system

Abstract

Provide a system. [Solution] means for accepting input from a user; means for analyzing the problem information input by the user; a means for searching past data and radio equipment specification data based on the analyzed problem information; means for presenting highly relevant information to a user based on the search results; means for retrieving further data and providing appropriate answers based on the user's follow-up questions; A means for updating the results of troubleshooting to a database; A system including:

Description

[Technical Field]

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

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

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

[0004] patent specification

[0005] Currently, when responding to base station failures, if a simple reset does not restore the system, a large number of resources are required, and identifying the cause of the problem is becoming more difficult every year. Furthermore, due to personnel changes caused by transfers, it is difficult to pass on skills, making it difficult to respond effectively. To solve this issue, a system that can quickly and efficiently identify the cause of the failure and support engineers is needed. [Means for solving the problem]

[0006] The present invention solves the above-mentioned problems by providing a system including: means for accepting input from a user; means for analyzing problem information input by the user; means for searching past data and radio specification data based on the analyzed problem information; means for presenting highly relevant information to the user based on the search results; means for searching further data and providing appropriate answers based on additional questions from the user; and means for updating a database with the results of troubleshooting.

[0007] ---

[0008] A "user" is a person who operates the system to handle base station failures.

[0009] The "means for accepting input" is a device or interface for inputting fault information or questions from the user.

[0010] "Problem information" is data or status reports entered by the user regarding base station failures.

[0011] The "analyzing means" is a device or program that analyzes the input problem information and extracts keywords and phrases.

[0012] A "searching means" is a device or algorithm that searches the database based on analyzed keywords or phrases.

[0013] The "database" is a recording system that stores information such as past troubleshooting history and radio equipment specifications.

[0014] "Highly relevant information" is information from the retrieved data that is likely to be useful in solving the current problem.

[0015] The "presentation means" refers to a device or method that displays search results and solutions to the user.

[0016] A "follow-up question" is data that a user enters to request more specific information or guidance.

[0017] A "means for providing an answer" is a device or algorithm that provides an appropriate answer to the user based on the further retrieved information.

[0018] "Results of troubleshooting" refers to a report on the troubleshooting measures that the user actually took and the results of those measures.

[0019] The "means for updating the database" is a device or program that adds new troubleshooting results to the existing database and updates the records.

[0020] --- [Brief explanation of the drawings]

[0021] [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 illustrating 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

[0022] 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.

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

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

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

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0036] 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.

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

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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."

[0042] ---

[0043] MODE FOR CARRYING OUT THE INVENTION

[0044] The system of the present invention is a support system that enables users to quickly and effectively deal with base station failures. A specific embodiment of this system will be described below.

[0045] The system includes the following components:

[0046] 1. User Interface (Terminal)

[0047] 2. Server

[0048] 3. Database

[0049] 1. User Input

[0050] Users log in to the system from their devices to troubleshoot base station failures. After logging in, users can enter the current status of the base station failure in chat format. For example, a problem such as "Base station A is not responding" can be reported.

[0051] 2. Server analysis

[0052] The device sends the entered information to the server. The server receives this information, and an analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted.

[0053] 3. Searching for data

[0054] The server uses the extracted keywords and phrases to search a database containing past troubleshooting history and wireless device specifications, collecting related past failure cases and technical information.

[0055] 4. Information provision

[0056] The server then provides the user with appropriate information in chat format based on the search results. For example, specific advice such as "In similar past cases, the cause was a power supply unit failure, so we recommend checking the operation of the power supply unit" is provided.

[0057] 5. Obtaining additional information

[0058] If the user needs more information, they can enter a follow-up question, such as "How do I check the power supply unit?" The device sends this question to the server, which again searches the database and generates an appropriate answer.

[0059] 6. Troubleshooting and updating the database

[0060] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user may enter information such as "I replaced the power supply unit and the problem was resolved." The server receives this information and records it in the database as a new troubleshooting result.

[0061] Specific examples

[0062] Case 1: If a connection loss occurs at base station B, the user can enter "base station B connection loss" and the server will search for past connection loss cases and suggest that "a similar case occurred after a firmware update and was resolved by rebooting the device." The user attempts to reboot the device and the problem is resolved.

[0063] Case 2: If base station C shows an abnormal flashing lamp, the user inputs "Base station C, abnormal flashing lamp." The server checks the meaning of the flashing lamp in the radio specifications and responds, "There is a possibility of an abnormal voltage. We recommend checking the voltage." The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[0064] This invention allows users to quickly and efficiently deal with base station failures, and helps to solve the problem of skill transfer due to personnel changes.

[0065] The processing flow will be explained below.

[0066] ---

[0067] Processing Steps

[0068] Step 1:

[0069] User: Enter your username and password to log into the system from a terminal.

[0070] Terminal: Sends authentication information (username and password) to the server.

[0071] Server: Checks the authentication information against the database, and if authentication is successful, sends the user a login success message and provides a chat entry screen.

[0072] Step 2:

[0073] User: Enter details of the base station problem in chat format (e.g., "Base station A is not responding").

[0074] Terminal: Sends typed chat messages to the server.

[0075] Server: Receives the problem details and sends them to the text analysis engine.

[0076] Step 3:

[0077] Server: A text analysis engine analyzes the outage details and extracts important keywords and phrases (e.g., "Base Station A" or "Not Responding").

[0078] Server: Using the extracted keywords and phrases, search the database of past fault responses and the database of radio equipment specifications.

[0079] Step 4:

[0080] Server: Filter search results to find information that is most relevant to the current problem (e.g., "power supply unit failure case").

[0081] Server: Send relevant information and recommended actions to the user via chat (e.g. "We recommend checking the power supply unit's operation").

[0082] Step 5:

[0083] User: Takes action based on the server's suggestion (e.g., "Check the power supply unit").

[0084] User: If more information is needed, enter further details in the chat (e.g. "How do I check my power supply unit?").

[0085] Terminal: Sends a follow-up question to the server.

[0086] Server: Receives additional questions, searches the database again, generates appropriate answers, and sends them via chat.

[0087] Step 6:

[0088] User: Continue troubleshooting based on the information provided, and when the problem is resolved, report the result to the system via chat (e.g., "Replaced the power supply unit and recovered").

[0089] Terminal: Sends the troubleshooting results to the server.

[0090] Server: Analyzes the received response results and records them in a database (e.g., "A reboot was required due to a power supply unit failure").

[0091] Step 7:

[0092] User: After the troubleshooting is completed and the report is complete, log out.

[0093] Terminal: Sends a logout request to the server.

[0094] Server: End the user session and display a logout complete message.

[0095] ---

[0096] This allows users to effectively handle base station failures and quickly resolve problems by utilizing past information.

[0097] Example 1

[0098] 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."

[0099] Conventional base station fault response systems have the problem that users need a great deal of specialized knowledge and experience to identify the cause of the fault and take appropriate measures. It is also difficult to effectively utilize past fault response history and technical information, which can result in time-consuming fault response. Furthermore, there is also the issue of skill transfer when personnel are replaced, resulting in inconsistent quality of fault response.

[0100] 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.

[0101] In this invention, the server includes means for accepting input from a user, means for authenticating the user, means for analyzing the problem information entered by the user, means for searching past data and specification data based on the analyzed problem information, means for providing the user with highly relevant information based on the search results, means for the user to input additional questions based on the provided information, means for searching further data based on the additional questions and providing appropriate answers, and means for updating the database with the results of troubleshooting. This allows the user to quickly and efficiently identify the cause of the problem and take appropriate measures. Furthermore, by effectively utilizing past troubleshooting history and technical information, it is expected that response time will be shortened and quality will be improved. Furthermore, the problem of skill transfer due to personnel changes will be eliminated, enabling consistent troubleshooting.

[0102] "User" refers to a person who uses this system to troubleshoot base station failures.

[0103] "Terminal" refers to an electronic device that allows a user to access and operate the system.

[0104] "Server" refers to a computer system that receives input information from a user and performs analysis and database searches.

[0105] "Database" refers to data storage that stores technical information such as past troubleshooting history and radio equipment specifications.

[0106] An "analysis device" refers to software or hardware that has the function of analyzing input information from a user and extracting important keywords and phrases.

[0107] "Chat style" refers to an interface style in which the user and the system exchange messages in a two-way manner.

[0108] "Keywords" refer to words or phrases that are considered to be particularly important in the analyzed problem information.

[0109] A "phrase" refers to a string of words that are considered to be particularly important from the analyzed problem information.

[0110] "Login" refers to the authentication process required for a user to access a system.

[0111] "Response results" refers to the specific actions and results that a user reports to the system after responding to a failure.

[0112] "Additional Information" refers to a question or request that a user enters into the system to seek more detailed information on an initial answer.

[0113] MODE FOR CARRYING OUT THE INVENTION

[0114] The system of the present invention is a support system that enables users to quickly and effectively deal with base station failures. A specific embodiment of this system will be described below.

[0115] Components

[0116] The system mainly consists of the following components:

[0117] 1. User Interface (Terminal)

[0118] 2. Server

[0119] 3. Database

[0120] User input and login

[0121] A user accesses the system using a terminal and logs in by entering a user ID and password. After successful authentication, the user enters the problem into the chat interface of the system. For example, the user reports a problem such as "Base Station A is not responding." The terminal then sends this input information to the server.

[0122] Server-based analysis and data retrieval

[0123] The server receives the user's input and uses a text analysis engine to extract important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted. The server then uses the extracted keywords to convert them into SQL queries and search the database for past troubleshooting history and specification data.

[0124] Information and responses

[0125] The server formats the search results and provides the user with appropriate information in chat format. For example, it can provide specific advice such as, "In similar past cases, the cause was a power supply unit failure, so we recommend checking the operation of the power supply unit." If the user needs more information, they can enter an additional question. The device sends this question to the server, which then searches the database again and provides an appropriate answer.

[0126] Fixing the problem and updating the database

[0127] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system from their terminal. For example, they may report that "the problem has been resolved by replacing the power supply unit." The server receives this information and records it as a new case in the database.

[0128] Specific examples

[0129] Case 1: When base station B loses connection

[0130] Prompt: "Please tell us about past cases of base station B losing connection."

[0131] When the user enters "Base Station B connection lost," the server searches for past connection loss cases and suggests, "In a previous similar case, this occurred after a firmware update. Restarting the device resolved the issue." The user attempts to restart the device and the issue is resolved.

[0132] Case 2: Base station C shows abnormal flashing light

[0133] Prompt: "What should you do if a lamp flashing abnormality occurs on base station C?"

[0134] When the user inputs "Base Station C Lamp Flashing Abnormal", the server checks the meaning of the lamp flashing from the specification data and responds, "There is a possibility of abnormal voltage. We recommend checking the voltage." The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[0135] This invention allows users to quickly and efficiently handle base station faults. Effective use of past fault handling history and technical information can be expected to shorten response times and improve quality. Furthermore, it also eliminates the problem of skill transfer due to personnel changes, enabling consistent fault handling.

[0136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0137] Processing flow

[0138] Step 1:

[0139] User login

[0140] Input: The user inputs the user ID and password from the terminal.

[0141] Data calculation: The terminal sends the user ID and password to the server, which compares them with the user information in the database and performs the authentication process.

[0142] Output: The server returns a message to the terminal indicating whether the authentication was successful or failed.

[0143] Specific operation: If the user successfully logs in, the system home screen will be displayed on the terminal.

[0144] Step 2:

[0145] Enter the fault status

[0146] Input: The user inputs the fault condition about the base station in the chat interface, for example, "Base station A is not responding."

[0147] Data calculation: The terminal sends input information to the server.

[0148] Output: The server saves the received input information in text format.

[0149] Specific operation: The terminal displays to the user that the input information has been successfully accepted.

[0150] Step 3:

[0151] Analysis of input information

[0152] Input: The server receives text data about the problem from the user.

[0153] Data Calculation: The server uses a text analysis engine to extract important keywords and phrases.

[0154] Output: Extracted keywords or phrases (e.g., "Base Station A" or "Not Responding").

[0155] Specific operation: The server saves the extracted keywords as variables.

[0156] Step 4:

[0157] Searching the database

[0158] Input: Extracted keywords (e.g., "Base Station A" or "Not Responding").

[0159] Data Calculation: The server uses the keywords to generate an SQL query to search the database.

[0160] Output: Relevant incident history and technical information.

[0161] Specific behavior: The server formats the search results and uses them in the next step.

[0162] Step 5:

[0163] Providing information

[0164] Input: Related information retrieved by the server as a search result.

[0165] Data Calculation: The server organizes relevant information and generates messages that are presented to the user in an easy-to-understand format.

[0166] Output: Generated message (e.g. "In similar past cases, the cause was a power supply unit failure. We recommend checking the power supply unit's operation.").

[0167] Specific operation: The server sends the generated message to the terminal, which displays it to the user.

[0168] Step 6:

[0169] Obtaining additional information

[0170] Input: A question to be entered by the user (e.g. "How do I check the power supply unit?").

[0171] Data calculation: The terminal sends a follow-up question to the server, which again searches the database and generates an appropriate answer.

[0172] Output: An appropriate answer (e.g. "Steps on how to check your power supply unit").

[0173] Specific operation: The server sends the generated answer to the terminal, which displays it to the user.

[0174] Step 7:

[0175] Troubleshooting

[0176] Input: The user performs troubleshooting based on the information provided.

[0177] Data calculation: Information on the results of the troubleshooting action taken (e.g., "The power supply unit was replaced and the problem was resolved").

[0178] Output: The user enters the result information into the terminal.

[0179] Specific operation: The terminal sends the result information to the server and stores it in the database.

[0180] Step 8:

[0181] Database Update

[0182] Input: User-reported troubleshooting result information.

[0183] Data calculation: The server stores the received result information in the database as a new case.

[0184] Output: A new incident record is added to the database.

[0185] Specific operation: A message is displayed on the user's device indicating that the response result has been successfully reported.

[0186] The above are the specific processing steps of the program of this system.

[0187] (Application example 1)

[0188] 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."

[0189] In modern manufacturing, when machinery used in factories breaks down, it is necessary to quickly and accurately identify the cause and take appropriate measures. However, in many cases, specialized knowledge is required to respond to the breakdown, which can lead to delays. Furthermore, it is difficult for inexperienced staff to take accurate action, resulting in a decline in production efficiency as the breakdown continues for a long time. This invention aims to prevent a decline in production efficiency by quickly and accurately identifying the breakdown status of machinery in factories and providing appropriate measures.

[0190] 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.

[0191] In this invention, the server includes means for accepting input from a user, means for analyzing the problem information input by the user, means for searching past data and specification data based on the analyzed problem information, means for presenting highly relevant information to the user based on the search results, means for searching further data based on additional questions from the user and providing appropriate answers, means for updating the database with the results of troubleshooting, and means for inputting the status of machine failures in a chat format and providing information on troubleshooting, thereby enabling the cause of the failure to be identified quickly and accurately and appropriate measures to be taken promptly.

[0192] "User" refers to the person who operates the system and provides input and questions.

[0193] "Input" refers to the act of a user providing information to a system.

[0194] "Problem information" refers to detailed information about a fault or malfunction entered by a user.

[0195] "Analysis" refers to the process by which the server reviews the problem information it receives and identifies significant keywords and patterns.

[0196] "Search" refers to the act of examining past data or specifications based on analyzed keywords or phrases.

[0197] "Presenting" refers to the act of displaying information relevant to the user based on the search results.

[0198] A "follow-up question" refers to a question a user asks to obtain more detailed information about information that has already been presented.

[0199] "Answer" refers to information provided in response to a user's follow-up question.

[0200] "Update" refers to the act of adding new troubleshooting results to the database.

[0201] "Search results" refers to past data and specification information obtained based on the analyzed problem information.

[0202] "Database" refers to a system that stores information such as past failure cases and specifications.

[0203] "Machinery in a factory" refers to various machinery and equipment installed and operated at manufacturing sites.

[0204] "Chat format" refers to a form of interaction via text messages.

[0205] This invention is a support system for quickly and effectively responding to breakdowns in machinery in a factory, and includes the following components:

[0206] System Components

[0207] 1. User Interface (Terminal)

[0208] 2. Server

[0209] 3. Database

[0210] 1. User Input

[0211] Users log in to the system using a tablet or smartphone and enter information about malfunctions in machinery within the factory in chat format. For example, they can report a problem such as "The motor of Machine A is making an unusual noise."

[0212] 2. Server analysis

[0213] The server receives the information sent from the device, and the analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "machine A," "motor," and "abnormal noise" are extracted.

[0214] 3. Searching for data

[0215] The server uses the extracted keywords and phrases to search a database containing past troubleshooting records and machine specifications, collecting relevant past failure cases and technical information.

[0216] 4. Information provision

[0217] The server then provides the user with appropriate information in chat format based on the search results. For example, it may provide specific advice such as, "If the motor is making strange noises, it is caused by worn bearings. Please check the condition of the bearings."

[0218] 5. Obtaining additional information

[0219] If the user needs more detailed information, they can enter a follow-up question, such as "How do I check the bearing?" The device sends this question to the server, which again searches the database and provides the appropriate answer.

[0220] 6. Troubleshooting and updating the database

[0221] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user might enter information such as "I replaced the bearing and the abnormal noise disappeared." The server receives this information and records it in the database as a new troubleshooting result.

[0222] Hardware and software used

[0223] Hardware: tablets, smartphones, factory robots

[0224] Software: Python, Requests library, Web API

[0225] Examples of concrete examples and prompts

[0226] As a concrete example, the following shows the procedure for a user to report that "the motor of machine A is making an abnormal noise" and obtain a solution to the problem. In this case, the server refers to past cases of "abnormal motor noise" and provides information such as "If an abnormal motor noise occurs, it is caused by worn bearings. Please check the condition of the bearings."

[0227] An example prompt for a generative AI model might be:

[0228] "The motor of machine A is making an unusual noise. Please suggest an appropriate solution based on past malfunction cases."

[0229] This invention allows users to quickly identify the cause of a malfunction and take appropriate measures. Furthermore, even inexperienced staff can handle the problem with a certain degree of accuracy, which contributes to improving production efficiency.

[0230] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0231] Step 1:

[0232] A user logs into the system using a tablet or smartphone. They enter a username and password to authenticate the login and begin the session. The input for this step is the user's authentication information, and the output is a message indicating whether the login was successful or not.

[0233] Step 2:

[0234] The user inputs the breakdown information in chat format. For example, "The motor of machine A is making an unusual noise." This information is sent from the terminal to the server. The input is text data of the breakdown information, and the output is the problem information received by the server.

[0235] Step 3:

[0236] The server analyzes the received problem information. The analysis device breaks down the text data using techniques such as natural language processing and extracts important keywords and phrases. For example, keywords such as "machine A," "motor," and "abnormal noise" are extracted. The input is the text data of the received problem information, and the output is a list of extracted keywords.

[0237] Step 4:

[0238] The server uses the extracted keywords and phrases to search the database for past troubleshooting records and specification data. The search results include related past cases and technical information. The input is a list of keywords, and the output is related past data.

[0239] Step 5:

[0240] Based on the search results, the server provides the user with appropriate information in chat format. For example, a message such as "If an abnormal noise occurs in the motor, it may be caused by worn bearings. Please check the condition of the bearings" is generated and sent to the terminal. The input is the search result data, and the output is a suggested message to the user.

[0241] Step 6:

[0242] If the user needs more detailed information, they enter a follow-up question, for example, "How do I check the bearing?" The question is sent from the terminal to the server. The input is the follow-up question text, and the output is the question received by the server.

[0243] Step 7:

[0244] The server searches the database again and generates an appropriate answer to the follow-up question. For example, it provides specific instructions such as "To check the bearing, first stop the motor, remove the cover, and check its condition." The input is the user's follow-up question, and the output is a detailed answer message.

[0245] Step 8:

[0246] The user performs troubleshooting based on the information provided and reports the results to the system. For example, the user may report that "the abnormal noise was resolved after replacing the bearing." The troubleshooting results are sent from the device to the server. The input is the text data of the troubleshooting results, and the output is the troubleshooting results received by the server.

[0247] Step 9:

[0248] The server updates the received response results in the database. They are recorded as new troubleshooting cases and used for future searches. The input is the troubleshooting result data, and the output is the updated database.

[0249] An example of a prompt for a generative AI model: "The motor of machine A is making an unusual noise. Please suggest an appropriate solution based on past failure cases."

[0250] 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.

[0251] ---

[0252] MODE FOR CARRYING OUT THE INVENTION

[0253] The system of the present invention combines an emotion engine with a support system that allows users to quickly and effectively handle base station failures. This system includes the following components:

[0254] The system includes the following components:

[0255] 1. User Interface (Terminal)

[0256] 2. Server

[0257] 3. Database

[0258] 4. Emotion Engine

[0259] 1. User Input

[0260] Users log in to the system from their devices to troubleshoot base station failures. After logging in, users can enter the current status of the base station failure in chat format. For example, a problem such as "Base station A is not responding" can be reported.

[0261] 2. Server analysis

[0262] The device sends the entered information to the server. The server receives this information, and an analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted.

[0263] 3. Emotion Recognition by Emotion Engine

[0264] At the same time, the server uses an emotion engine to recognize the user's emotions based on the content, speed, and frequency of input. For example, if it determines that the user is feeling stressed, it will recognize that action is necessary.

[0265] 4. Searching for data

[0266] The server uses the extracted keywords and phrases to search a database containing past troubleshooting history and wireless device specifications, collecting related past failure cases and technical information.

[0267] 5. Information provision

[0268] The server then provides the user with appropriate information in chat format based on the search results. If the user is feeling stressed, the emotion engine simplifies the information provided and provides specific step-by-step guidance. For example, specific advice such as "In similar past cases, a power supply unit failure was the cause, so we recommend checking the operation of the power supply unit" is provided.

[0269] 6. Obtaining additional information

[0270] If the user needs more detailed information, they enter an additional question, such as "How do I check the power supply unit?" The device sends this question to the server, which again searches the database and generates an appropriate answer. The emotion engine continuously monitors the user's emotional state and responds adaptively.

[0271] 7. Troubleshooting and updating the database

[0272] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user may enter information such as "I replaced the power supply unit and the problem was resolved." The server receives this information and records it in the database as a new troubleshooting result.

[0273] Specific examples

[0274] Case 1: If a connection loss occurs at base station B, the user can enter "base station B connection loss." The server will search for past connection loss cases and suggest, "In a previous similar case, this occurred after a firmware update. A reboot resolved the issue." If the emotion engine detects the user's stress state, it will provide an additional step-by-step guide detailing the reboot procedure. The user attempts to reboot and the issue is resolved.

[0275] Case 2: If base station C shows an abnormal flashing lamp, the user can input "Base station C, abnormal flashing lamp" and the server will look up the meaning of the flashing lamp in the radio specifications and respond with "There is a possibility of abnormal voltage. We recommend checking the voltage." If the emotion engine detects the user's hesitation, it will provide detailed instructions on how to check the voltage. The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[0276] This invention allows users to effectively respond to base station failures, and the introduction of an emotion engine allows information to be presented that is adapted to the user's psychological state, enabling faster and more reliable problem solving.

[0277] The processing flow will be explained below.

[0278] Processing Steps

[0279] Step 1:

[0280] User: Enter your username and password to log into the system from a terminal.

[0281] Terminal: Sends authentication information (username and password) to the server.

[0282] Server: Checks the authentication information against the database, and if authentication is successful, sends the user a login success message and provides a chat entry screen.

[0283] Step 2:

[0284] User: Enter details of the base station problem in chat format (e.g., "Base station A is not responding").

[0285] Terminal: Sends typed chat messages to the server.

[0286] Server: Receives the problem details and sends them to the text analysis engine.

[0287] Step 3:

[0288] Server: A text analysis engine analyzes the outage details and extracts important keywords and phrases (e.g., "Base Station A" or "Not Responding").

[0289] Server: Using the extracted keywords and phrases, search the database of past fault responses and the database of radio equipment specifications.

[0290] Step 4:

[0291] Server: Filter search results to find information that is most relevant to the current problem (e.g., "power supply unit failure case").

[0292] Server: Send relevant information and recommended actions to the user via chat (e.g. "We recommend checking the power supply unit's operation").

[0293] Step 5:

[0294] Server: The emotion engine recognizes the user's emotional state based on the content, speed, and frequency of the user's input.

[0295] Server: If the user feels stressed, the emotion engine will provide simplified response procedures, such as a concrete step-by-step guide with illustrations.

[0296] Step 6:

[0297] User: Takes action based on the server's suggestion (e.g., "Check the power supply unit").

[0298] User: If more information is needed, enter further details in the chat (e.g. "How do I check my power supply unit?").

[0299] Terminal: Sends a follow-up question to the server.

[0300] Server: Receives additional questions, searches the database again, generates appropriate answers, and sends them via chat.

[0301] Step 7:

[0302] User: Continue troubleshooting based on the information provided, and when the problem is resolved, report the result to the system via chat (e.g., "Replaced the power supply unit and recovered").

[0303] Terminal: Sends the troubleshooting results to the server.

[0304] Server: Analyzes the received response results and records them in a database (e.g., "The power supply unit failed and needed to be replaced").

[0305] Step 8:

[0306] User: After the troubleshooting is completed and the report is complete, log out.

[0307] Terminal: Sends a logout request to the server.

[0308] Server: End the user session and display a logout complete message.

[0309] ---

[0310] These detailed processing steps allow users to effectively respond to base station failures, and the introduction of an emotion engine allows for the presentation of information adapted to the user's psychological state, enabling faster and more reliable problem resolution.

[0311] Example 2

[0312] 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."

[0313] When a failure occurs in wireless communication equipment such as base stations, a fast and accurate response is required, but the stress and anxiety felt by users during this process often becomes a problem. Conventional failure response systems only provide technical information without considering the user's emotional state, which can result in a slow and inaccurate response. Another issue is the difficulty of quickly obtaining appropriate information when additional information is needed.

[0314] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting input from a user, means for analyzing problem information input by the user, means for searching past data and wireless communication device specification data based on the analyzed problem information, means for extracting keywords and phrases based on the analyzed problem information, means for recognizing the emotional state of the user from the input content, input speed, and input frequency and providing adaptive information, means for presenting information to the user in a chat format, means for searching further data based on additional questions from the user and providing appropriate answers, and means for updating the database with the results of the troubleshooting. This enables fast and accurate troubleshooting that is adapted to the user's psychological state.

[0315] "User" refers to a person or organization that logs into the system and responds to a fault by inputting the fault status of the base station.

[0316] The "means for accepting input" refers to an interface that allows a user to input a fault condition or question into the system, and has the function of receiving information input from the user.

[0317] "Means for analyzing problem information" refers to technology or devices for analyzing the input content, identifying the problem, and extracting keywords and phrases related to the problem.

[0318] The "searching means" refers to a function for investigating past data and wireless communication device specification data stored in a database based on the analyzed problem information.

[0319] "Means for recognizing emotional state" refers to technology that determines a user's emotional state based on the user's input content, input speed, input frequency, etc., and evaluates the stress or anxiety the user is currently feeling.

[0320] "Means for providing adaptive information" refers to technology that has the function of providing more appropriate and easy-to-understand information by taking into account the user's emotional state.

[0321] "Means using chat" refers to an interface that allows interaction with users in chat format and provides and obtains information through text messages.

[0322] "Means for providing appropriate answers" refers to the function of searching the database again in response to additional questions from the user and generating the most appropriate and relevant answer.

[0323] "Means of updating the database" refers to the technology that stores and records the results of troubleshooting as new data in a database so that they can be used to handle future troubleshooting.

[0324] MODE FOR CARRYING OUT THE INVENTION

[0325] overview

[0326] This invention relates to a support system that allows users to quickly and accurately respond to faults in base stations and wireless communication devices. This system is characterized by the fact that it can provide information according to the user's psychological state by incorporating emotion recognition technology. The system includes the following components:

[0327] 1. User Interface (Terminal)

[0328] 2. Server

[0329] 3. Database

[0330] 4. Emotion Engine

[0331] Components and Operation

[0332] User Interface (Terminal)

[0333] To troubleshoot a base station failure, a user logs into the system using a terminal. After logging in, the user inputs the problem situation into the terminal in chat format. For example, the user can input specific problem information such as "Base station A is not responding."

[0334] server

[0335] Information entered on the device is sent to the server. The server first analyzes this information and extracts important keywords and phrases (e.g., "Base Station A" or "Not Responding"). Next, the server uses an emotion engine (e.g., IBM Watson® or Azure® Text Analytics) to analyze the user's emotional state based on the content and speed of their input. For example, if the server determines that the user is feeling stressed, that information is reflected in the information provided to the user.

[0336] Database

[0337] The server searches a database (e.g., MySQL (registered trademark), PostgreSQL) based on the extracted keywords and phrases, and collects relevant data such as past troubleshooting history and wireless device specifications. Based on this information, the server generates a message to be provided to the user and presents appropriate information. If the user is feeling emotionally stressed, the presented information can be simplified and a specific step-by-step guide can be provided.

[0338] Information and further questions

[0339] The system responds to the problem based on the information provided by the user, but if more detailed information is needed, the device sends additional questions to the server. For example, a question such as "How do I check the power supply unit?" is entered. The server then searches the database again, generates an appropriate answer, and provides it to the user. The emotion engine is also utilized during this process, allowing the system to respond according to the user's psychological state.

[0340] Troubleshooting and database updates

[0341] The user performs troubleshooting based on the provided information, and when the problem is resolved, the result is reported to the system from the terminal. For example, information such as "The power supply unit was replaced and the problem was resolved" is entered. The server records this information and updates the database with the new troubleshooting result.

[0342] Specific examples

[0343] Case 1:

[0344] If a connection loss occurs at base station B, the user enters "base station B connection loss" into the device. The server searches for past cases of connection loss and suggests, "In a similar case in the past, this occurred after a firmware update. Restarting the device resolved the issue." If the emotion engine detects stress in the user, it provides an additional step-by-step guide detailing the restart procedure. The user attempts to restart the device and the issue is resolved.

[0345] Case 2:

[0346] If base station C shows an abnormal flashing lamp, the user can enter "Base station C abnormal flashing lamp" into their terminal. The server will look up the meaning of the flashing lamp in the wireless device specifications and respond with "There is a possibility of abnormal voltage. We recommend checking the voltage." If the emotion engine detects the user's hesitation, it will provide detailed instructions on how to check the voltage. The user checks the voltage and discovers an abnormal value. The problem can be resolved by replacing the power supply unit.

[0347] This invention enables users to respond to base station failures quickly and efficiently while receiving information and technical support that adapts to their psychological state. This system utilizes a user-friendly interface and advanced emotion analysis technology to respond to failures in base stations and other wireless communication devices more quickly and accurately than conventional methods.

[0348] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0349] Step 1:

[0350] A user logs in to the system using a terminal. The user enters a user ID and password as input. The terminal sends the entered user ID and password to the server. The server compares them with the authentication information stored in the database, and if authentication is successful, the user is presented with the main screen.

[0351] > Specific operation: The user accesses the system URL on a browser and enters their ID and password into the login form. The server checks the received ID and password against the database, and if authentication is successful, redirects them to the dashboard screen.

[0352] Step 2:

[0353] The user uses the chat window on the device to input the current base station failure status. The input sends specific problem information, such as "Base station A is not responding." The device then sends this information to the server.

[0354] > Specific operation: The user types "Base station A is not responding" in the chat window and clicks the send button. The device displays the input in real time and sends this information to the server.

[0355] Step 3:

[0356] The server analyzes the received information. It receives the problem information as input and uses an analyzer to extract important keywords and phrases. The output is keywords such as "Base Station A" and "Not Responding."

[0357] > What happens: The server uses a natural language processing library (e.g., NLTK, spaCy) to tokenize the incoming information and apply a keyword extraction algorithm. The extracted keywords are temporarily stored.

[0358] Step 4:

[0359] The server uses an emotion engine to analyze the user's emotional state, taking the user's problem information, input speed, and input frequency as input, and generating emotion tags (e.g., stress, impatience) as output.

[0360] > Specific operation: The server sends the input data to an emotion recognition engine (e.g., IBM Watson, Azure Text Analytics), which analyzes the obtained emotional information. As a result, an emotion tag such as "stress" or "anxiety" is assigned.

[0361] Step 5:

[0362] The server uses the extracted keywords and phrases to search the database. It receives keywords such as "base station A" and "not responding" as input, and obtains related past troubleshooting history and wireless device specification data as output.

[0363] > Specific operation: The server generates a search query and executes it against a database (e.g., MySQL, PostgreSQL). The search results are temporarily stored in the server's memory.

[0364] Step 6:

[0365] The server provides appropriate information to users based on the collected information and emotion tags. It receives search results and emotion tags as input, and generates edited information to be presented to users as output.

[0366] > Specific operation: The server refers to the search results and emotion tags and generates a message to present to the user. For example, it generates a guide such as "We recommend checking the operation of the power supply unit" and sends it to the device.

[0367] Step 7:

[0368] The user inputs additional questions based on the information provided. For example, "How do I check the power supply unit?" The device sends this information to the server.

[0369] > Specific operation: The user types "How do I check the power supply unit?" into the chat window and sends it. The device displays this information in real time and sends it to the server.

[0370] Step 8:

[0371] The server again searches the database and generates an appropriate answer, taking the additional question and related keywords as input and providing a specific answer as output.

[0372] > Specific action: The server again performs NLP processing, generates a search query, and executes a search against the database. The generated answer includes specific instructions such as "First, make sure the power cable is securely connected."

[0373] Step 9:

[0374] The user responds to the problem based on the information provided and resolves it. After the problem is resolved, the result of the response is reported to the system. The terminal sends a resolution result such as "The power supply unit was replaced and the problem was resolved." The terminal sends this information to the server, which records the result in a database.

[0375] > Specific operation: The user types "I replaced the power supply unit and the problem was resolved" in the chat window and sends it. The server receives this information and registers the corresponding result in the database using an INSERT statement.

[0376] This series of processes allows the user to take prompt and accurate action to resolve the problem, and also ensures efficient operation of the entire system.

[0377] (Application example 2)

[0378] 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."

[0379] Robots and other equipment operating in factories require a rapid and appropriate response when they break down or experience problems. However, conventional systems can be slow to identify the cause of a problem and provide a solution, which can lead to reduced productivity and escalation of the problem. Furthermore, the psychological stress and impatience of the workers who are dealing with the problem can also be a problem. The present invention aims to solve these problems by providing a system that enables rapid and effective troubleshooting and takes into consideration the psychological state of the workers.

[0380] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting input from a user, means for analyzing problem information input by the user, means for searching past data and specification data based on the analyzed problem information, means for presenting highly relevant information to the user based on the search results, means for searching further data based on additional questions from the user and providing appropriate answers, means for updating the database with the results of troubleshooting, means for recognizing the user's emotions based on the content, speed, and frequency of the user's input, and means for adjusting the information presented in accordance with the user's emotions. This enables quick and appropriate troubleshooting, reduces psychological stress on workers, and enables efficient problem solving.

[0381] definition statement

[0382] The "means for accepting input from the user" is an interface that allows the user to input problem information and questions into the system via a terminal.

[0383] The "means for analyzing the problem information input by the user" refers to an analysis device that receives the problem information input by the user and identifies and extracts relevant keywords and phrases.

[0384] The "means for searching past data and specification data based on the analyzed problem information" is a device that searches a database in which past failure cases and technical specifications are stored based on the analyzed information.

[0385] The "means for presenting highly relevant information to the user based on the search results" refers to an interface and its control device for displaying highly relevant information obtained by the search to the user.

[0386] "Means for searching for further data and providing an appropriate answer based on the user's additional question" refers to a system that searches for additional data and generates and provides an appropriate answer in response to a more detailed question from the user.

[0387] The "means for updating the results of troubleshooting in the database" is a function for recording the results of troubleshooting performed by the user in the database for future reference.

[0388] The "means for recognizing emotions based on the user's input content, input speed, and input frequency" is an emotion engine that analyzes the user's input content, input speed, input frequency, etc., and determines the user's emotional state.

[0389] The "means for adjusting the information presented in accordance with the user's emotions" is a function for adjusting the detail and format of the information presented based on the user's psychological state recognized by the emotion engine.

[0390] MODE FOR CARRYING OUT THE INVENTION

[0391] The system of this invention combines an emotion engine with a support system that enables users to quickly and effectively respond to problems with robots operating in factories. The components of this system are as follows:

[0392] User Interface (Terminal)

[0393] Users access the system using a smartphone or tablet. They log in to the system from their device and input the current problem with the robot. This problem is reported in chat format, and specific problems such as "the robot arm won't move" are entered.

[0394] server

[0395] The server receives the problem information entered by the user, analyzes the information using an analysis device, extracts specific keywords and phrases, and searches a database.

[0396] Database

[0397] The database stores past troubleshooting history and robot specifications. The server searches to collect related past failure cases and technical information.

[0398] Emotion Engine

[0399] The server uses an emotion engine to analyze the user's emotional state based on the content, speed, and frequency of their input. For example, if it determines that the user is feeling stressed, the emotion engine will respond accordingly.

[0400] Information provision

[0401] The server presents appropriate information to the user based on the analysis results and the emotion engine's analysis results. If the emotion engine determines that the user is feeling stressed, it simplifies the information presented and provides specific step-by-step guidance. For example, it may provide advice such as, "In similar past cases, restarting the device resolved the issue."

[0402] Obtaining additional information

[0403] If the user needs more information, they enter a follow-up question, and the server again searches the database and provides the appropriate answer.

[0404] Troubleshooting and database updates

[0405] The user attempts to resolve the problem according to the provided guidelines. If the problem is resolved, the user enters the results into the system and updates the database. For example, information such as "The power supply unit was replaced and the system returned to normal" is entered.

[0406] Specific examples

[0407] Case 1: If the user types "My robot arm won't move. Help me, I'm in trouble," the server will suggest "Emotional state: Stress. Case applies: Restart will solve it."

[0408] Prompt Sentence Examples

[0409] User input: "My robot arm won't move. Help, I'm in trouble."

[0410] Emotion engine detection result: Stress

[0411] Advice to offer: Rebooting solves the problem

[0412] This system allows users to quickly and appropriately respond to robot failures, and with the help of the emotion engine, it is also possible to reduce psychological stress.

[0413] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0414] Program processing steps

[0415] Step 1:

[0416] The user logs into the system using a terminal and inputs the robot's trouble status in chat format. This input includes specific problem information, such as "The robot arm won't move." The terminal then sends this input to the server.

[0417] Step 2:

[0418] The server analyzes the received fault information and extracts important keywords and phrases from the user's input. For example, keywords such as "robot arm" and "not working" are extracted. Based on the results of this analysis, the server prepares to search past data and specification data.

[0419] Step 3:

[0420] The server searches the database based on the keywords extracted through the analysis, collecting information related to past similar failure cases and technical specifications. For example, it can obtain relevant information such as "previous similar cases were resolved by restarting the system."

[0421] Step 4:

[0422] At the same time, the server uses an emotion engine to analyze the user's emotional state based on the content, speed, and frequency of input. For example, if the user types quickly and includes "I'm in trouble," the emotion engine will recognize that the user is in a stressful state.

[0423] Step 5:

[0424] The server presents relevant information to the user based on the search results and the emotion engine's analysis. If the emotion engine detects that the user is stressed, it simplifies the information presented and provides specific step-by-step guidance. For example, it may provide detailed instructions for rebooting the device.

[0425] Step 6:

[0426] If the user enters an additional question, the device sends it to the server, which again searches the database and generates an appropriate answer. For example, if the user asks, "How do I reboot?", the server provides detailed reboot instructions.

[0427] Step 7:

[0428] The user responds to the problem according to the information provided. If the problem is resolved, the result is reported to the system. For example, a result such as "After rebooting, the robot arm is now operating normally" is entered.

[0429] Step 8:

[0430] The server receives reports from users and updates the database with the results of the troubleshooting. The results are recorded as new troubleshooting results and are used for future troubleshooting.

[0431] 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.

[0432] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0433] 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.

[0434] [Second embodiment]

[0435] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0436] 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.

[0437] 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).

[0438] 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.

[0439] 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.

[0440] 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).

[0441] 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.

[0442] 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.

[0443] 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.

[0444] 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.

[0445] 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.

[0446] 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."

[0447] ---

[0448] MODE FOR CARRYING OUT THE INVENTION

[0449] The system of the present invention is a support system that enables users to quickly and effectively deal with base station failures. A specific embodiment of this system will be described below.

[0450] The system includes the following components:

[0451] 1. User Interface (Terminal)

[0452] 2. Server

[0453] 3. Database

[0454] 1. User Input

[0455] Users log in to the system from their devices to troubleshoot base station failures. After logging in, users can enter the current status of the base station failure in chat format. For example, a problem such as "Base station A is not responding" can be reported.

[0456] 2. Server analysis

[0457] The device sends the entered information to the server. The server receives this information, and an analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted.

[0458] 3. Searching for data

[0459] The server uses the extracted keywords and phrases to search a database containing past troubleshooting history and wireless device specifications, collecting related past failure cases and technical information.

[0460] 4. Information provision

[0461] The server then provides the user with appropriate information in chat format based on the search results. For example, specific advice such as "In similar past cases, the cause was a power supply unit failure, so we recommend checking the operation of the power supply unit" is provided.

[0462] 5. Obtaining additional information

[0463] If the user needs more information, they can enter a follow-up question, such as "How do I check the power supply unit?" The device sends this question to the server, which again searches the database and generates an appropriate answer.

[0464] 6. Troubleshooting and updating the database

[0465] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user may enter information such as "I replaced the power supply unit and the problem was resolved." The server receives this information and records it in the database as a new troubleshooting result.

[0466] Specific examples

[0467] Case 1: If a connection loss occurs at base station B, the user can enter "base station B connection loss" and the server will search for past connection loss cases and suggest that "a similar case occurred after a firmware update and was resolved by rebooting the device." The user attempts to reboot the device and the problem is resolved.

[0468] Case 2: If base station C shows an abnormal flashing lamp, the user inputs "Base station C, abnormal flashing lamp." The server checks the meaning of the flashing lamp in the radio specifications and responds, "There is a possibility of an abnormal voltage. We recommend checking the voltage." The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[0469] This invention allows users to quickly and efficiently deal with base station failures, and helps to solve the problem of skill transfer due to personnel changes.

[0470] The processing flow will be explained below.

[0471] ---

[0472] Processing Steps

[0473] Step 1:

[0474] User: Enter your username and password to log into the system from a terminal.

[0475] Terminal: Sends authentication information (username and password) to the server.

[0476] Server: Checks the authentication information against the database, and if authentication is successful, sends the user a login success message and provides a chat entry screen.

[0477] Step 2:

[0478] User: Enter details of the base station problem in chat format (e.g., "Base station A is not responding").

[0479] Terminal: Sends typed chat messages to the server.

[0480] Server: Receives the problem details and sends them to the text analysis engine.

[0481] Step 3:

[0482] Server: A text analysis engine analyzes the outage details and extracts important keywords and phrases (e.g., "Base Station A" or "Not Responding").

[0483] Server: Using the extracted keywords and phrases, search the database of past fault responses and the database of radio equipment specifications.

[0484] Step 4:

[0485] Server: Filter search results to find information that is most relevant to the current problem (e.g., "power supply unit failure case").

[0486] Server: Send relevant information and recommended actions to the user via chat (e.g. "We recommend checking the power supply unit's operation").

[0487] Step 5:

[0488] User: Takes action based on the server's suggestion (e.g., "Check the power supply unit").

[0489] User: If more information is needed, enter further details in the chat (e.g. "How do I check my power supply unit?").

[0490] Terminal: Sends a follow-up question to the server.

[0491] Server: Receives additional questions, searches the database again, generates appropriate answers, and sends them via chat.

[0492] Step 6:

[0493] User: Continue troubleshooting based on the information provided, and when the problem is resolved, report the result to the system via chat (e.g., "Replaced the power supply unit and recovered").

[0494] Terminal: Sends the troubleshooting results to the server.

[0495] Server: Analyzes the received response results and records them in a database (e.g., "A reboot was required due to a power supply unit failure").

[0496] Step 7:

[0497] User: After the troubleshooting is completed and the report is complete, log out.

[0498] Terminal: Sends a logout request to the server.

[0499] Server: End the user session and display a logout complete message.

[0500] ---

[0501] This allows users to effectively handle base station failures and quickly resolve problems by utilizing past information.

[0502] Example 1

[0503] 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."

[0504] Conventional base station fault response systems have the problem that users need a great deal of specialized knowledge and experience to identify the cause of the fault and take appropriate measures. It is also difficult to effectively utilize past fault response history and technical information, which can result in time-consuming fault response. Furthermore, there is also the issue of skill transfer when personnel are replaced, resulting in inconsistent quality of fault response.

[0505] 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.

[0506] In this invention, the server includes means for accepting input from a user, means for authenticating the user, means for analyzing the problem information entered by the user, means for searching past data and specification data based on the analyzed problem information, means for providing the user with highly relevant information based on the search results, means for the user to input additional questions based on the provided information, means for searching further data based on the additional questions and providing appropriate answers, and means for updating the database with the results of troubleshooting. This allows the user to quickly and efficiently identify the cause of the problem and take appropriate measures. Furthermore, by effectively utilizing past troubleshooting history and technical information, it is expected that response time will be shortened and quality will be improved. Furthermore, the problem of skill transfer due to personnel changes will be eliminated, enabling consistent troubleshooting.

[0507] "User" refers to a person who uses this system to troubleshoot base station failures.

[0508] "Terminal" refers to an electronic device that allows a user to access and operate the system.

[0509] "Server" refers to a computer system that receives input information from a user and performs analysis and database searches.

[0510] "Database" refers to data storage that stores technical information such as past troubleshooting history and radio equipment specifications.

[0511] An "analysis device" refers to software or hardware that has the function of analyzing input information from a user and extracting important keywords and phrases.

[0512] "Chat style" refers to an interface style in which the user and the system exchange messages in a two-way manner.

[0513] "Keywords" refer to words or phrases that are considered to be particularly important in the analyzed problem information.

[0514] A "phrase" refers to a string of words that are considered to be particularly important from the analyzed problem information.

[0515] "Login" refers to the authentication process required for a user to access a system.

[0516] "Response results" refers to the specific actions and results that a user reports to the system after responding to a failure.

[0517] "Additional Information" refers to a question or request that a user enters into the system to seek more detailed information on an initial answer.

[0518] MODE FOR CARRYING OUT THE INVENTION

[0519] The system of the present invention is a support system that enables users to quickly and effectively deal with base station failures. A specific embodiment of this system will be described below.

[0520] Components

[0521] The system mainly consists of the following components:

[0522] 1. User Interface (Terminal)

[0523] 2. Server

[0524] 3. Database

[0525] User input and login

[0526] A user accesses the system using a terminal and logs in by entering a user ID and password. After successful authentication, the user enters the problem into the chat interface of the system. For example, the user reports a problem such as "Base Station A is not responding." The terminal then sends this input information to the server.

[0527] Server-based analysis and data retrieval

[0528] The server receives the user's input and uses a text analysis engine to extract important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted. The server then uses the extracted keywords to convert them into SQL queries and search the database for past troubleshooting history and specification data.

[0529] Information and responses

[0530] The server formats the search results and provides the user with appropriate information in chat format. For example, it can provide specific advice such as, "In similar past cases, the cause was a power supply unit failure, so we recommend checking the operation of the power supply unit." If the user needs more information, they can enter an additional question. The device sends this question to the server, which then searches the database again and provides an appropriate answer.

[0531] Fixing the problem and updating the database

[0532] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system from their terminal. For example, they may report that "the problem has been resolved by replacing the power supply unit." The server receives this information and records it as a new case in the database.

[0533] Specific examples

[0534] Case 1: When base station B loses connection

[0535] Prompt: "Please tell us about past cases of base station B losing connection."

[0536] When the user enters "Base Station B connection lost," the server searches for past connection loss cases and suggests, "In a previous similar case, this occurred after a firmware update. Restarting the device resolved the issue." The user attempts to restart the device and the issue is resolved.

[0537] Case 2: Base station C shows abnormal flashing light

[0538] Prompt: "What should you do if a lamp flashing abnormality occurs on base station C?"

[0539] When the user inputs "Base Station C Lamp Flashing Abnormal", the server checks the meaning of the lamp flashing from the specification data and responds, "There is a possibility of abnormal voltage. We recommend checking the voltage." The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[0540] This invention allows users to quickly and efficiently handle base station faults. Effective use of past fault handling history and technical information can be expected to shorten response times and improve quality. Furthermore, it also eliminates the problem of skill transfer due to personnel changes, enabling consistent fault handling.

[0541] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0542] Processing flow

[0543] Step 1:

[0544] User login

[0545] Input: The user inputs the user ID and password from the terminal.

[0546] Data calculation: The terminal sends the user ID and password to the server, which compares them with the user information in the database and performs the authentication process.

[0547] Output: The server returns a message to the terminal indicating whether the authentication was successful or failed.

[0548] Specific operation: If the user successfully logs in, the system home screen will be displayed on the terminal.

[0549] Step 2:

[0550] Enter the fault status

[0551] Input: The user inputs the fault condition about the base station in the chat interface, for example, "Base station A is not responding."

[0552] Data calculation: The terminal sends input information to the server.

[0553] Output: The server saves the received input information in text format.

[0554] Specific operation: The terminal displays to the user that the input information has been successfully accepted.

[0555] Step 3:

[0556] Analysis of input information

[0557] Input: The server receives text data about the problem from the user.

[0558] Data Calculation: The server uses a text analysis engine to extract important keywords and phrases.

[0559] Output: Extracted keywords or phrases (e.g., "Base Station A" or "Not Responding").

[0560] Specific operation: The server saves the extracted keywords as variables.

[0561] Step 4:

[0562] Searching the database

[0563] Input: Extracted keywords (e.g., "Base Station A" or "Not Responding").

[0564] Data Calculation: The server uses the keywords to generate an SQL query to search the database.

[0565] Output: Relevant incident history and technical information.

[0566] Specific behavior: The server formats the search results and uses them in the next step.

[0567] Step 5:

[0568] Providing information

[0569] Input: Related information retrieved by the server as a search result.

[0570] Data Calculation: The server organizes relevant information and generates messages that are presented to the user in an easy-to-understand format.

[0571] Output: Generated message (e.g. "In similar past cases, the cause was a power supply unit failure. We recommend checking the power supply unit's operation.").

[0572] Specific operation: The server sends the generated message to the terminal, which displays it to the user.

[0573] Step 6:

[0574] Obtaining additional information

[0575] Input: A question to be entered by the user (e.g. "How do I check the power supply unit?").

[0576] Data calculation: The terminal sends a follow-up question to the server, which again searches the database and generates an appropriate answer.

[0577] Output: An appropriate answer (e.g. "Steps on how to check your power supply unit").

[0578] Specific operation: The server sends the generated answer to the terminal, which displays it to the user.

[0579] Step 7:

[0580] Troubleshooting

[0581] Input: The user performs troubleshooting based on the information provided.

[0582] Data calculation: Information on the results of the troubleshooting action taken (e.g., "The power supply unit was replaced and the problem was resolved").

[0583] Output: The user enters the result information into the terminal.

[0584] Specific operation: The terminal sends the result information to the server and stores it in the database.

[0585] Step 8:

[0586] Database Update

[0587] Input: User-reported troubleshooting result information.

[0588] Data calculation: The server stores the received result information in the database as a new case.

[0589] Output: A new incident record is added to the database.

[0590] Specific operation: A message is displayed on the user's device indicating that the response result has been successfully reported.

[0591] The above are the specific processing steps of the program of this system.

[0592] (Application example 1)

[0593] 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."

[0594] In modern manufacturing, when machinery used in factories breaks down, it is necessary to quickly and accurately identify the cause and take appropriate measures. However, in many cases, specialized knowledge is required to respond to the breakdown, which can lead to delays. Furthermore, it is difficult for inexperienced staff to take accurate action, resulting in a decline in production efficiency as the breakdown continues for a long time. This invention aims to prevent a decline in production efficiency by quickly and accurately identifying the breakdown status of machinery in factories and providing appropriate measures.

[0595] 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.

[0596] In this invention, the server includes means for accepting input from a user, means for analyzing the problem information input by the user, means for searching past data and specification data based on the analyzed problem information, means for presenting highly relevant information to the user based on the search results, means for searching further data based on additional questions from the user and providing appropriate answers, means for updating the database with the results of troubleshooting, and means for inputting the status of machine failures in a chat format and providing information on troubleshooting, thereby enabling the cause of the failure to be identified quickly and accurately and appropriate measures to be taken promptly.

[0597] "User" refers to the person who operates the system and provides input and questions.

[0598] "Input" refers to the act of a user providing information to a system.

[0599] "Problem information" refers to detailed information about a fault or malfunction entered by a user.

[0600] "Analysis" refers to the process by which the server reviews the problem information it receives and identifies significant keywords and patterns.

[0601] "Search" refers to the act of examining past data or specifications based on analyzed keywords or phrases.

[0602] "Presenting" refers to the act of displaying information relevant to the user based on the search results.

[0603] A "follow-up question" refers to a question a user asks to obtain more detailed information about information that has already been presented.

[0604] "Answer" refers to information provided in response to a user's follow-up question.

[0605] "Update" refers to the act of adding new troubleshooting results to the database.

[0606] "Search results" refers to past data and specification information obtained based on the analyzed problem information.

[0607] "Database" refers to a system that stores information such as past failure cases and specifications.

[0608] "Machinery in a factory" refers to various machinery and equipment installed and operated at manufacturing sites.

[0609] "Chat format" refers to a form of interaction via text messages.

[0610] This invention is a support system for quickly and effectively responding to breakdowns in machinery in a factory, and includes the following components:

[0611] System Components

[0612] 1. User Interface (Terminal)

[0613] 2. Server

[0614] 3. Database

[0615] 1. User Input

[0616] Users log in to the system using a tablet or smartphone and enter information about malfunctions in machinery within the factory in chat format. For example, they can report a problem such as "The motor of Machine A is making an unusual noise."

[0617] 2. Server analysis

[0618] The server receives the information sent from the device, and the analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "machine A," "motor," and "abnormal noise" are extracted.

[0619] 3. Searching for data

[0620] The server uses the extracted keywords and phrases to search a database containing past troubleshooting records and machine specifications, collecting relevant past failure cases and technical information.

[0621] 4. Information provision

[0622] The server then provides the user with appropriate information in chat format based on the search results. For example, it may provide specific advice such as, "If the motor is making strange noises, it is caused by worn bearings. Please check the condition of the bearings."

[0623] 5. Obtaining additional information

[0624] If the user needs more detailed information, they can enter a follow-up question, such as "How do I check the bearing?" The device sends this question to the server, which again searches the database and provides the appropriate answer.

[0625] 6. Troubleshooting and updating the database

[0626] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user might enter information such as "I replaced the bearing and the abnormal noise disappeared." The server receives this information and records it in the database as a new troubleshooting result.

[0627] Hardware and software used

[0628] Hardware: tablets, smartphones, factory robots

[0629] Software: Python, Requests library, Web API

[0630] Examples of concrete examples and prompts

[0631] As a concrete example, the following shows the procedure for a user to report that "the motor of machine A is making an abnormal noise" and obtain a solution to the problem. In this case, the server refers to past cases of "abnormal motor noise" and provides information such as "If an abnormal motor noise occurs, it is caused by worn bearings. Please check the condition of the bearings."

[0632] An example prompt for a generative AI model might be:

[0633] "The motor of machine A is making an unusual noise. Please suggest an appropriate solution based on past malfunction cases."

[0634] This invention allows users to quickly identify the cause of a malfunction and take appropriate measures. Furthermore, even inexperienced staff can handle the problem with a certain degree of accuracy, which contributes to improving production efficiency.

[0635] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0636] Step 1:

[0637] A user logs into the system using a tablet or smartphone. They enter a username and password to authenticate the login and begin the session. The input for this step is the user's authentication information, and the output is a message indicating whether the login was successful or not.

[0638] Step 2:

[0639] The user inputs the breakdown information in chat format. For example, "The motor of machine A is making an unusual noise." This information is sent from the terminal to the server. The input is text data of the breakdown information, and the output is the problem information received by the server.

[0640] Step 3:

[0641] The server analyzes the received problem information. The analysis device breaks down the text data using techniques such as natural language processing and extracts important keywords and phrases. For example, keywords such as "machine A," "motor," and "abnormal noise" are extracted. The input is the text data of the received problem information, and the output is a list of extracted keywords.

[0642] Step 4:

[0643] The server uses the extracted keywords and phrases to search the database for past troubleshooting records and specification data. The search results include related past cases and technical information. The input is a list of keywords, and the output is related past data.

[0644] Step 5:

[0645] Based on the search results, the server provides the user with appropriate information in chat format. For example, a message such as "If an abnormal noise occurs in the motor, it may be caused by worn bearings. Please check the condition of the bearings" is generated and sent to the terminal. The input is the search result data, and the output is a suggested message to the user.

[0646] Step 6:

[0647] If the user needs more detailed information, they enter a follow-up question, for example, "How do I check the bearing?" The question is sent from the terminal to the server. The input is the follow-up question text, and the output is the question received by the server.

[0648] Step 7:

[0649] The server searches the database again and generates an appropriate answer to the follow-up question. For example, it provides specific instructions such as "To check the bearing, first stop the motor, remove the cover, and check its condition." The input is the user's follow-up question, and the output is a detailed answer message.

[0650] Step 8:

[0651] The user performs troubleshooting based on the information provided and reports the results to the system. For example, the user may report that "the abnormal noise was resolved after replacing the bearing." The troubleshooting results are sent from the device to the server. The input is the text data of the troubleshooting results, and the output is the troubleshooting results received by the server.

[0652] Step 9:

[0653] The server updates the received response results in the database. They are recorded as new troubleshooting cases and used for future searches. The input is the troubleshooting result data, and the output is the updated database.

[0654] An example of a prompt for a generative AI model: "The motor of machine A is making an unusual noise. Please suggest an appropriate solution based on past failure cases."

[0655] 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.

[0656] ---

[0657] MODE FOR CARRYING OUT THE INVENTION

[0658] The system of the present invention combines an emotion engine with a support system that allows users to quickly and effectively handle base station failures. This system includes the following components:

[0659] The system includes the following components:

[0660] 1. User Interface (Terminal)

[0661] 2. Server

[0662] 3. Database

[0663] 4. Emotion Engine

[0664] 1. User Input

[0665] Users log in to the system from their devices to troubleshoot base station failures. After logging in, users can enter the current status of the base station failure in chat format. For example, a problem such as "Base station A is not responding" can be reported.

[0666] 2. Server analysis

[0667] The device sends the entered information to the server. The server receives this information, and an analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted.

[0668] 3. Emotion Recognition by Emotion Engine

[0669] At the same time, the server uses an emotion engine to recognize the user's emotions based on the content, speed, and frequency of input. For example, if it determines that the user is feeling stressed, it will recognize that action is necessary.

[0670] 4. Searching for data

[0671] The server uses the extracted keywords and phrases to search a database containing past troubleshooting history and wireless device specifications, collecting related past failure cases and technical information.

[0672] 5. Information provision

[0673] The server then provides the user with appropriate information in chat format based on the search results. If the user is feeling stressed, the emotion engine simplifies the information provided and provides specific step-by-step guidance. For example, specific advice such as "In similar past cases, a power supply unit failure was the cause, so we recommend checking the operation of the power supply unit" is provided.

[0674] 6. Obtaining additional information

[0675] If the user needs more detailed information, they enter an additional question, such as "How do I check the power supply unit?" The device sends this question to the server, which again searches the database and generates an appropriate answer. The emotion engine continuously monitors the user's emotional state and responds adaptively.

[0676] 7. Troubleshooting and updating the database

[0677] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user may enter information such as "I replaced the power supply unit and the problem was resolved." The server receives this information and records it in the database as a new troubleshooting result.

[0678] Specific examples

[0679] Case 1: If a connection loss occurs at base station B, the user can enter "base station B connection loss." The server will search for past connection loss cases and suggest, "In a previous similar case, this occurred after a firmware update. A reboot resolved the issue." If the emotion engine detects the user's stress state, it will provide an additional step-by-step guide detailing the reboot procedure. The user attempts to reboot and the issue is resolved.

[0680] Case 2: If base station C shows an abnormal flashing lamp, the user can input "Base station C, abnormal flashing lamp" and the server will look up the meaning of the flashing lamp in the radio specifications and respond with "There is a possibility of abnormal voltage. We recommend checking the voltage." If the emotion engine detects the user's hesitation, it will provide detailed instructions on how to check the voltage. The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[0681] This invention allows users to effectively respond to base station failures, and the introduction of an emotion engine allows information to be presented that is adapted to the user's psychological state, enabling faster and more reliable problem solving.

[0682] The processing flow will be explained below.

[0683] Processing Steps

[0684] Step 1:

[0685] User: Enter your username and password to log into the system from a terminal.

[0686] Terminal: Sends authentication information (username and password) to the server.

[0687] Server: Checks the authentication information against the database, and if authentication is successful, sends the user a login success message and provides a chat entry screen.

[0688] Step 2:

[0689] User: Enter details of the base station problem in chat format (e.g., "Base station A is not responding").

[0690] Terminal: Sends typed chat messages to the server.

[0691] Server: Receives the problem details and sends them to the text analysis engine.

[0692] Step 3:

[0693] Server: A text analysis engine analyzes the outage details and extracts important keywords and phrases (e.g., "Base Station A" or "Not Responding").

[0694] Server: Using the extracted keywords and phrases, search the database of past fault responses and the database of radio equipment specifications.

[0695] Step 4:

[0696] Server: Filter search results to find information that is most relevant to the current problem (e.g., "power supply unit failure case").

[0697] Server: Send relevant information and recommended actions to the user via chat (e.g. "We recommend checking the power supply unit's operation").

[0698] Step 5:

[0699] Server: The emotion engine recognizes the user's emotional state based on the content, speed, and frequency of the user's input.

[0700] Server: If the user feels stressed, the emotion engine will provide simplified response procedures, such as a concrete step-by-step guide with illustrations.

[0701] Step 6:

[0702] User: Takes action based on the server's suggestion (e.g., "Check the power supply unit").

[0703] User: If more information is needed, enter further details in the chat (e.g. "How do I check my power supply unit?").

[0704] Terminal: Sends a follow-up question to the server.

[0705] Server: Receives additional questions, searches the database again, generates appropriate answers, and sends them via chat.

[0706] Step 7:

[0707] User: Continue troubleshooting based on the information provided, and when the problem is resolved, report the result to the system via chat (e.g., "Replaced the power supply unit and recovered").

[0708] Terminal: Sends the troubleshooting results to the server.

[0709] Server: Analyzes the received response results and records them in a database (e.g., "The power supply unit failed and needed to be replaced").

[0710] Step 8:

[0711] User: After the troubleshooting is completed and the report is complete, log out.

[0712] Terminal: Sends a logout request to the server.

[0713] Server: End the user session and display a logout complete message.

[0714] ---

[0715] These detailed processing steps allow users to effectively respond to base station failures, and the introduction of an emotion engine allows for the presentation of information adapted to the user's psychological state, enabling faster and more reliable problem resolution.

[0716] Example 2

[0717] 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."

[0718] When a failure occurs in wireless communication equipment such as base stations, a fast and accurate response is required, but the stress and anxiety felt by users during this process often becomes a problem. Conventional failure response systems only provide technical information without considering the user's emotional state, which can result in a slow and inaccurate response. Another issue is the difficulty of quickly obtaining appropriate information when additional information is needed.

[0719] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting input from a user, means for analyzing problem information input by the user, means for searching past data and wireless communication device specification data based on the analyzed problem information, means for extracting keywords and phrases based on the analyzed problem information, means for recognizing the emotional state of the user from the input content, input speed, and input frequency and providing adaptive information, means for presenting information to the user in a chat format, means for searching further data based on additional questions from the user and providing appropriate answers, and means for updating the database with the results of the troubleshooting. This enables fast and accurate troubleshooting that is adapted to the user's psychological state.

[0720] "User" refers to a person or organization that logs into the system and responds to a fault by inputting the fault status of the base station.

[0721] The "means for accepting input" refers to an interface that allows a user to input a fault condition or question into the system, and has the function of receiving information input from the user.

[0722] "Means for analyzing problem information" refers to technology or devices for analyzing the input content, identifying the problem, and extracting keywords and phrases related to the problem.

[0723] The "searching means" refers to a function for investigating past data and wireless communication device specification data stored in a database based on the analyzed problem information.

[0724] "Means for recognizing emotional state" refers to technology that determines a user's emotional state based on the user's input content, input speed, input frequency, etc., and evaluates the stress or anxiety the user is currently feeling.

[0725] "Means for providing adaptive information" refers to technology that has the function of providing more appropriate and easy-to-understand information by taking into account the user's emotional state.

[0726] "Means using chat" refers to an interface that allows interaction with users in chat format and provides and obtains information through text messages.

[0727] "Means for providing appropriate answers" refers to the function of searching the database again in response to additional questions from the user and generating the most appropriate and relevant answer.

[0728] "Means of updating the database" refers to the technology that stores and records the results of troubleshooting as new data in a database so that they can be used to handle future troubleshooting.

[0729] MODE FOR CARRYING OUT THE INVENTION

[0730] overview

[0731] This invention relates to a support system that allows users to quickly and accurately respond to faults in base stations and wireless communication devices. This system is characterized by the fact that it can provide information according to the user's psychological state by incorporating emotion recognition technology. The system includes the following components:

[0732] 1. User Interface (Terminal)

[0733] 2. Server

[0734] 3. Database

[0735] 4. Emotion Engine

[0736] Components and Operation

[0737] User Interface (Terminal)

[0738] To troubleshoot a base station failure, a user logs into the system using a terminal. After logging in, the user inputs the problem situation into the terminal in chat format. For example, the user can input specific problem information such as "Base station A is not responding."

[0739] server

[0740] Information entered on the device is sent to the server. The server first analyzes this information and extracts important keywords and phrases (e.g., "base station A" or "not responding"). Next, the server uses an emotion engine (e.g., IBM Watson or Azure Text Analytics) to analyze the user's emotional state based on the content and speed of their input. For example, if the server determines that the user is feeling stressed, that information is reflected in the information provided to the user.

[0741] Database

[0742] The server searches a database (e.g., MySQL, PostgreSQL) based on the extracted keywords and phrases, collecting relevant data such as past troubleshooting history and wireless device specifications. Based on this information, the server generates a message to be provided to the user and presents appropriate information. If the user is feeling emotionally stressed, the server can simplify the displayed information and provide specific step-by-step guidance.

[0743] Information and further questions

[0744] The system responds to the problem based on the information provided by the user, but if more detailed information is needed, the device sends additional questions to the server. For example, a question such as "How do I check the power supply unit?" is entered. The server then searches the database again, generates an appropriate answer, and provides it to the user. The emotion engine is also utilized during this process, allowing the system to respond according to the user's psychological state.

[0745] Troubleshooting and database updates

[0746] The user performs troubleshooting based on the provided information, and when the problem is resolved, the result is reported to the system from the terminal. For example, information such as "The power supply unit was replaced and the problem was resolved" is entered. The server records this information and updates the database with the new troubleshooting result.

[0747] Specific examples

[0748] Case 1:

[0749] If a connection loss occurs at base station B, the user enters "base station B connection loss" into the device. The server searches for past cases of connection loss and suggests, "In a similar case in the past, this occurred after a firmware update. Restarting the device resolved the issue." If the emotion engine detects stress in the user, it provides an additional step-by-step guide detailing the restart procedure. The user attempts to restart the device and the issue is resolved.

[0750] Case 2:

[0751] If base station C shows an abnormal flashing lamp, the user can enter "Base station C abnormal flashing lamp" into their terminal. The server will look up the meaning of the flashing lamp in the wireless device specifications and respond with "There is a possibility of abnormal voltage. We recommend checking the voltage." If the emotion engine detects the user's hesitation, it will provide detailed instructions on how to check the voltage. The user checks the voltage and discovers an abnormal value. The problem can be resolved by replacing the power supply unit.

[0752] This invention enables users to respond to base station failures quickly and efficiently while receiving information and technical support that adapts to their psychological state. This system utilizes a user-friendly interface and advanced emotion analysis technology to respond to failures in base stations and other wireless communication devices more quickly and accurately than conventional methods.

[0753] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0754] Step 1:

[0755] A user logs in to the system using a terminal. The user enters a user ID and password as input. The terminal sends the entered user ID and password to the server. The server compares them with the authentication information stored in the database, and if authentication is successful, the user is presented with the main screen.

[0756] > Specific operation: The user accesses the system URL on a browser and enters their ID and password into the login form. The server checks the received ID and password against the database, and if authentication is successful, redirects them to the dashboard screen.

[0757] Step 2:

[0758] The user uses the chat window on the device to input the current base station failure status. The input sends specific problem information, such as "Base station A is not responding." The device then sends this information to the server.

[0759] > Specific operation: The user types "Base station A is not responding" in the chat window and clicks the send button. The device displays the input in real time and sends this information to the server.

[0760] Step 3:

[0761] The server analyzes the received information. It receives the problem information as input and uses an analyzer to extract important keywords and phrases. The output is keywords such as "Base Station A" and "Not Responding."

[0762] > What happens: The server uses a natural language processing library (e.g., NLTK, spaCy) to tokenize the incoming information and apply a keyword extraction algorithm. The extracted keywords are temporarily stored.

[0763] Step 4:

[0764] The server uses an emotion engine to analyze the user's emotional state, taking the user's problem information, input speed, and input frequency as input, and generating emotion tags (e.g., stress, impatience) as output.

[0765] > Specific operation: The server sends the input data to an emotion recognition engine (e.g., IBM Watson, Azure Text Analytics), which analyzes the obtained emotional information. As a result, an emotion tag such as "stress" or "anxiety" is assigned.

[0766] Step 5:

[0767] The server uses the extracted keywords and phrases to search the database. It receives keywords such as "base station A" and "not responding" as input, and obtains related past troubleshooting history and wireless device specification data as output.

[0768] > Specific operation: The server generates a search query and executes it against a database (e.g., MySQL, PostgreSQL). The search results are temporarily stored in the server's memory.

[0769] Step 6:

[0770] The server provides appropriate information to users based on the collected information and emotion tags. It receives search results and emotion tags as input, and generates edited information to be presented to users as output.

[0771] > Specific operation: The server refers to the search results and emotion tags and generates a message to present to the user. For example, it generates a guide such as "We recommend checking the operation of the power supply unit" and sends it to the device.

[0772] Step 7:

[0773] The user inputs additional questions based on the information provided. For example, "How do I check the power supply unit?" The device sends this information to the server.

[0774] > Specific operation: The user types "How do I check the power supply unit?" into the chat window and sends it. The device displays this information in real time and sends it to the server.

[0775] Step 8:

[0776] The server again searches the database and generates an appropriate answer, taking the additional question and related keywords as input and providing a specific answer as output.

[0777] > Specific action: The server again performs NLP processing, generates a search query, and executes a search against the database. The generated answer includes specific instructions such as "First, make sure the power cable is securely connected."

[0778] Step 9:

[0779] The user responds to the problem based on the information provided and resolves it. After the problem is resolved, the result of the response is reported to the system. The terminal sends a resolution result such as "The power supply unit was replaced and the problem was resolved." The terminal sends this information to the server, which records the result in a database.

[0780] > Specific operation: The user types "I replaced the power supply unit and the problem was resolved" in the chat window and sends it. The server receives this information and registers the corresponding result in the database using an INSERT statement.

[0781] This series of processes allows the user to take prompt and accurate action to resolve the problem, and also ensures efficient operation of the entire system.

[0782] (Application example 2)

[0783] 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."

[0784] Robots and other equipment operating in factories require a rapid and appropriate response when they break down or experience problems. However, conventional systems can be slow to identify the cause of a problem and provide a solution, which can lead to reduced productivity and escalation of the problem. Furthermore, the psychological stress and impatience of the workers who are dealing with the problem can also be a problem. The present invention aims to solve these problems by providing a system that enables rapid and effective troubleshooting and takes into consideration the psychological state of the workers.

[0785] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting input from a user, means for analyzing problem information input by the user, means for searching past data and specification data based on the analyzed problem information, means for presenting highly relevant information to the user based on the search results, means for searching further data based on additional questions from the user and providing appropriate answers, means for updating the database with the results of troubleshooting, means for recognizing the user's emotions based on the content, speed, and frequency of the user's input, and means for adjusting the information presented in accordance with the user's emotions. This enables quick and appropriate troubleshooting, reduces psychological stress on workers, and enables efficient problem solving.

[0786] definition statement

[0787] The "means for accepting input from the user" is an interface that allows the user to input problem information and questions into the system via a terminal.

[0788] The "means for analyzing the problem information input by the user" refers to an analysis device that receives the problem information input by the user and identifies and extracts relevant keywords and phrases.

[0789] The "means for searching past data and specification data based on the analyzed problem information" is a device that searches a database in which past failure cases and technical specifications are stored based on the analyzed information.

[0790] The "means for presenting highly relevant information to the user based on the search results" refers to an interface and its control device for displaying highly relevant information obtained by the search to the user.

[0791] "Means for searching for further data and providing an appropriate answer based on the user's additional question" refers to a system that searches for additional data and generates and provides an appropriate answer in response to a more detailed question from the user.

[0792] The "means for updating the results of troubleshooting in the database" is a function for recording the results of troubleshooting performed by the user in the database for future reference.

[0793] The "means for recognizing emotions based on the user's input content, input speed, and input frequency" is an emotion engine that analyzes the user's input content, input speed, input frequency, etc., and determines the user's emotional state.

[0794] The "means for adjusting the information presented in accordance with the user's emotions" is a function for adjusting the detail and format of the information presented based on the user's psychological state recognized by the emotion engine.

[0795] MODE FOR CARRYING OUT THE INVENTION

[0796] The system of this invention combines an emotion engine with a support system that enables users to quickly and effectively respond to problems with robots operating in factories. The components of this system are as follows:

[0797] User Interface (Terminal)

[0798] Users access the system using a smartphone or tablet. They log in to the system from their device and input the current problem with the robot. This problem is reported in chat format, and specific problems such as "the robot arm won't move" are entered.

[0799] server

[0800] The server receives the problem information entered by the user, analyzes the information using an analysis device, extracts specific keywords and phrases, and searches a database.

[0801] Database

[0802] The database stores past troubleshooting history and robot specifications. The server searches to collect related past failure cases and technical information.

[0803] Emotion Engine

[0804] The server uses an emotion engine to analyze the user's emotional state based on the content, speed, and frequency of their input. For example, if it determines that the user is feeling stressed, the emotion engine will respond accordingly.

[0805] Information provision

[0806] The server presents appropriate information to the user based on the analysis results and the emotion engine's analysis results. If the emotion engine determines that the user is feeling stressed, it simplifies the information presented and provides specific step-by-step guidance. For example, it may provide advice such as, "In similar past cases, restarting the device resolved the issue."

[0807] Obtaining additional information

[0808] If the user needs more information, they enter a follow-up question, and the server again searches the database and provides the appropriate answer.

[0809] Troubleshooting and database updates

[0810] The user attempts to resolve the problem according to the provided guidelines. If the problem is resolved, the user enters the results into the system and updates the database. For example, information such as "The power supply unit was replaced and the system returned to normal" is entered.

[0811] Specific examples

[0812] Case 1: If the user types "My robot arm won't move. Help me, I'm in trouble," the server will suggest "Emotional state: Stress. Case applies: Restart will solve it."

[0813] Prompt Sentence Examples

[0814] User input: "My robot arm won't move. Help, I'm in trouble."

[0815] Emotion engine detection result: Stress

[0816] Advice to offer: Rebooting solves the problem

[0817] This system allows users to quickly and appropriately respond to robot failures, and with the help of the emotion engine, it is also possible to reduce psychological stress.

[0818] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0819] Program processing steps

[0820] Step 1:

[0821] The user logs into the system using a terminal and inputs the robot's trouble status in chat format. This input includes specific problem information, such as "The robot arm won't move." The terminal then sends this input to the server.

[0822] Step 2:

[0823] The server analyzes the received fault information and extracts important keywords and phrases from the user's input. For example, keywords such as "robot arm" and "not working" are extracted. Based on the results of this analysis, the server prepares to search past data and specification data.

[0824] Step 3:

[0825] The server searches the database based on the keywords extracted through the analysis, collecting information related to past similar failure cases and technical specifications. For example, it can obtain relevant information such as "previous similar cases were resolved by restarting the system."

[0826] Step 4:

[0827] At the same time, the server uses an emotion engine to analyze the user's emotional state based on the content, speed, and frequency of input. For example, if the user types quickly and includes "I'm in trouble," the emotion engine will recognize that the user is in a stressful state.

[0828] Step 5:

[0829] The server presents relevant information to the user based on the search results and the emotion engine's analysis. If the emotion engine detects that the user is stressed, it simplifies the information presented and provides specific step-by-step guidance. For example, it may provide detailed instructions for rebooting the device.

[0830] Step 6:

[0831] If the user enters an additional question, the device sends it to the server, which again searches the database and generates an appropriate answer. For example, if the user asks, "How do I reboot?", the server provides detailed reboot instructions.

[0832] Step 7:

[0833] The user responds to the problem according to the information provided. If the problem is resolved, the result is reported to the system. For example, a result such as "After rebooting, the robot arm is now operating normally" is entered.

[0834] Step 8:

[0835] The server receives reports from users and updates the database with the results of the troubleshooting. The results are recorded as new troubleshooting results and are used for future troubleshooting.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] [Third embodiment]

[0840] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0841] 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.

[0842] 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).

[0843] 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.

[0844] 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.

[0845] 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).

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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."

[0852] ---

[0853] MODE FOR CARRYING OUT THE INVENTION

[0854] The system of the present invention is a support system that enables users to quickly and effectively deal with base station failures. A specific embodiment of this system will be described below.

[0855] The system includes the following components:

[0856] 1. User Interface (Terminal)

[0857] 2. Server

[0858] 3. Database

[0859] 1. User Input

[0860] Users log in to the system from their devices to troubleshoot base station failures. After logging in, users can enter the current status of the base station failure in chat format. For example, a problem such as "Base station A is not responding" can be reported.

[0861] 2. Server analysis

[0862] The device sends the entered information to the server. The server receives this information, and an analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted.

[0863] 3. Searching for data

[0864] The server uses the extracted keywords and phrases to search a database containing past troubleshooting history and wireless device specifications, collecting related past failure cases and technical information.

[0865] 4. Information provision

[0866] The server then provides the user with appropriate information in chat format based on the search results. For example, specific advice such as "In similar past cases, the cause was a power supply unit failure, so we recommend checking the operation of the power supply unit" is provided.

[0867] 5. Obtaining additional information

[0868] If the user needs more information, they can enter a follow-up question, such as "How do I check the power supply unit?" The device sends this question to the server, which again searches the database and generates an appropriate answer.

[0869] 6. Troubleshooting and updating the database

[0870] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user may enter information such as "I replaced the power supply unit and the problem was resolved." The server receives this information and records it in the database as a new troubleshooting result.

[0871] Specific examples

[0872] Case 1: If a connection loss occurs at base station B, the user can enter "base station B connection loss" and the server will search for past connection loss cases and suggest that "a similar case occurred after a firmware update and was resolved by rebooting the device." The user attempts to reboot the device and the problem is resolved.

[0873] Case 2: If base station C shows an abnormal flashing lamp, the user inputs "Base station C, abnormal flashing lamp." The server checks the meaning of the flashing lamp in the radio specifications and responds, "There is a possibility of an abnormal voltage. We recommend checking the voltage." The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[0874] This invention allows users to quickly and efficiently deal with base station failures, and helps to solve the problem of skill transfer due to personnel changes.

[0875] The processing flow will be explained below.

[0876] ---

[0877] Processing Steps

[0878] Step 1:

[0879] User: Enter your username and password to log into the system from a terminal.

[0880] Terminal: Sends authentication information (username and password) to the server.

[0881] Server: Checks the authentication information against the database, and if authentication is successful, sends the user a login success message and provides a chat entry screen.

[0882] Step 2:

[0883] User: Enter details of the base station problem in chat format (e.g., "Base station A is not responding").

[0884] Terminal: Sends typed chat messages to the server.

[0885] Server: Receives the problem details and sends them to the text analysis engine.

[0886] Step 3:

[0887] Server: A text analysis engine analyzes the outage details and extracts important keywords and phrases (e.g., "Base Station A" or "Not Responding").

[0888] Server: Using the extracted keywords and phrases, search the database of past fault responses and the database of radio equipment specifications.

[0889] Step 4:

[0890] Server: Filter search results to find information that is most relevant to the current problem (e.g., "power supply unit failure case").

[0891] Server: Send relevant information and recommended actions to the user via chat (e.g. "We recommend checking the power supply unit's operation").

[0892] Step 5:

[0893] User: Takes action based on the server's suggestion (e.g., "Check the power supply unit").

[0894] User: If more information is needed, enter further details in the chat (e.g. "How do I check my power supply unit?").

[0895] Terminal: Sends a follow-up question to the server.

[0896] Server: Receives additional questions, searches the database again, generates appropriate answers, and sends them via chat.

[0897] Step 6:

[0898] User: Continue troubleshooting based on the information provided, and when the problem is resolved, report the result to the system via chat (e.g., "Replaced the power supply unit and recovered").

[0899] Terminal: Sends the troubleshooting results to the server.

[0900] Server: Analyzes the received response results and records them in a database (e.g., "A reboot was required due to a power supply unit failure").

[0901] Step 7:

[0902] User: After the troubleshooting is completed and the report is complete, log out.

[0903] Terminal: Sends a logout request to the server.

[0904] Server: End the user session and display a logout complete message.

[0905] ---

[0906] This allows users to effectively handle base station failures and quickly resolve problems by utilizing past information.

[0907] Example 1

[0908] 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."

[0909] Conventional base station fault response systems have the problem that users need a great deal of specialized knowledge and experience to identify the cause of the fault and take appropriate measures. It is also difficult to effectively utilize past fault response history and technical information, which can result in time-consuming fault response. Furthermore, there is also the issue of skill transfer when personnel are replaced, resulting in inconsistent quality of fault response.

[0910] 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.

[0911] In this invention, the server includes means for accepting input from a user, means for authenticating the user, means for analyzing the problem information entered by the user, means for searching past data and specification data based on the analyzed problem information, means for providing the user with highly relevant information based on the search results, means for the user to input additional questions based on the provided information, means for searching further data based on the additional questions and providing appropriate answers, and means for updating the database with the results of troubleshooting. This allows the user to quickly and efficiently identify the cause of the problem and take appropriate measures. Furthermore, by effectively utilizing past troubleshooting history and technical information, it is expected that response time will be shortened and quality will be improved. Furthermore, the problem of skill transfer due to personnel changes will be eliminated, enabling consistent troubleshooting.

[0912] "User" refers to a person who uses this system to troubleshoot base station failures.

[0913] "Terminal" refers to an electronic device that allows a user to access and operate the system.

[0914] "Server" refers to a computer system that receives input information from a user and performs analysis and database searches.

[0915] "Database" refers to data storage that stores technical information such as past troubleshooting history and radio equipment specifications.

[0916] An "analysis device" refers to software or hardware that has the function of analyzing input information from a user and extracting important keywords and phrases.

[0917] "Chat style" refers to an interface style in which the user and the system exchange messages in a two-way manner.

[0918] "Keywords" refer to words or phrases that are considered to be particularly important in the analyzed problem information.

[0919] A "phrase" refers to a string of words that are considered to be particularly important from the analyzed problem information.

[0920] "Login" refers to the authentication process required for a user to access a system.

[0921] "Response results" refers to the specific actions and results that a user reports to the system after responding to a failure.

[0922] "Additional Information" refers to a question or request that a user enters into the system to seek more detailed information on an initial answer.

[0923] MODE FOR CARRYING OUT THE INVENTION

[0924] The system of the present invention is a support system that enables users to quickly and effectively deal with base station failures. A specific embodiment of this system will be described below.

[0925] Components

[0926] The system mainly consists of the following components:

[0927] 1. User Interface (Terminal)

[0928] 2. Server

[0929] 3. Database

[0930] User input and login

[0931] A user accesses the system using a terminal and logs in by entering a user ID and password. After successful authentication, the user enters the problem into the chat interface of the system. For example, the user reports a problem such as "Base Station A is not responding." The terminal then sends this input information to the server.

[0932] Server-based analysis and data retrieval

[0933] The server receives the user's input and uses a text analysis engine to extract important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted. The server then uses the extracted keywords to convert them into SQL queries and search the database for past troubleshooting history and specification data.

[0934] Information and responses

[0935] The server formats the search results and provides the user with appropriate information in chat format. For example, it can provide specific advice such as, "In similar past cases, the cause was a power supply unit failure, so we recommend checking the operation of the power supply unit." If the user needs more information, they can enter an additional question. The device sends this question to the server, which then searches the database again and provides an appropriate answer.

[0936] Fixing the problem and updating the database

[0937] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system from their terminal. For example, they may report that "the problem has been resolved by replacing the power supply unit." The server receives this information and records it as a new case in the database.

[0938] Specific examples

[0939] Case 1: When base station B loses connection

[0940] Prompt: "Please tell us about past cases of base station B losing connection."

[0941] When the user enters "Base Station B connection lost," the server searches for past connection loss cases and suggests, "In a previous similar case, this occurred after a firmware update. Restarting the device resolved the issue." The user attempts to restart the device and the issue is resolved.

[0942] Case 2: Base station C shows abnormal flashing light

[0943] Prompt: "What should you do if a lamp flashing abnormality occurs on base station C?"

[0944] When the user inputs "Base Station C Lamp Flashing Abnormal", the server checks the meaning of the lamp flashing from the specification data and responds, "There is a possibility of abnormal voltage. We recommend checking the voltage." The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[0945] This invention allows users to quickly and efficiently handle base station faults. Effective use of past fault handling history and technical information can be expected to shorten response times and improve quality. Furthermore, it also eliminates the problem of skill transfer due to personnel changes, enabling consistent fault handling.

[0946] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0947] Processing flow

[0948] Step 1:

[0949] User login

[0950] Input: The user inputs the user ID and password from the terminal.

[0951] Data calculation: The terminal sends the user ID and password to the server, which compares them with the user information in the database and performs the authentication process.

[0952] Output: The server returns a message to the terminal indicating whether the authentication was successful or failed.

[0953] Specific operation: If the user successfully logs in, the system home screen will be displayed on the terminal.

[0954] Step 2:

[0955] Enter the fault status

[0956] Input: The user inputs the fault condition about the base station in the chat interface, for example, "Base station A is not responding."

[0957] Data calculation: The terminal sends input information to the server.

[0958] Output: The server saves the received input information in text format.

[0959] Specific operation: The terminal displays to the user that the input information has been successfully accepted.

[0960] Step 3:

[0961] Analysis of input information

[0962] Input: The server receives text data about the problem from the user.

[0963] Data Calculation: The server uses a text analysis engine to extract important keywords and phrases.

[0964] Output: Extracted keywords or phrases (e.g., "Base Station A" or "Not Responding").

[0965] Specific operation: The server saves the extracted keywords as variables.

[0966] Step 4:

[0967] Searching the database

[0968] Input: Extracted keywords (e.g., "Base Station A" or "Not Responding").

[0969] Data Calculation: The server uses the keywords to generate an SQL query to search the database.

[0970] Output: Relevant incident history and technical information.

[0971] Specific behavior: The server formats the search results and uses them in the next step.

[0972] Step 5:

[0973] Providing information

[0974] Input: Related information retrieved by the server as a search result.

[0975] Data Calculation: The server organizes relevant information and generates messages that are presented to the user in an easy-to-understand format.

[0976] Output: Generated message (e.g. "In similar past cases, the cause was a power supply unit failure. We recommend checking the power supply unit's operation.").

[0977] Specific operation: The server sends the generated message to the terminal, which displays it to the user.

[0978] Step 6:

[0979] Obtaining additional information

[0980] Input: A question to be entered by the user (e.g. "How do I check the power supply unit?").

[0981] Data calculation: The terminal sends a follow-up question to the server, which again searches the database and generates an appropriate answer.

[0982] Output: An appropriate answer (e.g. "Steps on how to check your power supply unit").

[0983] Specific operation: The server sends the generated answer to the terminal, which displays it to the user.

[0984] Step 7:

[0985] Troubleshooting

[0986] Input: The user performs troubleshooting based on the information provided.

[0987] Data calculation: Information on the results of the troubleshooting action taken (e.g., "The power supply unit was replaced and the problem was resolved").

[0988] Output: The user enters the result information into the terminal.

[0989] Specific operation: The terminal sends the result information to the server and stores it in the database.

[0990] Step 8:

[0991] Database Update

[0992] Input: User-reported troubleshooting result information.

[0993] Data calculation: The server stores the received result information in the database as a new case.

[0994] Output: A new incident record is added to the database.

[0995] Specific operation: A message is displayed on the user's device indicating that the response result has been successfully reported.

[0996] The above are the specific processing steps of the program of this system.

[0997] (Application example 1)

[0998] 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."

[0999] In modern manufacturing, when machinery used in factories breaks down, it is necessary to quickly and accurately identify the cause and take appropriate measures. However, in many cases, specialized knowledge is required to respond to the breakdown, which can lead to delays. Furthermore, it is difficult for inexperienced staff to take accurate action, resulting in a decline in production efficiency as the breakdown continues for a long time. This invention aims to prevent a decline in production efficiency by quickly and accurately identifying the breakdown status of machinery in factories and providing appropriate measures.

[1000] 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.

[1001] In this invention, the server includes means for accepting input from a user, means for analyzing the problem information input by the user, means for searching past data and specification data based on the analyzed problem information, means for presenting highly relevant information to the user based on the search results, means for searching further data based on additional questions from the user and providing appropriate answers, means for updating the database with the results of troubleshooting, and means for inputting the status of machine failures in a chat format and providing information on troubleshooting, thereby enabling the cause of the failure to be identified quickly and accurately and appropriate measures to be taken promptly.

[1002] "User" refers to the person who operates the system and provides input and questions.

[1003] "Input" refers to the act of a user providing information to a system.

[1004] "Problem information" refers to detailed information about a fault or malfunction entered by a user.

[1005] "Analysis" refers to the process by which the server reviews the problem information it receives and identifies significant keywords and patterns.

[1006] "Search" refers to the act of examining past data or specifications based on analyzed keywords or phrases.

[1007] "Presenting" refers to the act of displaying information relevant to the user based on the search results.

[1008] A "follow-up question" refers to a question a user asks to obtain more detailed information about information that has already been presented.

[1009] "Answer" refers to information provided in response to a user's follow-up question.

[1010] "Update" refers to the act of adding new troubleshooting results to the database.

[1011] "Search results" refers to past data and specification information obtained based on the analyzed problem information.

[1012] "Database" refers to a system that stores information such as past failure cases and specifications.

[1013] "Machinery in a factory" refers to various machinery and equipment installed and operated at manufacturing sites.

[1014] "Chat format" refers to a form of interaction via text messages.

[1015] This invention is a support system for quickly and effectively responding to breakdowns in machinery in a factory, and includes the following components:

[1016] System Components

[1017] 1. User Interface (Terminal)

[1018] 2. Server

[1019] 3. Database

[1020] 1. User Input

[1021] Users log in to the system using a tablet or smartphone and enter information about malfunctions in machinery within the factory in chat format. For example, they can report a problem such as "The motor of Machine A is making an unusual noise."

[1022] 2. Server analysis

[1023] The server receives the information sent from the device, and the analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "machine A," "motor," and "abnormal noise" are extracted.

[1024] 3. Searching for data

[1025] The server uses the extracted keywords and phrases to search a database containing past troubleshooting records and machine specifications, collecting relevant past failure cases and technical information.

[1026] 4. Information provision

[1027] The server then provides the user with appropriate information in chat format based on the search results. For example, it may provide specific advice such as, "If the motor is making strange noises, it is caused by worn bearings. Please check the condition of the bearings."

[1028] 5. Obtaining additional information

[1029] If the user needs more detailed information, they can enter a follow-up question, such as "How do I check the bearing?" The device sends this question to the server, which again searches the database and provides the appropriate answer.

[1030] 6. Troubleshooting and updating the database

[1031] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user might enter information such as "I replaced the bearing and the abnormal noise disappeared." The server receives this information and records it in the database as a new troubleshooting result.

[1032] Hardware and software used

[1033] Hardware: tablets, smartphones, factory robots

[1034] Software: Python, Requests library, Web API

[1035] Examples of concrete examples and prompts

[1036] As a concrete example, the following shows the procedure for a user to report that "the motor of machine A is making an abnormal noise" and obtain a solution to the problem. In this case, the server refers to past cases of "abnormal motor noise" and provides information such as "If an abnormal motor noise occurs, it is caused by worn bearings. Please check the condition of the bearings."

[1037] An example prompt for a generative AI model might be:

[1038] "The motor of machine A is making an unusual noise. Please suggest an appropriate solution based on past malfunction cases."

[1039] This invention allows users to quickly identify the cause of a malfunction and take appropriate measures. Furthermore, even inexperienced staff can handle the problem with a certain degree of accuracy, which contributes to improving production efficiency.

[1040] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1041] Step 1:

[1042] A user logs into the system using a tablet or smartphone. They enter a username and password to authenticate the login and begin the session. The input for this step is the user's authentication information, and the output is a message indicating whether the login was successful or not.

[1043] Step 2:

[1044] The user inputs the breakdown information in chat format. For example, "The motor of machine A is making an unusual noise." This information is sent from the terminal to the server. The input is text data of the breakdown information, and the output is the problem information received by the server.

[1045] Step 3:

[1046] The server analyzes the received problem information. The analysis device breaks down the text data using techniques such as natural language processing and extracts important keywords and phrases. For example, keywords such as "machine A," "motor," and "abnormal noise" are extracted. The input is the text data of the received problem information, and the output is a list of extracted keywords.

[1047] Step 4:

[1048] The server uses the extracted keywords and phrases to search the database for past troubleshooting records and specification data. The search results include related past cases and technical information. The input is a list of keywords, and the output is related past data.

[1049] Step 5:

[1050] Based on the search results, the server provides the user with appropriate information in chat format. For example, a message such as "If an abnormal noise occurs in the motor, it may be caused by worn bearings. Please check the condition of the bearings" is generated and sent to the terminal. The input is the search result data, and the output is a suggested message to the user.

[1051] Step 6:

[1052] If the user needs more detailed information, they enter a follow-up question, for example, "How do I check the bearing?" The question is sent from the terminal to the server. The input is the follow-up question text, and the output is the question received by the server.

[1053] Step 7:

[1054] The server searches the database again and generates an appropriate answer to the follow-up question. For example, it provides specific instructions such as "To check the bearing, first stop the motor, remove the cover, and check its condition." The input is the user's follow-up question, and the output is a detailed answer message.

[1055] Step 8:

[1056] The user performs troubleshooting based on the information provided and reports the results to the system. For example, the user may report that "the abnormal noise was resolved after replacing the bearing." The troubleshooting results are sent from the device to the server. The input is the text data of the troubleshooting results, and the output is the troubleshooting results received by the server.

[1057] Step 9:

[1058] The server updates the received response results in the database. They are recorded as new troubleshooting cases and used for future searches. The input is the troubleshooting result data, and the output is the updated database.

[1059] An example of a prompt for a generative AI model: "The motor of machine A is making an unusual noise. Please suggest an appropriate solution based on past failure cases."

[1060] 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.

[1061] ---

[1062] MODE FOR CARRYING OUT THE INVENTION

[1063] The system of the present invention combines an emotion engine with a support system that allows users to quickly and effectively handle base station failures. This system includes the following components:

[1064] The system includes the following components:

[1065] 1. User Interface (Terminal)

[1066] 2. Server

[1067] 3. Database

[1068] 4. Emotion Engine

[1069] 1. User Input

[1070] Users log in to the system from their devices to troubleshoot base station failures. After logging in, users can enter the current status of the base station failure in chat format. For example, a problem such as "Base station A is not responding" can be reported.

[1071] 2. Server analysis

[1072] The device sends the entered information to the server. The server receives this information, and an analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted.

[1073] 3. Emotion Recognition by Emotion Engine

[1074] At the same time, the server uses an emotion engine to recognize the user's emotions based on the content, speed, and frequency of input. For example, if it determines that the user is feeling stressed, it will recognize that action is necessary.

[1075] 4. Searching for data

[1076] The server uses the extracted keywords and phrases to search a database containing past troubleshooting history and wireless device specifications, collecting related past failure cases and technical information.

[1077] 5. Information provision

[1078] The server then provides the user with appropriate information in chat format based on the search results. If the user is feeling stressed, the emotion engine simplifies the information provided and provides specific step-by-step guidance. For example, specific advice such as "In similar past cases, a power supply unit failure was the cause, so we recommend checking the operation of the power supply unit" is provided.

[1079] 6. Obtaining additional information

[1080] If the user needs more detailed information, they enter an additional question, such as "How do I check the power supply unit?" The device sends this question to the server, which again searches the database and generates an appropriate answer. The emotion engine continuously monitors the user's emotional state and responds adaptively.

[1081] 7. Troubleshooting and updating the database

[1082] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user may enter information such as "I replaced the power supply unit and the problem was resolved." The server receives this information and records it in the database as a new troubleshooting result.

[1083] Specific examples

[1084] Case 1: If a connection loss occurs at base station B, the user can enter "base station B connection loss." The server will search for past connection loss cases and suggest, "In a previous similar case, this occurred after a firmware update. A reboot resolved the issue." If the emotion engine detects the user's stress state, it will provide an additional step-by-step guide detailing the reboot procedure. The user attempts to reboot and the issue is resolved.

[1085] Case 2: If base station C shows an abnormal flashing lamp, the user can input "Base station C, abnormal flashing lamp" and the server will look up the meaning of the flashing lamp in the radio specifications and respond with "There is a possibility of abnormal voltage. We recommend checking the voltage." If the emotion engine detects the user's hesitation, it will provide detailed instructions on how to check the voltage. The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[1086] This invention allows users to effectively respond to base station failures, and the introduction of an emotion engine allows information to be presented that is adapted to the user's psychological state, enabling faster and more reliable problem solving.

[1087] The processing flow will be explained below.

[1088] Processing Steps

[1089] Step 1:

[1090] User: Enter your username and password to log into the system from a terminal.

[1091] Terminal: Sends authentication information (username and password) to the server.

[1092] Server: Checks the authentication information against the database, and if authentication is successful, sends the user a login success message and provides a chat entry screen.

[1093] Step 2:

[1094] User: Enter details of the base station problem in chat format (e.g., "Base station A is not responding").

[1095] Terminal: Sends typed chat messages to the server.

[1096] Server: Receives the problem details and sends them to the text analysis engine.

[1097] Step 3:

[1098] Server: A text analysis engine analyzes the outage details and extracts important keywords and phrases (e.g., "Base Station A" or "Not Responding").

[1099] Server: Using the extracted keywords and phrases, search the database of past fault responses and the database of radio equipment specifications.

[1100] Step 4:

[1101] Server: Filter search results to find information that is most relevant to the current problem (e.g., "power supply unit failure case").

[1102] Server: Send relevant information and recommended actions to the user via chat (e.g. "We recommend checking the power supply unit's operation").

[1103] Step 5:

[1104] Server: The emotion engine recognizes the user's emotional state based on the content, speed, and frequency of the user's input.

[1105] Server: If the user feels stressed, the emotion engine will provide simplified response procedures, such as a concrete step-by-step guide with illustrations.

[1106] Step 6:

[1107] User: Takes action based on the server's suggestion (e.g., "Check the power supply unit").

[1108] User: If more information is needed, enter further details in the chat (e.g. "How do I check my power supply unit?").

[1109] Terminal: Sends a follow-up question to the server.

[1110] Server: Receives additional questions, searches the database again, generates appropriate answers, and sends them via chat.

[1111] Step 7:

[1112] User: Continue troubleshooting based on the information provided, and when the problem is resolved, report the result to the system via chat (e.g., "Replaced the power supply unit and recovered").

[1113] Terminal: Sends the troubleshooting results to the server.

[1114] Server: Analyzes the received response results and records them in a database (e.g., "The power supply unit failed and needed to be replaced").

[1115] Step 8:

[1116] User: After the troubleshooting is completed and the report is complete, log out.

[1117] Terminal: Sends a logout request to the server.

[1118] Server: End the user session and display a logout complete message.

[1119] ---

[1120] These detailed processing steps allow users to effectively respond to base station failures, and the introduction of an emotion engine allows for the presentation of information adapted to the user's psychological state, enabling faster and more reliable problem resolution.

[1121] Example 2

[1122] 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."

[1123] When a failure occurs in wireless communication equipment such as base stations, a fast and accurate response is required, but the stress and anxiety felt by users during this process often becomes a problem. Conventional failure response systems only provide technical information without considering the user's emotional state, which can result in a slow and inaccurate response. Another issue is the difficulty of quickly obtaining appropriate information when additional information is needed.

[1124] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting input from a user, means for analyzing problem information input by the user, means for searching past data and wireless communication device specification data based on the analyzed problem information, means for extracting keywords and phrases based on the analyzed problem information, means for recognizing the emotional state of the user from the input content, input speed, and input frequency and providing adaptive information, means for presenting information to the user in a chat format, means for searching further data based on additional questions from the user and providing appropriate answers, and means for updating the database with the results of the troubleshooting. This enables fast and accurate troubleshooting that is adapted to the user's psychological state.

[1125] "User" refers to a person or organization that logs into the system and responds to a fault by inputting the fault status of the base station.

[1126] The "means for accepting input" refers to an interface that allows a user to input a fault condition or question into the system, and has the function of receiving information input from the user.

[1127] "Means for analyzing problem information" refers to technology or devices for analyzing the input content, identifying the problem, and extracting keywords and phrases related to the problem.

[1128] The "searching means" refers to a function for investigating past data and wireless communication device specification data stored in a database based on the analyzed problem information.

[1129] "Means for recognizing emotional state" refers to technology that determines a user's emotional state based on the user's input content, input speed, input frequency, etc., and evaluates the stress or anxiety the user is currently feeling.

[1130] "Means for providing adaptive information" refers to technology that has the function of providing more appropriate and easy-to-understand information by taking into account the user's emotional state.

[1131] "Means using chat" refers to an interface that allows interaction with users in chat format and provides and obtains information through text messages.

[1132] "Means for providing appropriate answers" refers to the function of searching the database again in response to additional questions from the user and generating the most appropriate and relevant answer.

[1133] "Means of updating the database" refers to the technology that stores and records the results of troubleshooting as new data in a database so that they can be used to handle future troubleshooting.

[1134] MODE FOR CARRYING OUT THE INVENTION

[1135] overview

[1136] This invention relates to a support system that allows users to quickly and accurately respond to faults in base stations and wireless communication devices. This system is characterized by the fact that it can provide information according to the user's psychological state by incorporating emotion recognition technology. The system includes the following components:

[1137] 1. User Interface (Terminal)

[1138] 2. Server

[1139] 3. Database

[1140] 4. Emotion Engine

[1141] Components and Operation

[1142] User Interface (Terminal)

[1143] To troubleshoot a base station failure, a user logs into the system using a terminal. After logging in, the user inputs the problem situation into the terminal in chat format. For example, the user can input specific problem information such as "Base station A is not responding."

[1144] server

[1145] Information entered on the device is sent to the server. The server first analyzes this information and extracts important keywords and phrases (e.g., "base station A" or "not responding"). Next, the server uses an emotion engine (e.g., IBM Watson or Azure Text Analytics) to analyze the user's emotional state based on the content and speed of their input. For example, if the server determines that the user is feeling stressed, that information is reflected in the information provided to the user.

[1146] Database

[1147] The server searches a database (e.g., MySQL, PostgreSQL) based on the extracted keywords and phrases, collecting relevant data such as past troubleshooting history and wireless device specifications. Based on this information, the server generates a message to be provided to the user and presents appropriate information. If the user is feeling emotionally stressed, the server can simplify the displayed information and provide specific step-by-step guidance.

[1148] Information and further questions

[1149] The system responds to the problem based on the information provided by the user, but if more detailed information is needed, the device sends additional questions to the server. For example, a question such as "How do I check the power supply unit?" is entered. The server then searches the database again, generates an appropriate answer, and provides it to the user. The emotion engine is also utilized during this process, allowing the system to respond according to the user's psychological state.

[1150] Troubleshooting and database updates

[1151] The user performs troubleshooting based on the provided information, and when the problem is resolved, the result is reported to the system from the terminal. For example, information such as "The power supply unit was replaced and the problem was resolved" is entered. The server records this information and updates the database with the new troubleshooting result.

[1152] Specific examples

[1153] Case 1:

[1154] If a connection loss occurs at base station B, the user enters "base station B connection loss" into the device. The server searches for past cases of connection loss and suggests, "In a similar case in the past, this occurred after a firmware update. Restarting the device resolved the issue." If the emotion engine detects stress in the user, it provides an additional step-by-step guide detailing the restart procedure. The user attempts to restart the device and the issue is resolved.

[1155] Case 2:

[1156] If base station C shows an abnormal flashing lamp, the user can enter "Base station C abnormal flashing lamp" into their terminal. The server will look up the meaning of the flashing lamp in the wireless device specifications and respond with "There is a possibility of abnormal voltage. We recommend checking the voltage." If the emotion engine detects the user's hesitation, it will provide detailed instructions on how to check the voltage. The user checks the voltage and discovers an abnormal value. The problem can be resolved by replacing the power supply unit.

[1157] This invention enables users to respond to base station failures quickly and efficiently while receiving information and technical support that adapts to their psychological state. This system utilizes a user-friendly interface and advanced emotion analysis technology to respond to failures in base stations and other wireless communication devices more quickly and accurately than conventional methods.

[1158] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1159] Step 1:

[1160] A user logs in to the system using a terminal. The user enters a user ID and password as input. The terminal sends the entered user ID and password to the server. The server compares them with the authentication information stored in the database, and if authentication is successful, the user is presented with the main screen.

[1161] > Specific operation: The user accesses the system URL on a browser and enters their ID and password into the login form. The server checks the received ID and password against the database, and if authentication is successful, redirects them to the dashboard screen.

[1162] Step 2:

[1163] The user uses the chat window on the device to input the current base station failure status. The input sends specific problem information, such as "Base station A is not responding." The device then sends this information to the server.

[1164] > Specific operation: The user types "Base station A is not responding" in the chat window and clicks the send button. The device displays the input in real time and sends this information to the server.

[1165] Step 3:

[1166] The server analyzes the received information. It receives the problem information as input and uses an analyzer to extract important keywords and phrases. The output is keywords such as "Base Station A" and "Not Responding."

[1167] > What happens: The server uses a natural language processing library (e.g., NLTK, spaCy) to tokenize the incoming information and apply a keyword extraction algorithm. The extracted keywords are temporarily stored.

[1168] Step 4:

[1169] The server uses an emotion engine to analyze the user's emotional state, taking the user's problem information, input speed, and input frequency as input, and generating emotion tags (e.g., stress, impatience) as output.

[1170] > Specific operation: The server sends the input data to an emotion recognition engine (e.g., IBM Watson, Azure Text Analytics), which analyzes the obtained emotional information. As a result, an emotion tag such as "stress" or "anxiety" is assigned.

[1171] Step 5:

[1172] The server uses the extracted keywords and phrases to search the database. It receives keywords such as "base station A" and "not responding" as input, and obtains related past troubleshooting history and wireless device specification data as output.

[1173] > Specific operation: The server generates a search query and executes it against a database (e.g., MySQL, PostgreSQL). The search results are temporarily stored in the server's memory.

[1174] Step 6:

[1175] The server provides appropriate information to users based on the collected information and emotion tags. It receives search results and emotion tags as input, and generates edited information to be presented to users as output.

[1176] > Specific operation: The server refers to the search results and emotion tags and generates a message to present to the user. For example, it generates a guide such as "We recommend checking the operation of the power supply unit" and sends it to the device.

[1177] Step 7:

[1178] The user inputs additional questions based on the information provided. For example, "How do I check the power supply unit?" The device sends this information to the server.

[1179] > Specific operation: The user types "How do I check the power supply unit?" into the chat window and sends it. The device displays this information in real time and sends it to the server.

[1180] Step 8:

[1181] The server again searches the database and generates an appropriate answer, taking the additional question and related keywords as input and providing a specific answer as output.

[1182] > Specific action: The server again performs NLP processing, generates a search query, and executes a search against the database. The generated answer includes specific instructions such as "First, make sure the power cable is securely connected."

[1183] Step 9:

[1184] The user responds to the problem based on the information provided and resolves it. After the problem is resolved, the result of the response is reported to the system. The terminal sends a resolution result such as "The power supply unit was replaced and the problem was resolved." The terminal sends this information to the server, which records the result in a database.

[1185] > Specific operation: The user types "I replaced the power supply unit and the problem was resolved" in the chat window and sends it. The server receives this information and registers the corresponding result in the database using an INSERT statement.

[1186] This series of processes allows the user to take prompt and accurate action to resolve the problem, and also ensures efficient operation of the entire system.

[1187] (Application example 2)

[1188] 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."

[1189] Robots and other equipment operating in factories require a rapid and appropriate response when they break down or experience problems. However, conventional systems can be slow to identify the cause of a problem and provide a solution, which can lead to reduced productivity and escalation of the problem. Furthermore, the psychological stress and impatience of the workers who are dealing with the problem can also be a problem. The present invention aims to solve these problems by providing a system that enables rapid and effective troubleshooting and takes into consideration the psychological state of the workers.

[1190] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting input from a user, means for analyzing problem information input by the user, means for searching past data and specification data based on the analyzed problem information, means for presenting highly relevant information to the user based on the search results, means for searching further data based on additional questions from the user and providing appropriate answers, means for updating the database with the results of troubleshooting, means for recognizing the user's emotions based on the content, speed, and frequency of the user's input, and means for adjusting the information presented in accordance with the user's emotions. This enables quick and appropriate troubleshooting, reduces psychological stress on workers, and enables efficient problem solving.

[1191] definition statement

[1192] The "means for accepting input from the user" is an interface that allows the user to input problem information and questions into the system via a terminal.

[1193] The "means for analyzing the problem information input by the user" refers to an analysis device that receives the problem information input by the user and identifies and extracts relevant keywords and phrases.

[1194] The "means for searching past data and specification data based on the analyzed problem information" is a device that searches a database in which past failure cases and technical specifications are stored based on the analyzed information.

[1195] The "means for presenting highly relevant information to the user based on the search results" refers to an interface and its control device for displaying highly relevant information obtained by the search to the user.

[1196] "Means for searching for further data and providing an appropriate answer based on the user's additional question" refers to a system that searches for additional data and generates and provides an appropriate answer in response to a more detailed question from the user.

[1197] The "means for updating the results of troubleshooting in the database" is a function for recording the results of troubleshooting performed by the user in the database for future reference.

[1198] The "means for recognizing emotions based on the user's input content, input speed, and input frequency" is an emotion engine that analyzes the user's input content, input speed, input frequency, etc., and determines the user's emotional state.

[1199] The "means for adjusting the information presented in accordance with the user's emotions" is a function for adjusting the detail and format of the information presented based on the user's psychological state recognized by the emotion engine.

[1200] MODE FOR CARRYING OUT THE INVENTION

[1201] The system of this invention combines an emotion engine with a support system that enables users to quickly and effectively respond to problems with robots operating in factories. The components of this system are as follows:

[1202] User Interface (Terminal)

[1203] Users access the system using a smartphone or tablet. They log in to the system from their device and input the current problem with the robot. This problem is reported in chat format, and specific problems such as "the robot arm won't move" are entered.

[1204] server

[1205] The server receives the problem information entered by the user, analyzes the information using an analysis device, extracts specific keywords and phrases, and searches a database.

[1206] Database

[1207] The database stores past troubleshooting history and robot specifications. The server searches to collect related past failure cases and technical information.

[1208] Emotion Engine

[1209] The server uses an emotion engine to analyze the user's emotional state based on the content, speed, and frequency of their input. For example, if it determines that the user is feeling stressed, the emotion engine will respond accordingly.

[1210] Information provision

[1211] The server presents appropriate information to the user based on the analysis results and the emotion engine's analysis results. If the emotion engine determines that the user is feeling stressed, it simplifies the information presented and provides specific step-by-step guidance. For example, it may provide advice such as, "In similar past cases, restarting the device resolved the issue."

[1212] Obtaining additional information

[1213] If the user needs more information, they enter a follow-up question, and the server again searches the database and provides the appropriate answer.

[1214] Troubleshooting and database updates

[1215] The user attempts to resolve the problem according to the provided guidelines. If the problem is resolved, the user enters the results into the system and updates the database. For example, information such as "The power supply unit was replaced and the system returned to normal" is entered.

[1216] Specific examples

[1217] Case 1: If the user types "My robot arm won't move. Help me, I'm in trouble," the server will suggest "Emotional state: Stress. Case applies: Restart will solve it."

[1218] Prompt Sentence Examples

[1219] User input: "My robot arm won't move. Help, I'm in trouble."

[1220] Emotion engine detection result: Stress

[1221] Advice to offer: Rebooting solves the problem

[1222] This system allows users to quickly and appropriately respond to robot failures, and with the help of the emotion engine, it is also possible to reduce psychological stress.

[1223] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1224] Program processing steps

[1225] Step 1:

[1226] The user logs into the system using a terminal and inputs the robot's trouble status in chat format. This input includes specific problem information, such as "The robot arm won't move." The terminal then sends this input to the server.

[1227] Step 2:

[1228] The server analyzes the received fault information and extracts important keywords and phrases from the user's input. For example, keywords such as "robot arm" and "not working" are extracted. Based on the results of this analysis, the server prepares to search past data and specification data.

[1229] Step 3:

[1230] The server searches the database based on the keywords extracted through the analysis, collecting information related to past similar failure cases and technical specifications. For example, it can obtain relevant information such as "previous similar cases were resolved by restarting the system."

[1231] Step 4:

[1232] At the same time, the server uses an emotion engine to analyze the user's emotional state based on the content, speed, and frequency of input. For example, if the user types quickly and includes "I'm in trouble," the emotion engine will recognize that the user is in a stressful state.

[1233] Step 5:

[1234] The server presents relevant information to the user based on the search results and the emotion engine's analysis. If the emotion engine detects that the user is stressed, it simplifies the information presented and provides specific step-by-step guidance. For example, it may provide detailed instructions for rebooting the device.

[1235] Step 6:

[1236] If the user enters an additional question, the device sends it to the server, which again searches the database and generates an appropriate answer. For example, if the user asks, "How do I reboot?", the server provides detailed reboot instructions.

[1237] Step 7:

[1238] The user responds to the problem according to the information provided. If the problem is resolved, the result is reported to the system. For example, a result such as "After rebooting, the robot arm is now operating normally" is entered.

[1239] Step 8:

[1240] The server receives reports from users and updates the database with the results of the troubleshooting. The results are recorded as new troubleshooting results and are used for future troubleshooting.

[1241] 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.

[1242] 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.

[1243] 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.

[1244] [Fourth embodiment]

[1245] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1246] 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.

[1247] 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).

[1248] 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.

[1249] 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.

[1250] 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).

[1251] 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.

[1252] 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.

[1253] 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.

[1254] 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.

[1255] 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.

[1256] 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.

[1257] 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."

[1258] ---

[1259] MODE FOR CARRYING OUT THE INVENTION

[1260] The system of the present invention is a support system that enables users to quickly and effectively deal with base station failures. A specific embodiment of this system will be described below.

[1261] The system includes the following components:

[1262] 1. User Interface (Terminal)

[1263] 2. Server

[1264] 3. Database

[1265] 1. User Input

[1266] Users log in to the system from their devices to troubleshoot base station failures. After logging in, users can enter the current status of the base station failure in chat format. For example, a problem such as "Base station A is not responding" can be reported.

[1267] 2. Server analysis

[1268] The device sends the entered information to the server. The server receives this information, and an analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted.

[1269] 3. Searching for data

[1270] The server uses the extracted keywords and phrases to search a database containing past troubleshooting history and wireless device specifications, collecting related past failure cases and technical information.

[1271] 4. Information provision

[1272] The server then provides the user with appropriate information in chat format based on the search results. For example, specific advice such as "In similar past cases, the cause was a power supply unit failure, so we recommend checking the operation of the power supply unit" is provided.

[1273] 5. Obtaining additional information

[1274] If the user needs more information, they can enter a follow-up question, such as "How do I check the power supply unit?" The device sends this question to the server, which again searches the database and generates an appropriate answer.

[1275] 6. Troubleshooting and updating the database

[1276] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user may enter information such as "I replaced the power supply unit and the problem was resolved." The server receives this information and records it in the database as a new troubleshooting result.

[1277] Specific examples

[1278] Case 1: If a connection loss occurs at base station B, the user can enter "base station B connection loss" and the server will search for past connection loss cases and suggest that "a similar case occurred after a firmware update and was resolved by rebooting the device." The user attempts to reboot the device and the problem is resolved.

[1279] Case 2: If base station C shows an abnormal flashing lamp, the user inputs "Base station C, abnormal flashing lamp." The server checks the meaning of the flashing lamp in the radio specifications and responds, "There is a possibility of an abnormal voltage. We recommend checking the voltage." The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[1280] This invention allows users to quickly and efficiently deal with base station failures, and helps to solve the problem of skill transfer due to personnel changes.

[1281] The processing flow will be explained below.

[1282] ---

[1283] Processing Steps

[1284] Step 1:

[1285] User: Enter your username and password to log into the system from a terminal.

[1286] Terminal: Sends authentication information (username and password) to the server.

[1287] Server: Checks the authentication information against the database, and if authentication is successful, sends the user a login success message and provides a chat entry screen.

[1288] Step 2:

[1289] User: Enter details of the base station problem in chat format (e.g., "Base station A is not responding").

[1290] Terminal: Sends typed chat messages to the server.

[1291] Server: Receives the problem details and sends them to the text analysis engine.

[1292] Step 3:

[1293] Server: A text analysis engine analyzes the outage details and extracts important keywords and phrases (e.g., "Base Station A" or "Not Responding").

[1294] Server: Using the extracted keywords and phrases, search the database of past fault responses and the database of radio equipment specifications.

[1295] Step 4:

[1296] Server: Filter search results to find information that is most relevant to the current problem (e.g., "power supply unit failure case").

[1297] Server: Send relevant information and recommended actions to the user via chat (e.g. "We recommend checking the power supply unit's operation").

[1298] Step 5:

[1299] User: Takes action based on the server's suggestion (e.g., "Check the power supply unit").

[1300] User: If more information is needed, enter further details in the chat (e.g. "How do I check my power supply unit?").

[1301] Terminal: Sends a follow-up question to the server.

[1302] Server: Receives additional questions, searches the database again, generates appropriate answers, and sends them via chat.

[1303] Step 6:

[1304] User: Continue troubleshooting based on the information provided, and when the problem is resolved, report the result to the system via chat (e.g., "Replaced the power supply unit and recovered").

[1305] Terminal: Sends the troubleshooting results to the server.

[1306] Server: Analyzes the received response results and records them in a database (e.g., "A reboot was required due to a power supply unit failure").

[1307] Step 7:

[1308] User: After the troubleshooting is completed and the report is complete, log out.

[1309] Terminal: Sends a logout request to the server.

[1310] Server: End the user session and display a logout complete message.

[1311] ---

[1312] This allows users to effectively handle base station failures and quickly resolve problems by utilizing past information.

[1313] Example 1

[1314] 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."

[1315] Conventional base station fault response systems have the problem that users need a great deal of specialized knowledge and experience to identify the cause of the fault and take appropriate measures. It is also difficult to effectively utilize past fault response history and technical information, which can result in time-consuming fault response. Furthermore, there is also the issue of skill transfer when personnel are replaced, resulting in inconsistent quality of fault response.

[1316] 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.

[1317] In this invention, the server includes means for accepting input from a user, means for authenticating the user, means for analyzing the problem information entered by the user, means for searching past data and specification data based on the analyzed problem information, means for providing the user with highly relevant information based on the search results, means for the user to input additional questions based on the provided information, means for searching further data based on the additional questions and providing appropriate answers, and means for updating the database with the results of troubleshooting. This allows the user to quickly and efficiently identify the cause of the problem and take appropriate measures. Furthermore, by effectively utilizing past troubleshooting history and technical information, it is expected that response time will be shortened and quality will be improved. Furthermore, the problem of skill transfer due to personnel changes will be eliminated, enabling consistent troubleshooting.

[1318] "User" refers to a person who uses this system to troubleshoot base station failures.

[1319] "Terminal" refers to an electronic device that allows a user to access and operate the system.

[1320] "Server" refers to a computer system that receives input information from a user and performs analysis and database searches.

[1321] "Database" refers to data storage that stores technical information such as past troubleshooting history and radio equipment specifications.

[1322] An "analysis device" refers to software or hardware that has the function of analyzing input information from a user and extracting important keywords and phrases.

[1323] "Chat style" refers to an interface style in which the user and the system exchange messages in a two-way manner.

[1324] "Keywords" refer to words or phrases that are considered to be particularly important in the analyzed problem information.

[1325] A "phrase" refers to a string of words that are considered to be particularly important from the analyzed problem information.

[1326] "Login" refers to the authentication process required for a user to access a system.

[1327] "Response results" refers to the specific actions and results that a user reports to the system after responding to a failure.

[1328] "Additional Information" refers to a question or request that a user enters into the system to seek more detailed information on an initial answer.

[1329] MODE FOR CARRYING OUT THE INVENTION

[1330] The system of the present invention is a support system that enables users to quickly and effectively deal with base station failures. A specific embodiment of this system will be described below.

[1331] Components

[1332] The system mainly consists of the following components:

[1333] 1. User Interface (Terminal)

[1334] 2. Server

[1335] 3. Database

[1336] User input and login

[1337] A user accesses the system using a terminal and logs in by entering a user ID and password. After successful authentication, the user enters the problem into the chat interface of the system. For example, the user reports a problem such as "Base Station A is not responding." The terminal then sends this input information to the server.

[1338] Server-based analysis and data retrieval

[1339] The server receives the user's input and uses a text analysis engine to extract important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted. The server then uses the extracted keywords to convert them into SQL queries and search the database for past troubleshooting history and specification data.

[1340] Information and responses

[1341] The server formats the search results and provides the user with appropriate information in chat format. For example, it can provide specific advice such as, "In similar past cases, the cause was a power supply unit failure, so we recommend checking the operation of the power supply unit." If the user needs more information, they can enter an additional question. The device sends this question to the server, which then searches the database again and provides an appropriate answer.

[1342] Fixing the problem and updating the database

[1343] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system from their terminal. For example, they may report that "the problem has been resolved by replacing the power supply unit." The server receives this information and records it as a new case in the database.

[1344] Specific examples

[1345] Case 1: When base station B loses connection

[1346] Prompt: "Please tell us about past cases of base station B losing connection."

[1347] When the user enters "Base Station B connection lost," the server searches for past connection loss cases and suggests, "In a previous similar case, this occurred after a firmware update. Restarting the device resolved the issue." The user attempts to restart the device and the issue is resolved.

[1348] Case 2: Base station C shows abnormal flashing light

[1349] Prompt: "What should you do if a lamp flashing abnormality occurs on base station C?"

[1350] When the user inputs "Base Station C Lamp Flashing Abnormal", the server checks the meaning of the lamp flashing from the specification data and responds, "There is a possibility of abnormal voltage. We recommend checking the voltage." The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[1351] This invention allows users to quickly and efficiently handle base station faults. Effective use of past fault handling history and technical information can be expected to shorten response times and improve quality. Furthermore, it also eliminates the problem of skill transfer due to personnel changes, enabling consistent fault handling.

[1352] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1353] Processing flow

[1354] Step 1:

[1355] User login

[1356] Input: The user inputs the user ID and password from the terminal.

[1357] Data calculation: The terminal sends the user ID and password to the server, which compares them with the user information in the database and performs the authentication process.

[1358] Output: The server returns a message to the terminal indicating whether the authentication was successful or failed.

[1359] Specific operation: If the user successfully logs in, the system home screen will be displayed on the terminal.

[1360] Step 2:

[1361] Enter the fault status

[1362] Input: The user inputs the fault condition about the base station in the chat interface, for example, "Base station A is not responding."

[1363] Data calculation: The terminal sends input information to the server.

[1364] Output: The server saves the received input information in text format.

[1365] Specific operation: The terminal displays to the user that the input information has been successfully accepted.

[1366] Step 3:

[1367] Analysis of input information

[1368] Input: The server receives text data about the problem from the user.

[1369] Data Calculation: The server uses a text analysis engine to extract important keywords and phrases.

[1370] Output: Extracted keywords or phrases (e.g., "Base Station A" or "Not Responding").

[1371] Specific operation: The server saves the extracted keywords as variables.

[1372] Step 4:

[1373] Searching the database

[1374] Input: Extracted keywords (e.g., "Base Station A" or "Not Responding").

[1375] Data Calculation: The server uses the keywords to generate an SQL query to search the database.

[1376] Output: Relevant incident history and technical information.

[1377] Specific behavior: The server formats the search results and uses them in the next step.

[1378] Step 5:

[1379] Providing information

[1380] Input: Related information retrieved by the server as a search result.

[1381] Data Calculation: The server organizes relevant information and generates messages that are presented to the user in an easy-to-understand format.

[1382] Output: Generated message (e.g. "In similar past cases, the cause was a power supply unit failure. We recommend checking the power supply unit's operation.").

[1383] Specific operation: The server sends the generated message to the terminal, which displays it to the user.

[1384] Step 6:

[1385] Obtaining additional information

[1386] Input: A question to be entered by the user (e.g. "How do I check the power supply unit?").

[1387] Data calculation: The terminal sends a follow-up question to the server, which again searches the database and generates an appropriate answer.

[1388] Output: An appropriate answer (e.g. "Steps on how to check your power supply unit").

[1389] Specific operation: The server sends the generated answer to the terminal, which displays it to the user.

[1390] Step 7:

[1391] Troubleshooting

[1392] Input: The user performs troubleshooting based on the information provided.

[1393] Data calculation: Information on the results of the troubleshooting action taken (e.g., "The power supply unit was replaced and the problem was resolved").

[1394] Output: The user enters the result information into the terminal.

[1395] Specific operation: The terminal sends the result information to the server and stores it in the database.

[1396] Step 8:

[1397] Database Update

[1398] Input: User-reported troubleshooting result information.

[1399] Data calculation: The server stores the received result information in the database as a new case.

[1400] Output: A new incident record is added to the database.

[1401] Specific operation: A message is displayed on the user's device indicating that the response result has been successfully reported.

[1402] The above are the specific processing steps of the program of this system.

[1403] (Application example 1)

[1404] 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."

[1405] In modern manufacturing, when machinery used in factories breaks down, it is necessary to quickly and accurately identify the cause and take appropriate measures. However, in many cases, specialized knowledge is required to respond to the breakdown, which can lead to delays. Furthermore, it is difficult for inexperienced staff to take accurate action, resulting in a decline in production efficiency as the breakdown continues for a long time. This invention aims to prevent a decline in production efficiency by quickly and accurately identifying the breakdown status of machinery in factories and providing appropriate measures.

[1406] 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.

[1407] In this invention, the server includes means for accepting input from a user, means for analyzing the problem information input by the user, means for searching past data and specification data based on the analyzed problem information, means for presenting highly relevant information to the user based on the search results, means for searching further data based on additional questions from the user and providing appropriate answers, means for updating the database with the results of troubleshooting, and means for inputting the status of machine failures in a chat format and providing information on troubleshooting, thereby enabling the cause of the failure to be identified quickly and accurately and appropriate measures to be taken promptly.

[1408] "User" refers to the person who operates the system and provides input and questions.

[1409] "Input" refers to the act of a user providing information to a system.

[1410] "Problem information" refers to detailed information about a fault or malfunction entered by a user.

[1411] "Analysis" refers to the process by which the server reviews the problem information it receives and identifies significant keywords and patterns.

[1412] "Search" refers to the act of examining past data or specifications based on analyzed keywords or phrases.

[1413] "Presenting" refers to the act of displaying information relevant to the user based on the search results.

[1414] A "follow-up question" refers to a question a user asks to obtain more detailed information about information that has already been presented.

[1415] "Answer" refers to information provided in response to a user's follow-up question.

[1416] "Update" refers to the act of adding new troubleshooting results to the database.

[1417] "Search results" refers to past data and specification information obtained based on the analyzed problem information.

[1418] "Database" refers to a system that stores information such as past failure cases and specifications.

[1419] "Machinery in a factory" refers to various machinery and equipment installed and operated at manufacturing sites.

[1420] "Chat format" refers to a form of interaction via text messages.

[1421] This invention is a support system for quickly and effectively responding to breakdowns in machinery in a factory, and includes the following components:

[1422] System Components

[1423] 1. User Interface (Terminal)

[1424] 2. Server

[1425] 3. Database

[1426] 1. User Input

[1427] Users log in to the system using a tablet or smartphone and enter information about malfunctions in machinery within the factory in chat format. For example, they can report a problem such as "The motor of Machine A is making an unusual noise."

[1428] 2. Server analysis

[1429] The server receives the information sent from the device, and the analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "machine A," "motor," and "abnormal noise" are extracted.

[1430] 3. Searching for data

[1431] The server uses the extracted keywords and phrases to search a database containing past troubleshooting records and machine specifications, collecting relevant past failure cases and technical information.

[1432] 4. Information provision

[1433] The server then provides the user with appropriate information in chat format based on the search results. For example, it may provide specific advice such as, "If the motor is making strange noises, it is caused by worn bearings. Please check the condition of the bearings."

[1434] 5. Obtaining additional information

[1435] If the user needs more detailed information, they can enter a follow-up question, such as "How do I check the bearing?" The device sends this question to the server, which again searches the database and provides the appropriate answer.

[1436] 6. Troubleshooting and updating the database

[1437] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user might enter information such as "I replaced the bearing and the abnormal noise disappeared." The server receives this information and records it in the database as a new troubleshooting result.

[1438] Hardware and software used

[1439] Hardware: tablets, smartphones, factory robots

[1440] Software: Python, Requests library, Web API

[1441] Examples of concrete examples and prompts

[1442] As a concrete example, the following shows the procedure for a user to report that "the motor of machine A is making an abnormal noise" and obtain a solution to the problem. In this case, the server refers to past cases of "abnormal motor noise" and provides information such as "If an abnormal motor noise occurs, it is caused by worn bearings. Please check the condition of the bearings."

[1443] An example prompt for a generative AI model might be:

[1444] "The motor of machine A is making an unusual noise. Please suggest an appropriate solution based on past malfunction cases."

[1445] This invention allows users to quickly identify the cause of a malfunction and take appropriate measures. Furthermore, even inexperienced staff can handle the problem with a certain degree of accuracy, which contributes to improving production efficiency.

[1446] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1447] Step 1:

[1448] A user logs into the system using a tablet or smartphone. They enter a username and password to authenticate the login and begin the session. The input for this step is the user's authentication information, and the output is a message indicating whether the login was successful or not.

[1449] Step 2:

[1450] The user inputs the breakdown information in chat format. For example, "The motor of machine A is making an unusual noise." This information is sent from the terminal to the server. The input is text data of the breakdown information, and the output is the problem information received by the server.

[1451] Step 3:

[1452] The server analyzes the received problem information. The analysis device breaks down the text data using techniques such as natural language processing and extracts important keywords and phrases. For example, keywords such as "machine A," "motor," and "abnormal noise" are extracted. The input is the text data of the received problem information, and the output is a list of extracted keywords.

[1453] Step 4:

[1454] The server uses the extracted keywords and phrases to search the database for past troubleshooting records and specification data. The search results include related past cases and technical information. The input is a list of keywords, and the output is related past data.

[1455] Step 5:

[1456] Based on the search results, the server provides the user with appropriate information in chat format. For example, a message such as "If an abnormal noise occurs in the motor, it may be caused by worn bearings. Please check the condition of the bearings" is generated and sent to the terminal. The input is the search result data, and the output is a suggested message to the user.

[1457] Step 6:

[1458] If the user needs more detailed information, they enter a follow-up question, for example, "How do I check the bearing?" The question is sent from the terminal to the server. The input is the follow-up question text, and the output is the question received by the server.

[1459] Step 7:

[1460] The server searches the database again and generates an appropriate answer to the follow-up question. For example, it provides specific instructions such as "To check the bearing, first stop the motor, remove the cover, and check its condition." The input is the user's follow-up question, and the output is a detailed answer message.

[1461] Step 8:

[1462] The user performs troubleshooting based on the information provided and reports the results to the system. For example, the user may report that "the abnormal noise was resolved after replacing the bearing." The troubleshooting results are sent from the device to the server. The input is the text data of the troubleshooting results, and the output is the troubleshooting results received by the server.

[1463] Step 9:

[1464] The server updates the received response results in the database. They are recorded as new troubleshooting cases and used for future searches. The input is the troubleshooting result data, and the output is the updated database.

[1465] An example of a prompt for a generative AI model: "The motor of machine A is making an unusual noise. Please suggest an appropriate solution based on past failure cases."

[1466] 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.

[1467] ---

[1468] MODE FOR CARRYING OUT THE INVENTION

[1469] The system of the present invention combines an emotion engine with a support system that allows users to quickly and effectively handle base station failures. This system includes the following components:

[1470] The system includes the following components:

[1471] 1. User Interface (Terminal)

[1472] 2. Server

[1473] 3. Database

[1474] 4. Emotion Engine

[1475] 1. User Input

[1476] Users log in to the system from their devices to troubleshoot base station failures. After logging in, users can enter the current status of the base station failure in chat format. For example, a problem such as "Base station A is not responding" can be reported.

[1477] 2. Server analysis

[1478] The device sends the entered information to the server. The server receives this information, and an analysis device analyzes the problem information. This analysis extracts important keywords and phrases. For example, keywords such as "base station A" and "not responding" are extracted.

[1479] 3. Emotion Recognition by Emotion Engine

[1480] At the same time, the server uses an emotion engine to recognize the user's emotions based on the content, speed, and frequency of input. For example, if it determines that the user is feeling stressed, it will recognize that action is necessary.

[1481] 4. Searching for data

[1482] The server uses the extracted keywords and phrases to search a database containing past troubleshooting history and wireless device specifications, collecting related past failure cases and technical information.

[1483] 5. Information provision

[1484] The server then provides the user with appropriate information in chat format based on the search results. If the user is feeling stressed, the emotion engine simplifies the information provided and provides specific step-by-step guidance. For example, specific advice such as "In similar past cases, a power supply unit failure was the cause, so we recommend checking the operation of the power supply unit" is provided.

[1485] 6. Obtaining additional information

[1486] If the user needs more detailed information, they enter an additional question, such as "How do I check the power supply unit?" The device sends this question to the server, which again searches the database and generates an appropriate answer. The emotion engine continuously monitors the user's emotional state and responds adaptively.

[1487] 7. Troubleshooting and updating the database

[1488] The user performs troubleshooting based on the provided information. After the problem is resolved, the user reports the results of the troubleshooting to the system. For example, the user may enter information such as "I replaced the power supply unit and the problem was resolved." The server receives this information and records it in the database as a new troubleshooting result.

[1489] Specific examples

[1490] Case 1: If a connection loss occurs at base station B, the user can enter "base station B connection loss." The server will search for past connection loss cases and suggest, "In a previous similar case, this occurred after a firmware update. A reboot resolved the issue." If the emotion engine detects the user's stress state, it will provide an additional step-by-step guide detailing the reboot procedure. The user attempts to reboot and the issue is resolved.

[1491] Case 2: If base station C shows an abnormal flashing lamp, the user can input "Base station C, abnormal flashing lamp" and the server will look up the meaning of the flashing lamp in the radio specifications and respond with "There is a possibility of abnormal voltage. We recommend checking the voltage." If the emotion engine detects the user's hesitation, it will provide detailed instructions on how to check the voltage. The user checks the voltage and finds an abnormal value. The problem is resolved by replacing the power supply unit.

[1492] This invention allows users to effectively respond to base station failures, and the introduction of an emotion engine allows information to be presented that is adapted to the user's psychological state, enabling faster and more reliable problem solving.

[1493] The processing flow will be explained below.

[1494] Processing Steps

[1495] Step 1:

[1496] User: Enter your username and password to log into the system from a terminal.

[1497] Terminal: Sends authentication information (username and password) to the server.

[1498] Server: Checks the authentication information against the database, and if authentication is successful, sends the user a login success message and provides a chat entry screen.

[1499] Step 2:

[1500] User: Enter details of the base station problem in chat format (e.g., "Base station A is not responding").

[1501] Terminal: Sends typed chat messages to the server.

[1502] Server: Receives the problem details and sends them to the text analysis engine.

[1503] Step 3:

[1504] Server: A text analysis engine analyzes the outage details and extracts important keywords and phrases (e.g., "Base Station A" or "Not Responding").

[1505] Server: Using the extracted keywords and phrases, search the database of past fault responses and the database of radio equipment specifications.

[1506] Step 4:

[1507] Server: Filter search results to find information that is most relevant to the current problem (e.g., "power supply unit failure case").

[1508] Server: Send relevant information and recommended actions to the user via chat (e.g. "We recommend checking the power supply unit's operation").

[1509] Step 5:

[1510] Server: The emotion engine recognizes the user's emotional state based on the content, speed, and frequency of the user's input.

[1511] Server: If the user feels stressed, the emotion engine will provide simplified response procedures, such as a concrete step-by-step guide with illustrations.

[1512] Step 6:

[1513] User: Takes action based on the server's suggestion (e.g., "Check the power supply unit").

[1514] User: If more information is needed, enter further details in the chat (e.g. "How do I check my power supply unit?").

[1515] Terminal: Sends a follow-up question to the server.

[1516] Server: Receives additional questions, searches the database again, generates appropriate answers, and sends them via chat.

[1517] Step 7:

[1518] User: Continue troubleshooting based on the information provided, and when the problem is resolved, report the result to the system via chat (e.g., "Replaced the power supply unit and recovered").

[1519] Terminal: Sends the troubleshooting results to the server.

[1520] Server: Analyzes the received response results and records them in a database (e.g., "The power supply unit failed and needed to be replaced").

[1521] Step 8:

[1522] User: After the troubleshooting is completed and the report is complete, log out.

[1523] Terminal: Sends a logout request to the server.

[1524] Server: End the user session and display a logout complete message.

[1525] ---

[1526] These detailed processing steps allow users to effectively respond to base station failures, and the introduction of an emotion engine allows for the presentation of information adapted to the user's psychological state, enabling faster and more reliable problem resolution.

[1527] Example 2

[1528] 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."

[1529] When a failure occurs in wireless communication equipment such as base stations, a fast and accurate response is required, but the stress and anxiety felt by users during this process often becomes a problem. Conventional failure response systems only provide technical information without considering the user's emotional state, which can result in a slow and inaccurate response. Another issue is the difficulty of quickly obtaining appropriate information when additional information is needed.

[1530] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting input from a user, means for analyzing problem information input by the user, means for searching past data and wireless communication device specification data based on the analyzed problem information, means for extracting keywords and phrases based on the analyzed problem information, means for recognizing the emotional state of the user from the input content, input speed, and input frequency and providing adaptive information, means for presenting information to the user in a chat format, means for searching further data based on additional questions from the user and providing appropriate answers, and means for updating the database with the results of the troubleshooting. This enables fast and accurate troubleshooting that is adapted to the user's psychological state.

[1531] "User" refers to a person or organization that logs into the system and responds to a fault by inputting the fault status of the base station.

[1532] The "means for accepting input" refers to an interface that allows a user to input a fault condition or question into the system, and has the function of receiving information input from the user.

[1533] "Means for analyzing problem information" refers to technology or devices for analyzing the input content, identifying the problem, and extracting keywords and phrases related to the problem.

[1534] The "searching means" refers to a function for investigating past data and wireless communication device specification data stored in a database based on the analyzed problem information.

[1535] "Means for recognizing emotional state" refers to technology that determines a user's emotional state based on the user's input content, input speed, input frequency, etc., and evaluates the stress or anxiety the user is currently feeling.

[1536] "Means for providing adaptive information" refers to technology that has the function of providing more appropriate and easy-to-understand information by taking into account the user's emotional state.

[1537] "Means using chat" refers to an interface that allows interaction with users in chat format and provides and obtains information through text messages.

[1538] "Means for providing appropriate answers" refers to the function of searching the database again in response to additional questions from the user and generating the most appropriate and relevant answer.

[1539] "Means of updating the database" refers to the technology that stores and records the results of troubleshooting as new data in a database so that they can be used to handle future troubleshooting.

[1540] MODE FOR CARRYING OUT THE INVENTION

[1541] overview

[1542] This invention relates to a support system that allows users to quickly and accurately respond to faults in base stations and wireless communication devices. This system is characterized by the fact that it can provide information according to the user's psychological state by incorporating emotion recognition technology. The system includes the following components:

[1543] 1. User Interface (Terminal)

[1544] 2. Server

[1545] 3. Database

[1546] 4. Emotion Engine

[1547] Components and Operation

[1548] User Interface (Terminal)

[1549] To troubleshoot a base station failure, a user logs into the system using a terminal. After logging in, the user inputs the problem situation into the terminal in chat format. For example, the user can input specific problem information such as "Base station A is not responding."

[1550] server

[1551] Information entered on the device is sent to the server. The server first analyzes this information and extracts important keywords and phrases (e.g., "base station A" or "not responding"). Next, the server uses an emotion engine (e.g., IBM Watson or Azure Text Analytics) to analyze the user's emotional state based on the content and speed of their input. For example, if the server determines that the user is feeling stressed, that information is reflected in the information provided to the user.

[1552] Database

[1553] The server searches a database (e.g., MySQL, PostgreSQL) based on the extracted keywords and phrases, collecting relevant data such as past troubleshooting history and wireless device specifications. Based on this information, the server generates a message to be provided to the user and presents appropriate information. If the user is feeling emotionally stressed, the server can simplify the displayed information and provide specific step-by-step guidance.

[1554] Information and further questions

[1555] The system responds to the problem based on the information provided by the user, but if more detailed information is needed, the device sends additional questions to the server. For example, a question such as "How do I check the power supply unit?" is entered. The server then searches the database again, generates an appropriate answer, and provides it to the user. The emotion engine is also utilized during this process, allowing the system to respond according to the user's psychological state.

[1556] Troubleshooting and database updates

[1557] The user performs troubleshooting based on the provided information, and when the problem is resolved, the result is reported to the system from the terminal. For example, information such as "The power supply unit was replaced and the problem was resolved" is entered. The server records this information and updates the database with the new troubleshooting result.

[1558] Specific examples

[1559] Case 1:

[1560] If a connection loss occurs at base station B, the user enters "base station B connection loss" into the device. The server searches for past cases of connection loss and suggests, "In a similar case in the past, this occurred after a firmware update. Restarting the device resolved the issue." If the emotion engine detects stress in the user, it provides an additional step-by-step guide detailing the restart procedure. The user attempts to restart the device and the issue is resolved.

[1561] Case 2:

[1562] If base station C shows an abnormal flashing lamp, the user can enter "Base station C abnormal flashing lamp" into their terminal. The server will look up the meaning of the flashing lamp in the wireless device specifications and respond with "There is a possibility of abnormal voltage. We recommend checking the voltage." If the emotion engine detects the user's hesitation, it will provide detailed instructions on how to check the voltage. The user checks the voltage and discovers an abnormal value. The problem can be resolved by replacing the power supply unit.

[1563] This invention enables users to respond to base station failures quickly and efficiently while receiving information and technical support that adapts to their psychological state. This system utilizes a user-friendly interface and advanced emotion analysis technology to respond to failures in base stations and other wireless communication devices more quickly and accurately than conventional methods.

[1564] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1565] Step 1:

[1566] A user logs in to the system using a terminal. The user enters a user ID and password as input. The terminal sends the entered user ID and password to the server. The server compares them with the authentication information stored in the database, and if authentication is successful, the user is presented with the main screen.

[1567] > Specific operation: The user accesses the system URL on a browser and enters their ID and password into the login form. The server checks the received ID and password against the database, and if authentication is successful, redirects them to the dashboard screen.

[1568] Step 2:

[1569] The user uses the chat window on the device to input the current base station failure status. The input sends specific problem information, such as "Base station A is not responding." The device then sends this information to the server.

[1570] > Specific operation: The user types "Base station A is not responding" in the chat window and clicks the send button. The device displays the input in real time and sends this information to the server.

[1571] Step 3:

[1572] The server analyzes the received information. It receives the problem information as input and uses an analyzer to extract important keywords and phrases. The output is keywords such as "Base Station A" and "Not Responding."

[1573] > What happens: The server uses a natural language processing library (e.g., NLTK, spaCy) to tokenize the incoming information and apply a keyword extraction algorithm. The extracted keywords are temporarily stored.

[1574] Step 4:

[1575] The server uses an emotion engine to analyze the user's emotional state, taking the user's problem information, input speed, and input frequency as input, and generating emotion tags (e.g., stress, impatience) as output.

[1576] > Specific operation: The server sends the input data to an emotion recognition engine (e.g., IBM Watson, Azure Text Analytics), which analyzes the obtained emotional information. As a result, an emotion tag such as "stress" or "anxiety" is assigned.

[1577] Step 5:

[1578] The server uses the extracted keywords and phrases to search the database. It receives keywords such as "base station A" and "not responding" as input, and obtains related past troubleshooting history and wireless device specification data as output.

[1579] > Specific operation: The server generates a search query and executes it against a database (e.g., MySQL, PostgreSQL). The search results are temporarily stored in the server's memory.

[1580] Step 6:

[1581] The server provides appropriate information to users based on the collected information and emotion tags. It receives search results and emotion tags as input, and generates edited information to be presented to users as output.

[1582] > Specific operation: The server refers to the search results and emotion tags and generates a message to present to the user. For example, it generates a guide such as "We recommend checking the operation of the power supply unit" and sends it to the device.

[1583] Step 7:

[1584] The user inputs additional questions based on the information provided. For example, "How do I check the power supply unit?" The device sends this information to the server.

[1585] > Specific operation: The user types "How do I check the power supply unit?" into the chat window and sends it. The device displays this information in real time and sends it to the server.

[1586] Step 8:

[1587] The server again searches the database and generates an appropriate answer, taking the additional question and related keywords as input and providing a specific answer as output.

[1588] > Specific action: The server again performs NLP processing, generates a search query, and executes a search against the database. The generated answer includes specific instructions such as "First, make sure the power cable is securely connected."

[1589] Step 9:

[1590] The user responds to the problem based on the information provided and resolves it. After the problem is resolved, the result of the response is reported to the system. The terminal sends a resolution result such as "The power supply unit was replaced and the problem was resolved." The terminal sends this information to the server, which records the result in a database.

[1591] > Specific operation: The user types "I replaced the power supply unit and the problem was resolved" in the chat window and sends it. The server receives this information and registers the corresponding result in the database using an INSERT statement.

[1592] This series of processes allows the user to take prompt and accurate action to resolve the problem, and also ensures efficient operation of the entire system.

[1593] (Application example 2)

[1594] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1595] Robots and other equipment operating in factories require a rapid and appropriate response when they break down or experience problems. However, conventional systems can be slow to identify the cause of a problem and provide a solution, which can lead to reduced productivity and escalation of the problem. Furthermore, the psychological stress and impatience of the workers who are dealing with the problem can also be a problem. The present invention aims to solve these problems by providing a system that enables rapid and effective troubleshooting and takes into consideration the psychological state of the workers.

[1596] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for accepting input from a user, means for analyzing problem information input by the user, means for searching past data and specification data based on the analyzed problem information, means for presenting highly relevant information to the user based on the search results, means for searching further data based on additional questions from the user and providing appropriate answers, means for updating the database with the results of troubleshooting, means for recognizing the user's emotions based on the content, speed, and frequency of the user's input, and means for adjusting the information presented in accordance with the user's emotions. This enables quick and appropriate troubleshooting, reduces psychological stress on workers, and enables efficient problem solving.

[1597] definition statement

[1598] The "means for accepting input from the user" is an interface that allows the user to input problem information and questions into the system via a terminal.

[1599] The "means for analyzing the problem information input by the user" refers to an analysis device that receives the problem information input by the user and identifies and extracts relevant keywords and phrases.

[1600] The "means for searching past data and specification data based on the analyzed problem information" is a device that searches a database in which past failure cases and technical specifications are stored based on the analyzed information.

[1601] The "means for presenting highly relevant information to the user based on the search results" refers to an interface and its control device for displaying highly relevant information obtained by the search to the user.

[1602] "Means for searching for further data and providing an appropriate answer based on the user's additional question" refers to a system that searches for additional data and generates and provides an appropriate answer in response to a more detailed question from the user.

[1603] The "means for updating the results of troubleshooting in the database" is a function for recording the results of troubleshooting performed by the user in the database for future reference.

[1604] The "means for recognizing emotions based on the user's input content, input speed, and input frequency" is an emotion engine that analyzes the user's input content, input speed, input frequency, etc., and determines the user's emotional state.

[1605] The "means for adjusting the information presented in accordance with the user's emotions" is a function for adjusting the detail and format of the information presented based on the user's psychological state recognized by the emotion engine.

[1606] MODE FOR CARRYING OUT THE INVENTION

[1607] The system of this invention combines an emotion engine with a support system that enables users to quickly and effectively respond to problems with robots operating in factories. The components of this system are as follows:

[1608] User Interface (Terminal)

[1609] Users access the system using a smartphone or tablet. They log in to the system from their device and input the current problem with the robot. This problem is reported in chat format, and specific problems such as "the robot arm won't move" are entered.

[1610] server

[1611] The server receives the problem information entered by the user, analyzes the information using an analysis device, extracts specific keywords and phrases, and searches a database.

[1612] Database

[1613] The database stores past troubleshooting history and robot specifications. The server searches to collect related past failure cases and technical information.

[1614] Emotion Engine

[1615] The server uses an emotion engine to analyze the user's emotional state based on the content, speed, and frequency of their input. For example, if it determines that the user is feeling stressed, the emotion engine will respond accordingly.

[1616] Information provision

[1617] The server presents appropriate information to the user based on the analysis results and the emotion engine's analysis results. If the emotion engine determines that the user is feeling stressed, it simplifies the information presented and provides specific step-by-step guidance. For example, it may provide advice such as, "In similar past cases, restarting the device resolved the issue."

[1618] Obtaining additional information

[1619] If the user needs more information, they enter a follow-up question, and the server again searches the database and provides the appropriate answer.

[1620] Troubleshooting and database updates

[1621] The user attempts to resolve the problem according to the provided guidelines. If the problem is resolved, the user enters the results into the system and updates the database. For example, information such as "The power supply unit was replaced and the system returned to normal" is entered.

[1622] Specific examples

[1623] Case 1: If the user types "My robot arm won't move. Help me, I'm in trouble," the server will suggest "Emotional state: Stress. Case applies: Restart will solve it."

[1624] Prompt Sentence Examples

[1625] User input: "My robot arm won't move. Help, I'm in trouble."

[1626] Emotion engine detection result: Stress

[1627] Advice to offer: Rebooting solves the problem

[1628] This system allows users to quickly and appropriately respond to robot failures, and with the help of the emotion engine, it is also possible to reduce psychological stress.

[1629] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1630] Program processing steps

[1631] Step 1:

[1632] The user logs into the system using a terminal and inputs the robot's trouble status in chat format. This input includes specific problem information, such as "The robot arm won't move." The terminal then sends this input to the server.

[1633] Step 2:

[1634] The server analyzes the received fault information and extracts important keywords and phrases from the user's input. For example, keywords such as "robot arm" and "not working" are extracted. Based on the results of this analysis, the server prepares to search past data and specification data.

[1635] Step 3:

[1636] The server searches the database based on the keywords extracted through the analysis, collecting information related to past similar failure cases and technical specifications. For example, it can obtain relevant information such as "previous similar cases were resolved by restarting the system."

[1637] Step 4:

[1638] At the same time, the server uses an emotion engine to analyze the user's emotional state based on the content, speed, and frequency of input. For example, if the user types quickly and includes "I'm in trouble," the emotion engine will recognize that the user is in a stressful state.

[1639] Step 5:

[1640] The server presents relevant information to the user based on the search results and the emotion engine's analysis. If the emotion engine detects that the user is stressed, it simplifies the information presented and provides specific step-by-step guidance. For example, it may provide detailed instructions for rebooting the device.

[1641] Step 6:

[1642] If the user enters an additional question, the device sends it to the server, which again searches the database and generates an appropriate answer. For example, if the user asks, "How do I reboot?", the server provides detailed reboot instructions.

[1643] Step 7:

[1644] The user responds to the problem according to the information provided. If the problem is resolved, the result is reported to the system. For example, a result such as "After rebooting, the robot arm is now operating normally" is entered.

[1645] Step 8:

[1646] The server receives reports from users and updates the database with the results of the troubleshooting. The results are recorded as new troubleshooting results and are used for future troubleshooting.

[1647] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1648] 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.

[1649] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1650] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1651] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1652] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1653] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1654] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1655] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1656] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1657] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1658] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1659] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1660] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1661] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1662] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1663] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1664] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1665] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1666] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1667] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1668] The following is further disclosed regarding the above embodiment.

[1669] Drafting of claims

[1670] (Claim 1)

[1671] means for accepting input from a user;

[1672] means for analyzing the problem information input by the user;

[1673] a means for searching past data and radio equipment specification data based on the analyzed problem information;

[1674] means for presenting highly relevant information to a user based on the search results;

[1675] means for retrieving further data and providing appropriate answers based on the user's follow-up questions;

[1676] A means for updating the results of troubleshooting to a database;

[1677] A system including:

[1678] (Claim 2)

[1679] 2. The system of claim 1, further comprising: extracting keywords and phrases based on the analyzed problem information.

[1680] (Claim 3)

[1681] 2. The system according to claim 1, wherein the presentation to the user is made in a chat format.

[1682] "Example 1"

[1683] (Claim 1)

[1684] means for accepting input from a user;

[1685] means for authenticating the user;

[1686] means for analyzing the problem information input by the user;

[1687] a means for searching past data and specification data based on the analyzed problem information;

[1688] means for providing highly relevant information to a user based on the search results;

[1689] means for the user to input follow-up questions based on the provided information;

[1690] means for retrieving further data based on said further questions and providing appropriate answers;

[1691] A means for updating the results of troubleshooting to a database;

[1692] A system including:

[1693] (Claim 2)

[1694] 2. The system of claim 1, further comprising: extracting keywords and phrases based on the analyzed problem information.

[1695] (Claim 3)

[1696] 2. The system according to claim 1, wherein the information is provided to the user in a chat format.

[1697] That's all.

[1698] "Application Example 1"

[1699] (Claim 1)

[1700] means for accepting input from a user;

[1701] means for analyzing the problem information input by the user;

[1702] a means for searching past data and specification data based on the analyzed problem information;

[1703] means for presenting highly relevant information to a user based on the search results;

[1704] means for retrieving further data based on said user's follow-up questions and providing appropriate answers;

[1705] A means for updating the results of troubleshooting to a database;

[1706] A means to input the breakdown status of machinery in the factory in chat format and provide information on how to deal with the breakdown;

[1707] A system including:

[1708] (Claim 2)

[1709] 2. The system of claim 1, further comprising: extracting keywords and phrases based on the analyzed problem information.

[1710] (Claim 3)

[1711] 2. The system according to claim 1, wherein the presentation to the user is made in a chat format.

[1712] "Example 2: Combining Emotion Engines"

[1713] (Claim 1)

[1714] means for accepting input from a user;

[1715] means for analyzing the problem information input by the user;

[1716] a means for searching past data and wireless communication device specification data based on the analyzed problem information;

[1717] means for presenting highly relevant information to a user based on the search results;

[1718] means for recognizing an emotional state of the user based on the input content, input speed, and input frequency of the user, and providing adaptive information;

[1719] means for retrieving further data and providing appropriate answers based on the user's follow-up questions;

[1720] A means for updating the results of troubleshooting to a database;

[1721] A system including:

[1722] (Claim 2)

[1723] 2. The system of claim 1, further comprising: extracting keywords and phrases based on the analyzed problem information.

[1724] (Claim 3)

[1725] 2. The system according to claim 1, wherein the presentation to the user is made in a chat format.

[1726] "Application example 2 when combining emotion engines"

[1727] (Claim 1)

[1728] means for accepting input from a user;

[1729] means for analyzing the problem information input by the user;

[1730] a means for searching past data and specification data based on the analyzed problem information;

[1731] means for presenting highly relevant information to a user based on the search results;

[1732] means for retrieving further data and providing appropriate answers based on the user's follow-up questions;

[1733] A means for updating the results of troubleshooting to a database;

[1734] means for recognizing emotions based on the content, speed, and frequency of user input;

[1735] a means for adjusting information to be presented in response to the user's emotions;

[1736] A system including:

[1737] (Claim 2)

[1738] 2. The system of claim 1, further comprising: extracting keywords and phrases based on the analyzed problem information.

[1739] (Claim 3)

[1740] 2. The system according to claim 1, wherein the presentation to the user is made in a chat format. [Explanation of symbols]

[1741] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for accepting input from a user; means for analyzing the problem information input by the user; a means for searching past data and radio equipment specification data based on the analyzed problem information; means for presenting highly relevant information to a user based on the search results; means for retrieving further data and providing appropriate answers based on the user's follow-up questions; A means for updating the results of troubleshooting to a database; A system including:

2. The system of claim 1 , further comprising: extracting keywords and phrases based on the analyzed problem information.

3. The system according to claim 1, wherein the presentation to the user is made in a chat format.

Images