system

Abstract

We provide the system. [Solution] A sensor means for collecting multiple environmental data in real time, An artificial intelligence means that analyzes the aforementioned environmental data and generates optimized instructions, A communication means for generating the aforementioned instructions as personalized suggestions and transmitting them to a user terminal, A control means that automatically adjusts the environment based on the above proposal, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern educational and home environments, the impact of the spread of digital devices on children's visual health is becoming more serious. In response to this problem, it is required to optimize the learning environment while efficiently managing visual health, but it is difficult to grasp various environmental factors in real time and provide accurate guidance for individual children. Therefore, there is a need for a data-driven environmental optimization system that takes visual health into consideration.

Means for Solving the Problems

[0005] To solve this problem, the present invention includes a sensor means for collecting multiple environmental data in real time, thereby acquiring information on light intensity, temperature, and sound volume in classrooms and homes. Next, an artificial intelligence means is used to analyze the environmental data and generate optimized instructions. Furthermore, a communication means is used to generate the generated instructions as personalized suggestions and transmit them to the user's terminal. Finally, a control means is provided to automatically adjust the environment based on the suggestions, thereby improving learning efficiency while maintaining visual health.

[0006] A "sensor means" is a device or system for collecting multiple environmental data in real time.

[0007] "Artificial intelligence means" refers to algorithms or models for analyzing collected environmental data and generating optimized instructions.

[0008] "Communication means" refers to network interfaces and protocols used to transmit generated instructions and suggestions to a user terminal.

[0009] A "control means" is a mechanism or system for automatically adjusting the environment based on a proposal.

[0010] "Environmental data" refers to information that indicates the physical conditions within a classroom or home, such as light intensity, temperature, and sound volume.

[0011] "Visual health" refers to a state of health aimed at maintaining visual function and reducing strain on the eyes.

[0012] "Optimized instructions" refer to specific actions proposed based on the analysis results to improve the environment and activities.

[0013] "Personalized recommendations" refer to specific recommendations that are customized according to the individual user and their specific circumstances. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [[ID=2"]] [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. <000008 "> [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the 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.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0028] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is an AI-integrated system for optimizing educational and home environments while maintaining visual health. The system comprises sensor means, artificial intelligence means, communication means, and control means, and operates as follows.

[0036] System Design

[0037] The server collects real-time environmental data such as light levels, temperature, and noise levels in classrooms and homes through multiple environmental sensors. This allows for constant monitoring of the latest conditions.

[0038] The server, acting as an artificial intelligence tool, highly analyzes collected environmental data and generates optimal instructions for maintaining visual health. This AI model learns by considering past data and environmental parameters, allowing its suggestions to improve accuracy over time.

[0039] The server generates personalized suggestions based on the analysis results and sends them to each user's terminal. These suggestions may include, for example, adjusting classroom lighting settings, managing break times during study sessions, and optimizing seating arrangements.

[0040] The terminal receives communications from the server and displays suggestions to the user in an easy-to-understand format. The user can then take specific actions in response to these suggestions.

[0041] By using control mechanisms, the terminal automatically adjusts lighting and volume as needed. Furthermore, by receiving user feedback and sending it to the server, more effective suggestions can be made.

[0042] Specific example

[0043] Specific measures in the classroom:

[0044] If the server detects that there is insufficient lighting in the classroom, it generates an instruction to increase the lighting.

[0045] The device notifies the teacher and automatically adjusts the light intensity in conjunction with the lighting system.

[0046] The user (teacher) can review the presented suggestions and make manual adjustments if necessary.

[0047] Specific examples in the home:

[0048] If the server detects that the volume level is high while studying at home, it will generate a suggestion recommending a quieter environment.

[0049] The device will notify parents or children to lower the volume, or it will automatically adjust the volume of the audio device.

[0050] Users (parents) can readjust the environment based on the suggestions to improve the effectiveness of home learning.

[0051] Thus, the system of the present invention collects and analyzes environmental data in real time and provides appropriate suggestions, thereby realizing an optimal learning environment while protecting visual health.

[0052] The following describes the processing flow.

[0053] Step 1:

[0054] The server collects environmental data in real time from multiple sensor devices placed in classrooms and homes. This includes light intensity, temperature, humidity, and sound levels. The collected data is immediately stored in a database.

[0055] Step 2:

[0056] The server preprocesses the collected data. Specifically, it filters out noise from the sensor data and imputes missing values. This preprocessing enhances the accuracy and consistency of the data.

[0057] Step 3:

[0058] The server uses artificial intelligence to analyze pre-processed data. Here, it identifies factors affecting visual health and generates instructions for optimal environmental adjustments.

[0059] Step 4:

[0060] The server generates personalized suggestions based on the analysis results. These suggestions include recommendations for the most suitable lighting adjustments, break times, and seating arrangements for each individual user.

[0061] Step 5:

[0062] The server sends the generated suggestions to each user's terminal. Information is efficiently transmitted over the network via communication means.

[0063] Step 6:

[0064] The terminal displays suggestions received from the server on the user interface and notifies the user. If necessary, it may also use voice alerts or pop-up notifications.

[0065] Step 7:

[0066] The terminal, through its control mechanisms, performs automatic control of the environment based on suggestions. For example, it sends a signal to the lighting system to adjust the amount of light in a classroom or home.

[0067] Step 8:

[0068] Users (teachers, parents, or children) receive notifications on their devices and take action according to the suggestions to maintain visual health and optimize the learning environment.

[0069] Step 9:

[0070] Users send feedback from their devices to the server regarding the effectiveness of the proposals and changes in the environment. This information is stored in a database and used to refine future proposals.

[0071] (Example 1)

[0072] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0073] There is a need for systems that can provide an optimal learning environment in real time while maintaining visual health in educational and home settings. However, conventional systems have insufficient collection and analysis of environmental information, making it difficult to provide personalized recommendations for individual users. Furthermore, there is a need for a mechanism that effectively incorporates user feedback to improve the accuracy of recommendations.

[0074] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0075] In this invention, the server includes a measurement means, an intelligent processing means, and an information communication means. This makes it possible to provide user-optimized suggestions while maintaining visual health based on real-time information of the educational and home environments.

[0076] "Measurement means" refers to a device that collects environmental information in real time using various sensors.

[0077] "Intelligent processing means" refers to a device that uses an artificial intelligence model to analyze collected environmental information and propose optimal environmental conditions while maintaining visual health.

[0078] "Information and communication means" refers to communication protocols and devices used to transmit proposals generated by a server to a user's terminal.

[0079] "Display means" refers to devices or interfaces that visually present suggestions sent from the server to the user's terminal in an easily understandable way.

[0080] "Means of receiving feedback" refers to devices or interfaces that collect user behavior and opinions, reflect them in a database, and improve the accuracy of system suggestions.

[0081] This invention is an advanced AI-integrated system for maintaining visual health in educational and home environments. The system utilizes servers, terminals, and sensor devices as its primary hardware components.

[0082] The server plays a central role in analyzing environmental information, utilizing an artificial intelligence model (generative AI model) aimed at maintaining visual health. This AI model learns from past environmental data and user feedback to generate optimal suggestions based on environmental conditions.

[0083] The sensor system functions as a means of measuring environmental information and includes various sensors such as light sensors, temperature sensors, and microphones. These sensors are placed in classrooms and homes to collect real-time data on light intensity, temperature, and sound volume. The collected data is transmitted to a server for analysis.

[0084] The terminal is equipped with information communication and display means to show the user suggestions sent from the server. The suggestions are represented on the terminal screen using icons and graphs so that they can be understood intuitively. The user can modify their actions based on the presented suggestions, and the terminal can also automatically adjust lighting and volume.

[0085] As a concrete example, in a classroom, the server detects insufficient light levels based on data from light sensors and generates a suggestion to increase the lighting. The terminal notifies the teacher of this suggestion, and the lighting system automatically adjusts. At home, the server detects excessive volume and suggests lowering it, and the terminal reduces the volume via an audio device.

[0086] As an example of a prompt, the following question can be input to the generating AI model:

[0087] "If the classroom lighting is insufficient, suggest how to adjust it."

[0088] "What volume settings are best for improving the home study environment?"

[0089] The system of the present invention can support users in creating an optimal learning environment while maintaining their visual health through these means.

[0090] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0091] Step 1:

[0092] The server collects real-time environmental data such as light intensity, temperature, and sound volume from sensor devices placed in classrooms and homes. This data is used as input and recorded in a database. Specifically, it converts the analog signals acquired from the sensors into digital data and stores it as time-series data.

[0093] Step 2:

[0094] The server analyzes the collected environmental data using intelligent processing tools. In this step, based on the input environmental data, it performs analysis using a generative AI model to calculate the optimal environmental conditions for maintaining visual health. It performs data calculations by referring to past data and feedback information, and outputs a proposal.

[0095] Step 3:

[0096] The server generates specific suggestions tailored to each user's environment based on the analysis results. In this process, it uses the output of intelligent processing to generate personalized suggestions, which are then output to the terminal via information and communication means. Specifically, the generated suggestions are converted into formats such as text, icons, and graphs, and transmitted using a communication protocol.

[0097] Step 4:

[0098] The terminal receives suggestions sent from the server and displays them to the user. In this step, the suggestions are visually presented on the terminal's display based on the received data. The user interface outputs the input data in a format that is easy to analyze and displays it in a format that is easy for the user to understand.

[0099] Step 5:

[0100] The user takes specific actions to adjust the environment based on the suggestions presented by the device. These actions may include adjusting the lighting, ventilating the room, or lowering the volume. The system then provides feedback information based on the user's actions.

[0101] Step 6:

[0102] The device collects user feedback and sends it to the server. The feedback data is then analyzed again on the server and used as valuable data to improve the accuracy of new suggestions. In this step, the input feedback information is accurately recorded in the database and output as training data for the generating AI model.

[0103] (Application Example 1)

[0104] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0105] To enhance user comfort in stores, educational facilities, and homes, it is necessary to appropriately adjust the environment. However, current methods make it difficult to adjust the environment in real time, often resulting in an inability to respond immediately. Furthermore, there are limitations to manually making detailed environmental adjustments to meet the individual needs of each user. A system is needed that can accommodate individual users while maintaining overall comfort.

[0106] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0107] In this invention, the server includes detection means for collecting multiple pieces of environmental information in real time, intelligent processing means for analyzing the environmental information and generating optimized instructions, and transmission means for generating the instructions as personalized suggestions and transmitting them to the user device. This makes it possible to generate suggestions to improve user comfort and quickly notify the user device.

[0108] "Environmental information" refers to data about the user's surrounding environment, such as light intensity, temperature, and sound volume.

[0109] "Detection means" refers to devices or systems that collect environmental information in real time.

[0110] "Intelligent processing means" refers to algorithms and software that analyze collected environmental information and generate instructions optimized for the user.

[0111] "Means of transmission" refers to communication devices and protocols used to transmit generated instructions and suggestions to user devices.

[0112] A "user device" is a device used to receive suggestions and notifications and provide information to users.

[0113] "Comfort" is a concept that describes the degree of pleasantness and ease of living that users experience.

[0114] "Instructions" refer to specific guidance and information generated to adjust the environment or make suggestions to users.

[0115] The system that realizes this invention comprises various sensor devices, an artificial intelligence-based data analysis device, a communication module, and a user terminal. Details of each component are described below.

[0116] The server acquires real-time data such as light intensity, temperature, and sound level from environmental sensors installed in commercial facilities and educational institutions. These environmental sensors are placed throughout stores and classrooms, and periodically transmit data to the server. This allows the server to always have access to the latest environmental information.

[0117] The server is equipped with artificial intelligence software such as TENSORFLOW® and PyTorch, which analyzes the collected environmental data. The analyzed data is optimized into suggestions to improve user comfort, and these suggestions are then personalized by a generative AI model.

[0118] The generated suggestions are transmitted to the user's smartphone or smart glasses via a communication module. The suggestions are displayed on the user's device and provided as instructions, for example, regarding temperature control or lighting settings within a store. Users can review these instructions and choose to respond automatically or manually.

[0119] As a concrete example, in a shopping mall on a weekend, a server analyzes information obtained from temperature sensors and, if it determines that the temperature inside the store is not suitable, generates a suggestion for air conditioning control. This suggestion is notified to the user's terminal, and by maintaining an optimal environment, customer comfort is improved.

[0120] An example of a prompt message that can be input into the AI ​​model is, "Based on the current environmental data within the store, please generate suggestions for temperature adjustments to improve customer comfort." This makes it possible to ensure comfort efficiently and effectively.

[0121] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0122] Step 1:

[0123] The server aggregates environmental information such as light intensity, temperature, and sound volume acquired from various sensors. This information is measured in real time by the sensors and transmitted to the server. This allows the server to understand the current environmental conditions. The input is environmental data from the sensors, and the output is integrated environmental information.

[0124] Step 2:

[0125] The server analyzes aggregated environmental information using artificial intelligence software (e.g., TensorFlow, PyTorch). The analysis process uses past data patterns and current environmental conditions to derive optimal suggestions for maintaining comfort. The input is integrated environmental information, and the output is the suggested content. A generative AI model is used with prompts to create personalized suggestions.

[0126] Step 3:

[0127] The server sends the generated suggestions to the user's terminal via a communication module. In this process, the suggestions are compiled in a user-friendly format and notified to the user's smartphone or smart glasses. The input is the suggested content, and the output is the notification message displayed on the terminal.

[0128] Step 4:

[0129] The device notifies the user of the proposed action based on the received suggestion. The user can review this notification and choose to take action according to the suggestion. The input is the notification message, and the output is the suggestion displayed on the user's screen.

[0130] Step 5:

[0131] Based on the suggestions displayed on the terminal, the user can manually adjust the environment as needed, or instruct the terminal to automatically adjust it. This includes specific actions such as changing air conditioning or lighting settings. The input is the user's selection, and the output is the instruction for environmental adjustment.

[0132] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0133] This invention is an AI integrated system for maintaining visual health and providing a comfortable learning environment, characterized by recognizing the user's emotions using an emotion engine and making suggestions based on those emotions. The system comprises sensor means for collecting and analyzing environmental data in real time, artificial intelligence means for processing the data, communication means for communicating with the user, and control means for adjusting the environment.

[0134] System Design

[0135] The server collects data such as light intensity, temperature, and volume in real time from environmental sensor devices placed in classrooms and homes. It also uses an emotion engine to recognize emotions from the user's facial expressions and voice tone, and evaluates their psychological state.

[0136] As an artificial intelligence tool, the server analyzes collected environmental and emotional data to generate optimal instructions that take visual and mental health into consideration. This analysis includes combining historical data with current environmental conditions to propose a personalized learning environment.

[0137] Using communication methods, the server sends the generated suggestions and instructions to the user's terminal. This allows the terminal to provide the user with information in a meaningful way and facilitate immediate action.

[0138] The control system supports users in engaging with an optimal environment by automatically adjusting environmental factors such as lighting and sound based on instructions from the terminal. It also performs adjustments to reduce stress based on information obtained from the emotion engine.

[0139] Specific example

[0140] Specific examples in the classroom:

[0141] The server uses an emotion engine to detect if a student may be fatigued.

[0142] The server suggests adjusting the light intensity and break times to create a more relaxing environment, and sends instructions to the terminal.

[0143] The device notifies the teacher of the suggestion and automatically adjusts the classroom lighting to an appropriate brightness.

[0144] Specific examples in the home:

[0145] The server uses an emotion engine to recognize when a child is experiencing stress.

[0146] The server suggests lowering the music volume or playing relaxation music and sends instructions to the terminal.

[0147] The device controls the audio device according to the suggestion and prompts the parent to take appropriate action.

[0148] As described above, the system of the present invention can provide a physically and psychologically optimized learning environment through the analysis of environmental data and emotional data.

[0149] The following describes the processing flow.

[0150] Step 1:

[0151] The server collects environmental data in real time from sensor devices installed in classrooms and homes. In addition to light intensity, temperature, and sound volume, it also records users' facial expressions and voices using cameras and microphones, which are then used as data for analysis by an emotion engine.

[0152] Step 2:

[0153] The server uses an emotion engine to recognize the user's emotional state from acquired facial expression data and voice tone. This recognition result is used to evaluate whether the user is tired or stressed.

[0154] Step 3:

[0155] The server integrates environmental data and emotion recognition results and analyzes them using artificial intelligence. The goal of the analysis is to generate optimal instructions to maintain visual health and ensure the user's psychological well-being.

[0156] Step 4:

[0157] Based on the analysis results, the server generates personalized suggestions. Specifically, these suggestions include recommendations tailored to the user's situation, such as appropriate light intensity adjustments, timing of study breaks, and playback of relaxation music.

[0158] Step 5:

[0159] The server sends the generated suggestions to the user's terminal using a communication method. During this process, the suggestions are notified visually or audibly, and measures are taken to ensure the user can easily understand them.

[0160] Step 6:

[0161] The terminal displays suggestions received from the server through a user interface. It also automatically adjusts environmental settings based on these suggestions, such as changing the brightness of the lighting or controlling the sound system.

[0162] Step 7:

[0163] Users (teachers, parents, or children) can receive notifications on their devices and choose appropriate actions based on the suggestions. For example, they may realize that environmental adjustments contribute to stress reduction, leading to a more comfortable learning and living environment.

[0164] Step 8:

[0165] Users send feedback and information about the effectiveness of the suggestions they receive from their devices to the server. This allows for continuous improvement, contributing to better accuracy of future suggestions.

[0166] (Example 2)

[0167] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0168] In modern times, a lack of physical and psychological comfort in the learning environment can negatively impact learning efficiency and visual health. Furthermore, conventional systems struggle to adjust the environment while considering the user's emotional state, making it difficult to provide individually optimized suggestions. Therefore, there is a need for a system that comprehensively analyzes environmental and emotional information to provide the optimal environment for learners.

[0169] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0170] In this invention, the server includes a measuring device that collects multiple pieces of environmental information in real time, a computing device that analyzes the environmental information and emotional information and generates optimized instructions, and a communication device that generates the instructions as personalized suggestions and transmits them to the user device. This makes it possible to optimize the learning environment to reflect the user's emotional state in real time.

[0171] "Environmental information" is a general term for physical data related to the space used by the user, such as light intensity, temperature, and sound volume.

[0172] A "measuring device" is a device used to collect environmental information in real time, and includes measuring instruments such as sensors.

[0173] A "computational device" is a device that analyzes collected environmental and emotional information and generates optimized instructions, and includes computers.

[0174] "Communication equipment" refers to devices and technologies used to transmit instructions generated by a server to user devices, and includes network interfaces, etc.

[0175] An "emotion analysis device" is a device that analyzes a user's facial expressions and voice to identify their emotional state.

[0176] An "evaluation device" is a device that collects feedback from users and incorporates it into the analysis results.

[0177] "Instructions" refer to specific suggestions or requirements for environmental adjustments generated based on the analysis results.

[0178] A "control device" is a device that automatically adjusts the environment based on a proposal, and includes the operation of lighting and sound equipment.

[0179] This invention is a system designed to provide a learning environment optimized for the user. Specifically, it involves collaboration between the server, terminal, and user to create an environment where the user can learn efficiently and comfortably.

[0180] server

[0181] The server uses multiple measuring devices to collect environmental information. These consist of sensors that measure important physical indicators in the learning space, such as light intensity, temperature, and sound volume. The server collects this data in real time and analyzes the user's facial expressions and voice tone using an emotion analysis device. This allows the server to assess the user's psychological state, and the user's emotional state is reflected in the operation of the entire system.

[0182] terminal

[0183] Upon receiving instructions from the server, the terminal automatically adjusts the environment based on that information. The terminal receives optimized instructions from the server via a communication device and uses a control device to adjust the brightness of the lighting or the volume of the sound. For example, if the room is too dark, the terminal will adjust the lighting to raise the brightness to an appropriate level.

[0184] User

[0185] Users provide feedback using information and environmental adjustments provided from their devices. The evaluation device collects this feedback and uses it to optimize environmental conditions for future use. This allows the system to continuously provide users with a better environment.

[0186] Hardware and software to be used

[0187] This system uses light intensity sensors, temperature sensors, and volume sensors as measuring devices. The server also includes an emotion analysis device and software implemented to evaluate emotional states using machine learning models.

[0188] Specific example

[0189] For example, when used in a classroom, the system detects fatigue from students' facial expressions and, if it detects excessive brightness from the light sensor, sends a command to the terminal to adjust the lighting to a warmer tone. This allows the learning environment to adapt to the students' comfort.

[0190] Example of a prompt

[0191] "Generate a procedure that proposes the optimal visual and psychological environment settings for the user based on environmental sensor data and emotional data."

[0192] Based on this prompt, the generative AI model constructs personalized and optimal environment suggestions.

[0193] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0194] Step 1:

[0195] The server collects environmental information such as light intensity, temperature, and sound volume in real time through measuring devices. The input is data measured by each sensor, and the output is an aggregate of this data. The server stores this data in a database in preparation for the next analysis step.

[0196] Step 2:

[0197] The server uses an emotion analysis device to acquire user facial expression and voice data. This input data is analyzed using image processing and voice analysis techniques. As output, the user's emotional state is identified and their psychological condition is evaluated.

[0198] Step 3:

[0199] The server uses collected environmental and emotional information to generate optimal instructions tailored to the user through a generative AI model. The AI ​​model's input consists of environmental and emotional data. Data processing outputs personalized suggestions for each user. For example, it might create environmental adjustment suggestions that improve the user's learning efficiency based on past history and current circumstances.

[0200] Step 4:

[0201] The server sends the generated proposal to the terminal via a communication device. The input is the generated instruction, which is sent to the terminal via the communication protocol. The output is the notification of the proposal to the terminal.

[0202] Step 5:

[0203] The terminal receives instructions from the server and uses a control unit to perform the corresponding environmental adjustments. The input is the instructions from the server, and specific actions include setting the lighting to a specific brightness or adjusting the volume appropriately. The output is the state in which the user can operate in the optimized environment after the adjustments.

[0204] Step 6:

[0205] Users evaluate their experience based on the provided environment and provide feedback. Input consists of the user's perceived usability and efficiency, collected by the evaluation device. Output is sent to the server as feedback data and used for future analysis and proposal generation.

[0206] (Application Example 2)

[0207] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0208] In current commercial facilities, it is difficult to maximize the customer experience because it is not possible to grasp customers' emotional states in real time and adaptively adjust the in-store environment based on that information. Furthermore, providing an environment that customers find comfortable requires processing large amounts of environmental and emotional data and responding flexibly accordingly.

[0209] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0210] In this invention, the server includes sensor means for collecting multiple environmental data in real time, artificial intelligence means for analyzing the environmental data and generating optimized instructions, and emotion recognition means for recognizing emotions and making suggestions for improving the environment based on that data. This makes it possible to adjust the environment appropriately to match the emotional state of the customer.

[0211] "Environmental data" refers to information about elements that affect a user's physical and psychological state, including light intensity, temperature, volume, and the user's facial expressions and voice.

[0212] "Sensing means" refers to a device or technology for collecting environmental data in real time.

[0213] "Artificial intelligence means" refers to a system or algorithm for analyzing collected environmental data and generating optimized instructions based on that data.

[0214] "Communication means" refers to technology or equipment for transmitting generated suggestions or instructions to a user terminal.

[0215] "Control means" refers to technology or devices for automatically adjusting the environment based on a proposal.

[0216] "Emotion recognition means" refers to a technology or system that recognizes a user's emotions from their facial expressions and voice, and makes improvement suggestions based on those emotions.

[0217] In order to implement the present invention, the following system configuration is necessary.

[0218] The server collects environmental data in real time from multiple sensors placed within the user environment, including light intensity, temperature, volume, facial expressions, and audio information. This includes sensor devices such as cameras and microphones, and utilizes software libraries such as OpenCV and librosa. The server analyzes this data and uses emotion recognition to evaluate the user's emotions and psychological state. The analyzed data is then processed by a generative AI model to generate suggestions for improving the environment.

[0219] The generated suggestions are sent to the user's terminal via a communication method. The user's terminal receives these suggestions and controls the store's IoT devices to make actual environmental adjustments. For example, it might adjust the store's lighting or music as needed to improve the customer experience. Additionally, prompt messages are generated in response to the user's actions, such as "Please suggest environmental adjustments to help customers relax," and these are used within the system.

[0220] As a concrete example, if a customer in a store feels stressed, a relaxing atmosphere can be created by playing soft music and dimming the lights. This entire process enhances customer satisfaction by providing an optimal environment.

[0221] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0222] Step 1:

[0223] The server uses sensor devices installed in the user's environment to collect environmental data such as light intensity, temperature, volume, facial expressions, and voice in real time. Input is data from various sensors, and output is an integrated environmental dataset. This data is used for subsequent emotion recognition and environmental adjustments.

[0224] Step 2:

[0225] The server uses software libraries such as OpenCV and librosa to analyze collected environmental data and recognize emotions from the user's facial expressions and voice. The input is an environmental dataset, and the output is an analysis result indicating the user's emotional state. This result is fed into a generative AI model, which serves as the basis for further data processing.

[0226] Step 3:

[0227] The server's AI model generates optimized environment improvement suggestions based on the analysis results. The input is the result of the emotion analysis, and the output is specific improvement suggestions. These suggestions include specific actions such as adjusting the lighting, selecting music, and adjusting the volume.

[0228] Step 4:

[0229] The server sends the generated improvement suggestions to the user terminal via a communication method. The input is the improvement suggestion, and the output is information as a notification on the user terminal. This prepares the user to review the suggestion and take the necessary actions.

[0230] Step 5:

[0231] The terminal controls IoT devices within the store based on the received suggestions to adjust the actual environment. The input is notification information from the server, and the output is the adjusted store environment. Specifically, actions such as changing the lighting and playing music are performed to provide a relaxing space for customers.

[0232] By following these steps, a comfortable environment tailored to the customer's emotional state is provided, resulting in a better customer experience.

[0233] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0234] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0235] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0236] [Second Embodiment]

[0237] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0238] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0239] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0240] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0241] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0242] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0243] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0244] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0245] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0246] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0247] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0248] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0249] This invention is an AI-integrated system for optimizing educational and home environments while maintaining visual health. The system comprises sensor means, artificial intelligence means, communication means, and control means, and operates as follows.

[0250] System Design

[0251] The server collects real-time environmental data such as light levels, temperature, and noise levels in classrooms and homes through multiple environmental sensors. This allows for constant monitoring of the latest conditions.

[0252] The server, acting as an artificial intelligence tool, highly analyzes collected environmental data and generates optimal instructions for maintaining visual health. This AI model learns by considering past data and environmental parameters, allowing its suggestions to improve accuracy over time.

[0253] The server generates personalized suggestions based on the analysis results and sends them to each user's terminal. These suggestions may include, for example, adjusting classroom lighting settings, managing break times during study sessions, and optimizing seating arrangements.

[0254] The terminal receives communications from the server and displays suggestions to the user in an easy-to-understand format. The user can then take specific actions in response to these suggestions.

[0255] By using control mechanisms, the terminal automatically adjusts lighting and volume as needed. Furthermore, by receiving user feedback and sending it to the server, more effective suggestions can be made.

[0256] Specific example

[0257] Specific measures in the classroom:

[0258] If the server detects that there is insufficient lighting in the classroom, it generates an instruction to increase the lighting.

[0259] The device notifies the teacher and automatically adjusts the light intensity in conjunction with the lighting system.

[0260] The user (teacher) can review the presented suggestions and make manual adjustments if necessary.

[0261] Specific examples in the home:

[0262] If the server detects that the volume level is high while studying at home, it will generate a suggestion recommending a quieter environment.

[0263] The device will notify parents or children to lower the volume, or it will automatically adjust the volume of the audio device.

[0264] Users (parents) can readjust the environment based on the suggestions to improve the effectiveness of home learning.

[0265] Thus, the system of the present invention collects and analyzes environmental data in real time and provides appropriate suggestions, thereby realizing an optimal learning environment while protecting visual health.

[0266] The following describes the processing flow.

[0267] Step 1:

[0268] The server collects environmental data in real time from multiple sensor devices placed in classrooms and homes. This includes light intensity, temperature, humidity, and sound levels. The collected data is immediately stored in a database.

[0269] Step 2:

[0270] The server preprocesses the collected data. Specifically, it filters out noise from the sensor data and imputes missing values. This preprocessing enhances the accuracy and consistency of the data.

[0271] Step 3:

[0272] The server uses artificial intelligence to analyze pre-processed data. Here, it identifies factors affecting visual health and generates instructions for optimal environmental adjustments.

[0273] Step 4:

[0274] The server generates personalized suggestions based on the analysis results. These suggestions include recommendations for the most suitable lighting adjustments, break times, and seating arrangements for each individual user.

[0275] Step 5:

[0276] The server sends the generated proposals to the terminals of each user. Information is efficiently transmitted through the network via the communication means.

[0277] Step 6:

[0278] The terminal displays the proposals received from the server on the user interface and notifies the user. Depending on the need, voice alerts or pop-up notifications may also be used.

[0279] Step 7:

[0280] The terminal executes the automatic control of the environment based on the proposals through the control means. For example, it sends a signal to the lighting system to adjust the light intensity in the classroom or home.

[0281] Step 8:

[0282] The user (teacher, parent, or child) receives the notification from the terminal and takes actions according to the proposals to maintain visual health and optimize the learning environment.

[0283] Step 9:

[0284] The user sends feedback on the effects of the proposals and environmental changes from the terminal to the server. This information is stored in the database and used to refine subsequent proposals.

[0285] (Example 1)

[0286] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0287] There is a need for systems that can provide an optimal learning environment in real time while maintaining visual health in educational and home settings. However, conventional systems have insufficient collection and analysis of environmental information, making it difficult to provide personalized recommendations for individual users. Furthermore, there is a need for a mechanism that effectively incorporates user feedback to improve the accuracy of recommendations.

[0288] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0289] In this invention, the server includes a measurement means, an intelligent processing means, and an information communication means. This makes it possible to provide user-optimized suggestions while maintaining visual health based on real-time information of the educational and home environments.

[0290] "Measurement means" refers to a device that collects environmental information in real time using various sensors.

[0291] "Intelligent processing means" refers to a device that uses an artificial intelligence model to analyze collected environmental information and propose optimal environmental conditions while maintaining visual health.

[0292] "Information and communication means" refers to communication protocols and devices used to transmit proposals generated by a server to a user's terminal.

[0293] "Display means" refers to devices or interfaces that visually present suggestions sent from the server to the user's terminal in an easily understandable way.

[0294] "Means of receiving feedback" refers to devices or interfaces that collect user behavior and opinions, reflect them in a database, and improve the accuracy of system suggestions.

[0295] This invention is an advanced AI-integrated system for maintaining visual health in educational and home environments. The system utilizes servers, terminals, and sensor devices as its primary hardware components.

[0296] The server plays a central role in analyzing environmental information, utilizing an artificial intelligence model (generative AI model) aimed at maintaining visual health. This AI model learns from past environmental data and user feedback to generate optimal suggestions based on environmental conditions.

[0297] The sensor system functions as a means of measuring environmental information and includes various sensors such as light sensors, temperature sensors, and microphones. These sensors are placed in classrooms and homes to collect real-time data on light intensity, temperature, and sound volume. The collected data is transmitted to a server for analysis.

[0298] The terminal is equipped with information communication and display means to show the user suggestions sent from the server. The suggestions are represented on the terminal screen using icons and graphs so that they can be understood intuitively. The user can modify their actions based on the presented suggestions, and the terminal can also automatically adjust lighting and volume.

[0299] As a concrete example, in a classroom, the server detects insufficient light levels based on data from light sensors and generates a suggestion to increase the lighting. The terminal notifies the teacher of this suggestion, and the lighting system automatically adjusts. At home, the server detects excessive volume and suggests lowering it, and the terminal reduces the volume via an audio device.

[0300] As an example of a prompt, the following question can be input to the generating AI model:

[0301] "If the classroom lighting is insufficient, suggest how to adjust it."

[0302] "What volume settings are best for improving the home study environment?"

[0303] Through these means, the system of the present invention can support the user to construct an optimal learning environment while maintaining visual health.

[0304] The flow of the specific process in Example 1 will be described with reference to FIG. 11.

[0305] Step ①:

[0306] The server collects real-time environmental data such as light intensity, temperature, and volume from sensor devices placed in classrooms and homes. Using this data as input, it records it in the database. Specifically, it converts the analog signal obtained from the sensor into digital data and stores it as time-series data.

[0307] Step ②:

[0308] The server analyzes the collected environmental data using intelligent processing means. In this step, based on the input environmental data, it performs analysis using the generated AI model to calculate the optimal environmental conditions for maintaining visual health. It performs data calculations by referring to past data and feedback information and outputs the proposed content.

[0309] Step ③:

[0310] The server generates specific proposals according to the environment of each user from the analysis results. In this process, it uses the output of the intelligent processing means to generate individualized proposals and outputs them to the terminal through information communication means. As specific operations, it converts the generated proposals into forms such as text, icons, and graphs and transmits them using communication protocols.

[0311] Step ④:

[0312] It should be noted that in the translation, "①" and "②" are used to represent "1" and "2" in Chinese characters to maintain the consistency of the original text's format. If you have any other questions, please feel free to let me know.The terminal receives suggestions sent from the server and displays them to the user. In this step, the suggestions are visually presented on the terminal's display based on the received data. The user interface outputs the input data in a format that is easy to analyze and displays it in a format that is easy for the user to understand.

[0313] Step 5:

[0314] The user takes specific actions to adjust the environment based on the suggestions presented by the device. These actions may include adjusting the lighting, ventilating the room, or lowering the volume. The system then provides feedback information based on the user's actions.

[0315] Step 6:

[0316] The device collects user feedback and sends it to the server. The feedback data is then analyzed again on the server and used as valuable data to improve the accuracy of new suggestions. In this step, the input feedback information is accurately recorded in the database and output as training data for the generating AI model.

[0317] (Application Example 1)

[0318] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0319] To enhance user comfort in stores, educational facilities, and homes, it is necessary to appropriately adjust the environment. However, current methods make it difficult to adjust the environment in real time, often resulting in an inability to respond immediately. Furthermore, there are limitations to manually making detailed environmental adjustments to meet the individual needs of each user. A system is needed that can accommodate individual users while maintaining overall comfort.

[0320] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0321] In this invention, the server includes detection means for collecting multiple pieces of environmental information in real time, intelligent processing means for analyzing the environmental information and generating optimized instructions, and transmission means for generating the instructions as personalized suggestions and transmitting them to the user device. This makes it possible to generate suggestions to improve user comfort and quickly notify the user device.

[0322] "Environmental information" refers to data about the user's surrounding environment, such as light intensity, temperature, and sound volume.

[0323] "Detection means" refers to devices or systems that collect environmental information in real time.

[0324] "Intelligent processing means" refers to algorithms and software that analyze collected environmental information and generate instructions optimized for the user.

[0325] "Means of transmission" refers to communication devices and protocols used to transmit generated instructions and suggestions to user devices.

[0326] A "user device" is a device used to receive suggestions and notifications and provide information to users.

[0327] "Comfort" is a concept that describes the degree of pleasantness and ease of living that users experience.

[0328] "Instructions" refer to specific guidance and information generated to adjust the environment or make suggestions to users.

[0329] The system that realizes this invention comprises various sensor devices, an artificial intelligence-based data analysis device, a communication module, and a user terminal. Details of each component are described below.

[0330] The server acquires real-time data such as light intensity, temperature, and sound level from environmental sensors installed in commercial facilities and educational institutions. These environmental sensors are placed throughout stores and classrooms, and periodically transmit data to the server. This allows the server to always have access to the latest environmental information.

[0331] The server is equipped with artificial intelligence software such as TensorFlow and PyTorch, which is used to analyze the collected environmental data. The analyzed data is optimized into suggestions to improve user comfort, and these suggestions are then personalized by a generative AI model.

[0332] The generated suggestions are transmitted to the user's smartphone or smart glasses via a communication module. The suggestions are displayed on the user's device and provided as instructions, for example, regarding temperature control or lighting settings within a store. Users can review these instructions and choose to respond automatically or manually.

[0333] As a concrete example, in a shopping mall on a weekend, a server analyzes information obtained from temperature sensors and, if it determines that the temperature inside the store is not suitable, generates a suggestion for air conditioning control. This suggestion is notified to the user's terminal, and by maintaining an optimal environment, customer comfort is improved.

[0334] An example of a prompt message that can be input into the AI ​​model is, "Based on the current environmental data within the store, please generate suggestions for temperature adjustments to improve customer comfort." This makes it possible to ensure comfort efficiently and effectively.

[0335] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0336] Step 1:

[0337] The server aggregates environmental information such as light intensity, temperature, and sound volume acquired from various sensors. This information is measured in real time by the sensors and transmitted to the server. This allows the server to understand the current environmental conditions. The input is environmental data from the sensors, and the output is integrated environmental information.

[0338] Step 2:

[0339] The server analyzes aggregated environmental information using artificial intelligence software (e.g., TensorFlow, PyTorch). The analysis process uses past data patterns and current environmental conditions to derive optimal suggestions for maintaining comfort. The input is integrated environmental information, and the output is the suggested content. A generative AI model is used with prompts to create personalized suggestions.

[0340] Step 3:

[0341] The server sends the generated suggestions to the user's terminal via a communication module. In this process, the suggestions are compiled in a user-friendly format and notified to the user's smartphone or smart glasses. The input is the suggested content, and the output is the notification message displayed on the terminal.

[0342] Step 4:

[0343] The device notifies the user of the proposed action based on the received suggestion. The user can review this notification and choose to take action according to the suggestion. The input is the notification message, and the output is the suggestion displayed on the user's screen.

[0344] Step 5:

[0345] Based on the suggestions displayed on the terminal, the user can manually adjust the environment as needed, or instruct the terminal to automatically adjust it. This includes specific actions such as changing air conditioning or lighting settings. The input is the user's selection, and the output is the instruction for environmental adjustment.

[0346] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0347] This invention is an AI integrated system for maintaining visual health and providing a comfortable learning environment, characterized by recognizing the user's emotions using an emotion engine and making suggestions based on those emotions. The system comprises sensor means for collecting and analyzing environmental data in real time, artificial intelligence means for processing the data, communication means for communicating with the user, and control means for adjusting the environment.

[0348] System Design

[0349] The server collects data such as light intensity, temperature, and volume in real time from environmental sensor devices placed in classrooms and homes. It also uses an emotion engine to recognize emotions from the user's facial expressions and voice tone, and evaluates their psychological state.

[0350] As an artificial intelligence tool, the server analyzes collected environmental and emotional data to generate optimal instructions that take visual and mental health into consideration. This analysis includes combining historical data with current environmental conditions to propose a personalized learning environment.

[0351] Using communication methods, the server sends the generated suggestions and instructions to the user's terminal. This allows the terminal to provide the user with information in a meaningful way and facilitate immediate action.

[0352] The control system supports users in engaging with an optimal environment by automatically adjusting environmental factors such as lighting and sound based on instructions from the terminal. It also performs adjustments to reduce stress based on information obtained from the emotion engine.

[0353] Specific example

[0354] Specific examples in the classroom:

[0355] The server uses an emotion engine to detect if a student may be fatigued.

[0356] The server suggests adjusting the light intensity and break times to create a more relaxing environment, and sends instructions to the terminal.

[0357] The device notifies the teacher of the suggestion and automatically adjusts the classroom lighting to an appropriate brightness.

[0358] Specific examples in the home:

[0359] The server uses an emotion engine to recognize when a child is experiencing stress.

[0360] The server suggests lowering the music volume or playing relaxation music and sends instructions to the terminal.

[0361] The device controls the audio device according to the suggestion and prompts the parent to take appropriate action.

[0362] As described above, the system of the present invention can provide a physically and psychologically optimized learning environment through the analysis of environmental data and emotional data.

[0363] The following describes the processing flow.

[0364] Step 1:

[0365] The server collects environmental data in real time from sensor devices installed in classrooms and homes. In addition to light intensity, temperature, and sound volume, it also records users' facial expressions and voices using cameras and microphones, which are then used as data for analysis by an emotion engine.

[0366] Step 2:

[0367] The server uses an emotion engine to recognize the user's emotional state from acquired facial expression data and voice tone. This recognition result is used to evaluate whether the user is tired or stressed.

[0368] Step 3:

[0369] The server integrates environmental data and emotion recognition results and analyzes them using artificial intelligence. The goal of the analysis is to generate optimal instructions to maintain visual health and ensure the user's psychological well-being.

[0370] Step 4:

[0371] Based on the analysis results, the server generates personalized suggestions. Specifically, these suggestions include recommendations tailored to the user's situation, such as appropriate light intensity adjustments, timing of study breaks, and playback of relaxation music.

[0372] Step 5:

[0373] The server sends the generated suggestions to the user's terminal using a communication method. During this process, the suggestions are notified visually or audibly, and measures are taken to ensure the user can easily understand them.

[0374] Step 6:

[0375] The terminal displays suggestions received from the server through a user interface. It also automatically adjusts environmental settings based on these suggestions, such as changing the brightness of the lighting or controlling the sound system.

[0376] Step 7:

[0377] Users (teachers, parents, or children) can receive notifications on their devices and choose appropriate actions based on the suggestions. For example, they may realize that environmental adjustments contribute to stress reduction, leading to a more comfortable learning and living environment.

[0378] Step 8:

[0379] Users send feedback and information about the effectiveness of the suggestions they receive from their devices to the server. This allows for continuous improvement, contributing to better accuracy of future suggestions.

[0380] (Example 2)

[0381] Next, we will describe Example 2. 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".

[0382] In modern times, a lack of physical and psychological comfort in the learning environment can negatively impact learning efficiency and visual health. Furthermore, conventional systems struggle to adjust the environment while considering the user's emotional state, making it difficult to provide individually optimized suggestions. Therefore, there is a need for a system that comprehensively analyzes environmental and emotional information to provide the optimal environment for learners.

[0383] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0384] In this invention, the server includes a measuring device that collects multiple pieces of environmental information in real time, a computing device that analyzes the environmental information and emotional information and generates optimized instructions, and a communication device that generates the instructions as personalized suggestions and transmits them to the user device. This makes it possible to optimize the learning environment to reflect the user's emotional state in real time.

[0385] "Environmental information" is a general term for physical data related to the space used by the user, such as light intensity, temperature, and sound volume.

[0386] A "measuring device" is a device used to collect environmental information in real time, and includes measuring instruments such as sensors.

[0387] A "computational device" is a device that analyzes collected environmental and emotional information and generates optimized instructions, and includes computers.

[0388] "Communication equipment" refers to devices and technologies used to transmit instructions generated by a server to user devices, and includes network interfaces, etc.

[0389] An "emotion analysis device" is a device that analyzes a user's facial expressions and voice to identify their emotional state.

[0390] An "evaluation device" is a device that collects feedback from users and incorporates it into the analysis results.

[0391] "Instructions" refer to specific suggestions or requirements for environmental adjustments generated based on the analysis results.

[0392] A "control device" is a device that automatically adjusts the environment based on a proposal, and includes the operation of lighting and sound equipment.

[0393] This invention is a system designed to provide a learning environment optimized for the user. Specifically, it involves collaboration between the server, terminal, and user to create an environment where the user can learn efficiently and comfortably.

[0394] server

[0395] The server uses multiple measuring devices to collect environmental information. These consist of sensors that measure important physical indicators in the learning space, such as light intensity, temperature, and sound volume. The server collects this data in real time and analyzes the user's facial expressions and voice tone using an emotion analysis device. This allows the server to assess the user's psychological state, and the user's emotional state is reflected in the operation of the entire system.

[0396] terminal

[0397] Upon receiving instructions from the server, the terminal automatically adjusts the environment based on that information. The terminal receives optimized instructions from the server via a communication device and uses a control device to adjust the brightness of the lighting or the volume of the sound. For example, if the room is too dark, the terminal will adjust the lighting to raise the brightness to an appropriate level.

[0398] User

[0399] Users provide feedback using information and environmental adjustments provided from their devices. The evaluation device collects this feedback and uses it to optimize environmental conditions for future use. This allows the system to continuously provide users with a better environment.

[0400] Hardware and software to be used

[0401] This system uses light intensity sensors, temperature sensors, and volume sensors as measuring devices. The server also includes an emotion analysis device and software implemented to evaluate emotional states using machine learning models.

[0402] Specific example

[0403] For example, when used in a classroom, the system detects fatigue from students' facial expressions and, if it detects excessive brightness from the light sensor, sends a command to the terminal to adjust the lighting to a warmer tone. This allows the learning environment to adapt to the students' comfort.

[0404] Example of a prompt

[0405] "Generate a procedure that proposes the optimal visual and psychological environment settings for the user based on environmental sensor data and emotional data."

[0406] Based on this prompt, the generative AI model constructs personalized and optimal environment suggestions.

[0407] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0408] Step 1:

[0409] The server collects environmental information such as light intensity, temperature, and sound volume in real time through measuring devices. The input is data measured by each sensor, and the output is an aggregate of this data. The server stores this data in a database in preparation for the next analysis step.

[0410] Step 2:

[0411] The server uses an emotion analysis device to acquire user facial expression and voice data. This input data is analyzed using image processing and voice analysis techniques. As output, the user's emotional state is identified and their psychological condition is evaluated.

[0412] Step 3:

[0413] The server uses collected environmental and emotional information to generate optimal instructions tailored to the user through a generative AI model. The AI ​​model's input consists of environmental and emotional data. Data processing outputs personalized suggestions for each user. For example, it might create environmental adjustment suggestions that improve the user's learning efficiency based on past history and current circumstances.

[0414] Step 4:

[0415] The server sends the generated proposal to the terminal via a communication device. The input is the generated instruction, which is sent to the terminal via the communication protocol. The output is the notification of the proposal to the terminal.

[0416] Step 5:

[0417] The terminal receives instructions from the server and uses a control unit to perform the corresponding environmental adjustments. The input is the instructions from the server, and specific actions include setting the lighting to a specific brightness or adjusting the volume appropriately. The output is the state in which the user can operate in the optimized environment after the adjustments.

[0418] Step 6:

[0419] Users evaluate their experience based on the provided environment and provide feedback. Input consists of the user's perceived usability and efficiency, collected by the evaluation device. Output is sent to the server as feedback data and used for future analysis and proposal generation.

[0420] (Application Example 2)

[0421] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0422] In current commercial facilities, it is difficult to maximize the customer experience because it is not possible to grasp customers' emotional states in real time and adaptively adjust the in-store environment based on that information. Furthermore, providing an environment that customers find comfortable requires processing large amounts of environmental and emotional data and responding flexibly accordingly.

[0423] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0424] In this invention, the server includes sensor means for collecting multiple environmental data in real time, artificial intelligence means for analyzing the environmental data and generating optimized instructions, and emotion recognition means for recognizing emotions and making suggestions for improving the environment based on that data. This makes it possible to adjust the environment appropriately to match the emotional state of the customer.

[0425] "Environmental data" refers to information about elements that affect a user's physical and psychological state, including light intensity, temperature, volume, and the user's facial expressions and voice.

[0426] "Sensing means" refers to a device or technology for collecting environmental data in real time.

[0427] "Artificial intelligence means" refers to a system or algorithm for analyzing collected environmental data and generating optimized instructions based on that data.

[0428] "Communication means" refers to technology or equipment for transmitting generated suggestions or instructions to a user terminal.

[0429] "Control means" refers to technology or devices for automatically adjusting the environment based on a proposal.

[0430] "Emotion recognition means" refers to a technology or system that recognizes a user's emotions from their facial expressions and voice, and makes improvement suggestions based on those emotions.

[0431] In order to implement the present invention, the following system configuration is necessary.

[0432] The server collects environmental data in real time from multiple sensors placed within the user environment, including light intensity, temperature, volume, facial expressions, and audio information. This includes sensor devices such as cameras and microphones, and utilizes software libraries such as OpenCV and librosa. The server analyzes this data and uses emotion recognition to evaluate the user's emotions and psychological state. The analyzed data is then processed by a generative AI model to generate suggestions for improving the environment.

[0433] The generated suggestions are sent to the user's terminal via a communication method. The user's terminal receives these suggestions and controls the store's IoT devices to make actual environmental adjustments. For example, it might adjust the store's lighting or music as needed to improve the customer experience. Additionally, prompt messages are generated in response to the user's actions, such as "Please suggest environmental adjustments to help customers relax," and these are used within the system.

[0434] As a concrete example, if a customer in a store feels stressed, a relaxing atmosphere can be created by playing soft music and dimming the lights. This entire process enhances customer satisfaction by providing an optimal environment.

[0435] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0436] Step 1:

[0437] The server uses sensor devices installed in the user's environment to collect environmental data such as light intensity, temperature, volume, facial expressions, and voice in real time. Input is data from various sensors, and output is an integrated environmental dataset. This data is used for subsequent emotion recognition and environmental adjustments.

[0438] Step 2:

[0439] The server uses software libraries such as OpenCV and librosa to analyze collected environmental data and recognize emotions from the user's facial expressions and voice. The input is an environmental dataset, and the output is an analysis result indicating the user's emotional state. This result is fed into a generative AI model, which serves as the basis for further data processing.

[0440] Step 3:

[0441] The server's AI model generates optimized environment improvement suggestions based on the analysis results. The input is the result of the emotion analysis, and the output is specific improvement suggestions. These suggestions include specific actions such as adjusting the lighting, selecting music, and adjusting the volume.

[0442] Step 4:

[0443] The server sends the generated improvement suggestions to the user terminal via a communication method. The input is the improvement suggestion, and the output is information as a notification on the user terminal. This prepares the user to review the suggestion and take the necessary actions.

[0444] Step 5:

[0445] The terminal controls IoT devices within the store based on the received suggestions to adjust the actual environment. The input is notification information from the server, and the output is the adjusted store environment. Specifically, actions such as changing the lighting and playing music are performed to provide a relaxing space for customers.

[0446] By following these steps, a comfortable environment tailored to the customer's emotional state is provided, resulting in a better customer experience.

[0447] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0448] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0449] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0450] [Third Embodiment]

[0451] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0452] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0453] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0454] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0455] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0456] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0457] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0458] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0459] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0460] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0461] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0462] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0463] This invention is an AI-integrated system for optimizing educational and home environments while maintaining visual health. The system comprises sensor means, artificial intelligence means, communication means, and control means, and operates as follows.

[0464] System Design

[0465] The server collects real-time environmental data such as light levels, temperature, and noise levels in classrooms and homes through multiple environmental sensors. This allows for constant monitoring of the latest conditions.

[0466] The server, acting as an artificial intelligence tool, highly analyzes collected environmental data and generates optimal instructions for maintaining visual health. This AI model learns by considering past data and environmental parameters, allowing its suggestions to improve accuracy over time.

[0467] The server generates personalized suggestions based on the analysis results and sends them to each user's terminal. These suggestions may include, for example, adjusting classroom lighting settings, managing break times during study sessions, and optimizing seating arrangements.

[0468] The terminal receives communications from the server and displays suggestions to the user in an easy-to-understand format. The user can then take specific actions in response to these suggestions.

[0469] By using control mechanisms, the terminal automatically adjusts lighting and volume as needed. Furthermore, by receiving user feedback and sending it to the server, more effective suggestions can be made.

[0470] Specific example

[0471] Specific measures in the classroom:

[0472] If the server detects that there is insufficient lighting in the classroom, it generates an instruction to increase the lighting.

[0473] The device notifies the teacher and automatically adjusts the light intensity in conjunction with the lighting system.

[0474] The user (teacher) can review the presented suggestions and make manual adjustments if necessary.

[0475] Specific examples in the home:

[0476] If the server detects that the volume level is high while studying at home, it will generate a suggestion recommending a quieter environment.

[0477] The device will notify parents or children to lower the volume, or it will automatically adjust the volume of the audio device.

[0478] Users (parents) can readjust the environment based on the suggestions to improve the effectiveness of home learning.

[0479] Thus, the system of the present invention collects and analyzes environmental data in real time and provides appropriate suggestions, thereby realizing an optimal learning environment while protecting visual health.

[0480] The following describes the processing flow.

[0481] Step 1:

[0482] The server collects environmental data in real time from multiple sensor devices placed in classrooms and homes. This includes light intensity, temperature, humidity, and sound levels. The collected data is immediately stored in a database.

[0483] Step 2:

[0484] The server preprocesses the collected data. Specifically, it filters out noise from the sensor data and imputes missing values. This preprocessing enhances the accuracy and consistency of the data.

[0485] Step 3:

[0486] The server uses artificial intelligence to analyze pre-processed data. Here, it identifies factors affecting visual health and generates instructions for optimal environmental adjustments.

[0487] Step 4:

[0488] The server generates personalized suggestions based on the analysis results. These suggestions include recommendations for the most suitable lighting adjustments, break times, and seating arrangements for each individual user.

[0489] Step 5:

[0490] The server sends the generated suggestions to each user's terminal. Information is efficiently transmitted over the network via communication means.

[0491] Step 6:

[0492] The terminal displays suggestions received from the server on the user interface and notifies the user. If necessary, it may also use voice alerts or pop-up notifications.

[0493] Step 7:

[0494] The terminal, through its control mechanisms, performs automatic control of the environment based on suggestions. For example, it sends a signal to the lighting system to adjust the amount of light in a classroom or home.

[0495] Step 8:

[0496] Users (teachers, parents, or children) receive notifications on their devices and take action according to the suggestions to maintain visual health and optimize the learning environment.

[0497] Step 9:

[0498] Users send feedback from their devices to the server regarding the effectiveness of the proposals and changes in the environment. This information is stored in a database and used to refine future proposals.

[0499] (Example 1)

[0500] Next, we will describe Example 1. 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."

[0501] There is a need for systems that can provide an optimal learning environment in real time while maintaining visual health in educational and home settings. However, conventional systems have insufficient collection and analysis of environmental information, making it difficult to provide personalized recommendations for individual users. Furthermore, there is a need for a mechanism that effectively incorporates user feedback to improve the accuracy of recommendations.

[0502] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0503] In this invention, the server includes a measurement means, an intelligent processing means, and an information communication means. This makes it possible to provide user-optimized suggestions while maintaining visual health based on real-time information of the educational and home environments.

[0504] "Measurement means" refers to a device that collects environmental information in real time using various sensors.

[0505] "Intelligent processing means" refers to a device that uses an artificial intelligence model to analyze collected environmental information and propose optimal environmental conditions while maintaining visual health.

[0506] "Information and communication means" refers to communication protocols and devices used to transmit proposals generated by a server to a user's terminal.

[0507] "Display means" refers to devices or interfaces that visually present suggestions sent from the server to the user's terminal in an easily understandable way.

[0508] "Means of receiving feedback" refers to devices or interfaces that collect user behavior and opinions, reflect them in a database, and improve the accuracy of system suggestions.

[0509] This invention is an advanced AI-integrated system for maintaining visual health in educational and home environments. The system utilizes servers, terminals, and sensor devices as its primary hardware components.

[0510] The server plays a central role in analyzing environmental information, utilizing an artificial intelligence model (generative AI model) aimed at maintaining visual health. This AI model learns from past environmental data and user feedback to generate optimal suggestions based on environmental conditions.

[0511] The sensor system functions as a means of measuring environmental information and includes various sensors such as light sensors, temperature sensors, and microphones. These sensors are placed in classrooms and homes to collect real-time data on light intensity, temperature, and sound volume. The collected data is transmitted to a server for analysis.

[0512] The terminal is equipped with information communication and display means to show the user suggestions sent from the server. The suggestions are represented on the terminal screen using icons and graphs so that they can be understood intuitively. The user can modify their actions based on the presented suggestions, and the terminal can also automatically adjust lighting and volume.

[0513] As a concrete example, in a classroom, the server detects insufficient light levels based on data from light sensors and generates a suggestion to increase the lighting. The terminal notifies the teacher of this suggestion, and the lighting system automatically adjusts. At home, the server detects excessive volume and suggests lowering it, and the terminal reduces the volume via an audio device.

[0514] As an example of a prompt, the following question can be input to the generating AI model:

[0515] "If the classroom lighting is insufficient, suggest how to adjust it."

[0516] "What volume settings are best for improving the home study environment?"

[0517] The system of the present invention can support users in creating an optimal learning environment while maintaining their visual health through these means.

[0518] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0519] Step 1:

[0520] The server collects real-time environmental data such as light intensity, temperature, and sound volume from sensor devices placed in classrooms and homes. This data is used as input and recorded in a database. Specifically, it converts the analog signals acquired from the sensors into digital data and stores it as time-series data.

[0521] Step 2:

[0522] The server analyzes the collected environmental data using intelligent processing tools. In this step, based on the input environmental data, it performs analysis using a generative AI model to calculate the optimal environmental conditions for maintaining visual health. It performs data calculations by referring to past data and feedback information, and outputs a proposal.

[0523] Step 3:

[0524] The server generates specific suggestions tailored to each user's environment based on the analysis results. In this process, it uses the output of intelligent processing to generate personalized suggestions, which are then output to the terminal via information and communication means. Specifically, the generated suggestions are converted into formats such as text, icons, and graphs, and transmitted using a communication protocol.

[0525] Step 4:

[0526] The terminal receives suggestions sent from the server and displays them to the user. In this step, the suggestions are visually presented on the terminal's display based on the received data. The user interface outputs the input data in a format that is easy to analyze and displays it in a format that is easy for the user to understand.

[0527] Step 5:

[0528] The user takes specific actions to adjust the environment based on the suggestions presented by the device. These actions may include adjusting the lighting, ventilating the room, or lowering the volume. The system then provides feedback information based on the user's actions.

[0529] Step 6:

[0530] The device collects user feedback and sends it to the server. The feedback data is then analyzed again on the server and used as valuable data to improve the accuracy of new suggestions. In this step, the input feedback information is accurately recorded in the database and output as training data for the generating AI model.

[0531] (Application Example 1)

[0532] Next, we will explain Application Example 1. In the following explanation, 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."

[0533] To enhance user comfort in stores, educational facilities, and homes, it is necessary to appropriately adjust the environment. However, current methods make it difficult to adjust the environment in real time, often resulting in an inability to respond immediately. Furthermore, there are limitations to manually making detailed environmental adjustments to meet the individual needs of each user. A system is needed that can accommodate individual users while maintaining overall comfort.

[0534] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0535] In this invention, the server includes detection means for collecting multiple pieces of environmental information in real time, intelligent processing means for analyzing the environmental information and generating optimized instructions, and transmission means for generating the instructions as personalized suggestions and transmitting them to the user device. This makes it possible to generate suggestions to improve user comfort and quickly notify the user device.

[0536] "Environmental information" refers to data about the user's surrounding environment, such as light intensity, temperature, and sound volume.

[0537] "Detection means" refers to devices or systems that collect environmental information in real time.

[0538] "Intelligent processing means" refers to algorithms and software that analyze collected environmental information and generate instructions optimized for the user.

[0539] "Means of transmission" refers to communication devices and protocols used to transmit generated instructions and suggestions to user devices.

[0540] A "user device" is a device used to receive suggestions and notifications and provide information to users.

[0541] "Comfort" is a concept that describes the degree of pleasantness and ease of living that users experience.

[0542] "Instructions" refer to specific guidance and information generated to adjust the environment or make suggestions to users.

[0543] The system that realizes this invention comprises various sensor devices, an artificial intelligence-based data analysis device, a communication module, and a user terminal. Details of each component are described below.

[0544] The server acquires real-time data such as light intensity, temperature, and sound level from environmental sensors installed in commercial facilities and educational institutions. These environmental sensors are placed throughout stores and classrooms, and periodically transmit data to the server. This allows the server to always have access to the latest environmental information.

[0545] The server is equipped with artificial intelligence software such as TensorFlow and PyTorch, which is used to analyze the collected environmental data. The analyzed data is optimized into suggestions to improve user comfort, and these suggestions are then personalized by a generative AI model.

[0546] The generated suggestions are transmitted to the user's smartphone or smart glasses via a communication module. The suggestions are displayed on the user's device and provided as instructions, for example, regarding temperature control or lighting settings within a store. Users can review these instructions and choose to respond automatically or manually.

[0547] As a concrete example, in a shopping mall on a weekend, a server analyzes information obtained from temperature sensors and, if it determines that the temperature inside the store is not suitable, generates a suggestion for air conditioning control. This suggestion is notified to the user's terminal, and by maintaining an optimal environment, customer comfort is improved.

[0548] An example of a prompt message that can be input into the AI ​​model is, "Based on the current environmental data within the store, please generate suggestions for temperature adjustments to improve customer comfort." This makes it possible to ensure comfort efficiently and effectively.

[0549] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0550] Step 1:

[0551] The server aggregates environmental information such as light intensity, temperature, and sound volume acquired from various sensors. This information is measured in real time by the sensors and transmitted to the server. This allows the server to understand the current environmental conditions. The input is environmental data from the sensors, and the output is integrated environmental information.

[0552] Step 2:

[0553] The server analyzes aggregated environmental information using artificial intelligence software (e.g., TensorFlow, PyTorch). The analysis process uses past data patterns and current environmental conditions to derive optimal suggestions for maintaining comfort. The input is integrated environmental information, and the output is the suggested content. A generative AI model is used with prompts to create personalized suggestions.

[0554] Step 3:

[0555] The server sends the generated suggestions to the user's terminal via a communication module. In this process, the suggestions are compiled in a user-friendly format and notified to the user's smartphone or smart glasses. The input is the suggested content, and the output is the notification message displayed on the terminal.

[0556] Step 4:

[0557] The device notifies the user of the proposed action based on the received suggestion. The user can review this notification and choose to take action according to the suggestion. The input is the notification message, and the output is the suggestion displayed on the user's screen.

[0558] Step 5:

[0559] Based on the suggestions displayed on the terminal, the user can manually adjust the environment as needed, or instruct the terminal to automatically adjust it. This includes specific actions such as changing air conditioning or lighting settings. The input is the user's selection, and the output is the instruction for environmental adjustment.

[0560] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0561] This invention is an AI integrated system for maintaining visual health and providing a comfortable learning environment, characterized by recognizing the user's emotions using an emotion engine and making suggestions based on those emotions. The system comprises sensor means for collecting and analyzing environmental data in real time, artificial intelligence means for processing the data, communication means for communicating with the user, and control means for adjusting the environment.

[0562] System Design

[0563] The server collects data such as light intensity, temperature, and volume in real time from environmental sensor devices placed in classrooms and homes. It also uses an emotion engine to recognize emotions from the user's facial expressions and voice tone, and evaluates their psychological state.

[0564] As an artificial intelligence tool, the server analyzes collected environmental and emotional data to generate optimal instructions that take visual and mental health into consideration. This analysis includes combining historical data with current environmental conditions to propose a personalized learning environment.

[0565] Using communication methods, the server sends the generated suggestions and instructions to the user's terminal. This allows the terminal to provide the user with information in a meaningful way and facilitate immediate action.

[0566] The control system supports users in engaging with an optimal environment by automatically adjusting environmental factors such as lighting and sound based on instructions from the terminal. It also performs adjustments to reduce stress based on information obtained from the emotion engine.

[0567] Specific example

[0568] Specific examples in the classroom:

[0569] The server uses an emotion engine to detect if a student may be fatigued.

[0570] The server suggests adjusting the light intensity and break times to create a more relaxing environment, and sends instructions to the terminal.

[0571] The device notifies the teacher of the suggestion and automatically adjusts the classroom lighting to an appropriate brightness.

[0572] Specific examples in the home:

[0573] The server uses an emotion engine to recognize when a child is experiencing stress.

[0574] The server suggests lowering the music volume or playing relaxation music and sends instructions to the terminal.

[0575] The device controls the audio device according to the suggestion and prompts the parent to take appropriate action.

[0576] As described above, the system of the present invention can provide a physically and psychologically optimized learning environment through the analysis of environmental data and emotional data.

[0577] The following describes the processing flow.

[0578] Step 1:

[0579] The server collects environmental data in real time from sensor devices installed in classrooms and homes. In addition to light intensity, temperature, and sound volume, it also records users' facial expressions and voices using cameras and microphones, which are then used as data for analysis by an emotion engine.

[0580] Step 2:

[0581] The server uses an emotion engine to recognize the user's emotional state from acquired facial expression data and voice tone. This recognition result is used to evaluate whether the user is tired or stressed.

[0582] Step 3:

[0583] The server integrates environmental data and emotion recognition results and analyzes them using artificial intelligence. The goal of the analysis is to generate optimal instructions to maintain visual health and ensure the user's psychological well-being.

[0584] Step 4:

[0585] Based on the analysis results, the server generates personalized suggestions. Specifically, these suggestions include recommendations tailored to the user's situation, such as appropriate light intensity adjustments, timing of study breaks, and playback of relaxation music.

[0586] Step 5:

[0587] The server sends the generated suggestions to the user's terminal using a communication method. During this process, the suggestions are notified visually or audibly, and measures are taken to ensure the user can easily understand them.

[0588] Step 6:

[0589] The terminal displays suggestions received from the server through a user interface. It also automatically adjusts environmental settings based on these suggestions, such as changing the brightness of the lighting or controlling the sound system.

[0590] Step 7:

[0591] Users (teachers, parents, or children) can receive notifications on their devices and choose appropriate actions based on the suggestions. For example, they may realize that environmental adjustments contribute to stress reduction, leading to a more comfortable learning and living environment.

[0592] Step 8:

[0593] Users send feedback and information about the effectiveness of the suggestions they receive from their devices to the server. This allows for continuous improvement, contributing to better accuracy of future suggestions.

[0594] (Example 2)

[0595] Next, we will describe Example 2. 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."

[0596] In modern times, a lack of physical and psychological comfort in the learning environment can negatively impact learning efficiency and visual health. Furthermore, conventional systems struggle to adjust the environment while considering the user's emotional state, making it difficult to provide individually optimized suggestions. Therefore, there is a need for a system that comprehensively analyzes environmental and emotional information to provide the optimal environment for learners.

[0597] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0598] In this invention, the server includes a measuring device that collects multiple pieces of environmental information in real time, a computing device that analyzes the environmental information and emotional information and generates optimized instructions, and a communication device that generates the instructions as personalized suggestions and transmits them to the user device. This makes it possible to optimize the learning environment to reflect the user's emotional state in real time.

[0599] "Environmental information" is a general term for physical data related to the space used by the user, such as light intensity, temperature, and sound volume.

[0600] A "measuring device" is a device used to collect environmental information in real time, and includes measuring instruments such as sensors.

[0601] A "computational device" is a device that analyzes collected environmental and emotional information and generates optimized instructions, and includes computers.

[0602] "Communication equipment" refers to devices and technologies used to transmit instructions generated by a server to user devices, and includes network interfaces, etc.

[0603] An "emotion analysis device" is a device that analyzes a user's facial expressions and voice to identify their emotional state.

[0604] An "evaluation device" is a device that collects feedback from users and incorporates it into the analysis results.

[0605] "Instructions" refer to specific suggestions or requirements for environmental adjustments generated based on the analysis results.

[0606] A "control device" is a device that automatically adjusts the environment based on a proposal, and includes the operation of lighting and sound equipment.

[0607] This invention is a system designed to provide a learning environment optimized for the user. Specifically, it involves collaboration between the server, terminal, and user to create an environment where the user can learn efficiently and comfortably.

[0608] server

[0609] The server uses multiple measuring devices to collect environmental information. These consist of sensors that measure important physical indicators in the learning space, such as light intensity, temperature, and sound volume. The server collects this data in real time and analyzes the user's facial expressions and voice tone using an emotion analysis device. This allows the server to assess the user's psychological state, and the user's emotional state is reflected in the operation of the entire system.

[0610] terminal

[0611] Upon receiving instructions from the server, the terminal automatically adjusts the environment based on that information. The terminal receives optimized instructions from the server via a communication device and uses a control device to adjust the brightness of the lighting or the volume of the sound. For example, if the room is too dark, the terminal will adjust the lighting to raise the brightness to an appropriate level.

[0612] User

[0613] Users provide feedback using information and environmental adjustments provided from their devices. The evaluation device collects this feedback and uses it to optimize environmental conditions for future use. This allows the system to continuously provide users with a better environment.

[0614] Hardware and software to be used

[0615] This system uses light intensity sensors, temperature sensors, and volume sensors as measuring devices. The server also includes an emotion analysis device and software implemented to evaluate emotional states using machine learning models.

[0616] Specific example

[0617] For example, when used in a classroom, the system detects fatigue from students' facial expressions and, if it detects excessive brightness from the light sensor, sends a command to the terminal to adjust the lighting to a warmer tone. This allows the learning environment to adapt to the students' comfort.

[0618] Example of a prompt

[0619] "Generate a procedure that proposes the optimal visual and psychological environment settings for the user based on environmental sensor data and emotional data."

[0620] Based on this prompt, the generative AI model constructs personalized and optimal environment suggestions.

[0621] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0622] Step 1:

[0623] The server collects environmental information such as light intensity, temperature, and sound volume in real time through measuring devices. The input is data measured by each sensor, and the output is an aggregate of this data. The server stores this data in a database in preparation for the next analysis step.

[0624] Step 2:

[0625] The server uses an emotion analysis device to acquire user facial expression and voice data. This input data is analyzed using image processing and voice analysis techniques. As output, the user's emotional state is identified and their psychological condition is evaluated.

[0626] Step 3:

[0627] The server uses collected environmental and emotional information to generate optimal instructions tailored to the user through a generative AI model. The AI ​​model's input consists of environmental and emotional data. Data processing outputs personalized suggestions for each user. For example, it might create environmental adjustment suggestions that improve the user's learning efficiency based on past history and current circumstances.

[0628] Step 4:

[0629] The server sends the generated proposal to the terminal via a communication device. The input is the generated instruction, which is sent to the terminal via the communication protocol. The output is the notification of the proposal to the terminal.

[0630] Step 5:

[0631] The terminal receives instructions from the server and uses a control unit to perform the corresponding environmental adjustments. The input is the instructions from the server, and specific actions include setting the lighting to a specific brightness or adjusting the volume appropriately. The output is the state in which the user can operate in the optimized environment after the adjustments.

[0632] Step 6:

[0633] Users evaluate their experience based on the provided environment and provide feedback. Input consists of the user's perceived usability and efficiency, collected by the evaluation device. Output is sent to the server as feedback data and used for future analysis and proposal generation.

[0634] (Application Example 2)

[0635] Next, we will explain application example 2. In the following explanation, 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."

[0636] In current commercial facilities, it is difficult to maximize the customer experience because it is not possible to grasp customers' emotional states in real time and adaptively adjust the in-store environment based on that information. Furthermore, providing an environment that customers find comfortable requires processing large amounts of environmental and emotional data and responding flexibly accordingly.

[0637] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0638] In this invention, the server includes sensor means for collecting multiple environmental data in real time, artificial intelligence means for analyzing the environmental data and generating optimized instructions, and emotion recognition means for recognizing emotions and making suggestions for improving the environment based on that data. This makes it possible to adjust the environment appropriately to match the emotional state of the customer.

[0639] "Environmental data" refers to information about elements that affect a user's physical and psychological state, including light intensity, temperature, volume, and the user's facial expressions and voice.

[0640] "Sensing means" refers to a device or technology for collecting environmental data in real time.

[0641] "Artificial intelligence means" refers to a system or algorithm for analyzing collected environmental data and generating optimized instructions based on that data.

[0642] "Communication means" refers to technology or equipment for transmitting generated suggestions or instructions to a user terminal.

[0643] "Control means" refers to technology or devices for automatically adjusting the environment based on a proposal.

[0644] "Emotion recognition means" refers to a technology or system that recognizes a user's emotions from their facial expressions and voice, and makes improvement suggestions based on those emotions.

[0645] In order to implement the present invention, the following system configuration is necessary.

[0646] The server collects environmental data in real time from multiple sensors placed within the user environment, including light intensity, temperature, volume, facial expressions, and audio information. This includes sensor devices such as cameras and microphones, and utilizes software libraries such as OpenCV and librosa. The server analyzes this data and uses emotion recognition to evaluate the user's emotions and psychological state. The analyzed data is then processed by a generative AI model to generate suggestions for improving the environment.

[0647] The generated suggestions are sent to the user's terminal via a communication method. The user's terminal receives these suggestions and controls the store's IoT devices to make actual environmental adjustments. For example, it might adjust the store's lighting or music as needed to improve the customer experience. Additionally, prompt messages are generated in response to the user's actions, such as "Please suggest environmental adjustments to help customers relax," and these are used within the system.

[0648] As a concrete example, if a customer in a store feels stressed, a relaxing atmosphere can be created by playing soft music and dimming the lights. This entire process enhances customer satisfaction by providing an optimal environment.

[0649] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0650] Step 1:

[0651] The server uses sensor devices installed in the user's environment to collect environmental data such as light intensity, temperature, volume, facial expressions, and voice in real time. Input is data from various sensors, and output is an integrated environmental dataset. This data is used for subsequent emotion recognition and environmental adjustments.

[0652] Step 2:

[0653] The server uses software libraries such as OpenCV and librosa to analyze collected environmental data and recognize emotions from the user's facial expressions and voice. The input is an environmental dataset, and the output is an analysis result indicating the user's emotional state. This result is fed into a generative AI model, which serves as the basis for further data processing.

[0654] Step 3:

[0655] The server's AI model generates optimized environment improvement suggestions based on the analysis results. The input is the result of the emotion analysis, and the output is specific improvement suggestions. These suggestions include specific actions such as adjusting the lighting, selecting music, and adjusting the volume.

[0656] Step 4:

[0657] The server sends the generated improvement suggestions to the user terminal via a communication method. The input is the improvement suggestion, and the output is information as a notification on the user terminal. This prepares the user to review the suggestion and take the necessary actions.

[0658] Step 5:

[0659] The terminal controls IoT devices within the store based on the received suggestions to adjust the actual environment. The input is notification information from the server, and the output is the adjusted store environment. Specifically, actions such as changing the lighting and playing music are performed to provide a relaxing space for customers.

[0660] By following these steps, a comfortable environment tailored to the customer's emotional state is provided, resulting in a better customer experience.

[0661] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0662] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0663] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0664] [Fourth Embodiment]

[0665] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0666] As shown in Figure 7, the 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.

[0667] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0668] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0669] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0670] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0671] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0672] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0673] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0674] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0675] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0676] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0677] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0678] This invention is an AI-integrated system for optimizing educational and home environments while maintaining visual health. The system comprises sensor means, artificial intelligence means, communication means, and control means, and operates as follows.

[0679] System Design

[0680] The server collects real-time environmental data such as light levels, temperature, and noise levels in classrooms and homes through multiple environmental sensors. This allows for constant monitoring of the latest conditions.

[0681] The server, acting as an artificial intelligence tool, highly analyzes collected environmental data and generates optimal instructions for maintaining visual health. This AI model learns by considering past data and environmental parameters, allowing its suggestions to improve accuracy over time.

[0682] The server generates personalized suggestions based on the analysis results and sends them to each user's terminal. These suggestions may include, for example, adjusting classroom lighting settings, managing break times during study sessions, and optimizing seating arrangements.

[0683] The terminal receives communications from the server and displays suggestions to the user in an easy-to-understand format. The user can then take specific actions in response to these suggestions.

[0684] By using control mechanisms, the terminal automatically adjusts lighting and volume as needed. Furthermore, by receiving user feedback and sending it to the server, more effective suggestions can be made.

[0685] Specific example

[0686] Specific measures in the classroom:

[0687] If the server detects that there is insufficient lighting in the classroom, it generates an instruction to increase the lighting.

[0688] The device notifies the teacher and automatically adjusts the light intensity in conjunction with the lighting system.

[0689] The user (teacher) can review the presented suggestions and make manual adjustments if necessary.

[0690] Specific examples in the home:

[0691] If the server detects that the volume level is high while studying at home, it will generate a suggestion recommending a quieter environment.

[0692] The device will notify parents or children to lower the volume, or it will automatically adjust the volume of the audio device.

[0693] Users (parents) can readjust the environment based on the suggestions to improve the effectiveness of home learning.

[0694] Thus, the system of the present invention collects and analyzes environmental data in real time and provides appropriate suggestions, thereby realizing an optimal learning environment while protecting visual health.

[0695] The following describes the processing flow.

[0696] Step 1:

[0697] The server collects environmental data in real time from multiple sensor devices placed in classrooms and homes. This includes light intensity, temperature, humidity, and sound levels. The collected data is immediately stored in a database.

[0698] Step 2:

[0699] The server preprocesses the collected data. Specifically, it filters out noise from the sensor data and imputes missing values. This preprocessing enhances the accuracy and consistency of the data.

[0700] Step 3:

[0701] The server uses artificial intelligence to analyze pre-processed data. Here, it identifies factors affecting visual health and generates instructions for optimal environmental adjustments.

[0702] Step 4:

[0703] The server generates personalized suggestions based on the analysis results. These suggestions include recommendations for the most suitable lighting adjustments, break times, and seating arrangements for each individual user.

[0704] Step 5:

[0705] The server sends the generated suggestions to each user's terminal. Information is efficiently transmitted over the network via communication means.

[0706] Step 6:

[0707] The terminal displays suggestions received from the server on the user interface and notifies the user. If necessary, it may also use voice alerts or pop-up notifications.

[0708] Step 7:

[0709] The terminal, through its control mechanisms, performs automatic control of the environment based on suggestions. For example, it sends a signal to the lighting system to adjust the amount of light in a classroom or home.

[0710] Step 8:

[0711] Users (teachers, parents, or children) receive notifications on their devices and take action according to the suggestions to maintain visual health and optimize the learning environment.

[0712] Step 9:

[0713] Users send feedback from their devices to the server regarding the effectiveness of the proposals and changes in the environment. This information is stored in a database and used to refine future proposals.

[0714] (Example 1)

[0715] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0716] There is a need for systems that can provide an optimal learning environment in real time while maintaining visual health in educational and home settings. However, conventional systems have insufficient collection and analysis of environmental information, making it difficult to provide personalized recommendations for individual users. Furthermore, there is a need for a mechanism that effectively incorporates user feedback to improve the accuracy of recommendations.

[0717] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0718] In this invention, the server includes a measurement means, an intelligent processing means, and an information communication means. This makes it possible to provide user-optimized suggestions while maintaining visual health based on real-time information of the educational and home environments.

[0719] "Measurement means" refers to a device that collects environmental information in real time using various sensors.

[0720] "Intelligent processing means" refers to a device that uses an artificial intelligence model to analyze collected environmental information and propose optimal environmental conditions while maintaining visual health.

[0721] "Information and communication means" refers to communication protocols and devices used to transmit proposals generated by a server to a user's terminal.

[0722] "Display means" refers to devices or interfaces that visually present suggestions sent from the server to the user's terminal in an easily understandable way.

[0723] "Means of receiving feedback" refers to devices or interfaces that collect user behavior and opinions, reflect them in a database, and improve the accuracy of system suggestions.

[0724] This invention is an advanced AI-integrated system for maintaining visual health in educational and home environments. The system utilizes servers, terminals, and sensor devices as its primary hardware components.

[0725] The server plays a central role in analyzing environmental information, utilizing an artificial intelligence model (generative AI model) aimed at maintaining visual health. This AI model learns from past environmental data and user feedback to generate optimal suggestions based on environmental conditions.

[0726] The sensor system functions as a means of measuring environmental information and includes various sensors such as light sensors, temperature sensors, and microphones. These sensors are placed in classrooms and homes to collect real-time data on light intensity, temperature, and sound volume. The collected data is transmitted to a server for analysis.

[0727] The terminal is equipped with information communication and display means to show the user suggestions sent from the server. The suggestions are represented on the terminal screen using icons and graphs so that they can be understood intuitively. The user can modify their actions based on the presented suggestions, and the terminal can also automatically adjust lighting and volume.

[0728] As a concrete example, in a classroom, the server detects insufficient light levels based on data from light sensors and generates a suggestion to increase the lighting. The terminal notifies the teacher of this suggestion, and the lighting system automatically adjusts. At home, the server detects excessive volume and suggests lowering it, and the terminal reduces the volume via an audio device.

[0729] As an example of a prompt, the following question can be input to the generating AI model:

[0730] "If the classroom lighting is insufficient, suggest how to adjust it."

[0731] "What volume settings are best for improving the home study environment?"

[0732] The system of the present invention can support users in creating an optimal learning environment while maintaining their visual health through these means.

[0733] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0734] Step 1:

[0735] The server collects real-time environmental data such as light intensity, temperature, and sound volume from sensor devices placed in classrooms and homes. This data is used as input and recorded in a database. Specifically, it converts the analog signals acquired from the sensors into digital data and stores it as time-series data.

[0736] Step 2:

[0737] The server analyzes the collected environmental data using intelligent processing tools. In this step, based on the input environmental data, it performs analysis using a generative AI model to calculate the optimal environmental conditions for maintaining visual health. It performs data calculations by referring to past data and feedback information, and outputs a proposal.

[0738] Step 3:

[0739] The server generates specific suggestions tailored to each user's environment based on the analysis results. In this process, it uses the output of intelligent processing to generate personalized suggestions, which are then output to the terminal via information and communication means. Specifically, the generated suggestions are converted into formats such as text, icons, and graphs, and transmitted using a communication protocol.

[0740] Step 4:

[0741] The terminal receives suggestions sent from the server and displays them to the user. In this step, the suggestions are visually presented on the terminal's display based on the received data. The user interface outputs the input data in a format that is easy to analyze and displays it in a format that is easy for the user to understand.

[0742] Step 5:

[0743] The user takes specific actions to adjust the environment based on the suggestions presented by the device. These actions may include adjusting the lighting, ventilating the room, or lowering the volume. The system then provides feedback information based on the user's actions.

[0744] Step 6:

[0745] The device collects user feedback and sends it to the server. The feedback data is then analyzed again on the server and used as valuable data to improve the accuracy of new suggestions. In this step, the input feedback information is accurately recorded in the database and output as training data for the generating AI model.

[0746] (Application Example 1)

[0747] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0748] To enhance user comfort in stores, educational facilities, and homes, it is necessary to appropriately adjust the environment. However, current methods make it difficult to adjust the environment in real time, often resulting in an inability to respond immediately. Furthermore, there are limitations to manually making detailed environmental adjustments to meet the individual needs of each user. A system is needed that can accommodate individual users while maintaining overall comfort.

[0749] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0750] In this invention, the server includes detection means for collecting multiple pieces of environmental information in real time, intelligent processing means for analyzing the environmental information and generating optimized instructions, and transmission means for generating the instructions as personalized suggestions and transmitting them to the user device. This makes it possible to generate suggestions to improve user comfort and quickly notify the user device.

[0751] "Environmental information" refers to data about the user's surrounding environment, such as light intensity, temperature, and sound volume.

[0752] "Detection means" refers to devices or systems that collect environmental information in real time.

[0753] "Intelligent processing means" refers to algorithms and software that analyze collected environmental information and generate instructions optimized for the user.

[0754] "Means of transmission" refers to communication devices and protocols used to transmit generated instructions and suggestions to user devices.

[0755] A "user device" is a device used to receive suggestions and notifications and provide information to users.

[0756] "Comfort" is a concept that describes the degree of pleasantness and ease of living that users experience.

[0757] "Instructions" refer to specific guidance and information generated to adjust the environment or make suggestions to users.

[0758] The system that realizes this invention comprises various sensor devices, an artificial intelligence-based data analysis device, a communication module, and a user terminal. Details of each component are described below.

[0759] The server acquires real-time data such as light intensity, temperature, and sound level from environmental sensors installed in commercial facilities and educational institutions. These environmental sensors are placed throughout stores and classrooms, and periodically transmit data to the server. This allows the server to always have access to the latest environmental information.

[0760] The server is equipped with artificial intelligence software such as TensorFlow and PyTorch, which is used to analyze the collected environmental data. The analyzed data is optimized into suggestions to improve user comfort, and these suggestions are then personalized by a generative AI model.

[0761] The generated suggestions are transmitted to the user's smartphone or smart glasses via a communication module. The suggestions are displayed on the user's device and provided as instructions, for example, regarding temperature control or lighting settings within a store. Users can review these instructions and choose to respond automatically or manually.

[0762] As a concrete example, in a shopping mall on a weekend, a server analyzes information obtained from temperature sensors and, if it determines that the temperature inside the store is not suitable, generates a suggestion for air conditioning control. This suggestion is notified to the user's terminal, and by maintaining an optimal environment, customer comfort is improved.

[0763] An example of a prompt message that can be input into the AI ​​model is, "Based on the current environmental data within the store, please generate suggestions for temperature adjustments to improve customer comfort." This makes it possible to ensure comfort efficiently and effectively.

[0764] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0765] Step 1:

[0766] The server aggregates environmental information such as light intensity, temperature, and sound volume acquired from various sensors. This information is measured in real time by the sensors and transmitted to the server. This allows the server to understand the current environmental conditions. The input is environmental data from the sensors, and the output is integrated environmental information.

[0767] Step 2:

[0768] The server analyzes aggregated environmental information using artificial intelligence software (e.g., TensorFlow, PyTorch). The analysis process uses past data patterns and current environmental conditions to derive optimal suggestions for maintaining comfort. The input is integrated environmental information, and the output is the suggested content. A generative AI model is used with prompts to create personalized suggestions.

[0769] Step 3:

[0770] The server sends the generated suggestions to the user's terminal via a communication module. In this process, the suggestions are compiled in a user-friendly format and notified to the user's smartphone or smart glasses. The input is the suggested content, and the output is the notification message displayed on the terminal.

[0771] Step 4:

[0772] The device notifies the user of the proposed action based on the received suggestion. The user can review this notification and choose to take action according to the suggestion. The input is the notification message, and the output is the suggestion displayed on the user's screen.

[0773] Step 5:

[0774] Based on the suggestions displayed on the terminal, the user can manually adjust the environment as needed, or instruct the terminal to automatically adjust it. This includes specific actions such as changing air conditioning or lighting settings. The input is the user's selection, and the output is the instruction for environmental adjustment.

[0775] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0776] This invention is an AI integrated system for maintaining visual health and providing a comfortable learning environment, characterized by recognizing the user's emotions using an emotion engine and making suggestions based on those emotions. The system comprises sensor means for collecting and analyzing environmental data in real time, artificial intelligence means for processing the data, communication means for communicating with the user, and control means for adjusting the environment.

[0777] System Design

[0778] The server collects data such as light intensity, temperature, and volume in real time from environmental sensor devices placed in classrooms and homes. It also uses an emotion engine to recognize emotions from the user's facial expressions and voice tone, and evaluates their psychological state.

[0779] As an artificial intelligence tool, the server analyzes collected environmental and emotional data to generate optimal instructions that take visual and mental health into consideration. This analysis includes combining historical data with current environmental conditions to propose a personalized learning environment.

[0780] Using communication methods, the server sends the generated suggestions and instructions to the user's terminal. This allows the terminal to provide the user with information in a meaningful way and facilitate immediate action.

[0781] The control system supports users in engaging with an optimal environment by automatically adjusting environmental factors such as lighting and sound based on instructions from the terminal. It also performs adjustments to reduce stress based on information obtained from the emotion engine.

[0782] Specific example

[0783] Specific examples in the classroom:

[0784] The server uses an emotion engine to detect if a student may be fatigued.

[0785] The server suggests adjusting the light intensity and break times to create a more relaxing environment, and sends instructions to the terminal.

[0786] The device notifies the teacher of the suggestion and automatically adjusts the classroom lighting to an appropriate brightness.

[0787] Specific examples in the home:

[0788] The server uses an emotion engine to recognize when a child is experiencing stress.

[0789] The server suggests lowering the music volume or playing relaxation music and sends instructions to the terminal.

[0790] The device controls the audio device according to the suggestion and prompts the parent to take appropriate action.

[0791] As described above, the system of the present invention can provide a physically and psychologically optimized learning environment through the analysis of environmental data and emotional data.

[0792] The following describes the processing flow.

[0793] Step 1:

[0794] The server collects environmental data in real time from sensor devices installed in classrooms and homes. In addition to light intensity, temperature, and sound volume, it also records users' facial expressions and voices using cameras and microphones, which are then used as data for analysis by an emotion engine.

[0795] Step 2:

[0796] The server uses an emotion engine to recognize the user's emotional state from acquired facial expression data and voice tone. This recognition result is used to evaluate whether the user is tired or stressed.

[0797] Step 3:

[0798] The server integrates environmental data and emotion recognition results and analyzes them using artificial intelligence. The goal of the analysis is to generate optimal instructions to maintain visual health and ensure the user's psychological well-being.

[0799] Step 4:

[0800] Based on the analysis results, the server generates personalized suggestions. Specifically, these suggestions include recommendations tailored to the user's situation, such as appropriate light intensity adjustments, timing of study breaks, and playback of relaxation music.

[0801] Step 5:

[0802] The server sends the generated suggestions to the user's terminal using a communication method. During this process, the suggestions are notified visually or audibly, and measures are taken to ensure the user can easily understand them.

[0803] Step 6:

[0804] The terminal displays suggestions received from the server through a user interface. It also automatically adjusts environmental settings based on these suggestions, such as changing the brightness of the lighting or controlling the sound system.

[0805] Step 7:

[0806] Users (teachers, parents, or children) can receive notifications on their devices and choose appropriate actions based on the suggestions. For example, they may realize that environmental adjustments contribute to stress reduction, leading to a more comfortable learning and living environment.

[0807] Step 8:

[0808] Users send feedback and information about the effectiveness of the suggestions they receive from their devices to the server. This allows for continuous improvement, contributing to better accuracy of future suggestions.

[0809] (Example 2)

[0810] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0811] In modern times, a lack of physical and psychological comfort in the learning environment can negatively impact learning efficiency and visual health. Furthermore, conventional systems struggle to adjust the environment while considering the user's emotional state, making it difficult to provide individually optimized suggestions. Therefore, there is a need for a system that comprehensively analyzes environmental and emotional information to provide the optimal environment for learners.

[0812] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0813] In this invention, the server includes a measuring device that collects multiple pieces of environmental information in real time, a computing device that analyzes the environmental information and emotional information and generates optimized instructions, and a communication device that generates the instructions as personalized suggestions and transmits them to the user device. This makes it possible to optimize the learning environment to reflect the user's emotional state in real time.

[0814] "Environmental information" is a general term for physical data related to the space used by the user, such as light intensity, temperature, and sound volume.

[0815] A "measuring device" is a device used to collect environmental information in real time, and includes measuring instruments such as sensors.

[0816] A "computational device" is a device that analyzes collected environmental and emotional information and generates optimized instructions, and includes computers.

[0817] "Communication equipment" refers to devices and technologies used to transmit instructions generated by a server to user devices, and includes network interfaces, etc.

[0818] An "emotion analysis device" is a device that analyzes a user's facial expressions and voice to identify their emotional state.

[0819] An "evaluation device" is a device that collects feedback from users and incorporates it into the analysis results.

[0820] "Instructions" refer to specific suggestions or requirements for environmental adjustments generated based on the analysis results.

[0821] A "control device" is a device that automatically adjusts the environment based on a proposal, and includes the operation of lighting and sound equipment.

[0822] This invention is a system designed to provide a learning environment optimized for the user. Specifically, it involves collaboration between the server, terminal, and user to create an environment where the user can learn efficiently and comfortably.

[0823] server

[0824] The server uses multiple measuring devices to collect environmental information. These consist of sensors that measure important physical indicators in the learning space, such as light intensity, temperature, and sound volume. The server collects this data in real time and analyzes the user's facial expressions and voice tone using an emotion analysis device. This allows the server to assess the user's psychological state, and the user's emotional state is reflected in the operation of the entire system.

[0825] terminal

[0826] Upon receiving instructions from the server, the terminal automatically adjusts the environment based on that information. The terminal receives optimized instructions from the server via a communication device and uses a control device to adjust the brightness of the lighting or the volume of the sound. For example, if the room is too dark, the terminal will adjust the lighting to raise the brightness to an appropriate level.

[0827] User

[0828] Users provide feedback using information and environmental adjustments provided from their devices. The evaluation device collects this feedback and uses it to optimize environmental conditions for future use. This allows the system to continuously provide users with a better environment.

[0829] Hardware and software to be used

[0830] This system uses light intensity sensors, temperature sensors, and volume sensors as measuring devices. The server also includes an emotion analysis device and software implemented to evaluate emotional states using machine learning models.

[0831] Specific example

[0832] For example, when used in a classroom, the system detects fatigue from students' facial expressions and, if it detects excessive brightness from the light sensor, sends a command to the terminal to adjust the lighting to a warmer tone. This allows the learning environment to adapt to the students' comfort.

[0833] Example of a prompt

[0834] "Generate a procedure that proposes the optimal visual and psychological environment settings for the user based on environmental sensor data and emotional data."

[0835] Based on this prompt, the generative AI model constructs personalized and optimal environment suggestions.

[0836] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0837] Step 1:

[0838] The server collects environmental information such as light intensity, temperature, and sound volume in real time through measuring devices. The input is data measured by each sensor, and the output is an aggregate of this data. The server stores this data in a database in preparation for the next analysis step.

[0839] Step 2:

[0840] The server uses an emotion analysis device to acquire user facial expression and voice data. This input data is analyzed using image processing and voice analysis techniques. As output, the user's emotional state is identified and their psychological condition is evaluated.

[0841] Step 3:

[0842] The server uses collected environmental and emotional information to generate optimal instructions tailored to the user through a generative AI model. The AI ​​model's input consists of environmental and emotional data. Data processing outputs personalized suggestions for each user. For example, it might create environmental adjustment suggestions that improve the user's learning efficiency based on past history and current circumstances.

[0843] Step 4:

[0844] The server sends the generated proposal to the terminal via a communication device. The input is the generated instruction, which is sent to the terminal via the communication protocol. The output is the notification of the proposal to the terminal.

[0845] Step 5:

[0846] The terminal receives instructions from the server and uses a control unit to perform the corresponding environmental adjustments. The input is the instructions from the server, and specific actions include setting the lighting to a specific brightness or adjusting the volume appropriately. The output is the state in which the user can operate in the optimized environment after the adjustments.

[0847] Step 6:

[0848] Users evaluate their experience based on the provided environment and provide feedback. Input consists of the user's perceived usability and efficiency, collected by the evaluation device. Output is sent to the server as feedback data and used for future analysis and proposal generation.

[0849] (Application Example 2)

[0850] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0851] In current commercial facilities, it is difficult to maximize the customer experience because it is not possible to grasp customers' emotional states in real time and adaptively adjust the in-store environment based on that information. Furthermore, providing an environment that customers find comfortable requires processing large amounts of environmental and emotional data and responding flexibly accordingly.

[0852] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0853] In this invention, the server includes sensor means for collecting multiple environmental data in real time, artificial intelligence means for analyzing the environmental data and generating optimized instructions, and emotion recognition means for recognizing emotions and making suggestions for improving the environment based on that data. This makes it possible to adjust the environment appropriately to match the emotional state of the customer.

[0854] "Environmental data" refers to information about elements that affect a user's physical and psychological state, including light intensity, temperature, volume, and the user's facial expressions and voice.

[0855] "Sensing means" refers to a device or technology for collecting environmental data in real time.

[0856] "Artificial intelligence means" refers to a system or algorithm for analyzing collected environmental data and generating optimized instructions based on that data.

[0857] "Communication means" refers to technology or equipment for transmitting generated suggestions or instructions to a user terminal.

[0858] "Control means" refers to technology or devices for automatically adjusting the environment based on a proposal.

[0859] "Emotion recognition means" refers to a technology or system that recognizes a user's emotions from their facial expressions and voice, and makes improvement suggestions based on those emotions.

[0860] In order to implement the present invention, the following system configuration is necessary.

[0861] The server collects environmental data in real time from multiple sensors placed within the user environment, including light intensity, temperature, volume, facial expressions, and audio information. This includes sensor devices such as cameras and microphones, and utilizes software libraries such as OpenCV and librosa. The server analyzes this data and uses emotion recognition to evaluate the user's emotions and psychological state. The analyzed data is then processed by a generative AI model to generate suggestions for improving the environment.

[0862] The generated suggestions are sent to the user's terminal via a communication method. The user's terminal receives these suggestions and controls the store's IoT devices to make actual environmental adjustments. For example, it might adjust the store's lighting or music as needed to improve the customer experience. Additionally, prompt messages are generated in response to the user's actions, such as "Please suggest environmental adjustments to help customers relax," and these are used within the system.

[0863] As a concrete example, if a customer in a store feels stressed, a relaxing atmosphere can be created by playing soft music and dimming the lights. This entire process enhances customer satisfaction by providing an optimal environment.

[0864] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0865] Step 1:

[0866] The server uses sensor devices installed in the user's environment to collect environmental data such as light intensity, temperature, volume, facial expressions, and voice in real time. Input is data from various sensors, and output is an integrated environmental dataset. This data is used for subsequent emotion recognition and environmental adjustments.

[0867] Step 2:

[0868] The server uses software libraries such as OpenCV and librosa to analyze collected environmental data and recognize emotions from the user's facial expressions and voice. The input is an environmental dataset, and the output is an analysis result indicating the user's emotional state. This result is fed into a generative AI model, which serves as the basis for further data processing.

[0869] Step 3:

[0870] The server's AI model generates optimized environment improvement suggestions based on the analysis results. The input is the result of the emotion analysis, and the output is specific improvement suggestions. These suggestions include specific actions such as adjusting the lighting, selecting music, and adjusting the volume.

[0871] Step 4:

[0872] The server sends the generated improvement suggestions to the user terminal via a communication method. The input is the improvement suggestion, and the output is information as a notification on the user terminal. This prepares the user to review the suggestion and take the necessary actions.

[0873] Step 5:

[0874] The terminal controls IoT devices within the store based on the received suggestions to adjust the actual environment. The input is notification information from the server, and the output is the adjusted store environment. Specifically, actions such as changing the lighting and playing music are performed to provide a relaxing space for customers.

[0875] By following these steps, a comfortable environment tailored to the customer's emotional state is provided, resulting in a better customer experience.

[0876] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0877] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0878] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0879] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0880] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0881] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0882] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0883] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0884] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0885] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0886] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0887] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0888] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0889] 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.

[0890] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0891] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0892] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0893] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0894] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0895] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0896] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0897] The following is further disclosed regarding the embodiments described above.

[0898] (Claim 1)

[0899] A sensor means for collecting multiple environmental data in real time,

[0900] An artificial intelligence means that analyzes the aforementioned environmental data and generates optimized instructions,

[0901] A communication means for generating the aforementioned instructions as personalized suggestions and transmitting them to a user terminal,

[0902] A control means that automatically adjusts the environment based on the above proposal,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, wherein the sensor means collects environmental data including light intensity and temperature and sound volume.

[0906] (Claim 3)

[0907] The system according to claim 1, wherein the artificial intelligence means performs analysis for the purpose of maintaining visual health and proposes a learning method according to environmental conditions.

[0908] "Example 1"

[0909] (Claim 1)

[0910] A measurement method for collecting multiple environmental information in real time,

[0911] An intelligent processing means that analyzes the aforementioned environmental information and generates optimal instructions for maintaining visual health,

[0912] Information and communication means for generating personalized suggestions based on the aforementioned instructions and transmitting them to a terminal,

[0913] A display means for showing the aforementioned proposal to the user and assisting the user's actions,

[0914] A means of receiving user behavior and feedback to improve the accuracy of system suggestions,

[0915] A system that includes this.

[0916] (Claim 2)

[0917] The system according to claim 1, wherein the measuring means collects environmental information including brightness and temperature and sound pressure.

[0918] (Claim 3)

[0919] The system according to claim 1, wherein the intelligent processing means performs analysis for the purpose of maintaining visual health and proposes environmental adjustments that take into account past data and user feedback.

[0920] "Application Example 1"

[0921] (Claim 1)

[0922] A detection means for collecting multiple environmental pieces of information in real time,

[0923] An intelligent processing means that analyzes the aforementioned environmental information and generates optimized instructions,

[0924] A communication means for generating the aforementioned instructions as personalized suggestions and transmitting them to the user device,

[0925] A control means that automatically adjusts the environment based on the above proposal,

[0926] A means for generating suggestions to improve user comfort and notifying the user device,

[0927] A system that includes this.

[0928] (Claim 2)

[0929] The system according to claim 1, wherein the detection means collects environmental information including light intensity and temperature and sound volume.

[0930] (Claim 3)

[0931] The system according to claim 1, wherein the intelligent processing means performs analysis for the purpose of user comfort and proposes an adjustment method according to environmental conditions.

[0932] "Example 2 of combining an emotion engine"

[0933] (Claim 1)

[0934] A measuring device that collects multiple environmental data in real time,

[0935] A computing device that analyzes the aforementioned environmental information and emotional information and generates optimized instructions,

[0936] A communication device that generates the aforementioned instructions as personalized suggestions and transmits them to the user device,

[0937] A control device that automatically adjusts the environment based on the above proposal,

[0938] An emotion analysis device that recognizes emotions using the user's facial expressions and voice,

[0939] An evaluation device that collects user feedback and feeds it back into the analysis results,

[0940] A system that includes this.

[0941] (Claim 2)

[0942] The system according to claim 1, wherein the measuring device collects environmental information including light intensity, temperature, and sound volume.

[0943] (Claim 3)

[0944] The system according to claim 1, wherein the computing device performs analysis that takes into account emotional state while maintaining visual health, and proposes a learning method according to environmental conditions.

[0945] "Application example 2 when combining with an emotional engine"

[0946] (Claim 1)

[0947] A sensor means for collecting multiple environmental data in real time,

[0948] An artificial intelligence means that analyzes the aforementioned environmental data and generates optimized instructions,

[0949] A communication means for generating the aforementioned instructions as personalized suggestions and transmitting them to a user terminal,

[0950] A control means that automatically adjusts the environment based on the above proposal,

[0951] An emotion recognition tool that recognizes emotions and makes suggestions for environmental improvements based on that data,

[0952] A system that includes this.

[0953] (Claim 2)

[0954] The system according to claim 1, wherein the sensor means collects environmental data including light intensity, temperature, volume, and the user's facial expressions and voice.

[0955] (Claim 3)

[0956] The system according to claim 1, wherein the artificial intelligence means uses emotional data to make suggestions according to environmental conditions for the purpose of improving the customer experience. [Explanation of symbols]

[0957] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A sensor means for collecting multiple environmental data in real time, An artificial intelligence means that analyzes the aforementioned environmental data and generates optimized instructions, A communication means for generating the aforementioned instructions as personalized suggestions and transmitting them to a user terminal, A control means that automatically adjusts the environment based on the above proposal, A system that includes this.

2. The system according to claim 1, wherein the sensor means collects environmental data including light intensity and temperature and sound volume.

3. The system according to claim 1, wherein the artificial intelligence means performs analysis for the purpose of maintaining visual health and proposes a learning method according to environmental conditions.

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