System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting an operation history and a game progress status of a user in real time; means for analyzing the operation history and the game progress status and detecting a timing at which an operation explanation is necessary; means for generating a request for the operation explanation based on the detected timing and transmitting the request to a terminal; and means for receiving the request, preparing a voice guide, and providing the voice guide to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, games have become more multifunctional, and tutorials have become longer, but users want to enjoy the game quickly. Furthermore, long tutorials are difficult for users to remember, and they often need to re-examine operation methods as they continue playing. Furthermore, creating tutorials increases the cost and testing burden of game development. To solve these issues, a system is needed that provides users with the operation instructions they need at the appropriate time. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for collecting a user's operation history and game progress status in real time, a means for analyzing the operation history and game progress status to detect when operation instructions are required, a means for generating an operation instruction request based on the detected timing and sending it to a terminal, and a means for receiving the request, preparing an audio guide, and providing it to the user. The system further includes a means for providing the audio guide through a smart speaker or earphones, making it possible to provide accurate operation instructions to the user in a timely manner. Furthermore, if the operation instruction request is related to how to use a new skill, the system also includes a means for detecting the acquisition of the new skill from the game log, thereby enabling the user to smoothly acquire the new skill and progress through the game.

[0006] "Operation history" refers to a series of operations (keystrokes, mouse movements, button clicks, etc.) performed by the user in the game.

[0007] "Game progress" refers to the progress the user has made in the game, the character's status (stamina, equipment, location information, etc.), and the current game area.

[0008] "Means for collecting information in real time" refers to a system or algorithm for continuously collecting a user's operation history and game progress during gameplay.

[0009] "Means for analyzing and detecting" refers to systems or algorithms that analyze collected operation history and game progress to identify when a user does not understand a particular operation or is experiencing difficulty in a particular area.

[0010] "Request for instruction" refers to information containing specific instruction that is generated based on the detected difficulty of the user.

[0011] "Terminal" refers to a device (such as a smart speaker or earphones) that provides audio guidance to the user.

[0012] "Audio guide" refers to a guide that provides instructions and explanations to the user by voice.

[0013] A "smart speaker" is a device that has a voice assistant function and provides voice commands and guidance.

[0014] "Earphones" refer to small acoustic devices that users wear in their ears to listen to audio guidance.

[0015] "New skills" refers to new abilities or techniques that a character acquires in the game.

[0016] A "game log" refers to data that records a series of events and actions that occur within a game. [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 present invention relates to a system that analyzes user behavior in a game in real time and provides operation instructions at appropriate times to improve the user experience. This system operates in cooperation with a server, a terminal, and a user.

[0039] System configuration

[0040] First, we will explain the system configuration. This system mainly consists of the following elements:

[0041] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. The server detects when operation instructions are required and generates a request for operation instructions.

[0042] 2. Terminal: Receives requests from the server, prepares audio guides, and provides them to the user. The terminal can be a smart speaker or earphones.

[0043] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[0044] Program processing

[0045] The program processing that realizes this is explained in natural language, and the behavior of the server, terminal, and user is described in detail.

[0046] Server Processing

[0047] 1. Data collection: The server collects game logs in real time, specifically recording user operation history (keystrokes, mouse movements, button clicks, etc.) and game progress (progress, character status, current game area).

[0048] 2. Analysis and Detection: The server analyzes the user's progress and operation history based on the collected data, detecting when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area.

[0049] 3. Request generation: The server generates a request for appropriate operation instructions based on the detected timing. For example, it specifies information such as "double jump is required."

[0050] Terminal handling

[0051] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[0052] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. For example, the device tells the user, "Here, press the jump button twice in succession."

[0053] User response

[0054] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[0055] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[0056] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis.

[0057] Specific examples

[0058] Example 1: Performing a double jump

[0059] Let's say a user is having trouble progressing in a particular area.

[0060] 1. Server: Detects that the user has been attempting to jump in the same place for more than 5 minutes and generates a request for a "need for a double jump."

[0061] 2. Device: Receives the request, generates a voice prompt saying "Please press the jump button twice in succession," and conveys this to the user through the smart speaker.

[0062] 3. User: Follow the voice guidance and press the jump button twice in rapid succession to perform a double jump and proceed to the next area.

[0063] Example 2: Using long-range attack skills

[0064] A user acquires a new skill and doesn't know how to use it.

[0065] 1. Server: Detects that the user has acquired a new skill (ranged attack) and generates a request for it.

[0066] 2. Device: Receives the request and generates and provides a voice prompt saying, "Press the right stick to perform a long-range attack."

[0067] 3. User: Follow the voice prompts and press the right stick to attempt a long-range attack and succeed.

[0068] In this way, users can receive real-time instructions and smoothly progress through the game, which greatly improves the user experience and reduces the costs and efforts of game developers.

[0069] The processing flow will be explained below.

[0070] Program processing steps

[0071] Server Processing

[0072] Step 1:

[0073] The server collects game logs in real time.

[0074] Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[0075] Step 2:

[0076] The server analyzes the collected operation history and progress.

[0077] Specifically, it analyzes whether a particular operation has not been successful for a long time or whether the user is stagnating in a particular area.

[0078] Step 3:

[0079] The server detects when an instruction for operation is required.

[0080] Specifically, this applies when a user is repeatedly performing a particular action without success, or when they have difficulty applying a new skill immediately after acquiring it.

[0081] Step 4:

[0082] The server generates a request for operation instructions based on the detection result.

[0083] For example, generate a specific request such as "Explain how to do a double jump."

[0084] Step 5:

[0085] The server transmits the generated request to the terminal.

[0086] Terminal handling

[0087] Step 6:

[0088] The terminal receives a request for operation instructions from the server.

[0089] Step 7:

[0090] The terminal prepares audio guidance based on the received request.

[0091] Specifically, specific instructions such as "Press the jump button twice in succession" are generated as an audio file using voice synthesis technology.

[0092] Step 8:

[0093] The terminal provides the prepared audio guide to the user.

[0094] Instructions are given to the user via voice through a smart speaker or earphones.

[0095] User response

[0096] Step 9:

[0097] The user follows the instructions on the terminal and attempts to perform specific operations.

[0098] For example, try to perform a double jump by pressing the jump button twice in succession.

[0099] Step 10:

[0100] The result of the user's operation is sent to the server again.

[0101] If successful, the data will be recorded for future analysis, if unsuccessful, a more detailed explanation may be provided.

[0102] Example 1: Double jump

[0103] Step 1:

[0104] The user is unable to overcome a particular obstacle during gameplay and becomes stuck.

[0105] Step 2:

[0106] The server detects that the user has clicked the jump button multiple times but without success.

[0107] Step 3:

[0108] The server determines that an explanation of double jumping is required and generates a request.

[0109] Step 4:

[0110] The server sends the request to the terminal.

[0111] Step 5:

[0112] The device receives the request and prepares a voice prompt saying, "Please press the jump button twice in succession."

[0113] Step 6:

[0114] The terminal provides audio guidance to the user.

[0115] Step 7:

[0116] The user follows the audio guidance and presses the jump button twice in succession to successfully perform a double jump.

[0117] Example 2: Using a new skill (long-range attack)

[0118] Step 1:

[0119] A user acquires a new skill.

[0120] Step 2:

[0121] The server detects the acquisition of a new skill (ranged attack).

[0122] Step 3:

[0123] The server determines that "an explanation of how to use long-range attacks is required" and generates a request.

[0124] Step 4:

[0125] The server sends the request to the terminal.

[0126] Step 5:

[0127] The device receives the request and prepares a voice prompt saying, "Press the right stick to perform a long-range attack."

[0128] Step 6:

[0129] The terminal provides audio guidance to the user.

[0130] Step 7:

[0131] Users follow the voice prompts and push the right stick to perform long-range attacks.

[0132] In this way, the user can receive the necessary operating instructions at the appropriate time and progress smoothly through the game.

[0133] Example 1

[0134] 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."

[0135] Current game systems have difficulty providing appropriate operational instructions in real time when a user experiences difficulty with a specific operation or new skill. This can impair the user experience and stall game progress. Furthermore, the increased time required for the user to overcome the difficulty can reduce satisfaction with the game. Therefore, the present invention aims to improve the user experience by monitoring and analyzing the user's operation history and game progress in real time and providing operational instructions at the appropriate time.

[0136] 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.

[0137] In this invention, the server includes means for collecting a user's operation history and game progress status in real time, means for analyzing the operation history and game progress status using a machine learning model to detect when a specific operation has not been attempted for a long time or when the user is experiencing difficulty in a specific area, and means for generating a request for appropriate operation instructions based on the detected timing and sending the request to the terminal. This makes it possible to detect difficulties the user is experiencing while playing the game in real time and provide appropriate operation instructions at that moment.

[0138] "User operation history" is a record of the specific operations performed by the user when playing a game, including keyboard keystrokes, mouse movements, button clicks, and the like.

[0139] "Game progress" refers to information related to the progress of the game, such as the character's current position and status in the game, mission progress, and game area.

[0140] A "machine learning model" is a general term for algorithms that learn patterns and trends based on past data and make predictions and classifications for new data.

[0141] A "request for operation instructions" is a request to generate instructions including specific operation procedures and send them to the terminal when the user is experiencing difficulty in the game.

[0142] "Speech synthesis technology" is a technology that generates voices that mimic human voices based on text data, and is used to create audio guides.

[0143] "Terminal" refers to a device that provides audio guidance to the user, including smart speakers and earphones.

[0144] "Audio guide" refers to instructions provided by voice that guide the user through the operational procedures required in the game, and is intended to aid the user in understanding.

[0145] "New skills" refer to new abilities or techniques that a user acquires in the game and that the user must learn how to use.

[0146] MODE FOR CARRYING OUT THE INVENTION

[0147] This invention relates to a system that collects a user's operation history and game progress in real time and provides necessary operation instructions based on that data. Here, we will explain how to implement this system in detail. This system is mainly composed of three parties: a server, a terminal, and a user.

[0148] Server Processing

[0149] 1. Gathering game logs

[0150] The server collects game logs in real time. Specifically, it uses an API and a database to collect user operation history (keystrokes, mouse movements, button clicks, etc.) and game progress (character status, progress, current game area). This data is necessary to understand the user's in-game behavior.

[0151] 2. Data Analysis

[0152] The server analyzes user behavior based on the collected data, using machine learning models (e.g., clustering and trend analysis algorithms) to detect when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area.

[0153] 3. Request Generation

[0154] The server uses the analysis results to determine when and how the user needs to be instructed on what operations. For example, if the user has been trying to jump in the same place for more than five minutes, the server detects this and generates a request indicating the need for a double jump. This request includes specific instructions and the reasons for them.

[0155] Terminal handling

[0156] 1. Receiving requests and preparing audio guides

[0157] The device (smart speaker or earphones) receives a request for operation instructions from the server. It uses speech synthesis technology (e.g., Google Text-to-Speech or Amazon Polly) to generate audio guidance based on the request. This audio guidance includes specific operation procedures.

[0158] 2. Provision of audio guides

[0159] The device provides the generated voice guidance to the user. For example, it transmits instructions such as "Please press the jump button twice in succession" in real time through earphones. This allows the user to follow the voice guidance and perform the appropriate operation.

[0160] User response

[0161] 1. Gameplay

[0162] The user plays the game as usual, but if they encounter a difficult situation or don't know how to perform a particular operation, they try it out on the spot.

[0163] 2. Audio guide execution

[0164] The user attempts to perform specific operations according to the voice guidance provided by the device. For example, by following the instruction to "press the jump button twice in succession," the user can successfully perform a double jump.

[0165] 3. Providing Feedback

[0166] If the user follows the instructions and the operation is successful, the information is sent back to the server. For example, a log stating "double jump successful" is sent to the server. This feedback will be used for future data analysis and contribute to improving the accuracy of the system.

[0167] Specific examples

[0168] Example 1: Performing a double jump

[0169] Let's assume that the user is having trouble progressing in a particular area.

[0170] 1. The server detects that the user has been attempting to jump in the same location for more than 5 minutes and generates a request for a "need for a double jump."

[0171] 2. The device receives the request, generates a voice prompt saying "Please press the jump button twice in succession," and conveys this to the user through the smart speaker.

[0172] 3. The user follows the audio guidance and presses the jump button twice in succession to perform a double jump and proceed to the next area.

[0173] Example 2: Using long-range attack skills

[0174] Suppose a user acquires a new skill and doesn't know how to use it.

[0175] 1. The server detects that the user has acquired a new skill (ranged attack) and generates a request for it.

[0176] 2. The device receives the request and generates and provides a voice prompt saying, "Press the right stick to perform a long-range attack."

[0177] 3. Following the voice guidance, the user presses the right stick to attempt a long-range attack and succeeds.

[0178] Specific examples of prompts

[0179] Below are some example prompts to input to the generative AI model for the system:

[0180] Please describe this system. The server collects game logs in real time and analyzes the user's operation history and game progress. At specific times, it generates and sends a request for audio guidance to the device. The device prepares audio guidance based on the request and provides it to the user. For example, if the user experiences difficulty, the server detects that situation and generates guidance instructing the user to press the jump button twice in succession.

[0181] As described above, implementing the present invention requires the ability to collect and analyze the user's operation history and game progress in real time, as well as the ability to provide audio guidance at appropriate times, which enables real-time operation explanations and significantly improves the user experience.

[0182] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0183] Step 1:

[0184] Gathering game logs

[0185] The server collects the user's operation history and game progress in real time. During this process, the game inputs operation data (keystrokes, mouse movements, button clicks, etc.) from the game. This data is collected via API and database and stored on the server. For example, the number of times the jump button was pressed and the character's current position are recorded. This makes it possible to monitor what operations the user is performing within the game.

[0186] Step 2:

[0187] Data analysis

[0188] The server analyzes the collected operation history and game progress using a machine learning model. The game logs collected in step 1 are used as input for this process. The analysis uses clustering algorithms and trend analysis algorithms to detect when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area. For example, a pattern such as "the user has been trying to jump in the same place for five minutes without success" can be detected. This makes it possible to identify when the user is experiencing difficulty.

[0189] Step 3:

[0190] Request Generation

[0191] Based on the analysis results from step 2, the server detects when instructions are needed and generates a request containing specific instructions. The input to this process is the information obtained through data analysis. The output is a request containing specific operating procedures and the reasons for them. For example, a request stating "double jump required" is created. This prepares the device to provide appropriate operating instructions to the user.

[0192] Step 4:

[0193] Receiving requests and preparing audio guides

[0194] The device receives a request for operation instructions from the server and prepares audio guidance based on the request. The input for this process is the request sent from the server. The device uses speech synthesis technology (e.g., Google Text-to-Speech or Amazon Polly) to generate audio guidance based on the request. The output is an audio guidance message. For example, an audio guidance message such as "Press the jump button twice in succession" is created. This completes the guidance for the user to perform the appropriate operation.

[0195] Step 5:

[0196] Audio guide provided

[0197] The device provides the generated audio guide to the user. The input of this process is the audio guide generated in step 4. The device provides the audio guide to the user through a smart speaker or earphones. The output includes the audio guide received by the user. For example, an instruction such as "Please press the jump button twice in succession" may be conveyed to the user through the earphones. This allows the user to receive instructions on how to operate the device in real time.

[0198] Step 6:

[0199] Execute audio guide

[0200] The user attempts to perform a specific operation according to the voice guidance provided by the device. The input to this process is the voice guidance provided by the device. Based on the instructions, the user performs a specific operation (for example, pressing the jump button twice in succession). The output includes the result of whether the user succeeded or failed in the operation. This allows the user to learn difficult operations or how to use new skills.

[0201] Step 7:

[0202] Providing Feedback

[0203] If the user successfully performs the instructed operation, that information is sent back to the server. The input to this process is the result of the user's operation. For example, a log stating "double jump successful" is sent to the server. The output is this feedback information, which is recorded on the server. Based on this feedback, the server can improve the accuracy of future analysis. This continuously improves the efficiency of the entire system.

[0204] (Application example 1)

[0205] 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."

[0206] Mistakes made by workers in factories and incorrect work procedures can lead to reduced production efficiency and safety risks. Furthermore, it is difficult to learn new operating procedures and how to use machines in real time, which causes further problems. Traditional textbooks and manuals do not allow for immediate response, and it takes time for workers to learn the correct operating methods.

[0207] 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.

[0208] In this invention, the server includes means for collecting the user's operation history and status in real time, means for analyzing the operation history and status and detecting the timing when operation instructions are required, means for generating an operation instruction request based on the detected timing and sending it to the terminal, and means for receiving the request, preparing visual and audio guides, and providing them to the user. This makes it possible to correct operational errors and errors in work procedures by workers in the factory in real time, and to progress work efficiently and safely.

[0209] An "operation history" is a record of a series of operations and actions performed by a user.

[0210] The "situation" is the totality of the environment in which the user is currently placed and the work that is currently in progress.

[0211] "Collecting in real time" means collecting operation history and status immediately without delay.

[0212] "Analysis" is the process of analyzing collected data to find specific patterns and trends.

[0213] "Detection" refers to the identification of a particular condition or event from the results of an analysis.

[0214] "Operation instructions" are specific operating procedures and methods provided to the user.

[0215] "Generating a request" means creating a necessary operation instruction and creating a request to provide it.

[0216] A "terminal" is a device or apparatus that receives a request for operation instructions and provides visual and audio guidance to the user.

[0217] A "visual guide" is a means of conveying operating procedures and information to users graphically.

[0218] "Audio guide" is a means of conveying operational procedures and information to the user by voice.

[0219] "User" refers to the worker or operator who uses the system and receives instructions on how to operate it.

[0220] This invention is a system for correcting worker errors and errors in work procedures in real time in a factory, ensuring efficient and safe work progress. This system mainly operates in cooperation with three parties: a server, a terminal, and a user.

[0221] System configuration

[0222] The system mainly consists of the following elements:

[0223] 1. Server: Collects the user's operation history and status in real time and detects when operation instructions are required. The server generates a request for operation instructions and sends it to the device.

[0224] 2. Terminal: Receives requests from the server, prepares visual and audio guides, and provides them to the user. The terminal can be a smart glass or other visual and audio output device.

[0225] 3. User: A worker who performs work in a factory. The user follows visual and audio guidance to carry out the correct work procedures.

[0226] Program processing

[0227] Server Processing

[0228] The server does the following:

[0229] 1. Data collection: Collect worker movements in real time from cameras and sensors in the factory (e.g., Azure Kinect, Microsoft Azure IoT Hub), including worker behavior data and the status of the work being performed.

[0230] 2. Analysis and detection: The collected data is analyzed using Google Cloud Dataflow and Azure Machine Learning to detect whether specific work procedures are being performed correctly based on the user's operation history and situation.

[0231] 3. Request generation: If the correct operating procedure is not performed, a request for operating instructions is generated based on the timing and sent to the terminal.

[0232] Terminal handling

[0233] The terminal does the following:

[0234] 1. Request reception and preparation: Smart glasses (e.g., Google Glass, Epson Moverio) receive a request for operation instructions from the server and prepare visual and audio guidance. Amazon Polly is used for speech synthesis.

[0235] 2. Providing visual and audio guidance: The device displays visual guidance on the screen and provides audio guidance, which helps users understand specific work procedures.

[0236] User response

[0237] The user takes the following actions:

[0238] 1. Task execution: The user follows the visual and audio guidance provided by the smart glasses to perform the correct task steps.

[0239] 2. Providing feedback: The progress of the work is reported to the server, and information about successes and failures is used again for data collection and analysis.

[0240] Specific examples

[0241] For example:

[0242] 1. Palletizing Guide:

[0243] The server detects incorrect movements when workers lift loads.

[0244] The server generates an instruction for operation such as "Next, carefully lift the luggage and place it in the designated location" and sends it to the terminal.

[0245] The device provides audio guidance along with visual guidance.

[0246] The user follows the guide and places the luggage in the correct position.

[0247] 2. Learning how to operate a new machine:

[0248] The server detects mistakes made by workers as they try out new ways of operating machines.

[0249] The server generates operating instructions such as "To operate this machine, first press the red button and then pull the lever" and sends them to the terminal.

[0250] The device provides visual and audio guidance through smart glasses.

[0251] Users follow the guide to learn the correct operating procedures.

[0252] As a result, it is possible to reduce work errors in the factory and perform work safely and efficiently.

[0253] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0254] Step 1:

[0255] The server collects worker movement data in real time using cameras and sensors (e.g., Azure Kinect, Microsoft Azure IoT Hub) in the factory. The input is raw data from the cameras and sensors, and the output is a log of worker movement. Specifically, it records video data captured by cameras and movement data acquired by sensors.

[0256] Step 2:

[0257] The server analyzes the collected operation data using a data analysis platform (e.g., Google Cloud Dataflow, Azure Machine Learning). The input here is the operation log, and the output is the analysis result, i.e., a determination of whether a specific work procedure was performed correctly. Specifically, an AI model is used to analyze operation patterns and detect mistakes or incorrect operations.

[0258] Step 3:

[0259] The server generates a request for operation instructions based on the analysis results and sends it to the terminal. The input is the analysis results, and the output is an operation instruction request. Specifically, it generates text information about appropriate operation procedures and actions that need to be corrected.

[0260] Step 4:

[0261] The device receives the operation instruction request sent from the server and prepares the audio guide using speech synthesis software (e.g., Amazon Polly). The input is the operation instruction request, and the output is the audio guide and visual guide. Specifically, the device converts the request into text and prepares to display it on the screen as visual information.

[0262] Step 5:

[0263] The terminal provides the prepared visual and audio guide to the user. The input is the audio and visual guide data, and the output is the display and audio output to convey it to the user. Specifically, the smart glasses display text and illustrated procedures, as well as audio instructions, so that the worker can receive them.

[0264] Step 6:

[0265] The user performs specific tasks according to the visual and audio guidance provided by the terminal. The input is the visual and audio guidance, and the output is the accurate execution of the work procedure. Specifically, the user performs the task according to the guidance and checks the results.

[0266] Step 7:

[0267] The results of the user's work are fed back to the server. The input is the work result, and the output is feedback data to the server. Specifically, the success or failure of the work and its details are sent to the server to help with future improvements.

[0268] 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.

[0269] This invention relates to a system that analyzes the user's behavior and emotional state in real time in a game and provides operation instructions at the appropriate time to improve the user experience. This system operates in cooperation with the server, the terminal, and the user.

[0270] System configuration

[0271] First, we will explain the system configuration. This system mainly consists of the following elements:

[0272] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. It also includes an emotion engine to recognize the user's emotional state. The server detects when operation instructions are required and generates an instruction request. The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data.

[0273] 2. Device: Receives requests from the server, prepares audio guides, and provides them to the user. The device can be a smart speaker or earphones. If the user is in a negative emotional state, the device adjusts the content and tone of the audio guide.

[0274] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[0275] Program processing

[0276] The program processing that realizes this is explained in natural language, and the behavior of the server, terminal, and user is described in detail.

[0277] Server Processing

[0278] 1. Data collection: The server collects game logs in real time. Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[0279] 2. Emotion Recognition: The server recognizes the user's emotional state using an emotion engine, which uses facial expression analysis, voice analysis, or vital sign data of the user.

[0280] 3. Analysis and Detection: The server analyzes the collected operation history and progress as well as the recognized emotion data to detect when a specific operation has not been performed successfully for a long time or when the user is stagnating in a particular area.

[0281] 4. Request Generation: The server generates a request for operation instructions based on the detection results and the emotional state. For example, it generates a specific request such as "double jump required."

[0282] Terminal handling

[0283] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[0284] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. If the user's emotional state is negative, the content and tone of the audio guidance will be adjusted.

[0285] User response

[0286] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[0287] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[0288] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis, and if unsuccessful, a more detailed explanation may be provided.

[0289] Specific examples

[0290] Example 1: Performing a double jump

[0291] Let's say a user is having trouble progressing in a particular area.

[0292] 1. Server: Detects when a user has been trying to jump in the same place for more than five minutes without success. The emotion engine also analyzes the user's facial expressions and recognizes frustration.

[0293] 2. Server: Sends a request for instructions, "Explain how to double jump," and information that "the user is frustrated" to the device.

[0294] 3. Device: Receive the request and prepare a voice prompt saying "Please press the jump button twice in succession," and provide it in a gentle tone depending on the user's emotional state.

[0295] 4. User: Follow the audio guide and press the jump button twice in succession to perform a double jump and proceed to the next area.

[0296] Example 2: Using a new skill (long-range attack)

[0297] A user acquires a new skill and doesn't know how to use it.

[0298] 1. Server: Detects when a user acquires a new skill (long-range attack). Also, the emotion engine recognizes the emotion of anxiety from the user's vital sign data.

[0299] 2. Server: Sends a request for operation instructions, "Explain how to use long-range attacks," and information about "the user's anxiety," to the device.

[0300] 3. Device: Receive the request and prepare a voice prompt saying "Press the right stick to perform a ranged attack" in a reassuring tone depending on the emotional state.

[0301] 4. User: Follow the voice prompts and press the right stick to perform a long-range attack.

[0302] In this way, users can receive real-time instructions and emotional support to smoothly progress through the game, which greatly improves the user experience and reduces the costs and efforts of game developers.

[0303] The processing flow will be explained below.

[0304] Program processing steps

[0305] Server Processing

[0306] Step 1:

[0307] The server collects game logs in real time.

[0308] Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[0309] Step 2:

[0310] The server uses an emotion engine to recognize the user's emotional state in real time.

[0311] The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data of the user.

[0312] Step 3:

[0313] The server analyzes the collected operation history and progress as well as the recognized emotion data.

[0314] Specifically, it checks if a particular operation has not been successful for a long time or if the user is stuck in a particular area.

[0315] Step 4:

[0316] The server detects when an instruction for operation is required.

[0317] For example, if the user has been trying to jump in the same place for more than five minutes without success, it is determined that an instruction on how to jump is necessary.

[0318] Step 5:

[0319] The server generates a request for operation instructions based on the detection result and the emotional state.

[0320] Specifically, information such as "a double jump is required" or "the user is feeling frustrated" is generated as a request.

[0321] Step 6:

[0322] The server transmits the generated request to the terminal.

[0323] Terminal handling

[0324] Step 7:

[0325] The terminal receives a request for operation instructions from the server.

[0326] Step 8:

[0327] The terminal prepares audio guidance based on the received request.

[0328] Specifically, instructions such as "Press the jump button twice in succession" are converted into voice using speech synthesis technology.

[0329] Step 9:

[0330] The terminal adjusts the tone of the audio guide according to the user's emotional state.

[0331] For example, if the user is feeling frustrated, prepare a voice prompt with a gentle tone.

[0332] Step 10:

[0333] The device provides the prepared audio guide to the user through a smart speaker or earphones.

[0334] User response

[0335] Step 11:

[0336] The user follows the voice guidance provided by the terminal and attempts to perform specific operations.

[0337] For example, try to perform a double jump by pressing the jump button twice in succession.

[0338] Step 12:

[0339] The result of the user's operation is sent to the server again.

[0340] If successful, the information will be recorded for future analysis, if unsuccessful a more detailed explanation may be provided.

[0341] Example 1: Double jump

[0342] Step 1:

[0343] The user is unable to overcome a particular obstacle during gameplay and becomes stuck.

[0344] Step 2:

[0345] The server detects that the user has clicked the jump button multiple times but without success.

[0346] Step 3:

[0347] The server uses an emotion engine to analyze the user's facial expressions and recognize the emotion of frustration.

[0348] Step 4:

[0349] The server sends the information "explain how to double jump" and "the user is feeling frustrated" as a request to the terminal.

[0350] Step 5:

[0351] The device receives the request and prepares a voice prompt saying, "Please press the jump button twice in succession."

[0352] Step 6:

[0353] The device recognizes that the user is frustrated and provides voice guidance in a gentle tone.

[0354] Step 7:

[0355] The user follows the audio guidance and presses the jump button twice in succession to perform a double jump and proceed to the next area.

[0356] Example 2: Using a new skill (long-range attack)

[0357] Step 1:

[0358] A user acquires a new skill.

[0359] Step 2:

[0360] The server detects the acquisition of a new skill (ranged attack).

[0361] Step 3:

[0362] The server uses an emotion engine to analyze the user's vital sign data and recognize emotions of anxiety.

[0363] Step 4:

[0364] The server sends the information "explain how to use long-range attacks" and "the user feels anxious" as a request to the terminal.

[0365] Step 5:

[0366] The device receives the request and prepares a voice prompt saying, "Press the right stick to perform a long-range attack."

[0367] Step 6:

[0368] The terminal recognizes that the user is feeling anxious and provides audio guidance in a reassuring tone.

[0369] Step 7:

[0370] Users follow the voice prompts and push the right stick to perform long-range attacks.

[0371] Example 2

[0372] 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."

[0373] Conventional game systems struggle to provide timely explanations of in-game operations that can easily confuse users or how to use new skills. Furthermore, when a user becomes stuck on a particular operation or area, this can be due to emotional factors, but the system lacks the ability to detect this in real time and take appropriate action. Furthermore, explanations that are not tailored to the user's emotional state can increase anxiety and frustration, detracting from the game experience.

[0374] 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.

[0375] In this invention, the server includes means for collecting a user's operation history and game progress status in real time, means for analyzing the operation history and game progress status and detecting timing when operation instructions are required, means for generating an operation instruction request based on the detected timing and sending it to the terminal, means for recognizing the user's emotional state using an emotion engine, and means for adjusting the content and tone of audio guidance based on the emotional state. This allows the user to receive operation instructions in the game at appropriate timing according to their emotions, improving the game experience.

[0376] The "user operation history" is a record of a series of operations performed by the user during the game. Specifically, this includes the number of clicks of the jump button, the direction of movement, attack actions, and so on.

[0377] "Game progress" refers to information about the progress of the game, such as the character's position in the game, progress, and acquired items.

[0378] The "emotion engine" is an analysis engine for recognizing the user's emotional state. Specifically, it analyzes facial expressions, voice, and vital sign data.

[0379] An "operation instruction request" is a request generated by a server to instruct a user on how to perform a particular operation.

[0380] "Audio guide" refers to audio instructions and explanations provided to the user by a device. The content and tone may be adjusted to make the instructions easier for the user to understand.

[0381] A "terminal" is a device that receives a request for operation instructions from the server, prepares audio guidance, and provides it to the user. This includes smart speakers and earphones.

[0382] "Emotional state" refers to the user's current feelings, including frustration, anxiety, joy, etc.

[0383] This invention relates to a system that analyzes the user's behavior and emotional state in real time in a game and provides operation instructions at the appropriate time to improve the user experience. This system operates in cooperation with the server, the terminal, and the user.

[0384] System configuration

[0385] The system mainly consists of the following elements:

[0386] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. It also includes an emotion engine to recognize the user's emotional state. The server detects when operation instructions are required and generates an instruction request. The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data.

[0387] 2. Device: Receives requests from the server, prepares audio guides, and provides them to the user. The device can be a smart speaker or earphones. If the user is in a negative emotional state, the device adjusts the content and tone of the audio guide.

[0388] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[0389] Server Processing

[0390] 1. Data collection: The server collects game logs in real time. Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[0391] 2. Emotion Recognition: The server uses an emotion engine to recognize the user's emotional state, which can be achieved by analyzing the user's facial expressions, voice, or vital sign data.

[0392] 3. Analysis and Detection: The server analyzes the collected operation history and progress as well as the recognized emotion data to detect when a specific operation has not been performed successfully for a long time or when the user is stagnating in a particular area.

[0393] 4. Request Generation: The server generates a request for operation instructions based on the detection results and the emotional state. For example, it generates a specific request such as "double jump required."

[0394] Terminal handling

[0395] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[0396] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. If the user's emotional state is negative, the content and tone of the audio guidance will be adjusted.

[0397] User response

[0398] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[0399] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[0400] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis, and if unsuccessful, a more detailed explanation may be provided.

[0401] Specific examples

[0402] Example 1: Performing a double jump

[0403] Let's say a user is having trouble progressing in a particular area.

[0404] 1. Server: Detects when a user has been trying to jump in the same place for more than five minutes without success. The emotion engine also analyzes the user's facial expressions and recognizes frustration.

[0405] 2. Server: Sends a request for instructions, "Explain how to double jump," and information that "the user is frustrated" to the device.

[0406] 3. Device: Receive the request and prepare a voice prompt saying "Please press the jump button twice in succession," and provide it in a gentle tone depending on the user's emotional state.

[0407] 4. User: Follow the audio guide and press the jump button twice in succession to perform a double jump and proceed to the next area.

[0408] Example 2: Using a new skill (long-range attack)

[0409] A user acquires a new skill and doesn't know how to use it.

[0410] 1. Server: Detects when a user acquires a new skill (long-range attack). Also, the emotion engine recognizes the emotion of anxiety from the user's vital sign data.

[0411] 2. Server: Sends a request for operation instructions, "Explain how to use long-range attacks," and information about "the user's anxiety," to the device.

[0412] 3. Device: Receive the request and prepare a voice prompt saying "Press the right stick to perform a ranged attack" in a reassuring tone depending on the emotional state.

[0413] 4. User: Follow the voice prompts and press the right stick to perform a long-range attack.

[0414] In this way, users can receive real-time instructions and support tailored to their emotional state, allowing them to progress smoothly through the game, significantly improving the user experience and reducing support costs for game developers.

[0415] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0416] Step 1: Data collection

[0417] The server collects game logs in real time. As input, it receives the user's operation history (number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.). The server records this data and accumulates it in a data store for subsequent analysis. Specific operations include receiving and saving log data.

[0418] Step 2: Recognize emotions

[0419] The server uses an emotion engine to recognize the user's emotional state. As input, it receives the user's facial expression data, voice data, and vital sign data. The emotion engine analyzes these data and identifies the user's emotional state (frustration, anxiety, joy, etc.). As output, it generates recognized emotion data, which is passed to the next analysis step. Specifically, it performs data analysis using a face recognition module and a voice analysis module.

[0420] Step 3: Analysis and detection

[0421] The server integrates and analyzes the collected operation history, game progress, and emotional data. It receives the above operation history, game progress, and emotional data as input. It integrates the data and detects when a specific operation has not been successful for a long time or when the user is stuck in a specific area. It generates problem identification results (e.g., the user is having difficulty jumping) as output. Specific operations include problem detection using database queries and machine learning algorithms.

[0422] Step 4: Request Generation

[0423] The server generates a request for operation instructions based on the detection results and the emotional state. As input, it receives the detected problem and emotional data. It generates a specific request, such as "double jump required" or "the user is feeling frustrated." As output, it sends the generated request to the terminal. As a specific operation, it creates a specific instruction sentence using a text generation engine and sends the request to the terminal using a communication module.

[0424] Step 5: Receiving and preparing the request

[0425] The device receives a request for operation instructions from the server. As input, it receives the request data sent from the server. Based on that content, it prepares audio guidance. It uses speech synthesis technology to convert the text instructions into speech. It prepares the generated audio data as output. Specifically, it calls a speech synthesis API to generate the audio data.

[0426] Step 6: Provide audio guides

[0427] The terminal provides audio guidance to the user through a smart speaker or earphones. As input, it receives prepared audio data. The content and tone of the audio guidance are adjusted according to the user's emotional state. As output, it provides specific audio instructions to the user. As a specific operation, it uses an audio playback module to play the audio guidance to the user.

[0428] Step 7: Gameplay

[0429] The user plays the game as usual. As input, they receive audio guidance provided by the device. If they are unsure of how to operate the device, they try and error on the spot. As output, a new operation history and game progress status are generated. As a specific operation, they operate the game controller and perform actions in the game.

[0430] Step 8: Receive and follow the audio guide

[0431] The user attempts specific operations according to the voice guidance provided by the device. As input, the user receives the instructions from the voice guidance. For example, the user attempts a double jump by pressing the jump button twice in succession. As output, a history of successful operations is generated. As a specific action, the user operates the game controller as instructed.

[0432] Step 9: Provide feedback

[0433] If the user successfully performs an operation, that information is sent to the server. As input, it receives information about whether the operation was successful or unsuccessful. The server analyzes this feedback information and checks whether the operation was performed correctly. As output, it generates a request indicating success or if further explanation is required. Specifically, when the operation is successful, it obtains satisfaction data from the vital sign data and sends it to the server.

[0434] (Application example 2)

[0435] 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."

[0436] Current security monitoring systems lack the ability to analyze users' real-time behavior and emotional state and provide appropriate responses. Furthermore, there is no system that can immediately guide users to appropriate measures when they feel stressed or anxious, making it difficult to provide efficient responses to ensure users' safety. This increases the risk of users being exposed to unstable situations.

[0437] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting a user's operation history and progress status in real time, means for analyzing the operation history and progress status and detecting a timing when an explanation is needed, means for generating an explanation request based on the detected timing and transmitting it to the terminal, means for receiving the request, preparing audio guidance, and providing it to the user, means for analyzing the user's behavior and emotional state, means for detecting a situation in which the user feels anxious or stressed, and generating a request for an appropriate response method, and means for collecting user location information and video data in real time and analyzing the security situation. This makes it possible to quickly provide an appropriate response method when the user feels anxious or stressed.

[0438] An "operation history" is a record of specific actions and operations performed by a user.

[0439] "Progress" is a record of the status that indicates how far a task or process has progressed.

[0440] The "timing when an explanation is required" refers to a time or situation when a user does not understand a particular operation or action and an explanation is required.

[0441] "Request" refers to a request for a specific operation or description of an action.

[0442] A "terminal" is a device that connects a server and a user and provides information such as audio guides.

[0443] "Audio guide" provides the user with audio instructions on specific operations and actions.

[0444] "Behavior" refers to a specific movement or activity taken by a user.

[0445] "Emotional state" indicates the type and strength of the user's emotion.

[0446] An "anxious or stressful situation" is a specific situation or environment in which a user feels psychological anxiety or tension.

[0447] "Appropriate response method" refers to instructions for the most appropriate procedure or action depending on the user's situation and emotions.

[0448] "Location information" is data that indicates the user's current geographical location.

[0449] "Video Data" refers to image or video data collected by a camera or other image capture device.

[0450] "Security situation" refers to the state of the environment or situation regarding safety.

[0451] This invention relates to a system that analyzes a user's operation history and emotional state in real time to implement a security monitoring system, and provides appropriate responses as audio guidance when the user feels anxious or stressed. This system operates in cooperation with a server, a terminal, and a user.

[0452] System configuration

[0453] The system mainly consists of the following components:

[0454] 1. Server: Collects and analyzes the user's operation history and progress in real time. It also has an emotion engine and recognizes the user's emotional state (specifically, anxiety or stress). It also analyzes security-related situations and generates requests for appropriate responses. The emotion engine and analysis tools used are Google Cloud's "AutoML Vision" and "AutoML Natural Language."

[0455] 2. Terminal: Receives requests from the server, prepares audio guides, and provides them to the user. Using speech synthesis technology, it converts instructions on the appropriate response method into speech. Google Cloud Text-to-Speech is used as the speech synthesis technology.

[0456] 3. User: Uses a device such as a smartphone or earphones to perform normal operations and actions. If the user feels anxious or stressed, they follow the voice guidance provided by the device to take appropriate measures. The voice guidance is provided in a reassuring tone to help the user take safe actions.

[0457] Program implementation steps

[0458] The server collects location information, camera footage, and microphone audio from the smartphone in real time. The emotion engine recognizes and analyzes the user's emotional state from the camera footage and microphone audio. It detects situations in which the user feels anxious or stressed and generates a request for how to respond (for example, directions to the nearest police station or directions to a safe route). The generated request is sent to the device, which uses speech synthesis technology to convert the instructions into voice and provide it to the user.

[0459] Specific examples

[0460] Example 1: Presence of a suspicious person

[0461] 1. Server: The user finds a suspicious person and analyzes emotions of fear and anxiety from camera footage and microphone audio.

[0462] 2. Server: Detects situations where the user is feeling anxious and generates a request to "show the location of the nearest police box."

[0463] 3. Device: Receives the request and prepares and provides an audio guide saying, "Don't worry, the nearest police box is located at XX. Head there immediately."

[0464] 4. User: Follow the audio guide and head immediately to the designated police box.

[0465] Example 2: Staying in a dark place late at night

[0466] 1. Server: Detects anxious facial expressions and voice when the user is in a dark place late at night.

[0467] 2. Server: Detects that the user is feeling anxious and needs guidance on a safe route, and generates the corresponding request.

[0468] 3. Terminal: Receives requests and provides voice guidance on safe routes.

[0469] 4. User: Follow the voice guidance to find a safe route and return home safely.

[0470] Example prompts to input to the generative AI model

[0471] "You are developing a smartphone application that analyzes the user's emotions from camera footage and audio data, and provides appropriate guidance on how to respond when the user feels anxious or stressed. Please generate the following audio guidance."

[0472] This system allows users to receive real-time guidance on appropriate response methods, enabling them to respond quickly and accurately to security risks.

[0473] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0474] Step 1: Data collection

[0475] The server collects location information, camera footage, and microphone audio from the smartphone in real time. These data are the basis for analyzing the user's behavior and emotional state. The input is location information, camera footage, and microphone audio, which are sent to the server. The output is that these data are stored on the server.

[0476] Step 2: Recognize emotions

[0477] The server sends the collected camera footage and microphone audio to the emotion engine to recognize the user's emotional state. Specifically, it uses AutoML Vision and AutoML Natural Language to analyze facial expressions and tone of voice. The input is the collected video and audio data, and the output is a judgment of the user's emotional state (e.g., anxiety, stress, relief, etc.).

[0478] Step 3: Detect security conditions

[0479] The server analyzes whether the user is in a dangerous situation (e.g., the presence of a suspicious person, being in a dark place) based on location information and emotional state data. Specifically, it detects this by comparing the current location with information on pre-defined safe and dangerous areas. The input is the location information and the result of the emotional state determination, and the output is the result of the determination of whether the situation is dangerous or safe.

[0480] Step 4: Generate a response request

[0481] If the server determines that the user is in a dangerous situation, it generates a request for an appropriate response (e.g., information about a nearby police station or a safe route). The content of the request is determined based on the user's current location information and the dangerous situation. The input is the location information and the result of the dangerous situation determination, and the output is a request for an appropriate response.

[0482] Step 5: Submit your request and prepare your audio guide

[0483] The device receives the response request sent from the server and prepares the audio guide. It converts the request into audio using Google Cloud Text-to-Speech. The input is the response request, and the output is the audio guide data.

[0484] Step 6: Provide audio guides

[0485] The device provides the audio guide to the user through a smartphone or earphone. If the user feels anxious, the audio guide is provided in a reassuring tone. The input is the audio guide data, and the output is the provision of the audio guide to the user.

[0486] Step 7: User Behavior

[0487] The user follows the voice guidance provided by the device and takes appropriate action. For example, heading to the nearest police station or following a safe route. The user's actions are fed back to the server and used for future analysis. The input is the content of the voice guidance, and the output is the user's specific actions.

[0488] 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.

[0489] 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.

[0490] 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.

[0491] [Second embodiment]

[0492] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0493] 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.

[0494] 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).

[0495] 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.

[0496] 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.

[0497] 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).

[0498] 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.

[0499] 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.

[0500] 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.

[0501] 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.

[0502] 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.

[0503] 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."

[0504] The present invention relates to a system that analyzes user behavior in a game in real time and provides operation instructions at appropriate times to improve the user experience. This system operates in cooperation with a server, a terminal, and a user.

[0505] System configuration

[0506] First, we will explain the system configuration. This system mainly consists of the following elements:

[0507] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. The server detects when operation instructions are required and generates a request for operation instructions.

[0508] 2. Terminal: Receives requests from the server, prepares audio guides, and provides them to the user. The terminal can be a smart speaker or earphones.

[0509] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[0510] Program processing

[0511] The program processing that realizes this is explained in natural language, and the behavior of the server, terminal, and user is described in detail.

[0512] Server Processing

[0513] 1. Data collection: The server collects game logs in real time, specifically recording user operation history (keystrokes, mouse movements, button clicks, etc.) and game progress (progress, character status, current game area).

[0514] 2. Analysis and Detection: The server analyzes the user's progress and operation history based on the collected data, detecting when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area.

[0515] 3. Request generation: The server generates a request for appropriate operation instructions based on the detected timing. For example, it specifies information such as "double jump is required."

[0516] Terminal handling

[0517] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[0518] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. For example, the device tells the user, "Here, press the jump button twice in succession."

[0519] User response

[0520] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[0521] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[0522] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis.

[0523] Specific examples

[0524] Example 1: Performing a double jump

[0525] Let's say a user is having trouble progressing in a particular area.

[0526] 1. Server: Detects that the user has been attempting to jump in the same place for more than 5 minutes and generates a request for a "need for a double jump."

[0527] 2. Device: Receives the request, generates a voice prompt saying "Please press the jump button twice in succession," and conveys this to the user through the smart speaker.

[0528] 3. User: Follow the voice guidance and press the jump button twice in rapid succession to perform a double jump and proceed to the next area.

[0529] Example 2: Using long-range attack skills

[0530] A user acquires a new skill and doesn't know how to use it.

[0531] 1. Server: Detects that the user has acquired a new skill (ranged attack) and generates a request for it.

[0532] 2. Device: Receives the request and generates and provides a voice prompt saying, "Press the right stick to perform a long-range attack."

[0533] 3. User: Follow the voice prompts and press the right stick to attempt a long-range attack and succeed.

[0534] In this way, users can receive real-time instructions and smoothly progress through the game, which greatly improves the user experience and reduces the costs and efforts of game developers.

[0535] The processing flow will be explained below.

[0536] Program processing steps

[0537] Server Processing

[0538] Step 1:

[0539] The server collects game logs in real time.

[0540] Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[0541] Step 2:

[0542] The server analyzes the collected operation history and progress.

[0543] Specifically, it analyzes whether a particular operation has not been successful for a long time or whether the user is stagnating in a particular area.

[0544] Step 3:

[0545] The server detects when an instruction for operation is required.

[0546] Specifically, this applies when a user is repeatedly performing a particular action without success, or when they have difficulty applying a new skill immediately after acquiring it.

[0547] Step 4:

[0548] The server generates a request for operation instructions based on the detection result.

[0549] For example, generate a specific request such as "Explain how to do a double jump."

[0550] Step 5:

[0551] The server transmits the generated request to the terminal.

[0552] Terminal handling

[0553] Step 6:

[0554] The terminal receives a request for operation instructions from the server.

[0555] Step 7:

[0556] The terminal prepares audio guidance based on the received request.

[0557] Specifically, specific instructions such as "Press the jump button twice in succession" are generated as an audio file using voice synthesis technology.

[0558] Step 8:

[0559] The terminal provides the prepared audio guide to the user.

[0560] Instructions are given to the user via voice through a smart speaker or earphones.

[0561] User response

[0562] Step 9:

[0563] The user follows the instructions on the terminal and attempts to perform specific operations.

[0564] For example, try to perform a double jump by pressing the jump button twice in succession.

[0565] Step 10:

[0566] The result of the user's operation is sent to the server again.

[0567] If successful, the data will be recorded for future analysis, if unsuccessful, a more detailed explanation may be provided.

[0568] Example 1: Double jump

[0569] Step 1:

[0570] The user is unable to overcome a particular obstacle during gameplay and becomes stuck.

[0571] Step 2:

[0572] The server detects that the user has clicked the jump button multiple times but without success.

[0573] Step 3:

[0574] The server determines that an explanation of double jumping is required and generates a request.

[0575] Step 4:

[0576] The server sends the request to the terminal.

[0577] Step 5:

[0578] The device receives the request and prepares a voice prompt saying, "Please press the jump button twice in succession."

[0579] Step 6:

[0580] The terminal provides audio guidance to the user.

[0581] Step 7:

[0582] The user follows the audio guidance and presses the jump button twice in succession to successfully perform a double jump.

[0583] Example 2: Using a new skill (long-range attack)

[0584] Step 1:

[0585] A user acquires a new skill.

[0586] Step 2:

[0587] The server detects the acquisition of a new skill (ranged attack).

[0588] Step 3:

[0589] The server determines that "an explanation of how to use long-range attacks is required" and generates a request.

[0590] Step 4:

[0591] The server sends the request to the terminal.

[0592] Step 5:

[0593] The device receives the request and prepares a voice prompt saying, "Press the right stick to perform a long-range attack."

[0594] Step 6:

[0595] The terminal provides audio guidance to the user.

[0596] Step 7:

[0597] Users follow the voice prompts and push the right stick to perform long-range attacks.

[0598] In this way, the user can receive the necessary operating instructions at the appropriate time and progress smoothly through the game.

[0599] Example 1

[0600] 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."

[0601] Current game systems have difficulty providing appropriate operational instructions in real time when a user experiences difficulty with a specific operation or new skill. This can impair the user experience and stall game progress. Furthermore, the increased time required for the user to overcome the difficulty can reduce satisfaction with the game. Therefore, the present invention aims to improve the user experience by monitoring and analyzing the user's operation history and game progress in real time and providing operational instructions at the appropriate time.

[0602] 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.

[0603] In this invention, the server includes means for collecting a user's operation history and game progress status in real time, means for analyzing the operation history and game progress status using a machine learning model to detect when a specific operation has not been attempted for a long time or when the user is experiencing difficulty in a specific area, and means for generating a request for appropriate operation instructions based on the detected timing and sending the request to the terminal. This makes it possible to detect difficulties the user is experiencing while playing the game in real time and provide appropriate operation instructions at that moment.

[0604] "User operation history" is a record of the specific operations performed by the user when playing a game, including keyboard keystrokes, mouse movements, button clicks, and the like.

[0605] "Game progress" refers to information related to the progress of the game, such as the character's current position and status in the game, mission progress, and game area.

[0606] A "machine learning model" is a general term for algorithms that learn patterns and trends based on past data and make predictions and classifications for new data.

[0607] A "request for operation instructions" is a request to generate instructions including specific operation procedures and send them to the terminal when the user is experiencing difficulty in the game.

[0608] "Speech synthesis technology" is a technology that generates voices that mimic human voices based on text data, and is used to create audio guides.

[0609] "Terminal" refers to a device that provides audio guidance to the user, including smart speakers and earphones.

[0610] "Audio guide" refers to instructions provided by voice that guide the user through the operational procedures required in the game, and is intended to aid the user in understanding.

[0611] "New skills" refer to new abilities or techniques that a user acquires in the game and that the user must learn how to use.

[0612] MODE FOR CARRYING OUT THE INVENTION

[0613] This invention relates to a system that collects a user's operation history and game progress in real time and provides necessary operation instructions based on that data. Here, we will explain how to implement this system in detail. This system is mainly composed of three parties: a server, a terminal, and a user.

[0614] Server Processing

[0615] 1. Gathering game logs

[0616] The server collects game logs in real time. Specifically, it uses an API and a database to collect user operation history (keystrokes, mouse movements, button clicks, etc.) and game progress (character status, progress, current game area). This data is necessary to understand the user's in-game behavior.

[0617] 2. Data Analysis

[0618] The server analyzes user behavior based on the collected data, using machine learning models (e.g., clustering and trend analysis algorithms) to detect when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area.

[0619] 3. Request Generation

[0620] The server uses the analysis results to determine when and how the user needs to be instructed on what operations. For example, if the user has been trying to jump in the same place for more than five minutes, the server detects this and generates a request indicating the need for a double jump. This request includes specific instructions and the reasons for them.

[0621] Terminal handling

[0622] 1. Receiving requests and preparing audio guides

[0623] The device (smart speaker or earphones) receives a request for operation instructions from the server. It uses speech synthesis technology (e.g., Google Text-to-Speech or Amazon Polly) to generate audio guidance based on the request. This audio guidance includes specific operation procedures.

[0624] 2. Provision of audio guides

[0625] The device provides the generated voice guidance to the user. For example, it transmits instructions such as "Please press the jump button twice in succession" in real time through earphones. This allows the user to follow the voice guidance and perform the appropriate operation.

[0626] User response

[0627] 1. Gameplay

[0628] The user plays the game as usual, but if they encounter a difficult situation or don't know how to perform a particular operation, they try it out on the spot.

[0629] 2. Audio guide execution

[0630] The user attempts to perform specific operations according to the voice guidance provided by the device. For example, by following the instruction to "press the jump button twice in succession," the user can successfully perform a double jump.

[0631] 3. Providing Feedback

[0632] If the user follows the instructions and the operation is successful, the information is sent back to the server. For example, a log stating "double jump successful" is sent to the server. This feedback will be used for future data analysis and contribute to improving the accuracy of the system.

[0633] Specific examples

[0634] Example 1: Performing a double jump

[0635] Let's assume that the user is having trouble progressing in a particular area.

[0636] 1. The server detects that the user has been attempting to jump in the same location for more than 5 minutes and generates a request for a "need for a double jump."

[0637] 2. The device receives the request, generates a voice prompt saying "Please press the jump button twice in succession," and conveys this to the user through the smart speaker.

[0638] 3. The user follows the audio guidance and presses the jump button twice in succession to perform a double jump and proceed to the next area.

[0639] Example 2: Using long-range attack skills

[0640] Suppose a user acquires a new skill and doesn't know how to use it.

[0641] 1. The server detects that the user has acquired a new skill (ranged attack) and generates a request for it.

[0642] 2. The device receives the request and generates and provides a voice prompt saying, "Press the right stick to perform a long-range attack."

[0643] 3. Following the voice guidance, the user presses the right stick to attempt a long-range attack and succeeds.

[0644] Specific examples of prompts

[0645] Below are some example prompts to input to the generative AI model for the system:

[0646] Please describe this system. The server collects game logs in real time and analyzes the user's operation history and game progress. At specific times, it generates and sends a request for audio guidance to the device. The device prepares audio guidance based on the request and provides it to the user. For example, if the user experiences difficulty, the server detects that situation and generates guidance instructing the user to press the jump button twice in succession.

[0647] As described above, implementing the present invention requires the ability to collect and analyze the user's operation history and game progress in real time, as well as the ability to provide audio guidance at appropriate times, which enables real-time operation explanations and significantly improves the user experience.

[0648] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0649] Step 1:

[0650] Gathering game logs

[0651] The server collects the user's operation history and game progress in real time. During this process, the game inputs operation data (keystrokes, mouse movements, button clicks, etc.) from the game. This data is collected via API and database and stored on the server. For example, the number of times the jump button was pressed and the character's current position are recorded. This makes it possible to monitor what operations the user is performing within the game.

[0652] Step 2:

[0653] Data analysis

[0654] The server analyzes the collected operation history and game progress using a machine learning model. The game logs collected in step 1 are used as input for this process. The analysis uses clustering algorithms and trend analysis algorithms to detect when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area. For example, a pattern such as "the user has been trying to jump in the same place for five minutes without success" can be detected. This makes it possible to identify when the user is experiencing difficulty.

[0655] Step 3:

[0656] Request Generation

[0657] Based on the analysis results from step 2, the server detects when instructions are needed and generates a request containing specific instructions. The input to this process is the information obtained through data analysis. The output is a request containing specific operating procedures and the reasons for them. For example, a request stating "double jump required" is created. This prepares the device to provide appropriate operating instructions to the user.

[0658] Step 4:

[0659] Receiving requests and preparing audio guides

[0660] The device receives a request for operation instructions from the server and prepares audio guidance based on the request. The input for this process is the request sent from the server. The device uses speech synthesis technology (e.g., Google Text-to-Speech or Amazon Polly) to generate audio guidance based on the request. The output is an audio guidance message. For example, an audio guidance message such as "Press the jump button twice in succession" is created. This completes the guidance for the user to perform the appropriate operation.

[0661] Step 5:

[0662] Audio guide provided

[0663] The device provides the generated audio guide to the user. The input of this process is the audio guide generated in step 4. The device provides the audio guide to the user through a smart speaker or earphones. The output includes the audio guide received by the user. For example, an instruction such as "Please press the jump button twice in succession" may be conveyed to the user through the earphones. This allows the user to receive instructions on how to operate the device in real time.

[0664] Step 6:

[0665] Execute audio guide

[0666] The user attempts to perform a specific operation according to the voice guidance provided by the device. The input to this process is the voice guidance provided by the device. Based on the instructions, the user performs a specific operation (for example, pressing the jump button twice in succession). The output includes the result of whether the user succeeded or failed in the operation. This allows the user to learn difficult operations or how to use new skills.

[0667] Step 7:

[0668] Providing Feedback

[0669] If the user successfully performs the instructed operation, that information is sent back to the server. The input to this process is the result of the user's operation. For example, a log stating "double jump successful" is sent to the server. The output is this feedback information, which is recorded on the server. Based on this feedback, the server can improve the accuracy of future analysis. This continuously improves the efficiency of the entire system.

[0670] (Application example 1)

[0671] 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."

[0672] Mistakes made by workers in factories and incorrect work procedures can lead to reduced production efficiency and safety risks. Furthermore, it is difficult to learn new operating procedures and how to use machines in real time, which causes further problems. Traditional textbooks and manuals do not allow for immediate response, and it takes time for workers to learn the correct operating methods.

[0673] 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.

[0674] In this invention, the server includes means for collecting the user's operation history and status in real time, means for analyzing the operation history and status and detecting the timing when operation instructions are required, means for generating an operation instruction request based on the detected timing and sending it to the terminal, and means for receiving the request, preparing visual and audio guides, and providing them to the user. This makes it possible to correct operational errors and errors in work procedures by workers in the factory in real time, and to progress work efficiently and safely.

[0675] An "operation history" is a record of a series of operations and actions performed by a user.

[0676] The "situation" is the totality of the environment in which the user is currently placed and the work that is currently in progress.

[0677] "Collecting in real time" means collecting operation history and status immediately without delay.

[0678] "Analysis" is the process of analyzing collected data to find specific patterns and trends.

[0679] "Detection" refers to the identification of a particular condition or event from the results of an analysis.

[0680] "Operation instructions" are specific operating procedures and methods provided to the user.

[0681] "Generating a request" means creating a necessary operation instruction and creating a request to provide it.

[0682] A "terminal" is a device or apparatus that receives a request for operation instructions and provides visual and audio guidance to the user.

[0683] A "visual guide" is a means of conveying operating procedures and information to users graphically.

[0684] "Audio guide" is a means of conveying operational procedures and information to the user by voice.

[0685] "User" refers to the worker or operator who uses the system and receives instructions on how to operate it.

[0686] This invention is a system for correcting worker errors and errors in work procedures in real time in a factory, ensuring efficient and safe work progress. This system mainly operates in cooperation with three parties: a server, a terminal, and a user.

[0687] System configuration

[0688] The system mainly consists of the following elements:

[0689] 1. Server: Collects the user's operation history and status in real time and detects when operation instructions are required. The server generates a request for operation instructions and sends it to the device.

[0690] 2. Terminal: Receives requests from the server, prepares visual and audio guides, and provides them to the user. The terminal can be a smart glass or other visual and audio output device.

[0691] 3. User: A worker who performs work in a factory. The user follows visual and audio guidance to carry out the correct work procedures.

[0692] Program processing

[0693] Server Processing

[0694] The server does the following:

[0695] 1. Data collection: Collect worker movements in real time from cameras and sensors in the factory (e.g., Azure Kinect, Microsoft Azure IoT Hub), including worker behavior data and the status of the work being performed.

[0696] 2. Analysis and detection: The collected data is analyzed using Google Cloud Dataflow and Azure Machine Learning to detect whether specific work procedures are being performed correctly based on the user's operation history and situation.

[0697] 3. Request generation: If the correct operating procedure is not performed, a request for operating instructions is generated based on the timing and sent to the terminal.

[0698] Terminal handling

[0699] The terminal does the following:

[0700] 1. Request reception and preparation: Smart glasses (e.g., Google Glass, Epson Moverio) receive a request for operation instructions from the server and prepare visual and audio guidance. Amazon Polly is used for speech synthesis.

[0701] 2. Providing visual and audio guidance: The device displays visual guidance on the screen and provides audio guidance, which helps users understand specific work procedures.

[0702] User response

[0703] The user takes the following actions:

[0704] 1. Task execution: The user follows the visual and audio guidance provided by the smart glasses to perform the correct task steps.

[0705] 2. Providing feedback: The progress of the work is reported to the server, and information about successes and failures is used again for data collection and analysis.

[0706] Specific examples

[0707] For example:

[0708] 1. Palletizing Guide:

[0709] The server detects incorrect movements when workers lift loads.

[0710] The server generates an instruction for operation such as "Next, carefully lift the luggage and place it in the designated location" and sends it to the terminal.

[0711] The device provides audio guidance along with visual guidance.

[0712] The user follows the guide and places the luggage in the correct position.

[0713] 2. Learning how to operate a new machine:

[0714] The server detects mistakes made by workers as they try out new ways of operating machines.

[0715] The server generates operating instructions such as "To operate this machine, first press the red button and then pull the lever" and sends them to the terminal.

[0716] The device provides visual and audio guidance through smart glasses.

[0717] Users follow the guide to learn the correct operating procedures.

[0718] As a result, it is possible to reduce work errors in the factory and perform work safely and efficiently.

[0719] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0720] Step 1:

[0721] The server collects worker movement data in real time using cameras and sensors (e.g., Azure Kinect, Microsoft Azure IoT Hub) in the factory. The input is raw data from the cameras and sensors, and the output is a log of worker movement. Specifically, it records video data captured by cameras and movement data acquired by sensors.

[0722] Step 2:

[0723] The server analyzes the collected operation data using a data analysis platform (e.g., Google Cloud Dataflow, Azure Machine Learning). The input here is the operation log, and the output is the analysis result, i.e., a determination of whether a specific work procedure was performed correctly. Specifically, an AI model is used to analyze operation patterns and detect mistakes or incorrect operations.

[0724] Step 3:

[0725] The server generates a request for operation instructions based on the analysis results and sends it to the terminal. The input is the analysis results, and the output is an operation instruction request. Specifically, it generates text information about appropriate operation procedures and actions that need to be corrected.

[0726] Step 4:

[0727] The device receives the operation instruction request sent from the server and prepares the audio guide using speech synthesis software (e.g., Amazon Polly). The input is the operation instruction request, and the output is the audio guide and visual guide. Specifically, the device converts the request into text and prepares to display it on the screen as visual information.

[0728] Step 5:

[0729] The terminal provides the prepared visual and audio guide to the user. The input is the audio and visual guide data, and the output is the display and audio output to convey it to the user. Specifically, the smart glasses display text and illustrated procedures, as well as audio instructions, so that the worker can receive them.

[0730] Step 6:

[0731] The user performs specific tasks according to the visual and audio guidance provided by the terminal. The input is the visual and audio guidance, and the output is the accurate execution of the work procedure. Specifically, the user performs the task according to the guidance and checks the results.

[0732] Step 7:

[0733] The results of the user's work are fed back to the server. The input is the work result, and the output is feedback data to the server. Specifically, the success or failure of the work and its details are sent to the server to help with future improvements.

[0734] 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.

[0735] This invention relates to a system that analyzes the user's behavior and emotional state in real time in a game and provides operation instructions at the appropriate time to improve the user experience. This system operates in cooperation with the server, the terminal, and the user.

[0736] System configuration

[0737] First, we will explain the system configuration. This system mainly consists of the following elements:

[0738] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. It also includes an emotion engine to recognize the user's emotional state. The server detects when operation instructions are required and generates an instruction request. The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data.

[0739] 2. Device: Receives requests from the server, prepares audio guides, and provides them to the user. The device can be a smart speaker or earphones. If the user is in a negative emotional state, the device adjusts the content and tone of the audio guide.

[0740] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[0741] Program processing

[0742] The program processing that realizes this is explained in natural language, and the behavior of the server, terminal, and user is described in detail.

[0743] Server Processing

[0744] 1. Data collection: The server collects game logs in real time. Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[0745] 2. Emotion Recognition: The server recognizes the user's emotional state using an emotion engine, which uses facial expression analysis, voice analysis, or vital sign data of the user.

[0746] 3. Analysis and Detection: The server analyzes the collected operation history and progress as well as the recognized emotion data to detect when a specific operation has not been performed successfully for a long time or when the user is stagnating in a particular area.

[0747] 4. Request Generation: The server generates a request for operation instructions based on the detection results and the emotional state. For example, it generates a specific request such as "double jump required."

[0748] Terminal handling

[0749] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[0750] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. If the user's emotional state is negative, the content and tone of the audio guidance will be adjusted.

[0751] User response

[0752] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[0753] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[0754] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis, and if unsuccessful, a more detailed explanation may be provided.

[0755] Specific examples

[0756] Example 1: Performing a double jump

[0757] Let's say a user is having trouble progressing in a particular area.

[0758] 1. Server: Detects when a user has been trying to jump in the same place for more than five minutes without success. The emotion engine also analyzes the user's facial expressions and recognizes frustration.

[0759] 2. Server: Sends a request for instructions, "Explain how to double jump," and information that "the user is frustrated" to the device.

[0760] 3. Device: Receive the request and prepare a voice prompt saying "Please press the jump button twice in succession," and provide it in a gentle tone depending on the user's emotional state.

[0761] 4. User: Follow the audio guide and press the jump button twice in succession to perform a double jump and proceed to the next area.

[0762] Example 2: Using a new skill (long-range attack)

[0763] A user acquires a new skill and doesn't know how to use it.

[0764] 1. Server: Detects when a user acquires a new skill (long-range attack). Also, the emotion engine recognizes the emotion of anxiety from the user's vital sign data.

[0765] 2. Server: Sends a request for operation instructions, "Explain how to use long-range attacks," and information about "the user's anxiety," to the device.

[0766] 3. Device: Receive the request and prepare a voice prompt saying "Press the right stick to perform a ranged attack" in a reassuring tone depending on the emotional state.

[0767] 4. User: Follow the voice prompts and press the right stick to perform a long-range attack.

[0768] In this way, users can receive real-time instructions and emotional support to smoothly progress through the game, which greatly improves the user experience and reduces the costs and efforts of game developers.

[0769] The processing flow will be explained below.

[0770] Program processing steps

[0771] Server Processing

[0772] Step 1:

[0773] The server collects game logs in real time.

[0774] Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[0775] Step 2:

[0776] The server uses an emotion engine to recognize the user's emotional state in real time.

[0777] The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data of the user.

[0778] Step 3:

[0779] The server analyzes the collected operation history and progress as well as the recognized emotion data.

[0780] Specifically, it checks if a particular operation has not been successful for a long time or if the user is stuck in a particular area.

[0781] Step 4:

[0782] The server detects when an instruction for operation is required.

[0783] For example, if the user has been trying to jump in the same place for more than five minutes without success, it is determined that an instruction on how to jump is necessary.

[0784] Step 5:

[0785] The server generates a request for operation instructions based on the detection result and the emotional state.

[0786] Specifically, information such as "a double jump is required" or "the user is feeling frustrated" is generated as a request.

[0787] Step 6:

[0788] The server transmits the generated request to the terminal.

[0789] Terminal handling

[0790] Step 7:

[0791] The terminal receives a request for operation instructions from the server.

[0792] Step 8:

[0793] The terminal prepares audio guidance based on the received request.

[0794] Specifically, instructions such as "Press the jump button twice in succession" are converted into voice using speech synthesis technology.

[0795] Step 9:

[0796] The terminal adjusts the tone of the audio guide according to the user's emotional state.

[0797] For example, if the user is feeling frustrated, prepare a voice prompt with a gentle tone.

[0798] Step 10:

[0799] The device provides the prepared audio guide to the user through a smart speaker or earphones.

[0800] User response

[0801] Step 11:

[0802] The user follows the voice guidance provided by the terminal and attempts to perform specific operations.

[0803] For example, try to perform a double jump by pressing the jump button twice in succession.

[0804] Step 12:

[0805] The result of the user's operation is sent to the server again.

[0806] If successful, the information will be recorded for future analysis, if unsuccessful a more detailed explanation may be provided.

[0807] Example 1: Double jump

[0808] Step 1:

[0809] The user is unable to overcome a particular obstacle during gameplay and becomes stuck.

[0810] Step 2:

[0811] The server detects that the user has clicked the jump button multiple times but without success.

[0812] Step 3:

[0813] The server uses an emotion engine to analyze the user's facial expressions and recognize the emotion of frustration.

[0814] Step 4:

[0815] The server sends the information "explain how to double jump" and "the user is feeling frustrated" as a request to the terminal.

[0816] Step 5:

[0817] The device receives the request and prepares a voice prompt saying, "Please press the jump button twice in succession."

[0818] Step 6:

[0819] The device recognizes that the user is frustrated and provides voice guidance in a gentle tone.

[0820] Step 7:

[0821] The user follows the audio guidance and presses the jump button twice in succession to perform a double jump and proceed to the next area.

[0822] Example 2: Using a new skill (long-range attack)

[0823] Step 1:

[0824] A user acquires a new skill.

[0825] Step 2:

[0826] The server detects the acquisition of a new skill (ranged attack).

[0827] Step 3:

[0828] The server uses an emotion engine to analyze the user's vital sign data and recognize emotions of anxiety.

[0829] Step 4:

[0830] The server sends the information "explain how to use long-range attacks" and "the user feels anxious" as a request to the terminal.

[0831] Step 5:

[0832] The device receives the request and prepares a voice prompt saying, "Press the right stick to perform a long-range attack."

[0833] Step 6:

[0834] The terminal recognizes that the user is feeling anxious and provides audio guidance in a reassuring tone.

[0835] Step 7:

[0836] Users follow the voice prompts and push the right stick to perform long-range attacks.

[0837] Example 2

[0838] 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."

[0839] Conventional game systems struggle to provide timely explanations of in-game operations that can easily confuse users or how to use new skills. Furthermore, when a user becomes stuck on a particular operation or area, this can be due to emotional factors, but the system lacks the ability to detect this in real time and take appropriate action. Furthermore, explanations that are not tailored to the user's emotional state can increase anxiety and frustration, detracting from the game experience.

[0840] 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.

[0841] In this invention, the server includes means for collecting a user's operation history and game progress status in real time, means for analyzing the operation history and game progress status and detecting timing when operation instructions are required, means for generating an operation instruction request based on the detected timing and sending it to the terminal, means for recognizing the user's emotional state using an emotion engine, and means for adjusting the content and tone of audio guidance based on the emotional state. This allows the user to receive operation instructions in the game at appropriate timing according to their emotions, improving the game experience.

[0842] The "user operation history" is a record of a series of operations performed by the user during the game. Specifically, this includes the number of clicks of the jump button, the direction of movement, attack actions, and so on.

[0843] "Game progress" refers to information about the progress of the game, such as the character's position in the game, progress, and acquired items.

[0844] The "emotion engine" is an analysis engine for recognizing the user's emotional state. Specifically, it analyzes facial expressions, voice, and vital sign data.

[0845] An "operation instruction request" is a request generated by a server to instruct a user on how to perform a particular operation.

[0846] "Audio guide" refers to audio instructions and explanations provided to the user by a device. The content and tone may be adjusted to make the instructions easier for the user to understand.

[0847] A "terminal" is a device that receives a request for operation instructions from the server, prepares audio guidance, and provides it to the user. This includes smart speakers and earphones.

[0848] "Emotional state" refers to the user's current feelings, including frustration, anxiety, joy, etc.

[0849] This invention relates to a system that analyzes the user's behavior and emotional state in real time in a game and provides operation instructions at the appropriate time to improve the user experience. This system operates in cooperation with the server, the terminal, and the user.

[0850] System configuration

[0851] The system mainly consists of the following elements:

[0852] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. It also includes an emotion engine to recognize the user's emotional state. The server detects when operation instructions are required and generates an instruction request. The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data.

[0853] 2. Device: Receives requests from the server, prepares audio guides, and provides them to the user. The device can be a smart speaker or earphones. If the user is in a negative emotional state, the device adjusts the content and tone of the audio guide.

[0854] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[0855] Server Processing

[0856] 1. Data collection: The server collects game logs in real time. Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[0857] 2. Emotion Recognition: The server uses an emotion engine to recognize the user's emotional state, which can be achieved by analyzing the user's facial expressions, voice, or vital sign data.

[0858] 3. Analysis and Detection: The server analyzes the collected operation history and progress as well as the recognized emotion data to detect when a specific operation has not been performed successfully for a long time or when the user is stagnating in a particular area.

[0859] 4. Request Generation: The server generates a request for operation instructions based on the detection results and the emotional state. For example, it generates a specific request such as "double jump required."

[0860] Terminal handling

[0861] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[0862] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. If the user's emotional state is negative, the content and tone of the audio guidance will be adjusted.

[0863] User response

[0864] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[0865] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[0866] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis, and if unsuccessful, a more detailed explanation may be provided.

[0867] Specific examples

[0868] Example 1: Performing a double jump

[0869] Let's say a user is having trouble progressing in a particular area.

[0870] 1. Server: Detects when a user has been trying to jump in the same place for more than five minutes without success. The emotion engine also analyzes the user's facial expressions and recognizes frustration.

[0871] 2. Server: Sends a request for instructions, "Explain how to double jump," and information that "the user is frustrated" to the device.

[0872] 3. Device: Receive the request and prepare a voice prompt saying "Please press the jump button twice in succession," and provide it in a gentle tone depending on the user's emotional state.

[0873] 4. User: Follow the audio guide and press the jump button twice in succession to perform a double jump and proceed to the next area.

[0874] Example 2: Using a new skill (long-range attack)

[0875] A user acquires a new skill and doesn't know how to use it.

[0876] 1. Server: Detects when a user acquires a new skill (long-range attack). Also, the emotion engine recognizes the emotion of anxiety from the user's vital sign data.

[0877] 2. Server: Sends a request for operation instructions, "Explain how to use long-range attacks," and information about "the user's anxiety," to the device.

[0878] 3. Device: Receive the request and prepare a voice prompt saying "Press the right stick to perform a ranged attack" in a reassuring tone depending on the emotional state.

[0879] 4. User: Follow the voice prompts and press the right stick to perform a long-range attack.

[0880] In this way, users can receive real-time instructions and support tailored to their emotional state, allowing them to progress smoothly through the game, significantly improving the user experience and reducing support costs for game developers.

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

[0882] Step 1: Data collection

[0883] The server collects game logs in real time. As input, it receives the user's operation history (number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.). The server records this data and accumulates it in a data store for subsequent analysis. Specific operations include receiving and saving log data.

[0884] Step 2: Recognize emotions

[0885] The server uses an emotion engine to recognize the user's emotional state. As input, it receives the user's facial expression data, voice data, and vital sign data. The emotion engine analyzes these data and identifies the user's emotional state (frustration, anxiety, joy, etc.). As output, it generates recognized emotion data, which is passed to the next analysis step. Specifically, it performs data analysis using a face recognition module and a voice analysis module.

[0886] Step 3: Analysis and detection

[0887] The server integrates and analyzes the collected operation history, game progress, and emotional data. It receives the above operation history, game progress, and emotional data as input. It integrates the data and detects when a specific operation has not been successful for a long time or when the user is stuck in a specific area. It generates problem identification results (e.g., the user is having difficulty jumping) as output. Specific operations include problem detection using database queries and machine learning algorithms.

[0888] Step 4: Request Generation

[0889] The server generates a request for operation instructions based on the detection results and the emotional state. As input, it receives the detected problem and emotional data. It generates a specific request, such as "double jump required" or "the user is feeling frustrated." As output, it sends the generated request to the terminal. As a specific operation, it creates a specific instruction sentence using a text generation engine and sends the request to the terminal using a communication module.

[0890] Step 5: Receiving and preparing the request

[0891] The device receives a request for operation instructions from the server. As input, it receives the request data sent from the server. Based on that content, it prepares audio guidance. It uses speech synthesis technology to convert the text instructions into speech. It prepares the generated audio data as output. Specifically, it calls a speech synthesis API to generate the audio data.

[0892] Step 6: Provide audio guides

[0893] The terminal provides audio guidance to the user through a smart speaker or earphones. As input, it receives prepared audio data. The content and tone of the audio guidance are adjusted according to the user's emotional state. As output, it provides specific audio instructions to the user. As a specific operation, it uses an audio playback module to play the audio guidance to the user.

[0894] Step 7: Gameplay

[0895] The user plays the game as usual. As input, they receive audio guidance provided by the device. If they are unsure of how to operate the device, they try and error on the spot. As output, a new operation history and game progress status are generated. As a specific operation, they operate the game controller and perform actions in the game.

[0896] Step 8: Receive and follow the audio guide

[0897] The user attempts specific operations according to the voice guidance provided by the device. As input, the user receives the instructions from the voice guidance. For example, the user attempts a double jump by pressing the jump button twice in succession. As output, a history of successful operations is generated. As a specific action, the user operates the game controller as instructed.

[0898] Step 9: Provide feedback

[0899] If the user successfully performs an operation, that information is sent to the server. As input, it receives information about whether the operation was successful or unsuccessful. The server analyzes this feedback information and checks whether the operation was performed correctly. As output, it generates a request indicating success or if further explanation is required. Specifically, when the operation is successful, it obtains satisfaction data from the vital sign data and sends it to the server.

[0900] (Application example 2)

[0901] 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."

[0902] Current security monitoring systems lack the ability to analyze users' real-time behavior and emotional state and provide appropriate responses. Furthermore, there is no system that can immediately guide users to appropriate measures when they feel stressed or anxious, making it difficult to provide efficient responses to ensure users' safety. This increases the risk of users being exposed to unstable situations.

[0903] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting a user's operation history and progress status in real time, means for analyzing the operation history and progress status and detecting a timing when an explanation is needed, means for generating an explanation request based on the detected timing and transmitting it to the terminal, means for receiving the request, preparing audio guidance, and providing it to the user, means for analyzing the user's behavior and emotional state, means for detecting a situation in which the user feels anxious or stressed, and generating a request for an appropriate response method, and means for collecting user location information and video data in real time and analyzing the security situation. This makes it possible to quickly provide an appropriate response method when the user feels anxious or stressed.

[0904] An "operation history" is a record of specific actions and operations performed by a user.

[0905] "Progress" is a record of the status that indicates how far a task or process has progressed.

[0906] The "timing when an explanation is required" refers to a time or situation when a user does not understand a particular operation or action and an explanation is required.

[0907] "Request" refers to a request for a specific operation or description of an action.

[0908] A "terminal" is a device that connects a server and a user and provides information such as audio guides.

[0909] "Audio guide" provides the user with audio instructions on specific operations and actions.

[0910] "Behavior" refers to a specific movement or activity taken by a user.

[0911] "Emotional state" indicates the type and strength of the user's emotion.

[0912] An "anxious or stressful situation" is a specific situation or environment in which a user feels psychological anxiety or tension.

[0913] "Appropriate response method" refers to instructions for the most appropriate procedure or action depending on the user's situation and emotions.

[0914] "Location information" is data that indicates the user's current geographical location.

[0915] "Video Data" refers to image or video data collected by a camera or other image capture device.

[0916] "Security situation" refers to the state of the environment or situation regarding safety.

[0917] This invention relates to a system that analyzes a user's operation history and emotional state in real time to implement a security monitoring system, and provides appropriate responses as audio guidance when the user feels anxious or stressed. This system operates in cooperation with a server, a terminal, and a user.

[0918] System configuration

[0919] The system mainly consists of the following components:

[0920] 1. Server: Collects and analyzes the user's operation history and progress in real time. It also has an emotion engine and recognizes the user's emotional state (specifically, anxiety or stress). It also analyzes security-related situations and generates requests for appropriate responses. The emotion engine and analysis tools used are Google Cloud's "AutoML Vision" and "AutoML Natural Language."

[0921] 2. Terminal: Receives requests from the server, prepares audio guides, and provides them to the user. Using speech synthesis technology, it converts instructions on the appropriate response method into speech. Google Cloud Text-to-Speech is used as the speech synthesis technology.

[0922] 3. User: Uses a device such as a smartphone or earphones to perform normal operations and actions. If the user feels anxious or stressed, they follow the voice guidance provided by the device to take appropriate measures. The voice guidance is provided in a reassuring tone to help the user take safe actions.

[0923] Program implementation steps

[0924] The server collects location information, camera footage, and microphone audio from the smartphone in real time. The emotion engine recognizes and analyzes the user's emotional state from the camera footage and microphone audio. It detects situations in which the user feels anxious or stressed and generates a request for how to respond (for example, directions to the nearest police station or directions to a safe route). The generated request is sent to the device, which uses speech synthesis technology to convert the instructions into voice and provide it to the user.

[0925] Specific examples

[0926] Example 1: Presence of a suspicious person

[0927] 1. Server: The user finds a suspicious person and analyzes emotions of fear and anxiety from camera footage and microphone audio.

[0928] 2. Server: Detects situations where the user is feeling anxious and generates a request to "show the location of the nearest police box."

[0929] 3. Device: Receives the request and prepares and provides an audio guide saying, "Don't worry, the nearest police box is located at XX. Head there immediately."

[0930] 4. User: Follow the audio guide and head immediately to the designated police box.

[0931] Example 2: Staying in a dark place late at night

[0932] 1. Server: Detects anxious facial expressions and voice when the user is in a dark place late at night.

[0933] 2. Server: Detects that the user is feeling anxious and needs guidance on a safe route, and generates the corresponding request.

[0934] 3. Terminal: Receives requests and provides voice guidance on safe routes.

[0935] 4. User: Follow the voice guidance to find a safe route and return home safely.

[0936] Example prompts to input to the generative AI model

[0937] "You are developing a smartphone application that analyzes the user's emotions from camera footage and audio data, and provides appropriate guidance on how to respond when the user feels anxious or stressed. Please generate the following audio guidance."

[0938] This system allows users to receive real-time guidance on appropriate response methods, enabling them to respond quickly and accurately to security risks.

[0939] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0940] Step 1: Data collection

[0941] The server collects location information, camera footage, and microphone audio from the smartphone in real time. These data are the basis for analyzing the user's behavior and emotional state. The input is location information, camera footage, and microphone audio, which are sent to the server. The output is that these data are stored on the server.

[0942] Step 2: Recognize emotions

[0943] The server sends the collected camera footage and microphone audio to the emotion engine to recognize the user's emotional state. Specifically, it uses AutoML Vision and AutoML Natural Language to analyze facial expressions and tone of voice. The input is the collected video and audio data, and the output is a judgment of the user's emotional state (e.g., anxiety, stress, relief, etc.).

[0944] Step 3: Detect security conditions

[0945] The server analyzes whether the user is in a dangerous situation (e.g., the presence of a suspicious person, being in a dark place) based on location information and emotional state data. Specifically, it detects this by comparing the current location with information on pre-defined safe and dangerous areas. The input is the location information and the result of the emotional state determination, and the output is the result of the determination of whether the situation is dangerous or safe.

[0946] Step 4: Generate a response request

[0947] If the server determines that the user is in a dangerous situation, it generates a request for an appropriate response (e.g., information about a nearby police station or a safe route). The content of the request is determined based on the user's current location information and the dangerous situation. The input is the location information and the result of the dangerous situation determination, and the output is a request for an appropriate response.

[0948] Step 5: Submit your request and prepare your audio guide

[0949] The device receives the response request sent from the server and prepares the audio guide. It converts the request into audio using Google Cloud Text-to-Speech. The input is the response request, and the output is the audio guide data.

[0950] Step 6: Provide audio guides

[0951] The device provides the audio guide to the user through a smartphone or earphone. If the user feels anxious, the audio guide is provided in a reassuring tone. The input is the audio guide data, and the output is the provision of the audio guide to the user.

[0952] Step 7: User Behavior

[0953] The user follows the voice guidance provided by the device and takes appropriate action. For example, heading to the nearest police station or following a safe route. The user's actions are fed back to the server and used for future analysis. The input is the content of the voice guidance, and the output is the user's specific actions.

[0954] 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.

[0955] 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.

[0956] 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.

[0957] [Third embodiment]

[0958] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0959] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0960] 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).

[0961] 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.

[0962] 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.

[0963] 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).

[0964] 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.

[0965] 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.

[0966] 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.

[0967] 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.

[0968] 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.

[0969] 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."

[0970] The present invention relates to a system that analyzes user behavior in a game in real time and provides operation instructions at appropriate times to improve the user experience. This system operates in cooperation with a server, a terminal, and a user.

[0971] System configuration

[0972] First, we will explain the system configuration. This system mainly consists of the following elements:

[0973] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. The server detects when operation instructions are required and generates a request for operation instructions.

[0974] 2. Terminal: Receives requests from the server, prepares audio guides, and provides them to the user. The terminal can be a smart speaker or earphones.

[0975] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[0976] Program processing

[0977] The program processing that realizes this is explained in natural language, and the behavior of the server, terminal, and user is described in detail.

[0978] Server Processing

[0979] 1. Data collection: The server collects game logs in real time, specifically recording user operation history (keystrokes, mouse movements, button clicks, etc.) and game progress (progress, character status, current game area).

[0980] 2. Analysis and Detection: The server analyzes the user's progress and operation history based on the collected data, detecting when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area.

[0981] 3. Request generation: The server generates a request for appropriate operation instructions based on the detected timing. For example, it specifies information such as "double jump is required."

[0982] Terminal handling

[0983] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[0984] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. For example, the device tells the user, "Here, press the jump button twice in succession."

[0985] User response

[0986] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[0987] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[0988] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis.

[0989] Specific examples

[0990] Example 1: Performing a double jump

[0991] Let's say a user is having trouble progressing in a particular area.

[0992] 1. Server: Detects that the user has been attempting to jump in the same place for more than 5 minutes and generates a request for a "need for a double jump."

[0993] 2. Device: Receives the request, generates a voice prompt saying "Please press the jump button twice in succession," and conveys this to the user through the smart speaker.

[0994] 3. User: Follow the voice guidance and press the jump button twice in rapid succession to perform a double jump and proceed to the next area.

[0995] Example 2: Using long-range attack skills

[0996] A user acquires a new skill and doesn't know how to use it.

[0997] 1. Server: Detects that the user has acquired a new skill (ranged attack) and generates a request for it.

[0998] 2. Device: Receives the request and generates and provides a voice prompt saying, "Press the right stick to perform a long-range attack."

[0999] 3. User: Follow the voice prompts and press the right stick to attempt a long-range attack and succeed.

[1000] In this way, users can receive real-time instructions and smoothly progress through the game, which greatly improves the user experience and reduces the costs and efforts of game developers.

[1001] The processing flow will be explained below.

[1002] Program processing steps

[1003] Server Processing

[1004] Step 1:

[1005] The server collects game logs in real time.

[1006] Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[1007] Step 2:

[1008] The server analyzes the collected operation history and progress.

[1009] Specifically, it analyzes whether a particular operation has not been successful for a long time or whether the user is stagnating in a particular area.

[1010] Step 3:

[1011] The server detects when an instruction for operation is required.

[1012] Specifically, this applies when a user is repeatedly performing a particular action without success, or when they have difficulty applying a new skill immediately after acquiring it.

[1013] Step 4:

[1014] The server generates a request for operation instructions based on the detection result.

[1015] For example, generate a specific request such as "Explain how to do a double jump."

[1016] Step 5:

[1017] The server transmits the generated request to the terminal.

[1018] Terminal handling

[1019] Step 6:

[1020] The terminal receives a request for operation instructions from the server.

[1021] Step 7:

[1022] The terminal prepares audio guidance based on the received request.

[1023] Specifically, specific instructions such as "Press the jump button twice in succession" are generated as an audio file using voice synthesis technology.

[1024] Step 8:

[1025] The terminal provides the prepared audio guide to the user.

[1026] Instructions are given to the user via voice through a smart speaker or earphones.

[1027] User response

[1028] Step 9:

[1029] The user follows the instructions on the terminal and attempts to perform specific operations.

[1030] For example, try to perform a double jump by pressing the jump button twice in succession.

[1031] Step 10:

[1032] The result of the user's operation is sent to the server again.

[1033] If successful, the data will be recorded for future analysis, if unsuccessful, a more detailed explanation may be provided.

[1034] Example 1: Double jump

[1035] Step 1:

[1036] The user is unable to overcome a particular obstacle during gameplay and becomes stuck.

[1037] Step 2:

[1038] The server detects that the user has clicked the jump button multiple times but without success.

[1039] Step 3:

[1040] The server determines that an explanation of double jumping is required and generates a request.

[1041] Step 4:

[1042] The server sends the request to the terminal.

[1043] Step 5:

[1044] The device receives the request and prepares a voice prompt saying, "Please press the jump button twice in succession."

[1045] Step 6:

[1046] The terminal provides audio guidance to the user.

[1047] Step 7:

[1048] The user follows the audio guidance and presses the jump button twice in succession to successfully perform a double jump.

[1049] Example 2: Using a new skill (long-range attack)

[1050] Step 1:

[1051] A user acquires a new skill.

[1052] Step 2:

[1053] The server detects the acquisition of a new skill (ranged attack).

[1054] Step 3:

[1055] The server determines that "an explanation of how to use long-range attacks is required" and generates a request.

[1056] Step 4:

[1057] The server sends the request to the terminal.

[1058] Step 5:

[1059] The device receives the request and prepares a voice prompt saying, "Press the right stick to perform a long-range attack."

[1060] Step 6:

[1061] The terminal provides audio guidance to the user.

[1062] Step 7:

[1063] Users follow the voice prompts and push the right stick to perform long-range attacks.

[1064] In this way, the user can receive the necessary operating instructions at the appropriate time and progress smoothly through the game.

[1065] Example 1

[1066] 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."

[1067] Current game systems have difficulty providing appropriate operational instructions in real time when a user experiences difficulty with a specific operation or new skill. This can impair the user experience and stall game progress. Furthermore, the increased time required for the user to overcome the difficulty can reduce satisfaction with the game. Therefore, the present invention aims to improve the user experience by monitoring and analyzing the user's operation history and game progress in real time and providing operational instructions at the appropriate time.

[1068] 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.

[1069] In this invention, the server includes means for collecting a user's operation history and game progress status in real time, means for analyzing the operation history and game progress status using a machine learning model to detect when a specific operation has not been attempted for a long time or when the user is experiencing difficulty in a specific area, and means for generating a request for appropriate operation instructions based on the detected timing and sending the request to the terminal. This makes it possible to detect difficulties the user is experiencing while playing the game in real time and provide appropriate operation instructions at that moment.

[1070] "User operation history" is a record of the specific operations performed by the user when playing a game, including keyboard keystrokes, mouse movements, button clicks, and the like.

[1071] "Game progress" refers to information related to the progress of the game, such as the character's current position and status in the game, mission progress, and game area.

[1072] A "machine learning model" is a general term for algorithms that learn patterns and trends based on past data and make predictions and classifications for new data.

[1073] A "request for operation instructions" is a request to generate instructions including specific operation procedures and send them to the terminal when the user is experiencing difficulty in the game.

[1074] "Speech synthesis technology" is a technology that generates voices that mimic human voices based on text data, and is used to create audio guides.

[1075] "Terminal" refers to a device that provides audio guidance to the user, including smart speakers and earphones.

[1076] "Audio guide" refers to instructions provided by voice that guide the user through the operational procedures required in the game, and is intended to aid the user in understanding.

[1077] "New skills" refer to new abilities or techniques that a user acquires in the game and that the user must learn how to use.

[1078] MODE FOR CARRYING OUT THE INVENTION

[1079] This invention relates to a system that collects a user's operation history and game progress in real time and provides necessary operation instructions based on that data. Here, we will explain how to implement this system in detail. This system is mainly composed of three parties: a server, a terminal, and a user.

[1080] Server Processing

[1081] 1. Gathering game logs

[1082] The server collects game logs in real time. Specifically, it uses an API and a database to collect user operation history (keystrokes, mouse movements, button clicks, etc.) and game progress (character status, progress, current game area). This data is necessary to understand the user's in-game behavior.

[1083] 2. Data Analysis

[1084] The server analyzes user behavior based on the collected data, using machine learning models (e.g., clustering and trend analysis algorithms) to detect when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area.

[1085] 3. Request Generation

[1086] The server uses the analysis results to determine when and how the user needs to be instructed on what operations. For example, if the user has been trying to jump in the same place for more than five minutes, the server detects this and generates a request indicating the need for a double jump. This request includes specific instructions and the reasons for them.

[1087] Terminal handling

[1088] 1. Receiving requests and preparing audio guides

[1089] The device (smart speaker or earphones) receives a request for operation instructions from the server. It uses speech synthesis technology (e.g., Google Text-to-Speech or Amazon Polly) to generate audio guidance based on the request. This audio guidance includes specific operation procedures.

[1090] 2. Provision of audio guides

[1091] The device provides the generated voice guidance to the user. For example, it transmits instructions such as "Please press the jump button twice in succession" in real time through earphones. This allows the user to follow the voice guidance and perform the appropriate operation.

[1092] User response

[1093] 1. Gameplay

[1094] The user plays the game as usual, but if they encounter a difficult situation or don't know how to perform a particular operation, they try it out on the spot.

[1095] 2. Audio guide execution

[1096] The user attempts to perform specific operations according to the voice guidance provided by the device. For example, by following the instruction to "press the jump button twice in succession," the user can successfully perform a double jump.

[1097] 3. Providing Feedback

[1098] If the user follows the instructions and the operation is successful, the information is sent back to the server. For example, a log stating "double jump successful" is sent to the server. This feedback will be used for future data analysis and contribute to improving the accuracy of the system.

[1099] Specific examples

[1100] Example 1: Performing a double jump

[1101] Let's assume that the user is having trouble progressing in a particular area.

[1102] 1. The server detects that the user has been attempting to jump in the same location for more than 5 minutes and generates a request for a "need for a double jump."

[1103] 2. The device receives the request, generates a voice prompt saying "Please press the jump button twice in succession," and conveys this to the user through the smart speaker.

[1104] 3. The user follows the audio guidance and presses the jump button twice in succession to perform a double jump and proceed to the next area.

[1105] Example 2: Using long-range attack skills

[1106] Suppose a user acquires a new skill and doesn't know how to use it.

[1107] 1. The server detects that the user has acquired a new skill (ranged attack) and generates a request for it.

[1108] 2. The device receives the request and generates and provides a voice prompt saying, "Press the right stick to perform a long-range attack."

[1109] 3. Following the voice guidance, the user presses the right stick to attempt a long-range attack and succeeds.

[1110] Specific examples of prompts

[1111] Below are some example prompts to input to the generative AI model for the system:

[1112] Please describe this system. The server collects game logs in real time and analyzes the user's operation history and game progress. At specific times, it generates and sends a request for audio guidance to the device. The device prepares audio guidance based on the request and provides it to the user. For example, if the user experiences difficulty, the server detects that situation and generates guidance instructing the user to press the jump button twice in succession.

[1113] As described above, implementing the present invention requires the ability to collect and analyze the user's operation history and game progress in real time, as well as the ability to provide audio guidance at appropriate times, which enables real-time operation explanations and significantly improves the user experience.

[1114] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1115] Step 1:

[1116] Gathering game logs

[1117] The server collects the user's operation history and game progress in real time. During this process, the game inputs operation data (keystrokes, mouse movements, button clicks, etc.) from the game. This data is collected via API and database and stored on the server. For example, the number of times the jump button was pressed and the character's current position are recorded. This makes it possible to monitor what operations the user is performing within the game.

[1118] Step 2:

[1119] Data analysis

[1120] The server analyzes the collected operation history and game progress using a machine learning model. The game logs collected in step 1 are used as input for this process. The analysis uses clustering algorithms and trend analysis algorithms to detect when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area. For example, a pattern such as "the user has been trying to jump in the same place for five minutes without success" can be detected. This makes it possible to identify when the user is experiencing difficulty.

[1121] Step 3:

[1122] Request Generation

[1123] Based on the analysis results from step 2, the server detects when instructions are needed and generates a request containing specific instructions. The input to this process is the information obtained through data analysis. The output is a request containing specific operating procedures and the reasons for them. For example, a request stating "double jump required" is created. This prepares the device to provide appropriate operating instructions to the user.

[1124] Step 4:

[1125] Receiving requests and preparing audio guides

[1126] The device receives a request for operation instructions from the server and prepares audio guidance based on the request. The input for this process is the request sent from the server. The device uses speech synthesis technology (e.g., Google Text-to-Speech or Amazon Polly) to generate audio guidance based on the request. The output is an audio guidance message. For example, an audio guidance message such as "Press the jump button twice in succession" is created. This completes the guidance for the user to perform the appropriate operation.

[1127] Step 5:

[1128] Audio guide provided

[1129] The device provides the generated audio guide to the user. The input of this process is the audio guide generated in step 4. The device provides the audio guide to the user through a smart speaker or earphones. The output includes the audio guide received by the user. For example, an instruction such as "Please press the jump button twice in succession" may be conveyed to the user through the earphones. This allows the user to receive instructions on how to operate the device in real time.

[1130] Step 6:

[1131] Execute audio guide

[1132] The user attempts to perform a specific operation according to the voice guidance provided by the device. The input to this process is the voice guidance provided by the device. Based on the instructions, the user performs a specific operation (for example, pressing the jump button twice in succession). The output includes the result of whether the user succeeded or failed in the operation. This allows the user to learn difficult operations or how to use new skills.

[1133] Step 7:

[1134] Providing Feedback

[1135] If the user successfully performs the instructed operation, that information is sent back to the server. The input to this process is the result of the user's operation. For example, a log stating "double jump successful" is sent to the server. The output is this feedback information, which is recorded on the server. Based on this feedback, the server can improve the accuracy of future analysis. This continuously improves the efficiency of the entire system.

[1136] (Application example 1)

[1137] 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."

[1138] Mistakes made by workers in factories and incorrect work procedures can lead to reduced production efficiency and safety risks. Furthermore, it is difficult to learn new operating procedures and how to use machines in real time, which causes further problems. Traditional textbooks and manuals do not allow for immediate response, and it takes time for workers to learn the correct operating methods.

[1139] 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.

[1140] In this invention, the server includes means for collecting the user's operation history and status in real time, means for analyzing the operation history and status and detecting the timing when operation instructions are required, means for generating an operation instruction request based on the detected timing and sending it to the terminal, and means for receiving the request, preparing visual and audio guides, and providing them to the user. This makes it possible to correct operational errors and errors in work procedures by workers in the factory in real time, and to progress work efficiently and safely.

[1141] An "operation history" is a record of a series of operations and actions performed by a user.

[1142] The "situation" is the totality of the environment in which the user is currently placed and the work that is currently in progress.

[1143] "Collecting in real time" means collecting operation history and status immediately without delay.

[1144] "Analysis" is the process of analyzing collected data to find specific patterns and trends.

[1145] "Detection" refers to the identification of a particular condition or event from the results of an analysis.

[1146] "Operation instructions" are specific operating procedures and methods provided to the user.

[1147] "Generating a request" means creating a necessary operation instruction and creating a request to provide it.

[1148] A "terminal" is a device or apparatus that receives a request for operation instructions and provides visual and audio guidance to the user.

[1149] A "visual guide" is a means of conveying operating procedures and information to users graphically.

[1150] "Audio guide" is a means of conveying operational procedures and information to the user by voice.

[1151] "User" refers to the worker or operator who uses the system and receives instructions on how to operate it.

[1152] This invention is a system for correcting worker errors and errors in work procedures in real time in a factory, ensuring efficient and safe work progress. This system mainly operates in cooperation with three parties: a server, a terminal, and a user.

[1153] System configuration

[1154] The system mainly consists of the following elements:

[1155] 1. Server: Collects the user's operation history and status in real time and detects when operation instructions are required. The server generates a request for operation instructions and sends it to the device.

[1156] 2. Terminal: Receives requests from the server, prepares visual and audio guides, and provides them to the user. The terminal can be a smart glass or other visual and audio output device.

[1157] 3. User: A worker who performs work in a factory. The user follows visual and audio guidance to carry out the correct work procedures.

[1158] Program processing

[1159] Server Processing

[1160] The server does the following:

[1161] 1. Data collection: Collect worker movements in real time from cameras and sensors in the factory (e.g., Azure Kinect, Microsoft Azure IoT Hub), including worker behavior data and the status of the work being performed.

[1162] 2. Analysis and detection: The collected data is analyzed using Google Cloud Dataflow and Azure Machine Learning to detect whether specific work procedures are being performed correctly based on the user's operation history and situation.

[1163] 3. Request generation: If the correct operating procedure is not performed, a request for operating instructions is generated based on the timing and sent to the terminal.

[1164] Terminal handling

[1165] The terminal does the following:

[1166] 1. Request reception and preparation: Smart glasses (e.g., Google Glass, Epson Moverio) receive a request for operation instructions from the server and prepare visual and audio guidance. Amazon Polly is used for speech synthesis.

[1167] 2. Providing visual and audio guidance: The device displays visual guidance on the screen and provides audio guidance, which helps users understand specific work procedures.

[1168] User response

[1169] The user takes the following actions:

[1170] 1. Task execution: The user follows the visual and audio guidance provided by the smart glasses to perform the correct task steps.

[1171] 2. Providing feedback: The progress of the work is reported to the server, and information about successes and failures is used again for data collection and analysis.

[1172] Specific examples

[1173] For example:

[1174] 1. Palletizing Guide:

[1175] The server detects incorrect movements when workers lift loads.

[1176] The server generates an instruction for operation such as "Next, carefully lift the luggage and place it in the designated location" and sends it to the terminal.

[1177] The device provides audio guidance along with visual guidance.

[1178] The user follows the guide and places the luggage in the correct position.

[1179] 2. Learning how to operate a new machine:

[1180] The server detects mistakes made by workers as they try out new ways of operating machines.

[1181] The server generates operating instructions such as "To operate this machine, first press the red button and then pull the lever" and sends them to the terminal.

[1182] The device provides visual and audio guidance through smart glasses.

[1183] Users follow the guide to learn the correct operating procedures.

[1184] As a result, it is possible to reduce work errors in the factory and perform work safely and efficiently.

[1185] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1186] Step 1:

[1187] The server collects worker movement data in real time using cameras and sensors (e.g., Azure Kinect, Microsoft Azure IoT Hub) in the factory. The input is raw data from the cameras and sensors, and the output is a log of worker movement. Specifically, it records video data captured by cameras and movement data acquired by sensors.

[1188] Step 2:

[1189] The server analyzes the collected operation data using a data analysis platform (e.g., Google Cloud Dataflow, Azure Machine Learning). The input here is the operation log, and the output is the analysis result, i.e., a determination of whether a specific work procedure was performed correctly. Specifically, an AI model is used to analyze operation patterns and detect mistakes or incorrect operations.

[1190] Step 3:

[1191] The server generates a request for operation instructions based on the analysis results and sends it to the terminal. The input is the analysis results, and the output is an operation instruction request. Specifically, it generates text information about appropriate operation procedures and actions that need to be corrected.

[1192] Step 4:

[1193] The device receives the operation instruction request sent from the server and prepares the audio guide using speech synthesis software (e.g., Amazon Polly). The input is the operation instruction request, and the output is the audio guide and visual guide. Specifically, the device converts the request into text and prepares to display it on the screen as visual information.

[1194] Step 5:

[1195] The terminal provides the prepared visual and audio guide to the user. The input is the audio and visual guide data, and the output is the display and audio output to convey it to the user. Specifically, the smart glasses display text and illustrated procedures, as well as audio instructions, so that the worker can receive them.

[1196] Step 6:

[1197] The user performs specific tasks according to the visual and audio guidance provided by the terminal. The input is the visual and audio guidance, and the output is the accurate execution of the work procedure. Specifically, the user performs the task according to the guidance and checks the results.

[1198] Step 7:

[1199] The results of the user's work are fed back to the server. The input is the work result, and the output is feedback data to the server. Specifically, the success or failure of the work and its details are sent to the server to help with future improvements.

[1200] 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.

[1201] This invention relates to a system that analyzes the user's behavior and emotional state in real time in a game and provides operation instructions at the appropriate time to improve the user experience. This system operates in cooperation with the server, the terminal, and the user.

[1202] System configuration

[1203] First, we will explain the system configuration. This system mainly consists of the following elements:

[1204] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. It also includes an emotion engine to recognize the user's emotional state. The server detects when operation instructions are required and generates an instruction request. The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data.

[1205] 2. Device: Receives requests from the server, prepares audio guides, and provides them to the user. The device can be a smart speaker or earphones. If the user is in a negative emotional state, the device adjusts the content and tone of the audio guide.

[1206] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[1207] Program processing

[1208] The program processing that realizes this is explained in natural language, and the behavior of the server, terminal, and user is described in detail.

[1209] Server Processing

[1210] 1. Data collection: The server collects game logs in real time. Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[1211] 2. Emotion Recognition: The server recognizes the user's emotional state using an emotion engine, which uses facial expression analysis, voice analysis, or vital sign data of the user.

[1212] 3. Analysis and Detection: The server analyzes the collected operation history and progress as well as the recognized emotion data to detect when a specific operation has not been performed successfully for a long time or when the user is stagnating in a particular area.

[1213] 4. Request Generation: The server generates a request for operation instructions based on the detection results and the emotional state. For example, it generates a specific request such as "double jump required."

[1214] Terminal handling

[1215] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[1216] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. If the user's emotional state is negative, the content and tone of the audio guidance will be adjusted.

[1217] User response

[1218] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[1219] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[1220] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis, and if unsuccessful, a more detailed explanation may be provided.

[1221] Specific examples

[1222] Example 1: Performing a double jump

[1223] Let's say a user is having trouble progressing in a particular area.

[1224] 1. Server: Detects when a user has been trying to jump in the same place for more than five minutes without success. The emotion engine also analyzes the user's facial expressions and recognizes frustration.

[1225] 2. Server: Sends a request for instructions, "Explain how to double jump," and information that "the user is frustrated" to the device.

[1226] 3. Device: Receive the request and prepare a voice prompt saying "Please press the jump button twice in succession," and provide it in a gentle tone depending on the user's emotional state.

[1227] 4. User: Follow the audio guide and press the jump button twice in succession to perform a double jump and proceed to the next area.

[1228] Example 2: Using a new skill (long-range attack)

[1229] A user acquires a new skill and doesn't know how to use it.

[1230] 1. Server: Detects when a user acquires a new skill (long-range attack). Also, the emotion engine recognizes the emotion of anxiety from the user's vital sign data.

[1231] 2. Server: Sends a request for operation instructions, "Explain how to use long-range attacks," and information about "the user's anxiety," to the device.

[1232] 3. Device: Receive the request and prepare a voice prompt saying "Press the right stick to perform a ranged attack" in a reassuring tone depending on the emotional state.

[1233] 4. User: Follow the voice prompts and press the right stick to perform a long-range attack.

[1234] In this way, users can receive real-time instructions and emotional support to smoothly progress through the game, which greatly improves the user experience and reduces the costs and efforts of game developers.

[1235] The processing flow will be explained below.

[1236] Program processing steps

[1237] Server Processing

[1238] Step 1:

[1239] The server collects game logs in real time.

[1240] Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[1241] Step 2:

[1242] The server uses an emotion engine to recognize the user's emotional state in real time.

[1243] The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data of the user.

[1244] Step 3:

[1245] The server analyzes the collected operation history and progress as well as the recognized emotion data.

[1246] Specifically, it checks if a particular operation has not been successful for a long time or if the user is stuck in a particular area.

[1247] Step 4:

[1248] The server detects when an instruction for operation is required.

[1249] For example, if the user has been trying to jump in the same place for more than five minutes without success, it is determined that an instruction on how to jump is necessary.

[1250] Step 5:

[1251] The server generates a request for operation instructions based on the detection result and the emotional state.

[1252] Specifically, information such as "a double jump is required" or "the user is feeling frustrated" is generated as a request.

[1253] Step 6:

[1254] The server transmits the generated request to the terminal.

[1255] Terminal handling

[1256] Step 7:

[1257] The terminal receives a request for operation instructions from the server.

[1258] Step 8:

[1259] The terminal prepares audio guidance based on the received request.

[1260] Specifically, instructions such as "Press the jump button twice in succession" are converted into voice using speech synthesis technology.

[1261] Step 9:

[1262] The terminal adjusts the tone of the audio guide according to the user's emotional state.

[1263] For example, if the user is feeling frustrated, prepare a voice prompt with a gentle tone.

[1264] Step 10:

[1265] The device provides the prepared audio guide to the user through a smart speaker or earphones.

[1266] User response

[1267] Step 11:

[1268] The user follows the voice guidance provided by the terminal and attempts to perform specific operations.

[1269] For example, try to perform a double jump by pressing the jump button twice in succession.

[1270] Step 12:

[1271] The result of the user's operation is sent to the server again.

[1272] If successful, the information will be recorded for future analysis, if unsuccessful a more detailed explanation may be provided.

[1273] Example 1: Double jump

[1274] Step 1:

[1275] The user is unable to overcome a particular obstacle during gameplay and becomes stuck.

[1276] Step 2:

[1277] The server detects that the user has clicked the jump button multiple times but without success.

[1278] Step 3:

[1279] The server uses an emotion engine to analyze the user's facial expressions and recognize the emotion of frustration.

[1280] Step 4:

[1281] The server sends the information "explain how to double jump" and "the user is feeling frustrated" as a request to the terminal.

[1282] Step 5:

[1283] The device receives the request and prepares a voice prompt saying, "Please press the jump button twice in succession."

[1284] Step 6:

[1285] The device recognizes that the user is frustrated and provides voice guidance in a gentle tone.

[1286] Step 7:

[1287] The user follows the audio guidance and presses the jump button twice in succession to perform a double jump and proceed to the next area.

[1288] Example 2: Using a new skill (long-range attack)

[1289] Step 1:

[1290] A user acquires a new skill.

[1291] Step 2:

[1292] The server detects the acquisition of a new skill (ranged attack).

[1293] Step 3:

[1294] The server uses an emotion engine to analyze the user's vital sign data and recognize emotions of anxiety.

[1295] Step 4:

[1296] The server sends the information "explain how to use long-range attacks" and "the user feels anxious" as a request to the terminal.

[1297] Step 5:

[1298] The device receives the request and prepares a voice prompt saying, "Press the right stick to perform a long-range attack."

[1299] Step 6:

[1300] The terminal recognizes that the user is feeling anxious and provides audio guidance in a reassuring tone.

[1301] Step 7:

[1302] Users follow the voice prompts and push the right stick to perform long-range attacks.

[1303] Example 2

[1304] 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."

[1305] Conventional game systems struggle to provide timely explanations of in-game operations that can easily confuse users or how to use new skills. Furthermore, when a user becomes stuck on a particular operation or area, this can be due to emotional factors, but the system lacks the ability to detect this in real time and take appropriate action. Furthermore, explanations that are not tailored to the user's emotional state can increase anxiety and frustration, detracting from the game experience.

[1306] 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.

[1307] In this invention, the server includes means for collecting a user's operation history and game progress status in real time, means for analyzing the operation history and game progress status and detecting timing when operation instructions are required, means for generating an operation instruction request based on the detected timing and sending it to the terminal, means for recognizing the user's emotional state using an emotion engine, and means for adjusting the content and tone of audio guidance based on the emotional state. This allows the user to receive operation instructions in the game at appropriate timing according to their emotions, improving the game experience.

[1308] The "user operation history" is a record of a series of operations performed by the user during the game. Specifically, this includes the number of clicks of the jump button, the direction of movement, attack actions, and so on.

[1309] "Game progress" refers to information about the progress of the game, such as the character's position in the game, progress, and acquired items.

[1310] The "emotion engine" is an analysis engine for recognizing the user's emotional state. Specifically, it analyzes facial expressions, voice, and vital sign data.

[1311] An "operation instruction request" is a request generated by a server to instruct a user on how to perform a particular operation.

[1312] "Audio guide" refers to audio instructions and explanations provided to the user by a device. The content and tone may be adjusted to make the instructions easier for the user to understand.

[1313] A "terminal" is a device that receives a request for operation instructions from the server, prepares audio guidance, and provides it to the user. This includes smart speakers and earphones.

[1314] "Emotional state" refers to the user's current feelings, including frustration, anxiety, joy, etc.

[1315] This invention relates to a system that analyzes the user's behavior and emotional state in real time in a game and provides operation instructions at the appropriate time to improve the user experience. This system operates in cooperation with the server, the terminal, and the user.

[1316] System configuration

[1317] The system mainly consists of the following elements:

[1318] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. It also includes an emotion engine to recognize the user's emotional state. The server detects when operation instructions are required and generates an instruction request. The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data.

[1319] 2. Device: Receives requests from the server, prepares audio guides, and provides them to the user. The device can be a smart speaker or earphones. If the user is in a negative emotional state, the device adjusts the content and tone of the audio guide.

[1320] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[1321] Server Processing

[1322] 1. Data collection: The server collects game logs in real time. Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[1323] 2. Emotion Recognition: The server uses an emotion engine to recognize the user's emotional state, which can be achieved by analyzing the user's facial expressions, voice, or vital sign data.

[1324] 3. Analysis and Detection: The server analyzes the collected operation history and progress as well as the recognized emotion data to detect when a specific operation has not been performed successfully for a long time or when the user is stagnating in a particular area.

[1325] 4. Request Generation: The server generates a request for operation instructions based on the detection results and the emotional state. For example, it generates a specific request such as "double jump required."

[1326] Terminal handling

[1327] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[1328] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. If the user's emotional state is negative, the content and tone of the audio guidance will be adjusted.

[1329] User response

[1330] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[1331] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[1332] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis, and if unsuccessful, a more detailed explanation may be provided.

[1333] Specific examples

[1334] Example 1: Performing a double jump

[1335] Let's say a user is having trouble progressing in a particular area.

[1336] 1. Server: Detects when a user has been trying to jump in the same place for more than five minutes without success. The emotion engine also analyzes the user's facial expressions and recognizes frustration.

[1337] 2. Server: Sends a request for instructions, "Explain how to double jump," and information that "the user is frustrated" to the device.

[1338] 3. Device: Receive the request and prepare a voice prompt saying "Please press the jump button twice in succession," and provide it in a gentle tone depending on the user's emotional state.

[1339] 4. User: Follow the audio guide and press the jump button twice in succession to perform a double jump and proceed to the next area.

[1340] Example 2: Using a new skill (long-range attack)

[1341] A user acquires a new skill and doesn't know how to use it.

[1342] 1. Server: Detects when a user acquires a new skill (long-range attack). Also, the emotion engine recognizes the emotion of anxiety from the user's vital sign data.

[1343] 2. Server: Sends a request for operation instructions, "Explain how to use long-range attacks," and information about "the user's anxiety," to the device.

[1344] 3. Device: Receive the request and prepare a voice prompt saying "Press the right stick to perform a ranged attack" in a reassuring tone depending on the emotional state.

[1345] 4. User: Follow the voice prompts and press the right stick to perform a long-range attack.

[1346] In this way, users can receive real-time instructions and support tailored to their emotional state, allowing them to progress smoothly through the game, significantly improving the user experience and reducing support costs for game developers.

[1347] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1348] Step 1: Data collection

[1349] The server collects game logs in real time. As input, it receives the user's operation history (number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.). The server records this data and accumulates it in a data store for subsequent analysis. Specific operations include receiving and saving log data.

[1350] Step 2: Recognize emotions

[1351] The server uses an emotion engine to recognize the user's emotional state. As input, it receives the user's facial expression data, voice data, and vital sign data. The emotion engine analyzes these data and identifies the user's emotional state (frustration, anxiety, joy, etc.). As output, it generates recognized emotion data, which is passed to the next analysis step. Specifically, it performs data analysis using a face recognition module and a voice analysis module.

[1352] Step 3: Analysis and detection

[1353] The server integrates and analyzes the collected operation history, game progress, and emotional data. It receives the above operation history, game progress, and emotional data as input. It integrates the data and detects when a specific operation has not been successful for a long time or when the user is stuck in a specific area. It generates problem identification results (e.g., the user is having difficulty jumping) as output. Specific operations include problem detection using database queries and machine learning algorithms.

[1354] Step 4: Request Generation

[1355] The server generates a request for operation instructions based on the detection results and the emotional state. As input, it receives the detected problem and emotional data. It generates a specific request, such as "double jump required" or "the user is feeling frustrated." As output, it sends the generated request to the terminal. As a specific operation, it creates a specific instruction sentence using a text generation engine and sends the request to the terminal using a communication module.

[1356] Step 5: Receiving and preparing the request

[1357] The device receives a request for operation instructions from the server. As input, it receives the request data sent from the server. Based on that content, it prepares audio guidance. It uses speech synthesis technology to convert the text instructions into speech. It prepares the generated audio data as output. Specifically, it calls a speech synthesis API to generate the audio data.

[1358] Step 6: Provide audio guides

[1359] The terminal provides audio guidance to the user through a smart speaker or earphones. As input, it receives prepared audio data. The content and tone of the audio guidance are adjusted according to the user's emotional state. As output, it provides specific audio instructions to the user. As a specific operation, it uses an audio playback module to play the audio guidance to the user.

[1360] Step 7: Gameplay

[1361] The user plays the game as usual. As input, they receive audio guidance provided by the device. If they are unsure of how to operate the device, they try and error on the spot. As output, a new operation history and game progress status are generated. As a specific operation, they operate the game controller and perform actions in the game.

[1362] Step 8: Receive and follow the audio guide

[1363] The user attempts specific operations according to the voice guidance provided by the device. As input, the user receives the instructions from the voice guidance. For example, the user attempts a double jump by pressing the jump button twice in succession. As output, a history of successful operations is generated. As a specific action, the user operates the game controller as instructed.

[1364] Step 9: Provide feedback

[1365] If the user successfully performs an operation, that information is sent to the server. As input, it receives information about whether the operation was successful or unsuccessful. The server analyzes this feedback information and checks whether the operation was performed correctly. As output, it generates a request indicating success or if further explanation is required. Specifically, when the operation is successful, it obtains satisfaction data from the vital sign data and sends it to the server.

[1366] (Application example 2)

[1367] 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."

[1368] Current security monitoring systems lack the ability to analyze users' real-time behavior and emotional state and provide appropriate responses. Furthermore, there is no system that can immediately guide users to appropriate measures when they feel stressed or anxious, making it difficult to provide efficient responses to ensure users' safety. This increases the risk of users being exposed to unstable situations.

[1369] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting a user's operation history and progress status in real time, means for analyzing the operation history and progress status and detecting a timing when an explanation is needed, means for generating an explanation request based on the detected timing and transmitting it to the terminal, means for receiving the request, preparing audio guidance, and providing it to the user, means for analyzing the user's behavior and emotional state, means for detecting a situation in which the user feels anxious or stressed, and generating a request for an appropriate response method, and means for collecting user location information and video data in real time and analyzing the security situation. This makes it possible to quickly provide an appropriate response method when the user feels anxious or stressed.

[1370] An "operation history" is a record of specific actions and operations performed by a user.

[1371] "Progress" is a record of the status that indicates how far a task or process has progressed.

[1372] The "timing when an explanation is required" refers to a time or situation when a user does not understand a particular operation or action and an explanation is required.

[1373] "Request" refers to a request for a specific operation or description of an action.

[1374] A "terminal" is a device that connects a server and a user and provides information such as audio guides.

[1375] "Audio guide" provides the user with audio instructions on specific operations and actions.

[1376] "Behavior" refers to a specific movement or activity taken by a user.

[1377] "Emotional state" indicates the type and strength of the user's emotion.

[1378] An "anxious or stressful situation" is a specific situation or environment in which a user feels psychological anxiety or tension.

[1379] "Appropriate response method" refers to instructions for the most appropriate procedure or action depending on the user's situation and emotions.

[1380] "Location information" is data that indicates the user's current geographical location.

[1381] "Video Data" refers to image or video data collected by a camera or other image capture device.

[1382] "Security situation" refers to the state of the environment or situation regarding safety.

[1383] This invention relates to a system that analyzes a user's operation history and emotional state in real time to implement a security monitoring system, and provides appropriate responses as audio guidance when the user feels anxious or stressed. This system operates in cooperation with a server, a terminal, and a user.

[1384] System configuration

[1385] The system mainly consists of the following components:

[1386] 1. Server: Collects and analyzes the user's operation history and progress in real time. It also has an emotion engine and recognizes the user's emotional state (specifically, anxiety or stress). It also analyzes security-related situations and generates requests for appropriate responses. The emotion engine and analysis tools used are Google Cloud's "AutoML Vision" and "AutoML Natural Language."

[1387] 2. Terminal: Receives requests from the server, prepares audio guides, and provides them to the user. Using speech synthesis technology, it converts instructions on the appropriate response method into speech. Google Cloud Text-to-Speech is used as the speech synthesis technology.

[1388] 3. User: Uses a device such as a smartphone or earphones to perform normal operations and actions. If the user feels anxious or stressed, they follow the voice guidance provided by the device to take appropriate measures. The voice guidance is provided in a reassuring tone to help the user take safe actions.

[1389] Program implementation steps

[1390] The server collects location information, camera footage, and microphone audio from the smartphone in real time. The emotion engine recognizes and analyzes the user's emotional state from the camera footage and microphone audio. It detects situations in which the user feels anxious or stressed and generates a request for how to respond (for example, directions to the nearest police station or directions to a safe route). The generated request is sent to the device, which uses speech synthesis technology to convert the instructions into voice and provide it to the user.

[1391] Specific examples

[1392] Example 1: Presence of a suspicious person

[1393] 1. Server: The user finds a suspicious person and analyzes emotions of fear and anxiety from camera footage and microphone audio.

[1394] 2. Server: Detects situations where the user is feeling anxious and generates a request to "show the location of the nearest police box."

[1395] 3. Device: Receives the request and prepares and provides an audio guide saying, "Don't worry, the nearest police box is located at XX. Head there immediately."

[1396] 4. User: Follow the audio guide and head immediately to the designated police box.

[1397] Example 2: Staying in a dark place late at night

[1398] 1. Server: Detects anxious facial expressions and voice when the user is in a dark place late at night.

[1399] 2. Server: Detects that the user is feeling anxious and needs guidance on a safe route, and generates the corresponding request.

[1400] 3. Terminal: Receives requests and provides voice guidance on safe routes.

[1401] 4. User: Follow the voice guidance to find a safe route and return home safely.

[1402] Example prompts to input to the generative AI model

[1403] "You are developing a smartphone application that analyzes the user's emotions from camera footage and audio data, and provides appropriate guidance on how to respond when the user feels anxious or stressed. Please generate the following audio guidance."

[1404] This system allows users to receive real-time guidance on appropriate response methods, enabling them to respond quickly and accurately to security risks.

[1405] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1406] Step 1: Data collection

[1407] The server collects location information, camera footage, and microphone audio from the smartphone in real time. These data are the basis for analyzing the user's behavior and emotional state. The input is location information, camera footage, and microphone audio, which are sent to the server. The output is that these data are stored on the server.

[1408] Step 2: Recognize emotions

[1409] The server sends the collected camera footage and microphone audio to the emotion engine to recognize the user's emotional state. Specifically, it uses AutoML Vision and AutoML Natural Language to analyze facial expressions and tone of voice. The input is the collected video and audio data, and the output is a judgment of the user's emotional state (e.g., anxiety, stress, relief, etc.).

[1410] Step 3: Detect security conditions

[1411] The server analyzes whether the user is in a dangerous situation (e.g., the presence of a suspicious person, being in a dark place) based on location information and emotional state data. Specifically, it detects this by comparing the current location with information on pre-defined safe and dangerous areas. The input is the location information and the result of the emotional state determination, and the output is the result of the determination of whether the situation is dangerous or safe.

[1412] Step 4: Generate a response request

[1413] If the server determines that the user is in a dangerous situation, it generates a request for an appropriate response (e.g., information about a nearby police station or a safe route). The content of the request is determined based on the user's current location information and the dangerous situation. The input is the location information and the result of the dangerous situation determination, and the output is a request for an appropriate response.

[1414] Step 5: Submit your request and prepare your audio guide

[1415] The device receives the response request sent from the server and prepares the audio guide. It converts the request into audio using Google Cloud Text-to-Speech. The input is the response request, and the output is the audio guide data.

[1416] Step 6: Provide audio guides

[1417] The device provides the audio guide to the user through a smartphone or earphone. If the user feels anxious, the audio guide is provided in a reassuring tone. The input is the audio guide data, and the output is the provision of the audio guide to the user.

[1418] Step 7: User Behavior

[1419] The user follows the voice guidance provided by the device and takes appropriate action. For example, heading to the nearest police station or following a safe route. The user's actions are fed back to the server and used for future analysis. The input is the content of the voice guidance, and the output is the user's specific actions.

[1420] 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.

[1421] 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.

[1422] 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.

[1423] [Fourth embodiment]

[1424] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1425] 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.

[1426] 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).

[1427] 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.

[1428] 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.

[1429] 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).

[1430] 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.

[1431] 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.

[1432] 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.

[1433] 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.

[1434] 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.

[1435] 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.

[1436] 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."

[1437] The present invention relates to a system that analyzes user behavior in a game in real time and provides operation instructions at appropriate times to improve the user experience. This system operates in cooperation with a server, a terminal, and a user.

[1438] System configuration

[1439] First, we will explain the system configuration. This system mainly consists of the following elements:

[1440] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. The server detects when operation instructions are required and generates a request for operation instructions.

[1441] 2. Terminal: Receives requests from the server, prepares audio guides, and provides them to the user. The terminal can be a smart speaker or earphones.

[1442] 3. User: The end user who plays the game. They follow audio prompts to learn difficult tasks or new skills.

[1443] Program processing

[1444] The program processing that realizes this is explained in natural language, and the behavior of the server, terminal, and user is described in detail.

[1445] Server Processing

[1446] 1. Data collection: The server collects game logs in real time, specifically recording user operation history (keystrokes, mouse movements, button clicks, etc.) and game progress (progress, character status, current game area).

[1447] 2. Analysis and Detection: The server analyzes the user's progress and operation history based on the collected data, detecting when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area.

[1448] 3. Request generation: The server generates a request for appropriate operation instructions based on the detected timing. For example, it specifies information such as "double jump is required."

[1449] Terminal handling

[1450] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[1451] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. For example, the device tells the user, "Here, press the jump button twice in succession."

[1452] User response

[1453] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[1454] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[1455] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis.

[1456] Specific examples

[1457] Example 1: Performing a double jump

[1458] Let's say a user is having trouble progressing in a particular area.

[1459] 1. Server: Detects that the user has been attempting to jump in the same place for more than 5 minutes and generates a request for a "need for a double jump."

[1460] 2. Device: Receives the request, generates a voice prompt saying "Please press the jump button twice in succession," and conveys this to the user through the smart speaker.

[1461] 3. User: Follow the voice guidance and press the jump button twice in rapid succession to perform a double jump and proceed to the next area.

[1462] Example 2: Using long-range attack skills

[1463] A user acquires a new skill and doesn't know how to use it.

[1464] 1. Server: Detects that the user has acquired a new skill (ranged attack) and generates a request for it.

[1465] 2. Device: Receives the request and generates and provides a voice prompt saying, "Press the right stick to perform a long-range attack."

[1466] 3. User: Follow the voice prompts and press the right stick to attempt a long-range attack and succeed.

[1467] In this way, users can receive real-time instructions and smoothly progress through the game, which greatly improves the user experience and reduces the costs and efforts of game developers.

[1468] The processing flow will be explained below.

[1469] Program processing steps

[1470] Server Processing

[1471] Step 1:

[1472] The server collects game logs in real time.

[1473] Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[1474] Step 2:

[1475] The server analyzes the collected operation history and progress.

[1476] Specifically, it analyzes whether a particular operation has not been successful for a long time or whether the user is stagnating in a particular area.

[1477] Step 3:

[1478] The server detects when an instruction for operation is required.

[1479] Specifically, this applies when a user is repeatedly performing a particular action without success, or when they have difficulty applying a new skill immediately after acquiring it.

[1480] Step 4:

[1481] The server generates a request for operation instructions based on the detection result.

[1482] For example, generate a specific request such as "Explain how to do a double jump."

[1483] Step 5:

[1484] The server transmits the generated request to the terminal.

[1485] Terminal handling

[1486] Step 6:

[1487] The terminal receives a request for operation instructions from the server.

[1488] Step 7:

[1489] The terminal prepares audio guidance based on the received request.

[1490] Specifically, specific instructions such as "Press the jump button twice in succession" are generated as an audio file using voice synthesis technology.

[1491] Step 8:

[1492] The terminal provides the prepared audio guide to the user.

[1493] Instructions are given to the user via voice through a smart speaker or earphones.

[1494] User response

[1495] Step 9:

[1496] The user follows the instructions on the terminal and attempts to perform specific operations.

[1497] For example, try to perform a double jump by pressing the jump button twice in succession.

[1498] Step 10:

[1499] The result of the user's operation is sent to the server again.

[1500] If successful, the data will be recorded for future analysis, if unsuccessful, a more detailed explanation may be provided.

[1501] Example 1: Double jump

[1502] Step 1:

[1503] The user is unable to overcome a particular obstacle during gameplay and becomes stuck.

[1504] Step 2:

[1505] The server detects that the user has clicked the jump button multiple times but without success.

[1506] Step 3:

[1507] The server determines that an explanation of double jumping is required and generates a request.

[1508] Step 4:

[1509] The server sends the request to the terminal.

[1510] Step 5:

[1511] The device receives the request and prepares a voice prompt saying, "Please press the jump button twice in succession."

[1512] Step 6:

[1513] The terminal provides audio guidance to the user.

[1514] Step 7:

[1515] The user follows the audio guidance and presses the jump button twice in succession to successfully perform a double jump.

[1516] Example 2: Using a new skill (long-range attack)

[1517] Step 1:

[1518] A user acquires a new skill.

[1519] Step 2:

[1520] The server detects the acquisition of a new skill (ranged attack).

[1521] Step 3:

[1522] The server determines that "an explanation of how to use long-range attacks is required" and generates a request.

[1523] Step 4:

[1524] The server sends the request to the terminal.

[1525] Step 5:

[1526] The device receives the request and prepares a voice prompt saying, "Press the right stick to perform a long-range attack."

[1527] Step 6:

[1528] The terminal provides audio guidance to the user.

[1529] Step 7:

[1530] Users follow the voice prompts and push the right stick to perform long-range attacks.

[1531] In this way, the user can receive the necessary operating instructions at the appropriate time and progress smoothly through the game.

[1532] Example 1

[1533] 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."

[1534] Current game systems have difficulty providing appropriate operational instructions in real time when a user experiences difficulty with a specific operation or using a new skill. This can impair the user experience and stall game progress. Furthermore, the increased time required for the user to overcome the difficulty can reduce satisfaction with the game. Therefore, the present invention aims to improve the user experience by monitoring and analyzing the user's operation history and game progress in real time and providing operational instructions at the appropriate time.

[1535] 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.

[1536] In this invention, the server includes means for collecting a user's operation history and game progress status in real time, means for analyzing the operation history and game progress status using a machine learning model to detect when a specific operation has not been attempted for a long time or when the user is experiencing difficulty in a specific area, and means for generating a request for appropriate operation instructions based on the detected timing and sending the request to the terminal. This makes it possible to detect difficulties the user is experiencing while playing the game in real time and provide appropriate operation instructions at that moment.

[1537] "User operation history" is a record of the specific operations performed by the user when playing a game, including keyboard keystrokes, mouse movements, button clicks, and the like.

[1538] "Game progress" refers to information related to the progress of the game, such as the character's current position and status in the game, mission progress, and game area.

[1539] A "machine learning model" is a general term for algorithms that learn patterns and trends based on past data and make predictions and classifications for new data.

[1540] A "request for operation instructions" is a request to generate instructions including specific operation procedures and send them to the terminal when the user is experiencing difficulty in the game.

[1541] "Speech synthesis technology" is a technology that generates voices that mimic human voices based on text data, and is used to create audio guides.

[1542] "Terminal" refers to a device that provides audio guidance to the user, including smart speakers and earphones.

[1543] "Audio guide" refers to instructions provided by voice that guide the user through the operational procedures required in the game, and is intended to aid the user in understanding.

[1544] "New skills" refer to new abilities or techniques that a user acquires in the game and that the user must learn how to use.

[1545] MODE FOR CARRYING OUT THE INVENTION

[1546] This invention relates to a system that collects a user's operation history and game progress in real time and provides necessary operation instructions based on that data. Here, we will explain how to implement this system in detail. This system is mainly composed of three parties: a server, a terminal, and a user.

[1547] Server Processing

[1548] 1. Gathering game logs

[1549] The server collects game logs in real time. Specifically, it uses an API and a database to collect user operation history (keystrokes, mouse movements, button clicks, etc.) and game progress (character status, progress, current game area). This data is necessary to understand the user's in-game behavior.

[1550] 2. Data Analysis

[1551] The server analyzes user behavior based on the collected data, using machine learning models (e.g., clustering and trend analysis algorithms) to detect when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area.

[1552] 3. Request Generation

[1553] The server uses the analysis results to determine when and how the user needs to be instructed on what operations. For example, if the user has been trying to jump in the same place for more than five minutes, the server detects this and generates a request indicating the need for a double jump. This request includes specific instructions and the reasons for them.

[1554] Terminal handling

[1555] 1. Receiving requests and preparing audio guides

[1556] The device (smart speaker or earphones) receives a request for operation instructions from the server. It uses speech synthesis technology (e.g., Google Text-to-Speech or Amazon Polly) to generate audio guidance based on the request. This audio guidance includes specific operation procedures.

[1557] 2. Provision of audio guides

[1558] The device provides the generated voice guidance to the user. For example, instructions such as "Please press the jump button twice in succession" are transmitted in real time through earphones. This allows the user to follow the voice guidance and perform the appropriate operation.

[1559] User response

[1560] 1. Gameplay

[1561] The user plays the game as usual, but if they encounter a difficult situation or don't know how to perform a particular operation, they try it out on the spot.

[1562] 2. Audio guide execution

[1563] The user attempts to perform specific operations according to the voice guidance provided by the device. For example, by following the instruction to "press the jump button twice in succession," the user can successfully perform a double jump.

[1564] 3. Providing Feedback

[1565] If the user follows the instructions and the operation is successful, the information is sent back to the server. For example, a log stating "double jump successful" is sent to the server. This feedback will be used for future data analysis and contribute to improving the accuracy of the system.

[1566] Specific examples

[1567] Example 1: Performing a double jump

[1568] Let's assume that the user is having trouble progressing in a particular area.

[1569] 1. The server detects that the user has been attempting to jump in the same location for more than 5 minutes and generates a request for a "need for a double jump."

[1570] 2. The device receives the request, generates a voice prompt saying "Please press the jump button twice in succession," and conveys this to the user through the smart speaker.

[1571] 3. The user follows the audio guidance and presses the jump button twice in succession to perform a double jump and proceed to the next area.

[1572] Example 2: Using long-range attack skills

[1573] Suppose a user acquires a new skill and doesn't know how to use it.

[1574] 1. The server detects that the user has acquired a new skill (ranged attack) and generates a request for it.

[1575] 2. The device receives the request and generates and provides a voice prompt saying, "Press the right stick to perform a long-range attack."

[1576] 3. Following the voice guidance, the user presses the right stick to attempt a long-range attack and succeeds.

[1577] Specific examples of prompts

[1578] Below are some example prompts to input to the generative AI model for the system:

[1579] Please describe this system. The server collects game logs in real time and analyzes the user's operation history and game progress. At specific times, it generates and sends a request for audio guidance to the device. The device prepares audio guidance based on the request and provides it to the user. For example, if the user experiences difficulty, the server detects that situation and generates guidance instructing the user to press the jump button twice in succession.

[1580] As described above, implementing the present invention requires the ability to collect and analyze the user's operation history and game progress in real time, as well as the ability to provide audio guidance at appropriate times, which enables real-time operation explanations and significantly improves the user experience.

[1581] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1582] Step 1:

[1583] Gathering game logs

[1584] The server collects the user's operation history and game progress in real time. During this process, the game inputs operation data (keystrokes, mouse movements, button clicks, etc.) from the game during gameplay. This data is collected via API and database and stored on the server. For example, the number of times the jump button was pressed and the character's current position are recorded. This makes it possible to monitor what operations the user is performing within the game.

[1585] Step 2:

[1586] Data analysis

[1587] The server analyzes the collected operation history and game progress using a machine learning model. The game logs collected in step 1 are used as input for this process. The analysis uses clustering algorithms and trend analysis algorithms to detect when a particular operation has not been attempted for a long time or when the user is experiencing difficulty in a particular area. For example, a pattern such as "the user has been trying to jump in the same place for five minutes without success" can be detected. This makes it possible to identify when the user is experiencing difficulty.

[1588] Step 3:

[1589] Request Generation

[1590] Based on the analysis results from step 2, the server detects when instructions are needed and generates a request containing specific instructions. The input to this process is the information obtained through data analysis. The output is a request containing specific operating procedures and the reasons for them. For example, a request stating "double jump required" is created. This prepares the device to provide appropriate operating instructions to the user.

[1591] Step 4:

[1592] Receiving requests and preparing audio guides

[1593] The device receives a request for operation instructions from the server and prepares audio guidance based on the request. The input for this process is the request sent from the server. The device uses speech synthesis technology (e.g., Google Text-to-Speech or Amazon Polly) to generate audio guidance based on the request. The output is an audio guidance message. For example, an audio guidance message such as "Press the jump button twice in succession" is created. This completes the guidance for the user to perform the appropriate operation.

[1594] Step 5:

[1595] Audio guide provided

[1596] The device provides the generated audio guide to the user. The input of this process is the audio guide generated in step 4. The device provides the audio guide to the user through a smart speaker or earphones. The output includes the audio guide received by the user. For example, an instruction such as "Please press the jump button twice in succession" may be conveyed to the user through the earphones. This allows the user to receive instructions on how to operate the device in real time.

[1597] Step 6:

[1598] Execute audio guide

[1599] The user attempts to perform a specific operation according to the voice guidance provided by the device. The input to this process is the voice guidance provided by the device. Based on the instructions, the user performs a specific operation (for example, pressing the jump button twice in succession). The output includes the result of whether the user succeeded or failed in the operation. This allows the user to learn difficult operations or how to use new skills.

[1600] Step 7:

[1601] Providing Feedback

[1602] If the user successfully performs the instructed operation, that information is sent back to the server. The input to this process is the result of the user's operation. For example, a log stating "double jump successful" is sent to the server. The output is this feedback information, which is recorded on the server. Based on this feedback, the server can improve the accuracy of future analysis. This continuously improves the efficiency of the entire system.

[1603] (Application example 1)

[1604] 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."

[1605] Mistakes made by workers in factories and incorrect work procedures can lead to reduced production efficiency and safety risks. Furthermore, it is difficult to learn new operating procedures and how to use machines in real time, which causes further problems. Traditional textbooks and manuals do not allow for immediate response, and it takes time for workers to learn the correct operating methods.

[1606] 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.

[1607] In this invention, the server includes means for collecting the user's operation history and status in real time, means for analyzing the operation history and status and detecting the timing when operation instructions are required, means for generating an operation instruction request based on the detected timing and sending it to the terminal, and means for receiving the request, preparing visual and audio guides, and providing them to the user. This makes it possible to correct operational errors and errors in work procedures by workers in the factory in real time, and to progress work efficiently and safely.

[1608] An "operation history" is a record of a series of operations and actions performed by a user.

[1609] The "situation" is the totality of the environment in which the user is currently placed and the work that is currently in progress.

[1610] "Collecting in real time" means collecting operation history and status immediately without delay.

[1611] "Analysis" is the process of analyzing collected data to find specific patterns and trends.

[1612] "Detection" refers to the identification of a particular condition or event from the results of an analysis.

[1613] "Operation instructions" are specific operating procedures and methods provided to the user.

[1614] "Generating a request" means creating a necessary operation instruction and creating a request to provide it.

[1615] A "terminal" is a device or apparatus that receives a request for operation instructions and provides visual and audio guidance to the user.

[1616] A "visual guide" is a means of conveying operating procedures and information to users graphically.

[1617] "Audio guide" is a means of conveying operational procedures and information to the user by voice.

[1618] "User" refers to the worker or operator who uses the system and receives instructions on how to operate it.

[1619] This invention is a system for correcting worker errors and errors in work procedures in real time in a factory, ensuring efficient and safe work progress. This system mainly operates in cooperation with three parties: a server, a terminal, and a user.

[1620] System configuration

[1621] The system mainly consists of the following elements:

[1622] 1. Server: Collects the user's operation history and status in real time and detects when operation instructions are required. The server generates a request for operation instructions and sends it to the device.

[1623] 2. Terminal: Receives requests from the server, prepares visual and audio guides, and provides them to the user. The terminal can be a smart glass or other visual and audio output device.

[1624] 3. User: A worker who performs work in a factory. The user follows visual and audio guidance to carry out the correct work procedures.

[1625] Program processing

[1626] Server Processing

[1627] The server does the following:

[1628] 1. Data collection: Collect worker movements in real time from cameras and sensors in the factory (e.g., Azure Kinect, Microsoft Azure IoT Hub), including worker behavior data and the status of the work being performed.

[1629] 2. Analysis and detection: The collected data is analyzed using Google Cloud Dataflow and Azure Machine Learning to detect whether specific work procedures are being performed correctly based on the user's operation history and situation.

[1630] 3. Request generation: If the correct operating procedure is not performed, a request for operating instructions is generated based on the timing and sent to the terminal.

[1631] Terminal handling

[1632] The terminal does the following:

[1633] 1. Request reception and preparation: Smart glasses (e.g., Google Glass, Epson Moverio) receive a request for operation instructions from the server and prepare visual and audio guidance. Amazon Polly is used for speech synthesis.

[1634] 2. Providing visual and audio guidance: The device displays visual guidance on the screen and provides audio guidance, which helps users understand specific work procedures.

[1635] User response

[1636] The user takes the following actions:

[1637] 1. Task execution: The user follows the visual and audio guidance provided by the smart glasses to perform the correct task steps.

[1638] 2. Providing feedback: The progress of the work is reported to the server, and information about successes and failures is used again for data collection and analysis.

[1639] Specific examples

[1640] For example:

[1641] 1. Palletizing Guide:

[1642] The server detects incorrect movements when workers lift loads.

[1643] The server generates an instruction for operation such as "Next, carefully lift the luggage and place it in the designated location" and sends it to the terminal.

[1644] The device provides audio guidance along with visual guidance.

[1645] The user follows the guide and places the luggage in the correct position.

[1646] 2. Learning how to operate a new machine:

[1647] The server detects mistakes made by workers as they try out new ways of operating machines.

[1648] The server generates operating instructions such as "To operate this machine, first press the red button and then pull the lever" and sends them to the terminal.

[1649] The device provides visual and audio guidance through smart glasses.

[1650] Users follow the guide to learn the correct operating procedures.

[1651] As a result, it is possible to reduce work errors in the factory and perform work safely and efficiently.

[1652] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1653] Step 1:

[1654] The server collects worker movement data in real time using cameras and sensors (e.g., Azure Kinect, Microsoft Azure IoT Hub) in the factory. The input is raw data from the cameras and sensors, and the output is a log of worker movement. Specifically, it records video data captured by cameras and movement data acquired by sensors.

[1655] Step 2:

[1656] The server analyzes the collected operation data using a data analysis platform (e.g., Google Cloud Dataflow, Azure Machine Learning). The input here is the operation log, and the output is the analysis result, i.e., a determination of whether a specific work procedure was performed correctly. Specifically, an AI model is used to analyze operation patterns and detect mistakes or incorrect operations.

[1657] Step 3:

[1658] The server generates a request for operation instructions based on the analysis results and sends it to the terminal. The input is the analysis results, and the output is an operation instruction request. Specifically, it generates text information about appropriate operation procedures and actions that need to be corrected.

[1659] Step 4:

[1660] The device receives the operation instruction request sent from the server and prepares the audio guide using speech synthesis software (e.g., Amazon Polly). The input is the operation instruction request, and the output is the audio guide and visual guide. Specifically, the device converts the request into text and prepares to display it on the screen as visual information.

[1661] Step 5:

[1662] The terminal provides the prepared visual and audio guide to the user. The input is the audio and visual guide data, and the output is the display and audio output to convey it to the user. Specifically, the smart glasses display text and illustrated procedures, as well as audio instructions, so that the worker can receive them.

[1663] Step 6:

[1664] The user performs specific tasks according to the visual and audio guidance provided by the terminal. The input is the visual and audio guidance, and the output is the accurate execution of the work procedure. Specifically, the user performs the task according to the guidance and checks the results.

[1665] Step 7:

[1666] The results of the user's work are fed back to the server. The input is the work result, and the output is feedback data to the server. Specifically, the success or failure of the work and its details are sent to the server to help with future improvements.

[1667] 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.

[1668] This invention relates to a system that analyzes the user's behavior and emotional state in real time in a game and provides operation instructions at the appropriate time to improve the user experience. This system operates in cooperation with the server, the terminal, and the user.

[1669] System configuration

[1670] First, we will explain the system configuration. This system mainly consists of the following elements:

[1671] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. It also includes an emotion engine to recognize the user's emotional state. The server detects when operation instructions are required and generates an instruction request. The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data.

[1672] 2. Device: Receives requests from the server, prepares audio guides, and provides them to the user. The device can be a smart speaker or earphones. If the user is in a negative emotional state, the device adjusts the content and tone of the audio guide.

[1673] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[1674] Program processing

[1675] The program processing that realizes this is explained in natural language, and the behavior of the server, terminal, and user is described in detail.

[1676] Server Processing

[1677] 1. Data collection: The server collects game logs in real time. Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[1678] 2. Emotion Recognition: The server recognizes the user's emotional state using an emotion engine, which uses facial expression analysis, voice analysis, or vital sign data of the user.

[1679] 3. Analysis and Detection: The server analyzes the collected operation history and progress as well as the recognized emotion data to detect when a specific operation has not been performed successfully for a long time or when the user is stagnating in a particular area.

[1680] 4. Request Generation: The server generates a request for operation instructions based on the detection results and the emotional state. For example, it generates a specific request such as "double jump required."

[1681] Terminal handling

[1682] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[1683] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. If the user's emotional state is negative, the content and tone of the audio guidance will be adjusted.

[1684] User response

[1685] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[1686] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[1687] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis, and if unsuccessful, a more detailed explanation may be provided.

[1688] Specific examples

[1689] Example 1: Performing a double jump

[1690] Let's say a user is having trouble progressing in a particular area.

[1691] 1. Server: Detects when a user has been trying to jump in the same place for more than five minutes without success. The emotion engine also analyzes the user's facial expressions and recognizes frustration.

[1692] 2. Server: Sends a request for instructions, "Explain how to double jump," and information that "the user is frustrated" to the device.

[1693] 3. Device: Receive the request and prepare a voice prompt saying "Please press the jump button twice in succession," and provide it in a gentle tone depending on the user's emotional state.

[1694] 4. User: Follow the audio guide and press the jump button twice in succession to perform a double jump and proceed to the next area.

[1695] Example 2: Using a new skill (long-range attack)

[1696] A user acquires a new skill and doesn't know how to use it.

[1697] 1. Server: Detects when a user acquires a new skill (long-range attack). Also, the emotion engine recognizes the emotion of anxiety from the user's vital sign data.

[1698] 2. Server: Sends a request for operation instructions, "Explain how to use long-range attacks," and information about "the user's anxiety," to the device.

[1699] 3. Device: Receive the request and prepare a voice prompt saying "Press the right stick to perform a ranged attack" in a reassuring tone depending on the emotional state.

[1700] 4. User: Follow the voice prompts and press the right stick to perform a long-range attack.

[1701] In this way, users can receive real-time instructions and emotional support to smoothly progress through the game, which greatly improves the user experience and reduces the costs and efforts of game developers.

[1702] The processing flow will be explained below.

[1703] Program processing steps

[1704] Server Processing

[1705] Step 1:

[1706] The server collects game logs in real time.

[1707] Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[1708] Step 2:

[1709] The server uses an emotion engine to recognize the user's emotional state in real time.

[1710] The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data of the user.

[1711] Step 3:

[1712] The server analyzes the collected operation history and progress as well as the recognized emotion data.

[1713] Specifically, it checks if a particular operation has not been successful for a long time or if the user is stuck in a particular area.

[1714] Step 4:

[1715] The server detects when an instruction for operation is required.

[1716] For example, if the user has been trying to jump in the same place for more than five minutes without success, it is determined that an instruction on how to jump is necessary.

[1717] Step 5:

[1718] The server generates a request for operation instructions based on the detection result and the emotional state.

[1719] Specifically, information such as "a double jump is required" or "the user is feeling frustrated" is generated as a request.

[1720] Step 6:

[1721] The server transmits the generated request to the terminal.

[1722] Terminal handling

[1723] Step 7:

[1724] The terminal receives a request for operation instructions from the server.

[1725] Step 8:

[1726] The terminal prepares audio guidance based on the received request.

[1727] Specifically, instructions such as "Press the jump button twice in succession" are converted into voice using speech synthesis technology.

[1728] Step 9:

[1729] The terminal adjusts the tone of the audio guide according to the user's emotional state.

[1730] For example, if the user is feeling frustrated, prepare a voice prompt with a gentle tone.

[1731] Step 10:

[1732] The device provides the prepared audio guide to the user through a smart speaker or earphones.

[1733] User response

[1734] Step 11:

[1735] The user follows the voice guidance provided by the terminal and attempts to perform specific operations.

[1736] For example, try to perform a double jump by pressing the jump button twice in succession.

[1737] Step 12:

[1738] The result of the user's operation is sent to the server again.

[1739] If successful, the information will be recorded for future analysis, if unsuccessful a more detailed explanation may be provided.

[1740] Example 1: Double jump

[1741] Step 1:

[1742] The user is unable to overcome a particular obstacle during gameplay and becomes stuck.

[1743] Step 2:

[1744] The server detects that the user has clicked the jump button multiple times but without success.

[1745] Step 3:

[1746] The server uses an emotion engine to analyze the user's facial expressions and recognize the emotion of frustration.

[1747] Step 4:

[1748] The server sends the information "explain how to double jump" and "the user is feeling frustrated" as a request to the terminal.

[1749] Step 5:

[1750] The device receives the request and prepares a voice prompt saying, "Please press the jump button twice in succession."

[1751] Step 6:

[1752] The device recognizes that the user is frustrated and provides voice guidance in a gentle tone.

[1753] Step 7:

[1754] The user follows the audio guidance and presses the jump button twice in succession to perform a double jump and proceed to the next area.

[1755] Example 2: Using a new skill (long-range attack)

[1756] Step 1:

[1757] A user acquires a new skill.

[1758] Step 2:

[1759] The server detects the acquisition of a new skill (ranged attack).

[1760] Step 3:

[1761] The server uses an emotion engine to analyze the user's vital sign data and recognize emotions of anxiety.

[1762] Step 4:

[1763] The server sends the information "explain how to use long-range attacks" and "the user feels anxious" as a request to the terminal.

[1764] Step 5:

[1765] The device receives the request and prepares a voice prompt saying, "Press the right stick to perform a long-range attack."

[1766] Step 6:

[1767] The terminal recognizes that the user is feeling anxious and provides audio guidance in a reassuring tone.

[1768] Step 7:

[1769] Users follow the voice prompts and push the right stick to perform long-range attacks.

[1770] Example 2

[1771] 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."

[1772] Conventional game systems struggle to provide timely explanations of in-game operations that can easily confuse users or how to use new skills. Furthermore, when a user becomes stuck on a particular operation or area, this can be due to emotional factors, but the system lacks the ability to detect this in real time and take appropriate action. Furthermore, explanations that are not tailored to the user's emotional state can increase anxiety and frustration, detracting from the game experience.

[1773] 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.

[1774] In this invention, the server includes means for collecting a user's operation history and game progress status in real time, means for analyzing the operation history and game progress status and detecting timing when operation instructions are required, means for generating an operation instruction request based on the detected timing and sending it to the terminal, means for recognizing the user's emotional state using an emotion engine, and means for adjusting the content and tone of audio guidance based on the emotional state. This allows the user to receive operation instructions in the game at appropriate timing according to their emotions, improving the game experience.

[1775] The "user operation history" is a record of a series of operations performed by the user during the game. Specifically, this includes the number of clicks of the jump button, the direction of movement, attack actions, and so on.

[1776] "Game progress" refers to information about the progress of the game, such as the character's position in the game, progress, and acquired items.

[1777] The "emotion engine" is an analysis engine for recognizing the user's emotional state. Specifically, it analyzes facial expressions, voice, and vital sign data.

[1778] An "operation instruction request" is a request generated by a server to instruct a user on how to perform a particular operation.

[1779] "Audio guide" refers to audio instructions and explanations provided to the user by a device. The content and tone may be adjusted to make the instructions easier for the user to understand.

[1780] A "terminal" is a device that receives a request for operation instructions from the server, prepares audio guidance, and provides it to the user. This includes smart speakers and earphones.

[1781] "Emotional state" refers to the user's current feelings, including frustration, anxiety, joy, etc.

[1782] This invention relates to a system that analyzes the user's behavior and emotional state in real time in a game and provides operation instructions at the appropriate time to improve the user experience. This system operates in cooperation with the server, the terminal, and the user.

[1783] System configuration

[1784] The system mainly consists of the following elements:

[1785] 1. Server: Collects game logs in real time and analyzes the user's operation history and game progress. It also includes an emotion engine to recognize the user's emotional state. The server detects when operation instructions are required and generates an instruction request. The emotion engine recognizes emotions using facial expression analysis, voice analysis, or vital sign data.

[1786] 2. Device: Receives requests from the server, prepares audio guides, and provides them to the user. The device can be a smart speaker or earphones. If the user is in a negative emotional state, the device adjusts the content and tone of the audio guide.

[1787] 3. User: The end user who plays the game. The user follows the audio prompts to learn difficult operations or new skills.

[1788] Server Processing

[1789] 1. Data collection: The server collects game logs in real time. Specifically, it records the user's operation history (e.g., number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.).

[1790] 2. Emotion Recognition: The server uses an emotion engine to recognize the user's emotional state, which can be achieved by analyzing the user's facial expressions, voice, or vital sign data.

[1791] 3. Analysis and Detection: The server analyzes the collected operation history and progress as well as the recognized emotion data to detect when a specific operation has not been performed successfully for a long time or when the user is stagnating in a particular area.

[1792] 4. Request Generation: The server generates a request for operation instructions based on the detection results and the emotional state. For example, it generates a specific request such as "double jump required."

[1793] Terminal handling

[1794] 1. Request reception and preparation: The device receives a request for operation instructions from the server and prepares audio guidance based on the request. It uses speech synthesis technology to convert specific instructions into audio.

[1795] 2. Providing audio guidance: The device provides audio guidance to the user through a smart speaker or earphones. If the user's emotional state is negative, the content and tone of the audio guidance will be adjusted.

[1796] User response

[1797] 1. Gameplay: The user plays the game as usual. If they don't know how to do something, they try it out on the spot.

[1798] 2. Receiving and executing voice guidance: The user follows the voice guidance provided by the device and attempts to perform a specific operation, such as performing a double jump.

[1799] 3. Providing feedback: If the user is successful, the information is sent back to the server for further analysis, and if unsuccessful, a more detailed explanation may be provided.

[1800] Specific examples

[1801] Example 1: Performing a double jump

[1802] Let's say a user is having trouble progressing in a particular area.

[1803] 1. Server: Detects when a user has been trying to jump in the same place for more than five minutes without success. The emotion engine also analyzes the user's facial expressions and recognizes frustration.

[1804] 2. Server: Sends a request for instructions, "Explain how to double jump," and information that "the user is frustrated" to the device.

[1805] 3. Device: Receive the request and prepare a voice prompt saying "Please press the jump button twice in succession," and provide it in a gentle tone depending on the user's emotional state.

[1806] 4. User: Follow the audio guide and press the jump button twice in succession to perform a double jump and proceed to the next area.

[1807] Example 2: Using a new skill (long-range attack)

[1808] A user acquires a new skill and doesn't know how to use it.

[1809] 1. Server: Detects when a user acquires a new skill (long-range attack). Also, the emotion engine recognizes the emotion of anxiety from the user's vital sign data.

[1810] 2. Server: Sends a request for operation instructions, "Explain how to use long-range attacks," and information about "the user's anxiety," to the device.

[1811] 3. Device: Receive the request and prepare a voice prompt saying "Press the right stick to perform a ranged attack" in a reassuring tone depending on the emotional state.

[1812] 4. User: Follow the voice prompts and press the right stick to perform a long-range attack.

[1813] In this way, users can receive real-time instructions and support tailored to their emotional state, allowing them to progress smoothly through the game, significantly improving the user experience and reducing support costs for game developers.

[1814] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1815] Step 1: Data collection

[1816] The server collects game logs in real time. As input, it receives the user's operation history (number of clicks of the jump button, movement direction, attack actions, etc.) and game progress (character position information, progress, acquired items, etc.). The server records this data and accumulates it in a data store for subsequent analysis. Specific operations include receiving and saving log data.

[1817] Step 2: Recognize emotions

[1818] The server uses an emotion engine to recognize the user's emotional state. As input, it receives the user's facial expression data, voice data, and vital sign data. The emotion engine analyzes these data and identifies the user's emotional state (frustration, anxiety, joy, etc.). As output, it generates recognized emotion data, which is passed to the next analysis step. Specifically, it performs data analysis using a face recognition module and a voice analysis module.

[1819] Step 3: Analysis and detection

[1820] The server integrates and analyzes the collected operation history, game progress, and emotional data. It receives the above operation history, game progress, and emotional data as input. It integrates the data and detects when a specific operation has not been successful for a long time or when the user is stuck in a specific area. It generates problem identification results (e.g., the user is having difficulty jumping) as output. Specific operations include problem detection using database queries and machine learning algorithms.

[1821] Step 4: Request Generation

[1822] The server generates a request for operation instructions based on the detection results and the emotional state. As input, it receives the detected problem and emotional data. It generates a specific request, such as "double jump required" or "the user is feeling frustrated." As output, it sends the generated request to the terminal. As a specific operation, it creates a specific instruction sentence using a text generation engine and sends the request to the terminal using a communication module.

[1823] Step 5: Receiving and preparing the request

[1824] The device receives a request for operation instructions from the server. As input, it receives the request data sent from the server. Based on that content, it prepares audio guidance. It uses speech synthesis technology to convert the text instructions into speech. It prepares the generated audio data as output. Specifically, it calls a speech synthesis API to generate the audio data.

[1825] Step 6: Provide audio guides

[1826] The terminal provides audio guidance to the user through a smart speaker or earphones. As input, it receives prepared audio data. The content and tone of the audio guidance are adjusted according to the user's emotional state. As output, it provides specific audio instructions to the user. As a specific operation, it uses an audio playback module to play the audio guidance to the user.

[1827] Step 7: Gameplay

[1828] The user plays the game as usual. As input, they receive audio guidance provided by the device. If they are unsure of how to operate the device, they try and error on the spot. As output, a new operation history and game progress status are generated. As a specific operation, they operate the game controller and perform actions in the game.

[1829] Step 8: Receive and follow the audio guide

[1830] The user attempts specific operations according to the voice guidance provided by the device. As input, the user receives the instructions from the voice guidance. For example, the user attempts a double jump by pressing the jump button twice in succession. As output, a history of successful operations is generated. As a specific action, the user operates the game controller as instructed.

[1831] Step 9: Provide feedback

[1832] If the user successfully performs an operation, that information is sent to the server. As input, it receives information about whether the operation was successful or unsuccessful. The server analyzes this feedback information and checks whether the operation was performed correctly. As output, it generates a request indicating success or if further explanation is required. Specifically, when the operation is successful, it obtains satisfaction data from the vital sign data and sends it to the server.

[1833] (Application example 2)

[1834] 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."

[1835] Current security monitoring systems lack the ability to analyze users' real-time behavior and emotional state and provide appropriate responses. Furthermore, there is no system that can immediately guide users to appropriate measures when they feel stressed or anxious, making it difficult to provide efficient responses to ensure users' safety. This increases the risk of users being exposed to unstable situations.

[1836] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting a user's operation history and progress status in real time, means for analyzing the operation history and progress status and detecting a timing when an explanation is needed, means for generating an explanation request based on the detected timing and transmitting it to the terminal, means for receiving the request, preparing audio guidance, and providing it to the user, means for analyzing the user's behavior and emotional state, means for detecting a situation in which the user feels anxious or stressed, and generating a request for an appropriate response method, and means for collecting user location information and video data in real time and analyzing the security situation. This makes it possible to quickly provide an appropriate response method when the user feels anxious or stressed.

[1837] An "operation history" is a record of specific actions and operations performed by a user.

[1838] "Progress" is a record of the status that indicates how far a task or process has progressed.

[1839] The "timing when an explanation is required" refers to a time or situation when a user does not understand a particular operation or action and an explanation is required.

[1840] "Request" refers to a request for a specific operation or description of an action.

[1841] A "terminal" is a device that connects a server and a user and provides information such as audio guides.

[1842] "Audio guide" provides the user with audio instructions on specific operations and actions.

[1843] "Behavior" refers to a specific movement or activity taken by a user.

[1844] "Emotional state" indicates the type and strength of the user's emotion.

[1845] An "anxious or stressful situation" is a specific situation or environment in which a user feels psychological anxiety or tension.

[1846] "Appropriate response method" refers to instructions for the most appropriate procedure or action depending on the user's situation and emotions.

[1847] "Location information" is data that indicates the user's current geographical location.

[1848] "Video Data" refers to image or video data collected by a camera or other image capture device.

[1849] "Security situation" refers to the state of the environment or situation regarding safety.

[1850] This invention relates to a system that analyzes a user's operation history and emotional state in real time to implement a security monitoring system, and provides appropriate responses as audio guidance when the user feels anxious or stressed. This system operates in cooperation with a server, a terminal, and a user.

[1851] System configuration

[1852] The system mainly consists of the following components:

[1853] 1. Server: Collects and analyzes the user's operation history and progress in real time. It also has an emotion engine and recognizes the user's emotional state (specifically, anxiety or stress). It also analyzes security-related situations and generates requests for appropriate responses. The emotion engine and analysis tools used are Google Cloud's "AutoML Vision" and "AutoML Natural Language."

[1854] 2. Terminal: Receives requests from the server, prepares audio guides, and provides them to the user. Using speech synthesis technology, it converts instructions on the appropriate response method into speech. Google Cloud Text-to-Speech is used as the speech synthesis technology.

[1855] 3. User: Uses a device such as a smartphone or earphones to perform normal operations and actions. If the user feels anxious or stressed, they follow the voice guidance provided by the device to take appropriate measures. The voice guidance is provided in a reassuring tone to help the user take safe actions.

[1856] Program implementation steps

[1857] The server collects location information, camera footage, and microphone audio from the smartphone in real time. The emotion engine recognizes and analyzes the user's emotional state from the camera footage and microphone audio. It detects situations in which the user feels anxious or stressed and generates a request for how to respond (for example, directions to the nearest police station or directions to a safe route). The generated request is sent to the device, which uses speech synthesis technology to convert the instructions into voice and provide it to the user.

[1858] Specific examples

[1859] Example 1: Presence of a suspicious person

[1860] 1. Server: The user finds a suspicious person and analyzes emotions of fear and anxiety from camera footage and microphone audio.

[1861] 2. Server: Detects situations where the user is feeling anxious and generates a request to "show the location of the nearest police box."

[1862] 3. Device: Receives the request and prepares and provides an audio guide saying, "Don't worry, the nearest police box is located at XX. Head there immediately."

[1863] 4. User: Follow the audio guide and head immediately to the designated police box.

[1864] Example 2: Staying in a dark place late at night

[1865] 1. Server: Detects anxious facial expressions and voice when the user is in a dark place late at night.

[1866] 2. Server: Detects that the user is feeling anxious and needs guidance on a safe route, and generates the corresponding request.

[1867] 3. Terminal: Receives requests and provides voice guidance on safe routes.

[1868] 4. User: Follow the voice guidance to find a safe route and return home safely.

[1869] Example prompts to input to the generative AI model

[1870] "You are developing a smartphone application that analyzes the user's emotions from camera footage and audio data, and provides appropriate guidance on how to respond when the user feels anxious or stressed. Please generate the following audio guidance."

[1871] This system allows users to receive real-time guidance on appropriate response methods, enabling them to respond quickly and accurately to security risks.

[1872] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1873] Step 1: Data collection

[1874] The server collects location information, camera footage, and microphone audio from the smartphone in real time. These data are the basis for analyzing the user's behavior and emotional state. The input is location information, camera footage, and microphone audio, which are sent to the server. The output is that these data are stored on the server.

[1875] Step 2: Recognize emotions

[1876] The server sends the collected camera footage and microphone audio to the emotion engine to recognize the user's emotional state. Specifically, it uses AutoML Vision and AutoML Natural Language to analyze facial expressions and tone of voice. The input is the collected video and audio data, and the output is a judgment of the user's emotional state (e.g., anxiety, stress, relief, etc.).

[1877] Step 3: Detect security conditions

[1878] The server analyzes whether the user is in a dangerous situation (e.g., the presence of a suspicious person, being in a dark place) based on location information and emotional state data. Specifically, it detects this by comparing the current location with information on pre-defined safe and dangerous areas. The input is the location information and the result of the emotional state determination, and the output is the result of the determination of whether the situation is dangerous or safe.

[1879] Step 4: Generate a response request

[1880] If the server determines that the user is in a dangerous situation, it generates a request for an appropriate response (e.g., information about a nearby police station or a safe route). The content of the request is determined based on the user's current location information and the dangerous situation. The input is the location information and the result of the dangerous situation determination, and the output is a request for an appropriate response.

[1881] Step 5: Submit your request and prepare your audio guide

[1882] The device receives the response request sent from the server and prepares the audio guide. It converts the request into audio using Google Cloud Text-to-Speech. The input is the response request, and the output is the audio guide data.

[1883] Step 6: Provide audio guides

[1884] The device provides the audio guide to the user through a smartphone or earphone. If the user feels anxious, the audio guide is provided in a reassuring tone. The input is the audio guide data, and the output is the provision of the audio guide to the user.

[1885] Step 7: User Behavior

[1886] The user follows the voice guidance provided by the device and takes appropriate action. For example, heading to the nearest police station or following a safe route. The user's actions are fed back to the server and used for future analysis. The input is the content of the voice guidance, and the output is the user's specific actions.

[1887] 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.

[1888] 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.

[1889] 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.

[1890] 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.

[1891] 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.

[1892] 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.

[1893] 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).

[1894] 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.

[1895] 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."

[1896] 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.

[1897] 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).

[1898] 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.

[1899] 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.

[1900] 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.

[1901] 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.

[1902] 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.

[1903] 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.

[1904] 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.

[1905] 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.

[1906] 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.

[1907] All publications, patent applications, and technical st...

Claims

1. A means for collecting user operation history and game progress in real time; means for analyzing the operation history and the game progress status to detect timing when operation instructions are required; means for generating a request for operation instructions based on the detected timing and transmitting the request to the terminal; means for receiving the request, preparing an audio guide, and providing it to the user; A system including:

2. The system of claim 1 , further comprising means for providing audio guidance through a smart speaker or earphones.

3. The system according to claim 1 , further comprising means for detecting acquisition of a new skill from a game log when the request for operation instructions is related to how to use a new skill.

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