the next step.

[0116] Step 4:

[0117] The server sends the information that has passed validation to the AI ​​engine. Specifically, the server sends the data to the AI ​​engine's API endpoint. At this time, the data to be sent uses the following prompt:

[0118] Input information: {

[0119] "Location Name": "Osaka Branch",

[0120] "Line details": "Fiber 500Mbps",

[0121] "Router IP Address": "192.168.2.1"

[0122] }

[0123] Use this information to generate and update management table entries and network diagram nodes.

[0124] Based on this prompt, the AI ​​engine begins analysis.

[0125] Step 5:

[0126] The AI ​​engine returns the analysis results to the server. Specifically, the AI ​​engine analyzes the input information and generates "management table entries" and "configuration diagram nodes." This data includes information such as the location name, line details, and IP address. The server receives this generated data.

[0127] Step 6:

[0128] The server updates the management table using the data received from the AI ​​engine. Specifically, the server adds a new entry to the database that stores the management table. This entry includes the branch name, line details, IP address, etc. For example, "Osaka Branch, Fiber 500Mbps, 192.168.2.1" is added as a new entry.

[0129] Step 7:

[0130] The server updates the network diagram using the generated data. Specifically, the server adds the new node to the network diagram database and updates the connections with other network elements. The new location is visually added to the updated diagram.

[0131] Step 8:

[0132] The server outputs the updated management table and network configuration diagram to the user's terminal. Specifically, the server returns the updated data to the terminal as an HTTP response. The terminal displays the received data on the screen, allowing the user to immediately check the new information. For example, "Osaka Branch, Fiber 500Mbps, 192.168.2.1" is added to the management table, and a new node is displayed on the network configuration diagram.

[0133] (Application example 1)

[0134] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0135] With conventional network site management systems, information about newly added sites must be manually updated in management tables and network configuration diagrams, which reduces efficiency when handling large amounts of data. Furthermore, when new equipment within a factory is added to the network, it is difficult to manage that information in real time, which can lead to incorrect information being updated. Furthermore, there is a lack of a way to visually check the network configuration, making it difficult for administrators to easily grasp the status of their equipment.

[0136] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0137] In this invention, the server includes means for receiving additional information about network locations from a user, means for transmitting the received additional information to the server, means for analyzing the received additional information and generating data necessary for updating the management table and the network configuration diagram, means for updating the management table using the generated data, means for updating the network configuration diagram using the generated data, means for outputting the updated management table and network configuration diagram to the user, means for collecting information about newly added equipment in the factory and automatically updating the management table and the network configuration diagram, and means for visually displaying the updated management table and the network configuration diagram. This provides an environment in which additional information about network locations in the factory can be automatically managed and visually confirmed, preventing errors and enabling efficient management.

[0138] A "network location" refers to a specific location or place where various digital devices and machines are connected.

[0139] "Means for receiving additional information" refers to the mechanism for collecting new data entered by the user.

[0140] "Means for sending to server" refers to the process of transferring collected data to the server.

[0141] "Means for analyzing and generating data necessary for updating the management table and configuration diagram" refers to a mechanism for analyzing input data and generating information necessary for updating the network management table and configuration diagram.

[0142] "Means for updating the management table" refers to a method for updating an existing management table to the latest version based on newly generated data.

[0143] "Means for updating a network configuration diagram" refers to a method for updating an existing network configuration diagram to the latest version based on newly generated data.

[0144] "Means of outputting to the user" refers to the mechanism for displaying and outputting the updated management table and network configuration diagram on the user's terminal.

[0145] "Means for collecting information on factory equipment and automatically updating management tables and configuration diagrams" refers to a system that automatically collects information on new machines or robots in the factory when they are connected to the network, and updates the management tables and configuration diagrams.

[0146] "Means for visual display" refers to a method for providing the user with an updated network configuration diagram or management table in a form that allows the user to visually confirm the updated network configuration diagram or management table.

[0147] The present invention is a system that automatically manages additional information for network locations within a factory and allows a manager to visually check it. A specific embodiment for realizing this system will be described below.

[0148] Program Generation

[0149] The system is built using the Python language. The main libraries used are the standard library for data validation, NetworkX and Matplotlib for generating and visualizing network configurations, and the AI ​​engine is designed to use generative AI models.

[0150] Natural language explanation of the process

[0151] The system works as follows:

[0152] 1. Collection and transmission of additional information about network locations

[0153] Using an application on a smartphone or tablet, users enter information (site name, line details, IP address) about the newly added factory equipment (robots and machines) into a form. This information is then sent from the device to the server.

[0154] 2. Data validation and analysis on the server

[0155] The server validates the received additional information to ensure that the format and content are correct. It then uses an AI engine to analyze the data and generate the data needed to update the management table and network diagram. This process utilizes a generative AI model to efficiently generate the data.

[0156] 3. Update management tables and network diagrams

[0157] Based on the generated data, the server updates the existing management table to the latest version. It also updates the network configuration diagram to visually reflect the new location and equipment information. This makes it possible to understand the network configuration within the factory at a glance.

[0158] 4. User Output and Visualization

[0159] The updated management table and network configuration diagram are output to the user's terminal in real time and displayed visually, allowing factory managers to immediately check information on newly added equipment.

[0160] Adding specific examples

[0161] For example, if a user enters the information "Maintenance Robot," "WiFi 600Mbps," and "192.168.0.40," the server receives and validates this information. The AI ​​engine then analyzes the information and adds a location called "Maintenance Robot" to the management table and adds it as a new node to the network configuration diagram. This allows factory managers to check the latest network status via smartphones or tablets.

[0162] Prompt Sentence Examples

[0163] Enter the information for your new factory robot. Include the site name, line details, and IP address. For example, "Site name: Maintenance Robot, Line details: WiFi 600Mbps, IP address: 192.168.0.40".

[0164] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0165] Step 1:

[0166] Collecting and sending additional information about your network locations

[0167] The user uses a smartphone or tablet application to input information about the newly added factory equipment (robots and machines). This information includes the base name, line details, and IP address. The input information is sent from the terminal to the server. As a specific example, the inputs are "Base name: Maintenance Robot," "Line details: WiFi 600Mbps," and "IP address: 192.168.0.40." The input for this step is the equipment information entered by the user, and the output is the data sent to the server.

[0168] Step 2:

[0169] Data Validation

[0170] The server validates the additional information it receives, specifically checking that the site name is entered correctly, that the line details are correct, and that the IP address is entered in the correct format. The data validation process ensures that the information entered is complete and accurate. If the data is successfully validated, it moves on to the next step. The input for validation is the data sent to the server, and the output is the validated data.

[0171] Step 3:

[0172] Data analysis

[0173] The server passes the data that has passed validation to the AI ​​engine. The AI ​​engine analyzes this data and generates new data needed to update the management table and network diagram. For example, it analyzes the location information for the "Maintenance Robot" and uses that data to generate a new entry in the management table and add a new node to the network diagram. The input to this step is validated data, and the output is the generated data.

[0174] Step 4:

[0175] Update management table

[0176] The server updates the management table using the data generated by the AI ​​engine. The management table is a database that records information about all network locations. New entries are added and existing information is kept up to date. For example, information about a "Maintenance Robot" is added as a new entry. The input to this step is the generated data, and the output is the updated management table.

[0177] Step 5:

[0178] Update the network diagram

[0179] The server updates the network diagram using the data generated by the AI ​​engine. New locations are added as nodes to the diagram, and their connections with other network elements are visually displayed. For example, a "Maintenance Robot" is added as a new node to the diagram, along with its line details and IP address. The input to this step is the generated data, and the output is an updated network diagram.

[0180] Step 6:

[0181] User Output and Visualization

[0182] The server outputs the updated management table and network configuration diagram to the user's device. This information is displayed visually, allowing the factory manager to easily check the new location information. Specifically, the user can view the updated network configuration diagram in real time on a smartphone or tablet. The input for this step is the updated management table and network configuration diagram, and the output is the visual information displayed on the user's device.

[0183] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0184] The system for implementing the present invention aims to efficiently and accurately manage information on newly added network nodes by users and automatically update the management table and network configuration diagram. Furthermore, the system includes an emotion engine for recognizing user emotions and improving the operating experience.

[0185] First, the user enters information about the new network site (site name, line details, router IP address, etc.) into the terminal. For example, information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" is entered into the form. The terminal then sends this information to the server.

[0186] The server validates the received information to ensure it is in the correct format and is complete. If all validations are passed, the server passes the data to the AI ​​engine and begins analysis. The AI ​​engine generates the data necessary to update the management table and network configuration diagram. For example, if the AI ​​engine receives the information "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it will generate a "management table entry" and a "configuration diagram node" for the update.

[0187] The server then uses the generated data to update the management table, which is a database that records and manages information about all nodes in the network, and adds an entry for the new node. This entry includes the node name, line details, IP address, and so on. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0188] Furthermore, this system incorporates an emotion engine to recognize the user's emotions. While the user is inputting information, the emotion engine analyzes the user's facial expressions and voice using a camera and microphone. The emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback.

[0189] For example, if the emotion engine determines that the user is feeling stressed while inputting information, the server can display input assistance and operation guides to the user. Also, if the server determines that the user is satisfied after adding a new location, it can highlight that result and provide positive feedback.

[0190] As a specific example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives this information and validates it. Next, the AI ​​engine analyzes it, adds the location "Tokyo Office" to the management table, and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it recognizes that the user is confused, it provides assistance with the input. Finally, the server outputs this updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[0191] In this way, the system provides accurate and efficient network management while minimizing user interaction, and also provides appropriate feedback according to the user's emotional state.

[0192] The processing flow will be explained below.

[0193] Step 1:

[0194] The user enters information about the new network location into the terminal. Specifically, the user enters information such as the location name "Osaka Branch," line details "Fiber 500Mbps," and router IP address "192.168.2.1" into the input form.

[0195] Step 2:

[0196] The terminal sends the input information to the server. Specifically, the data is sent as an HTTP request in JSON format.

[0197] Step 3:

[0198] The server analyzes the received HTTP request and parses the transmitted data. Specifically, it parses the request body in JSON format and obtains each key and value.

[0199] Step 4:

[0200] The server validates the data it receives, ensuring that it is formatted correctly and that all required fields are filled in. If the data is invalid, it generates an error message and sends it back to the terminal.

[0201] Step 5:

[0202] The server passes the data that has passed validation to the AI ​​engine, which then begins analysis. Specifically, the AI ​​engine generates the data necessary to update the management table and network configuration diagram based on the site name, line details, and router IP address.

[0203] Step 6:

[0204] The server updates the management table using the data returned from the AI ​​engine. Specifically, it inserts a new record into the management table database, adding the branch name "Osaka Branch," line details "Fiber 500Mbps," and router IP address "192.168.2.1."

[0205] Step 7:

[0206] The server updates the network diagram using the generated data. Specifically, it adds a new node, "Osaka Branch," to the network diagram database and sets its IP address, "192.168.2.1," and its connection information.

[0207] Step 8:

[0208] The server saves the updated management table and network diagram and writes it to the data store, performing additional checks to ensure data consistency and integrity.

[0209] Step 9:

[0210] The server uses an emotion engine to analyze the user's emotional state. Specifically, it analyzes the user's facial expressions and voice in real time through a camera and microphone to determine the user's emotional state (stress, frustration, joy, etc.).

[0211] Step 10:

[0212] The server generates appropriate feedback based on the user's emotional state. For example, if it determines that the user is feeling stressed, it displays input assistance and operation guides on the device. Conversely, if the user is satisfied, it displays positive feedback that emphasizes the user's satisfaction.

[0213] Step 11:

[0214] The server generates a response indicating that the update is complete and sends it to the terminal. The response includes details of the updated management table and network topology diagram, as well as a feedback message.

[0215] Step 12:

[0216] The terminal receives the response from the server and displays the updated results to the user. Specifically, it visually displays the updated management table and network configuration diagram, and displays feedback messages so that the user can check the results of the system's operation.

[0217] Example 2

[0218] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0219] Modern network management requires efficient and accurate management of additional information for new locations and smooth updates to management tables and network diagrams. It is also important to provide a good user experience by reducing the stress and confusion associated with data entry tasks. However, with conventional systems, it was difficult to perform these tasks efficiently and consistently.

[0220] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for receiving additional information about network nodes from a user; means for transmitting the received additional information to the server; means for validating the received additional information; means for analyzing the additional information using an AI engine and generating data necessary for updating the management table and the communication configuration diagram; means for updating the management table using the generated data; means for updating the communication configuration diagram using the generated data; means for outputting the updated management table and the communication configuration diagram to the user; and means for providing feedback according to the user's emotional state, which includes an emotion engine for analyzing the user's emotions. This improves the accuracy and efficiency of network management and improves the user's operation experience.

[0221] "Network location" is a term that refers to a specific physical or logical location or device within a computer network.

[0222] "Additional information" refers to new or changed data a user has about a network location.

[0223] "User" refers to a person who operates or uses this system.

[0224] A "server" is a computer connected to a network, and is a device that processes and manages data.

[0225] "Validation" is the process of checking whether entered data is of the correct format and content.

[0226] An "AI engine" is software or hardware that uses artificial intelligence technology to analyze and generate data.

[0227] A "management table" is a database or data structure for recording and managing information about network locations.

[0228] A "communication configuration diagram" is a diagram that visually shows each element in a network and its connection relationships.

[0229] The "emotion engine" is a system that analyzes the user's emotional state using input from a camera, microphone, etc., and provides appropriate feedback.

[0230] "Feedback" means the response or assistance information provided by the system to the user.

[0231] "Data generation" is the process of creating new data or required data structures based on received information.

[0232] The system for implementing the present invention comprises the following elements: It efficiently and accurately manages information about new network nodes added by users, automatically updates the management table and network configuration diagram, and includes an emotion engine for recognizing user emotions and improving the operating experience.

[0233] First, the user enters information about the new network site (site name, line details, IP address, etc.) on a device (PC, tablet, etc.). For example, information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" is entered into a form. The device sends this information to the server using a secure communication method (e.g., HTTPS).

[0234] The server validates the received information. Validation checks the accuracy of the branch name, the format of the IP address, the validity of the line details, etc. For example, it checks whether "Osaka Branch" is a valid string, and whether "192.168.2.1" is the correct IP address format. If all validations are passed, the server passes the data to the AI ​​engine to begin analysis.

[0235] The AI ​​engine uses the generative AI model to generate the data necessary to update the management table and network diagram. For example, when it receives "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it generates a management table entry and a diagram node. This allows the new branch information to be reflected in the management table and network diagram.

[0236] The server then uses the generated data to update the management table, which is a database that records information about all nodes in the network. The entry for the new node includes information such as the node name, line details, and IP address. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0237] Furthermore, this system incorporates an emotion engine to recognize the user's emotions. While the user is entering information, the emotion engine uses a camera and microphone to analyze the user's facial expressions and voice. The emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback. For example, if the emotion engine determines that the user is feeling stressed while entering information, the server will display input assistance and operation guides to the user. Also, if the server recognizes that the user is satisfied after adding a new location, it will highlight this result and provide positive feedback.

[0238] As a specific example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives this information and validates it. Next, the AI ​​engine analyzes it, adds the location "Tokyo Office" to the management table, and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it recognizes that the user is confused, it provides assistance with the input. Finally, the server outputs this updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[0239] Example prompt sentence:

[0240] "Please explain a system that, after a user inputs new network location information, validates the data, updates the management table and network diagram, and analyzes the user's sentiment in the process to provide appropriate feedback."

[0241] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0242] Step 1:

[0243] The user enters information about a new network site on the terminal. The information entered includes the site name, line details, IP address, etc. For example, "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1" are entered. This information is entered on a form and registered by pressing the Enter key or the submit button. The input data is collected as fields in the input form and converted to JSON format. The input data is sent to the next step.

[0244] Step 2:

[0245] The terminal sends the input information to the server. The terminal packages the input data in JSON format and sends it to the server using a secure communication protocol (e.g., HTTPS). The data is encrypted during transmission. The server receives the transmitted data and stores it in a database. The input data ("Tokyo Office", "Fiber 1Gbps", "192.168.3.1") is sent to the server, triggering a signal to start validation.

[0246] Step 3:

[0247] The server validates the information it receives. The server checks the data format, content integrity, and the accuracy of IP addresses. The validation process uses a validation script to ensure the data is in the correct format and that required fields are filled in. For example, it verifies that "Tokyo Office" is a valid location name field and that "192.168.3.1" is a valid IP address format. If validation is successful, the validated data is passed to the next analysis step.

[0248] Step 4:

[0249] The server sends the data to the AI ​​engine and instructs it to start analysis. The AI ​​engine uses the generative AI model to analyze the additional information it receives. The server sends the validated data to the AI ​​engine and begins analysis to generate a new dataset. For example, based on the input "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the AI ​​engine generates the necessary data, such as management table entries and configuration diagram nodes. The generated data is sent back from the AI ​​engine to the server.

[0250] Step 5:

[0251] The server updates the management table using the generated data. The server receives the data returned from the AI ​​engine and uses that data to update the management table database. For example, new location information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1" is added to the management table. The updated management table results are passed to the next configuration diagram update step.

[0252] Step 6:

[0253] The server updates the communication configuration diagram using the generated data. The server updates the network configuration diagram based on the generated data. New location information is visually added, and the connection relationships with existing network elements are shown. For example, a new node called "Tokyo Office" is added to the configuration diagram, and its connection relationships are visualized. The updated configuration diagram data is passed to the next output step.

[0254] Step 7:

[0255] The emotion engine analyzes the user's emotions. It analyzes the user's facial expressions and voice as they are inputting, and identifies their emotional state in real time. The emotion engine captures and analyzes data from the camera and microphone in real time. For example, if the user is feeling stressed, it recognizes this state and notifies the server. The notified emotional data is passed on to the next feedback step.

[0256] Step 8:

[0257] The server then feeds the results back to the user. The server provides feedback to the user based on the results of updating the management table and communication configuration diagram, and the analysis results of the emotion engine. For example, if the user is satisfied, this fact is highlighted and positive feedback is provided. If the user is feeling stressed, operation guides and input assistance are displayed. The feedback content is output to the terminal, allowing the user to visually confirm it.

[0258] (Application example 2)

[0259] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0260] In current logistics centers, efficient and accurate management of information about newly added network locations is an important issue. Furthermore, a lack of appropriate feedback based on the worker's emotions and status can lead to problems such as reduced operational efficiency and satisfaction. The present invention aims to solve these problems and improve the efficiency of network management in logistics centers and worker satisfaction.

[0261] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving additional information about network locations from a user, means for transmitting the received additional information to the server, means for analyzing the received additional information and generating data necessary for updating the management table and the network configuration diagram, means for updating the management table using the generated data, means for updating the network configuration diagram using the generated data, means for outputting the updated management table and the network configuration diagram to the user, and means including an emotion engine for recognizing the user's emotions and improving the operating experience. This not only enables efficient and accurate network management in a logistics center, but also provides feedback according to the emotions of workers, thereby improving operating efficiency and satisfaction.

[0262] A "network location" is a location or facility that is newly added to the network configuration.

[0263] "Additional information" is detailed information about the network location (e.g., location name, line speed, IP address).

[0264] A "user" is a person or entity that operates the system and inputs additional information for a network location.

[0265] The "server" is the central component of the system that receives and analyzes additional information sent by users and updates the management table and network configuration diagram.

[0266] The "management table" is a database for recording and managing information on all locations within the network.

[0267] A "network configuration diagram" is a diagram that visually shows the locations within a network and their connection relationships.

[0268] An "emotion engine" is an element of the system that uses a camera, microphone, etc. to analyze a user's facial expressions and voice and identify their emotional state.

[0269] "Validation" is the process of ensuring that any additional information received is accurate and complete.

[0270] An "AI engine" is an element of the system that uses artificial intelligence to analyze additional information and generate the data necessary to update management tables and network diagrams.

[0271] "Feedback" refers to the support and positive reactions provided by a system in response to a user's actions and emotions.

[0272] The system for implementing the present invention aims to efficiently and accurately manage and update additional information for network locations in a logistics center, and also includes an emotion engine for recognizing user emotions and improving the operating experience.

[0273] Specifically, a user enters information about a new network location into a management terminal at a logistics center. This information includes the location name, line details, IP address, etc. For example, information such as "Center A," "Fiber 500Mbps," and "192.168.2.1" might be used. Once the user has finished entering this information, the terminal sends it to the server. The server validates the received information to ensure it is in the correct format and complete. If all validations are met, the server passes the data to the AI ​​engine and begins analysis.

[0274] The AI ​​engine generates the data necessary to update the management table and network diagram. For example, after receiving information such as "Center A," "Fiber 500Mbps," and "192.168.2.1," the AI ​​engine generates a "management table entry" and a "diagram node" for the update. The server uses the generated data to update the management table and adds an entry for the new site. The server then updates the network diagram based on the generated data, adding the new site as a node and visually showing its connection relationships with other network elements.

[0275] The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice while they are entering information. This emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback. For example, if the emotion engine determines that the user is feeling stressed while entering information, the server will display input assistance and operation guides to the user. Also, if the server determines that the user is satisfied after adding a new network location, it will highlight that result and provide positive feedback.

[0276] A specific example is when a user enters information such as "Center B," "Fiber 1Gbps," and "192.168.3.1." In this case, the server receives the information and validates it, and the AI ​​engine begins analysis. The AI ​​engine adds a location called "Center B" to the management table and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it determines that the user is confused, it provides assistance with the input. Finally, the server outputs the updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[0277] The hardware used includes the management terminals, cameras, microphones, and server computers in the logistics center. The software used includes OpenCV (face recognition), EmotionRecognition (emotion recognition), NetworkValidation (data validation), UpdateNetworkConfig (updating the network configuration diagram), and the AI ​​engine that controls them. Specific examples of prompt statements are as follows:

[0278] Input information:

[0279] Branch Name: "Center A"

[0280] Line speed: "Fiber 500Mbps"

[0281] IP Address: 192.168.2.1

[0282] Expected output:

[0283] If the user feels stressed:

[0284] "The user is stressed. We will provide input assistance."

[0285] If the input passes validation:

[0286] "Network information validation was successful. The network diagram has been updated."

[0287] If the user is satisfied:

[0288] "Users are happy. They provide positive feedback."

[0289] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0290] Step 1:

[0291] The user enters the information for a new network location (e.g., "Center A," "Fiber 500Mbps," "192.168.2.1") into the terminal. This information is entered into a form in text format. The entered information is stored in the terminal.

[0292] Step 2:

[0293] The terminal sends the entered network location information to the server. The data sent is text data including the location name, line details, and IP address. By receiving the data sent from the terminal, the server is ready to start analyzing the data.

[0294] Step 3:

[0295] The server validates the received network location information. In this step, data validation is performed, including format confirmation and range checks for each value. If the correct format and complete data are confirmed, the server proceeds to the next step. Input: Received network location information, Output: Validation result (success / failure).

[0296] Step 4:

[0297] The server passes information that has passed validation to the AI ​​engine. The AI ​​engine analyzes the input information and generates the data necessary to update the management table entry and network diagram. For example, from the information "Center A," "Fiber 500Mbps," and "192.168.2.1," a "management table entry" and "diagram node" are generated. Input: Information that has passed validation. Output: Management table entry, diagram node.

[0298] Step 5:

[0299] The server uses the created management table entry to update the management table database, which contains information about all network nodes. It adds information about new nodes and keeps the overall network configuration information up to date. Input: Management table entry, Output: Updated management table.

[0300] Step 6:

[0301] The server updates the network diagram using the generated diagram nodes. New locations are added to the diagram, and the connections with other network elements are visually displayed. This allows the visual status of the entire network to be understood at a glance. Input: Diagram nodes, Output: Updated network diagram.

[0302] Step 7:

[0303] The server sends the updated management table and network configuration diagram to the user's device. The user can check the latest network information on the device. Input: Updated management table and network configuration diagram. Output: Latest information displayed on the user's device.

[0304] Step 8:

[0305] While the user is inputting information, the emotion engine is activated using the device's built-in camera and microphone. The emotion engine analyzes the user's facial expressions and voice to determine their emotional state in real time. For example, if the device determines that the user is feeling stressed, it will provide input assistance. Input: User's facial expressions and voice. Output: Determining emotional state and providing appropriate feedback.

[0306] Step 9:

[0307] The server provides appropriate feedback to the user based on the judgment made by the emotion engine. For example, if the server determines that the user is confused during input work, it will display operation guides to support the user. Also, if the server determines that the user is satisfied, it will provide positive feedback to improve the user's operation experience. Input: Result of the emotion engine, Output: Appropriate feedback.

[0308] This allows efficient and accurate management of network locations at the logistics center, and provides appropriate feedback according to the user's emotional state.

[0309] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0310] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0311] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0312] [Second embodiment]

[0313] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0314] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0315] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0316] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0317] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0318] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0319] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0320] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0321] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0322] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0323] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0324] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0325] The system for implementing this invention aims to easily and accurately manage information about new network locations added by users, and automatically update management tables and network configuration diagrams. This system transmits information entered by users from their terminals to a server, which analyzes it using an AI engine, thereby achieving automatic generation and updating of data.

[0326] First, the user enters additional information about the network site (site name, line details, router IP address, etc.) into the terminal. For example, the user enters information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" into the form. The terminal then sends this information to the server.

[0327] The server validates the received information to ensure it is in the correct format and is complete. If all validations are met, the server passes the data to the AI ​​engine and begins analysis. The AI ​​engine generates the data necessary to update the management table and network diagram. For example, if the AI ​​engine receives the information "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it will generate a "management table entry" and a "diagram node" for the update.

[0328] The server then uses the generated data to update the management table, which is a database that records and manages information about all nodes in the network, and adds an entry for the new node. This entry includes the node name, line details, IP address, and so on. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0329] Finally, the server outputs and displays the updated management table and network configuration diagram on the user's terminal, allowing the user to immediately check the information about the newly added base.

[0330] For example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives and validates this information. Next, the AI ​​engine analyzes the information and adds the "Tokyo Office" location to the management table and adds it as a new node to the network configuration diagram. The server then outputs this updated information to the user's device, where the user can view it.

[0331] In this way, the system provides accurate and efficient network management with minimal user intervention.

[0332] The processing flow will be explained below.

[0333] Step 1:

[0334] The user enters information about a new network site into the terminal. Specifically, the user enters information such as the site name, line details, and router IP address into the input form. For example, the user enters information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1."

[0335] Step 2:

[0336] The device sends the input information to the server as an HTTP request in JSON format.

[0337] Step 3:

[0338] The server receives the HTTP request and analyzes the data sent. Specifically, it parses the request body in JSON format and obtains each key and value.

[0339] Step 4:

[0340] The server validates the data it receives, checking that it is formatted correctly and that all required fields are filled in. If the data is invalid, it returns an error.

[0341] Step 5:

[0342] The server passes the data that has passed validation to the AI ​​engine, which then begins analysis. Specifically, the AI ​​engine generates the data necessary to update the management table and network configuration diagram based on the site name, line details, and router IP address.

[0343] Step 6:

[0344] The server updates the management table using the data returned from the AI ​​engine, specifically by inserting new records into the management table database or updating existing records.

[0345] Step 7:

[0346] The server also uses the generated data to update the network diagram, specifically adding new nodes to the network diagram database and setting connection information.

[0347] Step 8:

[0348] The server saves the updated management tables and network diagrams, writes them to the necessary data stores, and also performs checks to ensure data consistency and integrity.

[0349] Step 9:

[0350] The server generates a response indicating that the update is complete and sends it to the terminal, which includes the updated management table and details of the network topology diagram.

[0351] Step 10:

[0352] The terminal receives the response from the server and displays the updated results to the user. Specifically, it visually displays the updated management table and network configuration diagram, allowing the user to check the new location information.

[0353] Example 1

[0354] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0355] With existing network management systems, it is time-consuming to manually update management tables and network diagrams with additional information about network locations, which can lead to inaccuracies. Therefore, there is a need for a method to easily and accurately manage network location information and automatically update management tables and network diagrams.

[0356] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0357] In this invention, the server includes means for validating the additional information for the network site and confirming that it is in the correct format and complete, means for analyzing the received additional information and passing the data to an AI engine to generate data necessary for updating the management table and network configuration diagram, and means for updating the management table using the generated data. This makes it possible to automatically update the management table and network configuration diagram accurately and efficiently based on the network site information entered by the user.

[0358] "Network location" means a physical or logical location connected to a network, including the equipment and infrastructure for data transfer and communications.

[0359] "Additional information" refers to detailed data about a network site, including the site name, line details, router IP address, etc.

[0360] "User" means an individual or organization that uses the system to enter, manage, and review information about a network location.

[0361] "Terminal" refers to a device used by a user, such as a computer, tablet, or smartphone, and is a device for inputting and displaying information.

[0362] "Server" refers to a centralized computer system that provides services over a network, processes data received from users, and updates management tables and network diagrams.

[0363] "Validation" refers to the process of verifying data to ensure it is accurate and complete, including format and content checks.

[0364] "Analysis" refers to the process of using an AI engine to generate the necessary information based on the received data.

[0365] An "AI engine" refers to a system that uses artificial intelligence technology to analyze data and automatically generate management table entries and network configuration diagram nodes.

[0366] "Management table" refers to a database that records and manages information on all locations within a network.

[0367] A "network configuration diagram" refers to a diagram that visually shows each location within a network and their connection relationships.

[0368] "Generated data" refers to the management table entries and network diagram nodes that are analyzed and generated by the AI ​​engine.

[0369] This invention is a system that allows users to easily and accurately manage information about newly added network locations and automatically update management tables and network configuration diagrams. This system sends information entered by users to a terminal to a server, analyzes it using an AI engine, and automatically generates and updates data.

[0370] Hardware and software used

[0371] The system includes the following hardware and software:

[0372] Device: A computer, tablet, smartphone, etc. that a user operates.

[0373] Server: A centralized computer system.

[0374] AI Engine: An artificial intelligence system that performs data analysis and automatic generation.

[0375] Database: A database system for storing management tables.

[0376] Internet connection: Allows data communication between the device and the server.

[0377] Specific operation of the system

[0378] The user accesses the terminal and enters additional information about the network site (e.g., "site name," "line details," "router IP address," etc.). For example, the user enters "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1." The terminal then sends this information to the server.

[0379] The server validates the received information, checking whether the location name, line details, and router IP address are entered in a valid format. If validation is successful, the server passes the data to the AI ​​engine to begin analysis.

[0380] The AI ​​engine generates the data necessary to update the management table and network diagram. For example, it analyzes information on "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" to generate a "management table entry" and a "diagram node."

[0381] The server uses the generated data to update the management table, which records and manages information about all nodes in the network, and adds entries for new nodes. This includes the node name, line details, IP address, etc.

[0382] The server also updates the network diagram based on the generated data, adding new locations as nodes and visually showing their connections with other network elements.

[0383] Finally, the server outputs the updated management table and network configuration diagram to the terminal, allowing the user to immediately check them.

[0384] Specific examples

[0385] For example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," validation occurs when the server receives this information. The AI ​​engine then generates a "management table entry" and a "configuration diagram node" and returns them to the server. The server then updates the management table and network configuration diagram using the updated data and outputs this information to the user's device. The user can immediately view the new information.

[0386] Prompt Sentence Examples

[0387] An example of a prompt to be input to the generative AI model is as follows:

[0388] Input information: {

[0389] "Office Name": "Tokyo Office",

[0390] "Line details": "Fiber 1Gbps",

[0391] "Router IP Address": "192.168.3.1"

[0392] }

[0393] Use this information to generate and update management table entries and network diagram nodes.

[0394] In this way, the system provides accurate and efficient network management with minimal user intervention.

[0395] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0396] Step 1:

[0397] The user accesses the terminal and enters additional information about the network site. Specifically, the user enters the "site name," "line details," and "router IP address" into the input form. For example, the user might enter "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," and click the "Submit" button. The entered information is then imported into the terminal's system.

[0398] Step 2:

[0399] The device sends the additional information received from the user to the server. Specifically, the device sends the information entered in the form to the server as an HTTP POST request. This request contains data in JSON format. The sent information reaches the specified endpoint on the server.

[0400] Step 3:

[0401] The server validates the additional information it has received. Specifically, the server checks whether the site name, line details, and router IP address have been entered in the correct format. At this stage, it checks the format of the entered information (for example, whether the IP address format is correct) and whether all required fields have been filled in. If invalid data is found, it generates an error message and returns it to the terminal as an HTTP response. If validation is successful, it proceeds to the next step.

[0402] Step 4:

[0403] The server sends the information that has passed validation to the AI ​​engine. Specifically, the server sends the data to the AI ​​engine's API endpoint. At this time, the data to be sent uses the following prompt:

[0404] Input information: {

[0405] "Location Name": "Osaka Branch",

[0406] "Line details": "Fiber 500Mbps",

[0407] "Router IP Address": "192.168.2.1"

[0408] }

[0409] Use this information to generate and update management table entries and network diagram nodes.

[0410] Based on this prompt, the AI ​​engine begins analysis.

[0411] Step 5:

[0412] The AI ​​engine returns the analysis results to the server. Specifically, the AI ​​engine analyzes the input information and generates "management table entries" and "configuration diagram nodes." This data includes information such as the location name, line details, and IP address. The server receives this generated data.

[0413] Step 6:

[0414] The server updates the management table using the data received from the AI ​​engine. Specifically, the server adds a new entry to the database that stores the management table. This entry includes the branch name, line details, IP address, etc. For example, "Osaka Branch, Fiber 500Mbps, 192.168.2.1" is added as a new entry.

[0415] Step 7:

[0416] The server updates the network diagram using the generated data. Specifically, the server adds the new node to the network diagram database and updates the connections with other network elements. The new location is visually added to the updated diagram.

[0417] Step 8:

[0418] The server outputs the updated management table and network configuration diagram to the user's terminal. Specifically, the server returns the updated data to the terminal as an HTTP response. The terminal displays the received data on the screen, allowing the user to immediately check the new information. For example, "Osaka Branch, Fiber 500Mbps, 192.168.2.1" is added to the management table, and a new node is displayed on the network configuration diagram.

[0419] (Application example 1)

[0420] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0421] With conventional network site management systems, information about newly added sites must be manually updated in management tables and network configuration diagrams, which reduces efficiency when handling large amounts of data. Furthermore, when new equipment within a factory is added to the network, it is difficult to manage that information in real time, which can lead to incorrect information being updated. Furthermore, there is a lack of a way to visually check the network configuration, making it difficult for administrators to easily grasp the status of their equipment.

[0422] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0423] In this invention, the server includes means for receiving additional information about network locations from a user, means for transmitting the received additional information to the server, means for analyzing the received additional information and generating data necessary for updating the management table and the network configuration diagram, means for updating the management table using the generated data, means for updating the network configuration diagram using the generated data, means for outputting the updated management table and network configuration diagram to the user, means for collecting information about newly added equipment in the factory and automatically updating the management table and the network configuration diagram, and means for visually displaying the updated management table and the network configuration diagram. This provides an environment in which additional information about network locations in the factory can be automatically managed and visually confirmed, preventing errors and enabling efficient management.

[0424] A "network location" refers to a specific location or place where various digital devices and machines are connected.

[0425] "Means for receiving additional information" refers to the mechanism for collecting new data entered by the user.

[0426] "Means for sending to server" refers to the process of transferring collected data to the server.

[0427] "Means for analyzing and generating data necessary for updating the management table and configuration diagram" refers to a mechanism for analyzing input data and generating information necessary for updating the network management table and configuration diagram.

[0428] "Means for updating the management table" refers to a method for updating an existing management table to the latest version based on newly generated data.

[0429] "Means for updating a network configuration diagram" refers to a method for updating an existing network configuration diagram to the latest version based on newly generated data.

[0430] "Means of outputting to the user" refers to the mechanism for displaying and outputting the updated management table and network configuration diagram on the user's terminal.

[0431] "Means for collecting information on factory equipment and automatically updating management tables and configuration diagrams" refers to a system that automatically collects information on new machines or robots in the factory when they are connected to the network, and updates the management tables and configuration diagrams.

[0432] "Means for visual display" refers to a method for providing the user with an updated network configuration diagram or management table in a form that allows the user to visually confirm the updated network configuration diagram or management table.

[0433] The present invention is a system that automatically manages additional information for network locations within a factory and allows a manager to visually check it. A specific embodiment for realizing this system will be described below.

[0434] Program Generation

[0435] The system is built using the Python language. The main libraries used are the standard library for data validation, NetworkX and Matplotlib for generating and visualizing network configurations, and the AI ​​engine is designed to use generative AI models.

[0436] Natural language explanation of the process

[0437] The system works as follows:

[0438] 1. Collection and transmission of additional information about network locations

[0439] Using an application on a smartphone or tablet, users enter information (site name, line details, IP address) about the newly added factory equipment (robots and machines) into a form. This information is then sent from the device to the server.

[0440] 2. Data validation and analysis on the server

[0441] The server validates the received additional information to ensure that the format and content are correct. It then uses an AI engine to analyze the data and generate the data needed to update the management table and network diagram. This process utilizes a generative AI model to efficiently generate the data.

[0442] 3. Update management tables and network diagrams

[0443] Based on the generated data, the server updates the existing management table to the latest version. It also updates the network configuration diagram to visually reflect the new location and equipment information. This makes it possible to understand the network configuration within the factory at a glance.

[0444] 4. User Output and Visualization

[0445] The updated management table and network configuration diagram are output to the user's terminal in real time and displayed visually, allowing factory managers to immediately check information on newly added equipment.

[0446] Adding specific examples

[0447] For example, if a user enters the information "Maintenance Robot," "WiFi 600Mbps," and "192.168.0.40," the server receives and validates this information. The AI ​​engine then analyzes the information and adds a location called "Maintenance Robot" to the management table and adds it as a new node to the network configuration diagram. This allows factory managers to check the latest network status via smartphones or tablets.

[0448] Prompt Sentence Examples

[0449] Enter the information for your new factory robot. Include the site name, line details, and IP address. For example, "Site name: Maintenance Robot, Line details: WiFi 600Mbps, IP address: 192.168.0.40".

[0450] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0451] Step 1:

[0452] Collecting and sending additional information about your network locations

[0453] The user uses a smartphone or tablet application to input information about the newly added factory equipment (robots and machines). This information includes the base name, line details, and IP address. The input information is sent from the terminal to the server. As a specific example, the inputs are "Base name: Maintenance Robot," "Line details: WiFi 600Mbps," and "IP address: 192.168.0.40." The input for this step is the equipment information entered by the user, and the output is the data sent to the server.

[0454] Step 2:

[0455] Data Validation

[0456] The server validates the additional information it receives, specifically checking that the site name is entered correctly, that the line details are correct, and that the IP address is entered in the correct format. The data validation process ensures that the information entered is complete and accurate. If the data is successfully validated, it moves on to the next step. The input for validation is the data sent to the server, and the output is the validated data.

[0457] Step 3:

[0458] Data analysis

[0459] The server passes the data that has passed validation to the AI ​​engine. The AI ​​engine analyzes this data and generates new data needed to update the management table and network diagram. For example, it analyzes the location information for the "Maintenance Robot" and uses that data to generate a new entry in the management table and add a new node to the network diagram. The input to this step is validated data, and the output is the generated data.

[0460] Step 4:

[0461] Update management table

[0462] The server updates the management table using the data generated by the AI ​​engine. The management table is a database that records information about all network locations. New entries are added and existing information is kept up to date. For example, information about a "Maintenance Robot" is added as a new entry. The input to this step is the generated data, and the output is the updated management table.

[0463] Step 5:

[0464] Update the network diagram

[0465] The server updates the network diagram using the data generated by the AI ​​engine. New locations are added as nodes to the diagram, and their connections with other network elements are visually displayed. For example, a "Maintenance Robot" is added as a new node to the diagram, along with its line details and IP address. The input to this step is the generated data, and the output is an updated network diagram.

[0466] Step 6:

[0467] User Output and Visualization

[0468] The server outputs the updated management table and network configuration diagram to the user's device. This information is displayed visually, allowing the factory manager to easily check the new location information. Specifically, the user can view the updated network configuration diagram in real time on a smartphone or tablet. The input for this step is the updated management table and network configuration diagram, and the output is the visual information displayed on the user's device.

[0469] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0470] The system for implementing the present invention aims to efficiently and accurately manage information on newly added network nodes by users and automatically update the management table and network configuration diagram. Furthermore, the system includes an emotion engine for recognizing user emotions and improving the operating experience.

[0471] First, the user enters information about the new network site (site name, line details, router IP address, etc.) into the terminal. For example, information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" is entered into the form. The terminal then sends this information to the server.

[0472] The server validates the received information to ensure it is in the correct format and is complete. If all validations are passed, the server passes the data to the AI ​​engine and begins analysis. The AI ​​engine generates the data necessary to update the management table and network configuration diagram. For example, if the AI ​​engine receives the information "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it will generate a "management table entry" and a "configuration diagram node" for the update.

[0473] The server then uses the generated data to update the management table, which is a database that records and manages information about all nodes in the network, and adds an entry for the new node. This entry includes the node name, line details, IP address, and so on. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0474] Furthermore, this system incorporates an emotion engine to recognize the user's emotions. While the user is inputting information, the emotion engine analyzes the user's facial expressions and voice using a camera and microphone. The emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback.

[0475] For example, if the emotion engine determines that the user is feeling stressed while inputting information, the server can display input assistance and operation guides to the user. Also, if the server determines that the user is satisfied after adding a new location, it can highlight that result and provide positive feedback.

[0476] As a specific example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives this information and validates it. Next, the AI ​​engine analyzes it, adds the location "Tokyo Office" to the management table, and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it recognizes that the user is confused, it provides assistance with the input. Finally, the server outputs this updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[0477] In this way, the system provides accurate and efficient network management while minimizing user interaction, and also provides appropriate feedback according to the user's emotional state.

[0478] The processing flow will be explained below.

[0479] Step 1:

[0480] The user enters information about the new network location into the terminal. Specifically, the user enters information such as the location name "Osaka Branch," line details "Fiber 500Mbps," and router IP address "192.168.2.1" into the input form.

[0481] Step 2:

[0482] The terminal sends the input information to the server. Specifically, the data is sent as an HTTP request in JSON format.

[0483] Step 3:

[0484] The server analyzes the received HTTP request and parses the transmitted data. Specifically, it parses the request body in JSON format and obtains each key and value.

[0485] Step 4:

[0486] The server validates the data it receives, ensuring that it is formatted correctly and that all required fields are filled in. If the data is invalid, it generates an error message and sends it back to the terminal.

[0487] Step 5:

[0488] The server passes the data that has passed validation to the AI ​​engine, which then begins analysis. Specifically, the AI ​​engine generates the data necessary to update the management table and network configuration diagram based on the site name, line details, and router IP address.

[0489] Step 6:

[0490] The server updates the management table using the data returned from the AI ​​engine. Specifically, it inserts a new record into the management table database, adding the branch name "Osaka Branch," line details "Fiber 500Mbps," and router IP address "192.168.2.1."

[0491] Step 7:

[0492] The server updates the network diagram using the generated data. Specifically, it adds a new node, "Osaka Branch," to the network diagram database and sets its IP address, "192.168.2.1," and its connection information.

[0493] Step 8:

[0494] The server saves the updated management table and network diagram and writes it to the data store, performing additional checks to ensure data consistency and integrity.

[0495] Step 9:

[0496] The server uses an emotion engine to analyze the user's emotional state. Specifically, it analyzes the user's facial expressions and voice in real time through a camera and microphone to determine the user's emotional state (stress, frustration, joy, etc.).

[0497] Step 10:

[0498] The server generates appropriate feedback based on the user's emotional state. For example, if it determines that the user is feeling stressed, it displays input assistance and operation guides on the device. Conversely, if the user is satisfied, it displays positive feedback that emphasizes the user's satisfaction.

[0499] Step 11:

[0500] The server generates a response indicating that the update is complete and sends it to the terminal. The response includes details of the updated management table and network topology diagram, as well as a feedback message.

[0501] Step 12:

[0502] The terminal receives the response from the server and displays the updated results to the user. Specifically, it visually displays the updated management table and network configuration diagram, and displays feedback messages so that the user can check the results of the system's operation.

[0503] Example 2

[0504] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0505] Modern network management requires efficient and accurate management of additional information for new locations and smooth updates to management tables and network diagrams. It is also important to provide a good user experience by reducing the stress and confusion associated with data entry tasks. However, with conventional systems, it was difficult to perform these tasks efficiently and consistently.

[0506] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for receiving additional information about network nodes from a user; means for transmitting the received additional information to the server; means for validating the received additional information; means for analyzing the additional information using an AI engine and generating data necessary for updating the management table and the communication configuration diagram; means for updating the management table using the generated data; means for updating the communication configuration diagram using the generated data; means for outputting the updated management table and the communication configuration diagram to the user; and means for providing feedback according to the user's emotional state, which includes an emotion engine for analyzing the user's emotions. This improves the accuracy and efficiency of network management and improves the user's operation experience.

[0507] "Network location" is a term that refers to a specific physical or logical location or device within a computer network.

[0508] "Additional information" refers to new or changed data a user has about a network location.

[0509] "User" refers to a person who operates or uses this system.

[0510] A "server" is a computer connected to a network, and is a device that processes and manages data.

[0511] "Validation" is the process of checking whether entered data is of the correct format and content.

[0512] An "AI engine" is software or hardware that uses artificial intelligence technology to analyze and generate data.

[0513] A "management table" is a database or data structure for recording and managing information about network locations.

[0514] A "communication configuration diagram" is a diagram that visually shows each element in a network and its connection relationships.

[0515] The "emotion engine" is a system that analyzes the user's emotional state using input from a camera, microphone, etc., and provides appropriate feedback.

[0516] "Feedback" means the response or assistance information provided by the system to the user.

[0517] "Data generation" is the process of creating new data or required data structures based on received information.

[0518] The system for implementing the present invention comprises the following elements: It efficiently and accurately manages information about new network nodes added by users, automatically updates the management table and network configuration diagram, and includes an emotion engine for recognizing user emotions and improving the operating experience.

[0519] First, the user enters information about the new network site (site name, line details, IP address, etc.) on a device (PC, tablet, etc.). For example, information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" is entered into a form. The device sends this information to the server using a secure communication method (e.g., HTTPS).

[0520] The server validates the received information. Validation checks the accuracy of the branch name, the format of the IP address, the validity of the line details, etc. For example, it checks whether "Osaka Branch" is a valid string, and whether "192.168.2.1" is the correct IP address format. If all validations are passed, the server passes the data to the AI ​​engine to begin analysis.

[0521] The AI ​​engine uses the generative AI model to generate the data necessary to update the management table and network diagram. For example, when it receives "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it generates a management table entry and a diagram node. This allows the new branch information to be reflected in the management table and network diagram.

[0522] The server then uses the generated data to update the management table, which is a database that records information about all nodes in the network. The entry for the new node includes information such as the node name, line details, and IP address. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0523] Furthermore, this system incorporates an emotion engine to recognize the user's emotions. While the user is entering information, the emotion engine uses a camera and microphone to analyze the user's facial expressions and voice. The emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback. For example, if the emotion engine determines that the user is feeling stressed while entering information, the server will display input assistance and operation guides to the user. Also, if the server recognizes that the user is satisfied after adding a new location, it will highlight this result and provide positive feedback.

[0524] As a specific example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives this information and validates it. Next, the AI ​​engine analyzes it, adds the location "Tokyo Office" to the management table, and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it recognizes that the user is confused, it provides assistance with the input. Finally, the server outputs this updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[0525] Example prompt sentence:

[0526] "Please explain a system that, after a user inputs new network location information, validates the data, updates the management table and network diagram, and analyzes the user's sentiment in the process to provide appropriate feedback."

[0527] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0528] Step 1:

[0529] The user enters information about a new network site on the terminal. The information entered includes the site name, line details, IP address, etc. For example, "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1" are entered. This information is entered on a form and registered by pressing the Enter key or the submit button. The input data is collected as fields in the input form and converted to JSON format. The input data is sent to the next step.

[0530] Step 2:

[0531] The terminal sends the input information to the server. The terminal packages the input data in JSON format and sends it to the server using a secure communication protocol (e.g., HTTPS). The data is encrypted during transmission. The server receives the transmitted data and stores it in a database. The input data ("Tokyo Office", "Fiber 1Gbps", "192.168.3.1") is sent to the server, triggering a signal to start validation.

[0532] Step 3:

[0533] The server validates the information it receives. The server checks the data format, content integrity, and the accuracy of IP addresses. The validation process uses a validation script to ensure the data is in the correct format and that required fields are filled in. For example, it verifies that "Tokyo Office" is a valid location name field and that "192.168.3.1" is a valid IP address format. If validation is successful, the validated data is passed to the next analysis step.

[0534] Step 4:

[0535] The server sends the data to the AI ​​engine and instructs it to start analysis. The AI ​​engine uses the generative AI model to analyze the additional information it receives. The server sends the validated data to the AI ​​engine and begins analysis to generate a new dataset. For example, based on the input "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the AI ​​engine generates the necessary data, such as management table entries and configuration diagram nodes. The generated data is sent back from the AI ​​engine to the server.

[0536] Step 5:

[0537] The server updates the management table using the generated data. The server receives the data returned from the AI ​​engine and uses that data to update the management table database. For example, new location information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1" is added to the management table. The updated management table results are passed to the next configuration diagram update step.

[0538] Step 6:

[0539] The server updates the communication configuration diagram using the generated data. The server updates the network configuration diagram based on the generated data. New location information is visually added, and the connection relationships with existing network elements are shown. For example, a new node called "Tokyo Office" is added to the configuration diagram, and its connection relationships are visualized. The updated configuration diagram data is passed to the next output step.

[0540] Step 7:

[0541] The emotion engine analyzes the user's emotions. It analyzes the user's facial expressions and voice as they are inputting, and identifies their emotional state in real time. The emotion engine captures and analyzes data from the camera and microphone in real time. For example, if the user is feeling stressed, it recognizes this state and notifies the server. The notified emotional data is passed on to the next feedback step.

[0542] Step 8:

[0543] The server then feeds the results back to the user. The server provides feedback to the user based on the results of updating the management table and communication configuration diagram, and the analysis results of the emotion engine. For example, if the user is satisfied, this fact is highlighted and positive feedback is provided. If the user is feeling stressed, operation guides and input assistance are displayed. The feedback content is output to the terminal, allowing the user to visually confirm it.

[0544] (Application example 2)

[0545] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0546] In current logistics centers, efficient and accurate management of information about newly added network locations is an important issue. Furthermore, a lack of appropriate feedback based on the worker's emotions and status can lead to problems such as reduced operational efficiency and satisfaction. The present invention aims to solve these problems and improve the efficiency of network management in logistics centers and worker satisfaction.

[0547] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving additional information about network locations from a user, means for transmitting the received additional information to the server, means for analyzing the received additional information and generating data necessary for updating the management table and the network configuration diagram, means for updating the management table using the generated data, means for updating the network configuration diagram using the generated data, means for outputting the updated management table and the network configuration diagram to the user, and means including an emotion engine for recognizing the user's emotions and improving the operating experience. This not only enables efficient and accurate network management in a logistics center, but also provides feedback according to the emotions of workers, thereby improving operating efficiency and satisfaction.

[0548] A "network location" is a location or facility that is newly added to the network configuration.

[0549] "Additional information" is detailed information about the network location (e.g., location name, line speed, IP address).

[0550] A "user" is a person or entity that operates the system and inputs additional information for a network location.

[0551] The "server" is the central component of the system that receives and analyzes additional information sent by users and updates the management table and network configuration diagram.

[0552] The "management table" is a database for recording and managing information on all locations within the network.

[0553] A "network configuration diagram" is a diagram that visually shows the locations within a network and their connection relationships.

[0554] An "emotion engine" is an element of the system that uses a camera, microphone, etc. to analyze a user's facial expressions and voice and identify their emotional state.

[0555] "Validation" is the process of ensuring that any additional information received is accurate and complete.

[0556] An "AI engine" is an element of the system that uses artificial intelligence to analyze additional information and generate the data necessary to update management tables and network diagrams.

[0557] "Feedback" refers to the support and positive reactions provided by a system in response to a user's actions and emotions.

[0558] The system for implementing the present invention aims to efficiently and accurately manage and update additional information for network locations in a logistics center, and also includes an emotion engine for recognizing user emotions and improving the operating experience.

[0559] Specifically, a user enters information about a new network location into a management terminal at a logistics center. This information includes the location name, line details, IP address, etc. For example, information such as "Center A," "Fiber 500Mbps," and "192.168.2.1" might be used. Once the user has finished entering this information, the terminal sends it to the server. The server validates the received information to ensure it is in the correct format and complete. If all validations are met, the server passes the data to the AI ​​engine and begins analysis.

[0560] The AI ​​engine generates the data necessary to update the management table and network diagram. For example, after receiving information such as "Center A," "Fiber 500Mbps," and "192.168.2.1," the AI ​​engine generates a "management table entry" and a "diagram node" for the update. The server uses the generated data to update the management table and adds an entry for the new site. The server then updates the network diagram based on the generated data, adding the new site as a node and visually showing its connection relationships with other network elements.

[0561] The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice while they are entering information. This emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback. For example, if the emotion engine determines that the user is feeling stressed while entering information, the server will display input assistance and operation guides to the user. Also, if the server determines that the user is satisfied after adding a new network location, it will highlight that result and provide positive feedback.

[0562] A specific example is when a user enters information such as "Center B," "Fiber 1Gbps," and "192.168.3.1." In this case, the server receives the information and validates it, and the AI ​​engine begins analysis. The AI ​​engine adds a location called "Center B" to the management table and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it determines that the user is confused, it provides assistance with the input. Finally, the server outputs the updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[0563] The hardware used includes the management terminals, cameras, microphones, and server computers in the logistics center. The software used includes OpenCV (face recognition), EmotionRecognition (emotion recognition), NetworkValidation (data validation), UpdateNetworkConfig (updating the network configuration diagram), and the AI ​​engine that controls them. Specific examples of prompt statements are as follows:

[0564] Input information:

[0565] Branch Name: "Center A"

[0566] Line speed: "Fiber 500Mbps"

[0567] IP Address: 192.168.2.1

[0568] Expected output:

[0569] If the user feels stressed:

[0570] "The user is stressed. We will provide input assistance."

[0571] If the input passes validation:

[0572] "Network information validation was successful. The network diagram has been updated."

[0573] If the user is satisfied:

[0574] "Users are happy. They provide positive feedback."

[0575] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0576] Step 1:

[0577] The user enters the information for a new network location (e.g., "Center A," "Fiber 500Mbps," "192.168.2.1") into the terminal. This information is entered into a form in text format. The entered information is stored in the terminal.

[0578] Step 2:

[0579] The terminal sends the entered network location information to the server. The data sent is text data including the location name, line details, and IP address. By receiving the data sent from the terminal, the server is ready to start analyzing the data.

[0580] Step 3:

[0581] The server validates the received network location information. In this step, data validation is performed, including format confirmation and range checks for each value. If the correct format and complete data are confirmed, the server proceeds to the next step. Input: Received network location information, Output: Validation result (success / failure).

[0582] Step 4:

[0583] The server passes information that has passed validation to the AI ​​engine. The AI ​​engine analyzes the input information and generates the data necessary to update the management table entry and network diagram. For example, from the information "Center A," "Fiber 500Mbps," and "192.168.2.1," a "management table entry" and "diagram node" are generated. Input: Information that has passed validation. Output: Management table entry, diagram node.

[0584] Step 5:

[0585] The server uses the created management table entry to update the management table database, which contains information about all network nodes. It adds information about new nodes and keeps the overall network configuration information up to date. Input: Management table entry, Output: Updated management table.

[0586] Step 6:

[0587] The server updates the network diagram using the generated diagram nodes. New locations are added to the diagram, and the connections with other network elements are visually displayed. This allows the visual status of the entire network to be understood at a glance. Input: Diagram nodes, Output: Updated network diagram.

[0588] Step 7:

[0589] The server sends the updated management table and network configuration diagram to the user's device. The user can check the latest network information on the device. Input: Updated management table and network configuration diagram. Output: Latest information displayed on the user's device.

[0590] Step 8:

[0591] While the user is inputting information, the emotion engine is activated using the device's built-in camera and microphone. The emotion engine analyzes the user's facial expressions and voice to determine their emotional state in real time. For example, if the device determines that the user is feeling stressed, it will provide input assistance. Input: User's facial expressions and voice. Output: Determining emotional state and providing appropriate feedback.

[0592] Step 9:

[0593] The server provides appropriate feedback to the user based on the judgment made by the emotion engine. For example, if the server determines that the user is confused during input work, it will display operation guides to support the user. Also, if the server determines that the user is satisfied, it will provide positive feedback to improve the user's operation experience. Input: Result of the emotion engine, Output: Appropriate feedback.

[0594] This allows efficient and accurate management of network locations at the logistics center, and provides appropriate feedback according to the user's emotional state.

[0595] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0596] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0597] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0598] [Third embodiment]

[0599] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0600] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0601] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0602] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0603] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0604] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0605] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0606] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0607] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0608] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0609] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0610] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0611] The system for implementing this invention aims to easily and accurately manage information about new network locations added by users, and automatically update management tables and network configuration diagrams. This system transmits information entered by users from their terminals to a server, which analyzes it using an AI engine, thereby achieving automatic generation and updating of data.

[0612] First, the user enters additional information about the network site (site name, line details, router IP address, etc.) into the terminal. For example, the user enters information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" into the form. The terminal then sends this information to the server.

[0613] The server validates the received information to ensure it is in the correct format and is complete. If all validations are met, the server passes the data to the AI ​​engine and begins analysis. The AI ​​engine generates the data necessary to update the management table and network diagram. For example, if the AI ​​engine receives the information "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it will generate a "management table entry" and a "diagram node" for the update.

[0614] The server then uses the generated data to update the management table, which is a database that records and manages information about all nodes in the network, and adds an entry for the new node. This entry includes the node name, line details, IP address, and so on. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0615] Finally, the server outputs and displays the updated management table and network configuration diagram on the user's terminal, allowing the user to immediately check the information about the newly added base.

[0616] For example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives and validates this information. Next, the AI ​​engine analyzes the information and adds the "Tokyo Office" location to the management table and adds it as a new node to the network configuration diagram. The server then outputs this updated information to the user's device, where the user can view it.

[0617] In this way, the system provides accurate and efficient network management with minimal user intervention.

[0618] The processing flow will be explained below.

[0619] Step 1:

[0620] The user enters information about a new network site into the terminal. Specifically, the user enters information such as the site name, line details, and router IP address into the input form. For example, the user enters information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1."

[0621] Step 2:

[0622] The device sends the input information to the server as an HTTP request in JSON format.

[0623] Step 3:

[0624] The server receives the HTTP request and analyzes the data sent. Specifically, it parses the request body in JSON format and obtains each key and value.

[0625] Step 4:

[0626] The server validates the data it receives, checking that it is formatted correctly and that all required fields are filled in. If the data is invalid, it returns an error.

[0627] Step 5:

[0628] The server passes the data that has passed validation to the AI ​​engine, which then begins analysis. Specifically, the AI ​​engine generates the data necessary to update the management table and network configuration diagram based on the site name, line details, and router IP address.

[0629] Step 6:

[0630] The server updates the management table using the data returned from the AI ​​engine, specifically by inserting new records into the management table database or updating existing records.

[0631] Step 7:

[0632] The server also uses the generated data to update the network diagram, specifically adding new nodes to the network diagram database and setting connection information.

[0633] Step 8:

[0634] The server saves the updated management tables and network diagrams, writes them to the necessary data stores, and also performs checks to ensure data consistency and integrity.

[0635] Step 9:

[0636] The server generates a response indicating that the update is complete and sends it to the terminal, which includes the updated management table and details of the network topology diagram.

[0637] Step 10:

[0638] The terminal receives the response from the server and displays the updated results to the user. Specifically, it visually displays the updated management table and network configuration diagram, allowing the user to check the new location information.

[0639] Example 1

[0640] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0641] With existing network management systems, it is time-consuming to manually update management tables and network diagrams with additional information about network locations, which can lead to inaccuracies. Therefore, there is a need for a method to easily and accurately manage network location information and automatically update management tables and network diagrams.

[0642] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0643] In this invention, the server includes means for validating the additional information for the network site and confirming that it is in the correct format and complete, means for analyzing the received additional information and passing the data to an AI engine to generate data necessary for updating the management table and network configuration diagram, and means for updating the management table using the generated data. This makes it possible to automatically update the management table and network configuration diagram accurately and efficiently based on the network site information entered by the user.

[0644] "Network location" means a physical or logical location connected to a network, including the equipment and infrastructure for data transfer and communications.

[0645] "Additional information" refers to detailed data about a network site, including the site name, line details, router IP address, etc.

[0646] "User" means an individual or organization that uses the system to enter, manage, and review information about a network location.

[0647] "Terminal" refers to a device used by a user, such as a computer, tablet, or smartphone, and is a device for inputting and displaying information.

[0648] "Server" refers to a centralized computer system that provides services over a network, processes data received from users, and updates management tables and network diagrams.

[0649] "Validation" refers to the process of verifying data to ensure it is accurate and complete, including format and content checks.

[0650] "Analysis" refers to the process of using an AI engine to generate the necessary information based on the received data.

[0651] An "AI engine" refers to a system that uses artificial intelligence technology to analyze data and automatically generate management table entries and network configuration diagram nodes.

[0652] "Management table" refers to a database that records and manages information on all locations within a network.

[0653] A "network configuration diagram" refers to a diagram that visually shows each location within a network and their connection relationships.

[0654] "Generated data" refers to the management table entries and network diagram nodes that are analyzed and generated by the AI ​​engine.

[0655] This invention is a system that allows users to easily and accurately manage information about newly added network locations and automatically update management tables and network configuration diagrams. This system sends information entered by users to a terminal to a server, analyzes it using an AI engine, and automatically generates and updates data.

[0656] Hardware and software used

[0657] The system includes the following hardware and software:

[0658] Device: A computer, tablet, smartphone, etc. that a user operates.

[0659] Server: A centralized computer system.

[0660] AI Engine: An artificial intelligence system that performs data analysis and automatic generation.

[0661] Database: A database system for storing management tables.

[0662] Internet connection: Allows data communication between the device and the server.

[0663] Specific operation of the system

[0664] The user accesses the terminal and enters additional information about the network site (e.g., "site name," "line details," "router IP address," etc.). For example, the user enters "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1." The terminal then sends this information to the server.

[0665] The server validates the received information, checking whether the location name, line details, and router IP address are entered in a valid format. If validation is successful, the server passes the data to the AI ​​engine to begin analysis.

[0666] The AI ​​engine generates the data necessary to update the management table and network diagram. For example, it analyzes information on "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" to generate a "management table entry" and a "diagram node."

[0667] The server uses the generated data to update the management table, which records and manages information about all nodes in the network, and adds entries for new nodes. This includes the node name, line details, IP address, etc.

[0668] The server also updates the network diagram based on the generated data, adding new locations as nodes and visually showing their connections with other network elements.

[0669] Finally, the server outputs the updated management table and network configuration diagram to the terminal, allowing the user to immediately check them.

[0670] Specific examples

[0671] For example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," validation occurs when the server receives this information. The AI ​​engine then generates a "management table entry" and a "configuration diagram node" and returns them to the server. The server then updates the management table and network configuration diagram using the updated data and outputs this information to the user's device. The user can immediately view the new information.

[0672] Prompt Sentence Examples

[0673] An example of a prompt to be input to the generative AI model is as follows:

[0674] Input information: {

[0675] "Office Name": "Tokyo Office",

[0676] "Line details": "Fiber 1Gbps",

[0677] "Router IP Address": "192.168.3.1"

[0678] }

[0679] Use this information to generate and update management table entries and network diagram nodes.

[0680] In this way, the system provides accurate and efficient network management with minimal user intervention.

[0681] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0682] Step 1:

[0683] The user accesses the terminal and enters additional information about the network site. Specifically, the user enters the "site name," "line details," and "router IP address" into the input form. For example, the user might enter "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," and click the "Submit" button. The entered information is then imported into the terminal's system.

[0684] Step 2:

[0685] The device sends the additional information received from the user to the server. Specifically, the device sends the information entered in the form to the server as an HTTP POST request. This request contains data in JSON format. The sent information reaches the specified endpoint on the server.

[0686] Step 3:

[0687] The server validates the additional information it has received. Specifically, the server checks whether the site name, line details, and router IP address have been entered in the correct format. At this stage, it checks the format of the entered information (for example, whether the IP address format is correct) and whether all required fields have been filled in. If invalid data is found, it generates an error message and returns it to the terminal as an HTTP response. If validation is successful, it proceeds to the next step.

[0688] Step 4:

[0689] The server sends the information that has passed validation to the AI ​​engine. Specifically, the server sends the data to the AI ​​engine's API endpoint. At this time, the data to be sent uses the following prompt:

[0690] Input information: {

[0691] "Location Name": "Osaka Branch",

[0692] "Line details": "Fiber 500Mbps",

[0693] "Router IP Address": "192.168.2.1"

[0694] }

[0695] Use this information to generate and update management table entries and network diagram nodes.

[0696] Based on this prompt, the AI ​​engine begins analysis.

[0697] Step 5:

[0698] The AI ​​engine returns the analysis results to the server. Specifically, the AI ​​engine analyzes the input information and generates "management table entries" and "configuration diagram nodes." This data includes information such as the location name, line details, and IP address. The server receives this generated data.

[0699] Step 6:

[0700] The server updates the management table using the data received from the AI ​​engine. Specifically, the server adds a new entry to the database that stores the management table. This entry includes the branch name, line details, IP address, etc. For example, "Osaka Branch, Fiber 500Mbps, 192.168.2.1" is added as a new entry.

[0701] Step 7:

[0702] The server updates the network diagram using the generated data. Specifically, the server adds the new node to the network diagram database and updates the connections with other network elements. The new location is visually added to the updated diagram.

[0703] Step 8:

[0704] The server outputs the updated management table and network configuration diagram to the user's terminal. Specifically, the server returns the updated data to the terminal as an HTTP response. The terminal displays the received data on the screen, allowing the user to immediately check the new information. For example, "Osaka Branch, Fiber 500Mbps, 192.168.2.1" is added to the management table, and a new node is displayed on the network configuration diagram.

[0705] (Application example 1)

[0706] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0707] With conventional network site management systems, information about newly added sites must be manually updated in management tables and network configuration diagrams, which reduces efficiency when handling large amounts of data. Furthermore, when new equipment within a factory is added to the network, it is difficult to manage that information in real time, which can lead to incorrect information being updated. Furthermore, there is a lack of a way to visually check the network configuration, making it difficult for administrators to easily grasp the status of their equipment.

[0708] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0709] In this invention, the server includes means for receiving additional information about network locations from a user, means for transmitting the received additional information to the server, means for analyzing the received additional information and generating data necessary for updating the management table and the network configuration diagram, means for updating the management table using the generated data, means for updating the network configuration diagram using the generated data, means for outputting the updated management table and network configuration diagram to the user, means for collecting information about newly added equipment in the factory and automatically updating the management table and the network configuration diagram, and means for visually displaying the updated management table and the network configuration diagram. This provides an environment in which additional information about network locations in the factory can be automatically managed and visually confirmed, preventing errors and enabling efficient management.

[0710] A "network location" refers to a specific location or place where various digital devices and machines are connected.

[0711] "Means for receiving additional information" refers to the mechanism for collecting new data entered by the user.

[0712] "Means for sending to server" refers to the process of transferring collected data to the server.

[0713] "Means for analyzing and generating data necessary for updating the management table and configuration diagram" refers to a mechanism for analyzing input data and generating information necessary for updating the network management table and configuration diagram.

[0714] "Means for updating the management table" refers to a method for updating an existing management table to the latest version based on newly generated data.

[0715] "Means for updating a network configuration diagram" refers to a method for updating an existing network configuration diagram to the latest version based on newly generated data.

[0716] "Means of outputting to the user" refers to the mechanism for displaying and outputting the updated management table and network configuration diagram on the user's terminal.

[0717] "Means for collecting information on factory equipment and automatically updating management tables and configuration diagrams" refers to a system that automatically collects information on new machines or robots in the factory when they are connected to the network, and updates the management tables and configuration diagrams.

[0718] "Means for visual display" refers to a method for providing the user with an updated network configuration diagram or management table in a form that allows the user to visually confirm the updated network configuration diagram or management table.

[0719] The present invention is a system that automatically manages additional information for network locations within a factory and allows a manager to visually check it. A specific embodiment for realizing this system will be described below.

[0720] Program Generation

[0721] The system is built using the Python language. The main libraries used are the standard library for data validation, NetworkX and Matplotlib for generating and visualizing network configurations, and the AI ​​engine is designed to use generative AI models.

[0722] Natural language explanation of the process

[0723] The system works as follows:

[0724] 1. Collection and transmission of additional information about network locations

[0725] Using an application on a smartphone or tablet, users enter information (site name, line details, IP address) about the newly added factory equipment (robots and machines) into a form. This information is then sent from the device to the server.

[0726] 2. Data validation and analysis on the server

[0727] The server validates the received additional information to ensure that the format and content are correct. It then uses an AI engine to analyze the data and generate the data needed to update the management table and network diagram. This process utilizes a generative AI model to efficiently generate the data.

[0728] 3. Update management tables and network diagrams

[0729] Based on the generated data, the server updates the existing management table to the latest version. It also updates the network configuration diagram to visually reflect the new location and equipment information. This makes it possible to understand the network configuration within the factory at a glance.

[0730] 4. User Output and Visualization

[0731] The updated management table and network configuration diagram are output to the user's terminal in real time and displayed visually, allowing factory managers to immediately check information on newly added equipment.

[0732] Adding specific examples

[0733] For example, if a user enters the information "Maintenance Robot," "WiFi 600Mbps," and "192.168.0.40," the server receives and validates this information. The AI ​​engine then analyzes the information and adds a location called "Maintenance Robot" to the management table and adds it as a new node to the network configuration diagram. This allows factory managers to check the latest network status via smartphones or tablets.

[0734] Prompt Sentence Examples

[0735] Enter the information for your new factory robot. Include the site name, line details, and IP address. For example, "Site name: Maintenance Robot, Line details: WiFi 600Mbps, IP address: 192.168.0.40".

[0736] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0737] Step 1:

[0738] Collecting and sending additional information about your network locations

[0739] The user uses a smartphone or tablet application to input information about the newly added factory equipment (robots and machines). This information includes the base name, line details, and IP address. The input information is sent from the terminal to the server. As a specific example, the inputs are "Base name: Maintenance Robot," "Line details: WiFi 600Mbps," and "IP address: 192.168.0.40." The input for this step is the equipment information entered by the user, and the output is the data sent to the server.

[0740] Step 2:

[0741] Data Validation

[0742] The server validates the additional information it receives, specifically checking that the site name is entered correctly, that the line details are correct, and that the IP address is entered in the correct format. The data validation process ensures that the information entered is complete and accurate. If the data is successfully validated, it moves on to the next step. The input for validation is the data sent to the server, and the output is the validated data.

[0743] Step 3:

[0744] Data analysis

[0745] The server passes the data that has passed validation to the AI ​​engine. The AI ​​engine analyzes this data and generates new data needed to update the management table and network diagram. For example, it analyzes the location information for the "Maintenance Robot" and uses that data to generate a new entry in the management table and add a new node to the network diagram. The input to this step is validated data, and the output is the generated data.

[0746] Step 4:

[0747] Update management table

[0748] The server updates the management table using the data generated by the AI ​​engine. The management table is a database that records information about all network locations. New entries are added and existing information is kept up to date. For example, information about a "Maintenance Robot" is added as a new entry. The input to this step is the generated data, and the output is the updated management table.

[0749] Step 5:

[0750] Update the network diagram

[0751] The server updates the network diagram using the data generated by the AI ​​engine. New locations are added as nodes to the diagram, and their connections with other network elements are visually displayed. For example, a "Maintenance Robot" is added as a new node to the diagram, along with its line details and IP address. The input to this step is the generated data, and the output is an updated network diagram.

[0752] Step 6:

[0753] User Output and Visualization

[0754] The server outputs the updated management table and network configuration diagram to the user's device. This information is displayed visually, allowing the factory manager to easily check the new location information. Specifically, the user can view the updated network configuration diagram in real time on a smartphone or tablet. The input for this step is the updated management table and network configuration diagram, and the output is the visual information displayed on the user's device.

[0755] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0756] The system for implementing the present invention aims to efficiently and accurately manage information on newly added network nodes by users and automatically update the management table and network configuration diagram. Furthermore, the system includes an emotion engine for recognizing user emotions and improving the operating experience.

[0757] First, the user enters information about the new network site (site name, line details, router IP address, etc.) into the terminal. For example, information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" is entered into the form. The terminal then sends this information to the server.

[0758] The server validates the received information to ensure it is in the correct format and is complete. If all validations are passed, the server passes the data to the AI ​​engine and begins analysis. The AI ​​engine generates the data necessary to update the management table and network configuration diagram. For example, if the AI ​​engine receives the information "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it will generate a "management table entry" and a "configuration diagram node" for the update.

[0759] The server then uses the generated data to update the management table, which is a database that records and manages information about all nodes in the network, and adds an entry for the new node. This entry includes the node name, line details, IP address, and so on. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0760] Furthermore, this system incorporates an emotion engine to recognize the user's emotions. While the user is inputting information, the emotion engine analyzes the user's facial expressions and voice using a camera and microphone. The emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback.

[0761] For example, if the emotion engine determines that the user is feeling stressed while inputting information, the server can display input assistance and operation guides to the user. Also, if the server determines that the user is satisfied after adding a new location, it can highlight that result and provide positive feedback.

[0762] As a specific example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives this information and validates it. Next, the AI ​​engine analyzes it, adds the location "Tokyo Office" to the management table, and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it recognizes that the user is confused, it provides assistance with the input. Finally, the server outputs this updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[0763] In this way, the system provides accurate and efficient network management while minimizing user interaction, and also provides appropriate feedback according to the user's emotional state.

[0764] The processing flow will be explained below.

[0765] Step 1:

[0766] The user enters information about the new network location into the terminal. Specifically, the user enters information such as the location name "Osaka Branch," line details "Fiber 500Mbps," and router IP address "192.168.2.1" into the input form.

[0767] Step 2:

[0768] The terminal sends the input information to the server. Specifically, the data is sent as an HTTP request in JSON format.

[0769] Step 3:

[0770] The server analyzes the received HTTP request and parses the transmitted data. Specifically, it parses the request body in JSON format and obtains each key and value.

[0771] Step 4:

[0772] The server validates the data it receives, ensuring that it is formatted correctly and that all required fields are filled in. If the data is invalid, it generates an error message and sends it back to the terminal.

[0773] Step 5:

[0774] The server passes the data that has passed validation to the AI ​​engine, which then begins analysis. Specifically, the AI ​​engine generates the data necessary to update the management table and network configuration diagram based on the site name, line details, and router IP address.

[0775] Step 6:

[0776] The server updates the management table using the data returned from the AI ​​engine. Specifically, it inserts a new record into the management table database, adding the branch name "Osaka Branch," line details "Fiber 500Mbps," and router IP address "192.168.2.1."

[0777] Step 7:

[0778] The server updates the network diagram using the generated data. Specifically, it adds a new node, "Osaka Branch," to the network diagram database and sets its IP address, "192.168.2.1," and its connection information.

[0779] Step 8:

[0780] The server saves the updated management table and network diagram and writes it to the data store, performing additional checks to ensure data consistency and integrity.

[0781] Step 9:

[0782] The server uses an emotion engine to analyze the user's emotional state. Specifically, it analyzes the user's facial expressions and voice in real time through a camera and microphone to determine the user's emotional state (stress, frustration, joy, etc.).

[0783] Step 10:

[0784] The server generates appropriate feedback based on the user's emotional state. For example, if it determines that the user is feeling stressed, it displays input assistance and operation guides on the device. Conversely, if the user is satisfied, it displays positive feedback that emphasizes the user's satisfaction.

[0785] Step 11:

[0786] The server generates a response indicating that the update is complete and sends it to the terminal. The response includes details of the updated management table and network topology diagram, as well as a feedback message.

[0787] Step 12:

[0788] The terminal receives the response from the server and displays the updated results to the user. Specifically, it visually displays the updated management table and network configuration diagram, and displays feedback messages so that the user can check the results of the system's operation.

[0789] Example 2

[0790] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0791] Modern network management requires efficient and accurate management of additional information for new locations and smooth updates to management tables and network diagrams. It is also important to provide a good user experience by reducing the stress and confusion associated with data entry tasks. However, with conventional systems, it was difficult to perform these tasks efficiently and consistently.

[0792] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for receiving additional information about network nodes from a user; means for transmitting the received additional information to the server; means for validating the received additional information; means for analyzing the additional information using an AI engine and generating data necessary for updating the management table and the communication configuration diagram; means for updating the management table using the generated data; means for updating the communication configuration diagram using the generated data; means for outputting the updated management table and the communication configuration diagram to the user; and means for providing feedback according to the user's emotional state, which includes an emotion engine for analyzing the user's emotions. This improves the accuracy and efficiency of network management and improves the user's operation experience.

[0793] "Network location" is a term that refers to a specific physical or logical location or device within a computer network.

[0794] "Additional information" refers to new or changed data a user has about a network location.

[0795] "User" refers to a person who operates or uses this system.

[0796] A "server" is a computer connected to a network, and is a device that processes and manages data.

[0797] "Validation" is the process of checking whether entered data is of the correct format and content.

[0798] An "AI engine" is software or hardware that uses artificial intelligence technology to analyze and generate data.

[0799] A "management table" is a database or data structure for recording and managing information about network locations.

[0800] A "communication configuration diagram" is a diagram that visually shows each element in a network and its connection relationships.

[0801] The "emotion engine" is a system that analyzes the user's emotional state using input from a camera, microphone, etc., and provides appropriate feedback.

[0802] "Feedback" means the response or assistance information provided by the system to the user.

[0803] "Data generation" is the process of creating new data or required data structures based on received information.

[0804] The system for implementing the present invention comprises the following elements: It efficiently and accurately manages information about new network nodes added by users, automatically updates the management table and network configuration diagram, and includes an emotion engine for recognizing user emotions and improving the operating experience.

[0805] First, the user enters information about the new network site (site name, line details, IP address, etc.) on a device (PC, tablet, etc.). For example, information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" is entered into a form. The device sends this information to the server using a secure communication method (e.g., HTTPS).

[0806] The server validates the received information. Validation checks the accuracy of the branch name, the format of the IP address, the validity of the line details, etc. For example, it checks whether "Osaka Branch" is a valid string, and whether "192.168.2.1" is the correct IP address format. If all validations are passed, the server passes the data to the AI ​​engine to begin analysis.

[0807] The AI ​​engine uses the generative AI model to generate the data necessary to update the management table and network diagram. For example, when it receives "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it generates a management table entry and a diagram node. This allows the new branch information to be reflected in the management table and network diagram.

[0808] The server then uses the generated data to update the management table, which is a database that records information about all nodes in the network. The entry for the new node includes information such as the node name, line details, and IP address. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0809] Furthermore, this system incorporates an emotion engine to recognize the user's emotions. While the user is entering information, the emotion engine uses a camera and microphone to analyze the user's facial expressions and voice. The emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback. For example, if the emotion engine determines that the user is feeling stressed while entering information, the server will display input assistance and operation guides to the user. Also, if the server recognizes that the user is satisfied after adding a new location, it will highlight this result and provide positive feedback.

[0810] As a specific example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives this information and validates it. Next, the AI ​​engine analyzes it, adds the location "Tokyo Office" to the management table, and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it recognizes that the user is confused, it provides assistance with the input. Finally, the server outputs this updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[0811] Example prompt sentence:

[0812] "Please explain a system that, after a user inputs new network location information, validates the data, updates the management table and network diagram, and analyzes the user's sentiment in the process to provide appropriate feedback."

[0813] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0814] Step 1:

[0815] The user enters information about a new network site on the terminal. The information entered includes the site name, line details, IP address, etc. For example, "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1" are entered. This information is entered on a form and registered by pressing the Enter key or the submit button. The input data is collected as fields in the input form and converted to JSON format. The input data is sent to the next step.

[0816] Step 2:

[0817] The terminal sends the input information to the server. The terminal packages the input data in JSON format and sends it to the server using a secure communication protocol (e.g., HTTPS). The data is encrypted during transmission. The server receives the transmitted data and stores it in a database. The input data ("Tokyo Office", "Fiber 1Gbps", "192.168.3.1") is sent to the server, triggering a signal to start validation.

[0818] Step 3:

[0819] The server validates the information it receives. The server checks the data format, content integrity, and the accuracy of IP addresses. The validation process uses a validation script to ensure the data is in the correct format and that required fields are filled in. For example, it verifies that "Tokyo Office" is a valid location name field and that "192.168.3.1" is a valid IP address format. If validation is successful, the validated data is passed to the next analysis step.

[0820] Step 4:

[0821] The server sends the data to the AI ​​engine and instructs it to start analysis. The AI ​​engine uses the generative AI model to analyze the additional information it receives. The server sends the validated data to the AI ​​engine and begins analysis to generate a new dataset. For example, based on the input "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the AI ​​engine generates the necessary data, such as management table entries and configuration diagram nodes. The generated data is sent back from the AI ​​engine to the server.

[0822] Step 5:

[0823] The server updates the management table using the generated data. The server receives the data returned from the AI ​​engine and uses that data to update the management table database. For example, new location information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1" is added to the management table. The updated management table results are passed to the next configuration diagram update step.

[0824] Step 6:

[0825] The server updates the communication configuration diagram using the generated data. The server updates the network configuration diagram based on the generated data. New location information is visually added, and the connection relationships with existing network elements are shown. For example, a new node called "Tokyo Office" is added to the configuration diagram, and its connection relationships are visualized. The updated configuration diagram data is passed to the next output step.

[0826] Step 7:

[0827] The emotion engine analyzes the user's emotions. It analyzes the user's facial expressions and voice as they are inputting, and identifies their emotional state in real time. The emotion engine captures and analyzes data from the camera and microphone in real time. For example, if the user is feeling stressed, it recognizes this state and notifies the server. The notified emotional data is passed on to the next feedback step.

[0828] Step 8:

[0829] The server then feeds the results back to the user. The server provides feedback to the user based on the results of updating the management table and communication configuration diagram, and the analysis results of the emotion engine. For example, if the user is satisfied, this fact is highlighted and positive feedback is provided. If the user is feeling stressed, operation guides and input assistance are displayed. The feedback content is output to the terminal, allowing the user to visually confirm it.

[0830] (Application example 2)

[0831] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0832] In current logistics centers, efficient and accurate management of information about newly added network locations is an important issue. Furthermore, a lack of appropriate feedback based on the worker's emotions and status can lead to problems such as reduced operational efficiency and satisfaction. The present invention aims to solve these problems and improve the efficiency of network management in logistics centers and worker satisfaction.

[0833] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving additional information about network locations from a user, means for transmitting the received additional information to the server, means for analyzing the received additional information and generating data necessary for updating the management table and the network configuration diagram, means for updating the management table using the generated data, means for updating the network configuration diagram using the generated data, means for outputting the updated management table and the network configuration diagram to the user, and means including an emotion engine for recognizing the user's emotions and improving the operating experience. This not only enables efficient and accurate network management in a logistics center, but also provides feedback according to the emotions of workers, thereby improving operating efficiency and satisfaction.

[0834] A "network location" is a location or facility that is newly added to the network configuration.

[0835] "Additional information" is detailed information about the network location (e.g., location name, line speed, IP address).

[0836] A "user" is a person or entity that operates the system and inputs additional information for a network location.

[0837] The "server" is the central component of the system that receives and analyzes additional information sent by users and updates the management table and network configuration diagram.

[0838] The "management table" is a database for recording and managing information on all locations within the network.

[0839] A "network configuration diagram" is a diagram that visually shows the locations within a network and their connection relationships.

[0840] An "emotion engine" is an element of the system that uses a camera, microphone, etc. to analyze a user's facial expressions and voice and identify their emotional state.

[0841] "Validation" is the process of ensuring that any additional information received is accurate and complete.

[0842] An "AI engine" is an element of the system that uses artificial intelligence to analyze additional information and generate the data necessary to update management tables and network diagrams.

[0843] "Feedback" refers to the support and positive reactions provided by a system in response to a user's actions and emotions.

[0844] The system for implementing the present invention aims to efficiently and accurately manage and update additional information for network locations in a logistics center, and also includes an emotion engine for recognizing user emotions and improving the operating experience.

[0845] Specifically, a user enters information about a new network location into a management terminal at a logistics center. This information includes the location name, line details, IP address, etc. For example, information such as "Center A," "Fiber 500Mbps," and "192.168.2.1" might be used. Once the user has finished entering this information, the terminal sends it to the server. The server validates the received information to ensure it is in the correct format and complete. If all validations are met, the server passes the data to the AI ​​engine and begins analysis.

[0846] The AI ​​engine generates the data necessary to update the management table and network diagram. For example, after receiving information such as "Center A," "Fiber 500Mbps," and "192.168.2.1," the AI ​​engine generates a "management table entry" and a "diagram node" for the update. The server uses the generated data to update the management table and adds an entry for the new site. The server then updates the network diagram based on the generated data, adding the new site as a node and visually showing its connection relationships with other network elements.

[0847] The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice while they are entering information. This emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback. For example, if the emotion engine determines that the user is feeling stressed while entering information, the server will display input assistance and operation guides to the user. Also, if the server determines that the user is satisfied after adding a new network location, it will highlight that result and provide positive feedback.

[0848] A specific example is when a user enters information such as "Center B," "Fiber 1Gbps," and "192.168.3.1." In this case, the server receives the information and validates it, and the AI ​​engine begins analysis. The AI ​​engine adds a location called "Center B" to the management table and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it determines that the user is confused, it provides assistance with the input. Finally, the server outputs the updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[0849] The hardware used includes the management terminals, cameras, microphones, and server computers in the logistics center. The software used includes OpenCV (face recognition), EmotionRecognition (emotion recognition), NetworkValidation (data validation), UpdateNetworkConfig (updating the network configuration diagram), and the AI ​​engine that controls them. Specific examples of prompt statements are as follows:

[0850] Input information:

[0851] Branch Name: "Center A"

[0852] Line speed: "Fiber 500Mbps"

[0853] IP Address: 192.168.2.1

[0854] Expected output:

[0855] If the user feels stressed:

[0856] "The user is stressed. We will provide input assistance."

[0857] If the input passes validation:

[0858] "Network information validation was successful. The network diagram has been updated."

[0859] If the user is satisfied:

[0860] "Users are happy. They provide positive feedback."

[0861] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0862] Step 1:

[0863] The user enters the information for a new network location (e.g., "Center A," "Fiber 500Mbps," "192.168.2.1") into the terminal. This information is entered into a form in text format. The entered information is stored in the terminal.

[0864] Step 2:

[0865] The terminal sends the entered network location information to the server. The data sent is text data including the location name, line details, and IP address. By receiving the data sent from the terminal, the server is ready to start analyzing the data.

[0866] Step 3:

[0867] The server validates the received network location information. In this step, data validation is performed, including format confirmation and range checks for each value. If the correct format and complete data are confirmed, the server proceeds to the next step. Input: Received network location information, Output: Validation result (success / failure).

[0868] Step 4:

[0869] The server passes information that has passed validation to the AI ​​engine. The AI ​​engine analyzes the input information and generates the data necessary to update the management table entry and network diagram. For example, from the information "Center A," "Fiber 500Mbps," and "192.168.2.1," a "management table entry" and "diagram node" are generated. Input: Information that has passed validation. Output: Management table entry, diagram node.

[0870] Step 5:

[0871] The server uses the created management table entry to update the management table database, which contains information about all network nodes. It adds information about new nodes and keeps the overall network configuration information up to date. Input: Management table entry, Output: Updated management table.

[0872] Step 6:

[0873] The server updates the network diagram using the generated diagram nodes. New locations are added to the diagram, and the connections with other network elements are visually displayed. This allows the visual status of the entire network to be understood at a glance. Input: Diagram nodes, Output: Updated network diagram.

[0874] Step 7:

[0875] The server sends the updated management table and network configuration diagram to the user's device. The user can check the latest network information on the device. Input: Updated management table and network configuration diagram. Output: Latest information displayed on the user's device.

[0876] Step 8:

[0877] While the user is inputting information, the emotion engine is activated using the device's built-in camera and microphone. The emotion engine analyzes the user's facial expressions and voice to determine their emotional state in real time. For example, if the device determines that the user is feeling stressed, it will provide input assistance. Input: User's facial expressions and voice. Output: Determining emotional state and providing appropriate feedback.

[0878] Step 9:

[0879] The server provides appropriate feedback to the user based on the judgment made by the emotion engine. For example, if the server determines that the user is confused during input work, it will display operation guides to support the user. Also, if the server determines that the user is satisfied, it will provide positive feedback to improve the user's operation experience. Input: Result of the emotion engine, Output: Appropriate feedback.

[0880] This allows efficient and accurate management of network locations at the logistics center, and provides appropriate feedback according to the user's emotional state.

[0881] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0882] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0883] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[0884] [Fourth embodiment]

[0885] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0886] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0887] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0888] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0889] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0890] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0891] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0892] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0893] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0894] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0895] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0896] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0897] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0898] The system for implementing this invention aims to easily and accurately manage information about new network locations added by users, and automatically update management tables and network configuration diagrams. This system transmits information entered by users from their terminals to a server, which analyzes it using an AI engine, thereby achieving automatic generation and updating of data.

[0899] First, the user enters additional information about the network site (site name, line details, router IP address, etc.) into the terminal. For example, the user enters information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" into the form. The terminal then sends this information to the server.

[0900] The server validates the received information to ensure it is in the correct format and is complete. If all validations are met, the server passes the data to the AI ​​engine and begins analysis. The AI ​​engine generates the data necessary to update the management table and network diagram. For example, if the AI ​​engine receives the information "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it will generate a "management table entry" and a "diagram node" for the update.

[0901] The server then uses the generated data to update the management table, which is a database that records and manages information about all nodes in the network, and adds an entry for the new node. This entry includes the node name, line details, IP address, and so on. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[0902] Finally, the server outputs and displays the updated management table and network configuration diagram on the user's terminal, allowing the user to immediately check the information about the newly added base.

[0903] For example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives and validates this information. Next, the AI ​​engine analyzes the information and adds the "Tokyo Office" location to the management table and adds it as a new node to the network configuration diagram. The server then outputs this updated information to the user's device, where the user can view it.

[0904] In this way, the system provides accurate and efficient network management with minimal user intervention.

[0905] The processing flow will be explained below.

[0906] Step 1:

[0907] The user enters information about a new network site into the terminal. Specifically, the user enters information such as the site name, line details, and router IP address into the input form. For example, the user enters information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1."

[0908] Step 2:

[0909] The device sends the input information to the server as an HTTP request in JSON format.

[0910] Step 3:

[0911] The server receives the HTTP request and analyzes the data sent. Specifically, it parses the request body in JSON format and obtains each key and value.

[0912] Step 4:

[0913] The server validates the data it receives, checking that it is formatted correctly and that all required fields are filled in. If the data is invalid, it returns an error.

[0914] Step 5:

[0915] The server passes the data that has passed validation to the AI ​​engine, which then begins analysis. Specifically, the AI ​​engine generates the data necessary to update the management table and network configuration diagram based on the site name, line details, and router IP address.

[0916] Step 6:

[0917] The server updates the management table using the data returned from the AI ​​engine, specifically by inserting new records into the management table database or updating existing records.

[0918] Step 7:

[0919] The server also uses the generated data to update the network diagram, specifically adding new nodes to the network diagram database and setting connection information.

[0920] Step 8:

[0921] The server saves the updated management tables and network diagrams, writes them to the necessary data stores, and also performs checks to ensure data consistency and integrity.

[0922] Step 9:

[0923] The server generates a response indicating that the update is complete and sends it to the terminal, which includes the updated management table and details of the network topology diagram.

[0924] Step 10:

[0925] The terminal receives the response from the server and displays the updated results to the user. Specifically, it visually displays the updated management table and network configuration diagram, allowing the user to check the new location information.

[0926] Example 1

[0927] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0928] With existing network management systems, it is time-consuming to manually update management tables and network diagrams with additional information about network locations, which can lead to inaccuracies. Therefore, there is a need for a method to easily and accurately manage network location information and automatically update management tables and network diagrams.

[0929] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0930] In this invention, the server includes means for validating the additional information for the network site and confirming that it is in the correct format and complete, means for analyzing the received additional information and passing the data to an AI engine to generate data necessary for updating the management table and network configuration diagram, and means for updating the management table using the generated data. This makes it possible to automatically update the management table and network configuration diagram accurately and efficiently based on the network site information entered by the user.

[0931] "Network location" means a physical or logical location connected to a network, including the equipment and infrastructure for data transfer and communications.

[0932] "Additional information" refers to detailed data about a network site, including the site name, line details, router IP address, etc.

[0933] "User" means an individual or organization that uses the system to enter, manage, and review information about a network location.

[0934] "Terminal" refers to a device used by a user, such as a computer, tablet, or smartphone, and is a device for inputting and displaying information.

[0935] "Server" refers to a centralized computer system that provides services over a network, processes data received from users, and updates management tables and network diagrams.

[0936] "Validation" refers to the process of verifying data to ensure it is accurate and complete, including format and content checks.

[0937] "Analysis" refers to the process of using an AI engine to generate the necessary information based on the received data.

[0938] An "AI engine" refers to a system that uses artificial intelligence technology to analyze data and automatically generate management table entries and network configuration diagram nodes.

[0939] "Management table" refers to a database that records and manages information on all locations within a network.

[0940] A "network configuration diagram" refers to a diagram that visually shows each location within a network and their connection relationships.

[0941] "Generated data" refers to the management table entries and network diagram nodes that are analyzed and generated by the AI ​​engine.

[0942] This invention is a system that allows users to easily and accurately manage information about newly added network locations and automatically update management tables and network configuration diagrams. This system sends information entered by users to a terminal to a server, analyzes it using an AI engine, and automatically generates and updates data.

[0943] Hardware and software used

[0944] The system includes the following hardware and software:

[0945] Device: A computer, tablet, smartphone, etc. that a user operates.

[0946] Server: A centralized computer system.

[0947] AI Engine: An artificial intelligence system that performs data analysis and automatic generation.

[0948] Database: A database system for storing management tables.

[0949] Internet connection: Allows data communication between the device and the server.

[0950] Specific operation of the system

[0951] The user accesses the terminal and enters additional information about the network site (e.g., "site name," "line details," "router IP address," etc.). For example, the user enters "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1." The terminal then sends this information to the server.

[0952] The server validates the received information, checking whether the location name, line details, and router IP address are entered in a valid format. If validation is successful, the server passes the data to the AI ​​engine to begin analysis.

[0953] The AI ​​engine generates the data necessary to update the management table and network diagram. For example, it analyzes information on "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" to generate a "management table entry" and a "diagram node."

[0954] The server uses the generated data to update the management table, which records and manages information about all nodes in the network, and adds entries for new nodes. This includes the node name, line details, IP address, etc.

[0955] The server also updates the network diagram based on the generated data, adding new locations as nodes and visually showing their connections with other network elements.

[0956] Finally, the server outputs the updated management table and network configuration diagram to the terminal, allowing the user to immediately check them.

[0957] Specific examples

[0958] For example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," validation occurs when the server receives this information. The AI ​​engine then generates a "management table entry" and a "configuration diagram node" and returns them to the server. The server then updates the management table and network configuration diagram using the updated data and outputs this information to the user's device. The user can immediately view the new information.

[0959] Prompt Sentence Examples

[0960] An example of a prompt to be input to the generative AI model is as follows:

[0961] Input information: {

[0962] "Office Name": "Tokyo Office",

[0963] "Line details": "Fiber 1Gbps",

[0964] "Router IP Address": "192.168.3.1"

[0965] }

[0966] Use this information to generate and update management table entries and network diagram nodes.

[0967] In this way, the system provides accurate and efficient network management with minimal user intervention.

[0968] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0969] Step 1:

[0970] The user accesses the terminal and enters additional information about the network site. Specifically, the user enters the "site name," "line details," and "router IP address" into the input form. For example, the user might enter "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," and click the "Submit" button. The entered information is then imported into the terminal's system.

[0971] Step 2:

[0972] The device sends the additional information received from the user to the server. Specifically, the device sends the information entered in the form to the server as an HTTP POST request. This request contains data in JSON format. The sent information reaches the specified endpoint on the server.

[0973] Step 3:

[0974] The server validates the additional information it has received. Specifically, the server checks whether the site name, line details, and router IP address have been entered in the correct format. At this stage, it checks the format of the entered information (for example, whether the IP address format is correct) and whether all required fields have been filled in. If invalid data is found, it generates an error message and returns it to the terminal as an HTTP response. If validation is successful, it proceeds to the next step.

[0975] Step 4:

[0976] The server sends the information that has passed validation to the AI ​​engine. Specifically, the server sends the data to the AI ​​engine's API endpoint. At this time, the data to be sent uses the following prompt:

[0977] Input information: {

[0978] "Location Name": "Osaka Branch",

[0979] "Line details": "Fiber 500Mbps",

[0980] "Router IP Address": "192.168.2.1"

[0981] }

[0982] Use this information to generate and update management table entries and network diagram nodes.

[0983] Based on this prompt, the AI ​​engine begins analysis.

[0984] Step 5:

[0985] The AI ​​engine returns the analysis results to the server. Specifically, the AI ​​engine analyzes the input information and generates "management table entries" and "configuration diagram nodes." This data includes information such as the location name, line details, and IP address. The server receives this generated data.

[0986] Step 6:

[0987] The server updates the management table using the data received from the AI ​​engine. Specifically, the server adds a new entry to the database that stores the management table. This entry includes the branch name, line details, IP address, etc. For example, "Osaka Branch, Fiber 500Mbps, 192.168.2.1" is added as a new entry.

[0988] Step 7:

[0989] The server updates the network diagram using the generated data. Specifically, the server adds the new node to the network diagram database and updates the connections with other network elements. The new location is visually added to the updated diagram.

[0990] Step 8:

[0991] The server outputs the updated management table and network configuration diagram to the user's terminal. Specifically, the server returns the updated data to the terminal as an HTTP response. The terminal displays the received data on the screen, allowing the user to immediately check the new information. For example, "Osaka Branch, Fiber 500Mbps, 192.168.2.1" is added to the management table, and a new node is displayed on the network configuration diagram.

[0992] (Application example 1)

[0993] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0994] With conventional network site management systems, information about newly added sites must be manually updated in management tables and network configuration diagrams, which reduces efficiency when handling large amounts of data. Furthermore, when new equipment within a factory is added to the network, it is difficult to manage that information in real time, which can lead to incorrect information being updated. Furthermore, there is a lack of a way to visually check the network configuration, making it difficult for administrators to easily grasp the status of their equipment.

[0995] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0996] In this invention, the server includes means for receiving additional information about network locations from a user, means for transmitting the received additional information to the server, means for analyzing the received additional information and generating data necessary for updating the management table and the network configuration diagram, means for updating the management table using the generated data, means for updating the network configuration diagram using the generated data, means for outputting the updated management table and network configuration diagram to the user, means for collecting information about newly added equipment in the factory and automatically updating the management table and the network configuration diagram, and means for visually displaying the updated management table and the network configuration diagram. This provides an environment in which additional information about network locations in the factory can be automatically managed and visually confirmed, preventing errors and enabling efficient management.

[0997] A "network location" refers to a specific location or place where various digital devices and machines are connected.

[0998] "Means for receiving additional information" refers to the mechanism for collecting new data entered by the user.

[0999] "Means for sending to server" refers to the process of transferring collected data to the server.

[1000] "Means for analyzing and generating data necessary for updating the management table and configuration diagram" refers to a mechanism for analyzing input data and generating information necessary for updating the network management table and configuration diagram.

[1001] "Means for updating the management table" refers to a method for updating an existing management table to the latest version based on newly generated data.

[1002] "Means for updating a network configuration diagram" refers to a method for updating an existing network configuration diagram to the latest version based on newly generated data.

[1003] "Means of outputting to the user" refers to the mechanism for displaying and outputting the updated management table and network configuration diagram on the user's terminal.

[1004] "Means for collecting information on factory equipment and automatically updating management tables and configuration diagrams" refers to a system that automatically collects information on new machines or robots in the factory when they are connected to the network, and updates the management tables and configuration diagrams.

[1005] "Means for visual display" refers to a method for providing the user with an updated network configuration diagram or management table in a form that allows the user to visually confirm the updated network configuration diagram or management table.

[1006] The present invention is a system that automatically manages additional information for network locations within a factory and allows a manager to visually check it. A specific embodiment for realizing this system will be described below.

[1007] Program Generation

[1008] The system is built using the Python language. The main libraries used are the standard library for data validation, NetworkX and Matplotlib for generating and visualizing network configurations, and the AI ​​engine is designed to use generative AI models.

[1009] Natural language explanation of the process

[1010] The system works as follows:

[1011] 1. Collection and transmission of additional information about network locations

[1012] Using an application on a smartphone or tablet, users enter information (site name, line details, IP address) about the newly added factory equipment (robots and machines) into a form. This information is then sent from the device to the server.

[1013] 2. Data validation and analysis on the server

[1014] The server validates the received additional information to ensure that the format and content are correct. It then uses an AI engine to analyze the data and generate the data needed to update the management table and network diagram. This process utilizes a generative AI model to efficiently generate the data.

[1015] 3. Update management tables and network diagrams

[1016] Based on the generated data, the server updates the existing management table to the latest version. It also updates the network configuration diagram to visually reflect the new location and equipment information. This makes it possible to understand the network configuration within the factory at a glance.

[1017] 4. User Output and Visualization

[1018] The updated management table and network configuration diagram are output to the user's terminal in real time and displayed visually, allowing factory managers to immediately check information on newly added equipment.

[1019] Adding specific examples

[1020] For example, if a user enters the information "Maintenance Robot," "WiFi 600Mbps," and "192.168.0.40," the server receives and validates this information. The AI ​​engine then analyzes the information and adds a location called "Maintenance Robot" to the management table and adds it as a new node to the network configuration diagram. This allows factory managers to check the latest network status via smartphones or tablets.

[1021] Prompt Sentence Examples

[1022] Enter the information for your new factory robot. Include the site name, line details, and IP address. For example, "Site name: Maintenance Robot, Line details: WiFi 600Mbps, IP address: 192.168.0.40".

[1023] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1024] Step 1:

[1025] Collecting and sending additional information about your network locations

[1026] The user uses a smartphone or tablet application to input information about the newly added factory equipment (robots and machines). This information includes the base name, line details, and IP address. The input information is sent from the terminal to the server. As a specific example, the inputs are "Base name: Maintenance Robot," "Line details: WiFi 600Mbps," and "IP address: 192.168.0.40." The input for this step is the equipment information entered by the user, and the output is the data sent to the server.

[1027] Step 2:

[1028] Data Validation

[1029] The server validates the additional information it receives, specifically checking that the site name is entered correctly, that the line details are correct, and that the IP address is entered in the correct format. The data validation process ensures that the information entered is complete and accurate. If the data is successfully validated, it moves on to the next step. The input for validation is the data sent to the server, and the output is the validated data.

[1030] Step 3:

[1031] Data analysis

[1032] The server passes the data that has passed validation to the AI ​​engine. The AI ​​engine analyzes this data and generates new data needed to update the management table and network diagram. For example, it analyzes the location information for the "Maintenance Robot" and uses that data to generate a new entry in the management table and add a new node to the network diagram. The input to this step is validated data, and the output is the generated data.

[1033] Step 4:

[1034] Update management table

[1035] The server updates the management table using the data generated by the AI ​​engine. The management table is a database that records information about all network locations. New entries are added and existing information is kept up to date. For example, information about a "Maintenance Robot" is added as a new entry. The input to this step is the generated data, and the output is the updated management table.

[1036] Step 5:

[1037] Update the network diagram

[1038] The server updates the network diagram using the data generated by the AI ​​engine. New locations are added as nodes to the diagram, and their connections with other network elements are visually displayed. For example, a "Maintenance Robot" is added as a new node to the diagram, along with its line details and IP address. The input to this step is the generated data, and the output is an updated network diagram.

[1039] Step 6:

[1040] User Output and Visualization

[1041] The server outputs the updated management table and network configuration diagram to the user's device. This information is displayed visually, allowing the factory manager to easily check the new location information. Specifically, the user can view the updated network configuration diagram in real time on a smartphone or tablet. The input for this step is the updated management table and network configuration diagram, and the output is the visual information displayed on the user's device.

[1042] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1043] The system for implementing the present invention aims to efficiently and accurately manage information on newly added network nodes by users and automatically update the management table and network configuration diagram. Furthermore, the system includes an emotion engine for recognizing user emotions and improving the operating experience.

[1044] First, the user enters information about the new network site (site name, line details, router IP address, etc.) into the terminal. For example, information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" is entered into the form. The terminal then sends this information to the server.

[1045] The server validates the received information to ensure it is in the correct format and is complete. If all validations are passed, the server passes the data to the AI ​​engine and begins analysis. The AI ​​engine generates the data necessary to update the management table and network configuration diagram. For example, if the AI ​​engine receives the information "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it will generate a "management table entry" and a "configuration diagram node" for the update.

[1046] The server then uses the generated data to update the management table, which is a database that records and manages information about all nodes in the network, and adds an entry for the new node. This entry includes the node name, line details, IP address, and so on. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[1047] Furthermore, this system incorporates an emotion engine to recognize the user's emotions. While the user is inputting information, the emotion engine analyzes the user's facial expressions and voice using a camera and microphone. The emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback.

[1048] For example, if the emotion engine determines that the user is feeling stressed while inputting information, the server can display input assistance and operation guides to the user. Also, if the server determines that the user is satisfied after adding a new location, it can highlight that result and provide positive feedback.

[1049] As a specific example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives this information and validates it. Next, the AI ​​engine analyzes it, adds the location "Tokyo Office" to the management table, and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it recognizes that the user is confused, it provides assistance with the input. Finally, the server outputs this updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[1050] In this way, the system provides accurate and efficient network management while minimizing user interaction, and also provides appropriate feedback according to the user's emotional state.

[1051] The processing flow will be explained below.

[1052] Step 1:

[1053] The user enters information about the new network location into the terminal. Specifically, the user enters information such as the location name "Osaka Branch," line details "Fiber 500Mbps," and router IP address "192.168.2.1" into the input form.

[1054] Step 2:

[1055] The terminal sends the input information to the server. Specifically, the data is sent as an HTTP request in JSON format.

[1056] Step 3:

[1057] The server analyzes the received HTTP request and parses the transmitted data. Specifically, it parses the request body in JSON format and obtains each key and value.

[1058] Step 4:

[1059] The server validates the data it receives, ensuring that it is formatted correctly and that all required fields are filled in. If the data is invalid, it generates an error message and sends it back to the terminal.

[1060] Step 5:

[1061] The server passes the data that has passed validation to the AI ​​engine, which then begins analysis. Specifically, the AI ​​engine generates the data necessary to update the management table and network configuration diagram based on the site name, line details, and router IP address.

[1062] Step 6:

[1063] The server updates the management table using the data returned from the AI ​​engine. Specifically, it inserts a new record into the management table database, adding the branch name "Osaka Branch," line details "Fiber 500Mbps," and router IP address "192.168.2.1."

[1064] Step 7:

[1065] The server updates the network diagram using the generated data. Specifically, it adds a new node, "Osaka Branch," to the network diagram database and sets its IP address, "192.168.2.1," and its connection information.

[1066] Step 8:

[1067] The server saves the updated management table and network diagram and writes it to the data store, performing additional checks to ensure data consistency and integrity.

[1068] Step 9:

[1069] The server uses an emotion engine to analyze the user's emotional state. Specifically, it analyzes the user's facial expressions and voice in real time through a camera and microphone to determine the user's emotional state (stress, frustration, joy, etc.).

[1070] Step 10:

[1071] The server generates appropriate feedback based on the user's emotional state. For example, if it determines that the user is feeling stressed, it displays input assistance and operation guides on the device. Conversely, if the user is satisfied, it displays positive feedback that emphasizes the user's satisfaction.

[1072] Step 11:

[1073] The server generates a response indicating that the update is complete and sends it to the terminal. The response includes details of the updated management table and network topology diagram, as well as a feedback message.

[1074] Step 12:

[1075] The terminal receives the response from the server and displays the updated results to the user. Specifically, it visually displays the updated management table and network configuration diagram, and displays feedback messages so that the user can check the results of the system's operation.

[1076] Example 2

[1077] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1078] Modern network management requires efficient and accurate management of additional information for new locations and smooth updates to management tables and network diagrams. It is also important to provide a good user experience by reducing the stress and confusion associated with data entry tasks. However, with conventional systems, it was difficult to perform these tasks efficiently and consistently.

[1079] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for receiving additional information about network nodes from a user; means for transmitting the received additional information to the server; means for validating the received additional information; means for analyzing the additional information using an AI engine and generating data necessary for updating the management table and the communication configuration diagram; means for updating the management table using the generated data; means for updating the communication configuration diagram using the generated data; means for outputting the updated management table and the communication configuration diagram to the user; and means for providing feedback according to the user's emotional state, which includes an emotion engine for analyzing the user's emotions. This improves the accuracy and efficiency of network management and improves the user's operation experience.

[1080] "Network location" is a term that refers to a specific physical or logical location or device within a computer network.

[1081] "Additional information" refers to new or changed data a user has about a network location.

[1082] "User" refers to a person who operates or uses this system.

[1083] A "server" is a computer connected to a network, and is a device that processes and manages data.

[1084] "Validation" is the process of checking whether entered data is of the correct format and content.

[1085] An "AI engine" is software or hardware that uses artificial intelligence technology to analyze and generate data.

[1086] A "management table" is a database or data structure for recording and managing information about network locations.

[1087] A "communication configuration diagram" is a diagram that visually shows each element in a network and its connection relationships.

[1088] The "emotion engine" is a system that analyzes the user's emotional state using input from a camera, microphone, etc., and provides appropriate feedback.

[1089] "Feedback" means the response or assistance information provided by the system to the user.

[1090] "Data generation" is the process of creating new data or required data structures based on received information.

[1091] The system for implementing the present invention comprises the following elements: It efficiently and accurately manages information about new network nodes added by users, automatically updates the management table and network configuration diagram, and includes an emotion engine for recognizing user emotions and improving the operating experience.

[1092] First, the user enters information about the new network site (site name, line details, IP address, etc.) on a device (PC, tablet, etc.). For example, information such as "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1" is entered into a form. The device sends this information to the server using a secure communication method (e.g., HTTPS).

[1093] The server validates the received information. Validation checks the accuracy of the branch name, the format of the IP address, the validity of the line details, etc. For example, it checks whether "Osaka Branch" is a valid string, and whether "192.168.2.1" is the correct IP address format. If all validations are passed, the server passes the data to the AI ​​engine to begin analysis.

[1094] The AI ​​engine uses the generative AI model to generate the data necessary to update the management table and network diagram. For example, when it receives "Osaka Branch," "Fiber 500Mbps," and "192.168.2.1," it generates a management table entry and a diagram node. This allows the new branch information to be reflected in the management table and network diagram.

[1095] The server then uses the generated data to update the management table, which is a database that records information about all nodes in the network. The entry for the new node includes information such as the node name, line details, and IP address. The server also updates the network diagram based on the generated data. The new node is added as a node in the diagram, and its connection relationships with other network elements are visually displayed.

[1096] Furthermore, this system incorporates an emotion engine to recognize the user's emotions. While the user is entering information, the emotion engine uses a camera and microphone to analyze the user's facial expressions and voice. The emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback. For example, if the emotion engine determines that the user is feeling stressed while entering information, the server will display input assistance and operation guides to the user. Also, if the server recognizes that the user is satisfied after adding a new location, it will highlight this result and provide positive feedback.

[1097] As a specific example, if a user enters information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the server receives this information and validates it. Next, the AI ​​engine analyzes it, adds the location "Tokyo Office" to the management table, and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it recognizes that the user is confused, it provides assistance with the input. Finally, the server outputs this updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[1098] Example prompt sentence:

[1099] "Please explain a system that, after a user inputs new network location information, validates the data, updates the management table and network diagram, and analyzes the user's sentiment in the process to provide appropriate feedback."

[1100] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1101] Step 1:

[1102] The user enters information about a new network site on the terminal. The information entered includes the site name, line details, IP address, etc. For example, "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1" are entered. This information is entered on a form and registered by pressing the Enter key or the submit button. The input data is collected as fields in the input form and converted to JSON format. The input data is sent to the next step.

[1103] Step 2:

[1104] The terminal sends the input information to the server. The terminal packages the input data in JSON format and sends it to the server using a secure communication protocol (e.g., HTTPS). The data is encrypted during transmission. The server receives the transmitted data and stores it in a database. The input data ("Tokyo Office", "Fiber 1Gbps", "192.168.3.1") is sent to the server, triggering a signal to start validation.

[1105] Step 3:

[1106] The server validates the information it receives. The server checks the data format, content integrity, and the accuracy of IP addresses. The validation process uses a validation script to ensure the data is in the correct format and that required fields are filled in. For example, it verifies that "Tokyo Office" is a valid location name field and that "192.168.3.1" is a valid IP address format. If validation is successful, the validated data is passed to the next analysis step.

[1107] Step 4:

[1108] The server sends the data to the AI ​​engine and instructs it to start analysis. The AI ​​engine uses the generative AI model to analyze the additional information it receives. The server sends the validated data to the AI ​​engine and begins analysis to generate a new dataset. For example, based on the input "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1," the AI ​​engine generates the necessary data, such as management table entries and configuration diagram nodes. The generated data is sent back from the AI ​​engine to the server.

[1109] Step 5:

[1110] The server updates the management table using the generated data. The server receives the data returned from the AI ​​engine and uses that data to update the management table database. For example, new location information such as "Tokyo Office," "Fiber 1Gbps," and "192.168.3.1" is added to the management table. The updated management table results are passed to the next configuration diagram update step.

[1111] Step 6:

[1112] The server updates the communication configuration diagram using the generated data. The server updates the network configuration diagram based on the generated data. New location information is visually added, and the connection relationships with existing network elements are shown. For example, a new node called "Tokyo Office" is added to the configuration diagram, and its connection relationships are visualized. The updated configuration diagram data is passed to the next output step.

[1113] Step 7:

[1114] The emotion engine analyzes the user's emotions. It analyzes the user's facial expressions and voice as they are inputting, and identifies their emotional state in real time. The emotion engine captures and analyzes data from the camera and microphone in real time. For example, if the user is feeling stressed, it recognizes this state and notifies the server. The notified emotional data is passed on to the next feedback step.

[1115] Step 8:

[1116] The server then feeds the results back to the user. The server provides feedback to the user based on the results of updating the management table and communication configuration diagram, and the analysis results of the emotion engine. For example, if the user is satisfied, this fact is highlighted and positive feedback is provided. If the user is feeling stressed, operation guides and input assistance are displayed. The feedback content is output to the terminal, allowing the user to visually confirm it.

[1117] (Application example 2)

[1118] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1119] In current logistics centers, efficient and accurate management of information about newly added network locations is an important issue. Furthermore, a lack of appropriate feedback based on the worker's emotions and status can lead to problems such as reduced operational efficiency and satisfaction. The present invention aims to solve these problems and improve the efficiency of network management in logistics centers and worker satisfaction.

[1120] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving additional information about network locations from a user, means for transmitting the received additional information to the server, means for analyzing the received additional information and generating data necessary for updating the management table and the network configuration diagram, means for updating the management table using the generated data, means for updating the network configuration diagram using the generated data, means for outputting the updated management table and the network configuration diagram to the user, and means including an emotion engine for recognizing the user's emotions and improving the operating experience. This not only enables efficient and accurate network management in a logistics center, but also provides feedback according to the emotions of workers, thereby improving operating efficiency and satisfaction.

[1121] A "network location" is a location or facility that is newly added to the network configuration.

[1122] "Additional information" is detailed information about the network location (e.g., location name, line speed, IP address).

[1123] A "user" is a person or entity that operates the system and inputs additional information for a network location.

[1124] The "server" is the central component of the system that receives and analyzes additional information sent by users and updates the management table and network configuration diagram.

[1125] The "management table" is a database for recording and managing information on all locations within the network.

[1126] A "network configuration diagram" is a diagram that visually shows the locations within a network and their connection relationships.

[1127] An "emotion engine" is an element of the system that uses a camera, microphone, etc. to analyze a user's facial expressions and voice and identify their emotional state.

[1128] "Validation" is the process of ensuring that any additional information received is accurate and complete.

[1129] An "AI engine" is an element of the system that uses artificial intelligence to analyze additional information and generate the data necessary to update management tables and network diagrams.

[1130] "Feedback" refers to the support and positive reactions provided by a system in response to a user's actions and emotions.

[1131] The system for implementing the present invention aims to efficiently and accurately manage and update additional information for network locations in a logistics center, and also includes an emotion engine for recognizing user emotions and improving the operating experience.

[1132] Specifically, a user enters information about a new network location into a management terminal at a logistics center. This information includes the location name, line details, IP address, etc. For example, information such as "Center A," "Fiber 500Mbps," and "192.168.2.1" might be used. Once the user has finished entering this information, the terminal sends it to the server. The server validates the received information to ensure it is in the correct format and complete. If all validations are met, the server passes the data to the AI ​​engine and begins analysis.

[1133] The AI ​​engine generates the data necessary to update the management table and network diagram. For example, after receiving information such as "Center A," "Fiber 500Mbps," and "192.168.2.1," the AI ​​engine generates a "management table entry" and a "diagram node" for the update. The server uses the generated data to update the management table and adds an entry for the new site. The server then updates the network diagram based on the generated data, adding the new site as a node and visually showing its connection relationships with other network elements.

[1134] The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice while they are entering information. This emotion engine identifies the user's emotional state (e.g., stress, frustration, joy, etc.) in real time and provides appropriate feedback. For example, if the emotion engine determines that the user is feeling stressed while entering information, the server will display input assistance and operation guides to the user. Also, if the server determines that the user is satisfied after adding a new network location, it will highlight that result and provide positive feedback.

[1135] A specific example is when a user enters information such as "Center B," "Fiber 1Gbps," and "192.168.3.1." In this case, the server receives the information and validates it, and the AI ​​engine begins analysis. The AI ​​engine adds a location called "Center B" to the management table and adds it as a new node to the network configuration diagram. The emotion engine analyzes the user's facial expressions while they are entering information, and if it determines that the user is confused, it provides assistance with the input. Finally, the server outputs the updated information to the user's device so that the user can confirm it. If the user is satisfied, it provides feedback to that effect.

[1136] The hardware used includes the management terminals, cameras, microphones, and server computers in the logistics center. The software used includes OpenCV (face recognition), EmotionRecognition (emotion recognition), NetworkValidation (data validation), UpdateNetworkConfig (updating the network configuration diagram), and the AI ​​engine that controls them. Specific examples of prompt statements are as follows:

[1137] Input information:

[1138] Branch Name: "Center A"

[1139] Line speed: "Fiber 500Mbps"

[1140] IP Address: 192.168.2.1

[1141] Expected output:

[1142] If the user feels stressed:

[1143] "The user is stressed. We will provide input assistance."

[1144] If the input passes validation:

[1145] "Network information validation was successful. The network diagram has been updated."

[1146] If the user is satisfied:

[1147] "Users are happy. They provide positive feedback."

[1148] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1149] Step 1:

[1150] The user enters the information for a new network location (e.g., "Center A," "Fiber 500Mbps," "192.168.2.1") into the terminal. This information is entered into a form in text format. The entered information is stored in the terminal.

[1151] Step 2:

[1152] The terminal sends the entered network location information to the server. The data sent is text data including the location name, line details, and IP address. By receiving the data sent from the terminal, the server is ready to start analyzing the data.

[1153] Step 3:

[1154] The server validates the received network location information. In this step, data validation is performed, including format confirmation and range checks for each value. If the correct format and complete data are confirmed, the server proceeds to the next step. Input: Received network location information, Output: Validation result (success / failure).

[1155] Step 4:

[1156] The server passes information that has passed validation to the AI ​​engine. The AI ​​engine analyzes the input information and generates the data necessary to update the management table entry and network diagram. For example, from the information "Center A," "Fiber 500Mbps," and "192.168.2.1," a "management table entry" and "diagram node" are generated. Input: Information that has passed validation. Output: Management table entry, diagram node.

[1157] Step 5:

[1158] The server uses the created management table entry to update the management table database, which contains information about all network nodes. It adds information about new nodes and keeps the overall network configuration information up to date. Input: Management table entry, Output: Updated management table.

[1159] Step 6:

[1160] The server updates the network diagram using the generated diagram nodes. New locations are added to the diagram, and the connections with other network elements are visually displayed. This allows the visual status of the entire network to be understood at a glance. Input: Diagram nodes, Output: Updated network diagram.

[1161] Step 7:

[1162] The server sends the updated management table and network configuration diagram to the user's device. The user can check the latest network information on the device. Input: Updated management table and network configuration diagram. Output: Latest information displayed on the user's device.

[1163] Step 8:

[1164] While the user is inputting information, the emotion engine is activated using the device's built-in camera and microphone. The emotion engine analyzes the user's facial expressions and voice to determine their emotional state in real time. For example, if the device determines that the user is feeling stressed, it will provide input assistance. Input: User's facial expressions and voice. Output: Determining emotional state and providing appropriate feedback.

[1165] Step 9:

[1166] The server provides appropriate feedback to the user based on the judgment made by the emotion engine. For example, if the server determines that the user is confused during input work, it will display operation guides to support the user. Also, if the server determines that the user is satisfied, it will provide positive feedback to improve the user's operation experience. Input: Result of the emotion engine, Output: Appropriate feedback.

[1167] This allows efficient and accurate management of network locations at the logistics center, and provides appropriate feedback according to the user's emotional state.

[1168] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1169] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1170] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1171] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1172] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1173] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1174] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1175] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1176] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1177] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1178] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1179] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1180] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1181] 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.

[1182] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1183] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1184] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1185] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1186] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1187] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1188] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1189] The following is further disclosed regarding the above embodiment.

[1190] (Claim 1)

[1191] means for receiving additional information about the network location from the user;

[1192] means for transmitting the received additional information to a server;

[1193] means for analyzing the received additional information and generating data necessary to update the management table and the network configuration diagram;

[1194] means for updating the management table using the generated data;

[1195] means for updating the network configuration diagram using the generated data;

[1196] means for outputting the updated management table and network configuration diagram to a user;

[1197] A system including:

[1198] (Claim 2)

[1199] 10. The system of claim 1, further comprising means for validating the received additional information.

[1200] (Claim 3)

[1201] The system according to claim 1, further comprising means for analyzing the additional information using an AI engine and generating data necessary for updating the management table and the network configuration diagram.

[1202] "Example 1"

[1203] (Claim 1)

[1204] means for receiving additional information about the network location from the user;

[1205] means for transmitting the received additional information to a server;

[1206] A means of validating any additional information received to ensure it is in the correct format and completeness; and

[1207] A means for analyzing the received additional information and passing the data to an AI engine to generate data necessary to update the management table and network configuration diagram;

[1208] means for updating the management table using the generated data;

[1209] means for updating the network configuration diagram using the generated data;

[1210] means for outputting the updated management table and network configuration diagram to a user;

[1211] A system including:

[1212] (Claim 2)

[1213] 2. The system according to claim 1, further comprising means for performing validation and generating an error message and returning it to the terminal if invalid data is found.

[1214] (Claim 3)

[1215] 2. The system of claim 1, further comprising means for analyzing the additional information using an AI engine and generating management table entries and network topology diagram nodes.

[1216] "Application Example 1"

[1217] (Claim 1)

[1218] means for receiving additional information about the network location from the user;

[1219] means for transmitting the received additional information to a server;

[1220] means for analyzing the received additional information and generating data necessary to update the management table and the network configuration diagram;

[1221] means for updating the management table using the generated data;

[1222] means for updating the network configuration diagram using the generated data;

[1223] means for outputting the updated management table and network configuration diagram to a user;

[1224] A means for collecting information on newly added factory equipment and automatically updating the management table and network configuration diagram;

[1225] a means for visually displaying the updated management table and network configuration diagram;

[1226] A system including:

[1227] (Claim 2)

[1228] 10. The system of claim 1, further comprising means for validating the received additional information.

[1229] (Claim 3)

[1230] The system according to claim 1, further comprising means for analyzing the additional information using an AI engine and generating data necessary for updating the management table and the network configuration diagram.

[1231] "Example 2: Combining Emotion Engines"

[1232] (Claim 1)

[1233] a means for receiving additional information about the network location from the user;

[1234] means for transmitting the received additional information to a server;

[1235] A means of validating any additional information received; and

[1236] A means for analyzing the additional information using an AI engine and generating data necessary to update the management table and communication configuration diagram;

[1237] means for updating the management table using the generated data;

[1238] means for updating the communication configuration diagram using the generated data;

[1239] means for outputting the updated management table and communication configuration diagram to a user;

[1240] a means for providing feedback according to the user's emotional state, the means comprising an emotion engine for analyzing the user's emotions;

[1241] A system including:

[1242] (Claim 2)

[1243] 10. The system of claim 1, further comprising means for validating the received additional information.

[1244] (Claim 3)

[1245] The system according to claim 1, further comprising means for analyzing the additional information using an AI engine and generating data necessary for updating the management table and the communication configuration diagram.

[1246] "Application example 2 when combining emotion engines"

[1247] (Claim 1)

[1248] means for receiving additional information about the network location from the user;

[1249] means for transmitting the received additional information to a server;

[1250] means for analyzing the received additional information and generating data necessary to update the management table and the network configuration diagram;

[1251] means for updating the management table using the generated data;

[1252] means for updating the network configuration diagram using the generated data;

[1253] means for outputting the updated management table and network configuration diagram to a user;

[1254] means including an emotion engine for recognizing a user's emotion and improving the operation experience;

[1255] A system including:

[1256] (Claim 2)

[1257] 10. The system of claim 1, further comprising means for validating the received additional information.

[1258] (Claim 3)

[1259] The system according to claim 1, further comprising means for analyzing the additional information using an AI engine and generating data necessary for updating the management table and the network configuration diagram. [Explanation of symbols]

[1260] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving additional information about the network location from the user; means for transmitting the received additional information to a server; means for analyzing the received additional information and generating data necessary to update the management table and the network configuration diagram; means for updating the management table using the generated data; means for updating the network configuration diagram using the generated data; means for outputting the updated management table and network configuration diagram to a user; A system including:

2. 10. The system of claim 1, further comprising means for validating the received additional information.

3. The system according to claim 1, further comprising means for analyzing the additional information using an AI engine and generating data required to update the management table and the network configuration diagram.

Images