system

Abstract

Provide a system. A means for acquiring location information and time information input by a user; means for transmitting the location information and time information to a server; means for searching a database for a communication log corresponding to the location information and time information; means for analyzing the communication log and extracting defective data; a means for mapping the extracted data on a map and visually displaying it; A system including:

Description

[Technical Field]

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

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

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

[0004] In the operation of communication networks, it is difficult to accurately identify problems experienced by users. Conventional big data analysis alone makes it difficult to detect subtle communication problems experienced by users. In addition, there is a lack of methods to accurately determine when and where users specifically experience communication problems and to make area improvements based on that information. [Means for solving the problem]

[0005] According to the present invention, a system is provided that acquires specific location and time information based on a communication problem experienced by a user and transmits that information to a server. This system includes a means for searching for corresponding communication logs from a database based on the location and time information and analyzing them. Furthermore, the analysis results are mapped and visually displayed on a map, allowing the user to visually confirm the specific circumstances of the communication problem they experienced. This allows the operation of a communication network to accurately identify even subtle communication problems experienced by users and to be useful in improving coverage areas.

[0006] "Location information" is latitude and longitude data that indicates a specific location.

[0007] "Time information" is data indicating a specific point in time, including the year, month, day, hour, minute, and second.

[0008] A "server" is a computer system that centrally manages data and sends and receives data in response to requests from multiple terminals.

[0009] A database is a collection of data that is systematically organized and stored so that it can be quickly searched and retrieved when needed.

[0010] A "communication log" is recorded data such as connection status, communication speed, frequency, and delay in a communication network.

[0011] "Physical channel utilization rate" is an index that indicates the degree to which physical communication channels are utilized in a communication network.

[0012] "Frequency" is an indicator of the number of oscillations of radio waves used to transmit communication signals, and is expressed in units of Hz (Hertz).

[0013] "Communication speed" is an indicator of the amount of data transferred per unit time, and is usually expressed in bps (bits per second).

[0014] "Analysis" is the process of examining data in detail and extracting necessary information and trends.

[0015] "Mapping" is the operation of positioning acquired data on a map and visually displaying it.

[0016] "Visually displaying" means presenting data in a form that is easy for users to understand, such as in the form of charts, graphs, or maps. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The system of the present invention collects data based on communication problems experienced by users and visually displays the analysis results, thereby promoting area improvement in the operation of communication networks.

[0039] System Overview

[0040] The system of the present invention mainly comprises the following elements:

[0041] User terminal

[0042] server

[0043] Database

[0044] System components and roles

[0045] User terminal

[0046] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal has a location information service and an internal clock, and acquires current location information and time information.

[0047] server

[0048] The server receives location and time information sent from the user terminal, searches the database for the corresponding communication log, and analyzes the acquired communication log to extract any defective data and map it.

[0049] Database

[0050] The database is used to store communication logs, which include data such as physical channel utilization, frequency, and communication speed.

[0051] Program processing

[0052] User instruction input

[0053] When a user experiences a communication problem, they input a command to their device, such as "Show me the log of communication near XX station today." This command causes the device to collect current location information and time information.

[0054] Obtaining location and time information

[0055] The device uses location services to obtain the latitude and longitude of its current location, and it also uses the system's internal clock to record the exact time that you input your commands.

[0056] Sending information

[0057] The device then assembles the acquired location and time information into a data packet and transmits it to the server using a secure communication channel.

[0058] Searching from the database

[0059] The server searches the database based on the received location and time information and retrieves the corresponding communication log, which includes PCU (Physical Channel Utilization), frequency, communication speed, etc.

[0060] Data analysis

[0061] The server analyzes the acquired communication logs to identify data related to the malfunctions experienced by the user. It detects when the PCU exceeds a certain threshold or when communication speed drops, and extracts that data.

[0062] Visualizing the results

[0063] The server maps the analysis results onto a map and generates a visual display, which is sent to the user's device, including a color-coded map showing communication speeds and PCU status.

[0064] Displaying the results

[0065] The user's device displays the received map data and analysis results, allowing the user to visually check the specific communication situation.

[0066] Specific examples

[0067] For example, if a user feels that the communication speed is slow when passing near XX Station, they may input "Show me the communication log for today near XX Station" into their iPhone (registered trademark). In this case, the device obtains location information (e.g., latitude 35.6581, longitude 139.7414) and time information (e.g., October 5, 2023, 15:30) and sends them to the server.

[0068] The server searches the database, obtains and analyzes the communication log corresponding to this location and time (e.g., PCU 90%, frequency 2.4GHz, communication speed 1Mbps). The server generates map data based on the analysis results and provides it to the user so that they can visually check it. The user can understand the communication situation around XX station in detail and receive feedback for area improvements.

[0069] As described above, the system of the present invention supports efficient operation of communication networks and area improvement by collecting specific data based on communication problems experienced by users and visually displaying the analysis results.

[0070] The processing flow will be explained below.

[0071] Step 1: User input

[0072] The user inputs a command into the system on their iPhone, such as "Show me the log of communications near XX station today."

[0073] This instruction is recognized by a specific application or voice recognition system on the terminal.

[0074] Step 2: Obtaining location and time information

[0075] Your device uses location services (such as GPS or Wi-Fi location) to obtain its current latitude and longitude.

[0076] The device uses its internal clock to record the exact date and time when the instruction is entered.

[0077] Step 3: Sending location and time information to the server

[0078] The location information and time information acquired by the terminal are combined into a single data packet.

[0079] This data packet is sent to the server over a secure communication channel (e.g. HTTPS).

[0080] Step 4: Search communication logs from the database

[0081] The server analyzes the received location and time information and queries the database for information on the relevant area and time.

[0082] The server retrieves communication logs related to physical channel utilization, frequency, and communication speed from the database.

[0083] Step 5: Analyze the communication log

[0084] The communication log acquired by the server is analyzed to identify data related to the malfunction experienced by the user.

[0085] The server determines whether the PCU exceeds a certain threshold or whether the communication speed is slowing down.

[0086] Step 6: Visualize the results

[0087] The server creates map data based on the analysis results.

[0088] The server maps the data points from the communication log onto a map, color-coding the situation to create a visual representation.

[0089] Step 7: Sending the results to the device

[0090] The server sends the generated map data and analysis results to the terminal.

[0091] The submitted data is formatted as map images and interactive data.

[0092] Step 8: View the results

[0093] The terminal displays the received data to the user.

[0094] Users can view the map to check the specific communication status and the occurrence of any problems.

[0095] Specific examples

[0096] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[0097] The user enters the command "Show me the communication log for the area near XX station today" into their iPhone (Step 1).

[0098] The device obtains its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using GPS, and records the time (e.g., October 5, 2023, 15:30) using its internal clock (step 2).

[0099] This location and time information is sent to the server using HTTPS (step 3).

[0100] The server uses this information to retrieve the corresponding communication log from the database (physical channel utilization rate 90%, frequency 2.4 GHz, communication speed 1 Mbps) (Step 4).

[0101] The server analyzes this data and determines that the communication speed is slowing down due to a high PCU (step 5).

[0102] The server generates map data based on the acquired data and displays the problem areas in red, among other visual representations (step 6).

[0103] The analysis results and map data are sent to the terminal, which receives them (step 7).

[0104] The user checks the map on their iPhone and visually understands the communication situation around Station X (Step 8).

[0105] These detailed steps allow the user to accurately identify the communication problems they are experiencing, which can be used to improve the communication network.

[0106] Example 1

[0107] 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."

[0108] In modern communication networks, communication problems experienced by users frequently occur, but it is difficult to identify the specific causes and quickly fix them. In particular, there is a lack of methods to accurately grasp where and when users experience communication problems and provide corresponding data analysis and visual feedback.

[0109] 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.

[0110] In this invention, the server includes means for acquiring location information and time information input by a user, means for transmitting the location information and time information to the server via a secure communication channel, means for searching a database for a communication log corresponding to the location information and time information, means for analyzing the communication log to extract data including physical channel utilization rate, frequency, and communication speed, and means for mapping and visually displaying the extracted data on a map, thereby enabling the specific cause of a communication problem experienced by the user to be quickly identified and visual feedback to be provided.

[0111] "Location information" is data that indicates the user's current location, and is usually composed of latitude and longitude.

[0112] "Time information" is data indicating the time when the user inputs an instruction, and is recorded in the format of date and time.

[0113] A "secure communication channel" is a communication path that guarantees high security when sending and receiving data, and uses encryption protocols such as SSL / TLS.

[0114] A "server" refers to a computer system that processes various types of data over a network, and is a device that analyzes communication logs and performs data mapping.

[0115] A "database" is a storage system for effectively managing and searching large amounts of digital information, and is used to store information such as communication logs.

[0116] A "communication log" is data that records the usage status and performance of a communication network, and includes indicators such as physical channel utilization rate, frequency, and communication speed.

[0117] "Physical channel utilization" is a measure of the usage of physical channels in a communications network, usually expressed as a percentage.

[0118] "Frequency" is an indicator of the speed of periodic changes in signals used for communication, and is usually expressed in Hertz (Hz).

[0119] "Communication speed" is an indicator of the speed at which data can be sent and received over a communication line, and is usually expressed in bits per second (bps).

[0120] "Mapping on a map" refers to displaying acquired data in association with geographical locations, typically visually represented using a digital map.

[0121] The present invention is a system that collects and analyzes communication trouble information experienced by users and visually displays the results in order to improve the efficiency of communication network operation. This system is mainly composed of user terminals, a server, and a database, and is implemented in the following specific steps.

[0122] First, when a user experiences a communication problem, they use their own device (e.g., a smartphone) to give instructions by voice or text input. A specific input method could be, "Show me the communication log for today near XX station." The device receives this instruction, obtains the user's current location information using a GPS service, and collects accurate time information using its internal clock.

[0123] Next, the acquired location and time information is packaged into a data packet and sent to the server via a secure communication channel such as SSL / TLS. At this stage, the device encrypts the collected data to ensure the security of the communication. The server also searches a database for the corresponding communication log based on the received location and time information. The communication log contains data such as physical channel utilization (PCU), frequency, and communication speed.

[0124] The server analyzes the communication logs obtained from the database using analytical tools such as Python or R. For example, Python's NumPy or Pandas library can be used. During data analysis, the causes of malfunctions, such as PCUs exceeding a certain threshold or reduced communication speeds, are identified and extracted.

[0125] The analyzed data is converted into map data using a format such as GeoJSON. The server generates this map data and sends it back to the user's device. The user's device then visually displays the received map data using a map rendering library such as Google (registered trademark) Maps API or Leaflet.js. This allows the user to intuitively check the communication status at a specified location and time.

[0126] As a specific example, if a user types into their iPhone, "Show me today's communication log near Shibuya Station," the device will obtain the latitude (35.6581), longitude (139.7017), and time information for 15:30 on October 5, 2023, and send this information to the server. The server uses this information to search its database, obtains and analyzes log data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps. Map data is generated based on the analysis results and provided to the user's device. The user can visually check the communication status near Shibuya Station on their iPhone screen.

[0127] As described above, the system of the present invention improves the operational efficiency of a communication network by collecting data based on communication problems that users specifically experience and intuitively visualizing the analysis results.

[0128] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0129] Step 1:

[0130] When a user experiences a communication problem, they can give instructions to their smartphone or other device by voice or text input, such as "Show me the communication log for today near XX station." The input location and time information is then acquired.

[0131] Input: User voice or text input

[0132] Output: Location information (latitude, longitude) and time information (year, month, day, hour)

[0133] Specific behavior:

[0134] The user launches the app on their iPhone and says, "Show me the log of communications near Shibuya Station today."

[0135] The device obtains the user's current location using the GPS service as latitude 35.6581 and longitude 139.7017, and records the time information of 15:30 on October 5, 2023 using the internal clock.

[0136] Step 2:

[0137] The location and time information acquired by the terminal is compiled into a data packet and sent to the server using a secure communication channel (SSL / TLS).

[0138] Input: Location information (latitude, longitude) and time information (year, month, day, hour)

[0139] Output: Data packets over a secure communication channel

[0140] Specific behavior:

[0141] The terminal packages the location and time information into a data packet.

[0142] Using the SSL / TLS protocol, data packets are sent to a server such as Amazon Web Services or Microsoft® Azure®.

[0143] Step 3:

[0144] Based on the location information and time information received by the server, the corresponding communication log is searched for in the database.

[0145] Input: Location information (latitude, longitude) and time information (year, month, day, hour)

[0146] Output: Corresponding communication log (physical channel utilization, frequency, communication speed)

[0147] Specific behavior:

[0148] The server generates a database query and searches the database based on the location information (latitude 35.6581, longitude 139.7017) and time information (October 5, 2023, 15:30).

[0149] Obtain the corresponding communication log (e.g., PCU is 90%, frequency is 2.4GHz, communication speed is 1Mbps).

[0150] Step 4:

[0151] The communication log acquired by the server is analyzed and data such as physical channel utilization rate (PCU), frequency, and communication speed is extracted.

[0152] Input: Communication log data

[0153] Output: Analyzed failure data (physical channel utilization, reduced communication speed, etc.)

[0154] Specific behavior:

[0155] The server loads the communication logs using Python's NumPy and Pandas libraries.

[0156] Analyze and identify data on PCUs that exceed a certain threshold or have reduced communication speeds.

[0157] Step 5:

[0158] Based on the analysis results, the server generates map data in GeoJSON format and creates data for visual display.

[0159] Input: Analyzed failure data (physical channel utilization, reduced communication speed, etc.)

[0160] Output: Map data in GeoJSON format

[0161] Specific behavior:

[0162] The server generates map data in GeoJSON format, coloring areas with slow communication speeds in red and areas with fast speeds in green.

[0163] The generated GeoJSON data is sent to the user's device.

[0164] Step 6:

[0165] The GeoJSON data received by the user device is used to display the analysis results using map drawing libraries such as Google Maps API and Leaflet.js.

[0166] Input: Map data in GeoJSON format

[0167] Output: A visual map representation on the user interface

[0168] Specific behavior:

[0169] The user device uses the Google Maps API to draw the received GeoJSON data on a map.

[0170] Users can check the map displayed on the app and intuitively understand the communication situation near Station X.

[0171] The above are the specific processing steps of this system.

[0172] (Application example 1)

[0173] 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."

[0174] Stable communications are essential for the efficient and safe operation of robots in factories. However, if a communications failure occurs in a specific area of ​​the factory, it can affect the operation of the robots and reduce production efficiency. Conventional systems lack the means to quickly identify the cause of a failure and take appropriate action when it occurs. For this reason, there is a need to develop a system that can detect communications failures in real time and visually display the analysis results, enabling a rapid response.

[0175] 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.

[0176] In this invention, the server includes means for acquiring location information and time information input by a user, means for transmitting the location information and time information to the server, means for searching a database for a communication log corresponding to the location information and time information, means for analyzing the communication log and extracting defective data, means for mapping the extracted data on a map and visually displaying it, and means for a robot in a factory to automatically detect a communication failure and analyze and visualize the communication status in real time. This makes it possible to quickly identify a communication failure occurring in a specific area in a factory, analyze its cause, and visually grasp its cause.

[0177] "Location information" is the latitude and longitude data required to indicate a specific location.

[0178] "Time information" is data that indicates a specific time, and includes the date, hour, minute, and second.

[0179] A "database" is a system for storing and managing large amounts of data in an organized manner.

[0180] A "communication log" is recorded data generated during the communication process, and includes information such as physical channel utilization rate, frequency, and communication speed.

[0181] A "robot" is a machine that performs specific tasks automatically or under the control of a program.

[0182] "Communication failure" refers to a state in which communication is not carried out normally, including failure of data transmission or slowdown in speed.

[0183] "Analysis" is the process of examining and understanding the data obtained and extracting specific information.

[0184] "Visualization" refers to the visual presentation of data or information in an easy-to-understand manner.

[0185] This invention is a system that automatically detects communication problems in robots operated in factories and analyzes and visualizes the communication status in real time. This system acquires location and time information when a user experiences a communication problem, sends it to a server, searches and analyzes the corresponding communication log from a database, extracts the data containing the problem, and visually displays it on a map.

[0186] System configuration

[0187] Hardware and software used

[0188] The system hardware consists of the robots operated in the factory, the sensors installed on the robots, the GPS module, and the internal clock.The software consists of the robot control system, a dedicated server, a database (e.g., MySQL (registered trademark)), an analysis tool (e.g., Python's Pandas, NumPy), and a map display tool (e.g., Leaflet.js).

[0189] Processing flow

[0190] 1. Detecting communication problems

[0191] The robot utilizes internal sensors and a GPS module to obtain location information (latitude and longitude) and time information, which is automatically recorded when the robot detects a communication failure.

[0192] 2. Transmission of information

[0193] The robot assembles the acquired position and time information into a data packet and sends it to a dedicated server using a secure communication channel.

[0194] 3. Searching from the database

[0195] The server searches the database based on the received location and time information and obtains the corresponding communication log (physical channel utilization rate, frequency, communication speed, etc.).

[0196] 4. Data Analysis

[0197] The server analyzes the communication log using an analysis tool (e.g., Python's Pandas or NumPy) and identifies data related to the malfunction.

[0198] 5. Visualizing the results

[0199] The server uses a map display tool (e.g., Leaflet.js) to map the areas where the analysis results are occurring on a map of the factory, generating data that can be displayed visually.

[0200] 6. Displaying the results

[0201] Data is sent to the robot's control system and the results are displayed in real time via a tablet or head-mounted display, allowing factory managers to visually check the specific communication status.

[0202] Specific examples

[0203] For example, if a robot detects a communication problem (a drop in communication speed) in a specific area (latitude 35.6581, longitude 139.7414), the robot will send this information to the server along with the time information recorded by its internal clock (e.g., October 5, 2023, 15:30).

[0204] The server searches the database, obtains and analyzes the communication log corresponding to this location and time (e.g., physical channel utilization rate 90%, frequency 2.4GHz, communication speed 1Mbps).The server generates map data based on the analysis results and sends it to the robot's control system so that it can be displayed visually.

[0205] The robot's control system displays the analysis results in real time to factory managers via a tablet or head-mounted display, allowing them to grasp the specific communication situation in a specific area and take prompt action.

[0206] Prompt Sentence Examples

[0207] "Get a detailed log of communication issues in a specific area of ​​the factory (latitude 35.6581, longitude 139.7414) and visualize it on a map."

[0208] As described above, the system of the present invention allows robots in factories to automatically detect and analyze communication problems and visually display them, enabling quick and efficient responses.

[0209] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0210] Step 1:

[0211] Detection of communication problems

[0212] The robot uses its internal sensors and GPS module to obtain the latitude and longitude of its current location. It also uses its internal clock to record the current time. This location and time information is used as input. The robot automatically detects communication problems, such as slow communication speeds in a specific area, and uses this information as a trigger to start processing.

[0213] Step 2:

[0214] Sending information

[0215] The robot assembles the input location and time information into a data packet and sends it to the server using a secure communication channel. The transmitted data includes location information, time information, and communication status. The server receives this data and proceeds to the next step.

[0216] Step 3:

[0217] Searching from the database

[0218] The server searches the database based on the received location and time information. Specifically, it retrieves the communication log—data including physical channel utilization, frequency, and communication speed—corresponding to the received latitude, longitude, and time. This communication log data becomes the input for the next analysis process.

[0219] Step 4:

[0220] Data analysis

[0221] The server uses data analysis tools (e.g., Python's Pandas or NumPy) to analyze the communication logs retrieved from the database. The purpose of the analysis is to identify the cause of the problem, such as detecting physical channel utilization rates exceeding a certain threshold or reduced communication speeds. The analysis results in data containing the problem areas and their detailed information, which serves as input for the next process.

[0222] Step 5:

[0223] Visualizing the results

[0224] The server uses a map display tool (e.g., Leaflet.js) to map the analysis results on a map of the factory. Specifically, it identifies areas with defects based on the analysis results and generates map data that visually indicates those areas using color coding and markers. This map data becomes the input for the next process.

[0225] Step 6:

[0226] Displaying the results

[0227] The robot's control system receives map data and analysis results sent from the server and displays them in real time on a tablet or head-mounted display, allowing factory managers to visually confirm the location and details of communication problems and respond quickly.

[0228] Through the above processing steps, robots operating in factories automatically detect and analyze communication problems and visually display the results, enabling efficient factory operations and rapid problem resolution.

[0229] 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.

[0230] The system of the present invention not only recognizes communication problems experienced by users, but also has the ability to acquire user emotional information and analyze the status of the communication network based on that information, making it possible to identify more detailed communication conditions that are closer to the user's actual experience and improve the area.

[0231] System Overview

[0232] The system of the present invention comprises the following elements:

[0233] User terminal

[0234] server

[0235] Database

[0236] Emotion Engine

[0237] System components and roles

[0238] User terminal

[0239] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal is equipped with a location information service and an internal clock, which acquires current location and time information. It also has an emotion engine that recognizes the user's emotions and acquires emotional information.

[0240] server

[0241] The server receives location, time, and emotion information sent from the user terminal, searches for the corresponding communication log in the database, and analyzes the acquired communication log to extract any defective data and map it on a map.

[0242] Database

[0243] The database stores communication logs, which include data such as physical channel utilization, frequency, and communication speed.

[0244] Emotion Engine

[0245] The emotion engine analyzes emotions from the user's voice, facial expressions, text input, etc., and acquires specific emotional information.

[0246] Program processing

[0247] User instruction input

[0248] When a user experiences a communication problem, they input a command into their device, such as "Show me the log of communication near station X today." This command causes the device to collect current location and time information, and the emotion engine analyzes the user's emotions.

[0249] Acquiring location, time, and emotion information

[0250] The device uses location services to obtain the current latitude and longitude of the device, and uses the system's internal clock to record the exact time when the command was input. The emotion engine obtains emotional information from the user's voice and facial expressions.

[0251] Sending information

[0252] The location information, time information, and emotion information acquired by the terminal are packaged into a data packet and transmitted to a server using a secure communication channel.

[0253] Searching from the database

[0254] The server queries the database based on the received location information, time information, and emotion information, and searches for corresponding communication logs with priority based on emotion information in particular.

[0255] Data analysis

[0256] The server analyzes the communication logs it acquires and identifies data related to the problems experienced by the user. It detects when the PCU exceeds a certain threshold or when communication speed drops, and extracts that data.

[0257] Visualizing the results

[0258] The server creates map data based on the analysis results, maps the data points in the communication log onto a map, and visually represents the situation using color coding.

[0259] Sending the results to the device

[0260] The server sends the generated map data and analysis results to the device, where they are formatted as map images and interactive data.

[0261] Displaying the results

[0262] The device displays the received data to the user, who can then view the map to check the specific communication status and the occurrence of any problems.

[0263] Specific examples

[0264] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[0265] The user enters a command into their iPhone, such as "Show me the communication log for today near XX station."

[0266] The device obtains its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using GPS, and records the time (e.g., October 5, 2023, 15:30) using its internal clock.

[0267] The emotion engine acquires emotional information such as dissatisfaction and irritation from the user's voice and facial expressions.

[0268] This information is sent to the server using HTTPS.

[0269] The server uses this information to retrieve the corresponding communication log from the database. For example, it searches for data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[0270] The server analyzes this data, determines that the communication speed is slowing due to a high PCU, and generates an analysis result along with emotional information.

[0271] Based on the data acquired by the server and the analysis results, map data is generated and a visual representation is created, such as showing faulty points in red.

[0272] The analysis results and map data are sent to the terminal, which receives them.

[0273] Users can check the map on their iPhone and actively understand the communication situation around Station X.

[0274] As described above, the system of the present invention collects and analyzes specific data based on user sensory and emotional information, and visually displays the results, thereby supporting efficient operation of communication networks and area improvement.

[0275] The processing flow will be explained below.

[0276] Step 1: User input

[0277] The user inputs a command into the system on their iPhone, such as "Show me the log of communications near XX station today."

[0278] The user's voice and text inputs are analyzed by the emotion engine.

[0279] Step 2: Obtaining location and time information

[0280] Your device uses location services (such as GPS or Wi-Fi location) to obtain its current latitude and longitude.

[0281] The device uses its internal clock to record the exact date and time when the instruction is entered.

[0282] Step 3: Acquiring emotional information

[0283] The emotion engine installed in the device analyzes and acquires emotional information from the user's voice and facial expressions.

[0284] The emotion engine detects feelings of dissatisfaction or irritation from the user's tone of voice, facial expression recognition, text analysis, etc.

[0285] Step 4: Send location, time, and emotion information to the server

[0286] The location information, time information, and emotion information acquired by the terminal are combined into one data packet.

[0287] This data packet is sent to the server over a secure communication channel (e.g. HTTPS).

[0288] Step 5: Search communication logs from the database

[0289] The server analyzes the received location information, time information, and emotion information, and queries a database for information about the relevant area and time.

[0290] The server retrieves communication logs related to physical channel utilization, frequency, and communication speed from the database.

[0291] Step 6: Analyze the communication log

[0292] The communication log acquired by the server is analyzed to identify data related to the malfunction experienced by the user.

[0293] The server determines whether the PCU exceeds a certain threshold or whether the communication speed is slowing down.

[0294] Priority is set for the analysis results based on emotional information.

[0295] Step 7: Visualize the results

[0296] The server creates map data based on the analysis results.

[0297] The server maps the data points from the communication log onto a map, color-coding the situation to create a visual representation.

[0298] To highlight the severity of a defect based on emotional information.

[0299] Step 8: Sending the results to the device

[0300] The server sends the generated map data and analysis results to the terminal.

[0301] The submitted data is formatted as map images and interactive data.

[0302] Step 9: View the results

[0303] The terminal displays the received data to the user.

[0304] Users can view the map to check the specific communication status and the occurrence of any problems.

[0305] Specific examples

[0306] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[0307] Step 1: The user types into the iPhone, "Show me the log of communications near XX station today." The user's voice sounds irritated.

[0308] Step 2: The device uses GPS to obtain its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) and record the time (e.g., October 5, 2023, 15:30).

[0309] Step 3: The emotion engine obtains the emotion information of irritation from the user's voice tone and facial expression.

[0310] Step 4: This information is sent to the server using HTTPS.

[0311] Step 5: The server uses this information to retrieve the corresponding communication log from the database. For example, it searches for data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[0312] Step 6: The server analyzes this data, determines that the communication speed is slowing down due to a high PCU, and sets a high priority to the analysis results, taking into account emotional information.

[0313] Step 7: Based on the data acquired by the server and the analysis results, map data is generated and a visual representation is created, such as displaying faulty points in red.

[0314] Step 8: The analysis results and map data are sent to the terminal, which receives them.

[0315] Step 9: The user checks the map on their iPhone and actively understands the communication situation around Station XX.

[0316] These detailed steps allow users to accurately identify the communication problems they experience and use the information to improve the communication network. In addition, incorporating emotional information makes it possible to identify high-priority problems based on user experience.

[0317] Example 2

[0318] 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."

[0319] Conventional communication failure analysis systems have difficulty accurately grasping the detailed circumstances of communication failures experienced by users. In particular, because they do not take into account the user's emotional information, they are unable to properly reflect the degree of failure or urgency experienced by the user, making it difficult to efficiently operate communication networks and improve coverage areas. This makes it difficult to provide a communication environment that satisfies users.

[0320] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0321] In this invention, the server includes means for acquiring location information and time information input by the user, means for acquiring user emotion information based on the location information and time information, means for transmitting the location information, time information, and emotion information to the server, means for searching a corresponding communication log from a database based on the location information, time information, and emotion information, means for analyzing the communication log and extracting defective data, and means for mapping the extracted data on a map and visually displaying it. This enables more detailed identification of communication defects based on the user's bodily sensations and emotion information, and efficient operation and area improvement of the communication network.

[0322] "Location information" refers to the current latitude and longitude of the user terminal.

[0323] "Time information" records the exact date and time when the user inputs the instruction.

[0324] "Emotion information" refers to specific emotional data analyzed from the user's voice, facial expressions, text input, etc.

[0325] The term "server" refers to a computer system that receives location information, time information, and emotion information sent from a user terminal, searches a database based on this information, and analyzes communication logs.

[0326] A "communication log" is a record of the history of data exchange in a communication network, and includes information such as physical channel utilization rate, frequency, and communication speed.

[0327] "Database" refers to an information management system for storing communication logs.

[0328] "Extraction" refers to the process of extracting defect data that meets specific conditions from the analyzed communication log.

[0329] A "map" provides geographic information for visually displaying analyzed data.

[0330] "Mapping" refers to the process of locating and displaying acquired data on a map.

[0331] "Visual display" refers to a method of expressing data on a screen using color, shape, position, etc. so that the user can intuitively understand it.

[0332] The system of the present invention has the function of recognizing communication problems experienced by users, acquiring user emotional information, and analyzing the status of the communication network based on that information. This system makes it possible to identify detailed communication conditions and improve coverage areas based on the user's experience.

[0333] System components and roles

[0334] User terminal

[0335] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal is equipped with a location information service (GPS) and an internal clock, which acquires current location and time information. It also has an emotion engine that analyzes the user's emotions and acquires emotional information.

[0336] server

[0337] The server receives location, time, and emotion information sent from the user's device and searches the database for corresponding communication logs. The server also analyzes the acquired communication logs, extracts defective data, and maps it on a map. The server processes the data using Python and SQL.

[0338] Database

[0339] The database stores communication logs and includes data such as physical channel utilization, frequency, and communication speed.

[0340] Emotion Engine

[0341] The emotion engine analyzes emotions from the user's voice, facial expressions, text input, etc., and obtains specific emotional information. The emotion engine uses a cloud-based emotion analysis API.

[0342] Specific processing flow of the program

[0343] 1. User input:

[0344] When a user experiences a communication problem, they can input a command by voice, such as "Show me the communication log for today near station XX." The device then converts this voice command into text using the Google Speech-to-Text API.

[0345] 2. Obtaining location, time, and emotion information:

[0346] The device uses a GPS sensor to obtain its current latitude and longitude, and an internal clock to record the time when commands are input. The emotion engine uses a camera and microphone to analyze the user's voice and facial expressions to obtain emotional information such as "dissatisfaction" or "irritation."

[0347] 3. Transmission of Information:

[0348] The device sends the acquired location information (e.g., latitude 35.6581, longitude 139.7414), time information (e.g., October 5, 2023, 15:30), and emotion information to the server using HTTPS.

[0349] 4. Searching from the database:

[0350] The server searches the database based on the received information and retrieves the corresponding communication log. The server generates an SQL query to search the database for the required communication log (e.g., PCU is 90%, frequency is 2.4 GHz, communication speed is 1 Mbps).

[0351] 5. Data Analysis:

[0352] The server uses the Python pandas library to analyze the communication log and identify the cause of the problem. For example, if the PCU utilization rate exceeds a threshold (e.g., 85%), it can determine that the communication speed is decreasing.

[0353] 6. Visualizing the results:

[0354] The server uses the Google Maps API to map the analyzed data, creating a visual representation such as showing faulty areas in red.

[0355] 7. Sending the results to the device:

[0356] The server sends the generated map data and analysis results in JSON format to the terminal via HTTPS.

[0357] 8. Displaying the results:

[0358] The device uses React Native to visually display a map and analysis results to the user, who can then manipulate the map to check detailed communication status.

[0359] Specific examples

[0360] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[0361] The user voice-inputs instructions into the iPhone, such as "Show me the log of communications near XX station today."

[0362] The device uses the Google Speech-to-Text API to convert voice commands into text, which is then parsed by an internal engine.

[0363] The device obtains the current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using the GPS sensor, and records the time (e.g., October 5, 2023, 15:30) using its internal clock.

[0364] The device uses a camera and microphone to allow the emotion engine to acquire emotional information such as dissatisfaction and irritation.

[0365] This information is sent to the server using HTTPS.

[0366] Based on the information, the server retrieves the corresponding communication log from the database using an SQL query.

[0367] The server uses Python and the pandas library to analyze data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[0368] Map data is generated using the Google Maps API, and faulty areas are visually displayed in red.

[0369] The analysis results and map data are sent to the device in JSON format via HTTPS.

[0370] The device uses React Native to visually display maps and analysis results, allowing users to understand detailed communication conditions.

[0371] Prompt Sentence Examples

[0372] "If a user experiences a communication problem near XX station, please provide detailed information about the problem. Analyze the communication log based on the user's current location, time, and emotional state, and display the results on a map."

[0373] As described above, the system of the present invention collects and analyzes specific data based on user sensory and emotional information, and visually displays the results, thereby supporting efficient operation of communication networks and area improvement.

[0374] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0375] Step 1:

[0376] When a user experiences a communication problem, they can input a voice command into the device, such as "Show me the communication log for today near station XX." This command is converted into text data using the Google Speech-to-Text API. Specifically, the device captures the voice using the microphone, sends the captured voice to a cloud-based speech recognition service, and receives it as text data. The output is the user's command in text format.

[0377] Step 2:

[0378] The device uses the GPS sensor to obtain the current latitude and longitude (e.g., latitude 35.6581, longitude 139.7414). At the same time, it uses its internal clock to record the exact time the command was entered (e.g., October 5, 2023, 15:30). This data is obtained using the location service and system clock APIs. The output is location information and time information.

[0379] Step 3:

[0380] The emotion engine uses a camera and microphone to analyze the user's voice and facial expressions to obtain emotional information. Specifically, the device's camera captures the user's facial expressions and simultaneously records their voice. This data is sent to the analysis engine, which identifies emotions such as "dissatisfaction" or "irritation." The output is emotional information.

[0381] Step 4:

[0382] The location, time, and emotion information acquired by the device is sent to the server via a secure communication channel using HTTPS. This operation includes encoding the data into JSON format and sending it using the HTTPS protocol. The output is the data sent to the server.

[0383] Step 5:

[0384] The server searches the database based on the location, time, and emotion information it receives. The server generates an SQL query based on this input data and queries the database. Specifically, it creates a query using the server's SQL library, establishes a database connection, and retrieves the communication log. The output is the searched communication log.

[0385] Step 6:

[0386] The communication log acquired by the server is analyzed. Specifically, the communication log is converted into a data frame using the Python pandas library, and each column (channel utilization rate, communication speed, etc.) is analyzed. For example, if the PCU utilization rate exceeds a threshold (e.g., 85%), it is detected that the communication speed is decreasing. The output is the analyzed data.

[0387] Step 7:

[0388] The server generates map data based on the analysis results. Using the Google Maps API, the analyzed data points are mapped on a map, and any defects are visually displayed in red, etc. Specifically, the data points are added to a map object, and the display method is set based on their properties. The output is map data.

[0389] Step 8:

[0390] The server generates map data and sends the analysis results in JSON format to the device via HTTPS. Specifically, the server serializes the data in JSON format, encodes it using the HTTPS protocol, and sends it. The output is the map data and analysis results sent to the device.

[0391] Step 9:

[0392] The map data and analysis results received by the device are visually displayed. React Native is used to provide an interactive map display for the user. Specifically, the map is drawn on the device display, allowing the user to perform operations such as tapping and zooming in / out. The output is the visual map data and analysis results that are displayed to the user.

[0393] (Application example 2)

[0394] 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."

[0395] In modern communication networks, there is a need to identify communication problems experienced by users in more detail and in real time, and to take prompt measures. However, conventional systems do not analyze communication conditions taking into account user emotional information, making it difficult to identify specific problems based on user experience. Furthermore, communication stability is extremely important for autonomous vehicles, and measures must take into account the impact of communication problems on the emotions of drivers and passengers.

[0396] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0397] In this invention, the server includes means for acquiring location information, time information, and emotion information input by the user, means for transmitting this information to the server, means for searching a database for a communication log corresponding to this information, means for analyzing the communication log and extracting defective data, and means for mapping the extracted data on a map and visually displaying it. This makes it possible to identify more detailed communication conditions based on the user's emotion information and to respond quickly to defects.

[0398] "Location information" is data indicating the latitude and longitude of the location where the user terminal is currently located.

[0399] "Time information" is data indicating the specific date and time when the user experienced a communication problem.

[0400] "Emotion information" is data indicating the emotional state obtained by analyzing the user's voice, facial expression, text input, and the like.

[0401] A "server" is a computer system that has the function of receiving location information, time information, and emotion information sent from a user terminal, and searching and analyzing the corresponding communication log from a database.

[0402] A "database" is an information system that stores communication logs such as physical channel utilization rates, frequencies, and communication speeds.

[0403] A "communication log" is data that records various parameters (e.g., physical channel utilization rate, frequency, communication speed) in a communication network.

[0404] An "emotion engine" is an algorithm or software that analyzes a user's voice and facial expressions to obtain emotional information.

[0405] "Mapping" is the process of arranging acquired data based on location coordinates in order to display it on a map.

[0406] The system for implementing this invention comprises a user terminal, a server, a database, and an emotion engine. Each component of this system and their interactions will be described in detail below.

[0407] User terminal

[0408] The user terminal is a device installed in an autonomous vehicle and has the following functions to detect communication problems in real time:

[0409] GPS module: Used to obtain the latitude and longitude of the current location.

[0410] Internal clock: Used to record time information.

[0411] Camera and microphone: Used by the emotion engine to analyze the user's voice and facial expressions.

[0412] Communication module: Used to send collected data to the server.

[0413] server

[0414] The server receives location, time, and emotion information sent from the user's device, and searches and analyzes the corresponding communication logs from the database. The main functions of the server are as follows:

[0415] Database search: Search the database based on the received data to obtain related communication logs.

[0416] Data analysis: Analyze the acquired communication logs and extract any defective data.

[0417] Visualization: The extracted data is mapped on a map to generate map data for visual display.

[0418] Transmission: The generated visualization data is sent to the user's terminal.

[0419] Database

[0420] The database stores communication logs, which contain the following parameters:

[0421] Physical channel utilization

[0422] frequency

[0423] communication speed

[0424] Emotion Engine

[0425] The emotion engine is used to analyze the user's voice and facial expressions to obtain emotional information. Specifically, the following technologies are used:

[0426] Speech analysis: Google Cloud Speech-to-Text API

[0427] Facial Expression Analysis: Microsoft Azure Face API

[0428] Specific examples

[0429] Consider a situation where an autonomous vehicle is traveling through a busy downtown area and the connection speed slows down. If the passenger's emotion engine determines they are "unhappy," the application will execute the following steps:

[0430] The user device sends the GPS location (e.g., 35.6895, 139.6917) and the emotion "dissatisfied" to the server.

[0431] The server searches the database based on this information and retrieves the relevant communication logs.

[0432] Identify the cause of the slowdown in communication speed and generate visualization data.

[0433] The driver can check the visualization of the communication status on the in-vehicle display in real time and consider changing the route if necessary.

[0434] Prompt Sentence Examples

[0435] "Check the current communication status and passenger emotional state to generate analytical data to identify communication glitches."

[0436] "Extract emotional information from data from onboard cameras and microphones, and visualize it by cross-analyzing the current location and communication logs of the autonomous vehicle."

[0437] By using the system of the present invention, it is possible to identify communication problems and their impact in autonomous vehicles in real time, and to efficiently operate communication networks and quickly improve areas based on user experience and emotional information.

[0438] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0439] Step 1:

[0440] The device detects communication problems in real time. The device uses an on-board camera and microphone to input the user's voice and facial expressions into the emotion engine. The emotion engine generates the user's emotional information from this data, and obtains location and time information from the GPS module and internal clock. This information is integrated within the device. The input data is voice data, facial expression data, GPS location, and time information, and the output data is an integrated data packet.

[0441] Step 2:

[0442] The device sends the integrated data packet to the server using a secure communication channel. The data packet contains location information, time information, and emotion information. Specifically, the data is encrypted and transmitted using HTTPS. The input data is the integrated data packet, and the output data is the data that arrives at the server.

[0443] Step 3:

[0444] The server analyzes the received data packets and accesses the database to search for the corresponding communication logs. The server retrieves relevant entries from past communication logs based on location, time, and emotion information. The input data are location, time, and emotion information, and the output data is the identified communication log.

[0445] Step 4:

[0446] The server analyzes the communication logs it acquires and extracts defective data. Specifically, it evaluates parameters such as physical channel utilization, frequency, and communication speed, and detects slow communication speeds and high load conditions. Based on this data, the server identifies the cause of communication problems. The input data is the communication log, and the output data is the defective data.

[0447] Step 5:

[0448] The server maps the defect data onto map data and prepares it for visual display. The server colors the defect locations on the map and arranges the data in a format that is easy for users to understand visually. Specifically, it generates the map data using a geographic information system (GIS). The input data is the defect data, and the output data is map data that can be displayed visually.

[0449] Step 6:

[0450] The server sends the generated map data to the terminal. The terminal receives this data and displays it on the in-vehicle display. This allows the user to check the current communication status and any malfunctions in real time. The input data is the map data, and the output data is the visual data displayed on the terminal.

[0451] Step 7:

[0452] The user checks the information displayed on the in-vehicle display and considers route changes or other measures as necessary. The device receives the user's instructions and reflects them in the driving system. Specifically, it operates the navigation system to calculate a new route. The input data are visual data and the user's instructions, and the output data is the driving system's new route information.

[0453] 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.

[0454] 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.

[0455] 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.

[0456] [Second embodiment]

[0457] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0458] 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.

[0459] 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).

[0460] 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.

[0461] 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.

[0462] 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).

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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.

[0468] 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."

[0469] The system of the present invention collects data based on communication problems experienced by users and visually displays the analysis results, thereby promoting area improvement in the operation of communication networks.

[0470] System Overview

[0471] The system of the present invention mainly comprises the following elements:

[0472] User terminal

[0473] server

[0474] Database

[0475] System components and roles

[0476] User terminal

[0477] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal has a location information service and an internal clock, and acquires current location information and time information.

[0478] server

[0479] The server receives location and time information sent from the user terminal, searches the database for the corresponding communication log, and analyzes the acquired communication log to extract any defective data and map it.

[0480] Database

[0481] The database is used to store communication logs, which include data such as physical channel utilization, frequency, and communication speed.

[0482] Program processing

[0483] User instruction input

[0484] When a user experiences a communication problem, they input a command to their device, such as "Show me the log of communication near XX station today." This command causes the device to collect current location information and time information.

[0485] Obtaining location and time information

[0486] The device uses location services to obtain the latitude and longitude of its current location, and it also uses the system's internal clock to record the exact time that you input your commands.

[0487] Sending information

[0488] The device then assembles the acquired location and time information into a data packet and transmits it to the server using a secure communication channel.

[0489] Searching from the database

[0490] The server searches the database based on the received location and time information and retrieves the corresponding communication log, which includes PCU (Physical Channel Utilization), frequency, communication speed, etc.

[0491] Data analysis

[0492] The server analyzes the acquired communication logs to identify data related to the malfunctions experienced by the user. It detects when the PCU exceeds a certain threshold or when communication speed drops, and extracts that data.

[0493] Visualizing the results

[0494] The server maps the analysis results onto a map and generates a visual display, which is sent to the user's device, including a color-coded map showing communication speeds and PCU status.

[0495] Displaying the results

[0496] The user's device displays the received map data and analysis results, allowing the user to visually check the specific communication situation.

[0497] Specific examples

[0498] For example, if a user feels that the communication speed is slow when passing near XX station, they may type into their iPhone, "Show me the communication log for today near XX station." In this case, the device obtains location information (e.g., latitude 35.6581, longitude 139.7414) and time information (e.g., October 5, 2023, 15:30) and sends it to the server.

[0499] The server searches the database, obtains and analyzes the communication log corresponding to this location and time (e.g., PCU 90%, frequency 2.4GHz, communication speed 1Mbps). The server generates map data based on the analysis results and provides it to the user so that they can visually check it. The user can understand the communication situation around XX station in detail and receive feedback for area improvements.

[0500] As described above, the system of the present invention supports efficient operation of communication networks and area improvement by collecting specific data based on communication problems experienced by users and visually displaying the analysis results.

[0501] The processing flow will be explained below.

[0502] Step 1: User input

[0503] The user inputs a command into the system on their iPhone, such as "Show me the log of communications near XX station today."

[0504] This instruction is recognized by a specific application or voice recognition system on the terminal.

[0505] Step 2: Obtaining location and time information

[0506] Your device uses location services (such as GPS or Wi-Fi location) to obtain its current latitude and longitude.

[0507] The device uses its internal clock to record the exact date and time when the instruction is entered.

[0508] Step 3: Sending location and time information to the server

[0509] The location information and time information acquired by the terminal are combined into a single data packet.

[0510] This data packet is sent to the server over a secure communication channel (e.g. HTTPS).

[0511] Step 4: Search communication logs from the database

[0512] The server analyzes the received location and time information and queries the database for information on the relevant area and time.

[0513] The server retrieves communication logs related to physical channel utilization, frequency, and communication speed from the database.

[0514] Step 5: Analyze the communication log

[0515] The communication log acquired by the server is analyzed to identify data related to the malfunction experienced by the user.

[0516] The server determines whether the PCU exceeds a certain threshold or whether the communication speed is slowing down.

[0517] Step 6: Visualize the results

[0518] The server creates map data based on the analysis results.

[0519] The server maps the data points from the communication log onto a map, color-coding the situation to create a visual representation.

[0520] Step 7: Sending the results to the device

[0521] The server sends the generated map data and analysis results to the terminal.

[0522] The submitted data is formatted as map images and interactive data.

[0523] Step 8: View the results

[0524] The terminal displays the received data to the user.

[0525] Users can view the map to check the specific communication status and the occurrence of any problems.

[0526] Specific examples

[0527] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[0528] The user enters the command "Show me the communication log for the area near XX station today" into their iPhone (Step 1).

[0529] The device obtains its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using GPS, and records the time (e.g., October 5, 2023, 15:30) using its internal clock (step 2).

[0530] This location and time information is sent to the server using HTTPS (step 3).

[0531] The server uses this information to retrieve the corresponding communication log from the database (physical channel utilization rate 90%, frequency 2.4 GHz, communication speed 1 Mbps) (Step 4).

[0532] The server analyzes this data and determines that the communication speed is slowing down due to a high PCU (step 5).

[0533] The server generates map data based on the acquired data and displays the problem areas in red, among other visual representations (step 6).

[0534] The analysis results and map data are sent to the terminal, which receives them (step 7).

[0535] The user checks the map on their iPhone and visually understands the communication situation around Station X (Step 8).

[0536] These detailed steps allow the user to accurately identify the communication problems they are experiencing, which can be used to improve the communication network.

[0537] Example 1

[0538] 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."

[0539] In modern communication networks, communication problems experienced by users frequently occur, but it is difficult to identify the specific causes and quickly fix them. In particular, there is a lack of methods to accurately grasp where and when users experience communication problems and provide corresponding data analysis and visual feedback.

[0540] 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.

[0541] In this invention, the server includes means for acquiring location information and time information input by a user, means for transmitting the location information and time information to the server via a secure communication channel, means for searching a database for a communication log corresponding to the location information and time information, means for analyzing the communication log to extract data including physical channel utilization rate, frequency, and communication speed, and means for mapping and visually displaying the extracted data on a map, thereby enabling the specific cause of a communication problem experienced by the user to be quickly identified and visual feedback to be provided.

[0542] "Location information" is data that indicates the user's current location, and is usually composed of latitude and longitude.

[0543] "Time information" is data indicating the time when the user inputs an instruction, and is recorded in the format of date and time.

[0544] A "secure communication channel" is a communication path that guarantees high security when sending and receiving data, and uses encryption protocols such as SSL / TLS.

[0545] A "server" refers to a computer system that processes various types of data over a network, and is a device that analyzes communication logs and performs data mapping.

[0546] A "database" is a storage system for effectively managing and searching large amounts of digital information, and is used to store information such as communication logs.

[0547] A "communication log" is data that records the usage status and performance of a communication network, and includes indicators such as physical channel utilization rate, frequency, and communication speed.

[0548] "Physical channel utilization" is a measure of the usage of physical channels in a communications network, usually expressed as a percentage.

[0549] "Frequency" is an indicator of the speed of periodic changes in signals used for communication, and is usually expressed in Hertz (Hz).

[0550] "Communication speed" is an indicator of the speed at which data can be sent and received over a communication line, and is usually expressed in bits per second (bps).

[0551] "Mapping on a map" refers to displaying acquired data in association with geographical locations, typically visually represented using a digital map.

[0552] The present invention is a system that collects and analyzes communication trouble information experienced by users and visually displays the results in order to improve the efficiency of communication network operation. This system is mainly composed of user terminals, a server, and a database, and is implemented in the following specific steps.

[0553] First, when a user experiences a communication problem, they use their own device (e.g., a smartphone) to give instructions by voice or text input. A specific input method could be, "Show me the communication log for today near XX station." The device receives this instruction, obtains the user's current location information using a GPS service, and collects accurate time information using its internal clock.

[0554] Next, the acquired location and time information is packaged into a data packet and sent to the server via a secure communication channel such as SSL / TLS. At this stage, the device encrypts the collected data to ensure the security of the communication. The server also searches a database for the corresponding communication log based on the received location and time information. The communication log contains data such as physical channel utilization (PCU), frequency, and communication speed.

[0555] The server analyzes the communication logs obtained from the database using analytical tools such as Python or R. For example, Python's NumPy or Pandas library can be used. During data analysis, the causes of malfunctions, such as PCUs exceeding a certain threshold or reduced communication speeds, are identified and extracted.

[0556] The analyzed data is converted into map data using formats such as GeoJSON. The server generates this map data and sends it back to the user's device. The user's device then visually displays the received map data using a map drawing library such as Google Maps API or Leaflet.js. This allows the user to intuitively check the communication status at a specified location and time.

[0557] As a specific example, if a user types into their iPhone, "Show me today's communication log near Shibuya Station," the device will obtain the latitude (35.6581), longitude (139.7017), and time information for 15:30 on October 5, 2023, and send this information to the server. The server uses this information to search its database, obtains and analyzes log data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps. Map data is generated based on the analysis results and provided to the user's device. The user can visually check the communication status near Shibuya Station on their iPhone screen.

[0558] As described above, the system of the present invention improves the operational efficiency of a communication network by collecting data based on communication problems that users specifically experience and intuitively visualizing the analysis results.

[0559] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0560] Step 1:

[0561] When a user experiences a communication problem, they can give instructions to their smartphone or other device by voice or text input, such as "Show me the communication log for today near XX station." The input location and time information is then acquired.

[0562] Input: User voice or text input

[0563] Output: Location information (latitude, longitude) and time information (year, month, day, hour)

[0564] Specific behavior:

[0565] The user launches the app on their iPhone and says, "Show me the log of communications near Shibuya Station today."

[0566] The device obtains the user's current location using the GPS service as latitude 35.6581 and longitude 139.7017, and records the time information of 15:30 on October 5, 2023 using the internal clock.

[0567] Step 2:

[0568] The location and time information acquired by the terminal is compiled into a data packet and sent to the server using a secure communication channel (SSL / TLS).

[0569] Input: Location information (latitude, longitude) and time information (year, month, day, hour)

[0570] Output: Data packets over a secure communication channel

[0571] Specific behavior:

[0572] The terminal packages the location and time information into a data packet.

[0573] It uses the SSL / TLS protocol to send data packets to servers such as Amazon Web Services and Microsoft Azure.

[0574] Step 3:

[0575] Based on the location information and time information received by the server, the corresponding communication log is searched for in the database.

[0576] Input: Location information (latitude, longitude) and time information (year, month, day, hour)

[0577] Output: Corresponding communication log (physical channel utilization, frequency, communication speed)

[0578] Specific behavior:

[0579] The server generates a database query and searches the database based on the location information (latitude 35.6581, longitude 139.7017) and time information (October 5, 2023, 15:30).

[0580] Obtain the corresponding communication log (e.g., PCU is 90%, frequency is 2.4GHz, communication speed is 1Mbps).

[0581] Step 4:

[0582] The communication log acquired by the server is analyzed and data such as physical channel utilization rate (PCU), frequency, and communication speed is extracted.

[0583] Input: Communication log data

[0584] Output: Analyzed failure data (physical channel utilization, reduced communication speed, etc.)

[0585] Specific behavior:

[0586] The server loads the communication logs using Python's NumPy and Pandas libraries.

[0587] Analyze and identify data on PCUs that exceed a certain threshold or have reduced communication speeds.

[0588] Step 5:

[0589] Based on the analysis results, the server generates map data in GeoJSON format and creates data for visual display.

[0590] Input: Analyzed failure data (physical channel utilization, reduced communication speed, etc.)

[0591] Output: Map data in GeoJSON format

[0592] Specific behavior:

[0593] The server generates map data in GeoJSON format, coloring areas with slow communication speeds in red and areas with fast speeds in green.

[0594] The generated GeoJSON data is sent to the user's device.

[0595] Step 6:

[0596] The GeoJSON data received by the user device is used to display the analysis results using map drawing libraries such as Google Maps API and Leaflet.js.

[0597] Input: Map data in GeoJSON format

[0598] Output: A visual map representation on the user interface

[0599] Specific behavior:

[0600] The user device uses the Google Maps API to draw the received GeoJSON data on a map.

[0601] Users can check the map displayed on the app and intuitively understand the communication situation near Station X.

[0602] The above are the specific processing steps of this system.

[0603] (Application example 1)

[0604] 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."

[0605] Stable communications are essential for the efficient and safe operation of robots in factories. However, if a communications failure occurs in a specific area of ​​the factory, it can affect the operation of the robots and reduce production efficiency. Conventional systems lack the means to quickly identify the cause of a failure and take appropriate action when it occurs. For this reason, there is a need to develop a system that can detect communications failures in real time and visually display the analysis results, enabling a rapid response.

[0606] 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.

[0607] In this invention, the server includes means for acquiring location information and time information input by a user, means for transmitting the location information and time information to the server, means for searching a database for a communication log corresponding to the location information and time information, means for analyzing the communication log and extracting defective data, means for mapping the extracted data on a map and visually displaying it, and means for a robot in a factory to automatically detect a communication failure and analyze and visualize the communication status in real time. This makes it possible to quickly identify a communication failure occurring in a specific area in a factory, analyze its cause, and visually grasp its cause.

[0608] "Location information" is the latitude and longitude data required to indicate a specific location.

[0609] "Time information" is data that indicates a specific time, and includes the date, hour, minute, and second.

[0610] A "database" is a system for storing and managing large amounts of data in an organized manner.

[0611] A "communication log" is recorded data generated during the communication process, and includes information such as physical channel utilization rate, frequency, and communication speed.

[0612] A "robot" is a machine that performs specific tasks automatically or under the control of a program.

[0613] "Communication failure" refers to a state in which communication is not carried out normally, including failure of data transmission or slowdown in speed.

[0614] "Analysis" is the process of examining and understanding the data obtained and extracting specific information.

[0615] "Visualization" refers to the visual presentation of data or information in an easy-to-understand manner.

[0616] This invention is a system that automatically detects communication problems in robots operated in factories and analyzes and visualizes the communication status in real time. This system acquires location and time information when a user experiences a communication problem, sends it to a server, searches and analyzes the corresponding communication log from a database, extracts the data containing the problem, and visually displays it on a map.

[0617] System configuration

[0618] Hardware and software used

[0619] The system hardware includes the robots operated in the factory, the sensors, GPS modules, and internal clocks installed on the robots, while the software includes the robot control system, a dedicated server, a database (e.g., MySQL), an analysis tool (e.g., Python's Pandas, NumPy), and a map display tool (e.g., Leaflet.js).

[0620] Processing flow

[0621] 1. Detecting communication problems

[0622] The robot utilizes internal sensors and a GPS module to obtain location information (latitude and longitude) and time information, which is automatically recorded when the robot detects a communication failure.

[0623] 2. Transmission of information

[0624] The robot assembles the acquired position and time information into a data packet and sends it to a dedicated server using a secure communication channel.

[0625] 3. Searching from the database

[0626] The server searches the database based on the received location and time information and obtains the corresponding communication log (physical channel utilization rate, frequency, communication speed, etc.).

[0627] 4. Data Analysis

[0628] The server analyzes the communication log using an analysis tool (e.g., Python's Pandas or NumPy) and identifies data related to the malfunction.

[0629] 5. Visualizing the results

[0630] The server uses a map display tool (e.g., Leaflet.js) to map the areas where the analysis results are occurring on a map of the factory, generating data that can be displayed visually.

[0631] 6. Displaying the results

[0632] Data is sent to the robot's control system and the results are displayed in real time via a tablet or head-mounted display, allowing factory managers to visually check the specific communication status.

[0633] Specific examples

[0634] For example, if a robot detects a communication problem (a drop in communication speed) in a specific area (latitude 35.6581, longitude 139.7414), the robot will send this information to the server along with the time information recorded by its internal clock (e.g., October 5, 2023, 15:30).

[0635] The server searches the database, obtains and analyzes the communication log corresponding to this location and time (e.g., physical channel utilization rate 90%, frequency 2.4GHz, communication speed 1Mbps).The server generates map data based on the analysis results and sends it to the robot's control system so that it can be displayed visually.

[0636] The robot's control system displays the analysis results in real time to factory managers via a tablet or head-mounted display, allowing them to grasp the specific communication situation in a specific area and take prompt action.

[0637] Prompt Sentence Examples

[0638] "Get a detailed log of communication issues in a specific area of ​​the factory (latitude 35.6581, longitude 139.7414) and visualize it on a map."

[0639] As described above, the system of the present invention allows robots in factories to automatically detect and analyze communication problems and visually display them, enabling quick and efficient responses.

[0640] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0641] Step 1:

[0642] Detection of communication problems

[0643] The robot uses its internal sensors and GPS module to obtain the latitude and longitude of its current location. It also uses its internal clock to record the current time. This location and time information is used as input. The robot automatically detects communication problems, such as slow communication speeds in a specific area, and uses this information as a trigger to start processing.

[0644] Step 2:

[0645] Sending information

[0646] The robot assembles the input location and time information into a data packet and sends it to the server using a secure communication channel. The transmitted data includes location information, time information, and communication status. The server receives this data and proceeds to the next step.

[0647] Step 3:

[0648] Searching from the database

[0649] The server searches the database based on the received location and time information. Specifically, it retrieves the communication log—data including physical channel utilization, frequency, and communication speed—corresponding to the received latitude, longitude, and time. This communication log data becomes the input for the next analysis process.

[0650] Step 4:

[0651] Data analysis

[0652] The server uses data analysis tools (e.g., Python's Pandas or NumPy) to analyze the communication logs retrieved from the database. The purpose of the analysis is to identify the cause of the problem, such as detecting physical channel utilization rates exceeding a certain threshold or reduced communication speeds. The analysis results in data containing the problem areas and their detailed information, which serves as input for the next process.

[0653] Step 5:

[0654] Visualizing the results

[0655] The server uses a map display tool (e.g., Leaflet.js) to map the analysis results on a map of the factory. Specifically, it identifies areas with defects based on the analysis results and generates map data that visually indicates those areas using color coding and markers. This map data becomes the input for the next process.

[0656] Step 6:

[0657] Displaying the results

[0658] The robot's control system receives map data and analysis results sent from the server and displays them in real time on a tablet or head-mounted display, allowing factory managers to visually confirm the location and details of communication problems and respond quickly.

[0659] Through the above processing steps, robots operating in factories automatically detect and analyze communication problems and visually display the results, enabling efficient factory operations and rapid problem resolution.

[0660] 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.

[0661] The system of the present invention not only recognizes communication problems experienced by users, but also has the ability to acquire user emotional information and analyze the status of the communication network based on that information, making it possible to identify more detailed communication conditions that are closer to the user's actual experience and improve the area.

[0662] System Overview

[0663] The system of the present invention comprises the following elements:

[0664] User terminal

[0665] server

[0666] Database

[0667] Emotion Engine

[0668] System components and roles

[0669] User terminal

[0670] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal is equipped with a location information service and an internal clock, which acquires current location and time information. It also has an emotion engine that recognizes the user's emotions and acquires emotional information.

[0671] server

[0672] The server receives location, time, and emotion information sent from the user terminal, searches for the corresponding communication log in the database, and analyzes the acquired communication log to extract any defective data and map it on a map.

[0673] Database

[0674] The database stores communication logs, which include data such as physical channel utilization, frequency, and communication speed.

[0675] Emotion Engine

[0676] The emotion engine analyzes emotions from the user's voice, facial expressions, text input, etc., and acquires specific emotional information.

[0677] Program processing

[0678] User instruction input

[0679] When a user experiences a communication problem, they input a command into their device, such as "Show me the log of communication near station X today." This command causes the device to collect current location and time information, and the emotion engine analyzes the user's emotions.

[0680] Acquiring location, time, and emotion information

[0681] The device uses location services to obtain the current latitude and longitude of the device, and uses the system's internal clock to record the exact time when the command was input. The emotion engine obtains emotional information from the user's voice and facial expressions.

[0682] Sending information

[0683] The location information, time information, and emotion information acquired by the terminal are packaged into a data packet and transmitted to a server using a secure communication channel.

[0684] Searching from the database

[0685] The server queries the database based on the received location information, time information, and emotion information, and searches for corresponding communication logs with priority based on emotion information in particular.

[0686] Data analysis

[0687] The server analyzes the communication logs it acquires and identifies data related to the problems experienced by the user. It detects when the PCU exceeds a certain threshold or when communication speed drops, and extracts that data.

[0688] Visualizing the results

[0689] The server creates map data based on the analysis results, maps the data points in the communication log onto a map, and visually represents the situation using color coding.

[0690] Sending the results to the device

[0691] The server sends the generated map data and analysis results to the device, where they are formatted as map images and interactive data.

[0692] Displaying the results

[0693] The device displays the received data to the user, who can then view the map to check the specific communication status and the occurrence of any problems.

[0694] Specific examples

[0695] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[0696] The user enters a command into their iPhone, such as "Show me the communication log for today near XX station."

[0697] The device obtains its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using GPS, and records the time (e.g., October 5, 2023, 15:30) using its internal clock.

[0698] The emotion engine acquires emotional information such as dissatisfaction and irritation from the user's voice and facial expressions.

[0699] This information is sent to the server using HTTPS.

[0700] The server uses this information to retrieve the corresponding communication log from the database. For example, it searches for data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[0701] The server analyzes this data, determines that the communication speed is slowing due to a high PCU, and generates an analysis result along with emotional information.

[0702] Based on the data acquired by the server and the analysis results, map data is generated and a visual representation is created, such as showing faulty points in red.

[0703] The analysis results and map data are sent to the terminal, which receives them.

[0704] Users can check the map on their iPhone and actively understand the communication situation around Station X.

[0705] As described above, the system of the present invention collects and analyzes specific data based on user sensory and emotional information, and visually displays the results, thereby supporting efficient operation of communication networks and area improvement.

[0706] The processing flow will be explained below.

[0707] Step 1: User input

[0708] The user inputs a command into the system on their iPhone, such as "Show me the log of communications near XX station today."

[0709] The user's voice and text inputs are analyzed by the emotion engine.

[0710] Step 2: Obtaining location and time information

[0711] Your device uses location services (such as GPS or Wi-Fi location) to obtain its current latitude and longitude.

[0712] The device uses its internal clock to record the exact date and time when the instruction is entered.

[0713] Step 3: Acquiring emotional information

[0714] The emotion engine installed in the device analyzes and acquires emotional information from the user's voice and facial expressions.

[0715] The emotion engine detects feelings of dissatisfaction or irritation from the user's tone of voice, facial expression recognition, text analysis, etc.

[0716] Step 4: Send location, time, and emotion information to the server

[0717] The location information, time information, and emotion information acquired by the terminal are combined into one data packet.

[0718] This data packet is sent to the server over a secure communication channel (e.g. HTTPS).

[0719] Step 5: Search communication logs from the database

[0720] The server analyzes the received location information, time information, and emotion information, and queries a database for information about the relevant area and time.

[0721] The server retrieves communication logs related to physical channel utilization, frequency, and communication speed from the database.

[0722] Step 6: Analyze the communication log

[0723] The communication log acquired by the server is analyzed to identify data related to the malfunction experienced by the user.

[0724] The server determines whether the PCU exceeds a certain threshold or whether the communication speed is slowing down.

[0725] Priority is set for the analysis results based on emotional information.

[0726] Step 7: Visualize the results

[0727] The server creates map data based on the analysis results.

[0728] The server maps the data points from the communication log onto a map, color-coding the situation to create a visual representation.

[0729] To highlight the severity of a defect based on emotional information.

[0730] Step 8: Sending the results to the device

[0731] The server sends the generated map data and analysis results to the terminal.

[0732] The submitted data is formatted as map images and interactive data.

[0733] Step 9: View the results

[0734] The terminal displays the received data to the user.

[0735] Users can view the map to check the specific communication status and the occurrence of any problems.

[0736] Specific examples

[0737] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[0738] Step 1: The user types into the iPhone, "Show me the log of communications near XX station today." The user's voice sounds irritated.

[0739] Step 2: The device uses GPS to obtain its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) and record the time (e.g., October 5, 2023, 15:30).

[0740] Step 3: The emotion engine obtains the emotion information of irritation from the user's voice tone and facial expression.

[0741] Step 4: This information is sent to the server using HTTPS.

[0742] Step 5: The server uses this information to retrieve the corresponding communication log from the database. For example, it searches for data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[0743] Step 6: The server analyzes this data, determines that the communication speed is slowing down due to a high PCU, and sets a high priority to the analysis results, taking into account emotional information.

[0744] Step 7: Based on the data acquired by the server and the analysis results, map data is generated and a visual representation is created, such as displaying faulty points in red.

[0745] Step 8: The analysis results and map data are sent to the terminal, which receives them.

[0746] Step 9: The user checks the map on their iPhone and actively understands the communication situation around Station XX.

[0747] These detailed steps allow users to accurately identify the communication problems they experience and use the information to improve the communication network. In addition, incorporating emotional information makes it possible to identify high-priority problems based on user experience.

[0748] Example 2

[0749] 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."

[0750] Conventional communication failure analysis systems have difficulty accurately grasping the detailed circumstances of communication failures experienced by users. In particular, because they do not take into account the user's emotional information, they are unable to properly reflect the degree of failure or urgency experienced by the user, making it difficult to efficiently operate communication networks and improve coverage areas. This makes it difficult to provide a communication environment that satisfies users.

[0751] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0752] In this invention, the server includes means for acquiring location information and time information input by the user, means for acquiring user emotion information based on the location information and time information, means for transmitting the location information, time information, and emotion information to the server, means for searching a corresponding communication log from a database based on the location information, time information, and emotion information, means for analyzing the communication log and extracting defective data, and means for mapping the extracted data on a map and visually displaying it. This enables more detailed identification of communication defects based on the user's bodily sensations and emotion information, and efficient operation and area improvement of the communication network.

[0753] "Location information" refers to the current latitude and longitude of the user terminal.

[0754] "Time information" records the exact date and time when the user inputs the instruction.

[0755] "Emotion information" refers to specific emotional data analyzed from the user's voice, facial expressions, text input, etc.

[0756] The term "server" refers to a computer system that receives location information, time information, and emotion information sent from a user terminal, searches a database based on this information, and analyzes communication logs.

[0757] A "communication log" is a record of the history of data exchange in a communication network, and includes information such as physical channel utilization rate, frequency, and communication speed.

[0758] "Database" refers to an information management system for storing communication logs.

[0759] "Extraction" refers to the process of extracting defect data that meets specific conditions from the analyzed communication log.

[0760] A "map" provides geographic information for visually displaying analyzed data.

[0761] "Mapping" refers to the process of locating and displaying acquired data on a map.

[0762] "Visual display" refers to a method of expressing data on a screen using color, shape, position, etc. so that the user can intuitively understand it.

[0763] The system of the present invention has the function of recognizing communication problems experienced by users, acquiring user emotional information, and analyzing the status of the communication network based on that information. This system makes it possible to identify detailed communication conditions and improve coverage areas based on the user's experience.

[0764] System components and roles

[0765] User terminal

[0766] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal is equipped with a location information service (GPS) and an internal clock, which acquires current location and time information. It also has an emotion engine that analyzes the user's emotions and acquires emotional information.

[0767] server

[0768] The server receives location, time, and emotion information sent from the user's device and searches the database for corresponding communication logs. The server also analyzes the acquired communication logs, extracts defective data, and maps it on a map. The server processes the data using Python and SQL.

[0769] Database

[0770] The database stores communication logs and includes data such as physical channel utilization, frequency, and communication speed.

[0771] Emotion Engine

[0772] The emotion engine analyzes emotions from the user's voice, facial expressions, text input, etc., and obtains specific emotional information. The emotion engine uses a cloud-based emotion analysis API.

[0773] Specific processing flow of the program

[0774] 1. User input:

[0775] When a user experiences a communication problem, they can input a command by voice, such as "Show me the communication log for today near station XX." The device then converts this voice command into text using the Google Speech-to-Text API.

[0776] 2. Obtaining location, time, and emotion information:

[0777] The device uses a GPS sensor to obtain its current latitude and longitude, and an internal clock to record the time when commands are input. The emotion engine uses a camera and microphone to analyze the user's voice and facial expressions to obtain emotional information such as "dissatisfaction" or "irritation."

[0778] 3. Transmission of Information:

[0779] The device sends the acquired location information (e.g., latitude 35.6581, longitude 139.7414), time information (e.g., October 5, 2023, 15:30), and emotion information to the server using HTTPS.

[0780] 4. Searching from the database:

[0781] The server searches the database based on the received information and retrieves the corresponding communication log. The server generates an SQL query to search the database for the required communication log (e.g., PCU is 90%, frequency is 2.4 GHz, communication speed is 1 Mbps).

[0782] 5. Data Analysis:

[0783] The server uses the Python pandas library to analyze the communication log and identify the cause of the problem. For example, if the PCU utilization rate exceeds a threshold (e.g., 85%), it can determine that the communication speed is decreasing.

[0784] 6. Visualizing the results:

[0785] The server uses the Google Maps API to map the analyzed data, creating a visual representation such as showing faulty areas in red.

[0786] 7. Sending the results to the device:

[0787] The server sends the generated map data and analysis results in JSON format to the terminal via HTTPS.

[0788] 8. Displaying the results:

[0789] The device uses React Native to visually display a map and analysis results to the user, who can then manipulate the map to check detailed communication status.

[0790] Specific examples

[0791] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[0792] The user voice-inputs instructions into the iPhone, such as "Show me the log of communications near XX station today."

[0793] The device uses the Google Speech-to-Text API to convert voice commands into text, which is then parsed by an internal engine.

[0794] The device obtains the current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using the GPS sensor, and records the time (e.g., October 5, 2023, 15:30) using its internal clock.

[0795] The device uses a camera and microphone to allow the emotion engine to acquire emotional information such as dissatisfaction and irritation.

[0796] This information is sent to the server using HTTPS.

[0797] Based on the information, the server retrieves the corresponding communication log from the database using an SQL query.

[0798] The server uses Python and the pandas library to analyze data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[0799] Map data is generated using the Google Maps API, and faulty areas are visually displayed in red.

[0800] The analysis results and map data are sent to the device in JSON format via HTTPS.

[0801] The device uses React Native to visually display maps and analysis results, allowing users to understand detailed communication conditions.

[0802] Prompt Sentence Examples

[0803] "If a user experiences a communication problem near XX station, please provide detailed information about the problem. Analyze the communication log based on the user's current location, time, and emotional state, and display the results on a map."

[0804] As described above, the system of the present invention collects and analyzes specific data based on user sensory and emotional information, and visually displays the results, thereby supporting efficient operation of communication networks and area improvement.

[0805] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0806] Step 1:

[0807] When a user experiences a communication problem, they can input a voice command into the device, such as "Show me the communication log for today near station XX." This command is converted into text data using the Google Speech-to-Text API. Specifically, the device captures the voice using the microphone, sends the captured voice to a cloud-based speech recognition service, and receives it as text data. The output is the user's command in text format.

[0808] Step 2:

[0809] The device uses the GPS sensor to obtain the current latitude and longitude (e.g., latitude 35.6581, longitude 139.7414). At the same time, it uses its internal clock to record the exact time the command was entered (e.g., October 5, 2023, 15:30). This data is obtained using the location service and system clock APIs. The output is location information and time information.

[0810] Step 3:

[0811] The emotion engine uses a camera and microphone to analyze the user's voice and facial expressions to obtain emotional information. Specifically, the device's camera captures the user's facial expressions and simultaneously records their voice. This data is sent to the analysis engine, which identifies emotions such as "dissatisfaction" or "irritation." The output is emotional information.

[0812] Step 4:

[0813] The location, time, and emotion information acquired by the device is sent to the server via a secure communication channel using HTTPS. This operation includes encoding the data into JSON format and sending it using the HTTPS protocol. The output is the data sent to the server.

[0814] Step 5:

[0815] The server searches the database based on the location, time, and emotion information it receives. The server generates an SQL query based on this input data and queries the database. Specifically, it creates a query using the server's SQL library, establishes a database connection, and retrieves the communication log. The output is the searched communication log.

[0816] Step 6:

[0817] The communication log acquired by the server is analyzed. Specifically, the communication log is converted into a data frame using the Python pandas library, and each column (channel utilization rate, communication speed, etc.) is analyzed. For example, if the PCU utilization rate exceeds a threshold (e.g., 85%), it is detected that the communication speed is decreasing. The output is the analyzed data.

[0818] Step 7:

[0819] The server generates map data based on the analysis results. Using the Google Maps API, the analyzed data points are mapped on a map, and any defects are visually displayed in red, etc. Specifically, the data points are added to a map object, and the display method is set based on their properties. The output is map data.

[0820] Step 8:

[0821] The server generates map data and sends the analysis results in JSON format to the device via HTTPS. Specifically, the server serializes the data in JSON format, encodes it using the HTTPS protocol, and sends it. The output is the map data and analysis results sent to the device.

[0822] Step 9:

[0823] The map data and analysis results received by the device are visually displayed. React Native is used to provide an interactive map display for the user. Specifically, the map is drawn on the device display, allowing the user to perform operations such as tapping and zooming in / out. The output is the visual map data and analysis results that are displayed to the user.

[0824] (Application example 2)

[0825] 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."

[0826] In modern communication networks, there is a need to identify communication problems experienced by users in more detail and in real time, and to take prompt measures. However, conventional systems do not analyze communication conditions taking into account user emotional information, making it difficult to identify specific problems based on user experience. Furthermore, communication stability is extremely important for autonomous vehicles, and measures must take into account the impact of communication problems on the emotions of drivers and passengers.

[0827] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0828] In this invention, the server includes means for acquiring location information, time information, and emotion information input by the user, means for transmitting this information to the server, means for searching a database for a communication log corresponding to this information, means for analyzing the communication log and extracting defective data, and means for mapping the extracted data on a map and visually displaying it. This makes it possible to identify more detailed communication conditions based on the user's emotion information and to respond quickly to defects.

[0829] "Location information" is data indicating the latitude and longitude of the location where the user terminal is currently located.

[0830] "Time information" is data indicating the specific date and time when the user experienced a communication problem.

[0831] "Emotion information" is data indicating the emotional state obtained by analyzing the user's voice, facial expression, text input, and the like.

[0832] A "server" is a computer system that has the function of receiving location information, time information, and emotion information sent from a user terminal, and searching and analyzing the corresponding communication log from a database.

[0833] A "database" is an information system that stores communication logs such as physical channel utilization rates, frequencies, and communication speeds.

[0834] A "communication log" is data that records various parameters (e.g., physical channel utilization rate, frequency, communication speed) in a communication network.

[0835] An "emotion engine" is an algorithm or software that analyzes a user's voice and facial expressions to obtain emotional information.

[0836] "Mapping" is the process of arranging acquired data based on location coordinates in order to display it on a map.

[0837] The system for implementing this invention comprises a user terminal, a server, a database, and an emotion engine. Each component of this system and their interactions will be described in detail below.

[0838] User terminal

[0839] The user terminal is a device installed in an autonomous vehicle and has the following functions to detect communication problems in real time:

[0840] GPS module: Used to obtain the latitude and longitude of the current location.

[0841] Internal clock: Used to record time information.

[0842] Camera and microphone: Used by the emotion engine to analyze the user's voice and facial expressions.

[0843] Communication module: Used to send collected data to the server.

[0844] server

[0845] The server receives location, time, and emotion information sent from the user's device, and searches and analyzes the corresponding communication logs from the database. The main functions of the server are as follows:

[0846] Database search: Search the database based on the received data to obtain related communication logs.

[0847] Data analysis: Analyze the acquired communication logs and extract any defective data.

[0848] Visualization: The extracted data is mapped on a map to generate map data for visual display.

[0849] Transmission: The generated visualization data is sent to the user's terminal.

[0850] Database

[0851] The database stores communication logs, which contain the following parameters:

[0852] Physical channel utilization

[0853] frequency

[0854] communication speed

[0855] Emotion Engine

[0856] The emotion engine is used to analyze the user's voice and facial expressions to obtain emotional information. Specifically, the following technologies are used:

[0857] Speech analysis: Google Cloud Speech-to-Text API

[0858] Facial Expression Analysis: Microsoft Azure Face API

[0859] Specific examples

[0860] Consider a situation where an autonomous vehicle is traveling through a busy downtown area and the connection speed slows down. If the passenger's emotion engine determines they are "unhappy," the application will execute the following steps:

[0861] The user device sends the GPS location (e.g., 35.6895, 139.6917) and the emotion "dissatisfied" to the server.

[0862] The server searches the database based on this information and retrieves the relevant communication logs.

[0863] Identify the cause of the slowdown in communication speed and generate visualization data.

[0864] The driver can check the visualization of the communication status on the in-vehicle display in real time and consider changing the route if necessary.

[0865] Prompt Sentence Examples

[0866] "Check the current communication status and passenger emotional state to generate analytical data to identify communication glitches."

[0867] "Extract emotional information from data from onboard cameras and microphones, and visualize it by cross-analyzing the current location and communication logs of the autonomous vehicle."

[0868] By using the system of the present invention, it is possible to identify communication problems and their impact in autonomous vehicles in real time, and to efficiently operate communication networks and quickly improve areas based on user experience and emotional information.

[0869] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0870] Step 1:

[0871] The device detects communication problems in real time. The device uses an on-board camera and microphone to input the user's voice and facial expressions into the emotion engine. The emotion engine generates the user's emotional information from this data, and obtains location and time information from the GPS module and internal clock. This information is integrated within the device. The input data is voice data, facial expression data, GPS location, and time information, and the output data is an integrated data packet.

[0872] Step 2:

[0873] The device sends the integrated data packet to the server using a secure communication channel. The data packet contains location information, time information, and emotion information. Specifically, the data is encrypted and transmitted using HTTPS. The input data is the integrated data packet, and the output data is the data that arrives at the server.

[0874] Step 3:

[0875] The server analyzes the received data packets and accesses the database to search for the corresponding communication logs. The server retrieves relevant entries from past communication logs based on location, time, and emotion information. The input data are location, time, and emotion information, and the output data is the identified communication log.

[0876] Step 4:

[0877] The server analyzes the communication logs it acquires and extracts defective data. Specifically, it evaluates parameters such as physical channel utilization, frequency, and communication speed, and detects slow communication speeds and high load conditions. Based on this data, the server identifies the cause of communication problems. The input data is the communication log, and the output data is the defective data.

[0878] Step 5:

[0879] The server maps the defect data onto map data and prepares it for visual display. The server colors the defect locations on the map and arranges the data in a format that is easy for users to understand visually. Specifically, it generates the map data using a geographic information system (GIS). The input data is the defect data, and the output data is map data that can be displayed visually.

[0880] Step 6:

[0881] The server sends the generated map data to the terminal. The terminal receives this data and displays it on the in-vehicle display. This allows the user to check the current communication status and any malfunctions in real time. The input data is the map data, and the output data is the visual data displayed on the terminal.

[0882] Step 7:

[0883] The user checks the information displayed on the in-vehicle display and considers route changes or other measures as necessary. The device receives the user's instructions and reflects them in the driving system. Specifically, it operates the navigation system to calculate a new route. The input data are visual data and the user's instructions, and the output data is the driving system's new route information.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] [Third embodiment]

[0888] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0889] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0890] 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).

[0891] 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.

[0892] 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.

[0893] 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).

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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."

[0900] The system of the present invention collects data based on communication problems experienced by users and visually displays the analysis results, thereby promoting area improvement in the operation of communication networks.

[0901] System Overview

[0902] The system of the present invention mainly comprises the following elements:

[0903] User terminal

[0904] server

[0905] Database

[0906] System components and roles

[0907] User terminal

[0908] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal has a location information service and an internal clock, and acquires current location information and time information.

[0909] server

[0910] The server receives location and time information sent from the user terminal, searches the database for the corresponding communication log, and analyzes the acquired communication log to extract any defective data and map it.

[0911] Database

[0912] The database is used to store communication logs, which include data such as physical channel utilization, frequency, and communication speed.

[0913] Program processing

[0914] User instruction input

[0915] When a user experiences a communication problem, they input a command to their device, such as "Show me the log of communication near XX station today." This command causes the device to collect current location information and time information.

[0916] Obtaining location and time information

[0917] The device uses location services to obtain the latitude and longitude of its current location, and it also uses the system's internal clock to record the exact time that you input your commands.

[0918] Sending information

[0919] The device then assembles the acquired location and time information into a data packet and transmits it to the server using a secure communication channel.

[0920] Searching from the database

[0921] The server searches the database based on the received location and time information and retrieves the corresponding communication log, which includes PCU (Physical Channel Utilization), frequency, communication speed, etc.

[0922] Data analysis

[0923] The server analyzes the acquired communication logs to identify data related to the malfunctions experienced by the user. It detects when the PCU exceeds a certain threshold or when communication speed drops, and extracts that data.

[0924] Visualizing the results

[0925] The server maps the analysis results onto a map and generates a visual display, which is sent to the user's device, including a color-coded map showing communication speeds and PCU status.

[0926] Displaying the results

[0927] The user's device displays the received map data and analysis results, allowing the user to visually check the specific communication situation.

[0928] Specific examples

[0929] For example, if a user feels that the communication speed is slow when passing near XX station, they may type into their iPhone, "Show me the communication log for today near XX station." In this case, the device obtains location information (e.g., latitude 35.6581, longitude 139.7414) and time information (e.g., October 5, 2023, 15:30) and sends it to the server.

[0930] The server searches the database, obtains and analyzes the communication log corresponding to this location and time (e.g., PCU 90%, frequency 2.4GHz, communication speed 1Mbps). The server generates map data based on the analysis results and provides it to the user so that they can visually check it. The user can understand the communication situation around XX station in detail and receive feedback for area improvements.

[0931] As described above, the system of the present invention supports efficient operation of communication networks and area improvement by collecting specific data based on communication problems experienced by users and visually displaying the analysis results.

[0932] The processing flow will be explained below.

[0933] Step 1: User input

[0934] The user inputs a command into the system on their iPhone, such as "Show me the log of communications near XX station today."

[0935] This instruction is recognized by a specific application or voice recognition system on the terminal.

[0936] Step 2: Obtaining location and time information

[0937] Your device uses location services (such as GPS or Wi-Fi location) to obtain its current latitude and longitude.

[0938] The device uses its internal clock to record the exact date and time when the instruction is entered.

[0939] Step 3: Sending location and time information to the server

[0940] The location information and time information acquired by the terminal are combined into a single data packet.

[0941] This data packet is sent to the server over a secure communication channel (e.g. HTTPS).

[0942] Step 4: Search communication logs from the database

[0943] The server analyzes the received location and time information and queries the database for information on the relevant area and time.

[0944] The server retrieves communication logs related to physical channel utilization, frequency, and communication speed from the database.

[0945] Step 5: Analyze the communication log

[0946] The communication log acquired by the server is analyzed to identify data related to the malfunction experienced by the user.

[0947] The server determines whether the PCU exceeds a certain threshold or whether the communication speed is slowing down.

[0948] Step 6: Visualize the results

[0949] The server creates map data based on the analysis results.

[0950] The server maps the data points from the communication log onto a map, color-coding the situation to create a visual representation.

[0951] Step 7: Sending the results to the device

[0952] The server sends the generated map data and analysis results to the terminal.

[0953] The submitted data is formatted as map images and interactive data.

[0954] Step 8: View the results

[0955] The terminal displays the received data to the user.

[0956] Users can view the map to check the specific communication status and the occurrence of any problems.

[0957] Specific examples

[0958] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[0959] The user enters the command "Show me the communication log for the area near XX station today" into their iPhone (Step 1).

[0960] The device obtains its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using GPS, and records the time (e.g., October 5, 2023, 15:30) using its internal clock (step 2).

[0961] This location and time information is sent to the server using HTTPS (step 3).

[0962] The server uses this information to retrieve the corresponding communication log from the database (physical channel utilization rate 90%, frequency 2.4 GHz, communication speed 1 Mbps) (Step 4).

[0963] The server analyzes this data and determines that the communication speed is slowing down due to a high PCU (step 5).

[0964] The server generates map data based on the acquired data and displays the problem areas in red, among other visual representations (step 6).

[0965] The analysis results and map data are sent to the terminal, which receives them (step 7).

[0966] The user checks the map on their iPhone and visually understands the communication situation around Station X (Step 8).

[0967] These detailed steps allow the user to accurately identify the communication problems they are experiencing, which can be used to improve the communication network.

[0968] Example 1

[0969] 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."

[0970] In modern communication networks, communication problems experienced by users frequently occur, but it is difficult to identify the specific causes and quickly fix them. In particular, there is a lack of methods to accurately grasp where and when users experience communication problems and provide corresponding data analysis and visual feedback.

[0971] 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.

[0972] In this invention, the server includes means for acquiring location information and time information input by a user, means for transmitting the location information and time information to the server via a secure communication channel, means for searching a database for a communication log corresponding to the location information and time information, means for analyzing the communication log to extract data including physical channel utilization rate, frequency, and communication speed, and means for mapping and visually displaying the extracted data on a map, thereby enabling the specific cause of a communication problem experienced by the user to be quickly identified and visual feedback to be provided.

[0973] "Location information" is data that indicates the user's current location, and is usually composed of latitude and longitude.

[0974] "Time information" is data indicating the time when the user inputs an instruction, and is recorded in the format of date and time.

[0975] A "secure communication channel" is a communication path that guarantees high security when sending and receiving data, and uses encryption protocols such as SSL / TLS.

[0976] A "server" refers to a computer system that processes various types of data over a network, and is a device that analyzes communication logs and performs data mapping.

[0977] A "database" is a storage system for effectively managing and searching large amounts of digital information, and is used to store information such as communication logs.

[0978] A "communication log" is data that records the usage status and performance of a communication network, and includes indicators such as physical channel utilization rate, frequency, and communication speed.

[0979] "Physical channel utilization" is a measure of the usage of physical channels in a communications network, usually expressed as a percentage.

[0980] "Frequency" is an indicator of the speed of periodic changes in signals used for communication, and is usually expressed in Hertz (Hz).

[0981] "Communication speed" is an indicator of the speed at which data can be sent and received over a communication line, and is usually expressed in bits per second (bps).

[0982] "Mapping on a map" refers to displaying acquired data in association with geographical locations, typically visually represented using a digital map.

[0983] The present invention is a system that collects and analyzes communication trouble information experienced by users and visually displays the results in order to improve the efficiency of communication network operation. This system is mainly composed of user terminals, a server, and a database, and is implemented in the following specific steps.

[0984] First, when a user experiences a communication problem, they use their own device (e.g., a smartphone) to give instructions by voice or text input. A specific input method could be, "Show me the communication log for today near XX station." The device receives this instruction, obtains the user's current location information using a GPS service, and collects accurate time information using its internal clock.

[0985] Next, the acquired location and time information is packaged into a data packet and sent to the server via a secure communication channel such as SSL / TLS. At this stage, the device encrypts the collected data to ensure the security of the communication. The server also searches a database for the corresponding communication log based on the received location and time information. The communication log contains data such as physical channel utilization (PCU), frequency, and communication speed.

[0986] The server analyzes the communication logs obtained from the database using analytical tools such as Python or R. For example, Python's NumPy or Pandas library can be used. During data analysis, the causes of malfunctions, such as PCUs exceeding a certain threshold or reduced communication speeds, are identified and extracted.

[0987] The analyzed data is converted into map data using formats such as GeoJSON. The server generates this map data and sends it back to the user's device. The user's device then visually displays the received map data using a map drawing library such as Google Maps API or Leaflet.js. This allows the user to intuitively check the communication status at a specified location and time.

[0988] As a specific example, if a user types into their iPhone, "Show me today's communication log near Shibuya Station," the device will obtain the latitude (35.6581), longitude (139.7017), and time information for 15:30 on October 5, 2023, and send this information to the server. The server uses this information to search its database, obtains and analyzes log data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps. Map data is generated based on the analysis results and provided to the user's device. The user can visually check the communication status near Shibuya Station on their iPhone screen.

[0989] As described above, the system of the present invention improves the operational efficiency of a communication network by collecting data based on communication problems that users specifically experience and intuitively visualizing the analysis results.

[0990] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0991] Step 1:

[0992] When a user experiences a communication problem, they can give instructions to their smartphone or other device by voice or text input, such as "Show me the communication log for today near XX station." The input location and time information is then acquired.

[0993] Input: User voice or text input

[0994] Output: Location information (latitude, longitude) and time information (year, month, day, hour)

[0995] Specific behavior:

[0996] The user launches the app on their iPhone and says, "Show me the log of communications near Shibuya Station today."

[0997] The device obtains the user's current location using the GPS service as latitude 35.6581 and longitude 139.7017, and records the time information of 15:30 on October 5, 2023 using the internal clock.

[0998] Step 2:

[0999] The location and time information acquired by the terminal is compiled into a data packet and sent to the server using a secure communication channel (SSL / TLS).

[1000] Input: Location information (latitude, longitude) and time information (year, month, day, hour)

[1001] Output: Data packets over a secure communication channel

[1002] Specific behavior:

[1003] The terminal packages the location and time information into a data packet.

[1004] It uses the SSL / TLS protocol to send data packets to servers such as Amazon Web Services and Microsoft Azure.

[1005] Step 3:

[1006] Based on the location information and time information received by the server, the corresponding communication log is searched for in the database.

[1007] Input: Location information (latitude, longitude) and time information (year, month, day, hour)

[1008] Output: Corresponding communication log (physical channel utilization, frequency, communication speed)

[1009] Specific behavior:

[1010] The server generates a database query and searches the database based on the location information (latitude 35.6581, longitude 139.7017) and time information (October 5, 2023, 15:30).

[1011] Obtain the corresponding communication log (e.g., PCU is 90%, frequency is 2.4GHz, communication speed is 1Mbps).

[1012] Step 4:

[1013] The communication log acquired by the server is analyzed and data such as physical channel utilization rate (PCU), frequency, and communication speed is extracted.

[1014] Input: Communication log data

[1015] Output: Analyzed failure data (physical channel utilization, reduced communication speed, etc.)

[1016] Specific behavior:

[1017] The server loads the communication logs using Python's NumPy and Pandas libraries.

[1018] Analyze and identify data on PCUs that exceed a certain threshold or have reduced communication speeds.

[1019] Step 5:

[1020] Based on the analysis results, the server generates map data in GeoJSON format and creates data for visual display.

[1021] Input: Analyzed failure data (physical channel utilization, reduced communication speed, etc.)

[1022] Output: Map data in GeoJSON format

[1023] Specific behavior:

[1024] The server generates map data in GeoJSON format, coloring areas with slow communication speeds in red and areas with fast speeds in green.

[1025] The generated GeoJSON data is sent to the user's device.

[1026] Step 6:

[1027] The GeoJSON data received by the user device is used to display the analysis results using map drawing libraries such as Google Maps API and Leaflet.js.

[1028] Input: Map data in GeoJSON format

[1029] Output: A visual map representation on the user interface

[1030] Specific behavior:

[1031] The user device uses the Google Maps API to draw the received GeoJSON data on a map.

[1032] Users can check the map displayed on the app and intuitively understand the communication situation near Station X.

[1033] The above are the specific processing steps of this system.

[1034] (Application example 1)

[1035] 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."

[1036] Stable communications are essential for the efficient and safe operation of robots in factories. However, if a communications failure occurs in a specific area of ​​the factory, it can affect the operation of the robots and reduce production efficiency. Conventional systems lack the means to quickly identify the cause of a failure and take appropriate action when it occurs. For this reason, there is a need to develop a system that can detect communications failures in real time and visually display the analysis results, enabling a rapid response.

[1037] 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.

[1038] In this invention, the server includes means for acquiring location information and time information input by a user, means for transmitting the location information and time information to the server, means for searching a database for a communication log corresponding to the location information and time information, means for analyzing the communication log and extracting defective data, means for mapping the extracted data on a map and visually displaying it, and means for a robot in a factory to automatically detect a communication failure and analyze and visualize the communication status in real time. This makes it possible to quickly identify a communication failure occurring in a specific area in a factory, analyze its cause, and visually grasp its cause.

[1039] "Location information" is the latitude and longitude data required to indicate a specific location.

[1040] "Time information" is data that indicates a specific time, and includes the date, hour, minute, and second.

[1041] A "database" is a system for storing and managing large amounts of data in an organized manner.

[1042] A "communication log" is recorded data generated during the communication process, and includes information such as physical channel utilization rate, frequency, and communication speed.

[1043] A "robot" is a machine that performs specific tasks automatically or under the control of a program.

[1044] "Communication failure" refers to a state in which communication is not carried out normally, including failure of data transmission or slowdown in speed.

[1045] "Analysis" is the process of examining and understanding the data obtained and extracting specific information.

[1046] "Visualization" refers to the visual presentation of data or information in an easy-to-understand manner.

[1047] This invention is a system that automatically detects communication problems in robots operated in factories and analyzes and visualizes the communication status in real time. This system acquires location and time information when a user experiences a communication problem, sends it to a server, searches and analyzes the corresponding communication log from a database, extracts the data containing the problem, and visually displays it on a map.

[1048] System configuration

[1049] Hardware and software used

[1050] The system hardware includes the robots operated in the factory, the sensors, GPS modules, and internal clocks installed on the robots, while the software includes the robot control system, a dedicated server, a database (e.g., MySQL), an analysis tool (e.g., Python's Pandas, NumPy), and a map display tool (e.g., Leaflet.js).

[1051] Processing flow

[1052] 1. Detecting communication problems

[1053] The robot utilizes internal sensors and a GPS module to obtain location information (latitude and longitude) and time information, which is automatically recorded when the robot detects a communication failure.

[1054] 2. Transmission of information

[1055] The robot assembles the acquired position and time information into a data packet and sends it to a dedicated server using a secure communication channel.

[1056] 3. Searching from the database

[1057] The server searches the database based on the received location and time information and obtains the corresponding communication log (physical channel utilization rate, frequency, communication speed, etc.).

[1058] 4. Data Analysis

[1059] The server analyzes the communication log using an analysis tool (e.g., Python's Pandas or NumPy) and identifies data related to the malfunction.

[1060] 5. Visualizing the results

[1061] The server uses a map display tool (e.g., Leaflet.js) to map the areas where the analysis results are occurring on a map of the factory, generating data that can be displayed visually.

[1062] 6. Displaying the results

[1063] Data is sent to the robot's control system and the results are displayed in real time via a tablet or head-mounted display, allowing factory managers to visually check the specific communication status.

[1064] Specific examples

[1065] For example, if a robot detects a communication problem (a drop in communication speed) in a specific area (latitude 35.6581, longitude 139.7414), the robot will send this information to the server along with the time information recorded by its internal clock (e.g., October 5, 2023, 15:30).

[1066] The server searches the database, obtains and analyzes the communication log corresponding to this location and time (e.g., physical channel utilization rate 90%, frequency 2.4GHz, communication speed 1Mbps).The server generates map data based on the analysis results and sends it to the robot's control system so that it can be displayed visually.

[1067] The robot's control system displays the analysis results in real time to factory managers via a tablet or head-mounted display, allowing them to grasp the specific communication situation in a specific area and take prompt action.

[1068] Prompt Sentence Examples

[1069] "Get a detailed log of communication issues in a specific area of ​​the factory (latitude 35.6581, longitude 139.7414) and visualize it on a map."

[1070] As described above, the system of the present invention allows robots in factories to automatically detect and analyze communication problems and visually display them, enabling quick and efficient responses.

[1071] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1072] Step 1:

[1073] Detection of communication problems

[1074] The robot uses its internal sensors and GPS module to obtain the latitude and longitude of its current location. It also uses its internal clock to record the current time. This location and time information is used as input. The robot automatically detects communication problems, such as slow communication speeds in a specific area, and uses this information as a trigger to start processing.

[1075] Step 2:

[1076] Sending information

[1077] The robot assembles the input location and time information into a data packet and sends it to the server using a secure communication channel. The transmitted data includes location information, time information, and communication status. The server receives this data and proceeds to the next step.

[1078] Step 3:

[1079] Searching from the database

[1080] The server searches the database based on the received location and time information. Specifically, it retrieves the communication log—data including physical channel utilization, frequency, and communication speed—corresponding to the received latitude, longitude, and time. This communication log data becomes the input for the next analysis process.

[1081] Step 4:

[1082] Data analysis

[1083] The server uses data analysis tools (e.g., Python's Pandas or NumPy) to analyze the communication logs retrieved from the database. The purpose of the analysis is to identify the cause of the problem, such as detecting physical channel utilization rates exceeding a certain threshold or reduced communication speeds. The analysis results in data containing the problem areas and their detailed information, which serves as input for the next process.

[1084] Step 5:

[1085] Visualizing the results

[1086] The server uses a map display tool (e.g., Leaflet.js) to map the analysis results on a map of the factory. Specifically, it identifies areas with defects based on the analysis results and generates map data that visually indicates those areas using color coding and markers. This map data becomes the input for the next process.

[1087] Step 6:

[1088] Displaying the results

[1089] The robot's control system receives map data and analysis results sent from the server and displays them in real time on a tablet or head-mounted display, allowing factory managers to visually confirm the location and details of communication problems and respond quickly.

[1090] Through the above processing steps, robots operating in factories automatically detect and analyze communication problems and visually display the results, enabling efficient factory operations and rapid problem resolution.

[1091] 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.

[1092] The system of the present invention not only recognizes communication problems experienced by users, but also has the ability to acquire user emotional information and analyze the status of the communication network based on that information, making it possible to identify more detailed communication conditions that are closer to the user's actual experience and improve the area.

[1093] System Overview

[1094] The system of the present invention comprises the following elements:

[1095] User terminal

[1096] server

[1097] Database

[1098] Emotion Engine

[1099] System components and roles

[1100] User terminal

[1101] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal is equipped with a location information service and an internal clock, which acquires current location and time information. It also has an emotion engine that recognizes the user's emotions and acquires emotional information.

[1102] server

[1103] The server receives location, time, and emotion information sent from the user terminal, searches for the corresponding communication log in the database, and analyzes the acquired communication log to extract any defective data and map it on a map.

[1104] Database

[1105] The database stores communication logs, which include data such as physical channel utilization, frequency, and communication speed.

[1106] Emotion Engine

[1107] The emotion engine analyzes emotions from the user's voice, facial expressions, text input, etc., and acquires specific emotional information.

[1108] Program processing

[1109] User instruction input

[1110] When a user experiences a communication problem, they input a command into their device, such as "Show me the log of communication near station X today." This command causes the device to collect current location and time information, and the emotion engine analyzes the user's emotions.

[1111] Acquiring location, time, and emotion information

[1112] The device uses location services to obtain the current latitude and longitude of the device, and uses the system's internal clock to record the exact time when the command was input. The emotion engine obtains emotional information from the user's voice and facial expressions.

[1113] Sending information

[1114] The location information, time information, and emotion information acquired by the terminal are packaged into a data packet and transmitted to a server using a secure communication channel.

[1115] Searching from the database

[1116] The server queries the database based on the received location information, time information, and emotion information, and searches for corresponding communication logs with priority based on emotion information in particular.

[1117] Data analysis

[1118] The server analyzes the communication logs it acquires and identifies data related to the problems experienced by the user. It detects when the PCU exceeds a certain threshold or when communication speed drops, and extracts that data.

[1119] Visualizing the results

[1120] The server creates map data based on the analysis results, maps the data points in the communication log onto a map, and visually represents the situation using color coding.

[1121] Sending the results to the device

[1122] The server sends the generated map data and analysis results to the device, where they are formatted as map images and interactive data.

[1123] Displaying the results

[1124] The device displays the received data to the user, who can then view the map to check the specific communication status and the occurrence of any problems.

[1125] Specific examples

[1126] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[1127] The user enters a command into their iPhone, such as "Show me the communication log for today near XX station."

[1128] The device obtains its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using GPS, and records the time (e.g., October 5, 2023, 15:30) using its internal clock.

[1129] The emotion engine acquires emotional information such as dissatisfaction and irritation from the user's voice and facial expressions.

[1130] This information is sent to the server using HTTPS.

[1131] The server uses this information to retrieve the corresponding communication log from the database. For example, it searches for data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[1132] The server analyzes this data, determines that the communication speed is slowing due to a high PCU, and generates an analysis result along with emotional information.

[1133] Based on the data acquired by the server and the analysis results, map data is generated and a visual representation is created, such as showing faulty points in red.

[1134] The analysis results and map data are sent to the terminal, which receives them.

[1135] Users can check the map on their iPhone and actively understand the communication situation around Station X.

[1136] As described above, the system of the present invention collects and analyzes specific data based on user sensory and emotional information, and visually displays the results, thereby supporting efficient operation of communication networks and area improvement.

[1137] The processing flow will be explained below.

[1138] Step 1: User input

[1139] The user inputs a command into the system on their iPhone, such as "Show me the log of communications near XX station today."

[1140] The user's voice and text inputs are analyzed by the emotion engine.

[1141] Step 2: Obtaining location and time information

[1142] Your device uses location services (such as GPS or Wi-Fi location) to obtain its current latitude and longitude.

[1143] The device uses its internal clock to record the exact date and time when the instruction is entered.

[1144] Step 3: Acquiring emotional information

[1145] The emotion engine installed in the device analyzes and acquires emotional information from the user's voice and facial expressions.

[1146] The emotion engine detects feelings of dissatisfaction or irritation from the user's tone of voice, facial expression recognition, text analysis, etc.

[1147] Step 4: Send location, time, and emotion information to the server

[1148] The location information, time information, and emotion information acquired by the terminal are combined into one data packet.

[1149] This data packet is sent to the server over a secure communication channel (e.g. HTTPS).

[1150] Step 5: Search communication logs from the database

[1151] The server analyzes the received location information, time information, and emotion information, and queries a database for information about the relevant area and time.

[1152] The server retrieves communication logs related to physical channel utilization, frequency, and communication speed from the database.

[1153] Step 6: Analyze the communication log

[1154] The communication log acquired by the server is analyzed to identify data related to the malfunction experienced by the user.

[1155] The server determines whether the PCU exceeds a certain threshold or whether the communication speed is slowing down.

[1156] Priority is set for the analysis results based on emotional information.

[1157] Step 7: Visualize the results

[1158] The server creates map data based on the analysis results.

[1159] The server maps the data points from the communication log onto a map, color-coding the situation to create a visual representation.

[1160] To highlight the severity of a defect based on emotional information.

[1161] Step 8: Sending the results to the device

[1162] The server sends the generated map data and analysis results to the terminal.

[1163] The submitted data is formatted as map images and interactive data.

[1164] Step 9: View the results

[1165] The terminal displays the received data to the user.

[1166] Users can view the map to check the specific communication status and the occurrence of any problems.

[1167] Specific examples

[1168] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[1169] Step 1: The user types into the iPhone, "Show me the log of communications near XX station today." The user's voice sounds irritated.

[1170] Step 2: The device uses GPS to obtain its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) and record the time (e.g., October 5, 2023, 15:30).

[1171] Step 3: The emotion engine obtains the emotion information of irritation from the user's voice tone and facial expression.

[1172] Step 4: This information is sent to the server using HTTPS.

[1173] Step 5: The server uses this information to retrieve the corresponding communication log from the database. For example, it searches for data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[1174] Step 6: The server analyzes this data, determines that the communication speed is slowing down due to a high PCU, and sets a high priority to the analysis results, taking into account emotional information.

[1175] Step 7: Based on the data acquired by the server and the analysis results, map data is generated and a visual representation is created, such as displaying faulty points in red.

[1176] Step 8: The analysis results and map data are sent to the terminal, which receives them.

[1177] Step 9: The user checks the map on their iPhone and actively understands the communication situation around Station XX.

[1178] These detailed steps allow users to accurately identify the communication problems they experience and use the information to improve the communication network. In addition, incorporating emotional information makes it possible to identify high-priority problems based on user experience.

[1179] Example 2

[1180] 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."

[1181] Conventional communication failure analysis systems have difficulty accurately grasping the detailed circumstances of communication failures experienced by users. In particular, because they do not take into account the user's emotional information, they are unable to properly reflect the degree of failure or urgency experienced by the user, making it difficult to efficiently operate communication networks and improve coverage areas. This makes it difficult to provide a communication environment that satisfies users.

[1182] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1183] In this invention, the server includes means for acquiring location information and time information input by the user, means for acquiring user emotion information based on the location information and time information, means for transmitting the location information, time information, and emotion information to the server, means for searching a corresponding communication log from a database based on the location information, time information, and emotion information, means for analyzing the communication log and extracting defective data, and means for mapping the extracted data on a map and visually displaying it. This enables more detailed identification of communication defects based on the user's bodily sensations and emotion information, and efficient operation and area improvement of the communication network.

[1184] "Location information" refers to the current latitude and longitude of the user terminal.

[1185] "Time information" records the exact date and time when the user inputs the instruction.

[1186] "Emotion information" refers to specific emotional data analyzed from the user's voice, facial expressions, text input, etc.

[1187] The term "server" refers to a computer system that receives location information, time information, and emotion information sent from a user terminal, searches a database based on this information, and analyzes communication logs.

[1188] A "communication log" is a record of the history of data exchange in a communication network, and includes information such as physical channel utilization rate, frequency, and communication speed.

[1189] "Database" refers to an information management system for storing communication logs.

[1190] "Extraction" refers to the process of extracting defect data that meets specific conditions from the analyzed communication log.

[1191] A "map" provides geographic information for visually displaying analyzed data.

[1192] "Mapping" refers to the process of locating and displaying acquired data on a map.

[1193] "Visual display" refers to a method of expressing data on a screen using color, shape, position, etc. so that the user can intuitively understand it.

[1194] The system of the present invention has the function of recognizing communication problems experienced by users, acquiring user emotional information, and analyzing the status of the communication network based on that information. This system makes it possible to identify detailed communication conditions and improve coverage areas based on the user's experience.

[1195] System components and roles

[1196] User terminal

[1197] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal is equipped with a location information service (GPS) and an internal clock, which acquires current location and time information. It also has an emotion engine that analyzes the user's emotions and acquires emotional information.

[1198] server

[1199] The server receives location, time, and emotion information sent from the user's device and searches the database for corresponding communication logs. The server also analyzes the acquired communication logs, extracts defective data, and maps it on a map. The server processes the data using Python and SQL.

[1200] Database

[1201] The database stores communication logs and includes data such as physical channel utilization, frequency, and communication speed.

[1202] Emotion Engine

[1203] The emotion engine analyzes emotions from the user's voice, facial expressions, text input, etc., and obtains specific emotional information. The emotion engine uses a cloud-based emotion analysis API.

[1204] Specific processing flow of the program

[1205] 1. User input:

[1206] When a user experiences a communication problem, they can input a command by voice, such as "Show me the communication log for today near station XX." The device then converts this voice command into text using the Google Speech-to-Text API.

[1207] 2. Obtaining location, time, and emotion information:

[1208] The device uses a GPS sensor to obtain its current latitude and longitude, and an internal clock to record the time when commands are input. The emotion engine uses a camera and microphone to analyze the user's voice and facial expressions to obtain emotional information such as "dissatisfaction" or "irritation."

[1209] 3. Transmission of Information:

[1210] The device sends the acquired location information (e.g., latitude 35.6581, longitude 139.7414), time information (e.g., October 5, 2023, 15:30), and emotion information to the server using HTTPS.

[1211] 4. Searching from the database:

[1212] The server searches the database based on the received information and retrieves the corresponding communication log. The server generates an SQL query to search the database for the required communication log (e.g., PCU is 90%, frequency is 2.4 GHz, communication speed is 1 Mbps).

[1213] 5. Data Analysis:

[1214] The server uses the Python pandas library to analyze the communication log and identify the cause of the problem. For example, if the PCU utilization rate exceeds a threshold (e.g., 85%), it can determine that the communication speed is decreasing.

[1215] 6. Visualizing the results:

[1216] The server uses the Google Maps API to map the analyzed data, creating a visual representation such as showing faulty areas in red.

[1217] 7. Sending the results to the device:

[1218] The server sends the generated map data and analysis results in JSON format to the terminal via HTTPS.

[1219] 8. Displaying the results:

[1220] The device uses React Native to visually display a map and analysis results to the user, who can then manipulate the map to check detailed communication status.

[1221] Specific examples

[1222] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[1223] The user voice-inputs instructions into the iPhone, such as "Show me the log of communications near XX station today."

[1224] The device uses the Google Speech-to-Text API to convert voice commands into text, which is then parsed by an internal engine.

[1225] The device obtains the current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using the GPS sensor, and records the time (e.g., October 5, 2023, 15:30) using its internal clock.

[1226] The device uses a camera and microphone to allow the emotion engine to acquire emotional information such as dissatisfaction and irritation.

[1227] This information is sent to the server using HTTPS.

[1228] Based on the information, the server retrieves the corresponding communication log from the database using an SQL query.

[1229] The server uses Python and the pandas library to analyze data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[1230] Map data is generated using the Google Maps API, and faulty areas are visually displayed in red.

[1231] The analysis results and map data are sent to the device in JSON format via HTTPS.

[1232] The device uses React Native to visually display maps and analysis results, allowing users to understand detailed communication conditions.

[1233] Prompt Sentence Examples

[1234] "If a user experiences a communication problem near XX station, please provide detailed information about the problem. Analyze the communication log based on the user's current location, time, and emotional state, and display the results on a map."

[1235] As described above, the system of the present invention collects and analyzes specific data based on user sensory and emotional information, and visually displays the results, thereby supporting efficient operation of communication networks and area improvement.

[1236] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1237] Step 1:

[1238] When a user experiences a communication problem, they can input a voice command into the device, such as "Show me the communication log for today near station XX." This command is converted into text data using the Google Speech-to-Text API. Specifically, the device captures the voice using the microphone, sends the captured voice to a cloud-based speech recognition service, and receives it as text data. The output is the user's command in text format.

[1239] Step 2:

[1240] The device uses the GPS sensor to obtain the current latitude and longitude (e.g., latitude 35.6581, longitude 139.7414). At the same time, it uses its internal clock to record the exact time the command was entered (e.g., October 5, 2023, 15:30). This data is obtained using the location service and system clock APIs. The output is location information and time information.

[1241] Step 3:

[1242] The emotion engine uses a camera and microphone to analyze the user's voice and facial expressions to obtain emotional information. Specifically, the device's camera captures the user's facial expressions and simultaneously records their voice. This data is sent to the analysis engine, which identifies emotions such as "dissatisfaction" or "irritation." The output is emotional information.

[1243] Step 4:

[1244] The location, time, and emotion information acquired by the device is sent to the server via a secure communication channel using HTTPS. This operation includes encoding the data into JSON format and sending it using the HTTPS protocol. The output is the data sent to the server.

[1245] Step 5:

[1246] The server searches the database based on the location, time, and emotion information it receives. The server generates an SQL query based on this input data and queries the database. Specifically, it creates a query using the server's SQL library, establishes a database connection, and retrieves the communication log. The output is the searched communication log.

[1247] Step 6:

[1248] The communication log acquired by the server is analyzed. Specifically, the communication log is converted into a data frame using the Python pandas library, and each column (channel utilization rate, communication speed, etc.) is analyzed. For example, if the PCU utilization rate exceeds a threshold (e.g., 85%), it is detected that the communication speed is decreasing. The output is the analyzed data.

[1249] Step 7:

[1250] The server generates map data based on the analysis results. Using the Google Maps API, the analyzed data points are mapped on a map, and any defects are visually displayed in red, etc. Specifically, the data points are added to a map object, and the display method is set based on their properties. The output is map data.

[1251] Step 8:

[1252] The server generates map data and sends the analysis results in JSON format to the device via HTTPS. Specifically, the server serializes the data in JSON format, encodes it using the HTTPS protocol, and sends it. The output is the map data and analysis results sent to the device.

[1253] Step 9:

[1254] The map data and analysis results received by the device are visually displayed. React Native is used to provide an interactive map display for the user. Specifically, the map is drawn on the device display, allowing the user to perform operations such as tapping and zooming in / out. The output is the visual map data and analysis results that are displayed to the user.

[1255] (Application example 2)

[1256] 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."

[1257] In modern communication networks, there is a need to identify communication problems experienced by users in more detail and in real time, and to take prompt measures. However, conventional systems do not analyze communication conditions taking into account user emotional information, making it difficult to identify specific problems based on user experience. Furthermore, communication stability is extremely important for autonomous vehicles, and measures must take into account the impact of communication problems on the emotions of drivers and passengers.

[1258] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1259] In this invention, the server includes means for acquiring location information, time information, and emotion information input by the user, means for transmitting this information to the server, means for searching a database for a communication log corresponding to this information, means for analyzing the communication log and extracting defective data, and means for mapping the extracted data on a map and visually displaying it. This makes it possible to identify more detailed communication conditions based on the user's emotion information and to respond quickly to defects.

[1260] "Location information" is data indicating the latitude and longitude of the location where the user terminal is currently located.

[1261] "Time information" is data indicating the specific date and time when the user experienced a communication problem.

[1262] "Emotion information" is data indicating the emotional state obtained by analyzing the user's voice, facial expression, text input, and the like.

[1263] A "server" is a computer system that has the function of receiving location information, time information, and emotion information sent from a user terminal, and searching and analyzing the corresponding communication log from a database.

[1264] A "database" is an information system that stores communication logs such as physical channel utilization rates, frequencies, and communication speeds.

[1265] A "communication log" is data that records various parameters (e.g., physical channel utilization rate, frequency, communication speed) in a communication network.

[1266] An "emotion engine" is an algorithm or software that analyzes a user's voice and facial expressions to obtain emotional information.

[1267] "Mapping" is the process of arranging acquired data based on location coordinates in order to display it on a map.

[1268] The system for implementing this invention comprises a user terminal, a server, a database, and an emotion engine. Each component of this system and their interactions will be described in detail below.

[1269] User terminal

[1270] The user terminal is a device installed in an autonomous vehicle and has the following functions to detect communication problems in real time:

[1271] GPS module: Used to obtain the latitude and longitude of the current location.

[1272] Internal clock: Used to record time information.

[1273] Camera and microphone: Used by the emotion engine to analyze the user's voice and facial expressions.

[1274] Communication module: Used to send collected data to the server.

[1275] server

[1276] The server receives location, time, and emotion information sent from the user's device, and searches and analyzes the corresponding communication logs from the database. The main functions of the server are as follows:

[1277] Database search: Search the database based on the received data to obtain related communication logs.

[1278] Data analysis: Analyze the acquired communication logs and extract any defective data.

[1279] Visualization: The extracted data is mapped on a map to generate map data for visual display.

[1280] Transmission: The generated visualization data is sent to the user's terminal.

[1281] Database

[1282] The database stores communication logs, which contain the following parameters:

[1283] Physical channel utilization

[1284] frequency

[1285] communication speed

[1286] Emotion Engine

[1287] The emotion engine is used to analyze the user's voice and facial expressions to obtain emotional information. Specifically, the following technologies are used:

[1288] Speech analysis: Google Cloud Speech-to-Text API

[1289] Facial Expression Analysis: Microsoft Azure Face API

[1290] Specific examples

[1291] Consider a situation where an autonomous vehicle is traveling through a busy downtown area and the connection speed slows down. If the passenger's emotion engine determines they are "unhappy," the application will execute the following steps:

[1292] The user device sends the GPS location (e.g., 35.6895, 139.6917) and the emotion "dissatisfied" to the server.

[1293] The server searches the database based on this information and retrieves the relevant communication logs.

[1294] Identify the cause of the slowdown in communication speed and generate visualization data.

[1295] The driver can check the visualization of the communication status on the in-vehicle display in real time and consider changing the route if necessary.

[1296] Prompt Sentence Examples

[1297] "Check the current communication status and passenger emotional state to generate analytical data to identify communication glitches."

[1298] "Extract emotional information from data from onboard cameras and microphones, and visualize it by cross-analyzing the current location and communication logs of the autonomous vehicle."

[1299] By using the system of the present invention, it is possible to identify communication problems and their impact in autonomous vehicles in real time, and to efficiently operate communication networks and quickly improve areas based on user experience and emotional information.

[1300] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1301] Step 1:

[1302] The device detects communication problems in real time. The device uses an on-board camera and microphone to input the user's voice and facial expressions into the emotion engine. The emotion engine generates the user's emotional information from this data, and obtains location and time information from the GPS module and internal clock. This information is integrated within the device. The input data is voice data, facial expression data, GPS location, and time information, and the output data is an integrated data packet.

[1303] Step 2:

[1304] The device sends the integrated data packet to the server using a secure communication channel. The data packet contains location information, time information, and emotion information. Specifically, the data is encrypted and transmitted using HTTPS. The input data is the integrated data packet, and the output data is the data that arrives at the server.

[1305] Step 3:

[1306] The server analyzes the received data packets and accesses the database to search for the corresponding communication logs. The server retrieves relevant entries from past communication logs based on location, time, and emotion information. The input data are location, time, and emotion information, and the output data is the identified communication log.

[1307] Step 4:

[1308] The server analyzes the communication logs it acquires and extracts defective data. Specifically, it evaluates parameters such as physical channel utilization, frequency, and communication speed, and detects slow communication speeds and high load conditions. Based on this data, the server identifies the cause of communication problems. The input data is the communication log, and the output data is the defective data.

[1309] Step 5:

[1310] The server maps the defect data onto map data and prepares it for visual display. The server colors the defect locations on the map and arranges the data in a format that is easy for users to understand visually. Specifically, it generates the map data using a geographic information system (GIS). The input data is the defect data, and the output data is map data that can be displayed visually.

[1311] Step 6:

[1312] The server sends the generated map data to the terminal. The terminal receives this data and displays it on the in-vehicle display. This allows the user to check the current communication status and any malfunctions in real time. The input data is the map data, and the output data is the visual data displayed on the terminal.

[1313] Step 7:

[1314] The user checks the information displayed on the in-vehicle display and considers route changes or other measures as necessary. The device receives the user's instructions and reflects them in the driving system. Specifically, it operates the navigation system to calculate a new route. The input data are visual data and the user's instructions, and the output data is the driving system's new route information.

[1315] 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.

[1316] 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.

[1317] 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.

[1318] [Fourth embodiment]

[1319] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1320] 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.

[1321] 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).

[1322] 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.

[1323] 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.

[1324] 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).

[1325] 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.

[1326] 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.

[1327] 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.

[1328] 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.

[1329] 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.

[1330] 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.

[1331] 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."

[1332] The system of the present invention collects data based on communication problems experienced by users and visually displays the analysis results, thereby promoting area improvement in the operation of communication networks.

[1333] System Overview

[1334] The system of the present invention mainly comprises the following elements:

[1335] User terminal

[1336] server

[1337] Database

[1338] System components and roles

[1339] User terminal

[1340] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal has a location information service and an internal clock, and acquires current location information and time information.

[1341] server

[1342] The server receives location and time information sent from the user terminal, searches the database for the corresponding communication log, and analyzes the acquired communication log to extract any defective data and map it.

[1343] Database

[1344] The database is used to store communication logs, which include data such as physical channel utilization, frequency, and communication speed.

[1345] Program processing

[1346] User instruction input

[1347] When a user experiences a communication problem, they input a command to their device, such as "Show me the log of communication near XX station today." This command causes the device to collect current location information and time information.

[1348] Obtaining location and time information

[1349] The device uses location services to obtain the latitude and longitude of its current location, and it also uses the system's internal clock to record the exact time that you input your commands.

[1350] Sending information

[1351] The device then assembles the acquired location and time information into a data packet and transmits it to the server using a secure communication channel.

[1352] Searching from the database

[1353] The server searches the database based on the received location and time information and retrieves the corresponding communication log, which includes PCU (Physical Channel Utilization), frequency, communication speed, etc.

[1354] Data analysis

[1355] The server analyzes the acquired communication logs to identify data related to the malfunctions experienced by the user. It detects when the PCU exceeds a certain threshold or when communication speed drops, and extracts that data.

[1356] Visualizing the results

[1357] The server maps the analysis results onto a map and generates a visual display, which is sent to the user's device, including a color-coded map showing communication speeds and PCU status.

[1358] Displaying the results

[1359] The user's device displays the received map data and analysis results, allowing the user to visually check the specific communication situation.

[1360] Specific examples

[1361] For example, if a user feels that the communication speed is slow when passing near XX station, they may type into their iPhone, "Show me the communication log for today near XX station." In this case, the device obtains location information (e.g., latitude 35.6581, longitude 139.7414) and time information (e.g., October 5, 2023, 15:30) and sends it to the server.

[1362] The server searches the database, obtains and analyzes the communication log corresponding to this location and time (e.g., PCU 90%, frequency 2.4GHz, communication speed 1Mbps). The server generates map data based on the analysis results and provides it to the user so that they can visually check it. The user can understand the communication situation around XX station in detail and receive feedback for area improvements.

[1363] As described above, the system of the present invention supports efficient operation of communication networks and area improvement by collecting specific data based on communication problems experienced by users and visually displaying the analysis results.

[1364] The processing flow will be explained below.

[1365] Step 1: User input

[1366] The user inputs a command into the system on their iPhone, such as "Show me the log of communications near XX station today."

[1367] This instruction is recognized by a specific application or voice recognition system on the terminal.

[1368] Step 2: Obtaining location and time information

[1369] Your device uses location services (such as GPS or Wi-Fi location) to obtain its current latitude and longitude.

[1370] The device uses its internal clock to record the exact date and time when the instruction is entered.

[1371] Step 3: Sending location and time information to the server

[1372] The location information and time information acquired by the terminal are combined into a single data packet.

[1373] This data packet is sent to the server over a secure communication channel (e.g. HTTPS).

[1374] Step 4: Search communication logs from the database

[1375] The server analyzes the received location and time information and queries the database for information on the relevant area and time.

[1376] The server retrieves communication logs related to physical channel utilization, frequency, and communication speed from the database.

[1377] Step 5: Analyze the communication log

[1378] The communication log acquired by the server is analyzed to identify data related to the malfunction experienced by the user.

[1379] The server determines whether the PCU exceeds a certain threshold or whether the communication speed is slowing down.

[1380] Step 6: Visualize the results

[1381] The server creates map data based on the analysis results.

[1382] The server maps the data points from the communication log onto a map, color-coding the situation to create a visual representation.

[1383] Step 7: Sending the results to the device

[1384] The server sends the generated map data and analysis results to the terminal.

[1385] The submitted data is formatted as map images and interactive data.

[1386] Step 8: View the results

[1387] The terminal displays the received data to the user.

[1388] Users can view the map to check the specific communication status and the occurrence of any problems.

[1389] Specific examples

[1390] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[1391] The user enters the command "Show me the communication log for the area near XX station today" into their iPhone (Step 1).

[1392] The device obtains its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using GPS, and records the time (e.g., October 5, 2023, 15:30) using its internal clock (step 2).

[1393] This location and time information is sent to the server using HTTPS (step 3).

[1394] The server uses this information to retrieve the corresponding communication log from the database (physical channel utilization rate 90%, frequency 2.4 GHz, communication speed 1 Mbps) (Step 4).

[1395] The server analyzes this data and determines that the communication speed is slowing down due to a high PCU (step 5).

[1396] The server generates map data based on the acquired data and displays the problem areas in red, among other visual representations (step 6).

[1397] The analysis results and map data are sent to the terminal, which receives them (step 7).

[1398] The user checks the map on their iPhone and visually understands the communication situation around Station X (Step 8).

[1399] These detailed steps allow the user to accurately identify the communication problems they are experiencing, which can be used to improve the communication network.

[1400] Example 1

[1401] 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."

[1402] In modern communication networks, communication problems experienced by users frequently occur, but it is difficult to identify the specific causes and quickly fix them. In particular, there is a lack of methods to accurately grasp where and when users experience communication problems and provide corresponding data analysis and visual feedback.

[1403] 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.

[1404] In this invention, the server includes means for acquiring location information and time information input by a user, means for transmitting the location information and time information to the server via a secure communication channel, means for searching a database for a communication log corresponding to the location information and time information, means for analyzing the communication log to extract data including physical channel utilization rate, frequency, and communication speed, and means for mapping and visually displaying the extracted data on a map, thereby enabling the specific cause of a communication problem experienced by the user to be quickly identified and visual feedback to be provided.

[1405] "Location information" is data that indicates the user's current location, and is usually composed of latitude and longitude.

[1406] "Time information" is data indicating the time when the user inputs an instruction, and is recorded in the format of date and time.

[1407] A "secure communication channel" is a communication path that guarantees high security when sending and receiving data, and uses encryption protocols such as SSL / TLS.

[1408] A "server" refers to a computer system that processes various types of data over a network, and is a device that analyzes communication logs and performs data mapping.

[1409] A "database" is a storage system for effectively managing and searching large amounts of digital information, and is used to store information such as communication logs.

[1410] A "communication log" is data that records the usage status and performance of a communication network, and includes indicators such as physical channel utilization rate, frequency, and communication speed.

[1411] "Physical channel utilization" is a measure of the usage of physical channels in a communications network, usually expressed as a percentage.

[1412] "Frequency" is an indicator of the speed of periodic changes in signals used for communication, and is usually expressed in Hertz (Hz).

[1413] "Communication speed" is an indicator of the speed at which data can be sent and received over a communication line, and is usually expressed in bits per second (bps).

[1414] "Mapping on a map" refers to displaying acquired data in association with geographical locations, typically visually represented using a digital map.

[1415] The present invention is a system that collects and analyzes communication trouble information experienced by users and visually displays the results in order to improve the efficiency of communication network operation. This system is mainly composed of user terminals, a server, and a database, and is implemented in the following specific steps.

[1416] First, when a user experiences a communication problem, they use their own device (e.g., a smartphone) to give instructions by voice or text input. A specific input method could be, "Show me the communication log for today near XX station." The device receives this instruction, obtains the user's current location information using a GPS service, and collects accurate time information using its internal clock.

[1417] Next, the acquired location and time information is packaged into a data packet and sent to the server via a secure communication channel such as SSL / TLS. At this stage, the device encrypts the collected data to ensure the security of the communication. The server also searches a database for the corresponding communication log based on the received location and time information. The communication log contains data such as physical channel utilization (PCU), frequency, and communication speed.

[1418] The server analyzes the communication logs obtained from the database using analytical tools such as Python or R. For example, Python's NumPy or Pandas library can be used. During data analysis, the causes of malfunctions, such as PCUs exceeding a certain threshold or reduced communication speeds, are identified and extracted.

[1419] The analyzed data is converted into map data using formats such as GeoJSON. The server generates this map data and sends it back to the user's device. The user's device then visually displays the received map data using a map drawing library such as Google Maps API or Leaflet.js. This allows the user to intuitively check the communication status at a specified location and time.

[1420] As a specific example, if a user types into their iPhone, "Show me today's communication log near Shibuya Station," the device will obtain the latitude (35.6581), longitude (139.7017), and time information for 15:30 on October 5, 2023, and send this information to the server. The server uses this information to search its database, obtains and analyzes log data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps. Map data is generated based on the analysis results and provided to the user's device. The user can visually check the communication status near Shibuya Station on their iPhone screen.

[1421] As described above, the system of the present invention improves the operational efficiency of a communication network by collecting data based on communication problems that users specifically experience and intuitively visualizing the analysis results.

[1422] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1423] Step 1:

[1424] When a user experiences a communication problem, they can give instructions to their smartphone or other device by voice or text input, such as "Show me the communication log for today near XX station." The input location and time information is then acquired.

[1425] Input: User voice or text input

[1426] Output: Location information (latitude, longitude) and time information (year, month, day, hour)

[1427] Specific behavior:

[1428] The user launches the app on their iPhone and says, "Show me the log of communications near Shibuya Station today."

[1429] The device obtains the user's current location using the GPS service as latitude 35.6581 and longitude 139.7017, and records the time information of 15:30 on October 5, 2023 using the internal clock.

[1430] Step 2:

[1431] The location and time information acquired by the terminal is compiled into a data packet and sent to the server using a secure communication channel (SSL / TLS).

[1432] Input: Location information (latitude, longitude) and time information (year, month, day, hour)

[1433] Output: Data packets over a secure communication channel

[1434] Specific behavior:

[1435] The terminal packages the location and time information into a data packet.

[1436] It uses the SSL / TLS protocol to send data packets to servers such as Amazon Web Services and Microsoft Azure.

[1437] Step 3:

[1438] Based on the location information and time information received by the server, the corresponding communication log is searched for in the database.

[1439] Input: Location information (latitude, longitude) and time information (year, month, day, hour)

[1440] Output: Corresponding communication log (physical channel utilization, frequency, communication speed)

[1441] Specific behavior:

[1442] The server generates a database query and searches the database based on the location information (latitude 35.6581, longitude 139.7017) and time information (October 5, 2023, 15:30).

[1443] Obtain the corresponding communication log (e.g., PCU is 90%, frequency is 2.4GHz, communication speed is 1Mbps).

[1444] Step 4:

[1445] The communication log acquired by the server is analyzed and data such as physical channel utilization rate (PCU), frequency, and communication speed is extracted.

[1446] Input: Communication log data

[1447] Output: Analyzed failure data (physical channel utilization, reduced communication speed, etc.)

[1448] Specific behavior:

[1449] The server loads the communication logs using Python's NumPy and Pandas libraries.

[1450] Analyze and identify data on PCUs that exceed a certain threshold or have reduced communication speeds.

[1451] Step 5:

[1452] Based on the analysis results, the server generates map data in GeoJSON format and creates data for visual display.

[1453] Input: Analyzed failure data (physical channel utilization, reduced communication speed, etc.)

[1454] Output: Map data in GeoJSON format

[1455] Specific behavior:

[1456] The server generates map data in GeoJSON format, coloring areas with slow communication speeds in red and areas with fast speeds in green.

[1457] The generated GeoJSON data is sent to the user's device.

[1458] Step 6:

[1459] The GeoJSON data received by the user device is used to display the analysis results using map drawing libraries such as Google Maps API and Leaflet.js.

[1460] Input: Map data in GeoJSON format

[1461] Output: A visual map representation on the user interface

[1462] Specific behavior:

[1463] The user device uses the Google Maps API to draw the received GeoJSON data on a map.

[1464] Users can check the map displayed on the app and intuitively understand the communication situation near Station X.

[1465] The above are the specific processing steps of this system.

[1466] (Application example 1)

[1467] 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."

[1468] Stable communications are essential for the efficient and safe operation of robots in factories. However, if a communications failure occurs in a specific area of ​​the factory, it can affect the operation of the robots and reduce production efficiency. Conventional systems lack the means to quickly identify the cause of a failure and take appropriate action when it occurs. For this reason, there is a need to develop a system that can detect communications failures in real time and visually display the analysis results, enabling a rapid response.

[1469] 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.

[1470] In this invention, the server includes means for acquiring location information and time information input by a user, means for transmitting the location information and time information to the server, means for searching a database for a communication log corresponding to the location information and time information, means for analyzing the communication log and extracting defective data, means for mapping the extracted data on a map and visually displaying it, and means for a robot in a factory to automatically detect a communication failure and analyze and visualize the communication status in real time. This makes it possible to quickly identify a communication failure occurring in a specific area in a factory, analyze its cause, and visually grasp its cause.

[1471] "Location information" is the latitude and longitude data required to indicate a specific location.

[1472] "Time information" is data that indicates a specific time, and includes the date, hour, minute, and second.

[1473] A "database" is a system for storing and managing large amounts of data in an organized manner.

[1474] A "communication log" is recorded data generated during the communication process, and includes information such as physical channel utilization rate, frequency, and communication speed.

[1475] A "robot" is a machine that performs specific tasks automatically or under the control of a program.

[1476] "Communication failure" refers to a state in which communication is not carried out normally, including failure of data transmission or slowdown in speed.

[1477] "Analysis" is the process of examining and understanding the data obtained and extracting specific information.

[1478] "Visualization" refers to the visual presentation of data or information in an easy-to-understand manner.

[1479] This invention is a system that automatically detects communication problems in robots operated in factories and analyzes and visualizes the communication status in real time. This system acquires location and time information when a user experiences a communication problem, sends it to a server, searches and analyzes the corresponding communication log from a database, extracts the data containing the problem, and visually displays it on a map.

[1480] System configuration

[1481] Hardware and software used

[1482] The system hardware includes the robots operated in the factory, the sensors, GPS modules, and internal clocks installed on the robots, while the software includes the robot control system, a dedicated server, a database (e.g., MySQL), an analysis tool (e.g., Python's Pandas, NumPy), and a map display tool (e.g., Leaflet.js).

[1483] Processing flow

[1484] 1. Detecting communication problems

[1485] The robot utilizes internal sensors and a GPS module to obtain location information (latitude and longitude) and time information, which is automatically recorded when the robot detects a communication failure.

[1486] 2. Transmission of information

[1487] The robot assembles the acquired position and time information into a data packet and sends it to a dedicated server using a secure communication channel.

[1488] 3. Searching from the database

[1489] The server searches the database based on the received location and time information and obtains the corresponding communication log (physical channel utilization rate, frequency, communication speed, etc.).

[1490] 4. Data Analysis

[1491] The server analyzes the communication log using an analysis tool (e.g., Python's Pandas or NumPy) and identifies data related to the malfunction.

[1492] 5. Visualizing the results

[1493] The server uses a map display tool (e.g., Leaflet.js) to map the areas where the analysis results are occurring on a map of the factory, generating data that can be displayed visually.

[1494] 6. Displaying the results

[1495] Data is sent to the robot's control system and the results are displayed in real time via a tablet or head-mounted display, allowing factory managers to visually check the specific communication status.

[1496] Specific examples

[1497] For example, if a robot detects a communication problem (a drop in communication speed) in a specific area (latitude 35.6581, longitude 139.7414), the robot will send this information to the server along with the time information recorded by its internal clock (e.g., October 5, 2023, 15:30).

[1498] The server searches the database, obtains and analyzes the communication log corresponding to this location and time (e.g., physical channel utilization rate 90%, frequency 2.4GHz, communication speed 1Mbps).The server generates map data based on the analysis results and sends it to the robot's control system so that it can be displayed visually.

[1499] The robot's control system displays the analysis results in real time to factory managers via a tablet or head-mounted display, allowing them to grasp the specific communication situation in a specific area and take prompt action.

[1500] Prompt Sentence Examples

[1501] "Get a detailed log of communication issues in a specific area of ​​the factory (latitude 35.6581, longitude 139.7414) and visualize it on a map."

[1502] As described above, the system of the present invention allows robots in factories to automatically detect and analyze communication problems and visually display them, enabling quick and efficient responses.

[1503] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1504] Step 1:

[1505] Detection of communication problems

[1506] The robot uses its internal sensors and GPS module to obtain the latitude and longitude of its current location. It also uses its internal clock to record the current time. This location and time information is used as input. The robot automatically detects communication problems, such as slow communication speeds in a specific area, and uses this information as a trigger to start processing.

[1507] Step 2:

[1508] Sending information

[1509] The robot assembles the input location and time information into a data packet and sends it to the server using a secure communication channel. The transmitted data includes location information, time information, and communication status. The server receives this data and proceeds to the next step.

[1510] Step 3:

[1511] Searching from the database

[1512] The server searches the database based on the received location and time information. Specifically, it retrieves the communication log—data including physical channel utilization, frequency, and communication speed—corresponding to the received latitude, longitude, and time. This communication log data becomes the input for the next analysis process.

[1513] Step 4:

[1514] Data analysis

[1515] The server uses data analysis tools (e.g., Python's Pandas or NumPy) to analyze the communication logs retrieved from the database. The purpose of the analysis is to identify the cause of the problem, such as detecting physical channel utilization rates exceeding a certain threshold or reduced communication speeds. The analysis results in data containing the problem areas and their detailed information, which serves as input for the next process.

[1516] Step 5:

[1517] Visualizing the results

[1518] The server uses a map display tool (e.g., Leaflet.js) to map the analysis results on a map of the factory. Specifically, it identifies areas with defects based on the analysis results and generates map data that visually indicates those areas using color coding and markers. This map data becomes the input for the next process.

[1519] Step 6:

[1520] Displaying the results

[1521] The robot's control system receives map data and analysis results sent from the server and displays them in real time on a tablet or head-mounted display, allowing factory managers to visually confirm the location and details of communication problems and respond quickly.

[1522] Through the above processing steps, robots operating in factories automatically detect and analyze communication problems and visually display the results, enabling efficient factory operations and rapid problem resolution.

[1523] 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.

[1524] The system of the present invention not only recognizes communication problems experienced by users, but also has the ability to acquire user emotional information and analyze the status of the communication network based on that information, making it possible to identify more detailed communication conditions that are closer to the user's actual experience and improve the area.

[1525] System Overview

[1526] The system of the present invention comprises the following elements:

[1527] User terminal

[1528] server

[1529] Database

[1530] Emotion Engine

[1531] System components and roles

[1532] User terminal

[1533] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal is equipped with a location information service and an internal clock, which acquires current location and time information. It also has an emotion engine that recognizes the user's emotions and acquires emotional information.

[1534] server

[1535] The server receives location, time, and emotion information sent from the user terminal, searches for the corresponding communication log in the database, and analyzes the acquired communication log to extract any defective data and map it on a map.

[1536] Database

[1537] The database stores communication logs, which include data such as physical channel utilization, frequency, and communication speed.

[1538] Emotion Engine

[1539] The emotion engine analyzes emotions from the user's voice, facial expressions, text input, etc., and acquires specific emotional information.

[1540] Program processing

[1541] User instruction input

[1542] When a user experiences a communication problem, they input a command into their device, such as "Show me the log of communication near station X today." This command causes the device to collect current location and time information, and the emotion engine analyzes the user's emotions.

[1543] Acquiring location, time, and emotion information

[1544] The device uses location services to obtain the current latitude and longitude of the device, and uses the system's internal clock to record the exact time when the command was input. The emotion engine obtains emotional information from the user's voice and facial expressions.

[1545] Sending information

[1546] The location information, time information, and emotion information acquired by the terminal are packaged into a data packet and transmitted to a server using a secure communication channel.

[1547] Searching from the database

[1548] The server queries the database based on the received location information, time information, and emotion information, and searches for corresponding communication logs with priority based on emotion information in particular.

[1549] Data analysis

[1550] The server analyzes the communication logs it acquires and identifies data related to the problems experienced by the user. It detects when the PCU exceeds a certain threshold or when communication speed drops, and extracts that data.

[1551] Visualizing the results

[1552] The server creates map data based on the analysis results, maps the data points in the communication log onto a map, and visually represents the situation using color coding.

[1553] Sending the results to the device

[1554] The server sends the generated map data and analysis results to the device, where they are formatted as map images and interactive data.

[1555] Displaying the results

[1556] The device displays the received data to the user, who can then view the map to check the specific communication status and the occurrence of any problems.

[1557] Specific examples

[1558] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[1559] The user enters a command into their iPhone, such as "Show me the communication log for today near XX station."

[1560] The device obtains its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using GPS, and records the time (e.g., October 5, 2023, 15:30) using its internal clock.

[1561] The emotion engine acquires emotional information such as dissatisfaction and irritation from the user's voice and facial expressions.

[1562] This information is sent to the server using HTTPS.

[1563] The server uses this information to retrieve the corresponding communication log from the database. For example, it searches for data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[1564] The server analyzes this data, determines that the communication speed is slowing due to a high PCU, and generates an analysis result along with emotional information.

[1565] Based on the data acquired by the server and the analysis results, map data is generated and a visual representation is created, such as showing faulty points in red.

[1566] The analysis results and map data are sent to the terminal, which receives them.

[1567] Users can check the map on their iPhone and actively understand the communication situation around Station X.

[1568] As described above, the system of the present invention collects and analyzes specific data based on user sensory and emotional information, and visually displays the results, thereby supporting efficient operation of communication networks and area improvement.

[1569] The processing flow will be explained below.

[1570] Step 1: User input

[1571] The user inputs a command into the system on their iPhone, such as "Show me the log of communications near XX station today."

[1572] The user's voice and text inputs are analyzed by the emotion engine.

[1573] Step 2: Obtaining location and time information

[1574] Your device uses location services (such as GPS or Wi-Fi location) to obtain its current latitude and longitude.

[1575] The device uses its internal clock to record the exact date and time when the instruction is entered.

[1576] Step 3: Acquiring emotional information

[1577] The emotion engine installed in the device analyzes and acquires emotional information from the user's voice and facial expressions.

[1578] The emotion engine detects feelings of dissatisfaction or irritation from the user's tone of voice, facial expression recognition, text analysis, etc.

[1579] Step 4: Send location, time, and emotion information to the server

[1580] The location information, time information, and emotion information acquired by the terminal are combined into one data packet.

[1581] This data packet is sent to the server over a secure communication channel (e.g. HTTPS).

[1582] Step 5: Search communication logs from the database

[1583] The server analyzes the received location information, time information, and emotion information, and queries a database for information about the relevant area and time.

[1584] The server retrieves communication logs related to physical channel utilization, frequency, and communication speed from the database.

[1585] Step 6: Analyze the communication log

[1586] The communication log acquired by the server is analyzed to identify data related to the malfunction experienced by the user.

[1587] The server determines whether the PCU exceeds a certain threshold or whether the communication speed is slowing down.

[1588] Priority is set for the analysis results based on emotional information.

[1589] Step 7: Visualize the results

[1590] The server creates map data based on the analysis results.

[1591] The server maps the data points from the communication log onto a map, color-coding the situation to create a visual representation.

[1592] To highlight the severity of a defect based on emotional information.

[1593] Step 8: Sending the results to the device

[1594] The server sends the generated map data and analysis results to the terminal.

[1595] The submitted data is formatted as map images and interactive data.

[1596] Step 9: View the results

[1597] The terminal displays the received data to the user.

[1598] Users can view the map to check the specific communication status and the occurrence of any problems.

[1599] Specific examples

[1600] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[1601] Step 1: The user types into the iPhone, "Show me the log of communications near XX station today." The user's voice sounds irritated.

[1602] Step 2: The device uses GPS to obtain its current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) and record the time (e.g., October 5, 2023, 15:30).

[1603] Step 3: The emotion engine obtains the emotion information of irritation from the user's voice tone and facial expression.

[1604] Step 4: This information is sent to the server using HTTPS.

[1605] Step 5: The server uses this information to retrieve the corresponding communication log from the database. For example, it searches for data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[1606] Step 6: The server analyzes this data, determines that the communication speed is slowing down due to a high PCU, and sets a high priority to the analysis results, taking into account emotional information.

[1607] Step 7: Based on the data acquired by the server and the analysis results, map data is generated and a visual representation is created, such as displaying faulty points in red.

[1608] Step 8: The analysis results and map data are sent to the terminal, which receives them.

[1609] Step 9: The user checks the map on their iPhone and actively understands the communication situation around Station XX.

[1610] These detailed steps allow users to accurately identify the communication problems they experience and use the information to improve the communication network. In addition, incorporating emotional information makes it possible to identify high-priority problems based on user experience.

[1611] Example 2

[1612] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1613] Conventional communication failure analysis systems have difficulty accurately grasping the detailed circumstances of communication failures experienced by users. In particular, because they do not take into account the user's emotional information, they are unable to properly reflect the degree of failure or urgency experienced by the user, making it difficult to efficiently operate communication networks and improve coverage areas. This makes it difficult to provide a communication environment that satisfies users.

[1614] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1615] In this invention, the server includes means for acquiring location information and time information input by the user, means for acquiring user emotion information based on the location information and time information, means for transmitting the location information, time information, and emotion information to the server, means for searching a corresponding communication log from a database based on the location information, time information, and emotion information, means for analyzing the communication log and extracting defective data, and means for mapping the extracted data on a map and visually displaying it. This enables more detailed identification of communication defects based on the user's bodily sensations and emotion information, and efficient operation and area improvement of the communication network.

[1616] "Location information" refers to the current latitude and longitude of the user terminal.

[1617] "Time information" records the exact date and time when the user inputs the instruction.

[1618] "Emotion information" refers to specific emotional data analyzed from the user's voice, facial expressions, text input, etc.

[1619] The term "server" refers to a computer system that receives location information, time information, and emotion information sent from a user terminal, searches a database based on this information, and analyzes communication logs.

[1620] A "communication log" is a record of the history of data exchange in a communication network, and includes information such as physical channel utilization rate, frequency, and communication speed.

[1621] "Database" refers to an information management system for storing communication logs.

[1622] "Extraction" refers to the process of extracting defect data that meets specific conditions from the analyzed communication log.

[1623] A "map" provides geographic information for visually displaying analyzed data.

[1624] "Mapping" refers to the process of locating and displaying acquired data on a map.

[1625] "Visual display" refers to a method of expressing data on a screen using color, shape, position, etc. so that the user can intuitively understand it.

[1626] The system of the present invention has the function of recognizing communication problems experienced by users, acquiring user emotional information, and analyzing the status of the communication network based on that information. This system makes it possible to identify detailed communication conditions and improve coverage areas based on the user's experience.

[1627] System components and roles

[1628] User terminal

[1629] The user terminal is a device that allows the user to input instructions when experiencing communication problems. The terminal is equipped with a location information service (GPS) and an internal clock, which acquires current location and time information. It also has an emotion engine that analyzes the user's emotions and acquires emotional information.

[1630] server

[1631] The server receives location, time, and emotion information sent from the user's device and searches the database for corresponding communication logs. The server also analyzes the acquired communication logs, extracts defective data, and maps it on a map. The server processes the data using Python and SQL.

[1632] Database

[1633] The database stores communication logs and includes data such as physical channel utilization, frequency, and communication speed.

[1634] Emotion Engine

[1635] The emotion engine analyzes emotions from the user's voice, facial expressions, text input, etc., and obtains specific emotional information. The emotion engine uses a cloud-based emotion analysis API.

[1636] Specific processing flow of the program

[1637] 1. User input:

[1638] When a user experiences a communication problem, they can input a command by voice, such as "Show me the communication log for today near station XX." The device then converts this voice command into text using the Google Speech-to-Text API.

[1639] 2. Obtaining location, time, and emotion information:

[1640] The device uses a GPS sensor to obtain its current latitude and longitude, and an internal clock to record the time when commands are input. The emotion engine uses a camera and microphone to analyze the user's voice and facial expressions to obtain emotional information such as "dissatisfaction" or "irritation."

[1641] 3. Transmission of Information:

[1642] The device sends the acquired location information (e.g., latitude 35.6581, longitude 139.7414), time information (e.g., October 5, 2023, 15:30), and emotion information to the server using HTTPS.

[1643] 4. Searching from the database:

[1644] The server searches the database based on the received information and retrieves the corresponding communication log. The server generates an SQL query to search the database for the required communication log (e.g., PCU is 90%, frequency is 2.4 GHz, communication speed is 1 Mbps).

[1645] 5. Data Analysis:

[1646] The server uses the Python pandas library to analyze the communication log and identify the cause of the problem. For example, if the PCU utilization rate exceeds a threshold (e.g., 85%), it can determine that the communication speed is decreasing.

[1647] 6. Visualizing the results:

[1648] The server uses the Google Maps API to map the analyzed data, creating a visual representation such as showing faulty areas in red.

[1649] 7. Sending the results to the device:

[1650] The server sends the generated map data and analysis results in JSON format to the terminal via HTTPS.

[1651] 8. Displaying the results:

[1652] The device uses React Native to visually display a map and analysis results to the user, who can then manipulate the map to check detailed communication status.

[1653] Specific examples

[1654] As a specific example, consider a case where a user passes near a certain station and feels that the communication speed is slow.

[1655] The user voice-inputs instructions into the iPhone, such as "Show me the log of communications near XX station today."

[1656] The device uses the Google Speech-to-Text API to convert voice commands into text, which is then parsed by an internal engine.

[1657] The device obtains the current latitude (e.g., 35.6581) and longitude (e.g., 139.7414) using the GPS sensor, and records the time (e.g., October 5, 2023, 15:30) using its internal clock.

[1658] The device uses a camera and microphone to allow the emotion engine to acquire emotional information such as dissatisfaction and irritation.

[1659] This information is sent to the server using HTTPS.

[1660] Based on the information, the server retrieves the corresponding communication log from the database using an SQL query.

[1661] The server uses Python and the pandas library to analyze data with a PCU of 90%, a frequency of 2.4 GHz, and a communication speed of 1 Mbps.

[1662] Map data is generated using the Google Maps API, and faulty areas are visually displayed in red.

[1663] The analysis results and map data are sent to the device in JSON format via HTTPS.

[1664] The device uses React Native to visually display maps and analysis results, allowing users to understand detailed communication conditions.

[1665] Prompt Sentence Examples

[1666] "If a user experiences a communication problem near XX station, please provide detailed information about the problem. Analyze the communication log based on the user's current location, time, and emotional state, and display the results on a map."

[1667] As described above, the system of the present invention collects and analyzes specific data based on user sensory and emotional information, and visually displays the results, thereby supporting efficient operation of communication networks and area improvement.

[1668] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1669] Step 1:

[1670] When a user experiences a communication problem, they can input a voice command into the device, such as "Show me the communication log for today near station XX." This command is converted into text data using the Google Speech-to-Text API. Specifically, the device captures the voice using the microphone, sends the captured voice to a cloud-based speech recognition service, and receives it as text data. The output is the user's command in text format.

[1671] Step 2:

[1672] The device uses the GPS sensor to obtain the current latitude and longitude (e.g., latitude 35.6581, longitude 139.7414). At the same time, it uses its internal clock to record the exact time the command was entered (e.g., October 5, 2023, 15:30). This data is obtained using the location service and system clock APIs. The output is location information and time information.

[1673] Step 3:

[1674] The emotion engine uses a camera and microphone to analyze the user's voice and facial expressions to obtain emotional information. Specifically, the device's camera captures the user's facial expressions and simultaneously records their voice. This data is sent to the analysis engine, which identifies emotions such as "dissatisfaction" or "irritation." The output is emotional information.

[1675] Step 4:

[1676] The location, time, and emotion information acquired by the device is sent to the server via a secure communication channel using HTTPS. This operation includes encoding the data into JSON format and sending it using the HTTPS protocol. The output is the data sent to the server.

[1677] Step 5:

[1678] The server searches the database based on the location, time, and emotion information it receives. The server generates an SQL query based on this input data and queries the database. Specifically, it creates a query using the server's SQL library, establishes a database connection, and retrieves the communication log. The output is the searched communication log.

[1679] Step 6:

[1680] The communication log acquired by the server is analyzed. Specifically, the communication log is converted into a data frame using the Python pandas library, and each column (channel utilization rate, communication speed, etc.) is analyzed. For example, if the PCU utilization rate exceeds a threshold (e.g., 85%), it is detected that the communication speed is decreasing. The output is the analyzed data.

[1681] Step 7:

[1682] The server generates map data based on the analysis results. Using the Google Maps API, the analyzed data points are mapped on a map, and any defects are visually displayed in red, etc. Specifically, the data points are added to a map object, and the display method is set based on their properties. The output is map data.

[1683] Step 8:

[1684] The server generates map data and sends the analysis results in JSON format to the device via HTTPS. Specifically, the server serializes the data in JSON format, encodes it using the HTTPS protocol, and sends it. The output is the map data and analysis results sent to the device.

[1685] Step 9:

[1686] The map data and analysis results received by the device are visually displayed. React Native is used to provide an interactive map display for the user. Specifically, the map is drawn on the device display, allowing the user to perform operations such as tapping and zooming in / out. The output is the visual map data and analysis results that are displayed to the user.

[1687] (Application example 2)

[1688] 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."

[1689] In modern communication networks, there is a need to identify communication problems experienced by users in more detail and in real time, and to take prompt measures. However, conventional systems do not analyze communication conditions taking into account user emotional information, making it difficult to identify specific problems based on user experience. Furthermore, communication stability is extremely important for autonomous vehicles, and measures must take into account the impact of communication problems on the emotions of drivers and passengers.

[1690] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1691] In this invention, the server includes means for acquiring location information, time information, and emotion information input by the user, means for transmitting this information to the server, means for searching a database for a communication log corresponding to this information, means for analyzing the communication log and extracting defective data, and means for mapping the extracted data on a map and visually displaying it. This makes it possible to identify more detailed communication conditions based on the user's emotion information and to respond quickly to defects.

[1692] "Location information" is data indicating the latitude and longitude of the location where the user terminal is currently located.

[1693] "Time information" is data indicating the specific date and time when the user experienced a communication problem.

[1694] "Emotion information" is data indicating the emotional state obtained by analyzing the user's voice, facial expression, text input, and the like.

[1695] A "server" is a computer system that has the function of receiving location information, time information, and emotion information sent from a user terminal, and searching and analyzing the corresponding communication log from a database.

[1696] A "database" is an information system that stores communication logs such as physical channel utilization rates, frequencies, and communication speeds.

[1697] A "communication log" is data that records various parameters (e.g., physical channel utilization rate, frequency, communication speed) in a communication network.

[1698] An "emotion engine" is an algorithm or software that analyzes a user's voice and facial expressions to obtain emotional information.

[1699] "Mapping" is the process of arranging acquired data based on location coordinates in order to display it on a map.

[1700] The system for implementing this invention comprises a user terminal, a server, a database, and an emotion engine. Each component of this system and their interactions will be described in detail below.

[1701] User terminal

[1702] The user terminal is a device installed in an autonomous vehicle and has the following functions to detect communication problems in real time:

[1703] GPS module: Used to obtain the latitude and longitude of the current location.

[1704] Internal clock: Used to record time information.

[1705] Camera and microphone: Used by the emotion engine to analyze the user's voice and facial expressions.

[1706] Communication module: Used to send collected data to the server.

[1707] server

[1708] The server receives location, time, and emotion information sent from the user's device, and searches and analyzes the corresponding communication logs from the database. The main functions of the server are as follows:

[1709] Database search: Search the database based on the received data to obtain related communication logs.

[1710] Data analysis: Analyze the acquired communication logs and extract any defective data.

[1711] Visualization: The extracted data is mapped on a map to generate map data for visual display.

[1712] Transmission: The generated visualization data is sent to the user's terminal.

[1713] Database

[1714] The database stores communication logs, which contain the following parameters:

[1715] Physical channel utilization

[1716] frequency

[1717] communication speed

[1718] Emotion Engine

[1719] The emotion engine is used to analyze the user's voice and facial expressions to obtain emotional information. Specifically, the following technologies are used:

[1720] Speech analysis: Google Cloud Speech-to-Text API

[1721] Facial Expression Analysis: Microsoft Azure Face API

[1722] Specific examples

[1723] Consider a situation where an autonomous vehicle is traveling through a busy downtown area and the connection speed slows down. If the passenger's emotion engine determines they are "unhappy," the application will execute the following steps:

[1724] The user device sends the GPS location (e.g., 35.6895, 139.6917) and the emotion "dissatisfied" to the server.

[1725] The server searches the database based on this information and retrieves the relevant communication logs.

[1726] Identify the cause of the slowdown in communication speed and generate visualization data.

[1727] The driver can check the visualization of the communication status on the in-vehicle display in real time and consider changing the route if necessary.

[1728] Prompt Sentence Examples

[1729] "Check the current communication status and passenger emotional state to generate analytical data to identify communication glitches."

[1730] "Extract emotional information from data from onboard cameras and microphones, and visualize it by cross-analyzing the current location and communication logs of the autonomous vehicle."

[1731] By using the system of the present invention, it is possible to identify communication problems and their impact in autonomous vehicles in real time, and to efficiently operate communication networks and quickly improve areas based on user experience and emotional information.

[1732] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1733] Step 1:

[1734] The device detects communication problems in real time. The device uses an on-board camera and microphone to input the user's voice and facial expressions into the emotion engine. The emotion engine generates the user's emotional information from this data, and obtains location and time information from the GPS module and internal clock. This information is integrated within the device. The input data is voice data, facial expression data, GPS location, and time information, and the output data is an integrated data packet.

[1735] Step 2:

[1736] The device sends the integrated data packet to the server using a secure communication channel. The data packet contains location information, time information, and emotion information. Specifically, the data is encrypted and transmitted using HTTPS. The input data is the integrated data packet, and the output data is the data that arrives at the server.

[1737] Step 3:

[1738] The server analyzes the received data packets and accesses the database to search for the corresponding communication logs. The server retrieves relevant entries from past communication logs based on location, time, and emotion information. The input data are location, time, and emotion information, and the output data is the identified communication log.

[1739] Step 4:

[1740] The server analyzes the communication logs it acquires and extracts defective data. Specifically, it evaluates parameters such as physical channel utilization, frequency, and communication speed, and detects slow communication speeds and high load conditions. Based on this data, the server identifies the cause of communication problems. The input data is the communication log, and the output data is the defective data.

[1741] Step 5:

[1742] The server maps the defect data onto map data and prepares it for visual display. The server colors the defect locations on the map and arranges the data in a format that is easy for users to understand visually. Specifically, it generates the map data using a geographic information system (GIS). The input data is the defect data, and the output data is map data that can be displayed visually.

[1743] Step 6:

[1744] The server sends the generated map data to the terminal. The terminal receives this data and displays it on the in-vehicle display. This allows the user to check the current communication status and any malfunctions in real time. The input data is the map data, and the output data is the visual data displayed on the terminal.

[1745] Step 7:

[1746] The user checks the information displayed on the in-vehicle display and considers route changes or other measures as necessary. The device receives the user's instructions and reflects them in the driving system. Specifically, it operates the navigation system to calculate a new route. The input data are visual data and the user's instructions, and the output data is the driving system's new route information.

[1747] 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.

[1748] 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.

[1749] 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.

[1750] 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.

[1751] 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.

[1752] 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.

[1753] 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).

[1754] 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.

[1755] 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."

[1756] 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.

[1757] 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).

[1758] 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.

[1759] 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.

[1760] 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.

[1761] 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.

[1762] 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.

[1763] 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.

[1764] 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.

[1765] 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.

[1766] 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.

[1767] 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.

[1768] The following is further disclosed regarding the above embodiment.

[1769] (Claim 1)

[1770] means for acquiring location information and time information input by a user;

[1771] means for transmitting the location information and time information to a server;

[1772] means for searching a database for a communication log corresponding to the location information and time information;

[1773] means for analyzing the communication log and extracting defective data;

[1774] a means for mapping the extracted data on a map and visually displaying it;

[1775] A system including:

[1776] (Claim 2)

[1777] 10. The system of claim 1, wherein the location information and time information are transmitted over a secure communication channel.

[1778] (Claim 3)

[1779] 2. The system of claim 1, wherein the communication log is data including physical channel utilization, frequency, and communication speed.

[1780] "Example 1"

[1781] (Claim 1)

[1782] means for acquiring location information and time information input by a user;

[1783] means for transmitting the location information and time information to a server over a secure communication channel;

[1784] means for searching a database for a communication log corresponding to the location information and time information;

[1785] means for analyzing the communication log to extract data including a physical channel utilization rate, a frequency, and a communication speed;

[1786] a means for mapping the extracted data on a map and visually displaying it;

[1787] A system including:

[1788] (Claim 2)

[1789] 10. The system of claim 1, comprising a location-based service and an internal clock for obtaining the location and time information.

[1790] (Claim 3)

[1791] 10. The system of claim 1, wherein the communication log uses a software library to analyze data including physical channel utilization, frequency, and communication speed.

[1792] "Application Example 1"

[1793] (Claim 1)

[1794] means for acquiring location information and time information input by a user;

[1795] means for transmitting the location information and time information to a server;

[1796] means for searching a database for a communication log corresponding to the location information and time information;

[1797] means for analyzing the communication log and extracting defective data;

[1798] a means for mapping the extracted data on a map and visually displaying it;

[1799] A means for robots in factories to automatically detect communication problems and analyze and visualize the communication status in real time.

[1800] A system including:

[1801] (Claim 2)

[1802] 10. The system of claim 1, wherein the location information and time information are transmitted over a secure communication channel.

[1803] (Claim 3)

[1804] The system of claim 1, wherein the communication log is data including physical channel utilization rate, frequency, and communication speed, and location information and time information are obtained using sensors and a GPS module installed on the robot.

[1805] "Example 2: Combining Emotion Engines"

[1806] (Claim 1)

[1807] means for acquiring location information and time information input by a user;

[1808] means for acquiring emotion information of a user based on the position information and time information;

[1809] means for transmitting the location information, time information, and emotion information to a server;

[1810] a means for searching a corresponding communication log from a database based on the location information, time information, and emotion information;

[1811] means for analyzing the communication log and extracting defective data;

[1812] a means for mapping the extracted data on a map and visually displaying it;

[1813] A system including:

[1814] (Claim 2)

[1815] 10. The system of claim 1, wherein the location information, time information, and emotion information are transmitted over a secure communication channel.

[1816] (Claim 3)

[1817] 2. The system according to claim 1, wherein the communication log is data including wireless channel utilization rate, frequency, and communication speed.

[1818] "Application example 2 when combining emotion engines"

[1819] (Claim 1)

[1820] means for acquiring location information and time information input by a user;

[1821] means for transmitting the location information, time information, and emotion information to a server;

[1822] a means for searching a database for a communication log corresponding to the location information, time information, and emotion information;

[1823] means for analyzing the communication log and extracting defective data;

[1824] a means for mapping the extracted data on a map and visually displaying it;

[1825] A system including:

[1826] (Claim 2)

[1827] 10. The system of claim 1, wherein the location information, time information, and emotion information are transmitted over a secure communication channel.

[1828] (Claim 3)

[1829] the communication log is data including a physical channel utilization rate, a frequency, and a communication speed;

[1830] 2. The system according to claim 1, wherein the emotion engine acquires emotion information by analyzing the user's voice and facial expressions. [Explanation of symbols]

[1831] 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 acquiring location information and time information input by a user; means for transmitting the location information and time information to a server; means for searching a database for a communication log corresponding to the location information and time information; means for analyzing the communication log and extracting defective data; a means for mapping the extracted data on a map and visually displaying it; A system including:

2. The system of claim 1 , wherein the location information and time information are transmitted over a secure communication channel.

3. 2. The system of claim 1, wherein the communication log includes data on physical channel utilization, frequency, and communication speed.

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