System

Abstract

A system is provided.SOLUTION: A system comprising: means for automatically collecting setting information and parameters from a plurality of nodes; means for analyzing the collected setting information and parameters on the basis of standard materials and evaluating compatibility; means for automatically generating a design specification on the basis of an analysis result; means for acquiring comments and additional information from a system user and reflecting the comments and the additional information on the design specification; and means for finally checking the generated design specification, converting the design specification into an output format, and providing the output format.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In conventional engineering work, collecting configuration information and parameters from multiple nodes and creating design specifications based on that information takes a great deal of time and effort. Furthermore, these specifications must conform to standard documents, and comparing them with the standard documents is time-consuming, making efficient work difficult. As a result, design errors are likely to occur, raising the risk of system accidents. This invention aims to provide a new method for improving the efficiency of engineers' work and preventing system accidents caused by design errors. [Means for solving the problem]

[0005] This invention solves the above-mentioned problems by providing a system that automatically collects configuration information and parameters from multiple nodes, analyzes them based on standard data, and evaluates their compatibility. Specifically, the system first provides a means for collecting configuration information and parameters from multiple nodes. Next, the collected information is analyzed based on standard data to evaluate its compatibility. The system then includes a means for automatically generating a design specification based on the analysis results. The system further includes a means for receiving comments and additional information from system users and incorporating them into the design specification. Finally, the system provides a means for performing a final check of the generated design specification, converting it into an output format, and providing it, thereby enabling the efficient and accurate creation of design specifications. This reduces design errors and the risk of system accidents.

[0006] A "node" refers to an individual component or piece of equipment in a system.

[0007] "Configuration information" refers to data and parameters that define the operation and configuration of a system or node.

[0008] "Parameter" refers to a numerical value or setting used to optimize the operation of a system or node under specific conditions.

[0009] "Standards documents" refer to technical documents and guidelines that are based on industry standards or specifications. Examples include 3GPP and RFCs.

[0010] "Analysis" refers to the methods and processes used to understand and evaluate the content of collected data and information.

[0011] "Conformance" refers to the criteria for assessing how well a system or configuration conforms to a particular standard or specification.

[0012] "Design Specification" means a document that contains detailed information and instructions regarding the design of a system or node.

[0013] "Automatic generation" refers to the process of using programs or algorithms to generate required information or documentation with minimal manual intervention.

[0014] "Comments" refer to information such as explanations, instructions, and correction requests added by users.

[0015] "Additional information" refers to data relating to specific requests or conditions provided by the user in addition to basic configuration information and parameters.

[0016] "Final check" refers to the process of checking and verifying the contents of the generated design specifications to ensure there are no errors or omissions.

[0017] "Output format" refers to the format in which the generated document or data is stored or displayed. Examples include PDF and Word. [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] This invention is a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on that information. The functions of the system, which consists of three entities: users, terminals, and servers, are explained below.

[0040] Server Features

[0041] Data collection

[0042] The server first obtains a list of nodes to collect from the database. According to that list, it connects to each node and collects configuration information and parameters. Collection methods include SNMP, API calls, and SSH. The collected data is stored in a temporary database.

[0043] Data analysis and comparison with standard data

[0044] The collected data is analyzed based on standard documents (e.g., 3GPP, RFC). During the analysis, the collected data is normalized and compared with the standard documents to identify matches and inconsistencies.

[0045] Automatic generation of design specifications

[0046] The server automatically generates design specifications based on the analysis results. First, it reads a document template that conforms to the standard materials and embeds the collected data in the appropriate locations of the template. In this way, the design specifications are generated.

[0047] Providing a customization interface

[0048] The server provides an interface where the user can input comments and additional information, and when the comments and additional information are obtained from the user, the design specification is adjusted accordingly.

[0049] Final checks and output

[0050] Finally, the server checks the entire generated design specification and makes any necessary corrections. After the check is complete, the design specification is output in a format such as PDF or Word and provided to the user.

[0051] Device Features

[0052] Navigating the User Interface

[0053] The user starts the process of automatically generating design specifications through the GUI on the terminal. First, they input the necessary node information and collection parameters into the terminal and instruct the server to collect data.

[0054] Customized Input

[0055] After the automatic generation of the design specification is completed, the user accesses a screen on their terminal to input comments and additional information, where they can enter specific requirements and conditions and send them to the server.

[0056] User Roles

[0057] System Check

[0058] The user reviews the design specifications provided by the server, checks whether there are any problems with the content, and, if necessary, adds comments or requests corrections.

[0059] Final Approval

[0060] The user reviews the final specifications and, if satisfied, approves them. The approved design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[0061] Specific examples

[0062] As a concrete example, let's assume that a telecommunications carrier introduces a new base station (node) and automatically generates its design specifications. In this case, the server collects configuration information from existing base stations in the carrier's network. The collected data is analyzed based on 3GPP standard documents, and the design specifications are automatically generated based on the results. The user enters comments from their device regarding special requirements for the base station and any areas that need adjustment, and the server reflects these comments and modifies the specifications. After a final check, the design specifications are output in PDF format and provided to the user. This entire process streamlines design work and reduces the risk of accidents caused by design errors.

[0063] The processing flow will be explained below.

[0064] Server Processing Steps

[0065] Step 1: Get the node list

[0066] The server retrieves a list of nodes to connect to from a database, which contains the information needed to connect to the nodes, such as IP addresses and authentication information.

[0067] Step 2: Connect to the node

[0068] The server connects to each node in turn based on the node list, using methods such as SNMP, API calls, and SSH.

[0069] Step 3: Data collection

[0070] The server retrieves configuration information and parameters from the connected nodes, including the node's operating status, settings, sensor data, etc. This collected data is temporarily stored in a database.

[0071] Step 4: Loading the standard materials

[0072] The server loads standard documents such as 3GPP and RFCs and prepares them for comparison with the collected data, thereby clarifying the reference documents and guidelines.

[0073] Step 5: Data Preprocessing

[0074] The server preprocesses the collected data, normalizing it and imputing missing values. Preprocessing ensures data integrity and makes analysis easier.

[0075] Step 6: Data analysis and comparison with standard reference materials

[0076] The server then compares the pre-processed data against the standard, evaluating how well the data conforms to the standard and identifying any areas where it does not conform.

[0077] Step 7: Load the design specification template

[0078] The server loads a standard-compliant design specification template, which includes basic items and formats.

[0079] Step 8: Data Embedding

[0080] Based on the analysis results, the server embeds the collected data in the appropriate locations of the design specification template, thereby forming the basis of the design specification.

[0081] Step 9: Providing a Comment Interface

[0082] The server provides an interface for the user to enter comments and additional information, and adjusts the design specification according to the user's input.

[0083] Step 10: Final checks and adjustments

[0084] The server performs a final check of the generated design specifications, adjusting the layout and format, correcting errors, and so on.

[0085] Step 11: Output design specifications

[0086] The server outputs the final design specifications in PDF or Word format and provides them to the user, who can then share them with the project team and other stakeholders.

[0087] Terminal processing steps

[0088] Step 1: Launch the user interface

[0089] The user starts the GUI on the terminal and accesses the screen for automatically generating design specifications.

[0090] Step 2: Enter node information

[0091] The user inputs information about the target node and collection parameters into the terminal, including the node's IP address, authentication information, and collection items.

[0092] Step 3: Data collection instructions

[0093] The user issues an instruction to the server to collect the setting information and parameters of the specified node. This instruction is sent to the server, and data collection begins.

[0094] Step 4: Check the retrieved data

[0095] The user can check some of the collected data to see if specific data has been acquired. If there is a problem, the user can issue a collection command to the server again.

[0096] Step 5: Enter customization comments

[0097] The user operates an interface to enter any comments or special requirements they wish to add to the design specification, including requests for modifications based on specific conditions or requirements.

[0098] Step 6: Submit your comment

[0099] User comments and correction requests are sent from the terminal to the server, which receives this information and adjusts the design specifications accordingly.

[0100] User processing steps

[0101] Step 1: Review the design specifications

[0102] The user checks the design specifications provided by the server on their terminal, carefully examining the content to ensure there are no problems.

[0103] Step 2: Request additional revisions

[0104] If the user finds any deficiencies or errors in the design specifications, they can enter comments or correction requests and send them to the server, which then receives them and readjusts the specifications.

[0105] Step 3: Final Approval

[0106] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[0107] These are the specific processing steps for the server, terminal, and user. This process makes the creation of design specifications more efficient and reduces the risk of system accidents caused by design errors.

[0108] Example 1

[0109] 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."

[0110] In modern network systems, collecting configuration information and parameters from multiple nodes and creating design specifications based on that information is extremely complex and time-consuming. Furthermore, accurately reflecting the analysis results of the collected data requires specialized knowledge, which increases the risk of errors and inconsistencies. Furthermore, incorporating user comments and additional information into design specifications is often done manually, which is inefficient. Therefore, there is a need for a method to automate these processes and efficiently create high-quality design specifications.

[0111] 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.

[0112] In this invention, the server includes: means for automatically collecting setting information and parameters from multiple nodes; means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability; means for automatically generating design specifications based on the analysis results; means for acquiring comments and additional information from system users and reflecting them in the design specifications; means for performing a final check of the generated design specifications and converting them into an output format for provision; means for starting data collection and generation of design specifications through a user interface; and means for generating design specifications based on a template. This automates the entire process of collecting setting information from multiple nodes, comparing it with standard documents, automatically generating design specifications, incorporating user feedback, and finally outputting the document, enabling efficient creation of high-quality design specifications.

[0113] A "server" is a computer system that provides services and data processing to multiple clients over a network.

[0114] A "node" is an individual device or equipment connected to a network, including routers, switches, base stations, etc.

[0115] "Configuration information" refers to parameters and setting values ​​required to determine the operation and functions of a node.

[0116] A "parameter" is a numerical value or setting used to control the operation of a system or node.

[0117] "Standards documents" are documents that provide industry standards or guidelines, such as 3GPP and RFCs.

[0118] "Analysis" is the process of evaluating collected data against normative references and identifying matches and inconsistencies.

[0119] "Conformity" is an index that indicates the degree to which the collected setting information and parameters match the standard data.

[0120] A "design specification" is a document that details the design requirements and specifications of a system or equipment, and is used when introducing or building it.

[0121] "Automatic generation" is the process of generating specific documents or data programmatically without human intervention.

[0122] "System users" are the personnel or end users who operate the system, collect configuration information, add comments, and review and approve design specifications.

[0123] "Comments" are opinions, suggestions, and small corrections that system users add to the design specifications.

[0124] "Additional information" refers to new data or requirements to be included in the design specification.

[0125] "Final check" is the process of checking all the contents of the generated design specifications and correcting any errors or incomplete parts.

[0126] "Output format" refers to the file format, such as PDF or Word, used to save and display the generated design specifications.

[0127] A "user interface" is an interface through which a system user operates the system via a GUI, inputting configuration information and instructing the generation of design specifications.

[0128] A "template" is a predefined format that defines the format and structure of a design specification based on standard documents or guidelines.

[0129] This invention is a system that automatically collects setting information and parameters from multiple nodes and automatically generates design specifications based on the collected information. How this system can be implemented will be described below.

[0130] Server Features

[0131] Data collection

[0132] The server first obtains a list of nodes to collect from the database. Based on that list, it connects to each node and collects configuration information and parameters. Collection methods include SNMP (Simple Network Management Protocol), API calls, and SSH (Secure Shell). For example, the server connects via SNMP to a node with an IP address of 192.168.1.1 to collect configuration information. The collected data is saved in a temporary database.

[0133] Data analysis and comparison with standard data

[0134] The server analyzes the collected data based on standards such as 3GPP and RFCs. During the analysis, the collected data is normalized and compared with the standards to identify matching and non-matching parts. For example, it checks whether the node's interface settings comply with the 3GPP standard.

[0135] Automatic generation of design specifications

[0136] The server automatically generates design specifications based on the analysis results. This is done by loading a document template that conforms to the standard and embedding the collected data in the appropriate locations. For example, the server embeds the previously collected interface configuration information in the "Network Settings" section of the template.

[0137] Providing a customization interface

[0138] The server provides an interface where users can enter comments and additional information. The server acquires the user's comments and additional information and readjusts the design specifications based on them. For example, if a user enters a comment such as "I would like you to change a specific setting on the base station," the server will reflect that comment and modify the specifications.

[0139] Final checks and output

[0140] The server performs a final check, makes any necessary corrections, and then outputs the design specification in PDF or Word format and provides it to the user. For example, the server may find in the final check that "the section headings do not match the standards," correct them, and then output them in PDF format.

[0141] Device Features

[0142] Navigating the User Interface

[0143] The user starts the automatic generation process of the design specification using the terminal's GUI (Graphical User Interface). The user inputs node information and collection parameters into the terminal and instructs the server to collect data. For example, the user inputs "Collect configuration information for a new base station" into the GUI and presses the send button, which sends this instruction from the terminal to the server.

[0144] Customized Input

[0145] After the automatic generation of the design specification is completed, the user accesses a screen on the terminal to input comments and additional information. Here, the user inputs specific requirements and conditions, which are then sent to the server. For example, the user inputs specific requirements for configuration information and sends them from the terminal to the server.

[0146] User Roles

[0147] System Check

[0148] The user reviews the design specifications provided by the server and checks whether there are any problems with the content. If necessary, the user can add comments or request corrections. For example, if a user who has checked the design specifications feels that a certain setting is inappropriate, they can input that comment.

[0149] Final Approval

[0150] The user performs a final check and, if approved, the design specifications are shared with the project team and other stakeholders, and the installation and construction of the equipment begins. For example, if the user performs a final check and determines that there are no problems with the contents, they press the approval button to approve the design specifications.

[0151] Specific examples

[0152] We will explain the case where a telecommunications carrier introduces a new base station (node) and automatically generates its design specifications as a concrete example.

[0153] 1. Collection preparation

[0154] The server retrieves a list of existing base stations from the database. For example, the list contains the IP addresses 192.168.1.1 and 192.168.1.2.

[0155] 2. Data Collection

[0156] The server connects to each base station based on the list via SNMP and collects the configuration information. The collected information is stored in a temporary database. For example, the interface configuration is collected.

[0157] 3. Data Analysis

[0158] The server analyzes the collected information based on the 3GPP standard documents and checks whether the settings comply with the standard, for example, whether the interface settings are consistent with the standard.

[0159] 4. Generate design specifications

[0160] The server automatically generates the design specification by embedding it in a template based on the analysis results. For example, it adds collected information to the "Network Settings" section.

[0161] 5. Customizable interface provided

[0162] The user can input comments and additional information into the generated design specification through the GUI of the terminal. For example, the user can input a comment saying, "There are special requirements."

[0163] 6. Final Check

[0164] The server then modifies the design specifications based on the user's comments and performs a final check, for example, readjusting the configuration information based on the user's comments.

[0165] 7. Output of design specifications

[0166] The server outputs the design specification in PDF format and provides it to the user, who then performs a final check and approves it.

[0167] 8. Project Start

[0168] The approved design specifications will be shared with the project team and the installation and construction of the new base station will commence.

[0169] Prompt Sentence Examples

[0170] "Please explain how a telecommunications company automatically generates design specifications for new base stations. Please provide a detailed description of the process, including the specific steps for collecting data, analyzing the data, filling templates, incorporating user input, and finally outputting it."

[0171] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0172] Step 1:

[0173] Getting a list of nodes

[0174] The server retrieves a list of nodes to collect from a database. This list contains the IP addresses and identification information of each node in the network. The input is the list of nodes to retrieve from the database, and the output is a list of nodes. For example, the list might contain IP addresses 192.168.1.1 and 192.168.1.2.

[0175] Step 2:

[0176] Connecting to a node and collecting data

[0177] Based on the list of nodes obtained, the server connects to each node to collect configuration information and parameters. Connection methods include SNMP, API calls, and SSH. The input is the node list, and the output is the configuration information obtained from the nodes. For example, the server connects to the node at 192.168.1.1 via SNMP and collects configuration information. The collected data is stored in a temporary database.

[0178] Step 3:

[0179] Data normalization

[0180] The server normalizes the collected configuration information and parameters. During the normalization process, the data format is unified and unnecessary data is deleted. The input is the collected configuration information, and the output is normalized data. For example, the interface settings in the data are converted to a standard format.

[0181] Step 4:

[0182] Comparison with standard materials

[0183] The server compares the normalized data with standards such as 3GPP and RFCs to identify matches and mismatches. The input is the normalized data, and the output is information about matches and mismatches with the standards. For example, it checks whether an interface configuration is in accordance with the 3GPP standard.

[0184] Step 5:

[0185] Loading design specification templates

[0186] The server loads a pre-prepared document template. The template contains standard formats and sections. The input is a document template, and the output is the prepared template. For example, a design specification format that conforms to a standard document is loaded.

[0187] Step 6:

[0188] Embedding analysis results into data

[0189] The server embeds the analysis results in the appropriate position in the template to generate a design specification. The input is the analysis results and the document template, and the output is the design specification. For example, the analysis results are added to the "Network Settings" section of the template.

[0190] Step 7:

[0191] User Interface Display

[0192] The server displays an interface that allows the user to enter comments and additional information. The input is the user's comments and additional information, and the output is an updated design specification. For example, the user enters a comment such as "I would like you to change a specific setting on the base station."

[0193] Step 8:

[0194] Reflecting user comments

[0195] The server readjusts the design specification by reflecting comments and additional information obtained from the user. The input is the user's comments and additional information, and the output is an updated design specification. For example, the server modifies the configuration information based on the user's comments.

[0196] Step 9:

[0197] Final Check

[0198] The server performs a final check of the entire design specification and makes any necessary corrections. The input is the design specification, and the output is the final design specification. For example, it checks and corrects that "the section headings do not match the standards."

[0199] Step 10:

[0200] Design specification output

[0201] The server outputs the design specification after the final check in PDF or Word format and provides it to the user. The input is the design specification after the final check, and the output is a document in PDF or Word format. For example, the design specification is output in PDF format.

[0202] (Application example 1)

[0203] 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."

[0204] Modern production facilities are required to collect configuration information and parameters from multiple nodes and automatically generate design specifications and technical documents based on that information. However, previous methods have made it difficult to accurately evaluate and analyze the suitability of collected data and add comments and corrections in real time. Furthermore, the lack of efficient data collection and verification using smart devices has hindered work efficiency. This has led to issues such as complex production line management and maintenance work, and an increased risk of errors.

[0205] 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.

[0206] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, and means for collecting operational setting information and maintenance information for factory equipment and adding real-time comments to the automatically generated technical documents. This makes it possible to collect, check, and modify operational setting information and maintenance information for factory equipment in real time via smart devices.

[0207] A "node" is a piece of electronic equipment that transmits, receives, or processes data within a network.

[0208] "Setting information" refers to parameters and configuration information required to control the operation and functions of an electronic device.

[0209] A "parameter" is a variable used to determine a particular characteristic or behavior of a system or device.

[0210] A "standard document" is a document that sets out generally accepted guidelines or protocols in a particular field.

[0211] "Analysis" is the process of examining data in detail to understand its meaning and structure.

[0212] "Conformance" is the state of conformance to certain criteria or conditions.

[0213] A "design specification" is a document that provides detailed descriptions and instructions for the design of a system.

[0214] "Technical documents" are documents that provide specialized knowledge and information.

[0215] "Comments" are annotations that add opinions or explanations to a document.

[0216] "Additional information" is new data or knowledge provided to supplement existing information.

[0217] A "smart device" is an electronic device with advanced computing power and internet connectivity.

[0218] "Real-time" means that data is collected and processed immediately, without delay.

[0219] This invention is a system that collects operational setting information and maintenance information for factory equipment and automatically generates technical documents based on that information. The functions of the system, which consists of three entities: users, terminals, and servers, are explained below.

[0220] Server Features

[0221] Data collection

[0222] The server first obtains a list of nodes from which data is to be collected from the database. It then connects to each node (in this case, factory equipment) according to that list and collects configuration information and parameters. Collection methods include REST API calls, SNMP, and SSH. The collected data is then stored in a temporary database.

[0223] Data analysis and comparison with standard data

[0224] The collected data is analyzed based on standard documents (e.g., 3GPP, RFC). During the analysis, the collected data is normalized and compared with the standard documents to identify matches and inconsistencies.

[0225] Automatic generation of technical documents

[0226] The server automatically generates technical documents based on the analysis results. First, it reads a document template that conforms to the standard documents and embeds the collected data in the appropriate locations of the template. In this way, the technical documents are generated.

[0227] Providing a customization interface

[0228] The server provides an interface where users can enter comments and additional information, and when the comments and additional information are obtained from the users, the technical materials are adjusted accordingly.

[0229] Final checks and output

[0230] Finally, the server checks the entire generated technical document and makes any necessary corrections. After the check is complete, the technical document is output in a format such as PDF or Word and provided to the user.

[0231] Device Features

[0232] Navigating the User Interface

[0233] The user starts the process of automatically generating technical documentation through the GUI on the terminal. First, they input the necessary node information and collection parameters (operation setting information and maintenance information) into the terminal, and then instruct the server to collect data.

[0234] Customized Input

[0235] After the automatic generation of technical documents is completed, the user can access a screen on their terminal to input comments and additional information, where they can enter specific requirements and conditions and send them to the server.

[0236] User Roles

[0237] System Check

[0238] The user reviews the technical documents provided by the server, checks whether there are any problems with the contents, and makes comments or requests for corrections if necessary.

[0239] Final Approval

[0240] The user reviews the final technical documentation and, if satisfied with the content, approves it. The approved technical documentation is shared with the work team and other relevant parties, and operation and maintenance of the equipment begins.

[0241] Specific examples

[0242] As a concrete example, let's assume that a manufacturing plant introduces a new robot (node) and automatically generates its technical documentation. The server collects configuration information from existing equipment in the manufacturing plant. The collected data is analyzed based on standard documentation, and technical documentation is automatically generated based on the results. The user enters comments from their terminal regarding special requirements or areas that require adjustment, and the server reflects these comments and modifies the documentation. After a final check, the technical documentation is output in PDF format and provided to the user. This process makes the task of creating technical documentation more efficient and reduces the risk of accidents due to work errors.

[0243] Usage example

[0244] For example, a manufacturing plant might use a smartphone to collect operational settings and maintenance data for a newly installed robot. When a worker connects to the robot using a smartphone app, the server collects operational parameters via an API. The collected data is analyzed based on standard documents, and the necessary technical documents are automatically generated. The worker can then view the documents in real time through smart glasses and add any necessary comments or corrections.

[0245] Prompt Sentence Examples

[0246] "Please develop an application that collects the setting information and operating parameters of factory equipment and automatically generates technical documents based on the analysis results. The documents should be based on standard documents and contain accurate information. It should also have a function that allows workers to check them in real time via smart devices and add comments or correction requests."

[0247] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0248] Step 1: Data collection instructions

[0249] The user starts the automatic generation process of technical documents through a GUI on the terminal. The user inputs the necessary node information and collection parameters (e.g., robot operation settings and maintenance information) into the terminal and sends a collection instruction to the server. The input data includes a list of nodes to be collected and the collection parameters.

[0250] Step 2: Data collection

[0251] The server connects to each node based on the node list sent from the terminal. Specifically, it collects configuration information and parameters using methods such as REST API calls, SNMP, and SSH. The collected data is saved in a temporary database. The input is the node list and collected parameters, and the output is the collected configuration information and parameters.

[0252] Step 3: Data analysis and normalization

[0253] The server analyzes the data stored in the temporary database, normalizes the collected data based on standard documents (e.g., 3GPP, RFC), and evaluates the conformance of the collected data. During the normalization process, the input data is unified into a specified format. The input is the configuration information and parameters in the temporary database, and the output is the normalized data and conformance evaluation results.

[0254] Step 4: Automatic generation of technical documentation

[0255] The server automatically generates technical documents based on the analysis results. It loads a pre-defined document template and embeds the analyzed data in the appropriate location in the template. An initial version of the generated technical documents is created. The input is the normalized data and conformance assessment results, and the output is the initial version of the technical documents.

[0256] Step 5: Get user comments

[0257] Through the terminal, the user reviews the initial version of the technical document. If necessary, they enter comments and additional information, which is then sent to the server. This information is used to update the technical document. The input is the user's comments and additional information, and the output is the updated technical document.

[0258] Step 6: Final check of technical documentation

[0259] The server readjusts the technical documentation based on comments and additional information provided by the user. It then performs a final check of the entire technical documentation and makes any necessary corrections. The input is comments and additional information from the user, and the output is the final version of the technical documentation.

[0260] Step 7: Output technical documents

[0261] Finally, the server converts the final version of the technical document into the specified format, such as PDF or Word, and sends it to the terminal. The user can then view the technical document on the terminal and take any necessary actions. The input is the final version of the technical document, and the output is the technical document converted into the specified format.

[0262] 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.

[0263] This invention combines a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on them with an emotion engine that recognizes user emotions.The functions of this system, which consists of four entities: the user, the terminal, the server, and the emotion engine, are described in detail below.

[0264] Server Features

[0265] Data collection

[0266] The server retrieves a list of target nodes from the database and connects to each node based on that list. Connection methods include SNMP, API calls, and SSH. The configuration information and parameters retrieved from the nodes are saved in a temporary database.

[0267] Data analysis and comparison with standard data

[0268] The collected data is analyzed based on standards (e.g., 3GPP, RFC). The data is normalized and compared to the standards to assess conformance. Non-conformances are identified, and necessary corrections are made clear.

[0269] Automatic generation of design specifications

[0270] The server automatically generates a design specification template based on the analysis results by loading the collected data into the appropriate locations within the template. This template conforms to standard documents, with various items neatly arranged.

[0271] Emotion engine collaboration

[0272] The server recognizes the user's emotions using an emotion engine when receiving comments or additional information from the user. The recognized emotion data is fed back into the design specification generation process, and adjustments are made based on the specific emotion.

[0273] Providing a customization interface

[0274] The server provides an interface where users can enter comments and additional information. The data entered through this interface is analyzed through the emotion engine and reflected in the design specifications.

[0275] Final checks and output

[0276] The generated design specifications undergo a final check, with adjustments made to the layout and format, corrections of errors, etc. The final design specifications are output in PDF or Word format and provided to the user.

[0277] Device Features

[0278] Navigating the User Interface

[0279] The user starts the process of automatically generating design specifications using the GUI on the terminal. They input the target node information and collection parameters into the terminal and instruct the server to collect data.

[0280] Enter customization comments

[0281] After the automatic generation of the design specification is completed, the user operates the interface to input comments and additional information. The information entered by the user is analyzed by the emotion engine and processed on the server.

[0282] Emotion Engine Functions

[0283] emotion recognition

[0284] The emotion engine analyzes comments and additional information entered by users and recognizes their emotions. This recognition is performed using natural language processing technology. For example, it analyzes the user's sense of urgency from a comment such as "I'm in a hurry."

[0285] Feedback and Adjustments

[0286] The emotion engine feeds back the recognized emotion, and the server adjusts the content of the design specification. For example, if the user expresses dissatisfaction, it can provide additional explanation.

[0287] User Roles

[0288] System Check

[0289] The user checks the design specifications provided by the server and carefully examines the content to ensure there are no problems. If there are any deficiencies or errors, the user can enter comments or correction requests again.

[0290] Final Approval

[0291] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[0292] Specific examples

[0293] As a concrete example, consider a scenario in which a company introduces a new IT infrastructure (node). In this case, the server collects configuration information from existing systems and analyzes it in accordance with 3GPP and RFC standards. Once the design specifications are automatically generated, the user enters comments and additional information from their terminal. The emotion engine analyzes the user's input and recognizes their emotions. For example, if the user enters "needed immediately," the emotion engine senses the sense of urgency and adjusts the priority of the design specifications. Finally, the design specifications are output in PDF format and provided to the relevant parties. This process improves the efficiency of design work and enables flexible responses to user emotions.

[0294] The processing flow will be explained below.

[0295] Server Processing Steps

[0296] Step 1: Get the node list

[0297] The server gets a list of nodes to connect to from a database, which includes IP addresses, authentication information, etc.

[0298] Step 2: Connect to the node

[0299] The server connects to each node in turn based on the node list, using methods such as SNMP, API calls, and SSH.

[0300] Step 3: Data collection

[0301] The server retrieves configuration information and parameters from the connected nodes, including the node's operating status, settings, sensor data, etc. This collected data is temporarily stored in a database.

[0302] Step 4: Loading the standard materials

[0303] The server loads standard documents such as 3GPP and RFCs and prepares them for comparison with the collected data, thereby clarifying the reference documents and guidelines.

[0304] Step 5: Data Preprocessing

[0305] The server preprocesses the collected data, normalizing it and imputing missing values. Preprocessing ensures data integrity and makes analysis easier.

[0306] Step 6: Data analysis and comparison with standard reference materials

[0307] The server then compares the pre-processed data against the standard, evaluating how well the data conforms to the standard and identifying any areas where it does not conform.

[0308] Step 7: Load the design specification template

[0309] The server loads a standard-compliant design specification template, which includes basic items and formats.

[0310] Step 8: Data Embedding

[0311] Based on the analysis results, the server embeds the collected data in the appropriate locations of the design specification template, thereby forming the basis of the design specification.

[0312] Step 9: Providing a Comment Interface

[0313] The server provides an interface for users to input comments and additional information, adjusts the design specifications according to the user's input, and analyzes the user's emotions through an emotion engine and provides feedback based on the results.

[0314] Step 10: Emotion Recognition

[0315] The server analyzes the user's input through an emotion engine to recognize the user's emotions, for example, detecting a sense of urgency in the case of an urgent request.

[0316] Step 11: Refining the design specifications

[0317] The server readjusts the design specifications based on feedback from the emotion engine, adding necessary explanations and alerts to reflect the user's emotional data.

[0318] Step 12: Final checks and adjustments

[0319] The server performs a final check of the generated design specifications, adjusting the layout and format, correcting errors, and so on.

[0320] Step 13: Output design specifications

[0321] The server outputs the final design specifications in PDF or Word format and provides them to the user, who can then share them with the project team and other stakeholders.

[0322] Terminal processing steps

[0323] Step 1: Launch the user interface

[0324] The user starts the GUI on the terminal and accesses the screen for automatically generating design specifications.

[0325] Step 2: Enter node information

[0326] The user inputs information about the target node and collection parameters into the terminal, including the node's IP address, authentication information, and collection items.

[0327] Step 3: Data collection instructions

[0328] The user issues an instruction to the server to collect the setting information and parameters of the specified node. This instruction is sent to the server, and data collection begins.

[0329] Step 4: Check the retrieved data

[0330] The user can check some of the collected data to see if specific data has been acquired. If there is a problem, the user can issue a collection command to the server again.

[0331] Step 5: Enter customization comments

[0332] After the automatic generation of the design specification is complete, the user operates an interface to enter comments and additional information, including modification requests based on specific conditions or requirements.

[0333] Step 6: Submit your comment

[0334] User comments and correction requests are sent from the device to the server, which receives this information and adjusts the design specifications. The emotion engine analyzes the user's emotions.

[0335] Emotion Engine Processing Steps

[0336] Step 1: Get user comments

[0337] The emotion engine receives user comments and additional information from the server.

[0338] Step 2: Sentiment Analysis

[0339] The emotion engine uses natural language processing technology to analyze user comments and recognize their emotions, for example, detecting a sense of urgency from a comment like "I'm in a hurry."

[0340] Step 3: Feedback on results

[0341] The recognized emotion data is fed back to the server, and this data is reflected in adjustments to the design specifications.

[0342] User processing steps

[0343] Step 1: Review the design specifications

[0344] The user checks the design specifications provided by the server on their terminal, carefully examining the content to ensure there are no problems.

[0345] Step 2: Request additional revisions

[0346] If the user finds any deficiencies or errors in the design specifications, they can enter comments or correction requests and send them to the server, which then receives them and readjusts the specifications.

[0347] Step 3: Final Approval

[0348] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[0349] These are the specific processing steps for the server, terminal, user, and emotion engine. This process makes the creation of design specifications more efficient and enables flexible designs that respond to user emotions.

[0350] Example 2

[0351] 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."

[0352] In today's complex network systems, it is necessary to collect configuration information and parameters from numerous nodes and, based on this information, create design specifications that conform to standard documents. However, evaluating the conformance of collected data and automatically generating design specifications requires a great deal of time and effort, and there are also increasing cases where adjustments based on user emotions are required. Conventional systems have difficulty achieving these processes efficiently and in a user-friendly manner, and systems that include emotion recognition and feedback have particular limitations. Therefore, there is a need for a multifunctional and efficient system that can collect data, analyze it, generate design specifications, and recognize emotions.

[0353] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0354] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, and means for recognizing the emotions of system users and feeding back the emotion data to the design specification creation process. This makes it possible to consistently and efficiently perform the process from data collection to the generation of design specifications, and also realize flexible responses to user emotions.

[0355] A "node" is an independent device or computer system that exists on a communication network.

[0356] "Setting information" refers to various setting parameters and configuration data that define the operation of a node.

[0357] A "parameter" is a data value that indicates the operating conditions or operating state of a system or node.

[0358] A "standard document" is a document that represents a generally accepted technical code or standard.

[0359] "Conformity" refers to the degree to which collected data corresponds to standard data.

[0360] A "design specification" is a document that describes in detail the design of a system or node.

[0361] A "system user" is a user who operates the system, inputs data, and checks results.

[0362] "Emotion" refers to the psychological state and mood of the system user.

[0363] "Comments" are specific opinions or suggestions provided by system users regarding the system.

[0364] "Final check" is the process of finally inspecting the content and format of the generated design specification.

[0365] "Output format" refers to the type of document format (e.g., PDF or Word) in which the design specification is provided.

[0366] "Emotion recognition" is a technology that analyzes and understands the psychological state of a system user based on their input.

[0367] "Feedback" refers to the reuse of analysis results and evaluation information within the system to adjust and improve processes.

[0368] This invention is a system that automatically collects configuration information and parameters from multiple nodes and generates design specifications based on them. This system also includes a function to recognize and provide feedback to users' emotions. Below, we will explain in detail how the invention is implemented by the server, terminal, and user.

[0369] Server processing

[0370] Data collection

[0371] The server retrieves a list of nodes to collect from an SQL database. This is done using a standard SQL query and stores the node list in memory. It then connects to each node based on the list and retrieves configuration information and parameters. This connection method can be SNMP (Simple Network Management Protocol), API calls, or SSH (Secure Shell Protocol). The retrieved data is temporarily stored in a database such as Redis.

[0372] Data analysis and comparison with standard data

[0373] The server analyzes the collected data based on standard documents such as 3GPP and RFC. It uses Python regular expressions (re library) for data normalization. Based on the analysis results, it evaluates conformance and identifies non-conforming parts.

[0374] Automatic generation of design specifications

[0375] The server reads the design specification template (Markdown or LaTeX format) based on the analysis results. It uses Jinja2 as the template engine and automatically generates the design specification by embedding configuration information and parameters in the appropriate places.

[0376] Emotion engine collaboration

[0377] When collecting comments and additional information from users, the server uses an emotion engine (such as the Google Cloud Natural Language API) to recognize the user's emotions. The recognized emotion data is fed back into the design specification creation process, and appropriate adjustments are made.

[0378] Providing a customization interface

[0379] The server provides an electronic form interface using React and Vue.js. Comments and additional information entered by users are analyzed in real time by the emotion engine and reflected in the design specifications.

[0380] Final checks and output

[0381] The server performs a final check of the generated design specification, correcting the layout and formatting, and correcting any errors. The generated design specification is finally converted into PDF or Word format and provided to the user. For example, PDF conversion is performed using LaTeX or Pandoc.

[0382] Processing by the terminal

[0383] Navigating the User Interface

[0384] The user starts the automatic generation process of the design specification using a dedicated GUI on the terminal (e.g., an Electron app), inputs the target node information and collection parameters, and issues a command to the server to collect data.

[0385] Enter customization comments

[0386] After the automatic generation of the design specification is completed, the user can enter comments and additional information using the provided web interface. The user's input data is sent to the server and analyzed by the emotion engine.

[0387] User Roles

[0388] System Check

[0389] The user checks the design specifications provided by the server and carefully examines the contents to ensure there are no problems. If there are any deficiencies or errors, the user can enter comments or correction requests again.

[0390] Final Approval

[0391] The user reviews the final design specifications and, if satisfied, approves them. Once approved, the design specifications are shared with the project team and other stakeholders, and installation and construction can begin.

[0392] Specific examples

[0393] Consider an example where a company is introducing new IT infrastructure. In this case, the server collects configuration information from existing systems and analyzes it based on 3GPP and RFC standards. Once the design specifications are automatically generated, the user can use a terminal to input comments and additional information. The emotion engine analyzes the user's input and recognizes their emotions. For example, if the user enters "immediately needed," the emotion engine will sense the sense of urgency and adjust the priority of the design specifications. The design specifications generated in this way are output in PDF format and provided to the relevant parties.

[0394] Example prompts to input to the generative AI model

[0395] If the user enters "I need it now," the emotion engine will sense the urgency and adjust the priority of the design specification. Finally, the design specification is output in PDF format and provided to the stakeholders. This process improves the efficiency of design work and allows for flexible responses based on the user's emotions.

[0396] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0397] Step 1:

[0398] Starting Data Collection

[0399] The server retrieves the list of nodes to be collected from the SQL database.

[0400] Input: A SQL database query stored on the server.

[0401] Output: A list of nodes.

[0402] Specific operation: The server executes an SQL query to obtain information about the target node and stores it in memory. It executes an SQL statement such as SELECT FROM nodes.

[0403] Step 2:

[0404] Connecting to a node

[0405] The server connects to each node based on the obtained node list.

[0406] Input: Node list, connection method (e.g. SNMP, API, SSH).

[0407] Output: Configuration information and parameters obtained from each node.

[0408] Specific operation: The server connects to each node using Python's paramiko and requests libraries and collects configuration information. For example, use paramiko.SSHClient().connect(hostname, username, password).

[0409] Step 3:

[0410] Temporary data storage

[0411] The server stores the configuration information and parameters collected from the connected nodes in a database for temporary storage.

[0412] Input: Configuration information and parameters obtained from each node.

[0413] Output: Data stored in a temporary location.

[0414] What happens: The server stores the data in a temporary database like Redis. Use redis.set(node_id, data).

[0415] Step 4:

[0416] Data analysis and comparison with standard data

[0417] The server analyzes the collected data based on standard documents such as 3GPP and RFC.

[0418] Input: Data stored in temporary database, standard materials.

[0419] Output: Normalized data and fit assessment results.

[0420] What happens: The server uses Python's re library to normalize the data and match it to a standard reference, e.g., using re.match(pattern, data) to evaluate the relevance.

[0421] Step 5:

[0422] Automatic generation of design specifications

[0423] Based on the analysis results, the server reads the design specification template and fills in the data.

[0424] Input: Normalized data, design specification template.

[0425] Output: Auto-generated design specification.

[0426] What happens: The server uses the Jinja2 template engine to embed the data into the template, for example, by using template.render(data=parsed_data).

[0427] Step 6:

[0428] Collecting user comments

[0429] The terminal allows the user to enter comments and additional information through a web interface.

[0430] Input: User comments and additional information.

[0431] Output: User comment data sent to the server.

[0432] Specific operation: The device displays the user interface (React application) and sends the information entered by the user to the server in real time, for example, using fetch(' / api / comments', {method: 'POST', body: JSON.stringify(comment)}).

[0433] Step 7:

[0434] Starting Emotion Recognition

[0435] The server analyzes the comments from users using an emotion engine and recognizes their emotions.

[0436] Input: User comment data.

[0437] Output: Emotion analysis results.

[0438] What happens: The server sends the comment to the Google Cloud Natural Language API and receives the analysis result. For example, use nlp.analyzeSentiment({document: {content: comment, type: 'PLAIN_TEXT'}}).

[0439] Step 8:

[0440] Emotional Data Feedback

[0441] The server feeds back the recognized emotion data to the design specification generation process.

[0442] Input: Sentiment analysis results.

[0443] Output: Adjusted design specifications.

[0444] Specific operation: The server uses emotion data to adjust the content and priority of the design specifications. For example, if the user indicates urgency, it raises the priority of the design specifications.

[0445] Step 9:

[0446] Final checks and output

[0447] The server performs a final check of the generated design specifications, correcting the layout and format and correcting any errors.

[0448] Input: Auto-generated design specification.

[0449] Output: A PDF or Word file of the design specification that has passed the final check.

[0450] Specific operation: The server uses Pandoc to convert the design specification to PDF or Word format and provide it to the user. For example, use pandoc input.md -o output.pdf.

[0451] This enables the system to efficiently and user-friendly data collection, analysis, design specification generation, and emotion recognition.

[0452] (Application example 2)

[0453] 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."

[0454] Conventional systems generate design specifications based on configuration information and parameters automatically collected from multiple nodes, but they are unable to reflect user sentiment, making it difficult to generate flexible design specifications that meet diverse user needs. Furthermore, content distribution services rely on simple recommendation algorithms, which do not adequately examine user sentiment, making it difficult to recommend optimal content. This leads to problems such as reduced user satisfaction.

[0455] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0456] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard materials and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, means for recognizing user emotions using an emotion engine and adjusting the design specifications based on the recognition results, and means for analyzing user emotions and generating an optimal recommendation plan in a content distribution service. This enables the generation of flexible design specifications that reflect user emotions, and further enables optimal content recommendations based on user emotions in the content distribution service.

[0457] A "node" is a general term for a terminal or device that can operate independently on a network and exchange information.

[0458] "Configuration information" is a general term for information and parameters required to control the operation of network devices and terminals.

[0459] A "parameter" is a variable or value that is set to control the behavior of a system or application.

[0460] "Standard documents" refer to technical documents, guidelines, and protocols that are recognized and referenced as standards within an industry.

[0461] The "emotion engine" is a system that applies natural language processing technology to analyze emotions from user input data and provide feedback on the results.

[0462] A "design specification" is a document that describes the design contents, components, operating conditions, etc. of a system or project.

[0463] "Analysis" refers to the process of examining collected data and information in detail and finding meaning.

[0464] "Comments" refers to opinions, impressions, additional information, etc. that users enter through the interface.

[0465] "Additional information" is supplementary information provided by the user in addition to basic parameters and setting information.

[0466] A "content distribution service" is a system that provides digital content such as music, videos, and articles via the Internet.

[0467] A "recommendation plan" is a plan that suggests optimal content based on the preferences and status of each individual user.

[0468] "Final check" is a procedure for checking the contents of the generated design specifications, correcting errors, and ensuring format consistency.

[0469] "Output format" refers to the manner in which generated data or documents are stored, displayed, or presented in a particular format.

[0470] As an embodiment of the present invention, a system will be described in which an emotion engine is combined with a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on the collected information.

[0471] System configuration

[0472] The system mainly consists of a server, a terminal, an emotion engine, and a user. The role of each component is described in detail below.

[0473] server

[0474] The server is responsible for automatically collecting configuration information and parameters from multiple nodes. The collected data is stored in a temporary database. This data is analyzed based on standard documents (e.g., 3GPP and RFCs), and normalization processing is performed to evaluate its conformance. Design specifications are automatically generated based on the evaluation results, and an interface is also provided for reflecting user comments and additional information. By using an emotion engine to recognize user emotions and reflecting the results in the design specifications, it is possible to generate documents that are more flexible and tailored to user needs.

[0475] Terminal

[0476] The terminal provides a user interface through which users can input information and provide feedback. Collection parameters can be entered through the terminal's GUI, and data collection instructions can be sent to the server. After generating the design specifications, users can enter comments and additional information through the terminal, which is then analyzed by the emotion engine.

[0477] Emotion Engine

[0478] The emotion engine analyzes comments and additional information entered by the user on the device and recognizes emotions. The results are fed back to the server, which then adjusts the content of the design specifications. For example, if the user enters "I'm in a hurry," the emotion engine will detect a sense of urgency and adjust the content to prioritize the speed of creating the design specifications.

[0479] User

[0480] Users operate the system through their terminals to provide comments and additional information, and also review the generated design specifications and give their final approval. User feedback is properly analyzed through the emotion engine, improving the completeness of the design specifications.

[0481] Hardware and software used

[0482] Server: Central server for data collection, analysis, and automatic generation of design specifications

[0483] Terminal: A device that provides a user interface (e.g., a smartphone or tablet).

[0484] Emotion engine: Natural language processing engines such as IBM Watson Natural Language Understanding and Google Cloud NLP

[0485] Database: Relational database such as PostgreSQL

[0486] Specific examples

[0487] For example, in a content distribution service, a user may provide feedback on music content by commenting, "I want to relax." The emotion engine analyzes this comment and recognizes the user's desire to relax. Based on the results, the server recommends optimal content (e.g., relaxing music or videos). This process makes it possible to provide more personalized content to users.

[0488] Prompt Sentence Examples

[0489] "If a user enters 'I'm tired' or 'I want to relax' in the comment field, please provide an algorithm that will recommend content based on that. The input is the comment text and its sentiment classification data, and the output is a recommendation."

[0490] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0491] Step 1:

[0492] The server automatically collects configuration information and parameters from multiple nodes using protocols such as API calls, SNMP, and SSH. The data collected from each node is stored in a temporary database. The input is the node's configuration information and parameters, and the output is the raw data stored in the temporary database.

[0493] Step 2:

[0494] The server analyzes the configuration information and parameters stored in the temporary database based on standard documents (e.g., 3GPP or RFC). This analysis process normalizes the data and checks it against the standard documents. The input is the raw data stored in the temporary database, and the output is the normalized data and the conformance evaluation result.

[0495] Step 3:

[0496] The server reads the design specification template based on the analysis results and automatically generates the design specification by embedding the collected data in the appropriate locations within the template. The input is the normalized data and evaluation results, and the output is the automatically generated design specification.

[0497] Step 4:

[0498] The user uses a terminal to check the design specifications and input comments and additional information. This is done through the terminal's GUI interface. The input is the design specifications and the user's comments and additional information, and the output is the user's feedback.

[0499] Step 5:

[0500] The emotion engine analyzes user comments and additional information sent from the device and recognizes emotions. This analysis uses natural language processing technology. The input is the user's comments and additional information, and the output is the emotion recognition results.

[0501] Step 6:

[0502] The server adjusts the design specifications based on feedback from the emotion engine. For example, if the user feels "hurried," it will respond by raising the priority. The input is the emotion recognition results and the design specifications, and the output is the adjusted design specifications.

[0503] Step 7:

[0504] The server operates in the same way in content distribution services, generating an optimal recommendation plan based on comments entered by users. The input is the user's comments and emotion recognition results, and the output is a content recommendation plan.

[0505] Step 8:

[0506] The server performs a final check and formatting, then outputs a design specification or content recommendation plan in a variety of formats, including PDF, Word, and a list of recommended content. The input is the adjusted data, and the output is the final design specification or list of recommended content.

[0507] The above is the relationship between the specific operations at each processing step and the input and output based on the data processing and calculation.

[0508] 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.

[0509] 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.

[0510] 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.

[0511] [Second embodiment]

[0512] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0513] 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.

[0514] 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).

[0515] 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.

[0516] 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.

[0517] 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).

[0518] 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.

[0519] 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.

[0520] 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.

[0521] 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.

[0522] 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.

[0523] 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."

[0524] This invention is a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on that information. The functions of the system, which consists of three entities: users, terminals, and servers, are explained below.

[0525] Server Features

[0526] Data collection

[0527] The server first obtains a list of nodes to collect from the database. According to that list, it connects to each node and collects configuration information and parameters. Collection methods include SNMP, API calls, and SSH. The collected data is stored in a temporary database.

[0528] Data analysis and comparison with standard data

[0529] The collected data is analyzed based on standard documents (e.g., 3GPP, RFC). During the analysis, the collected data is normalized and compared with the standard documents to identify matches and inconsistencies.

[0530] Automatic generation of design specifications

[0531] The server automatically generates design specifications based on the analysis results. First, it reads a document template that conforms to the standard materials and embeds the collected data in the appropriate locations of the template. In this way, the design specifications are generated.

[0532] Providing a customization interface

[0533] The server provides an interface where the user can input comments and additional information, and when the comments and additional information are obtained from the user, the design specification is adjusted accordingly.

[0534] Final checks and output

[0535] Finally, the server checks the entire generated design specification and makes any necessary corrections. After the check is complete, the design specification is output in a format such as PDF or Word and provided to the user.

[0536] Device Features

[0537] Navigating the User Interface

[0538] The user starts the process of automatically generating design specifications through the GUI on the terminal. First, they input the necessary node information and collection parameters into the terminal and instruct the server to collect data.

[0539] Customized Input

[0540] After the automatic generation of the design specification is completed, the user accesses a screen on their terminal to input comments and additional information, where they can enter specific requirements and conditions and send them to the server.

[0541] User Roles

[0542] System Check

[0543] The user reviews the design specifications provided by the server, checks whether there are any problems with the content, and, if necessary, adds comments or requests corrections.

[0544] Final Approval

[0545] The user reviews the final specifications and, if satisfied, approves them. The approved design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[0546] Specific examples

[0547] As a concrete example, let's assume that a telecommunications carrier introduces a new base station (node) and automatically generates its design specifications. In this case, the server collects configuration information from existing base stations in the carrier's network. The collected data is analyzed based on 3GPP standard documents, and the design specifications are automatically generated based on the results. The user enters comments from their device regarding special requirements for the base station and any areas that need adjustment, and the server reflects these comments and modifies the specifications. After a final check, the design specifications are output in PDF format and provided to the user. This entire process streamlines design work and reduces the risk of accidents caused by design errors.

[0548] The processing flow will be explained below.

[0549] Server Processing Steps

[0550] Step 1: Get the node list

[0551] The server retrieves a list of nodes to connect to from a database, which contains the information needed to connect to the nodes, such as IP addresses and authentication information.

[0552] Step 2: Connect to the node

[0553] The server connects to each node in turn based on the node list, using methods such as SNMP, API calls, and SSH.

[0554] Step 3: Data collection

[0555] The server retrieves configuration information and parameters from the connected nodes, including the node's operating status, settings, sensor data, etc. This collected data is temporarily stored in a database.

[0556] Step 4: Loading the standard materials

[0557] The server loads standard documents such as 3GPP and RFCs and prepares them for comparison with the collected data, thereby clarifying the reference documents and guidelines.

[0558] Step 5: Data Preprocessing

[0559] The server preprocesses the collected data, normalizing it and imputing missing values. Preprocessing ensures data integrity and makes analysis easier.

[0560] Step 6: Data analysis and comparison with standard reference materials

[0561] The server then compares the pre-processed data against the standard, evaluating how well the data conforms to the standard and identifying any areas where it does not conform.

[0562] Step 7: Load the design specification template

[0563] The server loads a standard-compliant design specification template, which includes basic items and formats.

[0564] Step 8: Data Embedding

[0565] Based on the analysis results, the server embeds the collected data in the appropriate locations of the design specification template, thereby forming the basis of the design specification.

[0566] Step 9: Providing a Comment Interface

[0567] The server provides an interface for the user to enter comments and additional information, and adjusts the design specification according to the user's input.

[0568] Step 10: Final checks and adjustments

[0569] The server performs a final check of the generated design specifications, adjusting the layout and format, correcting errors, and so on.

[0570] Step 11: Output design specifications

[0571] The server outputs the final design specifications in PDF or Word format and provides them to the user, who can then share them with the project team and other stakeholders.

[0572] Terminal processing steps

[0573] Step 1: Launch the user interface

[0574] The user starts the GUI on the terminal and accesses the screen for automatically generating design specifications.

[0575] Step 2: Enter node information

[0576] The user inputs information about the target node and collection parameters into the terminal, including the node's IP address, authentication information, and collection items.

[0577] Step 3: Data collection instructions

[0578] The user issues an instruction to the server to collect the setting information and parameters of the specified node. This instruction is sent to the server, and data collection begins.

[0579] Step 4: Check the retrieved data

[0580] The user can check some of the collected data to see if specific data has been acquired. If there is a problem, the user can issue a collection command to the server again.

[0581] Step 5: Enter customization comments

[0582] The user operates an interface to enter any comments or special requirements they wish to add to the design specification, including requests for modifications based on specific conditions or requirements.

[0583] Step 6: Submit your comment

[0584] User comments and correction requests are sent from the terminal to the server, which receives this information and adjusts the design specifications accordingly.

[0585] User processing steps

[0586] Step 1: Review the design specifications

[0587] The user checks the design specifications provided by the server on their terminal, carefully examining the content to ensure there are no problems.

[0588] Step 2: Request additional revisions

[0589] If the user finds any deficiencies or errors in the design specifications, they can enter comments or correction requests and send them to the server, which then receives them and readjusts the specifications.

[0590] Step 3: Final Approval

[0591] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[0592] These are the specific processing steps for the server, terminal, and user. This process makes the creation of design specifications more efficient and reduces the risk of system accidents caused by design errors.

[0593] Example 1

[0594] 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."

[0595] In modern network systems, collecting configuration information and parameters from multiple nodes and creating design specifications based on that information is extremely complex and time-consuming. Furthermore, accurately reflecting the analysis results of the collected data requires specialized knowledge, which increases the risk of errors and inconsistencies. Furthermore, incorporating user comments and additional information into design specifications is often done manually, which is inefficient. Therefore, there is a need for a method to automate these processes and efficiently create high-quality design specifications.

[0596] 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.

[0597] In this invention, the server includes: means for automatically collecting setting information and parameters from multiple nodes; means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability; means for automatically generating design specifications based on the analysis results; means for acquiring comments and additional information from system users and reflecting them in the design specifications; means for performing a final check of the generated design specifications and converting them into an output format for provision; means for starting data collection and generation of design specifications through a user interface; and means for generating design specifications based on a template. This automates the entire process of collecting setting information from multiple nodes, comparing it with standard documents, automatically generating design specifications, incorporating user feedback, and finally outputting the document, enabling efficient creation of high-quality design specifications.

[0598] A "server" is a computer system that provides services and data processing to multiple clients over a network.

[0599] A "node" is an individual device or equipment connected to a network, including routers, switches, base stations, etc.

[0600] "Configuration information" refers to parameters and setting values ​​required to determine the operation and functions of a node.

[0601] A "parameter" is a numerical value or setting used to control the operation of a system or node.

[0602] "Standards documents" are documents that provide industry standards or guidelines, such as 3GPP and RFCs.

[0603] "Analysis" is the process of evaluating collected data against normative references and identifying matches and inconsistencies.

[0604] "Conformity" is an index that indicates the degree to which the collected setting information and parameters match the standard data.

[0605] A "design specification" is a document that details the design requirements and specifications of a system or equipment, and is used when introducing or building it.

[0606] "Automatic generation" is the process of generating specific documents or data programmatically without human intervention.

[0607] "System users" are the personnel or end users who operate the system, collect configuration information, add comments, and review and approve design specifications.

[0608] "Comments" are opinions, suggestions, and small corrections that system users add to the design specifications.

[0609] "Additional information" refers to new data or requirements to be included in the design specification.

[0610] "Final check" is the process of checking all the contents of the generated design specifications and correcting any errors or incomplete parts.

[0611] "Output format" refers to the file format, such as PDF or Word, used to save and display the generated design specifications.

[0612] A "user interface" is an interface through which a system user operates the system via a GUI, inputting configuration information and instructing the generation of design specifications.

[0613] A "template" is a predefined format that defines the format and structure of a design specification based on standard documents or guidelines.

[0614] This invention is a system that automatically collects setting information and parameters from multiple nodes and automatically generates design specifications based on the collected information. How this system can be implemented will be described below.

[0615] Server Features

[0616] Data collection

[0617] The server first obtains a list of nodes to collect from the database. Based on that list, it connects to each node and collects configuration information and parameters. Collection methods include SNMP (Simple Network Management Protocol), API calls, and SSH (Secure Shell). For example, the server connects via SNMP to a node with an IP address of 192.168.1.1 to collect configuration information. The collected data is saved in a temporary database.

[0618] Data analysis and comparison with standard data

[0619] The server analyzes the collected data based on standards such as 3GPP and RFCs. During the analysis, the collected data is normalized and compared with the standards to identify matching and non-matching parts. For example, it checks whether the node's interface settings comply with the 3GPP standard.

[0620] Automatic generation of design specifications

[0621] The server automatically generates design specifications based on the analysis results. This is done by loading a document template that conforms to the standard and embedding the collected data in the appropriate locations. For example, the server embeds the previously collected interface configuration information in the "Network Settings" section of the template.

[0622] Providing a customization interface

[0623] The server provides an interface where users can enter comments and additional information. The server acquires the user's comments and additional information and readjusts the design specifications based on them. For example, if a user enters a comment such as "I would like you to change a specific setting on the base station," the server will reflect that comment and modify the specifications.

[0624] Final checks and output

[0625] The server performs a final check, makes any necessary corrections, and then outputs the design specification in PDF or Word format and provides it to the user. For example, the server may find in the final check that "the section headings do not match the standards," correct them, and then output them in PDF format.

[0626] Device Features

[0627] Navigating the User Interface

[0628] The user starts the automatic generation process of the design specification using the terminal's GUI (Graphical User Interface). The user inputs node information and collection parameters into the terminal and instructs the server to collect data. For example, the user inputs "Collect configuration information for a new base station" into the GUI and presses the send button, which sends this instruction from the terminal to the server.

[0629] Customized Input

[0630] After the automatic generation of the design specification is completed, the user accesses a screen on the terminal to input comments and additional information. Here, the user inputs specific requirements and conditions, which are then sent to the server. For example, the user inputs specific requirements for configuration information and sends them from the terminal to the server.

[0631] User Roles

[0632] System Check

[0633] The user reviews the design specifications provided by the server and checks whether there are any problems with the content. If necessary, the user can add comments or request corrections. For example, if a user who has checked the design specifications feels that a certain setting is inappropriate, they can input that comment.

[0634] Final Approval

[0635] The user performs a final check and, if approved, the design specifications are shared with the project team and other stakeholders, and the installation and construction of the equipment begins. For example, if the user performs a final check and determines that there are no problems with the contents, they press the approval button to approve the design specifications.

[0636] Specific examples

[0637] We will explain the case where a telecommunications carrier introduces a new base station (node) and automatically generates its design specifications as a concrete example.

[0638] 1. Collection preparation

[0639] The server retrieves a list of existing base stations from the database. For example, the list contains the IP addresses 192.168.1.1 and 192.168.1.2.

[0640] 2. Data Collection

[0641] The server connects to each base station based on the list via SNMP and collects the configuration information. The collected information is stored in a temporary database. For example, the interface configuration is collected.

[0642] 3. Data Analysis

[0643] The server analyzes the collected information based on the 3GPP standard documents and checks whether the settings comply with the standard, for example, whether the interface settings are consistent with the standard.

[0644] 4. Generate design specifications

[0645] The server automatically generates the design specification by embedding it in a template based on the analysis results. For example, it adds collected information to the "Network Settings" section.

[0646] 5. Customizable interface provided

[0647] The user can input comments and additional information into the generated design specification through the GUI of the terminal. For example, the user can input a comment saying, "There are special requirements."

[0648] 6. Final Check

[0649] The server then modifies the design specifications based on the user's comments and performs a final check, for example, readjusting the configuration information based on the user's comments.

[0650] 7. Output of design specifications

[0651] The server outputs the design specification in PDF format and provides it to the user, who then performs a final check and approves it.

[0652] 8. Project Start

[0653] The approved design specifications will be shared with the project team and the installation and construction of the new base station will commence.

[0654] Prompt Sentence Examples

[0655] "Please explain how a telecommunications company automatically generates design specifications for new base stations. Please provide a detailed description of the process, including the specific steps for collecting data, analyzing the data, filling templates, incorporating user input, and finally outputting it."

[0656] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0657] Step 1:

[0658] Getting a list of nodes

[0659] The server retrieves a list of nodes to collect from a database. This list contains the IP addresses and identification information of each node in the network. The input is the list of nodes to retrieve from the database, and the output is a list of nodes. For example, the list might contain IP addresses 192.168.1.1 and 192.168.1.2.

[0660] Step 2:

[0661] Connecting to a node and collecting data

[0662] Based on the list of nodes obtained, the server connects to each node to collect configuration information and parameters. Connection methods include SNMP, API calls, and SSH. The input is the node list, and the output is the configuration information obtained from the nodes. For example, the server connects to the node at 192.168.1.1 via SNMP and collects configuration information. The collected data is stored in a temporary database.

[0663] Step 3:

[0664] Data normalization

[0665] The server normalizes the collected configuration information and parameters. During the normalization process, the data format is unified and unnecessary data is deleted. The input is the collected configuration information, and the output is normalized data. For example, the interface settings in the data are converted to a standard format.

[0666] Step 4:

[0667] Comparison with standard materials

[0668] The server compares the normalized data with standards such as 3GPP and RFCs to identify matches and mismatches. The input is the normalized data, and the output is information about matches and mismatches with the standards. For example, it checks whether an interface configuration is in accordance with the 3GPP standard.

[0669] Step 5:

[0670] Loading design specification templates

[0671] The server loads a pre-prepared document template. The template contains standard formats and sections. The input is a document template, and the output is the prepared template. For example, a design specification format that conforms to a standard document is loaded.

[0672] Step 6:

[0673] Embedding analysis results into data

[0674] The server embeds the analysis results in the appropriate position in the template to generate a design specification. The input is the analysis results and the document template, and the output is the design specification. For example, the analysis results are added to the "Network Settings" section of the template.

[0675] Step 7:

[0676] User Interface Display

[0677] The server displays an interface that allows the user to enter comments and additional information. The input is the user's comments and additional information, and the output is an updated design specification. For example, the user enters a comment such as "I would like you to change a specific setting on the base station."

[0678] Step 8:

[0679] Reflecting user comments

[0680] The server readjusts the design specification by reflecting comments and additional information obtained from the user. The input is the user's comments and additional information, and the output is an updated design specification. For example, the server modifies the configuration information based on the user's comments.

[0681] Step 9:

[0682] Final Check

[0683] The server performs a final check of the entire design specification and makes any necessary corrections. The input is the design specification, and the output is the final design specification. For example, it checks and corrects that "the section headings do not match the standards."

[0684] Step 10:

[0685] Design specification output

[0686] The server outputs the design specification after the final check in PDF or Word format and provides it to the user. The input is the design specification after the final check, and the output is a document in PDF or Word format. For example, the design specification is output in PDF format.

[0687] (Application example 1)

[0688] 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."

[0689] Modern production facilities are required to collect configuration information and parameters from multiple nodes and automatically generate design specifications and technical documents based on that information. However, previous methods have made it difficult to accurately evaluate and analyze the suitability of collected data and add comments and corrections in real time. Furthermore, the lack of efficient data collection and verification using smart devices has hindered work efficiency. This has led to issues such as complex production line management and maintenance work, and an increased risk of errors.

[0690] 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.

[0691] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, and means for collecting operational setting information and maintenance information for factory equipment and adding real-time comments to the automatically generated technical documents. This makes it possible to collect, check, and modify operational setting information and maintenance information for factory equipment in real time via smart devices.

[0692] A "node" is a piece of electronic equipment that transmits, receives, or processes data within a network.

[0693] "Setting information" refers to parameters and configuration information required to control the operation and functions of an electronic device.

[0694] A "parameter" is a variable used to determine a particular characteristic or behavior of a system or device.

[0695] A "standard document" is a document that sets out generally accepted guidelines or protocols in a particular field.

[0696] "Analysis" is the process of examining data in detail to understand its meaning and structure.

[0697] "Conformance" is the state of conformance to certain criteria or conditions.

[0698] A "design specification" is a document that provides detailed descriptions and instructions for the design of a system.

[0699] "Technical documents" are documents that provide specialized knowledge and information.

[0700] "Comments" are annotations that add opinions or explanations to a document.

[0701] "Additional information" is new data or knowledge provided to supplement existing information.

[0702] A "smart device" is an electronic device with advanced computing power and internet connectivity.

[0703] "Real-time" means that data is collected and processed immediately, without delay.

[0704] This invention is a system that collects operational setting information and maintenance information for factory equipment and automatically generates technical documents based on that information. The functions of the system, which consists of three entities: users, terminals, and servers, are explained below.

[0705] Server Features

[0706] Data collection

[0707] The server first obtains a list of nodes from which data is to be collected from the database. It then connects to each node (in this case, factory equipment) according to that list and collects configuration information and parameters. Collection methods include REST API calls, SNMP, and SSH. The collected data is then stored in a temporary database.

[0708] Data analysis and comparison with standard data

[0709] The collected data is analyzed based on standard documents (e.g., 3GPP, RFC). During the analysis, the collected data is normalized and compared with the standard documents to identify matches and inconsistencies.

[0710] Automatic generation of technical documents

[0711] The server automatically generates technical documents based on the analysis results. First, it reads a document template that conforms to the standard documents and embeds the collected data in the appropriate locations of the template. In this way, the technical documents are generated.

[0712] Providing a customization interface

[0713] The server provides an interface where users can enter comments and additional information, and when the comments and additional information are obtained from the users, the technical materials are adjusted accordingly.

[0714] Final checks and output

[0715] Finally, the server checks the entire generated technical document and makes any necessary corrections. After the check is complete, the technical document is output in a format such as PDF or Word and provided to the user.

[0716] Device Features

[0717] Navigating the User Interface

[0718] The user starts the process of automatically generating technical documentation through the GUI on the terminal. First, they input the necessary node information and collection parameters (operation setting information and maintenance information) into the terminal, and then instruct the server to collect data.

[0719] Customized Input

[0720] After the automatic generation of technical documents is completed, the user can access a screen on their terminal to input comments and additional information, where they can enter specific requirements and conditions and send them to the server.

[0721] User Roles

[0722] System Check

[0723] The user reviews the technical documents provided by the server, checks whether there are any problems with the contents, and makes comments or requests for corrections if necessary.

[0724] Final Approval

[0725] The user reviews the final technical documentation and, if satisfied with the content, approves it. The approved technical documentation is shared with the work team and other relevant parties, and operation and maintenance of the equipment begins.

[0726] Specific examples

[0727] As a concrete example, let's assume that a manufacturing plant introduces a new robot (node) and automatically generates its technical documentation. The server collects configuration information from existing equipment in the manufacturing plant. The collected data is analyzed based on standard documentation, and technical documentation is automatically generated based on the results. The user enters comments from their terminal regarding special requirements or areas that require adjustment, and the server reflects these comments and modifies the documentation. After a final check, the technical documentation is output in PDF format and provided to the user. This process makes the task of creating technical documentation more efficient and reduces the risk of accidents due to work errors.

[0728] Usage example

[0729] For example, a manufacturing plant might use a smartphone to collect operational settings and maintenance data for a newly installed robot. When a worker connects to the robot using a smartphone app, the server collects operational parameters via an API. The collected data is analyzed based on standard documents, and the necessary technical documents are automatically generated. The worker can then view the documents in real time through smart glasses and add any necessary comments or corrections.

[0730] Prompt Sentence Examples

[0731] "Please develop an application that collects the setting information and operating parameters of factory equipment and automatically generates technical documents based on the analysis results. The documents should be based on standard documents and contain accurate information. It should also have a function that allows workers to check them in real time via smart devices and add comments or correction requests."

[0732] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0733] Step 1: Data collection instructions

[0734] The user starts the automatic generation process of technical documents through a GUI on the terminal. The user inputs the necessary node information and collection parameters (e.g., robot operation settings and maintenance information) into the terminal and sends a collection instruction to the server. The input data includes a list of nodes to be collected and the collection parameters.

[0735] Step 2: Data collection

[0736] The server connects to each node based on the node list sent from the terminal. Specifically, it collects configuration information and parameters using methods such as REST API calls, SNMP, and SSH. The collected data is saved in a temporary database. The input is the node list and collected parameters, and the output is the collected configuration information and parameters.

[0737] Step 3: Data analysis and normalization

[0738] The server analyzes the data stored in the temporary database, normalizes the collected data based on standard documents (e.g., 3GPP, RFC), and evaluates the conformance of the collected data. During the normalization process, the input data is unified into a specified format. The input is the configuration information and parameters in the temporary database, and the output is the normalized data and conformance evaluation results.

[0739] Step 4: Automatic generation of technical documentation

[0740] The server automatically generates technical documents based on the analysis results. It loads a pre-defined document template and embeds the analyzed data in the appropriate location in the template. An initial version of the generated technical documents is created. The input is the normalized data and conformance assessment results, and the output is the initial version of the technical documents.

[0741] Step 5: Get user comments

[0742] Through the terminal, the user reviews the initial version of the technical document. If necessary, they enter comments and additional information, which is then sent to the server. This information is used to update the technical document. The input is the user's comments and additional information, and the output is the updated technical document.

[0743] Step 6: Final check of technical documentation

[0744] The server readjusts the technical documentation based on comments and additional information provided by the user. It then performs a final check of the entire technical documentation and makes any necessary corrections. The input is comments and additional information from the user, and the output is the final version of the technical documentation.

[0745] Step 7: Output technical documents

[0746] Finally, the server converts the final version of the technical document into the specified format, such as PDF or Word, and sends it to the terminal. The user can then view the technical document on the terminal and take any necessary actions. The input is the final version of the technical document, and the output is the technical document converted into the specified format.

[0747] 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.

[0748] This invention combines a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on them with an emotion engine that recognizes user emotions.The functions of this system, which consists of four entities: the user, the terminal, the server, and the emotion engine, are described in detail below.

[0749] Server Features

[0750] Data collection

[0751] The server retrieves a list of target nodes from the database and connects to each node based on that list. Connection methods include SNMP, API calls, and SSH. The configuration information and parameters retrieved from the nodes are saved in a temporary database.

[0752] Data analysis and comparison with standard data

[0753] The collected data is analyzed based on standards (e.g., 3GPP, RFC). The data is normalized and compared to the standards to assess conformance. Non-conformances are identified, and necessary corrections are made clear.

[0754] Automatic generation of design specifications

[0755] The server automatically generates a design specification template based on the analysis results by loading the collected data into the appropriate locations within the template. This template conforms to standard documents, with various items neatly arranged.

[0756] Emotion engine collaboration

[0757] The server recognizes the user's emotions using an emotion engine when receiving comments or additional information from the user. The recognized emotion data is fed back into the design specification generation process, and adjustments are made based on the specific emotion.

[0758] Providing a customization interface

[0759] The server provides an interface where users can enter comments and additional information. The data entered through this interface is analyzed through the emotion engine and reflected in the design specifications.

[0760] Final checks and output

[0761] The generated design specifications undergo a final check, with adjustments made to the layout and format, corrections of errors, etc. The final design specifications are output in PDF or Word format and provided to the user.

[0762] Device Features

[0763] Navigating the User Interface

[0764] The user starts the process of automatically generating design specifications using the GUI on the terminal. They input the target node information and collection parameters into the terminal and instruct the server to collect data.

[0765] Enter customization comments

[0766] After the automatic generation of the design specification is completed, the user operates the interface to input comments and additional information. The information entered by the user is analyzed by the emotion engine and processed on the server.

[0767] Emotion Engine Functions

[0768] emotion recognition

[0769] The emotion engine analyzes comments and additional information entered by users and recognizes their emotions. This recognition is performed using natural language processing technology. For example, it analyzes the user's sense of urgency from a comment such as "I'm in a hurry."

[0770] Feedback and Adjustments

[0771] The emotion engine feeds back the recognized emotion, and the server adjusts the content of the design specification. For example, if the user expresses dissatisfaction, it can provide additional explanation.

[0772] User Roles

[0773] System Check

[0774] The user checks the design specifications provided by the server and carefully examines the content to ensure there are no problems. If there are any deficiencies or errors, the user can enter comments or correction requests again.

[0775] Final Approval

[0776] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[0777] Specific examples

[0778] As a concrete example, consider a scenario in which a company introduces a new IT infrastructure (node). In this case, the server collects configuration information from existing systems and analyzes it in accordance with 3GPP and RFC standards. Once the design specifications are automatically generated, the user enters comments and additional information from their terminal. The emotion engine analyzes the user's input and recognizes their emotions. For example, if the user enters "needed immediately," the emotion engine senses the sense of urgency and adjusts the priority of the design specifications. Finally, the design specifications are output in PDF format and provided to the relevant parties. This process improves the efficiency of design work and enables flexible responses to user emotions.

[0779] The processing flow will be explained below.

[0780] Server Processing Steps

[0781] Step 1: Get the node list

[0782] The server gets a list of nodes to connect to from a database, which includes IP addresses, authentication information, etc.

[0783] Step 2: Connect to the node

[0784] The server connects to each node in turn based on the node list, using methods such as SNMP, API calls, and SSH.

[0785] Step 3: Data collection

[0786] The server retrieves configuration information and parameters from the connected nodes, including the node's operating status, settings, sensor data, etc. This collected data is temporarily stored in a database.

[0787] Step 4: Loading the standard materials

[0788] The server loads standard documents such as 3GPP and RFCs and prepares them for comparison with the collected data, thereby clarifying the reference documents and guidelines.

[0789] Step 5: Data Preprocessing

[0790] The server preprocesses the collected data, normalizing it and imputing missing values. Preprocessing ensures data integrity and makes analysis easier.

[0791] Step 6: Data analysis and comparison with standard reference materials

[0792] The server then compares the pre-processed data against the standard, evaluating how well the data conforms to the standard and identifying any areas where it does not conform.

[0793] Step 7: Load the design specification template

[0794] The server loads a standard-compliant design specification template, which includes basic items and formats.

[0795] Step 8: Data Embedding

[0796] Based on the analysis results, the server embeds the collected data in the appropriate locations of the design specification template, thereby forming the basis of the design specification.

[0797] Step 9: Providing a Comment Interface

[0798] The server provides an interface for users to input comments and additional information, adjusts the design specifications according to the user's input, and analyzes the user's emotions through an emotion engine and provides feedback based on the results.

[0799] Step 10: Emotion Recognition

[0800] The server analyzes the user's input through an emotion engine to recognize the user's emotions, for example, detecting a sense of urgency in the case of an urgent request.

[0801] Step 11: Refining the design specifications

[0802] The server readjusts the design specifications based on feedback from the emotion engine, adding necessary explanations and alerts to reflect the user's emotional data.

[0803] Step 12: Final checks and adjustments

[0804] The server performs a final check of the generated design specifications, adjusting the layout and format, correcting errors, and so on.

[0805] Step 13: Output design specifications

[0806] The server outputs the final design specifications in PDF or Word format and provides them to the user, who can then share them with the project team and other stakeholders.

[0807] Terminal processing steps

[0808] Step 1: Launch the user interface

[0809] The user starts the GUI on the terminal and accesses the screen for automatically generating design specifications.

[0810] Step 2: Enter node information

[0811] The user inputs information about the target node and collection parameters into the terminal, including the node's IP address, authentication information, and collection items.

[0812] Step 3: Data collection instructions

[0813] The user issues an instruction to the server to collect the setting information and parameters of the specified node. This instruction is sent to the server, and data collection begins.

[0814] Step 4: Check the retrieved data

[0815] The user can check some of the collected data to see if specific data has been acquired. If there is a problem, the user can issue a collection command to the server again.

[0816] Step 5: Enter customization comments

[0817] After the automatic generation of the design specification is complete, the user operates an interface to enter comments and additional information, including modification requests based on specific conditions or requirements.

[0818] Step 6: Submit your comment

[0819] User comments and correction requests are sent from the device to the server, which receives this information and adjusts the design specifications. The emotion engine analyzes the user's emotions.

[0820] Emotion Engine Processing Steps

[0821] Step 1: Get user comments

[0822] The emotion engine receives user comments and additional information from the server.

[0823] Step 2: Sentiment Analysis

[0824] The emotion engine uses natural language processing technology to analyze user comments and recognize their emotions, for example, detecting a sense of urgency from a comment like "I'm in a hurry."

[0825] Step 3: Feedback on results

[0826] The recognized emotion data is fed back to the server, and this data is reflected in adjustments to the design specifications.

[0827] User processing steps

[0828] Step 1: Review the design specifications

[0829] The user checks the design specifications provided by the server on their terminal, carefully examining the content to ensure there are no problems.

[0830] Step 2: Request additional revisions

[0831] If the user finds any deficiencies or errors in the design specifications, they can enter comments or correction requests and send them to the server, which then receives them and readjusts the specifications.

[0832] Step 3: Final Approval

[0833] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[0834] These are the specific processing steps for the server, terminal, user, and emotion engine. This process makes the creation of design specifications more efficient and enables flexible designs that respond to user emotions.

[0835] Example 2

[0836] 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."

[0837] In today's complex network systems, it is necessary to collect configuration information and parameters from numerous nodes and, based on this information, create design specifications that conform to standard documents. However, evaluating the conformance of collected data and automatically generating design specifications requires a great deal of time and effort, and there are also increasing cases where adjustments based on user emotions are required. Conventional systems have difficulty achieving these processes efficiently and in a user-friendly manner, and systems that include emotion recognition and feedback have particular limitations. Therefore, there is a need for a multifunctional and efficient system that can collect data, analyze it, generate design specifications, and recognize emotions.

[0838] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0839] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, and means for recognizing the emotions of system users and feeding back the emotion data to the design specification creation process. This makes it possible to consistently and efficiently perform the process from data collection to the generation of design specifications, and also realize flexible responses to user emotions.

[0840] A "node" is an independent device or computer system that exists on a communication network.

[0841] "Setting information" refers to various setting parameters and configuration data that define the operation of a node.

[0842] A "parameter" is a data value that indicates the operating conditions or operating state of a system or node.

[0843] A "standard document" is a document that represents a generally accepted technical code or standard.

[0844] "Conformity" refers to the degree to which collected data corresponds to standard data.

[0845] A "design specification" is a document that describes in detail the design of a system or node.

[0846] A "system user" is a user who operates the system, inputs data, and checks results.

[0847] "Emotion" refers to the psychological state and mood of the system user.

[0848] "Comments" are specific opinions or suggestions provided by system users regarding the system.

[0849] "Final check" is the process of finally inspecting the content and format of the generated design specification.

[0850] "Output format" refers to the type of document format (e.g., PDF or Word) in which the design specification is provided.

[0851] "Emotion recognition" is a technology that analyzes and understands the psychological state of a system user based on their input.

[0852] "Feedback" refers to the reuse of analysis results and evaluation information within the system to adjust and improve processes.

[0853] This invention is a system that automatically collects configuration information and parameters from multiple nodes and generates design specifications based on them. This system also includes a function to recognize and provide feedback to users' emotions. Below, we will explain in detail how the invention is implemented by the server, terminal, and user.

[0854] Server processing

[0855] Data collection

[0856] The server retrieves a list of nodes to collect from an SQL database. This is done using a standard SQL query and stores the node list in memory. It then connects to each node based on the list and retrieves configuration information and parameters. This connection method can be SNMP (Simple Network Management Protocol), API calls, or SSH (Secure Shell Protocol). The retrieved data is temporarily stored in a database such as Redis.

[0857] Data analysis and comparison with standard data

[0858] The server analyzes the collected data based on standard documents such as 3GPP and RFC. It uses Python regular expressions (re library) for data normalization. Based on the analysis results, it evaluates conformance and identifies non-conforming parts.

[0859] Automatic generation of design specifications

[0860] The server reads the design specification template (Markdown or LaTeX format) based on the analysis results. It uses Jinja2 as the template engine and automatically generates the design specification by embedding configuration information and parameters in the appropriate places.

[0861] Emotion engine collaboration

[0862] When collecting comments and additional information from users, the server uses an emotion engine (such as the Google Cloud Natural Language API) to recognize the user's emotions. The recognized emotion data is fed back into the design specification creation process, and appropriate adjustments are made.

[0863] Providing a customization interface

[0864] The server provides an electronic form interface using React and Vue.js. Comments and additional information entered by users are analyzed in real time by the emotion engine and reflected in the design specifications.

[0865] Final checks and output

[0866] The server performs a final check of the generated design specification, correcting the layout and formatting, and correcting any errors. The generated design specification is finally converted into PDF or Word format and provided to the user. For example, PDF conversion is performed using LaTeX or Pandoc.

[0867] Processing by the terminal

[0868] Navigating the User Interface

[0869] The user starts the automatic generation process of the design specification using a dedicated GUI on the terminal (e.g., an Electron app), inputs the target node information and collection parameters, and issues a command to the server to collect data.

[0870] Enter customization comments

[0871] After the automatic generation of the design specification is completed, the user can enter comments and additional information using the provided web interface. The user's input data is sent to the server and analyzed by the emotion engine.

[0872] User Roles

[0873] System Check

[0874] The user checks the design specifications provided by the server and carefully examines the contents to ensure there are no problems. If there are any deficiencies or errors, the user can enter comments or correction requests again.

[0875] Final Approval

[0876] The user reviews the final design specifications and, if satisfied, approves them. Once approved, the design specifications are shared with the project team and other stakeholders, and installation and construction can begin.

[0877] Specific examples

[0878] Consider an example where a company is introducing new IT infrastructure. In this case, the server collects configuration information from existing systems and analyzes it based on 3GPP and RFC standards. Once the design specifications are automatically generated, the user can use a terminal to input comments and additional information. The emotion engine analyzes the user's input and recognizes their emotions. For example, if the user enters "immediately needed," the emotion engine will sense the sense of urgency and adjust the priority of the design specifications. The design specifications generated in this way are output in PDF format and provided to the relevant parties.

[0879] Example prompts to input to the generative AI model

[0880] If the user enters "I need it now," the emotion engine will sense the urgency and adjust the priority of the design specification. Finally, the design specification is output in PDF format and provided to the stakeholders. This process improves the efficiency of design work and allows for flexible responses based on the user's emotions.

[0881] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0882] Step 1:

[0883] Starting Data Collection

[0884] The server retrieves the list of nodes to be collected from the SQL database.

[0885] Input: A SQL database query stored on the server.

[0886] Output: A list of nodes.

[0887] Specific operation: The server executes an SQL query to obtain information about the target node and stores it in memory. It executes an SQL statement such as SELECT FROM nodes.

[0888] Step 2:

[0889] Connecting to a node

[0890] The server connects to each node based on the obtained node list.

[0891] Input: Node list, connection method (e.g. SNMP, API, SSH).

[0892] Output: Configuration information and parameters obtained from each node.

[0893] Specific operation: The server connects to each node using Python's paramiko and requests libraries and collects configuration information. For example, use paramiko.SSHClient().connect(hostname, username, password).

[0894] Step 3:

[0895] Temporary data storage

[0896] The server stores the configuration information and parameters collected from the connected nodes in a database for temporary storage.

[0897] Input: Configuration information and parameters obtained from each node.

[0898] Output: Data stored in a temporary location.

[0899] What happens: The server stores the data in a temporary database like Redis. Use redis.set(node_id, data).

[0900] Step 4:

[0901] Data analysis and comparison with standard data

[0902] The server analyzes the collected data based on standard documents such as 3GPP and RFC.

[0903] Input: Data stored in temporary database, standard materials.

[0904] Output: Normalized data and fit assessment results.

[0905] What happens: The server uses Python's re library to normalize the data and match it to a standard reference, e.g., using re.match(pattern, data) to evaluate the relevance.

[0906] Step 5:

[0907] Automatic generation of design specifications

[0908] Based on the analysis results, the server reads the design specification template and fills in the data.

[0909] Input: Normalized data, design specification template.

[0910] Output: Auto-generated design specification.

[0911] What happens: The server uses the Jinja2 template engine to embed the data into the template, for example, by using template.render(data=parsed_data).

[0912] Step 6:

[0913] Collecting user comments

[0914] The terminal allows the user to enter comments and additional information through a web interface.

[0915] Input: User comments and additional information.

[0916] Output: User comment data sent to the server.

[0917] Specific operation: The device displays the user interface (React application) and sends the information entered by the user to the server in real time, for example, using fetch(' / api / comments', {method: 'POST', body: JSON.stringify(comment)}).

[0918] Step 7:

[0919] Starting Emotion Recognition

[0920] The server analyzes the comments from users using an emotion engine and recognizes their emotions.

[0921] Input: User comment data.

[0922] Output: Emotion analysis results.

[0923] What happens: The server sends the comment to the Google Cloud Natural Language API and receives the analysis result. For example, use nlp.analyzeSentiment({document: {content: comment, type: 'PLAIN_TEXT'}}).

[0924] Step 8:

[0925] Emotional Data Feedback

[0926] The server feeds back the recognized emotion data to the design specification generation process.

[0927] Input: Sentiment analysis results.

[0928] Output: Adjusted design specifications.

[0929] Specific operation: The server uses emotion data to adjust the content and priority of the design specifications. For example, if the user indicates urgency, it raises the priority of the design specifications.

[0930] Step 9:

[0931] Final checks and output

[0932] The server performs a final check of the generated design specifications, correcting the layout and format and correcting any errors.

[0933] Input: Auto-generated design specification.

[0934] Output: A PDF or Word file of the design specification that has passed the final check.

[0935] Specific operation: The server uses Pandoc to convert the design specification to PDF or Word format and provide it to the user. For example, use pandoc input.md -o output.pdf.

[0936] This enables the system to efficiently and user-friendly data collection, analysis, design specification generation, and emotion recognition.

[0937] (Application example 2)

[0938] 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."

[0939] Conventional systems generate design specifications based on configuration information and parameters automatically collected from multiple nodes, but they are unable to reflect user sentiment, making it difficult to generate flexible design specifications that meet diverse user needs. Furthermore, content distribution services rely on simple recommendation algorithms, which do not adequately examine user sentiment, making it difficult to recommend optimal content. This leads to problems such as reduced user satisfaction.

[0940] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0941] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard materials and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, means for recognizing user emotions using an emotion engine and adjusting the design specifications based on the recognition results, and means for analyzing user emotions and generating an optimal recommendation plan in a content distribution service. This enables the generation of flexible design specifications that reflect user emotions, and further enables optimal content recommendations based on user emotions in the content distribution service.

[0942] A "node" is a general term for a terminal or device that can operate independently on a network and exchange information.

[0943] "Configuration information" is a general term for information and parameters required to control the operation of network devices and terminals.

[0944] A "parameter" is a variable or value that is set to control the behavior of a system or application.

[0945] "Standard documents" refer to technical documents, guidelines, and protocols that are recognized and referenced as standards within an industry.

[0946] The "emotion engine" is a system that applies natural language processing technology to analyze emotions from user input data and provide feedback on the results.

[0947] A "design specification" is a document that describes the design contents, components, operating conditions, etc. of a system or project.

[0948] "Analysis" refers to the process of examining collected data and information in detail and finding meaning.

[0949] "Comments" refers to opinions, impressions, additional information, etc. that users enter through the interface.

[0950] "Additional information" is supplementary information provided by the user in addition to basic parameters and setting information.

[0951] A "content distribution service" is a system that provides digital content such as music, videos, and articles via the Internet.

[0952] A "recommendation plan" is a plan that suggests optimal content based on the preferences and status of each individual user.

[0953] "Final check" is a procedure for checking the contents of the generated design specifications, correcting errors, and ensuring format consistency.

[0954] "Output format" refers to the manner in which generated data or documents are stored, displayed, or presented in a particular format.

[0955] As an embodiment of the present invention, a system will be described in which an emotion engine is combined with a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on the collected information.

[0956] System configuration

[0957] The system mainly consists of a server, a terminal, an emotion engine, and a user. The role of each component is described in detail below.

[0958] server

[0959] The server is responsible for automatically collecting configuration information and parameters from multiple nodes. The collected data is stored in a temporary database. This data is analyzed based on standard documents (e.g., 3GPP and RFCs), and normalization processing is performed to evaluate its conformance. Design specifications are automatically generated based on the evaluation results, and an interface is also provided for reflecting user comments and additional information. By using an emotion engine to recognize user emotions and reflecting the results in the design specifications, it is possible to generate documents that are more flexible and tailored to user needs.

[0960] Terminal

[0961] The terminal provides a user interface through which users can input information and provide feedback. Collection parameters can be entered through the terminal's GUI, and data collection instructions can be sent to the server. After generating the design specifications, users can enter comments and additional information through the terminal, which is then analyzed by the emotion engine.

[0962] Emotion Engine

[0963] The emotion engine analyzes comments and additional information entered by the user on the device and recognizes emotions. The results are fed back to the server, which then adjusts the content of the design specifications. For example, if the user enters "I'm in a hurry," the emotion engine will detect a sense of urgency and adjust the content to prioritize the speed of creating the design specifications.

[0964] User

[0965] Users operate the system through their terminals to provide comments and additional information, and also review the generated design specifications and give their final approval. User feedback is properly analyzed through the emotion engine, improving the completeness of the design specifications.

[0966] Hardware and software used

[0967] Server: Central server for data collection, analysis, and automatic generation of design specifications

[0968] Terminal: A device that provides a user interface (e.g., a smartphone or tablet).

[0969] Emotion engine: Natural language processing engines such as IBM Watson Natural Language Understanding and Google Cloud NLP

[0970] Database: Relational database such as PostgreSQL

[0971] Specific examples

[0972] For example, in a content distribution service, a user may provide feedback on music content by commenting, "I want to relax." The emotion engine analyzes this comment and recognizes the user's desire to relax. Based on the results, the server recommends optimal content (e.g., relaxing music or videos). This process makes it possible to provide more personalized content to users.

[0973] Prompt Sentence Examples

[0974] "If a user enters 'I'm tired' or 'I want to relax' in the comment field, please provide an algorithm that will recommend content based on that. The input is the comment text and its sentiment classification data, and the output is a recommendation."

[0975] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0976] Step 1:

[0977] The server automatically collects configuration information and parameters from multiple nodes using protocols such as API calls, SNMP, and SSH. The data collected from each node is stored in a temporary database. The input is the node's configuration information and parameters, and the output is the raw data stored in the temporary database.

[0978] Step 2:

[0979] The server analyzes the configuration information and parameters stored in the temporary database based on standard documents (e.g., 3GPP or RFC). This analysis process normalizes the data and checks it against the standard documents. The input is the raw data stored in the temporary database, and the output is the normalized data and the conformance evaluation result.

[0980] Step 3:

[0981] The server reads the design specification template based on the analysis results and automatically generates the design specification by embedding the collected data in the appropriate locations within the template. The input is the normalized data and evaluation results, and the output is the automatically generated design specification.

[0982] Step 4:

[0983] The user uses a terminal to check the design specifications and input comments and additional information. This is done through the terminal's GUI interface. The input is the design specifications and the user's comments and additional information, and the output is the user's feedback.

[0984] Step 5:

[0985] The emotion engine analyzes user comments and additional information sent from the device and recognizes emotions. This analysis uses natural language processing technology. The input is the user's comments and additional information, and the output is the emotion recognition results.

[0986] Step 6:

[0987] The server adjusts the design specifications based on feedback from the emotion engine. For example, if the user feels "hurried," it will respond by raising the priority. The input is the emotion recognition results and the design specifications, and the output is the adjusted design specifications.

[0988] Step 7:

[0989] The server operates in the same way in content distribution services, generating an optimal recommendation plan based on comments entered by users. The input is the user's comments and emotion recognition results, and the output is a content recommendation plan.

[0990] Step 8:

[0991] The server performs a final check and formatting, then outputs a design specification or content recommendation plan in a variety of formats, including PDF, Word, and a list of recommended content. The input is the adjusted data, and the output is the final design specification or list of recommended content.

[0992] The above is the relationship between the specific operations at each processing step and the input and output based on the data processing and calculation.

[0993] 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.

[0994] 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.

[0995] 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.

[0996] [Third embodiment]

[0997] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0998] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0999] 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).

[1000] 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.

[1001] 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.

[1002] 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).

[1003] 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.

[1004] 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.

[1005] 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.

[1006] 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.

[1007] 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.

[1008] 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."

[1009] This invention is a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on that information. The functions of the system, which consists of three entities: users, terminals, and servers, are explained below.

[1010] Server Features

[1011] Data collection

[1012] The server first obtains a list of nodes to collect from the database. According to that list, it connects to each node and collects configuration information and parameters. Collection methods include SNMP, API calls, and SSH. The collected data is stored in a temporary database.

[1013] Data analysis and comparison with standard data

[1014] The collected data is analyzed based on standard documents (e.g., 3GPP, RFC). During the analysis, the collected data is normalized and compared with the standard documents to identify matches and inconsistencies.

[1015] Automatic generation of design specifications

[1016] The server automatically generates design specifications based on the analysis results. First, it reads a document template that conforms to the standard materials and embeds the collected data in the appropriate locations of the template. In this way, the design specifications are generated.

[1017] Providing a customization interface

[1018] The server provides an interface where the user can input comments and additional information, and when the comments and additional information are obtained from the user, the design specification is adjusted accordingly.

[1019] Final checks and output

[1020] Finally, the server checks the entire generated design specification and makes any necessary corrections. After the check is complete, the design specification is output in a format such as PDF or Word and provided to the user.

[1021] Device Features

[1022] Navigating the User Interface

[1023] The user starts the process of automatically generating design specifications through the GUI on the terminal. First, they input the necessary node information and collection parameters into the terminal and instruct the server to collect data.

[1024] Customized Input

[1025] After the automatic generation of the design specification is completed, the user accesses a screen on their terminal to input comments and additional information, where they can enter specific requirements and conditions and send them to the server.

[1026] User Roles

[1027] System Check

[1028] The user reviews the design specifications provided by the server, checks whether there are any problems with the content, and, if necessary, adds comments or requests corrections.

[1029] Final Approval

[1030] The user reviews the final specifications and, if satisfied, approves them. The approved design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[1031] Specific examples

[1032] As a concrete example, let's assume that a telecommunications carrier introduces a new base station (node) and automatically generates its design specifications. In this case, the server collects configuration information from existing base stations in the carrier's network. The collected data is analyzed based on 3GPP standard documents, and the design specifications are automatically generated based on the results. The user enters comments from their device regarding special requirements for the base station and any areas that need adjustment, and the server reflects these comments and modifies the specifications. After a final check, the design specifications are output in PDF format and provided to the user. This entire process streamlines design work and reduces the risk of accidents caused by design errors.

[1033] The processing flow will be explained below.

[1034] Server Processing Steps

[1035] Step 1: Get the node list

[1036] The server retrieves a list of nodes to connect to from a database, which contains the information needed to connect to the nodes, such as IP addresses and authentication information.

[1037] Step 2: Connect to the node

[1038] The server connects to each node in turn based on the node list, using methods such as SNMP, API calls, and SSH.

[1039] Step 3: Data collection

[1040] The server retrieves configuration information and parameters from the connected nodes, including the node's operating status, settings, sensor data, etc. This collected data is temporarily stored in a database.

[1041] Step 4: Loading the standard materials

[1042] The server loads standard documents such as 3GPP and RFCs and prepares them for comparison with the collected data, thereby clarifying the reference documents and guidelines.

[1043] Step 5: Data Preprocessing

[1044] The server preprocesses the collected data, normalizing it and imputing missing values. Preprocessing ensures data integrity and makes analysis easier.

[1045] Step 6: Data analysis and comparison with standard reference materials

[1046] The server then compares the pre-processed data against the standard, evaluating how well the data conforms to the standard and identifying any areas where it does not conform.

[1047] Step 7: Load the design specification template

[1048] The server loads a standard-compliant design specification template, which includes basic items and formats.

[1049] Step 8: Data Embedding

[1050] Based on the analysis results, the server embeds the collected data in the appropriate locations of the design specification template, thereby forming the basis of the design specification.

[1051] Step 9: Providing a Comment Interface

[1052] The server provides an interface for the user to enter comments and additional information, and adjusts the design specification according to the user's input.

[1053] Step 10: Final checks and adjustments

[1054] The server performs a final check of the generated design specifications, adjusting the layout and format, correcting errors, and so on.

[1055] Step 11: Output design specifications

[1056] The server outputs the final design specifications in PDF or Word format and provides them to the user, who can then share them with the project team and other stakeholders.

[1057] Terminal processing steps

[1058] Step 1: Launch the user interface

[1059] The user starts the GUI on the terminal and accesses the screen for automatically generating design specifications.

[1060] Step 2: Enter node information

[1061] The user inputs information about the target node and collection parameters into the terminal, including the node's IP address, authentication information, and collection items.

[1062] Step 3: Data collection instructions

[1063] The user issues an instruction to the server to collect the setting information and parameters of the specified node. This instruction is sent to the server, and data collection begins.

[1064] Step 4: Check the retrieved data

[1065] The user can check some of the collected data to see if specific data has been acquired. If there is a problem, the user can issue a collection command to the server again.

[1066] Step 5: Enter customization comments

[1067] The user operates an interface to enter any comments or special requirements they wish to add to the design specification, including requests for modifications based on specific conditions or requirements.

[1068] Step 6: Submit your comment

[1069] User comments and correction requests are sent from the terminal to the server, which receives this information and adjusts the design specifications accordingly.

[1070] User processing steps

[1071] Step 1: Review the design specifications

[1072] The user checks the design specifications provided by the server on their terminal, carefully examining the content to ensure there are no problems.

[1073] Step 2: Request additional revisions

[1074] If the user finds any deficiencies or errors in the design specifications, they can enter comments or correction requests and send them to the server, which then receives them and readjusts the specifications.

[1075] Step 3: Final Approval

[1076] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[1077] These are the specific processing steps for the server, terminal, and user. This process makes the creation of design specifications more efficient and reduces the risk of system accidents caused by design errors.

[1078] Example 1

[1079] 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."

[1080] In modern network systems, collecting configuration information and parameters from multiple nodes and creating design specifications based on that information is extremely complex and time-consuming. Furthermore, accurately reflecting the analysis results of the collected data requires specialized knowledge, which increases the risk of errors and inconsistencies. Furthermore, incorporating user comments and additional information into design specifications is often done manually, which is inefficient. Therefore, there is a need for a method to automate these processes and efficiently create high-quality design specifications.

[1081] 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.

[1082] In this invention, the server includes: means for automatically collecting setting information and parameters from multiple nodes; means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability; means for automatically generating design specifications based on the analysis results; means for acquiring comments and additional information from system users and reflecting them in the design specifications; means for performing a final check of the generated design specifications and converting them into an output format for provision; means for starting data collection and generation of design specifications through a user interface; and means for generating design specifications based on a template. This automates the entire process of collecting setting information from multiple nodes, comparing it with standard documents, automatically generating design specifications, incorporating user feedback, and finally outputting the document, enabling efficient creation of high-quality design specifications.

[1083] A "server" is a computer system that provides services and data processing to multiple clients over a network.

[1084] A "node" is an individual device or equipment connected to a network, including routers, switches, base stations, etc.

[1085] "Configuration information" refers to parameters and setting values ​​required to determine the operation and functions of a node.

[1086] A "parameter" is a numerical value or setting used to control the operation of a system or node.

[1087] "Standards documents" are documents that provide industry standards or guidelines, such as 3GPP and RFCs.

[1088] "Analysis" is the process of evaluating collected data against normative references and identifying matches and inconsistencies.

[1089] "Conformity" is an index that indicates the degree to which the collected setting information and parameters match the standard data.

[1090] A "design specification" is a document that details the design requirements and specifications of a system or equipment, and is used when introducing or building it.

[1091] "Automatic generation" is the process of generating specific documents or data programmatically without human intervention.

[1092] "System users" are the personnel or end users who operate the system, collect configuration information, add comments, and review and approve design specifications.

[1093] "Comments" are opinions, suggestions, and small corrections that system users add to the design specifications.

[1094] "Additional information" refers to new data or requirements to be included in the design specification.

[1095] "Final check" is the process of checking all the contents of the generated design specifications and correcting any errors or incomplete parts.

[1096] "Output format" refers to the file format, such as PDF or Word, used to save and display the generated design specifications.

[1097] A "user interface" is an interface through which a system user operates the system via a GUI, inputting configuration information and instructing the generation of design specifications.

[1098] A "template" is a predefined format that defines the format and structure of a design specification based on standard documents or guidelines.

[1099] This invention is a system that automatically collects setting information and parameters from multiple nodes and automatically generates design specifications based on the collected information. How this system can be implemented will be described below.

[1100] Server Features

[1101] Data collection

[1102] The server first obtains a list of nodes to collect from the database. Based on that list, it connects to each node and collects configuration information and parameters. Collection methods include SNMP (Simple Network Management Protocol), API calls, and SSH (Secure Shell). For example, the server connects via SNMP to a node with an IP address of 192.168.1.1 to collect configuration information. The collected data is saved in a temporary database.

[1103] Data analysis and comparison with standard data

[1104] The server analyzes the collected data based on standards such as 3GPP and RFCs. During the analysis, the collected data is normalized and compared with the standards to identify matching and non-matching parts. For example, it checks whether the node's interface settings comply with the 3GPP standard.

[1105] Automatic generation of design specifications

[1106] The server automatically generates design specifications based on the analysis results. This is done by loading a document template that conforms to the standard and embedding the collected data in the appropriate locations. For example, the server embeds the previously collected interface configuration information in the "Network Settings" section of the template.

[1107] Providing a customization interface

[1108] The server provides an interface where users can enter comments and additional information. The server acquires the user's comments and additional information and readjusts the design specifications based on them. For example, if a user enters a comment such as "I would like you to change a specific setting on the base station," the server will reflect that comment and modify the specifications.

[1109] Final checks and output

[1110] The server performs a final check, makes any necessary corrections, and then outputs the design specification in PDF or Word format and provides it to the user. For example, the server may find in the final check that "the section headings do not match the standards," correct them, and then output them in PDF format.

[1111] Device Features

[1112] Navigating the User Interface

[1113] The user starts the automatic generation process of the design specification using the terminal's GUI (Graphical User Interface). The user inputs node information and collection parameters into the terminal and instructs the server to collect data. For example, the user inputs "Collect configuration information for a new base station" into the GUI and presses the send button, which sends this instruction from the terminal to the server.

[1114] Customized Input

[1115] After the automatic generation of the design specification is completed, the user accesses a screen on the terminal to input comments and additional information. Here, the user inputs specific requirements and conditions, which are then sent to the server. For example, the user inputs specific requirements for configuration information and sends them from the terminal to the server.

[1116] User Roles

[1117] System Check

[1118] The user reviews the design specifications provided by the server and checks whether there are any problems with the content. If necessary, the user can add comments or request corrections. For example, if a user who has checked the design specifications feels that a certain setting is inappropriate, they can input that comment.

[1119] Final Approval

[1120] The user performs a final check and, if approved, the design specifications are shared with the project team and other stakeholders, and the installation and construction of the equipment begins. For example, if the user performs a final check and determines that there are no problems with the contents, they press the approval button to approve the design specifications.

[1121] Specific examples

[1122] We will explain the case where a telecommunications carrier introduces a new base station (node) and automatically generates its design specifications as a concrete example.

[1123] 1. Collection preparation

[1124] The server retrieves a list of existing base stations from the database. For example, the list contains the IP addresses 192.168.1.1 and 192.168.1.2.

[1125] 2. Data Collection

[1126] The server connects to each base station based on the list via SNMP and collects the configuration information. The collected information is stored in a temporary database. For example, the interface configuration is collected.

[1127] 3. Data Analysis

[1128] The server analyzes the collected information based on the 3GPP standard documents and checks whether the settings comply with the standard, for example, whether the interface settings are consistent with the standard.

[1129] 4. Generate design specifications

[1130] The server automatically generates the design specification by embedding it in a template based on the analysis results. For example, it adds collected information to the "Network Settings" section.

[1131] 5. Customizable interface provided

[1132] The user can input comments and additional information into the generated design specification through the GUI of the terminal. For example, the user can input a comment saying, "There are special requirements."

[1133] 6. Final Check

[1134] The server then modifies the design specifications based on the user's comments and performs a final check, for example, readjusting the configuration information based on the user's comments.

[1135] 7. Output of design specifications

[1136] The server outputs the design specification in PDF format and provides it to the user, who then performs a final check and approves it.

[1137] 8. Project Start

[1138] The approved design specifications will be shared with the project team and the installation and construction of the new base station will commence.

[1139] Prompt Sentence Examples

[1140] "Please explain how a telecommunications company automatically generates design specifications for new base stations. Please provide a detailed description of the process, including the specific steps for collecting data, analyzing the data, filling templates, incorporating user input, and finally outputting it."

[1141] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1142] Step 1:

[1143] Getting a list of nodes

[1144] The server retrieves a list of nodes to collect from a database. This list contains the IP addresses and identification information of each node in the network. The input is the list of nodes to retrieve from the database, and the output is a list of nodes. For example, the list might contain IP addresses 192.168.1.1 and 192.168.1.2.

[1145] Step 2:

[1146] Connecting to a node and collecting data

[1147] Based on the list of nodes obtained, the server connects to each node to collect configuration information and parameters. Connection methods include SNMP, API calls, and SSH. The input is the node list, and the output is the configuration information obtained from the nodes. For example, the server connects to the node at 192.168.1.1 via SNMP and collects configuration information. The collected data is stored in a temporary database.

[1148] Step 3:

[1149] Data normalization

[1150] The server normalizes the collected configuration information and parameters. During the normalization process, the data format is unified and unnecessary data is deleted. The input is the collected configuration information, and the output is normalized data. For example, the interface settings in the data are converted to a standard format.

[1151] Step 4:

[1152] Comparison with standard materials

[1153] The server compares the normalized data with standards such as 3GPP and RFCs to identify matches and mismatches. The input is the normalized data, and the output is information about matches and mismatches with the standards. For example, it checks whether an interface configuration is in accordance with the 3GPP standard.

[1154] Step 5:

[1155] Loading design specification templates

[1156] The server loads a pre-prepared document template. The template contains standard formats and sections. The input is a document template, and the output is the prepared template. For example, a design specification format that conforms to a standard document is loaded.

[1157] Step 6:

[1158] Embedding analysis results into data

[1159] The server embeds the analysis results in the appropriate position in the template to generate a design specification. The input is the analysis results and the document template, and the output is the design specification. For example, the analysis results are added to the "Network Settings" section of the template.

[1160] Step 7:

[1161] User Interface Display

[1162] The server displays an interface that allows the user to enter comments and additional information. The input is the user's comments and additional information, and the output is an updated design specification. For example, the user enters a comment such as "I would like you to change a specific setting on the base station."

[1163] Step 8:

[1164] Reflecting user comments

[1165] The server readjusts the design specification by reflecting comments and additional information obtained from the user. The input is the user's comments and additional information, and the output is an updated design specification. For example, the server modifies the configuration information based on the user's comments.

[1166] Step 9:

[1167] Final Check

[1168] The server performs a final check of the entire design specification and makes any necessary corrections. The input is the design specification, and the output is the final design specification. For example, it checks and corrects that "the section headings do not match the standards."

[1169] Step 10:

[1170] Design specification output

[1171] The server outputs the design specification after the final check in PDF or Word format and provides it to the user. The input is the design specification after the final check, and the output is a document in PDF or Word format. For example, the design specification is output in PDF format.

[1172] (Application example 1)

[1173] 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."

[1174] Modern production facilities are required to collect configuration information and parameters from multiple nodes and automatically generate design specifications and technical documents based on that information. However, previous methods have made it difficult to accurately evaluate and analyze the suitability of collected data and add comments and corrections in real time. Furthermore, the lack of efficient data collection and verification using smart devices has hindered work efficiency. This has led to issues such as complex production line management and maintenance work, and an increased risk of errors.

[1175] 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.

[1176] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, and means for collecting operational setting information and maintenance information for factory equipment and adding real-time comments to the automatically generated technical documents. This makes it possible to collect, check, and modify operational setting information and maintenance information for factory equipment in real time via smart devices.

[1177] A "node" is a piece of electronic equipment that transmits, receives, or processes data within a network.

[1178] "Setting information" refers to parameters and configuration information required to control the operation and functions of an electronic device.

[1179] A "parameter" is a variable used to determine a particular characteristic or behavior of a system or device.

[1180] A "standard document" is a document that sets out generally accepted guidelines or protocols in a particular field.

[1181] "Analysis" is the process of examining data in detail to understand its meaning and structure.

[1182] "Conformance" is the state of conformance to certain criteria or conditions.

[1183] A "design specification" is a document that provides detailed descriptions and instructions for the design of a system.

[1184] "Technical documents" are documents that provide specialized knowledge and information.

[1185] "Comments" are annotations that add opinions or explanations to a document.

[1186] "Additional information" is new data or knowledge provided to supplement existing information.

[1187] A "smart device" is an electronic device with advanced computing power and internet connectivity.

[1188] "Real-time" means that data is collected and processed immediately, without delay.

[1189] This invention is a system that collects operational setting information and maintenance information for factory equipment and automatically generates technical documents based on that information. The functions of the system, which consists of three entities: users, terminals, and servers, are explained below.

[1190] Server Features

[1191] Data collection

[1192] The server first obtains a list of nodes from which data is to be collected from the database. It then connects to each node (in this case, factory equipment) according to that list and collects configuration information and parameters. Collection methods include REST API calls, SNMP, and SSH. The collected data is then stored in a temporary database.

[1193] Data analysis and comparison with standard data

[1194] The collected data is analyzed based on standard documents (e.g., 3GPP, RFC). During the analysis, the collected data is normalized and compared with the standard documents to identify matches and inconsistencies.

[1195] Automatic generation of technical documents

[1196] The server automatically generates technical documents based on the analysis results. First, it reads a document template that conforms to the standard documents and embeds the collected data in the appropriate locations of the template. In this way, the technical documents are generated.

[1197] Providing a customization interface

[1198] The server provides an interface where users can enter comments and additional information, and when the comments and additional information are obtained from the users, the technical materials are adjusted accordingly.

[1199] Final checks and output

[1200] Finally, the server checks the entire generated technical document and makes any necessary corrections. After the check is complete, the technical document is output in a format such as PDF or Word and provided to the user.

[1201] Device Features

[1202] Navigating the User Interface

[1203] The user starts the process of automatically generating technical documentation through the GUI on the terminal. First, they input the necessary node information and collection parameters (operation setting information and maintenance information) into the terminal, and then instruct the server to collect data.

[1204] Customized Input

[1205] After the automatic generation of technical documents is completed, the user can access a screen on their terminal to input comments and additional information, where they can enter specific requirements and conditions and send them to the server.

[1206] User Roles

[1207] System Check

[1208] The user reviews the technical documents provided by the server, checks whether there are any problems with the contents, and makes comments or requests for corrections if necessary.

[1209] Final Approval

[1210] The user reviews the final technical documentation and, if satisfied with the content, approves it. The approved technical documentation is shared with the work team and other relevant parties, and operation and maintenance of the equipment begins.

[1211] Specific examples

[1212] As a concrete example, let's assume that a manufacturing plant introduces a new robot (node) and automatically generates its technical documentation. The server collects configuration information from existing equipment in the manufacturing plant. The collected data is analyzed based on standard documentation, and technical documentation is automatically generated based on the results. The user enters comments from their terminal regarding special requirements or areas that require adjustment, and the server reflects these comments and modifies the documentation. After a final check, the technical documentation is output in PDF format and provided to the user. This process makes the task of creating technical documentation more efficient and reduces the risk of accidents due to work errors.

[1213] Usage example

[1214] For example, a manufacturing plant might use a smartphone to collect operational settings and maintenance data for a newly installed robot. When a worker connects to the robot using a smartphone app, the server collects operational parameters via an API. The collected data is analyzed based on standard documents, and the necessary technical documents are automatically generated. The worker can then view the documents in real time through smart glasses and add any necessary comments or corrections.

[1215] Prompt Sentence Examples

[1216] "Please develop an application that collects the setting information and operating parameters of factory equipment and automatically generates technical documents based on the analysis results. The documents should be based on standard documents and contain accurate information. It should also have a function that allows workers to check them in real time via smart devices and add comments or correction requests."

[1217] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1218] Step 1: Data collection instructions

[1219] The user starts the automatic generation process of technical documents through a GUI on the terminal. The user inputs the necessary node information and collection parameters (e.g., robot operation settings and maintenance information) into the terminal and sends a collection instruction to the server. The input data includes a list of nodes to be collected and the collection parameters.

[1220] Step 2: Data collection

[1221] The server connects to each node based on the node list sent from the terminal. Specifically, it collects configuration information and parameters using methods such as REST API calls, SNMP, and SSH. The collected data is saved in a temporary database. The input is the node list and collected parameters, and the output is the collected configuration information and parameters.

[1222] Step 3: Data analysis and normalization

[1223] The server analyzes the data stored in the temporary database, normalizes the collected data based on standard documents (e.g., 3GPP, RFC), and evaluates the conformance of the collected data. During the normalization process, the input data is unified into a specified format. The input is the configuration information and parameters in the temporary database, and the output is the normalized data and conformance evaluation results.

[1224] Step 4: Automatic generation of technical documentation

[1225] The server automatically generates technical documents based on the analysis results. It loads a pre-defined document template and embeds the analyzed data in the appropriate location in the template. An initial version of the generated technical documents is created. The input is the normalized data and conformance assessment results, and the output is the initial version of the technical documents.

[1226] Step 5: Get user comments

[1227] Through the terminal, the user reviews the initial version of the technical document. If necessary, they enter comments and additional information, which is then sent to the server. This information is used to update the technical document. The input is the user's comments and additional information, and the output is the updated technical document.

[1228] Step 6: Final check of technical documentation

[1229] The server readjusts the technical documentation based on comments and additional information provided by the user. It then performs a final check of the entire technical documentation and makes any necessary corrections. The input is comments and additional information from the user, and the output is the final version of the technical documentation.

[1230] Step 7: Output technical documents

[1231] Finally, the server converts the final version of the technical document into the specified format, such as PDF or Word, and sends it to the terminal. The user can then view the technical document on the terminal and take any necessary actions. The input is the final version of the technical document, and the output is the technical document converted into the specified format.

[1232] 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.

[1233] This invention combines a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on them with an emotion engine that recognizes user emotions.The functions of this system, which consists of four entities: the user, the terminal, the server, and the emotion engine, are described in detail below.

[1234] Server Features

[1235] Data collection

[1236] The server retrieves a list of target nodes from the database and connects to each node based on that list. Connection methods include SNMP, API calls, and SSH. The configuration information and parameters retrieved from the nodes are saved in a temporary database.

[1237] Data analysis and comparison with standard data

[1238] The collected data is analyzed based on standards (e.g., 3GPP, RFC). The data is normalized and compared to the standards to assess conformance. Non-conformances are identified, and necessary corrections are made clear.

[1239] Automatic generation of design specifications

[1240] The server automatically generates a design specification template based on the analysis results by loading the collected data into the appropriate locations within the template. This template conforms to standard documents, with various items neatly arranged.

[1241] Emotion engine collaboration

[1242] The server recognizes the user's emotions using an emotion engine when receiving comments or additional information from the user. The recognized emotion data is fed back into the design specification generation process, and adjustments are made based on the specific emotion.

[1243] Providing a customization interface

[1244] The server provides an interface where users can enter comments and additional information. The data entered through this interface is analyzed through the emotion engine and reflected in the design specifications.

[1245] Final checks and output

[1246] The generated design specifications undergo a final check, with adjustments made to the layout and format, corrections of errors, etc. The final design specifications are output in PDF or Word format and provided to the user.

[1247] Device Features

[1248] Navigating the User Interface

[1249] The user starts the process of automatically generating design specifications using the GUI on the terminal. They input the target node information and collection parameters into the terminal and instruct the server to collect data.

[1250] Enter customization comments

[1251] After the automatic generation of the design specification is completed, the user operates the interface to input comments and additional information. The information entered by the user is analyzed by the emotion engine and processed on the server.

[1252] Emotion Engine Functions

[1253] emotion recognition

[1254] The emotion engine analyzes comments and additional information entered by users and recognizes their emotions. This recognition is performed using natural language processing technology. For example, it analyzes the user's sense of urgency from a comment such as "I'm in a hurry."

[1255] Feedback and Adjustments

[1256] The emotion engine feeds back the recognized emotion, and the server adjusts the content of the design specification. For example, if the user expresses dissatisfaction, it can provide additional explanation.

[1257] User Roles

[1258] System Check

[1259] The user checks the design specifications provided by the server and carefully examines the content to ensure there are no problems. If there are any deficiencies or errors, the user can enter comments or correction requests again.

[1260] Final Approval

[1261] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[1262] Specific examples

[1263] As a concrete example, consider a scenario in which a company introduces a new IT infrastructure (node). In this case, the server collects configuration information from existing systems and analyzes it in accordance with 3GPP and RFC standards. Once the design specifications are automatically generated, the user enters comments and additional information from their terminal. The emotion engine analyzes the user's input and recognizes their emotions. For example, if the user enters "needed immediately," the emotion engine senses the sense of urgency and adjusts the priority of the design specifications. Finally, the design specifications are output in PDF format and provided to the relevant parties. This process improves the efficiency of design work and enables flexible responses to user emotions.

[1264] The processing flow will be explained below.

[1265] Server Processing Steps

[1266] Step 1: Get the node list

[1267] The server gets a list of nodes to connect to from a database, which includes IP addresses, authentication information, etc.

[1268] Step 2: Connect to the node

[1269] The server connects to each node in turn based on the node list, using methods such as SNMP, API calls, and SSH.

[1270] Step 3: Data collection

[1271] The server retrieves configuration information and parameters from the connected nodes, including the node's operating status, settings, sensor data, etc. This collected data is temporarily stored in a database.

[1272] Step 4: Loading the standard materials

[1273] The server loads standard documents such as 3GPP and RFCs and prepares them for comparison with the collected data, thereby clarifying the reference documents and guidelines.

[1274] Step 5: Data Preprocessing

[1275] The server preprocesses the collected data, normalizing it and imputing missing values. Preprocessing ensures data integrity and makes analysis easier.

[1276] Step 6: Data analysis and comparison with standard reference materials

[1277] The server then compares the pre-processed data against the standard, evaluating how well the data conforms to the standard and identifying any areas where it does not conform.

[1278] Step 7: Load the design specification template

[1279] The server loads a standard-compliant design specification template, which includes basic items and formats.

[1280] Step 8: Data Embedding

[1281] Based on the analysis results, the server embeds the collected data in the appropriate locations of the design specification template, thereby forming the basis of the design specification.

[1282] Step 9: Providing a Comment Interface

[1283] The server provides an interface for users to input comments and additional information, adjusts the design specifications according to the user's input, and analyzes the user's emotions through an emotion engine and provides feedback based on the results.

[1284] Step 10: Emotion Recognition

[1285] The server analyzes the user's input through an emotion engine to recognize the user's emotions, for example, detecting a sense of urgency in the case of an urgent request.

[1286] Step 11: Refining the design specifications

[1287] The server readjusts the design specifications based on feedback from the emotion engine, adding necessary explanations and alerts to reflect the user's emotional data.

[1288] Step 12: Final checks and adjustments

[1289] The server performs a final check of the generated design specifications, adjusting the layout and format, correcting errors, and so on.

[1290] Step 13: Output design specifications

[1291] The server outputs the final design specifications in PDF or Word format and provides them to the user, who can then share them with the project team and other stakeholders.

[1292] Terminal processing steps

[1293] Step 1: Launch the user interface

[1294] The user starts the GUI on the terminal and accesses the screen for automatically generating design specifications.

[1295] Step 2: Enter node information

[1296] The user inputs information about the target node and collection parameters into the terminal, including the node's IP address, authentication information, and collection items.

[1297] Step 3: Data collection instructions

[1298] The user issues an instruction to the server to collect the setting information and parameters of the specified node. This instruction is sent to the server, and data collection begins.

[1299] Step 4: Check the retrieved data

[1300] The user can check some of the collected data to see if specific data has been acquired. If there is a problem, the user can issue a collection command to the server again.

[1301] Step 5: Enter customization comments

[1302] After the automatic generation of the design specification is complete, the user operates an interface to enter comments and additional information, including modification requests based on specific conditions or requirements.

[1303] Step 6: Submit your comment

[1304] User comments and correction requests are sent from the device to the server, which receives this information and adjusts the design specifications. The emotion engine analyzes the user's emotions.

[1305] Emotion Engine Processing Steps

[1306] Step 1: Get user comments

[1307] The emotion engine receives user comments and additional information from the server.

[1308] Step 2: Sentiment Analysis

[1309] The emotion engine uses natural language processing technology to analyze user comments and recognize their emotions, for example, detecting a sense of urgency from a comment like "I'm in a hurry."

[1310] Step 3: Feedback on results

[1311] The recognized emotion data is fed back to the server, and this data is reflected in adjustments to the design specifications.

[1312] User processing steps

[1313] Step 1: Review the design specifications

[1314] The user checks the design specifications provided by the server on their terminal, carefully examining the content to ensure there are no problems.

[1315] Step 2: Request additional revisions

[1316] If the user finds any deficiencies or errors in the design specifications, they can enter comments or correction requests and send them to the server, which then receives them and readjusts the specifications.

[1317] Step 3: Final Approval

[1318] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[1319] These are the specific processing steps for the server, terminal, user, and emotion engine. This process makes the creation of design specifications more efficient and enables flexible designs that respond to user emotions.

[1320] Example 2

[1321] 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."

[1322] In today's complex network systems, it is necessary to collect configuration information and parameters from numerous nodes and, based on this information, create design specifications that conform to standard documents. However, evaluating the conformance of collected data and automatically generating design specifications requires a great deal of time and effort, and there are also increasing cases where adjustments based on user emotions are required. Conventional systems have difficulty achieving these processes efficiently and in a user-friendly manner, and systems that include emotion recognition and feedback have particular limitations. Therefore, there is a need for a multifunctional and efficient system that can collect data, analyze it, generate design specifications, and recognize emotions.

[1323] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1324] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, and means for recognizing the emotions of system users and feeding back the emotion data to the design specification creation process. This makes it possible to consistently and efficiently perform the process from data collection to the generation of design specifications, and also realize flexible responses to user emotions.

[1325] A "node" is an independent device or computer system that exists on a communication network.

[1326] "Setting information" refers to various setting parameters and configuration data that define the operation of a node.

[1327] A "parameter" is a data value that indicates the operating conditions or operating state of a system or node.

[1328] A "standard document" is a document that represents a generally accepted technical code or standard.

[1329] "Conformity" refers to the degree to which collected data corresponds to standard data.

[1330] A "design specification" is a document that describes in detail the design of a system or node.

[1331] A "system user" is a user who operates the system, inputs data, and checks results.

[1332] "Emotion" refers to the psychological state and mood of the system user.

[1333] "Comments" are specific opinions or suggestions provided by system users regarding the system.

[1334] "Final check" is the process of finally inspecting the content and format of the generated design specification.

[1335] "Output format" refers to the type of document format (e.g., PDF or Word) in which the design specification is provided.

[1336] "Emotion recognition" is a technology that analyzes and understands the psychological state of a system user based on their input.

[1337] "Feedback" refers to the reuse of analysis results and evaluation information within the system to adjust and improve processes.

[1338] This invention is a system that automatically collects configuration information and parameters from multiple nodes and generates design specifications based on them. This system also includes a function to recognize and provide feedback to users' emotions. Below, we will explain in detail how the invention is implemented by the server, terminal, and user.

[1339] Server processing

[1340] Data collection

[1341] The server retrieves a list of nodes to collect from an SQL database. This is done using a standard SQL query and stores the node list in memory. It then connects to each node based on the list and retrieves configuration information and parameters. This connection method can be SNMP (Simple Network Management Protocol), API calls, or SSH (Secure Shell Protocol). The retrieved data is temporarily stored in a database such as Redis.

[1342] Data analysis and comparison with standard data

[1343] The server analyzes the collected data based on standard documents such as 3GPP and RFC. It uses Python regular expressions (re library) for data normalization. Based on the analysis results, it evaluates conformance and identifies non-conforming parts.

[1344] Automatic generation of design specifications

[1345] The server reads the design specification template (Markdown or LaTeX format) based on the analysis results. It uses Jinja2 as the template engine and automatically generates the design specification by embedding configuration information and parameters in the appropriate places.

[1346] Emotion engine collaboration

[1347] When collecting comments and additional information from users, the server uses an emotion engine (such as the Google Cloud Natural Language API) to recognize the user's emotions. The recognized emotion data is fed back into the design specification creation process, and appropriate adjustments are made.

[1348] Providing a customization interface

[1349] The server provides an electronic form interface using React and Vue.js. Comments and additional information entered by users are analyzed in real time by the emotion engine and reflected in the design specifications.

[1350] Final checks and output

[1351] The server performs a final check of the generated design specification, correcting the layout and formatting, and correcting any errors. The generated design specification is finally converted into PDF or Word format and provided to the user. For example, PDF conversion is performed using LaTeX or Pandoc.

[1352] Processing by the terminal

[1353] Navigating the User Interface

[1354] The user starts the automatic generation process of the design specification using a dedicated GUI on the terminal (e.g., an Electron app), inputs the target node information and collection parameters, and issues a command to the server to collect data.

[1355] Enter customization comments

[1356] After the automatic generation of the design specification is completed, the user can enter comments and additional information using the provided web interface. The user's input data is sent to the server and analyzed by the emotion engine.

[1357] User Roles

[1358] System Check

[1359] The user checks the design specifications provided by the server and carefully examines the contents to ensure there are no problems. If there are any deficiencies or errors, the user can enter comments or correction requests again.

[1360] Final Approval

[1361] The user reviews the final design specifications and, if satisfied, approves them. Once approved, the design specifications are shared with the project team and other stakeholders, and installation and construction can begin.

[1362] Specific examples

[1363] Consider an example where a company is introducing new IT infrastructure. In this case, the server collects configuration information from existing systems and analyzes it based on 3GPP and RFC standards. Once the design specifications are automatically generated, the user can use a terminal to input comments and additional information. The emotion engine analyzes the user's input and recognizes their emotions. For example, if the user enters "immediately needed," the emotion engine will sense the sense of urgency and adjust the priority of the design specifications. The design specifications generated in this way are output in PDF format and provided to the relevant parties.

[1364] Example prompts to input to the generative AI model

[1365] If the user enters "I need it now," the emotion engine will sense the urgency and adjust the priority of the design specification. Finally, the design specification is output in PDF format and provided to the stakeholders. This process improves the efficiency of design work and allows for flexible responses based on the user's emotions.

[1366] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1367] Step 1:

[1368] Starting Data Collection

[1369] The server retrieves the list of nodes to be collected from the SQL database.

[1370] Input: A SQL database query stored on the server.

[1371] Output: A list of nodes.

[1372] Specific operation: The server executes an SQL query to obtain information about the target node and stores it in memory. It executes an SQL statement such as SELECT FROM nodes.

[1373] Step 2:

[1374] Connecting to a node

[1375] The server connects to each node based on the obtained node list.

[1376] Input: Node list, connection method (e.g. SNMP, API, SSH).

[1377] Output: Configuration information and parameters obtained from each node.

[1378] Specific operation: The server connects to each node using Python's paramiko and requests libraries and collects configuration information. For example, use paramiko.SSHClient().connect(hostname, username, password).

[1379] Step 3:

[1380] Temporary data storage

[1381] The server stores the configuration information and parameters collected from the connected nodes in a database for temporary storage.

[1382] Input: Configuration information and parameters obtained from each node.

[1383] Output: Data stored in a temporary location.

[1384] What happens: The server stores the data in a temporary database like Redis. Use redis.set(node_id, data).

[1385] Step 4:

[1386] Data analysis and comparison with standard data

[1387] The server analyzes the collected data based on standard documents such as 3GPP and RFC.

[1388] Input: Data stored in temporary database, standard materials.

[1389] Output: Normalized data and fit assessment results.

[1390] What happens: The server uses Python's re library to normalize the data and match it to a standard reference, e.g., using re.match(pattern, data) to evaluate the relevance.

[1391] Step 5:

[1392] Automatic generation of design specifications

[1393] Based on the analysis results, the server reads the design specification template and fills in the data.

[1394] Input: Normalized data, design specification template.

[1395] Output: Auto-generated design specification.

[1396] What happens: The server uses the Jinja2 template engine to embed the data into the template, for example, by using template.render(data=parsed_data).

[1397] Step 6:

[1398] Collecting user comments

[1399] The terminal allows the user to enter comments and additional information through a web interface.

[1400] Input: User comments and additional information.

[1401] Output: User comment data sent to the server.

[1402] Specific operation: The device displays the user interface (React application) and sends the information entered by the user to the server in real time, for example, using fetch(' / api / comments', {method: 'POST', body: JSON.stringify(comment)}).

[1403] Step 7:

[1404] Starting Emotion Recognition

[1405] The server analyzes the comments from users using an emotion engine and recognizes their emotions.

[1406] Input: User comment data.

[1407] Output: Emotion analysis results.

[1408] What happens: The server sends the comment to the Google Cloud Natural Language API and receives the analysis result. For example, use nlp.analyzeSentiment({document: {content: comment, type: 'PLAIN_TEXT'}}).

[1409] Step 8:

[1410] Emotional Data Feedback

[1411] The server feeds back the recognized emotion data to the design specification generation process.

[1412] Input: Sentiment analysis results.

[1413] Output: Adjusted design specifications.

[1414] Specific operation: The server uses emotion data to adjust the content and priority of the design specifications. For example, if the user indicates urgency, it raises the priority of the design specifications.

[1415] Step 9:

[1416] Final checks and output

[1417] The server performs a final check of the generated design specifications, correcting the layout and format and correcting any errors.

[1418] Input: Auto-generated design specification.

[1419] Output: A PDF or Word file of the design specification that has passed the final check.

[1420] Specific operation: The server uses Pandoc to convert the design specification to PDF or Word format and provide it to the user. For example, use pandoc input.md -o output.pdf.

[1421] This enables the system to efficiently and user-friendly data collection, analysis, design specification generation, and emotion recognition.

[1422] (Application example 2)

[1423] 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."

[1424] Conventional systems generate design specifications based on configuration information and parameters automatically collected from multiple nodes, but they are unable to reflect user sentiment, making it difficult to generate flexible design specifications that meet diverse user needs. Furthermore, content distribution services rely on simple recommendation algorithms, which do not adequately examine user sentiment, making it difficult to recommend optimal content. This leads to problems such as reduced user satisfaction.

[1425] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1426] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard materials and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, means for recognizing user emotions using an emotion engine and adjusting the design specifications based on the recognition results, and means for analyzing user emotions and generating an optimal recommendation plan in a content distribution service. This enables the generation of flexible design specifications that reflect user emotions, and further enables optimal content recommendations based on user emotions in the content distribution service.

[1427] A "node" is a general term for a terminal or device that can operate independently on a network and exchange information.

[1428] "Configuration information" is a general term for information and parameters required to control the operation of network devices and terminals.

[1429] A "parameter" is a variable or value that is set to control the behavior of a system or application.

[1430] "Standard documents" refer to technical documents, guidelines, and protocols that are recognized and referenced as standards within an industry.

[1431] The "emotion engine" is a system that applies natural language processing technology to analyze emotions from user input data and provide feedback on the results.

[1432] A "design specification" is a document that describes the design contents, components, operating conditions, etc. of a system or project.

[1433] "Analysis" refers to the process of examining collected data and information in detail and finding meaning.

[1434] "Comments" refers to opinions, impressions, additional information, etc. that users enter through the interface.

[1435] "Additional information" is supplementary information provided by the user in addition to basic parameters and setting information.

[1436] A "content distribution service" is a system that provides digital content such as music, videos, and articles via the Internet.

[1437] A "recommendation plan" is a plan that suggests optimal content based on the preferences and status of each individual user.

[1438] "Final check" is a procedure for checking the contents of the generated design specifications, correcting errors, and ensuring format consistency.

[1439] "Output format" refers to the manner in which generated data or documents are stored, displayed, or presented in a particular format.

[1440] As an embodiment of the present invention, a system will be described in which an emotion engine is combined with a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on the collected information.

[1441] System configuration

[1442] The system mainly consists of a server, a terminal, an emotion engine, and a user. The role of each component is described in detail below.

[1443] server

[1444] The server is responsible for automatically collecting configuration information and parameters from multiple nodes. The collected data is stored in a temporary database. This data is analyzed based on standard documents (e.g., 3GPP and RFCs), and normalization processing is performed to evaluate its conformance. Design specifications are automatically generated based on the evaluation results, and an interface is also provided for reflecting user comments and additional information. By using an emotion engine to recognize user emotions and reflecting the results in the design specifications, it is possible to generate documents that are more flexible and tailored to user needs.

[1445] Terminal

[1446] The terminal provides a user interface through which users can input information and provide feedback. Collection parameters can be entered through the terminal's GUI, and data collection instructions can be sent to the server. After generating the design specifications, users can enter comments and additional information through the terminal, which is then analyzed by the emotion engine.

[1447] Emotion Engine

[1448] The emotion engine analyzes comments and additional information entered by the user on the device and recognizes emotions. The results are fed back to the server, which then adjusts the content of the design specifications. For example, if the user enters "I'm in a hurry," the emotion engine will detect a sense of urgency and adjust the content to prioritize the speed of creating the design specifications.

[1449] User

[1450] Users operate the system through their terminals to provide comments and additional information, and also review the generated design specifications and give their final approval. User feedback is properly analyzed through the emotion engine, improving the completeness of the design specifications.

[1451] Hardware and software used

[1452] Server: Central server for data collection, analysis, and automatic generation of design specifications

[1453] Terminal: A device that provides a user interface (e.g., a smartphone or tablet).

[1454] Emotion engine: Natural language processing engines such as IBM Watson Natural Language Understanding and Google Cloud NLP

[1455] Database: Relational database such as PostgreSQL

[1456] Specific examples

[1457] For example, in a content distribution service, a user may provide feedback on music content by commenting, "I want to relax." The emotion engine analyzes this comment and recognizes the user's desire to relax. Based on the results, the server recommends optimal content (e.g., relaxing music or videos). This process makes it possible to provide more personalized content to users.

[1458] Prompt Sentence Examples

[1459] "If a user enters 'I'm tired' or 'I want to relax' in the comment field, please provide an algorithm that will recommend content based on that. The input is the comment text and its sentiment classification data, and the output is a recommendation."

[1460] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1461] Step 1:

[1462] The server automatically collects configuration information and parameters from multiple nodes using protocols such as API calls, SNMP, and SSH. The data collected from each node is stored in a temporary database. The input is the node's configuration information and parameters, and the output is the raw data stored in the temporary database.

[1463] Step 2:

[1464] The server analyzes the configuration information and parameters stored in the temporary database based on standard documents (e.g., 3GPP or RFC). This analysis process normalizes the data and checks it against the standard documents. The input is the raw data stored in the temporary database, and the output is the normalized data and the conformance evaluation result.

[1465] Step 3:

[1466] The server reads the design specification template based on the analysis results and automatically generates the design specification by embedding the collected data in the appropriate locations within the template. The input is the normalized data and evaluation results, and the output is the automatically generated design specification.

[1467] Step 4:

[1468] The user uses a terminal to check the design specifications and input comments and additional information. This is done through the terminal's GUI interface. The input is the design specifications and the user's comments and additional information, and the output is the user's feedback.

[1469] Step 5:

[1470] The emotion engine analyzes user comments and additional information sent from the device and recognizes emotions. This analysis uses natural language processing technology. The input is the user's comments and additional information, and the output is the emotion recognition results.

[1471] Step 6:

[1472] The server adjusts the design specifications based on feedback from the emotion engine. For example, if the user feels "hurried," it will respond by raising the priority. The input is the emotion recognition results and the design specifications, and the output is the adjusted design specifications.

[1473] Step 7:

[1474] The server operates in the same way in content distribution services, generating an optimal recommendation plan based on comments entered by users. The input is the user's comments and emotion recognition results, and the output is a content recommendation plan.

[1475] Step 8:

[1476] The server performs a final check and formatting, then outputs a design specification or content recommendation plan in a variety of formats, including PDF, Word, and a list of recommended content. The input is the adjusted data, and the output is the final design specification or list of recommended content.

[1477] The above is the relationship between the specific operations at each processing step and the input and output based on the data processing and calculation.

[1478] 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.

[1479] 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.

[1480] 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.

[1481] [Fourth embodiment]

[1482] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1483] 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.

[1484] 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).

[1485] 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.

[1486] 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.

[1487] 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).

[1488] 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.

[1489] 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.

[1490] 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.

[1491] 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.

[1492] 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.

[1493] 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.

[1494] 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."

[1495] This invention is a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on that information. The functions of the system, which consists of three entities: users, terminals, and servers, are explained below.

[1496] Server Features

[1497] Data collection

[1498] The server first obtains a list of nodes to collect from the database. According to that list, it connects to each node and collects configuration information and parameters. Collection methods include SNMP, API calls, and SSH. The collected data is stored in a temporary database.

[1499] Data analysis and comparison with standard data

[1500] The collected data is analyzed based on standard documents (e.g., 3GPP, RFC). During the analysis, the collected data is normalized and compared with the standard documents to identify matches and inconsistencies.

[1501] Automatic generation of design specifications

[1502] The server automatically generates design specifications based on the analysis results. First, it reads a document template that conforms to the standard materials and embeds the collected data in the appropriate locations of the template. In this way, the design specifications are generated.

[1503] Providing a customization interface

[1504] The server provides an interface where the user can input comments and additional information, and when the comments and additional information are obtained from the user, the design specification is adjusted accordingly.

[1505] Final checks and output

[1506] Finally, the server checks the entire generated design specification and makes any necessary corrections. After the check is complete, the design specification is output in a format such as PDF or Word and provided to the user.

[1507] Device Features

[1508] Navigating the User Interface

[1509] The user starts the process of automatically generating design specifications through the GUI on the terminal. First, they input the necessary node information and collection parameters into the terminal and instruct the server to collect data.

[1510] Customized Input

[1511] After the automatic generation of the design specification is completed, the user accesses a screen on their terminal to input comments and additional information, where they can enter specific requirements and conditions and send them to the server.

[1512] User Roles

[1513] System Check

[1514] The user reviews the design specifications provided by the server, checks whether there are any problems with the content, and, if necessary, adds comments or requests corrections.

[1515] Final Approval

[1516] The user reviews the final specifications and, if satisfied, approves them. The approved design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[1517] Specific examples

[1518] As a concrete example, let's assume that a telecommunications carrier introduces a new base station (node) and automatically generates its design specifications. In this case, the server collects configuration information from existing base stations in the carrier's network. The collected data is analyzed based on 3GPP standard documents, and the design specifications are automatically generated based on the results. The user enters comments from their device regarding special requirements for the base station and any areas that need adjustment, and the server reflects these comments and modifies the specifications. After a final check, the design specifications are output in PDF format and provided to the user. This entire process streamlines design work and reduces the risk of accidents caused by design errors.

[1519] The processing flow will be explained below.

[1520] Server Processing Steps

[1521] Step 1: Get the node list

[1522] The server retrieves a list of nodes to connect to from a database, which contains the information needed to connect to the nodes, such as IP addresses and authentication information.

[1523] Step 2: Connect to the node

[1524] The server connects to each node in turn based on the node list, using methods such as SNMP, API calls, and SSH.

[1525] Step 3: Data collection

[1526] The server retrieves configuration information and parameters from the connected nodes, including the node's operating status, settings, sensor data, etc. This collected data is temporarily stored in a database.

[1527] Step 4: Loading the standard materials

[1528] The server loads standard documents such as 3GPP and RFCs and prepares them for comparison with the collected data, thereby clarifying the reference documents and guidelines.

[1529] Step 5: Data Preprocessing

[1530] The server preprocesses the collected data, normalizing it and imputing missing values. Preprocessing ensures data integrity and makes analysis easier.

[1531] Step 6: Data analysis and comparison with standard reference materials

[1532] The server then compares the pre-processed data against the standard, evaluating how well the data conforms to the standard and identifying any areas where it does not conform.

[1533] Step 7: Load the design specification template

[1534] The server loads a standard-compliant design specification template, which includes basic items and formats.

[1535] Step 8: Data Embedding

[1536] Based on the analysis results, the server embeds the collected data in the appropriate locations of the design specification template, thereby forming the basis of the design specification.

[1537] Step 9: Providing a Comment Interface

[1538] The server provides an interface for the user to enter comments and additional information, and adjusts the design specification according to the user's input.

[1539] Step 10: Final checks and adjustments

[1540] The server performs a final check of the generated design specifications, adjusting the layout and format, correcting errors, and so on.

[1541] Step 11: Output design specifications

[1542] The server outputs the final design specifications in PDF or Word format and provides them to the user, who can then share them with the project team and other stakeholders.

[1543] Terminal processing steps

[1544] Step 1: Launch the user interface

[1545] The user starts the GUI on the terminal and accesses the screen for automatically generating design specifications.

[1546] Step 2: Enter node information

[1547] The user inputs information about the target node and collection parameters into the terminal, including the node's IP address, authentication information, and collection items.

[1548] Step 3: Data collection instructions

[1549] The user issues an instruction to the server to collect the setting information and parameters of the specified node. This instruction is sent to the server, and data collection begins.

[1550] Step 4: Check the retrieved data

[1551] The user can check some of the collected data to see if specific data has been acquired. If there is a problem, the user can issue a collection command to the server again.

[1552] Step 5: Enter customization comments

[1553] The user operates an interface to enter any comments or special requirements they wish to add to the design specification, including requests for modifications based on specific conditions or requirements.

[1554] Step 6: Submit your comment

[1555] User comments and correction requests are sent from the terminal to the server, which receives this information and adjusts the design specifications accordingly.

[1556] User processing steps

[1557] Step 1: Review the design specifications

[1558] The user checks the design specifications provided by the server on their terminal, carefully examining the content to ensure there are no problems.

[1559] Step 2: Request additional revisions

[1560] If the user finds any deficiencies or errors in the design specifications, they can enter comments or correction requests and send them to the server, which then receives them and readjusts the specifications.

[1561] Step 3: Final Approval

[1562] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[1563] These are the specific processing steps for the server, terminal, and user. This process makes the creation of design specifications more efficient and reduces the risk of system accidents caused by design errors.

[1564] Example 1

[1565] 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."

[1566] In modern network systems, collecting configuration information and parameters from multiple nodes and creating design specifications based on that information is extremely complex and time-consuming. Furthermore, accurately reflecting the analysis results of the collected data requires specialized knowledge, which increases the risk of errors and inconsistencies. Furthermore, incorporating user comments and additional information into design specifications is often done manually, which is inefficient. Therefore, there is a need for a method to automate these processes and efficiently create high-quality design specifications.

[1567] 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.

[1568] In this invention, the server includes: means for automatically collecting setting information and parameters from multiple nodes; means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability; means for automatically generating design specifications based on the analysis results; means for acquiring comments and additional information from system users and reflecting them in the design specifications; means for performing a final check of the generated design specifications and converting them into an output format for provision; means for starting data collection and generation of design specifications through a user interface; and means for generating design specifications based on a template. This automates the entire process of collecting setting information from multiple nodes, comparing it with standard documents, automatically generating design specifications, incorporating user feedback, and finally outputting the document, enabling efficient creation of high-quality design specifications.

[1569] A "server" is a computer system that provides services and data processing to multiple clients over a network.

[1570] A "node" is an individual device or equipment connected to a network, including routers, switches, base stations, etc.

[1571] "Configuration information" refers to parameters and setting values ​​required to determine the operation and functions of a node.

[1572] A "parameter" is a numerical value or setting used to control the operation of a system or node.

[1573] "Standards documents" are documents that provide industry standards or guidelines, such as 3GPP and RFCs.

[1574] "Analysis" is the process of evaluating collected data against normative references and identifying matches and inconsistencies.

[1575] "Conformity" is an index that indicates the degree to which the collected setting information and parameters match the standard data.

[1576] A "design specification" is a document that details the design requirements and specifications of a system or equipment, and is used when introducing or building it.

[1577] "Automatic generation" is the process of generating specific documents or data programmatically without human intervention.

[1578] "System users" are the personnel or end users who operate the system, collect configuration information, add comments, and review and approve design specifications.

[1579] "Comments" are opinions, suggestions, and small corrections that system users add to the design specifications.

[1580] "Additional information" refers to new data or requirements to be included in the design specification.

[1581] "Final check" is the process of checking all the contents of the generated design specifications and correcting any errors or incomplete parts.

[1582] "Output format" refers to the file format, such as PDF or Word, used to save and display the generated design specifications.

[1583] A "user interface" is an interface through which a system user operates the system via a GUI, inputting configuration information and instructing the generation of design specifications.

[1584] A "template" is a predefined format that defines the format and structure of a design specification based on standard documents or guidelines.

[1585] This invention is a system that automatically collects setting information and parameters from multiple nodes and automatically generates design specifications based on the collected information. How this system can be implemented will be described below.

[1586] Server Features

[1587] Data collection

[1588] The server first obtains a list of nodes to collect from the database. Based on that list, it connects to each node and collects configuration information and parameters. Collection methods include SNMP (Simple Network Management Protocol), API calls, and SSH (Secure Shell). For example, the server connects via SNMP to a node with an IP address of 192.168.1.1 to collect configuration information. The collected data is saved in a temporary database.

[1589] Data analysis and comparison with standard data

[1590] The server analyzes the collected data based on standards such as 3GPP and RFCs. During the analysis, the collected data is normalized and compared with the standards to identify matching and non-matching parts. For example, it checks whether the node's interface settings comply with the 3GPP standard.

[1591] Automatic generation of design specifications

[1592] The server automatically generates design specifications based on the analysis results. This is done by loading a document template that conforms to the standard and embedding the collected data in the appropriate locations. For example, the server embeds the previously collected interface configuration information in the "Network Settings" section of the template.

[1593] Providing a customization interface

[1594] The server provides an interface where users can enter comments and additional information. The server acquires the user's comments and additional information and readjusts the design specifications based on them. For example, if a user enters a comment such as "I would like you to change a specific setting on the base station," the server will reflect that comment and modify the specifications.

[1595] Final checks and output

[1596] The server performs a final check, makes any necessary corrections, and then outputs the design specification in PDF or Word format and provides it to the user. For example, the server may find in the final check that "the section headings do not match the standards," correct them, and then output them in PDF format.

[1597] Device Features

[1598] Navigating the User Interface

[1599] The user starts the automatic generation process of the design specification using the terminal's GUI (Graphical User Interface). The user inputs node information and collection parameters into the terminal and instructs the server to collect data. For example, the user inputs "Collect configuration information for a new base station" into the GUI and presses the send button, which sends this instruction from the terminal to the server.

[1600] Customized Input

[1601] After the automatic generation of the design specification is completed, the user accesses a screen on the terminal to input comments and additional information. Here, the user inputs specific requirements and conditions, which are then sent to the server. For example, the user inputs specific requirements for configuration information and sends them from the terminal to the server.

[1602] User Roles

[1603] System Check

[1604] The user reviews the design specifications provided by the server and checks whether there are any problems with the content. If necessary, the user can add comments or request corrections. For example, if a user who has checked the design specifications feels that a certain setting is inappropriate, they can input that comment.

[1605] Final Approval

[1606] The user performs a final check and, if approved, the design specifications are shared with the project team and other stakeholders, and the installation and construction of the equipment begins. For example, if the user performs a final check and determines that there are no problems with the contents, they press the approval button to approve the design specifications.

[1607] Specific examples

[1608] We will explain the case where a telecommunications carrier introduces a new base station (node) and automatically generates its design specifications as a concrete example.

[1609] 1. Collection preparation

[1610] The server retrieves a list of existing base stations from the database. For example, the list contains the IP addresses 192.168.1.1 and 192.168.1.2.

[1611] 2. Data Collection

[1612] The server connects to each base station based on the list via SNMP and collects the configuration information. The collected information is stored in a temporary database. For example, the interface configuration is collected.

[1613] 3. Data Analysis

[1614] The server analyzes the collected information based on the 3GPP standard documents and checks whether the settings comply with the standard, for example, whether the interface settings are consistent with the standard.

[1615] 4. Generate design specifications

[1616] The server automatically generates the design specification by embedding it in a template based on the analysis results. For example, it adds collected information to the "Network Settings" section.

[1617] 5. Customizable interface provided

[1618] The user can input comments and additional information into the generated design specification through the GUI of the terminal. For example, the user can input a comment saying, "There are special requirements."

[1619] 6. Final Check

[1620] The server then modifies the design specifications based on the user's comments and performs a final check, for example, readjusting the configuration information based on the user's comments.

[1621] 7. Output of design specifications

[1622] The server outputs the design specification in PDF format and provides it to the user, who then performs a final check and approves it.

[1623] 8. Project Start

[1624] The approved design specifications will be shared with the project team and the installation and construction of the new base station will commence.

[1625] Prompt Sentence Examples

[1626] "Please explain how a telecommunications company automatically generates design specifications for new base stations. Please provide a detailed description of the process, including the specific steps for collecting data, analyzing the data, filling templates, incorporating user input, and finally outputting it."

[1627] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1628] Step 1:

[1629] Getting a list of nodes

[1630] The server retrieves a list of nodes to collect from a database. This list contains the IP addresses and identification information of each node in the network. The input is the list of nodes to retrieve from the database, and the output is a list of nodes. For example, the list might contain IP addresses 192.168.1.1 and 192.168.1.2.

[1631] Step 2:

[1632] Connecting to a node and collecting data

[1633] Based on the list of nodes obtained, the server connects to each node to collect configuration information and parameters. Connection methods include SNMP, API calls, and SSH. The input is the node list, and the output is the configuration information obtained from the nodes. For example, the server connects to the node at 192.168.1.1 via SNMP and collects configuration information. The collected data is stored in a temporary database.

[1634] Step 3:

[1635] Data normalization

[1636] The server normalizes the collected configuration information and parameters. During the normalization process, the data format is unified and unnecessary data is deleted. The input is the collected configuration information, and the output is normalized data. For example, the interface settings in the data are converted to a standard format.

[1637] Step 4:

[1638] Comparison with standard materials

[1639] The server compares the normalized data with standards such as 3GPP and RFCs to identify matches and mismatches. The input is the normalized data, and the output is information about matches and mismatches with the standards. For example, it checks whether an interface configuration is in accordance with the 3GPP standard.

[1640] Step 5:

[1641] Loading design specification templates

[1642] The server loads a pre-prepared document template. The template contains standard formats and sections. The input is a document template, and the output is the prepared template. For example, a design specification format that conforms to a standard document is loaded.

[1643] Step 6:

[1644] Embedding analysis results into data

[1645] The server embeds the analysis results in the appropriate position in the template to generate a design specification. The input is the analysis results and the document template, and the output is the design specification. For example, the analysis results are added to the "Network Settings" section of the template.

[1646] Step 7:

[1647] User Interface Display

[1648] The server displays an interface that allows the user to enter comments and additional information. The input is the user's comments and additional information, and the output is an updated design specification. For example, the user enters a comment such as "I would like you to change a specific setting on the base station."

[1649] Step 8:

[1650] Reflecting user comments

[1651] The server readjusts the design specification by reflecting comments and additional information obtained from the user. The input is the user's comments and additional information, and the output is an updated design specification. For example, the server modifies the configuration information based on the user's comments.

[1652] Step 9:

[1653] Final Check

[1654] The server performs a final check of the entire design specification and makes any necessary corrections. The input is the design specification, and the output is the final design specification. For example, it checks and corrects that "the section headings do not match the standards."

[1655] Step 10:

[1656] Design specification output

[1657] The server outputs the design specification after the final check in PDF or Word format and provides it to the user. The input is the design specification after the final check, and the output is a document in PDF or Word format. For example, the design specification is output in PDF format.

[1658] (Application example 1)

[1659] 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."

[1660] Modern production facilities are required to collect configuration information and parameters from multiple nodes and automatically generate design specifications and technical documents based on that information. However, previous methods have made it difficult to accurately evaluate and analyze the suitability of collected data and add comments and corrections in real time. Furthermore, the lack of efficient data collection and verification using smart devices has hindered work efficiency. This has led to issues such as complex production line management and maintenance work, and an increased risk of errors.

[1661] 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.

[1662] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, and means for collecting operational setting information and maintenance information for factory equipment and adding real-time comments to the automatically generated technical documents. This makes it possible to collect, check, and modify operational setting information and maintenance information for factory equipment in real time via smart devices.

[1663] A "node" is a piece of electronic equipment that transmits, receives, or processes data within a network.

[1664] "Setting information" refers to parameters and configuration information required to control the operation and functions of an electronic device.

[1665] A "parameter" is a variable used to determine a particular characteristic or behavior of a system or device.

[1666] A "standard document" is a document that sets out generally accepted guidelines or protocols in a particular field.

[1667] "Analysis" is the process of examining data in detail to understand its meaning and structure.

[1668] "Conformance" is the state of conformance to certain criteria or conditions.

[1669] A "design specification" is a document that provides detailed descriptions and instructions for the design of a system.

[1670] "Technical documents" are documents that provide specialized knowledge and information.

[1671] "Comments" are annotations that add opinions or explanations to a document.

[1672] "Additional information" is new data or knowledge provided to supplement existing information.

[1673] A "smart device" is an electronic device with advanced computing power and internet connectivity.

[1674] "Real-time" means that data is collected and processed immediately, without delay.

[1675] This invention is a system that collects operational setting information and maintenance information for factory equipment and automatically generates technical documents based on that information. The functions of the system, which consists of three entities: users, terminals, and servers, are explained below.

[1676] Server Features

[1677] Data collection

[1678] The server first obtains a list of nodes from which data is to be collected from the database. It then connects to each node (in this case, factory equipment) according to that list and collects configuration information and parameters. Collection methods include REST API calls, SNMP, and SSH. The collected data is then stored in a temporary database.

[1679] Data analysis and comparison with standard data

[1680] The collected data is analyzed based on standard documents (e.g., 3GPP, RFC). During the analysis, the collected data is normalized and compared with the standard documents to identify matches and inconsistencies.

[1681] Automatic generation of technical documents

[1682] The server automatically generates technical documents based on the analysis results. First, it reads a document template that conforms to the standard documents and embeds the collected data in the appropriate locations of the template. In this way, the technical documents are generated.

[1683] Providing a customization interface

[1684] The server provides an interface where users can enter comments and additional information, and when the comments and additional information are obtained from the users, the technical materials are adjusted accordingly.

[1685] Final checks and output

[1686] Finally, the server checks the entire generated technical document and makes any necessary corrections. After the check is complete, the technical document is output in a format such as PDF or Word and provided to the user.

[1687] Device Features

[1688] Navigating the User Interface

[1689] The user starts the process of automatically generating technical documentation through the GUI on the terminal. First, they input the necessary node information and collection parameters (operation setting information and maintenance information) into the terminal, and then instruct the server to collect data.

[1690] Customized Input

[1691] After the automatic generation of technical documents is completed, the user can access a screen on their terminal to input comments and additional information, where they can enter specific requirements and conditions and send them to the server.

[1692] User Roles

[1693] System Check

[1694] The user reviews the technical documents provided by the server, checks whether there are any problems with the contents, and makes comments or requests for corrections if necessary.

[1695] Final Approval

[1696] The user reviews the final technical documentation and, if satisfied with the content, approves it. The approved technical documentation is shared with the work team and other relevant parties, and operation and maintenance of the equipment begins.

[1697] Specific examples

[1698] As a concrete example, let's assume that a manufacturing plant introduces a new robot (node) and automatically generates its technical documentation. The server collects configuration information from existing equipment in the manufacturing plant. The collected data is analyzed based on standard documentation, and technical documentation is automatically generated based on the results. The user enters comments from their terminal regarding special requirements or areas that require adjustment, and the server reflects these comments and modifies the documentation. After a final check, the technical documentation is output in PDF format and provided to the user. This process makes the task of creating technical documentation more efficient and reduces the risk of accidents due to work errors.

[1699] Usage example

[1700] For example, a manufacturing plant might use a smartphone to collect operational settings and maintenance data for a newly installed robot. When a worker connects to the robot using a smartphone app, the server collects operational parameters via an API. The collected data is analyzed based on standard documents, and the necessary technical documents are automatically generated. The worker can then view the documents in real time through smart glasses and add any necessary comments or corrections.

[1701] Prompt Sentence Examples

[1702] "Please develop an application that collects the setting information and operating parameters of factory equipment and automatically generates technical documents based on the analysis results. The documents should be based on standard documents and contain accurate information. It should also have a function that allows workers to check them in real time via smart devices and add comments or correction requests."

[1703] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1704] Step 1: Data collection instructions

[1705] The user starts the automatic generation process of technical documents through a GUI on the terminal. The user inputs the necessary node information and collection parameters (e.g., robot operation settings and maintenance information) into the terminal and sends a collection instruction to the server. The input data includes a list of nodes to be collected and the collection parameters.

[1706] Step 2: Data collection

[1707] The server connects to each node based on the node list sent from the terminal. Specifically, it collects configuration information and parameters using methods such as REST API calls, SNMP, and SSH. The collected data is saved in a temporary database. The input is the node list and collected parameters, and the output is the collected configuration information and parameters.

[1708] Step 3: Data analysis and normalization

[1709] The server analyzes the data stored in the temporary database, normalizes the collected data based on standard documents (e.g., 3GPP, RFC), and evaluates the conformance of the collected data. During the normalization process, the input data is unified into a specified format. The input is the configuration information and parameters in the temporary database, and the output is the normalized data and conformance evaluation results.

[1710] Step 4: Automatic generation of technical documentation

[1711] The server automatically generates technical documents based on the analysis results. It loads a pre-defined document template and embeds the analyzed data in the appropriate location in the template. An initial version of the generated technical documents is created. The input is the normalized data and conformance assessment results, and the output is the initial version of the technical documents.

[1712] Step 5: Get user comments

[1713] Through the terminal, the user reviews the initial version of the technical document. If necessary, they enter comments and additional information, which is then sent to the server. This information is used to update the technical document. The input is the user's comments and additional information, and the output is the updated technical document.

[1714] Step 6: Final check of technical documentation

[1715] The server readjusts the technical documentation based on comments and additional information provided by the user. It then performs a final check of the entire technical documentation and makes any necessary corrections. The input is comments and additional information from the user, and the output is the final version of the technical documentation.

[1716] Step 7: Output technical documents

[1717] Finally, the server converts the final version of the technical document into the specified format, such as PDF or Word, and sends it to the terminal. The user can then view the technical document on the terminal and take any necessary actions. The input is the final version of the technical document, and the output is the technical document converted into the specified format.

[1718] 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.

[1719] This invention combines a system that collects setting information and parameters from multiple nodes and automatically generates design specifications based on them with an emotion engine that recognizes user emotions.The functions of this system, which consists of four entities: the user, the terminal, the server, and the emotion engine, are described in detail below.

[1720] Server Features

[1721] Data collection

[1722] The server retrieves a list of target nodes from the database and connects to each node based on that list. Connection methods include SNMP, API calls, and SSH. The configuration information and parameters retrieved from the nodes are saved in a temporary database.

[1723] Data analysis and comparison with standard data

[1724] The collected data is analyzed based on standards (e.g., 3GPP, RFC). The data is normalized and compared to the standards to assess conformance. Non-conformances are identified, and necessary corrections are made clear.

[1725] Automatic generation of design specifications

[1726] The server automatically generates a design specification template based on the analysis results by loading the collected data into the appropriate locations within the template. This template conforms to standard documents, with various items neatly arranged.

[1727] Emotion engine collaboration

[1728] The server recognizes the user's emotions using an emotion engine when receiving comments or additional information from the user. The recognized emotion data is fed back into the design specification generation process, and adjustments are made based on the specific emotion.

[1729] Providing a customization interface

[1730] The server provides an interface where users can enter comments and additional information. The data entered through this interface is analyzed through the emotion engine and reflected in the design specifications.

[1731] Final checks and output

[1732] The generated design specifications undergo a final check, with adjustments made to the layout and format, corrections of errors, etc. The final design specifications are output in PDF or Word format and provided to the user.

[1733] Device Features

[1734] Navigating the User Interface

[1735] The user starts the process of automatically generating design specifications using the GUI on the terminal. They input the target node information and collection parameters into the terminal and instruct the server to collect data.

[1736] Enter customization comments

[1737] After the automatic generation of the design specification is completed, the user operates the interface to input comments and additional information. The information entered by the user is analyzed by the emotion engine and processed on the server.

[1738] Emotion Engine Functions

[1739] emotion recognition

[1740] The emotion engine analyzes comments and additional information entered by users and recognizes their emotions. This recognition is performed using natural language processing technology. For example, it analyzes the user's sense of urgency from a comment such as "I'm in a hurry."

[1741] Feedback and Adjustments

[1742] The emotion engine feeds back the recognized emotion, and the server adjusts the content of the design specification. For example, if the user expresses dissatisfaction, it can provide additional explanation.

[1743] User Roles

[1744] System Check

[1745] The user checks the design specifications provided by the server and carefully examines the content to ensure there are no problems. If there are any deficiencies or errors, the user can enter comments or correction requests again.

[1746] Final Approval

[1747] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[1748] Specific examples

[1749] As a concrete example, consider a scenario in which a company introduces a new IT infrastructure (node). In this case, the server collects configuration information from existing systems and analyzes it in accordance with 3GPP and RFC standards. Once the design specifications are automatically generated, the user enters comments and additional information from their terminal. The emotion engine analyzes the user's input and recognizes their emotions. For example, if the user enters "needed immediately," the emotion engine senses the sense of urgency and adjusts the priority of the design specifications. Finally, the design specifications are output in PDF format and provided to the relevant parties. This process improves the efficiency of design work and enables flexible responses to user emotions.

[1750] The processing flow will be explained below.

[1751] Server Processing Steps

[1752] Step 1: Get the node list

[1753] The server gets a list of nodes to connect to from a database, which includes IP addresses, authentication information, etc.

[1754] Step 2: Connect to the node

[1755] The server connects to each node in turn based on the node list, using methods such as SNMP, API calls, and SSH.

[1756] Step 3: Data collection

[1757] The server retrieves configuration information and parameters from the connected nodes, including the node's operating status, settings, sensor data, etc. This collected data is temporarily stored in a database.

[1758] Step 4: Loading the standard materials

[1759] The server loads standard documents such as 3GPP and RFCs and prepares them for comparison with the collected data, thereby clarifying the reference documents and guidelines.

[1760] Step 5: Data Preprocessing

[1761] The server preprocesses the collected data, normalizing it and imputing missing values. Preprocessing ensures data integrity and makes analysis easier.

[1762] Step 6: Data analysis and comparison with standard reference materials

[1763] The server then compares the pre-processed data against the standard, evaluating how well the data conforms to the standard and identifying any areas where it does not conform.

[1764] Step 7: Load the design specification template

[1765] The server loads a standard-compliant design specification template, which includes basic items and formats.

[1766] Step 8: Data Embedding

[1767] Based on the analysis results, the server embeds the collected data in the appropriate locations of the design specification template, thereby forming the basis of the design specification.

[1768] Step 9: Providing a Comment Interface

[1769] The server provides an interface for users to input comments and additional information, adjusts the design specifications according to the user's input, and analyzes the user's emotions through an emotion engine and provides feedback based on the results.

[1770] Step 10: Emotion Recognition

[1771] The server analyzes the user's input through an emotion engine to recognize the user's emotions, for example, detecting a sense of urgency in the case of an urgent request.

[1772] Step 11: Refining the design specifications

[1773] The server readjusts the design specifications based on feedback from the emotion engine, adding necessary explanations and alerts to reflect the user's emotional data.

[1774] Step 12: Final checks and adjustments

[1775] The server performs a final check of the generated design specifications, adjusting the layout and format, correcting errors, and so on.

[1776] Step 13: Output design specifications

[1777] The server outputs the final design specifications in PDF or Word format and provides them to the user, who can then share them with the project team and other stakeholders.

[1778] Terminal processing steps

[1779] Step 1: Launch the user interface

[1780] The user starts the GUI on the terminal and accesses the screen for automatically generating design specifications.

[1781] Step 2: Enter node information

[1782] The user inputs information about the target node and collection parameters into the terminal, including the node's IP address, authentication information, and collection items.

[1783] Step 3: Data collection instructions

[1784] The user issues an instruction to the server to collect the setting information and parameters of the specified node. This instruction is sent to the server, and data collection begins.

[1785] Step 4: Check the retrieved data

[1786] The user can check some of the collected data to see if specific data has been acquired. If there is a problem, the user can issue a collection command to the server again.

[1787] Step 5: Enter customization comments

[1788] After the automatic generation of the design specification is complete, the user operates an interface to enter comments and additional information, including modification requests based on specific conditions or requirements.

[1789] Step 6: Submit your comment

[1790] User comments and correction requests are sent from the device to the server, which receives this information and adjusts the design specifications. The emotion engine analyzes the user's emotions.

[1791] Emotion Engine Processing Steps

[1792] Step 1: Get user comments

[1793] The emotion engine receives user comments and additional information from the server.

[1794] Step 2: Sentiment Analysis

[1795] The emotion engine uses natural language processing technology to analyze user comments and recognize their emotions, for example, detecting a sense of urgency from a comment like "I'm in a hurry."

[1796] Step 3: Feedback on results

[1797] The recognized emotion data is fed back to the server, and this data is reflected in adjustments to the design specifications.

[1798] User processing steps

[1799] Step 1: Review the design specifications

[1800] The user checks the design specifications provided by the server on their terminal, carefully examining the content to ensure there are no problems.

[1801] Step 2: Request additional revisions

[1802] If the user finds any deficiencies or errors in the design specifications, they can enter comments or correction requests and send them to the server, which then receives them and readjusts the specifications.

[1803] Step 3: Final Approval

[1804] The user reviews the final specifications and, if satisfied, approves them. After approval, the design specifications are shared with the project team and other stakeholders, and installation and construction of the equipment begins.

[1805] These are the specific processing steps for the server, terminal, user, and emotion engine. This process makes the creation of design specifications more efficient and enables flexible designs that respond to user emotions.

[1806] Example 2

[1807] 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."

[1808] In today's complex network systems, it is necessary to collect configuration information and parameters from numerous nodes and, based on this information, create design specifications that conform to standard documents. However, evaluating the conformance of collected data and automatically generating design specifications requires a great deal of time and effort, and there are also increasing cases where adjustments based on user emotions are required. Conventional systems have difficulty achieving these processes efficiently and in a user-friendly manner, and systems that include emotion recognition and feedback have particular limitations. Therefore, there is a need for a multifunctional and efficient system that can collect data, analyze it, generate design specifications, and recognize emotions.

[1809] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1810] In this invention, the server includes means for automatically collecting setting information and parameters from multiple nodes, means for analyzing the collected setting information and parameters based on standard documents and evaluating their suitability, means for automatically generating design specifications based on the analysis results, means for acquiring comments and additional information from system users and reflecting them in the design specifications, means for performing a final check of the generated design specifications and converting them into an output format for provision, and means for recognizing the emotions of system users and feeding back the emotion data to the design specification creation process. This makes it possible to consistently and efficiently perform the process from data collection to the generation of design specifications, and also realize flexible responses to user emotions.

[1811] A "node" is an independent device or computer system that exists on a communication network.

[1812] "Setting information" refers to various setting parameters and configuration data that define the operation of a node.

[1813] A "parameter" is a data value that indicates the operating conditions or operating state of a system or node.

[1814] A "standard document" is a document that represents a generally accepted technical code or standard.

[1815] "Conformity" refers to the degree to which collected data corresponds to standard data.

[1816] A "design specification" is a document that describes in detail the design of a system or node.

[1817] A "system user" is a user who operates the system, inputs data, and checks results.

[1818] "Emotion" refers to the psychological state and mood of the system user.

[1819] "Comments" are specific opinions or suggestions provided by system users regarding the system.

[1820] "Final check" is the process of finally inspecting the content and format of the generated design specification.

[1821] "Output format" refers to the type of document format (e.g., PDF or Word) in which the design specification is provided.

[1822] "Emotion recognition" is a technology that analyzes and understands the psychological state of a system user based on their input.

[1823] "Feedback" refers to the reuse of analysis results and evaluation information within the system to adjust and improve processes.

[1824] This invention is a system that automatically collects configuration information and parameters from multiple nodes and generates design specifications based on them. This system also includes a function to recognize and provide feedback to users' emotions. Below, we will explain in detail how the invention is implemented by the server, terminal, and user.

[1825] Server processing

[1826] Data collection

[1827] The server retrieves a list of nodes to collect from an SQL database. This is done using a standard SQL query and stores the node list in memory. It then connects to each node based on the list and retrieves configuration information and parameters. This connection method can be SNMP (Simple Network Management Protocol), API calls, or SSH (Secure Shell Protocol). The retrieved data is temporarily stored in a database such as Redis.

[1828] Data analysis and comparison with standard data

[1829] The server analyzes the collected data based on standard documents such as 3GPP and RFC. It uses Python regular expressions (re library) for data normalization. Based on the analysis results, it evaluates conformance and identifies non-conforming parts.

[1830] Automatic generation of design specifications

[1831] The server reads the design specification template (Markdown or LaTeX format) based on the analysis results. It uses Jinja2 as the template engine and automatically generates the design specification by embedding configuration information and parameters in the appropriate places.

[1832] Emotion engine collaboration

[1833] When collecting comments and additional information from users, the server uses an emotion eng...

Claims

1. A means for automatically collecting configuration information and parameters from multiple nodes; A means for analyzing the collected setting information and parameters based on standard materials and evaluating their suitability; A means for automatically generating a design specification based on the analysis results; A means of obtaining comments and additional information from system users and reflecting them in the design specifications, and A means for performing a final check on the generated design specification, converting it into an output format, and providing it; A system including:

2. 2. The system of claim 1, wherein documents including 3GPP and RFC are used as standard materials.

3. 2. The system according to claim 1, wherein natural language processing technology is used to obtain comments and additional information.

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