System

Abstract

A system is provided.SOLUTION: A system, comprising: means for collecting vital signs of a user; means for analyzing the collected vital signs data; means for adjusting an indoor environment based on an analysis result; and means for sending a cheering message to motivate the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, many people are expected to perform at high levels in their work and studies, but they often experience stress and fatigue. Furthermore, many people are troubled by the lack of results despite their efforts, and many want to reduce wasted effort. Furthermore, while it is known that providing an optimal indoor environment and maintaining and improving motivation have a significant impact on performance, there is a lack of automated methods for doing so. [Means for solving the problem]

[0005] The present invention provides the following means to solve the above-mentioned problems. A system is provided that includes a means for collecting a user's vital signs, a means for analyzing the collected vital sign data, a means for adjusting the indoor environment based on the analysis results, and a means for sending a cheering message to motivate the user. This allows for real-time monitoring of the user's vital signs and maintaining an optimal environment. The system also includes a means for suggesting optimal rest times and hydration when the user's vital signs meet certain conditions, and a means for evaluating the correlation between vital sign data and performance and suggesting optimal work environments and tasks. This allows for providing "ways of working hard" tailored to each individual user and maintaining high performance. By using audio glasses or a smartwatch to collect vital signs, vital sign data can be easily acquired, improving the operating accuracy of the entire system.

[0006] "Vital signs" refer to physiological indicators such as body temperature, heart rate, and blood pressure, and are important data that indicate an individual's health condition and stress level.

[0007] "Means for collecting" refers to a method or apparatus for acquiring a user's vital signs using a wearable device such as audio glasses or a smartwatch.

[0008] "Means for analysis" refers to algorithms or software that analyze collected vital sign data and evaluate the user's physical condition and environmental settings.

[0009] "Adjusting means" refers to a method or device for automatically changing the indoor environment, such as temperature, humidity, or illuminance, based on the analysis results.

[0010] "Support messages" refer to encouraging words or messages displayed to increase the user's motivation, and are used in "Go for it mode."

[0011] "Rest time" refers to time during which a user temporarily steps away from work to recover from fatigue.

[0012] "Hydration" refers to the act of a user consuming a beverage to maintain fluid balance in the body.

[0013] "Performance" refers to the degree of efficiency and success in the work or tasks performed by a user.

[0014] "Work environment" refers to the physical and psychological environment that affects the user's work, including factors such as temperature, humidity, and light intensity. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The present invention is a system that collects and analyzes a user's vital signs and works with smart home appliances to provide an optimal indoor environment. Furthermore, a "Go for it" mode can send encouraging messages to the user, increasing their motivation. An example of how to specifically implement the present invention is shown below.

[0037] System Configuration

[0038] The system consists of the following main components:

[0039] 1. Vital Signs Collection Device

[0040] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[0041] 2. Data Collection and Transfer

[0042] The device sends the collected vital sign data to a server, where it is encrypted and transmitted over the internet.

[0043] 3. Data analysis server

[0044] The server analyzes the received vital sign data and calculates the optimal settings for the user's physical condition and indoor environment. The server can analyze the data using machine learning algorithms and perform statistical analysis.

[0045] 4. Smart appliances

[0046] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0047] 5. Support message function

[0048] The server periodically sends encouraging messages to users using the "Ganbare Mode" function, which is introduced to motivate users and keep them focused.

[0049] Program processing

[0050] 1. Data Collection

[0051] The terminal acquires vital sign data such as the user's body temperature, heart rate, blood pressure, etc. from the wearable device. For example, suppose the user's current body temperature is 36.8 degrees, heart rate is 72 BPM, and blood pressure is 120 / 80 mmHg.

[0052] 2. Data Transmission

[0053] The device transmits the collected data in real time to a server, where it is securely stored.

[0054] 3. Data analysis

[0055] The server analyzes the received vital sign data and evaluates the user's physical condition. For example, if the body temperature exceeds 37.2 degrees, it determines that the user's physical condition is unstable and sets the room temperature to be lowered by 2 degrees.

[0056] 4. Determine your environment settings

[0057] The server then determines the optimal indoor environmental settings based on the analysis results, for example, setting the temperature between 24 and 22 degrees Celsius, maintaining humidity at 50%, and setting the illumination to 500 lux.

[0058] 5. Controlling smart appliances

[0059] The device adjusts the air conditioner, humidifier, and lighting based on the environmental setting data received from the server, allowing the user to work in a comfortable environment.

[0060] 6. Send a message of support

[0061] The server periodically sends encouraging messages to the user through the "Ganbare Mode." For example, the message "Ganbare!" is displayed every 5 seconds to motivate the user.

[0062] Specific examples

[0063] The user puts on the wearable device and begins collecting vital signs. The device sends the data to a server, which then dynamically analyzes it. For example, if the user's body temperature rises, the server will issue a command to lower the air conditioner temperature. At the same time, the server will activate the "Go for it" mode and display a message of encouragement saying "Go for it!" This allows the user to continue working in an optimal environment while maintaining high motivation.

[0064] The above is an embodiment of the present invention. This system allows users to effectively concentrate on their work while maintaining their health, thereby maximizing performance.

[0065] The processing flow will be explained below.

[0066] Step 1:

[0067] The device collects vital sign data, such as body temperature, heart rate, and blood pressure, in real time through wearable devices worn by the user, such as audio glasses or a smartwatch.

[0068] Step 2:

[0069] The device encrypts the collected vital signs data and sends it to a server over the internet, using encryption protocols to ensure secure data transfer.

[0070] Step 3:

[0071] The server analyzes the received vital sign data using machine learning algorithms and statistical analysis tools to assess the user's physical condition.

[0072] Step 4:

[0073] The server then calculates the optimal indoor environment settings based on the analysis results. For example, if the user's body temperature is above 37.2 degrees, the room temperature will be lowered from 24 degrees to 22 degrees.

[0074] Step 5:

[0075] The server then transmits the determined environmental settings to the device, including parameters such as temperature, humidity, and illuminance.

[0076] Step 6:

[0077] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental settings received from the server, setting the room temperature to 22 degrees, humidity to 50%, and illuminance to 500 lux.

[0078] Step 7:

[0079] The server activates the "Ganbare mode" and periodically sends a cheering message to the user. For example, the server sends the message "Ganbare!" to the terminal every 5 seconds.

[0080] Step 8:

[0081] The device displays the support message received from the server to the user, which increases the user's motivation and improves work efficiency.

[0082] Step 9:

[0083] The terminal repeats the processes from step 1 to step 8 at regular time intervals, for example, every 30 seconds.

[0084] Step 10:

[0085] Users continue working while receiving regular, optimized environments and encouraging messages, helping them maintain their health and perform at their best.

[0086] Example 1

[0087] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0088] In today's busy living environment, it is difficult for users to maintain a comfortable indoor environment while properly managing their own health. Furthermore, there are few ways to motivate users, making it difficult to improve work efficiency and quality of life. In particular, there is a lack of systems that can quickly adjust the environment in response to changes in health status and provide accurate advice based on the user's physical condition.

[0089] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0090] In this invention, the server includes means for collecting physical information of the user, means for analyzing the collected physical information, means for adjusting the indoor environment based on the analysis results, and means for sending encouraging messages to motivate the user. This makes it possible to monitor the user's health condition in real time, create an optimal indoor environment, and increase the user's motivation.

[0091] "User" means an individual using the System.

[0092] "Physical information" refers to biometric data including vital sign data such as the user's body temperature, heart rate, and blood pressure.

[0093] "Means of collection" refers to the function of obtaining the user's physical information in real time using wearable devices and sensors.

[0094] "Means for analyzing" refers to a processing device or software for analyzing the collected physical information and assessing the user's health status and changes therein.

[0095] "Adjusting means" refers to equipment or devices that automatically change indoor environmental parameters such as temperature, humidity, and illuminance based on the analysis results.

[0096] The "means for sending a cheering message to motivate" refers to a function for displaying or notifying a cheering message by voice to increase the motivation of the user.

[0097] "Certain conditions" refers to a state in which the user's physical information satisfies a predetermined standard or range.

[0098] "Means for suggesting break times and hydration" refers to a function for recommending appropriate breaks and hydration based on the user's physical condition.

[0099] "Real-time monitoring" refers to continuously acquiring the user's physical information and immediately reflecting it.

[0100] "Means for automatic adjustment" refers to a system for changing the indoor environment in response to the user's physical information without manual intervention.

[0101] The present invention is a system that collects and analyzes a user's physical information and works in conjunction with smart home appliances to provide an optimal indoor environment. Furthermore, a "Go for it" mode can be used to send encouraging messages to the user, increasing their motivation. An example of a specific implementation of the present invention is shown below.

[0102] System Configuration

[0103] The system consists of the following main components:

[0104] 1. Physical information collection devices

[0105] The device collects the user's physical information using wearable devices such as audio glasses and smartwatches, which collect data such as body temperature, heart rate, and blood pressure in real time.

[0106] 2. Data Collection and Transfer

[0107] The device sends the collected physiological data to a server, where it is encrypted and transmitted over the internet.

[0108] 3. Data analysis server

[0109] The server analyzes the received physiological data and calculates the optimal settings for the user's physical condition and indoor environment. The server can analyze the data using machine learning algorithms and perform statistical analysis, specifically using software such as Python's Scikit-learn and TensorFlow.

[0110] 4. Smart appliances

[0111] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0112] 5. Support message function

[0113] The server periodically sends encouraging messages to users using the "Ganbare Mode" feature, which is introduced to motivate users and keep them focused.

[0114] Specific examples

[0115] The user puts on the wearable device and begins collecting physical information. The device sends the data to a server, which then dynamically analyzes it. For example, if the user's body temperature rises, the server will issue a command to lower the air conditioner temperature. At the same time, the server will activate a "go for it" mode and display a message of encouragement saying, "Take it easy today, relax." This allows the user to continue working in an optimal environment while maintaining high motivation.

[0116] Prompt Sentence Examples

[0117] Examples of prompts to be input to a generative AI model include:

[0118] "Please suggest optimal temperature and humidity settings for the room based on body temperature and heart rate data collected from the user's smartwatch."

[0119] "Please explain what indoor environmental settings should be made when the user's physical condition is unstable, including specific temperature, humidity, and illuminance."

[0120] "Please provide five specific motivational and encouraging messages for users who are feeling unwell."

[0121] The above is an embodiment of the present invention. This system allows users to effectively concentrate on their work while maintaining their health, thereby maximizing performance.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Step 1:

[0124] Data collection

[0125] The terminal acquires the user's physical information (body temperature, heart rate, blood pressure, etc.) in real time from wearable devices such as audio glasses or smartwatches. Sensors in the devices measure body temperature and heart rate and transmit the data to the terminal. The input is the user's current biometric data, and the output is the collected vital sign data.

[0126] Step 2:

[0127] Data transmission

[0128] The device sends the collected physiological data to a server via the Internet. The data is encrypted and securely transferred. The input is the collected vital sign data, and the output is the received vital sign data, which is stored on the server.

[0129] Step 3:

[0130] Data storage

[0131] The server stores the received physiological data in a database, for example, an SQL database or a NoSQL database. The input is the received vital sign data, and the output is the data stored in an organized manner in the database. The stored data is organized by date and time, making it easy to search.

[0132] Step 4:

[0133] Data analysis

[0134] The server analyzes the stored vital sign data and uses machine learning algorithms to evaluate the user's physical condition. For example, it uses Python's Scikit-learn or TensorFlow to analyze data from the past week. The input is the vital sign data stored in the database, and the output is the analysis results regarding the user's health condition.

[0135] Step 5:

[0136] Determining your environment settings

[0137] The server determines the optimal indoor environment settings based on the analysis results. For example, if the body temperature exceeds 37.2 degrees, the room temperature will be lowered by 2 degrees. The input is the health status analysis result, and the output is the specific indoor environment setting parameters (temperature, humidity, illuminance, etc.).

[0138] Step 6:

[0139] Smart home appliance control

[0140] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental setting data received from the server. For example, the device changes the temperature setting of an air conditioner from 24 degrees to 22 degrees and sets the humidity to 50%. The input is the environmental setting data from the server, and the output is the adjusted indoor environment.

[0141] Step 7:

[0142] Send a message of support

[0143] The server periodically sends encouraging messages to the user through the "Ganbare Mode." For example, the message "Take it easy today, relax!" is displayed every hour. The input is data about the user's health status and a template message to improve motivation, and the output is the display or audio notification of the encouraging message to the user.

[0144] The above are the specific processing steps of the program of this system.

[0145] (Application example 1)

[0146] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0147] Currently, it is difficult to provide an optimal environment based on the health status of staff and customers in stores. It is also difficult to maintain staff motivation, especially during busy times. This leads to poor staff efficiency and lower customer satisfaction. Additionally, there is a lack of systems that can analyze vital sign data in real time and automatically adjust the store environment based on that data.

[0148] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0149] In this invention, the server includes means for collecting users' vital signs, means for analyzing the collected vital sign data, means for adjusting the indoor environment based on the analysis results, means for sending cheering messages to motivate users, means for collecting vital signs of store staff and customers and providing an optimal store environment, means for automatically controlling smart equipment using the vital sign data, and means for sending cheering messages to staff and customers in real time. This makes it possible to optimize the in-store environment, maintain the health and motivation of staff, and improve customer satisfaction.

[0150] "Vital signs" refers to basic biological information such as body temperature, heart rate, and blood pressure.

[0151] "Collection methods" refers to devices and systems used to obtain vital signs of users, staff, or customers.

[0152] "Analysis means" refers to a server or software that analyzes collected vital sign data and evaluates the user's physical condition and environmental settings.

[0153] "Environmental adjustment means" refers to smart home appliances and control systems that automatically change indoor temperature, humidity, lighting, etc. based on analysis results.

[0154] "Encouragement message means" refers to a function or system that sends encouraging messages to increase the user's motivation.

[0155] "Store environment provision means" refers to systems and equipment for creating an optimal store environment based on the vital signs of store staff and customers.

[0156] "Smart equipment control means" refers to a system that automatically controls smart equipment such as air conditioners, humidifiers, and lighting based on vital sign data.

[0157] "Real-time transmission means" refers to a communication system for instantly sending support messages and notifications to customers and staff.

[0158] This invention is a system for collecting and analyzing vital signs of users, store staff, and customers to provide an optimal indoor environment. This system consists of a device for collecting vital signs, a server for transmitting and analyzing the data, smart equipment for adjusting the indoor environment, and a means for sending encouraging messages to users and staff. Below is a detailed explanation of how this system works.

[0159] The system consists of the following:

[0160] 1. Vital Signs Collection Device

[0161] Collect vital signs such as body temperature, heart rate, and blood pressure of users, staff, or customers using wearable devices such as smartwatches and audio glasses. The devices collect vital sign data in real time.

[0162] 2. Data Collection and Transfer

[0163] The collected vital sign data is sent to a server via smartphone, where it is encrypted and securely transmitted over the internet.

[0164] 3. Data analysis server

[0165] The server analyzes the received vital signs data and assesses the status of the user, staff, or customer. Machine learning algorithms (e.g., scikit-learn) are used to perform statistical analysis of the data.

[0166] 4. Decide on indoor environmental adjustments

[0167] Based on the server's analysis results, the optimal indoor environment settings are determined. Specifically, the air conditioner temperature is adjusted, the humidifier is activated, and the lighting is adjusted. This automatically optimizes temperature, humidity, and lighting intensity.

[0168] 5. Controlling smart equipment

[0169] The server then sends the determined environmental setting data to the smart equipment, adjusting the air conditioner, humidifier, lighting, etc., thereby optimizing the in-store environment in real time.

[0170] 6. Support message function

[0171] The server sends encouraging messages to users and staff using the "Ganbare Mode" function. This function is used to increase motivation and reduce stress for users and staff. The messages are displayed on smartwatches or smart glasses.

[0172] Specific examples

[0173] For example, consider a situation where there are a lot of customers during lunchtime and store staff are tired.

[0174] Hardware: Smartwatches, air conditioners, lighting, humidifiers

[0175] Software: Python, scikit-learn, IoT device control library

[0176] At this time, the smartwatch collects the staff member's body temperature (e.g., 37.5°C), heart rate (e.g., 80 BPM), and blood pressure (e.g., 130 / 85 mmHg), and sends this data to a server using a Python script. The server then analyzes the data using a machine learning algorithm using scikit-learn and determines that the staff member's physical condition is stressed. Based on the analysis results, an instruction is issued to change the air conditioner temperature from 24°C to 22°C, and at the same time, a cheering message saying "Do your best!" is displayed on the smartwatch every five seconds.

[0177] Prompt Sentence Examples

[0178] "For users whose body temperature exceeds 37.2 degrees, please lower the air conditioner temperature by 2 degrees. Also, please display a message of encouragement every 5 seconds."

[0179] This optimizes the store environment, allowing staff to continue working in a comfortable environment and improving customer satisfaction.

[0180] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0181] Step 1:

[0182] The user wears a vital sign collection device such as a smartwatch or audio glasses. This device acquires the user's vital signs, such as body temperature, heart rate, and blood pressure, in real time. The inputs are the user's body temperature (e.g., 36.8°C), heart rate (e.g., 72 BPM), and blood pressure (e.g., 120 / 80 mmHg), and these data are stored in the device as outputs.

[0183] Step 2:

[0184] The terminal sends the collected vital sign data to a server via the internet via the smartphone. The data is encrypted and transferred securely. The input is the vital sign data acquired from the smart device, and the output is the encrypted vital sign data sent to the server. Specifically, the smartphone receives data from the device using Bluetooth and sends the data to the server using the HTTPS protocol.

[0185] Step 3:

[0186] The server analyzes the received vital sign data and evaluates the user's physical condition. A Python machine learning library (e.g., scikit-learn) is used for the analysis, and statistical analysis of the data is performed. The input is the vital sign data sent to the server, and the output is the user's physical condition evaluation result. Specifically, the server runs an algorithm based on the temperature, heart rate, and blood pressure data to determine whether there are any abnormal values.

[0187] Step 4:

[0188] The server determines the optimal indoor environmental settings based on the analysis results. For example, if the body temperature exceeds 37.2 degrees, it will instruct the air conditioner to lower the temperature by 2 degrees. The input is the physical condition evaluation result, and the output is the environmental setting parameters (e.g., the air conditioner's set temperature). Specific operations involve determining the environmental adjustment parameters based on if statements and threshold setting rules.

[0189] Step 5:

[0190] The terminal controls smart equipment (e.g., air conditioners, humidifiers, and lighting) based on the environmental setting data received from the server. This automatically optimizes the temperature, humidity, and illuminance. The input is the environmental setting parameters from the server, and the output is the new settings for the air conditioner, humidifier, and lighting. Specifically, the terminal uses the IoT device control library to send commands to control each piece of equipment.

[0191] Step 6:

[0192] The server periodically sends cheering messages to users and staff using the "Go for it mode." For example, the message "Go for it!" is displayed every five seconds. The input is the cheering message data on the server, and the output is the message displayed on the smartwatch or smart glasses. Specifically, the server executes the message sending protocol using a periodic timer.

[0193] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0194] This invention is a system that collects and analyzes the user's vital signs in real time, and combines this with an emotion engine that recognizes the user's emotions to provide an optimal indoor environment. It can also send encouraging messages to the user through a "Go for it" mode to increase their motivation. An example of how this system can be implemented is shown below.

[0195] System Configuration

[0196] The system consists of the following main components:

[0197] 1. Vital Signs Collection Device

[0198] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[0199] 2. Emotion Recognition Engine

[0200] The device collects emotional data from the user through voice input and facial expression analysis. Voice input is analyzed through a microphone to capture the user's tone of voice and emotional state, while facial expression analysis is performed using a camera.

[0201] 3. Data Collection and Transfer

[0202] The device encrypts the collected vital sign and emotion data and transmits it to a server via the internet, using encryption protocols to ensure data transmission is secure.

[0203] 4. Data Analysis Server

[0204] The server analyzes the received vital sign data and emotion data to evaluate the user's physical and emotional state. The server can analyze the data using machine learning algorithms and perform statistical analysis.

[0205] 5. Smart appliances

[0206] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0207] 6. Support message function

[0208] The server uses the "Ganbare Mode" to send users cheering messages that change dynamically based on their emotional data. This feature was introduced to motivate users and help them maintain their concentration.

[0209] Program processing

[0210] 1. Data Collection

[0211] The terminal acquires vital sign data such as the user's body temperature, heart rate, and blood pressure from the wearable device. At the same time, it uses a microphone and camera to collect the user's emotional data. For example, if the user's body temperature is 36.8 degrees, the emotional state is recognized as "relaxed."

[0212] 2. Data Transmission

[0213] The device transmits the collected vital sign data and emotion data in real time to a server, where the data is securely stored.

[0214] 3. Data analysis

[0215] The server analyzes the received vital sign data and emotional data to evaluate the user's physical and emotional state. For example, if the body temperature is over 37.2 degrees and the emotional state is recognized as "stressed," the server adjusts the environmental settings to be more lenient.

[0216] 4. Determine your environment settings

[0217] The server then determines the optimal indoor environmental settings based on the analysis results, for example, setting the temperature between 24 and 22 degrees Celsius, maintaining humidity at 50%, and setting the illumination to 500 lux.

[0218] 5. Controlling smart appliances

[0219] The device adjusts the air conditioner, humidifier, and lighting based on the environmental setting data received from the server, allowing the user to work in a comfortable environment.

[0220] 6. Send a message of support

[0221] The server periodically sends encouraging messages based on the user's emotional data through the "Ganbare Mode." For example, the message "Ganbare!" is displayed every five seconds, or the message "Relax!" is displayed to motivate the user.

[0222] Specific examples

[0223] The user uses a system that combines a wearable device with an emotion recognition engine. The device collects vital signs and emotion data and sends this data to a server. If the server determines that the user's body temperature is 37.2 degrees and that the user is feeling stressed, it will operate the air conditioner to set the room temperature to 22 degrees, use a humidifier to keep the humidity at 50%, and adjust the lighting to 500 lux. At the same time, it sends a supportive message saying, "Relax!" This allows the user to continue working in a comfortable environment, maintaining their health and concentration.

[0224] The above is an embodiment of the present invention, which allows users to optimize their health and emotional state and perform at their best.

[0225] The processing flow will be explained below.

[0226] Step 1:

[0227] The device collects vital sign data, such as body temperature, heart rate, and blood pressure, in real time through wearable devices worn by the user, such as audio glasses or a smartwatch.

[0228] Step 2:

[0229] The device collects the user's voice input and facial expressions using a camera and microphone, and then uses an emotion recognition engine to analyze the user's emotional data, recognizing, for example, emotions such as joy, anger, sadness, and happiness.

[0230] Step 3:

[0231] The device encrypts the collected vital sign data and emotional data and transmits it to a server in real time via the Internet.

[0232] Step 4:

[0233] The server analyzes the received vital sign and emotion data using machine learning algorithms and statistical analysis tools to assess the user's physical and emotional state.

[0234] Step 5:

[0235] The server calculates the optimal room environment settings based on the analysis results. For example, if the user's body temperature exceeds 37.2 degrees Celsius or their emotional state is recognized as "stressed," the server will adjust the room temperature from 24 degrees Celsius to 22 degrees Celsius.

[0236] Step 6:

[0237] The server then transmits the determined environmental settings to the device, including parameters such as temperature, humidity, and illuminance.

[0238] Step 7:

[0239] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental settings received from the server, setting the room temperature to 22 degrees, humidity to 50%, and illuminance to 500 lux.

[0240] Step 8:

[0241] The server activates the "Go for it" mode and dynamically generates a supportive message based on the user's vital sign data and emotional data, and sends it to the device. For example, if the user is feeling stressed, the server sends a message saying, "Relax!"

[0242] Step 9:

[0243] The device displays the cheering message received from the server to the user, allowing the user to receive a motivational message at an appropriate time.

[0244] Step 10:

[0245] The terminal repeats the processes from step 1 to step 9 at regular time intervals, for example, every 30 seconds.

[0246] Step 11:

[0247] Users continue working while receiving regular, optimized environments and encouraging messages, which help them optimize their health and emotional state and perform at their best.

[0248] Example 2

[0249] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0250] In modern society, users are constantly exposed to stress, which can lead to deterioration in their health. It is difficult for users to manually adjust their indoor environment to create an optimal one. Furthermore, it is necessary to adjust the environment to respond to emotional changes and improve motivation. However, existing systems lack the ability to analyze a user's vital signs and emotional state in real time, adjust the indoor environment accordingly, or generate and send personalized support messages.

[0251] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0252] In this invention, the server includes means for collecting the user's vital signs, means for analyzing the collected vital sign data and emotional data, means for adjusting the indoor environment based on the analysis results, and means for sending a cheering message using a generative AI model based on the user's emotional state. This allows the user to optimize both their health and emotional state in real time, enabling them to perform at a high level in a comfortable environment.

[0253] "User" refers to an individual who uses this system.

[0254] "Vital signs" refers to basic vital indicators of the human body, such as body temperature, heart rate, and blood pressure.

[0255] "Data" refers to vital signs and emotional information collected from sensors and devices.

[0256] "Emotional data" refers to information about the user's emotional state obtained from voice input and facial expression analysis.

[0257] "Collection means" refers to the devices and methods for acquiring vital signs and emotional data using wearable devices and sensors.

[0258] "Analysis means" refers to algorithms or software that analyze the collected data and assess the user's physical and emotional state.

[0259] "Adjustment means" refers to a device or method that automatically adjusts the indoor temperature, humidity, illuminance, etc. based on the analysis results.

[0260] "Generative AI model" refers to an artificial intelligence model that dynamically generates cheering messages based on the user's emotional state.

[0261] "Support messages" refer to text that encourages or motivates users to increase their motivation.

[0262] MODE FOR CARRYING OUT THE INVENTION

[0263] This invention is a system that collects and analyzes a user's vital signs in real time, and integrates a means of recognizing the user's emotions to provide an optimal indoor environment. Furthermore, through the "Go for it" mode, a generative AI model can be used to send encouraging messages based on the user's emotional state, increasing the user's motivation. An example of how this system can be implemented is shown below.

[0264] System Configuration

[0265] The system consists of the following main components:

[0266] 1. Vital Signs Collection Device

[0267] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[0268] 2. Emotion Recognition Engine

[0269] The device collects emotional data from the user through voice input and facial expression analysis. Voice input is analyzed through a microphone to capture the user's tone of voice and emotional state, while facial expression analysis is performed using a camera.

[0270] 3. Data Collection and Transfer

[0271] The device encrypts the collected vital sign and emotion data and sends it to a server via the Internet, using the TLS / SSL protocol to ensure secure data transfer.

[0272] 4. Data Analysis Server

[0273] The server analyzes the received vital sign data and emotion data to evaluate the user's physical and emotional state. The server can analyze the data using machine learning algorithms (e.g., TensorFlow and scikit-learn) and perform statistical analysis.

[0274] 5. Smart appliances

[0275] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0276] 6. Support message function

[0277] The server uses "Go for it" mode to send dynamically changing cheering messages to users based on their emotional data. Prompts for the generative AI model (e.g., GPT-3) include, "The user's body temperature is 37.2 degrees and their emotional state is stressed. Please tell me what kind of cheering message would be appropriate in this case."

[0278] Specific examples

[0279] The user wears audio glasses and a smartwatch. The device captures the user's body temperature and heart rate in real time, and also collects emotional data (e.g., "stress" state) via a microphone and camera. This data is encrypted and sent to a server.

[0280] The server analyzes this data and evaluates the user's health condition. For example, if the server determines that the user's body temperature is 37.2 degrees, indicating stress, it will operate the air conditioner to set the room temperature to 22 degrees, use a humidifier to keep the humidity at 50%, and adjust the lighting to 500 lux. At the same time, it will use a generative AI model to generate a supportive message such as "Relax!" and send it to the device.

[0281] Based on this, the device will set the air conditioner to 22 degrees, adjust the humidifier to 50% humidity, and display a message to the user saying "Relax!", allowing the user to continue working in a comfortable environment, maintaining their health and concentration.

[0282] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0283] Step 1:

[0284] Data collection

[0285] The device acquires vital sign data such as the user's body temperature, heart rate, and blood pressure using sensors in wearable devices (audio glasses or smartwatches). For example, the device reads the body temperature and heart rate from the sensors every second.

[0286] The device uses a microphone to pick up the user's tone of voice and emotional state and saves the audio data. It also uses a camera to capture the user's facial expressions and performs real-time emotion analysis. For example, it uses facial recognition technology to distinguish between smiling and angry expressions.

[0287] Input: Vital sign data from sensors, audio data from microphones, video data from cameras

[0288] Output: Collected vital sign data and emotional data (voice analysis results and facial expression analysis results)

[0289] Step 2:

[0290] Data transmission

[0291] The device encrypts the collected vital sign and emotion data in real time and transmits it to a server over the Internet using the TLS / SSL protocol via HTTPS. For example, the data is sent in packets every 10 seconds.

[0292] Input: Collected vital signs and emotion data

[0293] Output: Encrypted data sent to the server

[0294] Step 3:

[0295] Data analysis

[0296] The server analyzes the received vital sign data and emotion data. The received data is stored in a database and a dedicated analysis algorithm (e.g., TensorFlow, scikit-learn) is used for analysis. The data is preprocessed and inconsistencies are removed before it is used for analysis.

[0297] The server evaluates the user's health condition (hyperthermia, normal body temperature, etc.) and emotional state (relaxed, stressed, etc.) based on the analysis results. For example, if the body temperature is 37.2 degrees and the emotional state is determined to be stressed, it will determine that relaxation is necessary.

[0298] Input: Encrypted data sent to the server

[0299] Output: Assessment of health and emotional state based on analyzed vital signs and emotion data.

[0300] Step 4:

[0301] Determining your environment settings

[0302] The server then recommends the optimal indoor environment based on the analysis results. For example, if a user has a body temperature of 37.2 degrees and is in a state of stress, it will recommend setting the air conditioner to 22 degrees and the humidifier to 50% humidity. The settings are determined taking into account past data and weather data.

[0303] Input: Analyzed health and emotional state ratings

[0304] Output: Recommended indoor environment setting data

[0305] Step 5:

[0306] Smart home appliance control

[0307] The terminal controls smart home appliances in the room based on the environmental setting data sent from the server, for example, sending control commands to set the air conditioner to 22 degrees and the humidifier to 50% humidity.

[0308] The terminal checks whether the sent control command was successful and reports success or failure to the server. For example, it sends a command via an API for air conditioner settings and checks whether the setting was successful.

[0309] Input: Preference data sent from the server

[0310] Output: Controlled smart appliances and confirmation of successful control

[0311] Step 6:

[0312] Send a message of support

[0313] The server activates the "Go for it" mode and uses a generative AI model (e.g., GPT-3) to create a cheering message based on the user's emotional data. The prompt used is, "The user's body temperature is 37.2 degrees and their emotional state is stressed. In this case, please tell us what kind of cheering message would be appropriate."

[0314] The server sends the generated cheer message to the device, which then displays it to the user. For example, an automatically generated message like "Relax!" is displayed as a pop-up every five minutes.

[0315] Input: User emotion data and prompt sentence

[0316] Output: Generated cheer message and its display

[0317] (Application example 2)

[0318] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0319] This invention relates to a system that collects and analyzes a user's biosignals and emotional data in real time and provides an optimal environment based on this data. However, conventional systems have insufficient means for ensuring user safety and are unable to respond appropriately when the user experiences stress or abnormalities in their biosignals. Therefore, a system is needed that uses a user's biosignals and emotional data to instantly assess security risks and send appropriate warnings and emergency notifications.

[0320] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting biosignal and emotional data of the user, means for analyzing the collected biosignal and emotional data, means for adjusting the environment based on the analysis results, means for sending a cheering message to motivate the user, means for assessing security risks using the biosignal and emotional data of the user, and means for issuing an alert and sending an emergency notification when a risk is detected. This not only optimizes the user's health and emotional state and enables high performance, but also makes it possible to ensure the user's safety in real time and respond quickly to emergencies.

[0321] "User" means an individual using the System.

[0322] "Biological signals" refer to data that indicates the state of the body, such as body temperature, heart rate, and blood pressure.

[0323] "Emotional data" refers to data that indicates the user's emotional state through voice and facial expression analysis.

[0324] "Analysis" refers to the process of evaluating and interpreting collected biosignal and emotional data.

[0325] "Environmental adjustment" refers to the operation of optimizing the indoor environment, such as temperature, humidity, and lighting, based on the analysis results.

[0326] "Motivation" refers to efforts to increase the user's motivation and enthusiasm.

[0327] A "support message" refers to words of encouragement or instructions sent to motivate a user.

[0328] "Security risk" refers to a potential threat or danger to the safety of a user.

[0329] "Warning" refers to a notification sent to users and other relevant parties when a danger or abnormality is detected.

[0330] "Emergency notifications" refer to alerts or messages sent immediately when an abnormality occurs.

[0331] This invention is a real-time security risk assessment system that collects and analyzes a user's biometric and emotional data to ensure their safety. This system shares data with smart glasses, a server, and the Internet, and can adjust the environment as needed, issue warnings, and send emergency notifications according to the user's situation. The specific configuration and operation of this system are described below.

[0332] System Configuration Overview

[0333] Hardware

[0334] 1. Smart Glasses

[0335] Camera: Records the user's facial expressions in real time and collects emotional data.

[0336] Microphone: Records the user's voice and provides data for emotional analysis.

[0337] Various sensors: Measure vital signs such as body temperature, heart rate, and blood pressure.

[0338] 2. Server

[0339] Data analysis engine: Analyzes collected bio-signals and emotional data to assess the user's condition.

[0340] Machine learning algorithms: Machine learning algorithms are used to generate accurate analysis results from biometric and emotional data.

[0341] Cheer message generation module: Generates cheer messages according to the situation.

[0342] software

[0343] Python program: The main program for data collection, data transmission, and security risk assessment.

[0344] Rest API: A standard API for communicating with the server.

[0345] Encryption protocol: Encrypts data to ensure security during transmission.

[0346] Process Details

[0347] The server receives data sent from the smart glasses. The smart glasses use a camera, microphone, and various sensors to collect the user's biometric and emotional data. The collected data is sent to the server in real time and analyzed using machine learning algorithms. Based on the analysis results, the server evaluates the user's current health and emotional state.

[0348] Based on the evaluation results, the server can issue instructions to adjust the indoor environment. For example, if a user's body temperature is rising, the server can lower the air conditioner temperature setting or adjust the lighting. If the user is feeling stressed, the server can also send a message of encouragement such as "Relax!"

[0349] It also assesses security risks based on the user's health and emotional state: if the user is stressed and has a high body temperature, for example, the system will issue an alert, adjust the environment as needed, and send an emergency notification to security staff.

[0350] Specific examples

[0351] For example, when a user is wearing smart glasses, if the system detects a body temperature of 37.3 degrees, a heart rate of 90, a blood pressure of 120 / 80, and an emotional state of "stress," it will lower the air conditioning temperature setting, display a supportive message saying "Relax!", and automatically send an emergency notification to security staff.

[0352] Example prompt sentence:

[0353] "Temperature is 37.3°C, emotional state is recognized as 'stressed'. These are abnormal values. Please implement emergency response."

[0354] This allows the system to optimize the user's health and emotional state, providing a comfortable and safe environment for the user.

[0355] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0356] Step 1:

[0357] The device uses the camera, microphone, and various sensors in the smart glasses to collect the user's biometric signals (body temperature, heart rate, blood pressure) and emotional data (facial expressions, voice). Specific data collected includes a body temperature of 36.8 degrees, a heart rate of 85, and an emotional state of "relaxed."

[0358] Step 2:

[0359] The device transmits the collected biometric and emotional data to a server in real time. The data is encrypted using an encryption protocol to ensure security. Input data includes body temperature, heart rate, and emotional state.

[0360] Step 3:

[0361] The server analyzes the received biometric and emotional data. It uses machine learning algorithms to evaluate the data and determine the user's current health and emotional state. For example, if the body temperature is 37.2 degrees and the emotional state is "stressed," the user is diagnosed with high stress. The input data is analyzed, and the user's health and emotional state are obtained as outputs.

[0362] Step 4:

[0363] The server then adjusts the environment based on the analysis results. For example, it may change the air conditioner's temperature setting from 24 degrees to 22 degrees and adjust the lighting brightness to 500 lux. The analysis results are used as input for this process, and environmental setting data (temperature, illuminance, etc.) is obtained as output.

[0364] Step 5:

[0365] The device controls smart home appliances such as air conditioners and lighting based on the configuration data received from the server. The device receives the configuration data as input and executes specific home appliance control commands (such as changing the temperature setting of the air conditioner or adjusting the brightness of the lights) as output.

[0366] Step 6:

[0367] The server uses a "Ganbare Mode" to send encouraging messages to motivate the user. For example, if the user is feeling stressed, the server sends a message saying "Relax!". This process uses emotional state data as input, and generates and sends encouraging messages as output.

[0368] Step 7:

[0369] The server evaluates the security risk based on the user's health and emotional state. If the user's body temperature rises and the emotional state is judged to be "stressed," it issues an alert and sends an emergency notification to security staff. The input to this process is the health and emotional state data, and the output is a warning message and an emergency notification.

[0370] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0371] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0372] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0373] [Second embodiment]

[0374] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0375] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0376] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0377] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0378] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0379] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0380] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0381] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0382] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0383] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0384] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0385] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0386] The present invention is a system that collects and analyzes a user's vital signs and works with smart home appliances to provide an optimal indoor environment. Furthermore, a "Go for it" mode can send encouraging messages to the user, increasing their motivation. An example of how to specifically implement the present invention is shown below.

[0387] System Configuration

[0388] The system consists of the following main components:

[0389] 1. Vital Signs Collection Device

[0390] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[0391] 2. Data Collection and Transfer

[0392] The device sends the collected vital sign data to a server, where it is encrypted and transmitted over the internet.

[0393] 3. Data analysis server

[0394] The server analyzes the received vital sign data and calculates the optimal settings for the user's physical condition and indoor environment. The server can analyze the data using machine learning algorithms and perform statistical analysis.

[0395] 4. Smart appliances

[0396] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0397] 5. Support message function

[0398] The server periodically sends encouraging messages to users using the "Ganbare Mode" function, which is introduced to motivate users and keep them focused.

[0399] Program processing

[0400] 1. Data Collection

[0401] The terminal acquires vital sign data such as the user's body temperature, heart rate, blood pressure, etc. from the wearable device. For example, suppose the user's current body temperature is 36.8 degrees, heart rate is 72 BPM, and blood pressure is 120 / 80 mmHg.

[0402] 2. Data Transmission

[0403] The device transmits the collected data in real time to a server, where it is securely stored.

[0404] 3. Data analysis

[0405] The server analyzes the received vital sign data and evaluates the user's physical condition. For example, if the body temperature exceeds 37.2 degrees, it determines that the user's physical condition is unstable and sets the room temperature to be lowered by 2 degrees.

[0406] 4. Determine your environment settings

[0407] The server then determines the optimal indoor environmental settings based on the analysis results, for example, setting the temperature between 24 and 22 degrees Celsius, maintaining humidity at 50%, and setting the illumination to 500 lux.

[0408] 5. Controlling smart appliances

[0409] The device adjusts the air conditioner, humidifier, and lighting based on the environmental setting data received from the server, allowing the user to work in a comfortable environment.

[0410] 6. Send a message of support

[0411] The server periodically sends encouraging messages to the user through the "Ganbare Mode." For example, the message "Ganbare!" is displayed every 5 seconds to motivate the user.

[0412] Specific examples

[0413] The user puts on the wearable device and begins collecting vital signs. The device sends the data to a server, which then dynamically analyzes it. For example, if the user's body temperature rises, the server will issue a command to lower the air conditioner temperature. At the same time, the server will activate the "Go for it" mode and display a message of encouragement saying "Go for it!" This allows the user to continue working in an optimal environment while maintaining high motivation.

[0414] The above is an embodiment of the present invention. This system allows users to effectively concentrate on their work while maintaining their health, thereby maximizing performance.

[0415] The processing flow will be explained below.

[0416] Step 1:

[0417] The device collects vital sign data, such as body temperature, heart rate, and blood pressure, in real time through wearable devices worn by the user, such as audio glasses or a smartwatch.

[0418] Step 2:

[0419] The device encrypts the collected vital signs data and sends it to a server over the internet, using encryption protocols to ensure secure data transfer.

[0420] Step 3:

[0421] The server analyzes the received vital sign data using machine learning algorithms and statistical analysis tools to assess the user's physical condition.

[0422] Step 4:

[0423] The server then calculates the optimal indoor environment settings based on the analysis results. For example, if the user's body temperature is above 37.2 degrees, the room temperature will be lowered from 24 degrees to 22 degrees.

[0424] Step 5:

[0425] The server then transmits the determined environmental settings to the device, including parameters such as temperature, humidity, and illuminance.

[0426] Step 6:

[0427] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental settings received from the server, setting the room temperature to 22 degrees, humidity to 50%, and illuminance to 500 lux.

[0428] Step 7:

[0429] The server activates the "Ganbare mode" and periodically sends a cheering message to the user. For example, the server sends the message "Ganbare!" to the terminal every 5 seconds.

[0430] Step 8:

[0431] The device displays the support message received from the server to the user, which increases the user's motivation and improves work efficiency.

[0432] Step 9:

[0433] The terminal repeats the processes from step 1 to step 8 at regular time intervals, for example, every 30 seconds.

[0434] Step 10:

[0435] Users continue working while receiving regular, optimized environments and encouraging messages, helping them maintain their health and perform at their best.

[0436] Example 1

[0437] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0438] In today's busy living environment, it is difficult for users to maintain a comfortable indoor environment while properly managing their own health. Furthermore, there are few ways to motivate users, making it difficult to improve work efficiency and quality of life. In particular, there is a lack of systems that can quickly adjust the environment in response to changes in health status and provide accurate advice based on the user's physical condition.

[0439] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0440] In this invention, the server includes means for collecting physical information of the user, means for analyzing the collected physical information, means for adjusting the indoor environment based on the analysis results, and means for sending encouraging messages to motivate the user. This makes it possible to monitor the user's health condition in real time, create an optimal indoor environment, and increase the user's motivation.

[0441] "User" means an individual using the System.

[0442] "Physical information" refers to biometric data including vital sign data such as the user's body temperature, heart rate, and blood pressure.

[0443] "Means of collection" refers to the function of obtaining the user's physical information in real time using wearable devices and sensors.

[0444] "Means for analyzing" refers to a processing device or software for analyzing the collected physical information and assessing the user's health status and changes therein.

[0445] "Adjusting means" refers to equipment or devices that automatically change indoor environmental parameters such as temperature, humidity, and illuminance based on the analysis results.

[0446] The "means for sending a cheering message to motivate" refers to a function for displaying or notifying a cheering message by voice to increase the motivation of the user.

[0447] "Certain conditions" refers to a state in which the user's physical information satisfies a predetermined standard or range.

[0448] "Means for suggesting break times and hydration" refers to a function for recommending appropriate breaks and hydration based on the user's physical condition.

[0449] "Real-time monitoring" refers to continuously acquiring the user's physical information and immediately reflecting it.

[0450] "Means for automatic adjustment" refers to a system for changing the indoor environment in response to the user's physical information without manual intervention.

[0451] The present invention is a system that collects and analyzes a user's physical information and works in conjunction with smart home appliances to provide an optimal indoor environment. Furthermore, a "Go for it" mode can be used to send encouraging messages to the user, increasing their motivation. An example of a specific implementation of the present invention is shown below.

[0452] System Configuration

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

[0454] 1. Physical information collection devices

[0455] The device collects the user's physical information using wearable devices such as audio glasses and smartwatches, which collect data such as body temperature, heart rate, and blood pressure in real time.

[0456] 2. Data Collection and Transfer

[0457] The device sends the collected physiological data to a server, where it is encrypted and transmitted over the internet.

[0458] 3. Data analysis server

[0459] The server analyzes the received physiological data and calculates the optimal settings for the user's physical condition and indoor environment. The server can analyze the data using machine learning algorithms and perform statistical analysis, specifically using software such as Python's Scikit-learn and TensorFlow.

[0460] 4. Smart appliances

[0461] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0462] 5. Support message function

[0463] The server periodically sends encouraging messages to users using the "Ganbare Mode" feature, which is introduced to motivate users and keep them focused.

[0464] Specific examples

[0465] The user puts on the wearable device and begins collecting physical information. The device sends the data to a server, which then dynamically analyzes it. For example, if the user's body temperature rises, the server will issue a command to lower the air conditioner temperature. At the same time, the server will activate a "go for it" mode and display a message of encouragement saying, "Take it easy today, relax." This allows the user to continue working in an optimal environment while maintaining high motivation.

[0466] Prompt Sentence Examples

[0467] Examples of prompts to be input to a generative AI model include:

[0468] "Please suggest optimal temperature and humidity settings for the room based on body temperature and heart rate data collected from the user's smartwatch."

[0469] "Please explain what indoor environmental settings should be made when the user's physical condition is unstable, including specific temperature, humidity, and illuminance."

[0470] "Please provide five specific motivational and encouraging messages for users who are feeling unwell."

[0471] The above is an embodiment of the present invention. This system allows users to effectively concentrate on their work while maintaining their health, thereby maximizing performance.

[0472] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0473] Step 1:

[0474] Data collection

[0475] The terminal acquires the user's physical information (body temperature, heart rate, blood pressure, etc.) in real time from wearable devices such as audio glasses or smartwatches. Sensors in the devices measure body temperature and heart rate and transmit the data to the terminal. The input is the user's current biometric data, and the output is the collected vital sign data.

[0476] Step 2:

[0477] Data transmission

[0478] The device sends the collected physiological data to a server via the Internet. The data is encrypted and securely transferred. The input is the collected vital sign data, and the output is the received vital sign data, which is stored on the server.

[0479] Step 3:

[0480] Data storage

[0481] The server stores the received physiological data in a database, for example, an SQL database or a NoSQL database. The input is the received vital sign data, and the output is the data stored in an organized manner in the database. The stored data is organized by date and time, making it easy to search.

[0482] Step 4:

[0483] Data analysis

[0484] The server analyzes the stored vital sign data and uses machine learning algorithms to evaluate the user's physical condition. For example, it uses Python's Scikit-learn or TensorFlow to analyze data from the past week. The input is the vital sign data stored in the database, and the output is the analysis results regarding the user's health condition.

[0485] Step 5:

[0486] Determining your environment settings

[0487] The server determines the optimal indoor environment settings based on the analysis results. For example, if the body temperature exceeds 37.2 degrees, the room temperature will be lowered by 2 degrees. The input is the health status analysis result, and the output is the specific indoor environment setting parameters (temperature, humidity, illuminance, etc.).

[0488] Step 6:

[0489] Smart home appliance control

[0490] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental setting data received from the server. For example, the device changes the temperature setting of an air conditioner from 24 degrees to 22 degrees and sets the humidity to 50%. The input is the environmental setting data from the server, and the output is the adjusted indoor environment.

[0491] Step 7:

[0492] Send a message of support

[0493] The server periodically sends encouraging messages to the user through the "Ganbare Mode." For example, the message "Take it easy today, relax!" is displayed every hour. The input is data about the user's health status and a template message to improve motivation, and the output is the display or audio notification of the encouraging message to the user.

[0494] The above are the specific processing steps of the program of this system.

[0495] (Application example 1)

[0496] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0497] Currently, it is difficult to provide an optimal environment based on the health status of staff and customers in stores. It is also difficult to maintain staff motivation, especially during busy times. This leads to poor staff efficiency and lower customer satisfaction. Additionally, there is a lack of systems that can analyze vital sign data in real time and automatically adjust the store environment based on that data.

[0498] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0499] In this invention, the server includes means for collecting users' vital signs, means for analyzing the collected vital sign data, means for adjusting the indoor environment based on the analysis results, means for sending cheering messages to motivate users, means for collecting vital signs of store staff and customers and providing an optimal store environment, means for automatically controlling smart equipment using the vital sign data, and means for sending cheering messages to staff and customers in real time. This makes it possible to optimize the in-store environment, maintain the health and motivation of staff, and improve customer satisfaction.

[0500] "Vital signs" refers to basic biological information such as body temperature, heart rate, and blood pressure.

[0501] "Collection methods" refers to devices and systems used to obtain vital signs of users, staff, or customers.

[0502] "Analysis means" refers to a server or software that analyzes collected vital sign data and evaluates the user's physical condition and environmental settings.

[0503] "Environmental adjustment means" refers to smart home appliances and control systems that automatically change indoor temperature, humidity, lighting, etc. based on analysis results.

[0504] "Encouragement message means" refers to a function or system that sends encouraging messages to increase the user's motivation.

[0505] "Store environment provision means" refers to systems and equipment for creating an optimal store environment based on the vital signs of store staff and customers.

[0506] "Smart equipment control means" refers to a system that automatically controls smart equipment such as air conditioners, humidifiers, and lighting based on vital sign data.

[0507] "Real-time transmission means" refers to a communication system for instantly sending support messages and notifications to customers and staff.

[0508] This invention is a system for collecting and analyzing vital signs of users, store staff, and customers to provide an optimal indoor environment. This system consists of a device for collecting vital signs, a server for transmitting and analyzing the data, smart equipment for adjusting the indoor environment, and a means for sending encouraging messages to users and staff. Below is a detailed explanation of how this system works.

[0509] The system consists of the following:

[0510] 1. Vital Signs Collection Device

[0511] Collect vital signs such as body temperature, heart rate, and blood pressure of users, staff, or customers using wearable devices such as smartwatches and audio glasses. The devices collect vital sign data in real time.

[0512] 2. Data Collection and Transfer

[0513] The collected vital sign data is sent to a server via smartphone, where it is encrypted and securely transmitted over the internet.

[0514] 3. Data analysis server

[0515] The server analyzes the received vital signs data and assesses the status of the user, staff, or customer. Machine learning algorithms (e.g., scikit-learn) are used to perform statistical analysis of the data.

[0516] 4. Decide on indoor environmental adjustments

[0517] Based on the server's analysis results, the optimal indoor environment settings are determined. Specifically, the air conditioner temperature is adjusted, the humidifier is activated, and the lighting is adjusted. This automatically optimizes temperature, humidity, and lighting intensity.

[0518] 5. Controlling smart equipment

[0519] The server then sends the determined environmental setting data to the smart equipment, adjusting the air conditioner, humidifier, lighting, etc., thereby optimizing the in-store environment in real time.

[0520] 6. Support message function

[0521] The server sends encouraging messages to users and staff using the "Ganbare Mode" function. This function is used to increase motivation and reduce stress for users and staff. The messages are displayed on smartwatches or smart glasses.

[0522] Specific examples

[0523] For example, consider a situation where there are a lot of customers during lunchtime and store staff are tired.

[0524] Hardware: Smartwatches, air conditioners, lighting, humidifiers

[0525] Software: Python, scikit-learn, IoT device control library

[0526] At this time, the smartwatch collects the staff member's body temperature (e.g., 37.5°C), heart rate (e.g., 80 BPM), and blood pressure (e.g., 130 / 85 mmHg), and sends this data to a server using a Python script. The server then analyzes the data using a machine learning algorithm using scikit-learn and determines that the staff member's physical condition is stressed. Based on the analysis results, an instruction is issued to change the air conditioner temperature from 24°C to 22°C, and at the same time, a cheering message saying "Do your best!" is displayed on the smartwatch every five seconds.

[0527] Prompt Sentence Examples

[0528] "For users whose body temperature exceeds 37.2 degrees, please lower the air conditioner temperature by 2 degrees. Also, please display a message of encouragement every 5 seconds."

[0529] This optimizes the store environment, allowing staff to continue working in a comfortable environment and improving customer satisfaction.

[0530] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0531] Step 1:

[0532] The user wears a vital sign collection device such as a smartwatch or audio glasses. This device acquires the user's vital signs, such as body temperature, heart rate, and blood pressure, in real time. The inputs are the user's body temperature (e.g., 36.8°C), heart rate (e.g., 72 BPM), and blood pressure (e.g., 120 / 80 mmHg), and these data are stored in the device as outputs.

[0533] Step 2:

[0534] The terminal sends the collected vital sign data to a server via the internet via the smartphone. The data is encrypted and transferred securely. The input is the vital sign data acquired from the smart device, and the output is the encrypted vital sign data sent to the server. Specifically, the smartphone receives data from the device using Bluetooth and sends the data to the server using the HTTPS protocol.

[0535] Step 3:

[0536] The server analyzes the received vital sign data and evaluates the user's physical condition. A Python machine learning library (e.g., scikit-learn) is used for the analysis, and statistical analysis of the data is performed. The input is the vital sign data sent to the server, and the output is the user's physical condition evaluation result. Specifically, the server runs an algorithm based on the temperature, heart rate, and blood pressure data to determine whether there are any abnormal values.

[0537] Step 4:

[0538] The server determines the optimal indoor environmental settings based on the analysis results. For example, if the body temperature exceeds 37.2 degrees, it will instruct the air conditioner to lower the temperature by 2 degrees. The input is the physical condition evaluation result, and the output is the environmental setting parameters (e.g., the air conditioner's set temperature). Specific operations involve determining the environmental adjustment parameters based on if statements and threshold setting rules.

[0539] Step 5:

[0540] The terminal controls smart equipment (e.g., air conditioners, humidifiers, and lighting) based on the environmental setting data received from the server. This automatically optimizes the temperature, humidity, and illuminance. The input is the environmental setting parameters from the server, and the output is the new settings for the air conditioner, humidifier, and lighting. Specifically, the terminal uses the IoT device control library to send commands to control each piece of equipment.

[0541] Step 6:

[0542] The server periodically sends cheering messages to users and staff using the "Go for it mode." For example, the message "Go for it!" is displayed every five seconds. The input is the cheering message data on the server, and the output is the message displayed on the smartwatch or smart glasses. Specifically, the server executes the message sending protocol using a periodic timer.

[0543] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0544] This invention is a system that collects and analyzes the user's vital signs in real time, and combines this with an emotion engine that recognizes the user's emotions to provide an optimal indoor environment. It can also send encouraging messages to the user through a "Go for it" mode to increase their motivation. An example of how this system can be implemented is shown below.

[0545] System Configuration

[0546] The system consists of the following main components:

[0547] 1. Vital Signs Collection Device

[0548] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[0549] 2. Emotion Recognition Engine

[0550] The device collects emotional data from the user through voice input and facial expression analysis. Voice input is analyzed through a microphone to capture the user's tone of voice and emotional state, while facial expression analysis is performed using a camera.

[0551] 3. Data Collection and Transfer

[0552] The device encrypts the collected vital sign and emotion data and transmits it to a server via the internet, using encryption protocols to ensure data transmission is secure.

[0553] 4. Data Analysis Server

[0554] The server analyzes the received vital sign data and emotion data to evaluate the user's physical and emotional state. The server can analyze the data using machine learning algorithms and perform statistical analysis.

[0555] 5. Smart appliances

[0556] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0557] 6. Support message function

[0558] The server uses the "Ganbare Mode" to send users cheering messages that change dynamically based on their emotional data. This feature was introduced to motivate users and help them maintain their concentration.

[0559] Program processing

[0560] 1. Data Collection

[0561] The terminal acquires vital sign data such as the user's body temperature, heart rate, and blood pressure from the wearable device. At the same time, it uses a microphone and camera to collect the user's emotional data. For example, if the user's body temperature is 36.8 degrees, the emotional state is recognized as "relaxed."

[0562] 2. Data Transmission

[0563] The device transmits the collected vital sign data and emotion data in real time to a server, where the data is securely stored.

[0564] 3. Data analysis

[0565] The server analyzes the received vital sign data and emotional data to evaluate the user's physical and emotional state. For example, if the body temperature is over 37.2 degrees and the emotional state is recognized as "stressed," the server adjusts the environmental settings to be more lenient.

[0566] 4. Determine your environment settings

[0567] The server then determines the optimal indoor environmental settings based on the analysis results, for example, setting the temperature between 24 and 22 degrees Celsius, maintaining humidity at 50%, and setting the illumination to 500 lux.

[0568] 5. Controlling smart appliances

[0569] The device adjusts the air conditioner, humidifier, and lighting based on the environmental setting data received from the server, allowing the user to work in a comfortable environment.

[0570] 6. Send a message of support

[0571] The server periodically sends encouraging messages based on the user's emotional data through the "Ganbare Mode." For example, the message "Ganbare!" is displayed every five seconds, or the message "Relax!" is displayed to motivate the user.

[0572] Specific examples

[0573] The user uses a system that combines a wearable device with an emotion recognition engine. The device collects vital signs and emotion data and sends this data to a server. If the server determines that the user's body temperature is 37.2 degrees and that the user is feeling stressed, it will operate the air conditioner to set the room temperature to 22 degrees, use a humidifier to keep the humidity at 50%, and adjust the lighting to 500 lux. At the same time, it sends a supportive message saying, "Relax!" This allows the user to continue working in a comfortable environment, maintaining their health and concentration.

[0574] The above is an embodiment of the present invention, which allows users to optimize their health and emotional state and perform at their best.

[0575] The processing flow will be explained below.

[0576] Step 1:

[0577] The device collects vital sign data, such as body temperature, heart rate, and blood pressure, in real time through wearable devices worn by the user, such as audio glasses or a smartwatch.

[0578] Step 2:

[0579] The device collects the user's voice input and facial expressions using a camera and microphone, and then uses an emotion recognition engine to analyze the user's emotional data, recognizing, for example, emotions such as joy, anger, sadness, and happiness.

[0580] Step 3:

[0581] The device encrypts the collected vital sign data and emotional data and transmits it to a server in real time via the Internet.

[0582] Step 4:

[0583] The server analyzes the received vital sign and emotion data using machine learning algorithms and statistical analysis tools to assess the user's physical and emotional state.

[0584] Step 5:

[0585] The server calculates the optimal room environment settings based on the analysis results. For example, if the user's body temperature exceeds 37.2 degrees Celsius or their emotional state is recognized as "stressed," the server will adjust the room temperature from 24 degrees Celsius to 22 degrees Celsius.

[0586] Step 6:

[0587] The server then transmits the determined environmental settings to the device, including parameters such as temperature, humidity, and illuminance.

[0588] Step 7:

[0589] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental settings received from the server, setting the room temperature to 22 degrees, humidity to 50%, and illuminance to 500 lux.

[0590] Step 8:

[0591] The server activates the "Go for it" mode and dynamically generates a supportive message based on the user's vital sign data and emotional data, and sends it to the device. For example, if the user is feeling stressed, the server sends a message saying, "Relax!"

[0592] Step 9:

[0593] The device displays the cheering message received from the server to the user, allowing the user to receive a motivational message at an appropriate time.

[0594] Step 10:

[0595] The terminal repeats the processes from step 1 to step 9 at regular time intervals, for example, every 30 seconds.

[0596] Step 11:

[0597] Users continue working while receiving regular, optimized environments and encouraging messages, which help them optimize their health and emotional state and perform at their best.

[0598] Example 2

[0599] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0600] In modern society, users are constantly exposed to stress, which can lead to deterioration in their health. It is difficult for users to manually adjust their indoor environment to create an optimal one. Furthermore, it is necessary to adjust the environment to respond to emotional changes and improve motivation. However, existing systems lack the ability to analyze a user's vital signs and emotional state in real time, adjust the indoor environment accordingly, or generate and send personalized support messages.

[0601] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0602] In this invention, the server includes means for collecting the user's vital signs, means for analyzing the collected vital sign data and emotional data, means for adjusting the indoor environment based on the analysis results, and means for sending a cheering message using a generative AI model based on the user's emotional state. This allows the user to optimize both their health and emotional state in real time, enabling them to perform at a high level in a comfortable environment.

[0603] "User" refers to an individual who uses this system.

[0604] "Vital signs" refers to basic vital indicators of the human body, such as body temperature, heart rate, and blood pressure.

[0605] "Data" refers to vital signs and emotional information collected from sensors and devices.

[0606] "Emotional data" refers to information about the user's emotional state obtained from voice input and facial expression analysis.

[0607] "Collection means" refers to the devices and methods for acquiring vital signs and emotional data using wearable devices and sensors.

[0608] "Analysis means" refers to algorithms or software that analyze the collected data and assess the user's physical and emotional state.

[0609] "Adjustment means" refers to a device or method that automatically adjusts the indoor temperature, humidity, illuminance, etc. based on the analysis results.

[0610] "Generative AI model" refers to an artificial intelligence model that dynamically generates cheering messages based on the user's emotional state.

[0611] "Support messages" refer to text that encourages or motivates users to increase their motivation.

[0612] MODE FOR CARRYING OUT THE INVENTION

[0613] This invention is a system that collects and analyzes a user's vital signs in real time, and integrates a means of recognizing the user's emotions to provide an optimal indoor environment. Furthermore, through the "Go for it" mode, a generative AI model can be used to send encouraging messages based on the user's emotional state, increasing the user's motivation. An example of how this system can be implemented is shown below.

[0614] System Configuration

[0615] The system consists of the following main components:

[0616] 1. Vital Signs Collection Device

[0617] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[0618] 2. Emotion Recognition Engine

[0619] The device collects emotional data from the user through voice input and facial expression analysis. Voice input is analyzed through a microphone to capture the user's tone of voice and emotional state, while facial expression analysis is performed using a camera.

[0620] 3. Data Collection and Transfer

[0621] The device encrypts the collected vital sign and emotion data and sends it to a server via the Internet, using the TLS / SSL protocol to ensure secure data transfer.

[0622] 4. Data Analysis Server

[0623] The server analyzes the received vital sign data and emotion data to evaluate the user's physical and emotional state. The server can analyze the data using machine learning algorithms (e.g., TensorFlow and scikit-learn) and perform statistical analysis.

[0624] 5. Smart appliances

[0625] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0626] 6. Support message function

[0627] The server uses "Go for it" mode to send dynamically changing cheering messages to users based on their emotional data. Prompts for the generative AI model (e.g., GPT-3) include, "The user's body temperature is 37.2 degrees and their emotional state is stressed. Please tell me what kind of cheering message would be appropriate in this case."

[0628] Specific examples

[0629] The user wears audio glasses and a smartwatch. The device captures the user's body temperature and heart rate in real time, and also collects emotional data (e.g., "stress" state) via a microphone and camera. This data is encrypted and sent to a server.

[0630] The server analyzes this data and evaluates the user's health condition. For example, if the server determines that the user's body temperature is 37.2 degrees, indicating stress, it will operate the air conditioner to set the room temperature to 22 degrees, use a humidifier to keep the humidity at 50%, and adjust the lighting to 500 lux. At the same time, it will use a generative AI model to generate a supportive message such as "Relax!" and send it to the device.

[0631] Based on this, the device will set the air conditioner to 22 degrees, adjust the humidifier to 50% humidity, and display a message to the user saying "Relax!", allowing the user to continue working in a comfortable environment, maintaining their health and concentration.

[0632] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0633] Step 1:

[0634] Data collection

[0635] The device acquires vital sign data such as the user's body temperature, heart rate, and blood pressure using sensors in wearable devices (audio glasses or smartwatches). For example, the device reads the body temperature and heart rate from the sensors every second.

[0636] The device uses a microphone to pick up the user's tone of voice and emotional state and saves the audio data. It also uses a camera to capture the user's facial expressions and performs real-time emotion analysis. For example, it uses facial recognition technology to distinguish between smiling and angry expressions.

[0637] Input: Vital sign data from sensors, audio data from microphones, video data from cameras

[0638] Output: Collected vital sign data and emotional data (voice analysis results and facial expression analysis results)

[0639] Step 2:

[0640] Data transmission

[0641] The device encrypts the collected vital sign and emotion data in real time and transmits it to a server over the Internet using the TLS / SSL protocol via HTTPS. For example, the data is sent in packets every 10 seconds.

[0642] Input: Collected vital signs and emotion data

[0643] Output: Encrypted data sent to the server

[0644] Step 3:

[0645] Data analysis

[0646] The server analyzes the received vital sign data and emotion data. The received data is stored in a database and a dedicated analysis algorithm (e.g., TensorFlow, scikit-learn) is used for analysis. The data is preprocessed and inconsistencies are removed before it is used for analysis.

[0647] The server evaluates the user's health condition (hyperthermia, normal body temperature, etc.) and emotional state (relaxed, stressed, etc.) based on the analysis results. For example, if the body temperature is 37.2 degrees and the emotional state is determined to be stressed, it will determine that relaxation is necessary.

[0648] Input: Encrypted data sent to the server

[0649] Output: Assessment of health and emotional state based on analyzed vital signs and emotion data.

[0650] Step 4:

[0651] Determining your environment settings

[0652] The server then recommends the optimal indoor environment based on the analysis results. For example, if a user has a body temperature of 37.2 degrees and is in a state of stress, it will recommend setting the air conditioner to 22 degrees and the humidifier to 50% humidity. The settings are determined taking into account past data and weather data.

[0653] Input: Analyzed health and emotional state ratings

[0654] Output: Recommended indoor environment setting data

[0655] Step 5:

[0656] Smart home appliance control

[0657] The terminal controls smart home appliances in the room based on the environmental setting data sent from the server, for example, sending control commands to set the air conditioner to 22 degrees and the humidifier to 50% humidity.

[0658] The terminal checks whether the sent control command was successful and reports success or failure to the server. For example, it sends a command via an API for air conditioner settings and checks whether the setting was successful.

[0659] Input: Preference data sent from the server

[0660] Output: Controlled smart appliances and confirmation of successful control

[0661] Step 6:

[0662] Send a message of support

[0663] The server activates the "Go for it" mode and uses a generative AI model (e.g., GPT-3) to create a cheering message based on the user's emotional data. The prompt used is, "The user's body temperature is 37.2 degrees and their emotional state is stressed. In this case, please tell us what kind of cheering message would be appropriate."

[0664] The server sends the generated cheer message to the device, which then displays it to the user. For example, an automatically generated message like "Relax!" is displayed as a pop-up every five minutes.

[0665] Input: User emotion data and prompt sentence

[0666] Output: Generated cheer message and its display

[0667] (Application example 2)

[0668] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0669] This invention relates to a system that collects and analyzes a user's biosignals and emotional data in real time and provides an optimal environment based on this data. However, conventional systems have insufficient means for ensuring user safety and are unable to respond appropriately when the user experiences stress or abnormalities in their biosignals. Therefore, a system is needed that uses a user's biosignals and emotional data to instantly assess security risks and send appropriate warnings and emergency notifications.

[0670] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting biosignal and emotional data of the user, means for analyzing the collected biosignal and emotional data, means for adjusting the environment based on the analysis results, means for sending a cheering message to motivate the user, means for assessing security risks using the biosignal and emotional data of the user, and means for issuing an alert and sending an emergency notification when a risk is detected. This not only optimizes the user's health and emotional state and enables high performance, but also makes it possible to ensure the user's safety in real time and respond quickly to emergencies.

[0671] "User" means an individual using the System.

[0672] "Biological signals" refer to data that indicates the state of the body, such as body temperature, heart rate, and blood pressure.

[0673] "Emotional data" refers to data that indicates the user's emotional state through voice and facial expression analysis.

[0674] "Analysis" refers to the process of evaluating and interpreting collected biosignal and emotional data.

[0675] "Environmental adjustment" refers to the operation of optimizing the indoor environment, such as temperature, humidity, and lighting, based on the analysis results.

[0676] "Motivation" refers to efforts to increase the user's motivation and enthusiasm.

[0677] A "support message" refers to words of encouragement or instructions sent to motivate a user.

[0678] "Security risk" refers to a potential threat or danger to the safety of a user.

[0679] "Warning" refers to a notification sent to users and other relevant parties when a danger or abnormality is detected.

[0680] "Emergency notifications" refer to alerts or messages sent immediately when an abnormality occurs.

[0681] This invention is a real-time security risk assessment system that collects and analyzes a user's biometric and emotional data to ensure their safety. This system shares data with smart glasses, a server, and the Internet, and can adjust the environment as needed, issue warnings, and send emergency notifications according to the user's situation. The specific configuration and operation of this system are described below.

[0682] System Configuration Overview

[0683] Hardware

[0684] 1. Smart Glasses

[0685] Camera: Records the user's facial expressions in real time and collects emotional data.

[0686] Microphone: Records the user's voice and provides data for emotional analysis.

[0687] Various sensors: Measure vital signs such as body temperature, heart rate, and blood pressure.

[0688] 2. Server

[0689] Data analysis engine: Analyzes collected bio-signals and emotional data to assess the user's condition.

[0690] Machine learning algorithms: Machine learning algorithms are used to generate accurate analysis results from biometric and emotional data.

[0691] Cheer message generation module: Generates cheer messages according to the situation.

[0692] software

[0693] Python program: The main program for data collection, data transmission, and security risk assessment.

[0694] Rest API: A standard API for communicating with the server.

[0695] Encryption protocol: Encrypts data to ensure security during transmission.

[0696] Process Details

[0697] The server receives data sent from the smart glasses. The smart glasses use a camera, microphone, and various sensors to collect the user's biometric and emotional data. The collected data is sent to the server in real time and analyzed using machine learning algorithms. Based on the analysis results, the server evaluates the user's current health and emotional state.

[0698] Based on the evaluation results, the server can issue instructions to adjust the indoor environment. For example, if a user's body temperature is rising, the server can lower the air conditioner temperature setting or adjust the lighting. If the user is feeling stressed, the server can also send a message of encouragement such as "Relax!"

[0699] It also assesses security risks based on the user's health and emotional state: if the user is stressed and has a high body temperature, for example, the system will issue an alert, adjust the environment as needed, and send an emergency notification to security staff.

[0700] Specific examples

[0701] For example, when a user is wearing smart glasses, if the system detects a body temperature of 37.3 degrees, a heart rate of 90, a blood pressure of 120 / 80, and an emotional state of "stress," it will lower the air conditioning temperature setting, display a supportive message saying "Relax!", and automatically send an emergency notification to security staff.

[0702] Example prompt sentence:

[0703] "Temperature is 37.3°C, emotional state is recognized as 'stressed'. These are abnormal values. Please implement emergency response."

[0704] This allows the system to optimize the user's health and emotional state, providing a comfortable and safe environment for the user.

[0705] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0706] Step 1:

[0707] The device uses the camera, microphone, and various sensors in the smart glasses to collect the user's biometric signals (body temperature, heart rate, blood pressure) and emotional data (facial expressions, voice). Specific data collected includes a body temperature of 36.8 degrees, a heart rate of 85, and an emotional state of "relaxed."

[0708] Step 2:

[0709] The device transmits the collected biometric and emotional data to a server in real time. The data is encrypted using an encryption protocol to ensure security. Input data includes body temperature, heart rate, and emotional state.

[0710] Step 3:

[0711] The server analyzes the received biometric and emotional data. It uses machine learning algorithms to evaluate the data and determine the user's current health and emotional state. For example, if the body temperature is 37.2 degrees and the emotional state is "stressed," the user is diagnosed with high stress. The input data is analyzed, and the user's health and emotional state are obtained as outputs.

[0712] Step 4:

[0713] The server then adjusts the environment based on the analysis results. For example, it may change the air conditioner's temperature setting from 24 degrees to 22 degrees and adjust the lighting brightness to 500 lux. The analysis results are used as input for this process, and environmental setting data (temperature, illuminance, etc.) is obtained as output.

[0714] Step 5:

[0715] The device controls smart home appliances such as air conditioners and lighting based on the configuration data received from the server. The device receives the configuration data as input and executes specific home appliance control commands (such as changing the temperature setting of the air conditioner or adjusting the brightness of the lights) as output.

[0716] Step 6:

[0717] The server uses a "Ganbare Mode" to send encouraging messages to motivate the user. For example, if the user is feeling stressed, the server sends a message saying "Relax!". This process uses emotional state data as input, and generates and sends encouraging messages as output.

[0718] Step 7:

[0719] The server evaluates the security risk based on the user's health and emotional state. If the user's body temperature rises and the emotional state is judged to be "stressed," it issues an alert and sends an emergency notification to security staff. The input to this process is the health and emotional state data, and the output is a warning message and an emergency notification.

[0720] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0721] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0722] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0723] [Third embodiment]

[0724] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0725] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0726] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0727] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0728] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0729] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0730] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0731] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0732] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0733] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0734] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0735] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0736] The present invention is a system that collects and analyzes a user's vital signs and works with smart home appliances to provide an optimal indoor environment. Furthermore, a "Go for it" mode can send encouraging messages to the user, increasing their motivation. An example of how to specifically implement the present invention is shown below.

[0737] System Configuration

[0738] The system consists of the following main components:

[0739] 1. Vital Signs Collection Device

[0740] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[0741] 2. Data Collection and Transfer

[0742] The device sends the collected vital sign data to a server, where it is encrypted and transmitted over the internet.

[0743] 3. Data analysis server

[0744] The server analyzes the received vital sign data and calculates the optimal settings for the user's physical condition and indoor environment. The server can analyze the data using machine learning algorithms and perform statistical analysis.

[0745] 4. Smart appliances

[0746] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0747] 5. Support message function

[0748] The server periodically sends encouraging messages to users using the "Ganbare Mode" function, which is introduced to motivate users and keep them focused.

[0749] Program processing

[0750] 1. Data Collection

[0751] The terminal acquires vital sign data such as the user's body temperature, heart rate, blood pressure, etc. from the wearable device. For example, suppose the user's current body temperature is 36.8 degrees, heart rate is 72 BPM, and blood pressure is 120 / 80 mmHg.

[0752] 2. Data Transmission

[0753] The device transmits the collected data in real time to a server, where it is securely stored.

[0754] 3. Data analysis

[0755] The server analyzes the received vital sign data and evaluates the user's physical condition. For example, if the body temperature exceeds 37.2 degrees, it determines that the user's physical condition is unstable and sets the room temperature to be lowered by 2 degrees.

[0756] 4. Determine your environment settings

[0757] The server then determines the optimal indoor environmental settings based on the analysis results, for example, setting the temperature between 24 and 22 degrees Celsius, maintaining humidity at 50%, and setting the illumination to 500 lux.

[0758] 5. Controlling smart appliances

[0759] The device adjusts the air conditioner, humidifier, and lighting based on the environmental setting data received from the server, allowing the user to work in a comfortable environment.

[0760] 6. Send a message of support

[0761] The server periodically sends encouraging messages to the user through the "Ganbare Mode." For example, the message "Ganbare!" is displayed every 5 seconds to motivate the user.

[0762] Specific examples

[0763] The user puts on the wearable device and begins collecting vital signs. The device sends the data to a server, which then dynamically analyzes it. For example, if the user's body temperature rises, the server will issue a command to lower the air conditioner temperature. At the same time, the server will activate the "Go for it" mode and display a message of encouragement saying "Go for it!" This allows the user to continue working in an optimal environment while maintaining high motivation.

[0764] The above is an embodiment of the present invention. This system allows users to effectively concentrate on their work while maintaining their health, thereby maximizing performance.

[0765] The processing flow will be explained below.

[0766] Step 1:

[0767] The device collects vital sign data, such as body temperature, heart rate, and blood pressure, in real time through wearable devices worn by the user, such as audio glasses or a smartwatch.

[0768] Step 2:

[0769] The device encrypts the collected vital signs data and sends it to a server over the internet, using encryption protocols to ensure secure data transfer.

[0770] Step 3:

[0771] The server analyzes the received vital sign data using machine learning algorithms and statistical analysis tools to assess the user's physical condition.

[0772] Step 4:

[0773] The server then calculates the optimal indoor environment settings based on the analysis results. For example, if the user's body temperature is above 37.2 degrees, the room temperature will be lowered from 24 degrees to 22 degrees.

[0774] Step 5:

[0775] The server then transmits the determined environmental settings to the device, including parameters such as temperature, humidity, and illuminance.

[0776] Step 6:

[0777] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental settings received from the server, setting the room temperature to 22 degrees, humidity to 50%, and illuminance to 500 lux.

[0778] Step 7:

[0779] The server activates the "Ganbare mode" and periodically sends a cheering message to the user. For example, the server sends the message "Ganbare!" to the terminal every 5 seconds.

[0780] Step 8:

[0781] The device displays the support message received from the server to the user, which increases the user's motivation and improves work efficiency.

[0782] Step 9:

[0783] The terminal repeats the processes from step 1 to step 8 at regular time intervals, for example, every 30 seconds.

[0784] Step 10:

[0785] Users continue working while receiving regular, optimized environments and encouraging messages, helping them maintain their health and perform at their best.

[0786] Example 1

[0787] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0788] In today's busy living environment, it is difficult for users to maintain a comfortable indoor environment while properly managing their own health. Furthermore, there are few ways to motivate users, making it difficult to improve work efficiency and quality of life. In particular, there is a lack of systems that can quickly adjust the environment in response to changes in health status and provide accurate advice based on the user's physical condition.

[0789] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0790] In this invention, the server includes means for collecting physical information of the user, means for analyzing the collected physical information, means for adjusting the indoor environment based on the analysis results, and means for sending encouraging messages to motivate the user. This makes it possible to monitor the user's health condition in real time, create an optimal indoor environment, and increase the user's motivation.

[0791] "User" means an individual using the System.

[0792] "Physical information" refers to biometric data including vital sign data such as the user's body temperature, heart rate, and blood pressure.

[0793] "Means of collection" refers to the function of obtaining the user's physical information in real time using wearable devices and sensors.

[0794] "Means for analyzing" refers to a processing device or software for analyzing the collected physical information and assessing the user's health status and changes therein.

[0795] "Adjusting means" refers to equipment or devices that automatically change indoor environmental parameters such as temperature, humidity, and illuminance based on the analysis results.

[0796] The "means for sending a cheering message to motivate" refers to a function for displaying or notifying a cheering message by voice to increase the motivation of the user.

[0797] "Certain conditions" refers to a state in which the user's physical information satisfies a predetermined standard or range.

[0798] "Means for suggesting break times and hydration" refers to a function for recommending appropriate breaks and hydration based on the user's physical condition.

[0799] "Real-time monitoring" refers to continuously acquiring the user's physical information and immediately reflecting it.

[0800] "Means for automatic adjustment" refers to a system for changing the indoor environment in response to the user's physical information without manual intervention.

[0801] The present invention is a system that collects and analyzes a user's physical information and works in conjunction with smart home appliances to provide an optimal indoor environment. Furthermore, a "Go for it" mode can be used to send encouraging messages to the user, increasing their motivation. An example of a specific implementation of the present invention is shown below.

[0802] System Configuration

[0803] The system consists of the following main components:

[0804] 1. Physical information collection devices

[0805] The device collects the user's physical information using wearable devices such as audio glasses and smartwatches, which collect data such as body temperature, heart rate, and blood pressure in real time.

[0806] 2. Data Collection and Transfer

[0807] The device sends the collected physiological data to a server, where it is encrypted and transmitted over the internet.

[0808] 3. Data analysis server

[0809] The server analyzes the received physiological data and calculates the optimal settings for the user's physical condition and indoor environment. The server can analyze the data using machine learning algorithms and perform statistical analysis, specifically using software such as Python's Scikit-learn and TensorFlow.

[0810] 4. Smart appliances

[0811] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0812] 5. Support message function

[0813] The server periodically sends encouraging messages to users using the "Ganbare Mode" feature, which is introduced to motivate users and keep them focused.

[0814] Specific examples

[0815] The user puts on the wearable device and begins collecting physical information. The device sends the data to a server, which then dynamically analyzes it. For example, if the user's body temperature rises, the server will issue a command to lower the air conditioner temperature. At the same time, the server will activate a "go for it" mode and display a message of encouragement saying, "Take it easy today, relax." This allows the user to continue working in an optimal environment while maintaining high motivation.

[0816] Prompt Sentence Examples

[0817] Examples of prompts to be input to a generative AI model include:

[0818] "Please suggest optimal temperature and humidity settings for the room based on body temperature and heart rate data collected from the user's smartwatch."

[0819] "Please explain what indoor environmental settings should be made when the user's physical condition is unstable, including specific temperature, humidity, and illuminance."

[0820] "Please provide five specific motivational and encouraging messages for users who are feeling unwell."

[0821] The above is an embodiment of the present invention. This system allows users to effectively concentrate on their work while maintaining their health, thereby maximizing performance.

[0822] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0823] Step 1:

[0824] Data collection

[0825] The terminal acquires the user's physical information (body temperature, heart rate, blood pressure, etc.) in real time from wearable devices such as audio glasses or smartwatches. Sensors in the devices measure body temperature and heart rate and transmit the data to the terminal. The input is the user's current biometric data, and the output is the collected vital sign data.

[0826] Step 2:

[0827] Data transmission

[0828] The device sends the collected physiological data to a server via the Internet. The data is encrypted and securely transferred. The input is the collected vital sign data, and the output is the received vital sign data, which is stored on the server.

[0829] Step 3:

[0830] Data storage

[0831] The server stores the received physiological data in a database, for example, an SQL database or a NoSQL database. The input is the received vital sign data, and the output is the data stored in an organized manner in the database. The stored data is organized by date and time, making it easy to search.

[0832] Step 4:

[0833] Data analysis

[0834] The server analyzes the stored vital sign data and uses machine learning algorithms to evaluate the user's physical condition. For example, it uses Python's Scikit-learn or TensorFlow to analyze data from the past week. The input is the vital sign data stored in the database, and the output is the analysis results regarding the user's health condition.

[0835] Step 5:

[0836] Determining your environment settings

[0837] The server determines the optimal indoor environment settings based on the analysis results. For example, if the body temperature exceeds 37.2 degrees, the room temperature will be lowered by 2 degrees. The input is the health status analysis result, and the output is the specific indoor environment setting parameters (temperature, humidity, illuminance, etc.).

[0838] Step 6:

[0839] Smart home appliance control

[0840] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental setting data received from the server. For example, the device changes the temperature setting of an air conditioner from 24 degrees to 22 degrees and sets the humidity to 50%. The input is the environmental setting data from the server, and the output is the adjusted indoor environment.

[0841] Step 7:

[0842] Send a message of support

[0843] The server periodically sends encouraging messages to the user through the "Ganbare Mode." For example, the message "Take it easy today, relax!" is displayed every hour. The input is data about the user's health status and a template message to improve motivation, and the output is the display or audio notification of the encouraging message to the user.

[0844] The above are the specific processing steps of the program of this system.

[0845] (Application example 1)

[0846] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0847] Currently, it is difficult to provide an optimal environment based on the health status of staff and customers in stores. It is also difficult to maintain staff motivation, especially during busy times. This leads to poor staff efficiency and lower customer satisfaction. Additionally, there is a lack of systems that can analyze vital sign data in real time and automatically adjust the store environment based on that data.

[0848] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0849] In this invention, the server includes means for collecting users' vital signs, means for analyzing the collected vital sign data, means for adjusting the indoor environment based on the analysis results, means for sending cheering messages to motivate users, means for collecting vital signs of store staff and customers and providing an optimal store environment, means for automatically controlling smart equipment using the vital sign data, and means for sending cheering messages to staff and customers in real time. This makes it possible to optimize the in-store environment, maintain the health and motivation of staff, and improve customer satisfaction.

[0850] "Vital signs" refers to basic biological information such as body temperature, heart rate, and blood pressure.

[0851] "Collection methods" refers to devices and systems used to obtain vital signs of users, staff, or customers.

[0852] "Analysis means" refers to a server or software that analyzes collected vital sign data and evaluates the user's physical condition and environmental settings.

[0853] "Environmental adjustment means" refers to smart home appliances and control systems that automatically change indoor temperature, humidity, lighting, etc. based on analysis results.

[0854] "Encouragement message means" refers to a function or system that sends encouraging messages to increase the user's motivation.

[0855] "Store environment provision means" refers to systems and equipment for creating an optimal store environment based on the vital signs of store staff and customers.

[0856] "Smart equipment control means" refers to a system that automatically controls smart equipment such as air conditioners, humidifiers, and lighting based on vital sign data.

[0857] "Real-time transmission means" refers to a communication system for instantly sending support messages and notifications to customers and staff.

[0858] This invention is a system for collecting and analyzing vital signs of users, store staff, and customers to provide an optimal indoor environment. This system consists of a device for collecting vital signs, a server for transmitting and analyzing the data, smart equipment for adjusting the indoor environment, and a means for sending encouraging messages to users and staff. Below is a detailed explanation of how this system works.

[0859] The system consists of the following:

[0860] 1. Vital Signs Collection Device

[0861] Collect vital signs such as body temperature, heart rate, and blood pressure of users, staff, or customers using wearable devices such as smartwatches and audio glasses. The devices collect vital sign data in real time.

[0862] 2. Data Collection and Transfer

[0863] The collected vital sign data is sent to a server via smartphone, where it is encrypted and securely transmitted over the internet.

[0864] 3. Data analysis server

[0865] The server analyzes the received vital signs data and assesses the status of the user, staff, or customer. Machine learning algorithms (e.g., scikit-learn) are used to perform statistical analysis of the data.

[0866] 4. Decide on indoor environmental adjustments

[0867] Based on the server's analysis results, the optimal indoor environment settings are determined. Specifically, the air conditioner temperature is adjusted, the humidifier is activated, and the lighting is adjusted. This automatically optimizes temperature, humidity, and lighting intensity.

[0868] 5. Controlling smart equipment

[0869] The server then sends the determined environmental setting data to the smart equipment, adjusting the air conditioner, humidifier, lighting, etc., thereby optimizing the in-store environment in real time.

[0870] 6. Support message function

[0871] The server sends encouraging messages to users and staff using the "Ganbare Mode" function. This function is used to increase motivation and reduce stress for users and staff. The messages are displayed on smartwatches or smart glasses.

[0872] Specific examples

[0873] For example, consider a situation where there are a lot of customers during lunchtime and store staff are tired.

[0874] Hardware: Smartwatches, air conditioners, lighting, humidifiers

[0875] Software: Python, scikit-learn, IoT device control library

[0876] At this time, the smartwatch collects the staff member's body temperature (e.g., 37.5°C), heart rate (e.g., 80 BPM), and blood pressure (e.g., 130 / 85 mmHg), and sends this data to a server using a Python script. The server then analyzes the data using a machine learning algorithm using scikit-learn and determines that the staff member's physical condition is stressed. Based on the analysis results, an instruction is issued to change the air conditioner temperature from 24°C to 22°C, and at the same time, a cheering message saying "Do your best!" is displayed on the smartwatch every five seconds.

[0877] Prompt Sentence Examples

[0878] "For users whose body temperature exceeds 37.2 degrees, please lower the air conditioner temperature by 2 degrees. Also, please display a message of encouragement every 5 seconds."

[0879] This optimizes the store environment, allowing staff to continue working in a comfortable environment and improving customer satisfaction.

[0880] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0881] Step 1:

[0882] The user wears a vital sign collection device such as a smartwatch or audio glasses. This device acquires the user's vital signs, such as body temperature, heart rate, and blood pressure, in real time. The inputs are the user's body temperature (e.g., 36.8°C), heart rate (e.g., 72 BPM), and blood pressure (e.g., 120 / 80 mmHg), and these data are stored in the device as outputs.

[0883] Step 2:

[0884] The terminal sends the collected vital sign data to a server via the internet via the smartphone. The data is encrypted and transferred securely. The input is the vital sign data acquired from the smart device, and the output is the encrypted vital sign data sent to the server. Specifically, the smartphone receives data from the device using Bluetooth and sends the data to the server using the HTTPS protocol.

[0885] Step 3:

[0886] The server analyzes the received vital sign data and evaluates the user's physical condition. A Python machine learning library (e.g., scikit-learn) is used for the analysis, and statistical analysis of the data is performed. The input is the vital sign data sent to the server, and the output is the user's physical condition evaluation result. Specifically, the server runs an algorithm based on the temperature, heart rate, and blood pressure data to determine whether there are any abnormal values.

[0887] Step 4:

[0888] The server determines the optimal indoor environmental settings based on the analysis results. For example, if the body temperature exceeds 37.2 degrees, it will instruct the air conditioner to lower the temperature by 2 degrees. The input is the physical condition evaluation result, and the output is the environmental setting parameters (e.g., the air conditioner's set temperature). Specific operations involve determining the environmental adjustment parameters based on if statements and threshold setting rules.

[0889] Step 5:

[0890] The terminal controls smart equipment (e.g., air conditioners, humidifiers, and lighting) based on the environmental setting data received from the server. This automatically optimizes the temperature, humidity, and illuminance. The input is the environmental setting parameters from the server, and the output is the new settings for the air conditioner, humidifier, and lighting. Specifically, the terminal uses the IoT device control library to send commands to control each piece of equipment.

[0891] Step 6:

[0892] The server periodically sends cheering messages to users and staff using the "Go for it mode." For example, the message "Go for it!" is displayed every five seconds. The input is the cheering message data on the server, and the output is the message displayed on the smartwatch or smart glasses. Specifically, the server executes the message sending protocol using a periodic timer.

[0893] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0894] This invention is a system that collects and analyzes the user's vital signs in real time, and combines this with an emotion engine that recognizes the user's emotions to provide an optimal indoor environment. It can also send encouraging messages to the user through a "Go for it" mode to increase their motivation. An example of how this system can be implemented is shown below.

[0895] System Configuration

[0896] The system consists of the following main components:

[0897] 1. Vital Signs Collection Device

[0898] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[0899] 2. Emotion Recognition Engine

[0900] The device collects emotional data from the user through voice input and facial expression analysis. Voice input is analyzed through a microphone to capture the user's tone of voice and emotional state, while facial expression analysis is performed using a camera.

[0901] 3. Data Collection and Transfer

[0902] The device encrypts the collected vital sign and emotion data and transmits it to a server via the internet, using encryption protocols to ensure data transmission is secure.

[0903] 4. Data Analysis Server

[0904] The server analyzes the received vital sign data and emotion data to evaluate the user's physical and emotional state. The server can analyze the data using machine learning algorithms and perform statistical analysis.

[0905] 5. Smart appliances

[0906] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0907] 6. Support message function

[0908] The server uses the "Ganbare Mode" to send users cheering messages that change dynamically based on their emotional data. This feature was introduced to motivate users and help them maintain their concentration.

[0909] Program processing

[0910] 1. Data Collection

[0911] The terminal acquires vital sign data such as the user's body temperature, heart rate, and blood pressure from the wearable device. At the same time, it uses a microphone and camera to collect the user's emotional data. For example, if the user's body temperature is 36.8 degrees, the emotional state is recognized as "relaxed."

[0912] 2. Data Transmission

[0913] The device transmits the collected vital sign data and emotion data in real time to a server, where the data is securely stored.

[0914] 3. Data analysis

[0915] The server analyzes the received vital sign data and emotional data to evaluate the user's physical and emotional state. For example, if the body temperature is over 37.2 degrees and the emotional state is recognized as "stressed," the server adjusts the environmental settings to be more lenient.

[0916] 4. Determine your environment settings

[0917] The server then determines the optimal indoor environmental settings based on the analysis results, for example, setting the temperature between 24 and 22 degrees Celsius, maintaining humidity at 50%, and setting the illumination to 500 lux.

[0918] 5. Controlling smart appliances

[0919] The device adjusts the air conditioner, humidifier, and lighting based on the environmental setting data received from the server, allowing the user to work in a comfortable environment.

[0920] 6. Send a message of support

[0921] The server periodically sends encouraging messages based on the user's emotional data through the "Ganbare Mode." For example, the message "Ganbare!" is displayed every five seconds, or the message "Relax!" is displayed to motivate the user.

[0922] Specific examples

[0923] The user uses a system that combines a wearable device with an emotion recognition engine. The device collects vital signs and emotion data and sends this data to a server. If the server determines that the user's body temperature is 37.2 degrees and that the user is feeling stressed, it will operate the air conditioner to set the room temperature to 22 degrees, use a humidifier to keep the humidity at 50%, and adjust the lighting to 500 lux. At the same time, it sends a supportive message saying, "Relax!" This allows the user to continue working in a comfortable environment, maintaining their health and concentration.

[0924] The above is an embodiment of the present invention, which allows users to optimize their health and emotional state and perform at their best.

[0925] The processing flow will be explained below.

[0926] Step 1:

[0927] The device collects vital sign data, such as body temperature, heart rate, and blood pressure, in real time through wearable devices worn by the user, such as audio glasses or a smartwatch.

[0928] Step 2:

[0929] The device collects the user's voice input and facial expressions using a camera and microphone, and then uses an emotion recognition engine to analyze the user's emotional data, recognizing, for example, emotions such as joy, anger, sadness, and happiness.

[0930] Step 3:

[0931] The device encrypts the collected vital sign data and emotional data and transmits it to a server in real time via the Internet.

[0932] Step 4:

[0933] The server analyzes the received vital sign and emotion data using machine learning algorithms and statistical analysis tools to assess the user's physical and emotional state.

[0934] Step 5:

[0935] The server calculates the optimal room environment settings based on the analysis results. For example, if the user's body temperature exceeds 37.2 degrees Celsius or their emotional state is recognized as "stressed," the server will adjust the room temperature from 24 degrees Celsius to 22 degrees Celsius.

[0936] Step 6:

[0937] The server then transmits the determined environmental settings to the device, including parameters such as temperature, humidity, and illuminance.

[0938] Step 7:

[0939] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental settings received from the server, setting the room temperature to 22 degrees, humidity to 50%, and illuminance to 500 lux.

[0940] Step 8:

[0941] The server activates the "Go for it" mode and dynamically generates a supportive message based on the user's vital sign data and emotional data, and sends it to the device. For example, if the user is feeling stressed, the server sends a message saying, "Relax!"

[0942] Step 9:

[0943] The device displays the cheering message received from the server to the user, allowing the user to receive a motivational message at an appropriate time.

[0944] Step 10:

[0945] The terminal repeats the processes from step 1 to step 9 at regular time intervals, for example, every 30 seconds.

[0946] Step 11:

[0947] Users continue working while receiving regular, optimized environments and encouraging messages, which help them optimize their health and emotional state and perform at their best.

[0948] Example 2

[0949] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0950] In modern society, users are constantly exposed to stress, which can lead to deterioration in their health. It is difficult for users to manually adjust their indoor environment to create an optimal one. Furthermore, it is necessary to adjust the environment to respond to emotional changes and improve motivation. However, existing systems lack the ability to analyze a user's vital signs and emotional state in real time, adjust the indoor environment accordingly, or generate and send personalized support messages.

[0951] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0952] In this invention, the server includes means for collecting the user's vital signs, means for analyzing the collected vital sign data and emotional data, means for adjusting the indoor environment based on the analysis results, and means for sending a cheering message using a generative AI model based on the user's emotional state. This allows the user to optimize both their health and emotional state in real time, enabling them to perform at a high level in a comfortable environment.

[0953] "User" refers to an individual who uses this system.

[0954] "Vital signs" refers to basic vital indicators of the human body, such as body temperature, heart rate, and blood pressure.

[0955] "Data" refers to vital signs and emotional information collected from sensors and devices.

[0956] "Emotional data" refers to information about the user's emotional state obtained from voice input and facial expression analysis.

[0957] "Collection means" refers to the devices and methods for acquiring vital signs and emotional data using wearable devices and sensors.

[0958] "Analysis means" refers to algorithms or software that analyze the collected data and assess the user's physical and emotional state.

[0959] "Adjustment means" refers to a device or method that automatically adjusts the indoor temperature, humidity, illuminance, etc. based on the analysis results.

[0960] "Generative AI model" refers to an artificial intelligence model that dynamically generates cheering messages based on the user's emotional state.

[0961] "Support messages" refer to text that encourages or motivates users to increase their motivation.

[0962] MODE FOR CARRYING OUT THE INVENTION

[0963] This invention is a system that collects and analyzes a user's vital signs in real time, and integrates a means of recognizing the user's emotions to provide an optimal indoor environment. Furthermore, through the "Go for it" mode, a generative AI model can be used to send encouraging messages based on the user's emotional state, increasing the user's motivation. An example of how this system can be implemented is shown below.

[0964] System Configuration

[0965] The system consists of the following main components:

[0966] 1. Vital Signs Collection Device

[0967] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[0968] 2. Emotion Recognition Engine

[0969] The device collects emotional data from the user through voice input and facial expression analysis. Voice input is analyzed through a microphone to capture the user's tone of voice and emotional state, while facial expression analysis is performed using a camera.

[0970] 3. Data Collection and Transfer

[0971] The device encrypts the collected vital sign and emotion data and sends it to a server via the Internet, using the TLS / SSL protocol to ensure secure data transfer.

[0972] 4. Data Analysis Server

[0973] The server analyzes the received vital sign data and emotion data to evaluate the user's physical and emotional state. The server can analyze the data using machine learning algorithms (e.g., TensorFlow and scikit-learn) and perform statistical analysis.

[0974] 5. Smart appliances

[0975] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[0976] 6. Support message function

[0977] The server uses "Go for it" mode to send dynamically changing cheering messages to users based on their emotional data. Prompts for the generative AI model (e.g., GPT-3) include, "The user's body temperature is 37.2 degrees and their emotional state is stressed. Please tell me what kind of cheering message would be appropriate in this case."

[0978] Specific examples

[0979] The user wears audio glasses and a smartwatch. The device captures the user's body temperature and heart rate in real time, and also collects emotional data (e.g., "stress" state) via a microphone and camera. This data is encrypted and sent to a server.

[0980] The server analyzes this data and evaluates the user's health condition. For example, if the server determines that the user's body temperature is 37.2 degrees, indicating stress, it will operate the air conditioner to set the room temperature to 22 degrees, use a humidifier to keep the humidity at 50%, and adjust the lighting to 500 lux. At the same time, it will use a generative AI model to generate a supportive message such as "Relax!" and send it to the device.

[0981] Based on this, the device will set the air conditioner to 22 degrees, adjust the humidifier to 50% humidity, and display a message to the user saying "Relax!", allowing the user to continue working in a comfortable environment, maintaining their health and concentration.

[0982] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0983] Step 1:

[0984] Data collection

[0985] The device acquires vital sign data such as the user's body temperature, heart rate, and blood pressure using sensors in wearable devices (audio glasses or smartwatches). For example, the device reads the body temperature and heart rate from the sensors every second.

[0986] The device uses a microphone to pick up the user's tone of voice and emotional state and saves the audio data. It also uses a camera to capture the user's facial expressions and performs real-time emotion analysis. For example, it uses facial recognition technology to distinguish between smiling and angry expressions.

[0987] Input: Vital sign data from sensors, audio data from microphones, video data from cameras

[0988] Output: Collected vital sign data and emotional data (voice analysis results and facial expression analysis results)

[0989] Step 2:

[0990] Data transmission

[0991] The device encrypts the collected vital sign and emotion data in real time and transmits it to a server over the Internet using the TLS / SSL protocol via HTTPS. For example, the data is sent in packets every 10 seconds.

[0992] Input: Collected vital signs and emotion data

[0993] Output: Encrypted data sent to the server

[0994] Step 3:

[0995] Data analysis

[0996] The server analyzes the received vital sign data and emotion data. The received data is stored in a database and a dedicated analysis algorithm (e.g., TensorFlow, scikit-learn) is used for analysis. The data is preprocessed and inconsistencies are removed before it is used for analysis.

[0997] The server evaluates the user's health condition (hyperthermia, normal body temperature, etc.) and emotional state (relaxed, stressed, etc.) based on the analysis results. For example, if the body temperature is 37.2 degrees and the emotional state is determined to be stressed, it will determine that relaxation is necessary.

[0998] Input: Encrypted data sent to the server

[0999] Output: Assessment of health and emotional state based on analyzed vital signs and emotion data.

[1000] Step 4:

[1001] Determining your environment settings

[1002] The server then recommends the optimal indoor environment based on the analysis results. For example, if a user has a body temperature of 37.2 degrees and is in a state of stress, it will recommend setting the air conditioner to 22 degrees and the humidifier to 50% humidity. The settings are determined taking into account past data and weather data.

[1003] Input: Analyzed health and emotional state ratings

[1004] Output: Recommended indoor environment setting data

[1005] Step 5:

[1006] Smart home appliance control

[1007] The terminal controls smart home appliances in the room based on the environmental setting data sent from the server, for example, sending control commands to set the air conditioner to 22 degrees and the humidifier to 50% humidity.

[1008] The terminal checks whether the sent control command was successful and reports success or failure to the server. For example, it sends a command via an API for air conditioner settings and checks whether the setting was successful.

[1009] Input: Preference data sent from the server

[1010] Output: Controlled smart appliances and confirmation of successful control

[1011] Step 6:

[1012] Send a message of support

[1013] The server activates the "Go for it" mode and uses a generative AI model (e.g., GPT-3) to create a cheering message based on the user's emotional data. The prompt used is, "The user's body temperature is 37.2 degrees and their emotional state is stressed. In this case, please tell us what kind of cheering message would be appropriate."

[1014] The server sends the generated cheer message to the device, which then displays it to the user. For example, an automatically generated message like "Relax!" is displayed as a pop-up every five minutes.

[1015] Input: User emotion data and prompt sentence

[1016] Output: Generated cheer message and its display

[1017] (Application example 2)

[1018] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1019] This invention relates to a system that collects and analyzes a user's biosignals and emotional data in real time and provides an optimal environment based on this data. However, conventional systems have insufficient means for ensuring user safety and are unable to respond appropriately when the user experiences stress or abnormalities in their biosignals. Therefore, a system is needed that uses a user's biosignals and emotional data to instantly assess security risks and send appropriate warnings and emergency notifications.

[1020] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting biosignal and emotional data of the user, means for analyzing the collected biosignal and emotional data, means for adjusting the environment based on the analysis results, means for sending a cheering message to motivate the user, means for assessing security risks using the biosignal and emotional data of the user, and means for issuing an alert and sending an emergency notification when a risk is detected. This not only optimizes the user's health and emotional state and enables high performance, but also makes it possible to ensure the user's safety in real time and respond quickly to emergencies.

[1021] "User" means an individual using the System.

[1022] "Biological signals" refer to data that indicates the state of the body, such as body temperature, heart rate, and blood pressure.

[1023] "Emotional data" refers to data that indicates the user's emotional state through voice and facial expression analysis.

[1024] "Analysis" refers to the process of evaluating and interpreting collected biosignal and emotional data.

[1025] "Environmental adjustment" refers to the operation of optimizing the indoor environment, such as temperature, humidity, and lighting, based on the analysis results.

[1026] "Motivation" refers to efforts to increase the user's motivation and enthusiasm.

[1027] A "support message" refers to words of encouragement or instructions sent to motivate a user.

[1028] "Security risk" refers to a potential threat or danger to the safety of a user.

[1029] "Warning" refers to a notification sent to users and other relevant parties when a danger or abnormality is detected.

[1030] "Emergency notifications" refer to alerts or messages sent immediately when an abnormality occurs.

[1031] This invention is a real-time security risk assessment system that collects and analyzes a user's biometric and emotional data to ensure their safety. This system shares data with smart glasses, a server, and the Internet, and can adjust the environment as needed, issue warnings, and send emergency notifications according to the user's situation. The specific configuration and operation of this system are described below.

[1032] System Configuration Overview

[1033] Hardware

[1034] 1. Smart Glasses

[1035] Camera: Records the user's facial expressions in real time and collects emotional data.

[1036] Microphone: Records the user's voice and provides data for emotional analysis.

[1037] Various sensors: Measure vital signs such as body temperature, heart rate, and blood pressure.

[1038] 2. Server

[1039] Data analysis engine: Analyzes collected bio-signals and emotional data to assess the user's condition.

[1040] Machine learning algorithms: Machine learning algorithms are used to generate accurate analysis results from biometric and emotional data.

[1041] Cheer message generation module: Generates cheer messages according to the situation.

[1042] software

[1043] Python program: The main program for data collection, data transmission, and security risk assessment.

[1044] Rest API: A standard API for communicating with the server.

[1045] Encryption protocol: Encrypts data to ensure security during transmission.

[1046] Process Details

[1047] The server receives data sent from the smart glasses. The smart glasses use a camera, microphone, and various sensors to collect the user's biometric and emotional data. The collected data is sent to the server in real time and analyzed using machine learning algorithms. Based on the analysis results, the server evaluates the user's current health and emotional state.

[1048] Based on the evaluation results, the server can issue instructions to adjust the indoor environment. For example, if a user's body temperature is rising, the server can lower the air conditioner temperature setting or adjust the lighting. If the user is feeling stressed, the server can also send a message of encouragement such as "Relax!"

[1049] It also assesses security risks based on the user's health and emotional state: if the user is stressed and has a high body temperature, for example, the system will issue an alert, adjust the environment as needed, and send an emergency notification to security staff.

[1050] Specific examples

[1051] For example, when a user is wearing smart glasses, if the system detects a body temperature of 37.3 degrees, a heart rate of 90, a blood pressure of 120 / 80, and an emotional state of "stress," it will lower the air conditioning temperature setting, display a supportive message saying "Relax!", and automatically send an emergency notification to security staff.

[1052] Example prompt sentence:

[1053] "Temperature is 37.3°C, emotional state is recognized as 'stressed'. These are abnormal values. Please implement emergency response."

[1054] This allows the system to optimize the user's health and emotional state, providing a comfortable and safe environment for the user.

[1055] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1056] Step 1:

[1057] The device uses the camera, microphone, and various sensors in the smart glasses to collect the user's biometric signals (body temperature, heart rate, blood pressure) and emotional data (facial expressions, voice). Specific data collected includes a body temperature of 36.8 degrees, a heart rate of 85, and an emotional state of "relaxed."

[1058] Step 2:

[1059] The device transmits the collected biometric and emotional data to a server in real time. The data is encrypted using an encryption protocol to ensure security. Input data includes body temperature, heart rate, and emotional state.

[1060] Step 3:

[1061] The server analyzes the received biometric and emotional data. It uses machine learning algorithms to evaluate the data and determine the user's current health and emotional state. For example, if the body temperature is 37.2 degrees and the emotional state is "stressed," the user is diagnosed with high stress. The input data is analyzed, and the user's health and emotional state are obtained as outputs.

[1062] Step 4:

[1063] The server then adjusts the environment based on the analysis results. For example, it may change the air conditioner's temperature setting from 24 degrees to 22 degrees and adjust the lighting brightness to 500 lux. The analysis results are used as input for this process, and environmental setting data (temperature, illuminance, etc.) is obtained as output.

[1064] Step 5:

[1065] The device controls smart home appliances such as air conditioners and lighting based on the configuration data received from the server. The device receives the configuration data as input and executes specific home appliance control commands (such as changing the temperature setting of the air conditioner or adjusting the brightness of the lights) as output.

[1066] Step 6:

[1067] The server uses a "Ganbare Mode" to send encouraging messages to motivate the user. For example, if the user is feeling stressed, the server sends a message saying "Relax!". This process uses emotional state data as input, and generates and sends encouraging messages as output.

[1068] Step 7:

[1069] The server evaluates the security risk based on the user's health and emotional state. If the user's body temperature rises and the emotional state is judged to be "stressed," it issues an alert and sends an emergency notification to security staff. The input to this process is the health and emotional state data, and the output is a warning message and an emergency notification.

[1070] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1071] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1072] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1073] [Fourth embodiment]

[1074] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1075] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1076] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1077] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1078] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1079] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1080] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1081] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1082] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1083] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1084] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1085] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1086] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1087] The present invention is a system that collects and analyzes a user's vital signs and works with smart home appliances to provide an optimal indoor environment. Furthermore, a "Go for it" mode can send encouraging messages to the user, increasing their motivation. An example of how to specifically implement the present invention is shown below.

[1088] System Configuration

[1089] The system consists of the following main components:

[1090] 1. Vital Signs Collection Device

[1091] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[1092] 2. Data Collection and Transfer

[1093] The device sends the collected vital sign data to a server, where it is encrypted and transmitted over the internet.

[1094] 3. Data analysis server

[1095] The server analyzes the received vital sign data and calculates the optimal settings for the user's physical condition and indoor environment. The server can analyze the data using machine learning algorithms and perform statistical analysis.

[1096] 4. Smart appliances

[1097] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[1098] 5. Support message function

[1099] The server periodically sends encouraging messages to users using the "Ganbare Mode" function, which is introduced to motivate users and keep them focused.

[1100] Program processing

[1101] 1. Data Collection

[1102] The terminal acquires vital sign data such as the user's body temperature, heart rate, blood pressure, etc. from the wearable device. For example, suppose the user's current body temperature is 36.8 degrees, heart rate is 72 BPM, and blood pressure is 120 / 80 mmHg.

[1103] 2. Data Transmission

[1104] The device transmits the collected data in real time to a server, where it is securely stored.

[1105] 3. Data analysis

[1106] The server analyzes the received vital sign data and evaluates the user's physical condition. For example, if the body temperature exceeds 37.2 degrees, it determines that the user's physical condition is unstable and sets the room temperature to be lowered by 2 degrees.

[1107] 4. Determine your environment settings

[1108] The server then determines the optimal indoor environmental settings based on the analysis results, for example, setting the temperature between 24 and 22 degrees Celsius, maintaining humidity at 50%, and setting the illumination to 500 lux.

[1109] 5. Controlling smart appliances

[1110] The device adjusts the air conditioner, humidifier, and lighting based on the environmental setting data received from the server, allowing the user to work in a comfortable environment.

[1111] 6. Send a message of support

[1112] The server periodically sends encouraging messages to the user through the "Ganbare Mode." For example, the message "Ganbare!" is displayed every 5 seconds to motivate the user.

[1113] Specific examples

[1114] The user puts on the wearable device and begins collecting vital signs. The device sends the data to a server, which then dynamically analyzes it. For example, if the user's body temperature rises, the server will issue a command to lower the air conditioner temperature. At the same time, the server will activate the "Go for it" mode and display a message of encouragement saying "Go for it!" This allows the user to continue working in an optimal environment while maintaining high motivation.

[1115] The above is an embodiment of the present invention. This system allows users to effectively concentrate on their work while maintaining their health, thereby maximizing performance.

[1116] The processing flow will be explained below.

[1117] Step 1:

[1118] The device collects vital sign data, such as body temperature, heart rate, and blood pressure, in real time through wearable devices worn by the user, such as audio glasses or a smartwatch.

[1119] Step 2:

[1120] The device encrypts the collected vital signs data and sends it to a server over the internet, using encryption protocols to ensure secure data transfer.

[1121] Step 3:

[1122] The server analyzes the received vital sign data using machine learning algorithms and statistical analysis tools to assess the user's physical condition.

[1123] Step 4:

[1124] The server then calculates the optimal indoor environment settings based on the analysis results. For example, if the user's body temperature is above 37.2 degrees, the room temperature will be lowered from 24 degrees to 22 degrees.

[1125] Step 5:

[1126] The server then transmits the determined environmental settings to the device, including parameters such as temperature, humidity, and illuminance.

[1127] Step 6:

[1128] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental settings received from the server, setting the room temperature to 22 degrees, humidity to 50%, and illuminance to 500 lux.

[1129] Step 7:

[1130] The server activates the "Ganbare mode" and periodically sends a cheering message to the user. For example, the server sends the message "Ganbare!" to the terminal every 5 seconds.

[1131] Step 8:

[1132] The device displays the support message received from the server to the user, which increases the user's motivation and improves work efficiency.

[1133] Step 9:

[1134] The terminal repeats the processes from step 1 to step 8 at regular time intervals, for example, every 30 seconds.

[1135] Step 10:

[1136] Users continue working while receiving regular, optimized environments and encouraging messages, helping them maintain their health and perform at their best.

[1137] Example 1

[1138] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1139] In today's busy living environment, it is difficult for users to maintain a comfortable indoor environment while properly managing their own health. Furthermore, there are few ways to motivate users, making it difficult to improve work efficiency and quality of life. In particular, there is a lack of systems that can quickly adjust the environment in response to changes in health status and provide accurate advice based on the user's physical condition.

[1140] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1141] In this invention, the server includes means for collecting physical information of the user, means for analyzing the collected physical information, means for adjusting the indoor environment based on the analysis results, and means for sending encouraging messages to motivate the user. This makes it possible to monitor the user's health condition in real time, create an optimal indoor environment, and increase the user's motivation.

[1142] "User" means an individual using the System.

[1143] "Physical information" refers to biometric data including vital sign data such as the user's body temperature, heart rate, and blood pressure.

[1144] "Means of collection" refers to the function of obtaining the user's physical information in real time using wearable devices and sensors.

[1145] "Means for analyzing" refers to a processing device or software for analyzing the collected physical information and assessing the user's health status and changes therein.

[1146] "Adjusting means" refers to equipment or devices that automatically change indoor environmental parameters such as temperature, humidity, and illuminance based on the analysis results.

[1147] The "means for sending a cheering message to motivate" refers to a function for displaying or notifying a cheering message by voice to increase the motivation of the user.

[1148] "Certain conditions" refers to a state in which the user's physical information satisfies a predetermined standard or range.

[1149] "Means for suggesting break times and hydration" refers to a function for recommending appropriate breaks and hydration based on the user's physical condition.

[1150] "Real-time monitoring" refers to continuously acquiring the user's physical information and immediately reflecting it.

[1151] "Means for automatic adjustment" refers to a system for changing the indoor environment in response to the user's physical information without manual intervention.

[1152] The present invention is a system that collects and analyzes a user's physical information and works in conjunction with smart home appliances to provide an optimal indoor environment. Furthermore, a "Go for it" mode can be used to send encouraging messages to the user, increasing their motivation. An example of a specific implementation of the present invention is shown below.

[1153] System Configuration

[1154] The system consists of the following main components:

[1155] 1. Physical information collection devices

[1156] The device collects the user's physical information using wearable devices such as audio glasses and smartwatches, which collect data such as body temperature, heart rate, and blood pressure in real time.

[1157] 2. Data Collection and Transfer

[1158] The device sends the collected physiological data to a server, where it is encrypted and transmitted over the internet.

[1159] 3. Data analysis server

[1160] The server analyzes the received physiological data and calculates the optimal settings for the user's physical condition and indoor environment. The server can analyze the data using machine learning algorithms and perform statistical analysis, specifically using software such as Python's Scikit-learn and TensorFlow.

[1161] 4. Smart appliances

[1162] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[1163] 5. Support message function

[1164] The server periodically sends encouraging messages to users using the "Ganbare Mode" feature, which is introduced to motivate users and keep them focused.

[1165] Specific examples

[1166] The user puts on the wearable device and begins collecting physical information. The device sends the data to a server, which then dynamically analyzes it. For example, if the user's body temperature rises, the server will issue a command to lower the air conditioner temperature. At the same time, the server will activate a "go for it" mode and display a message of encouragement saying, "Take it easy today, relax." This allows the user to continue working in an optimal environment while maintaining high motivation.

[1167] Prompt Sentence Examples

[1168] Examples of prompts to be input to a generative AI model include:

[1169] "Please suggest optimal temperature and humidity settings for the room based on body temperature and heart rate data collected from the user's smartwatch."

[1170] "Please explain what indoor environmental settings should be made when the user's physical condition is unstable, including specific temperature, humidity, and illuminance."

[1171] "Please provide five specific motivational and encouraging messages for users who are feeling unwell."

[1172] The above is an embodiment of the present invention. This system allows users to effectively concentrate on their work while maintaining their health, thereby maximizing performance.

[1173] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1174] Step 1:

[1175] Data collection

[1176] The terminal acquires the user's physical information (body temperature, heart rate, blood pressure, etc.) in real time from wearable devices such as audio glasses or smartwatches. Sensors in the devices measure body temperature and heart rate and transmit the data to the terminal. The input is the user's current biometric data, and the output is the collected vital sign data.

[1177] Step 2:

[1178] Data transmission

[1179] The device sends the collected physiological data to a server via the Internet. The data is encrypted and securely transferred. The input is the collected vital sign data, and the output is the received vital sign data, which is stored on the server.

[1180] Step 3:

[1181] Data storage

[1182] The server stores the received physiological data in a database, for example, an SQL database or a NoSQL database. The input is the received vital sign data, and the output is the data stored in an organized manner in the database. The stored data is organized by date and time, making it easy to search.

[1183] Step 4:

[1184] Data analysis

[1185] The server analyzes the stored vital sign data and uses machine learning algorithms to evaluate the user's physical condition. For example, it uses Python's Scikit-learn or TensorFlow to analyze data from the past week. The input is the vital sign data stored in the database, and the output is the analysis results regarding the user's health condition.

[1186] Step 5:

[1187] Determining your environment settings

[1188] The server determines the optimal indoor environment settings based on the analysis results. For example, if the body temperature exceeds 37.2 degrees, the room temperature will be lowered by 2 degrees. The input is the health status analysis result, and the output is the specific indoor environment setting parameters (temperature, humidity, illuminance, etc.).

[1189] Step 6:

[1190] Smart home appliance control

[1191] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental setting data received from the server. For example, the device changes the temperature setting of an air conditioner from 24 degrees to 22 degrees and sets the humidity to 50%. The input is the environmental setting data from the server, and the output is the adjusted indoor environment.

[1192] Step 7:

[1193] Send a message of support

[1194] The server periodically sends encouraging messages to the user through the "Ganbare Mode." For example, the message "Take it easy today, relax!" is displayed every hour. The input is data about the user's health status and a template message to improve motivation, and the output is the display or audio notification of the encouraging message to the user.

[1195] The above are the specific processing steps of the program of this system.

[1196] (Application example 1)

[1197] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1198] Currently, it is difficult to provide an optimal environment based on the health status of staff and customers in stores. It is also difficult to maintain staff motivation, especially during busy times. This leads to poor staff efficiency and lower customer satisfaction. Additionally, there is a lack of systems that can analyze vital sign data in real time and automatically adjust the store environment based on that data.

[1199] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1200] In this invention, the server includes means for collecting users' vital signs, means for analyzing the collected vital sign data, means for adjusting the indoor environment based on the analysis results, means for sending cheering messages to motivate users, means for collecting vital signs of store staff and customers and providing an optimal store environment, means for automatically controlling smart equipment using the vital sign data, and means for sending cheering messages to staff and customers in real time. This makes it possible to optimize the in-store environment, maintain the health and motivation of staff, and improve customer satisfaction.

[1201] "Vital signs" refers to basic biological information such as body temperature, heart rate, and blood pressure.

[1202] "Collection methods" refers to devices and systems used to obtain vital signs of users, staff, or customers.

[1203] "Analysis means" refers to a server or software that analyzes collected vital sign data and evaluates the user's physical condition and environmental settings.

[1204] "Environmental adjustment means" refers to smart home appliances and control systems that automatically change indoor temperature, humidity, lighting, etc. based on analysis results.

[1205] "Encouragement message means" refers to a function or system that sends encouraging messages to increase the user's motivation.

[1206] "Store environment provision means" refers to systems and equipment for creating an optimal store environment based on the vital signs of store staff and customers.

[1207] "Smart equipment control means" refers to a system that automatically controls smart equipment such as air conditioners, humidifiers, and lighting based on vital sign data.

[1208] "Real-time transmission means" refers to a communication system for instantly sending support messages and notifications to customers and staff.

[1209] This invention is a system for collecting and analyzing vital signs of users, store staff, and customers to provide an optimal indoor environment. This system consists of a device for collecting vital signs, a server for transmitting and analyzing the data, smart equipment for adjusting the indoor environment, and a means for sending encouraging messages to users and staff. Below is a detailed explanation of how this system works.

[1210] The system consists of the following:

[1211] 1. Vital Signs Collection Device

[1212] Collect vital signs such as body temperature, heart rate, and blood pressure of users, staff, or customers using wearable devices such as smartwatches and audio glasses. The devices collect vital sign data in real time.

[1213] 2. Data Collection and Transfer

[1214] The collected vital sign data is sent to a server via smartphone, where it is encrypted and securely transmitted over the internet.

[1215] 3. Data analysis server

[1216] The server analyzes the received vital signs data and assesses the status of the user, staff, or customer. Machine learning algorithms (e.g., scikit-learn) are used to perform statistical analysis of the data.

[1217] 4. Decide on indoor environmental adjustments

[1218] Based on the server's analysis results, the optimal indoor environment settings are determined. Specifically, the air conditioner temperature is adjusted, the humidifier is activated, and the lighting is adjusted. This automatically optimizes temperature, humidity, and lighting intensity.

[1219] 5. Controlling smart equipment

[1220] The server then sends the determined environmental setting data to the smart equipment, adjusting the air conditioner, humidifier, lighting, etc., thereby optimizing the in-store environment in real time.

[1221] 6. Support message function

[1222] The server sends encouraging messages to users and staff using the "Ganbare Mode" function. This function is used to increase motivation and reduce stress for users and staff. The messages are displayed on smartwatches or smart glasses.

[1223] Specific examples

[1224] For example, consider a situation where there are a lot of customers during lunchtime and store staff are tired.

[1225] Hardware: Smartwatches, air conditioners, lighting, humidifiers

[1226] Software: Python, scikit-learn, IoT device control library

[1227] At this time, the smartwatch collects the staff member's body temperature (e.g., 37.5°C), heart rate (e.g., 80 BPM), and blood pressure (e.g., 130 / 85 mmHg), and sends this data to a server using a Python script. The server then analyzes the data using a machine learning algorithm using scikit-learn and determines that the staff member's physical condition is stressed. Based on the analysis results, an instruction is issued to change the air conditioner temperature from 24°C to 22°C, and at the same time, a cheering message saying "Do your best!" is displayed on the smartwatch every five seconds.

[1228] Prompt Sentence Examples

[1229] "For users whose body temperature exceeds 37.2 degrees, please lower the air conditioner temperature by 2 degrees. Also, please display a message of encouragement every 5 seconds."

[1230] This optimizes the store environment, allowing staff to continue working in a comfortable environment and improving customer satisfaction.

[1231] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1232] Step 1:

[1233] The user wears a vital sign collection device such as a smartwatch or audio glasses. This device acquires the user's vital signs, such as body temperature, heart rate, and blood pressure, in real time. The inputs are the user's body temperature (e.g., 36.8°C), heart rate (e.g., 72 BPM), and blood pressure (e.g., 120 / 80 mmHg), and these data are stored in the device as outputs.

[1234] Step 2:

[1235] The terminal sends the collected vital sign data to a server via the internet via the smartphone. The data is encrypted and transferred securely. The input is the vital sign data acquired from the smart device, and the output is the encrypted vital sign data sent to the server. Specifically, the smartphone receives data from the device using Bluetooth and sends the data to the server using the HTTPS protocol.

[1236] Step 3:

[1237] The server analyzes the received vital sign data and evaluates the user's physical condition. A Python machine learning library (e.g., scikit-learn) is used for the analysis, and statistical analysis of the data is performed. The input is the vital sign data sent to the server, and the output is the user's physical condition evaluation result. Specifically, the server runs an algorithm based on the temperature, heart rate, and blood pressure data to determine whether there are any abnormal values.

[1238] Step 4:

[1239] The server determines the optimal indoor environmental settings based on the analysis results. For example, if the body temperature exceeds 37.2 degrees, it will instruct the air conditioner to lower the temperature by 2 degrees. The input is the physical condition evaluation result, and the output is the environmental setting parameters (e.g., the air conditioner's set temperature). Specific operations involve determining the environmental adjustment parameters based on if statements and threshold setting rules.

[1240] Step 5:

[1241] The terminal controls smart equipment (e.g., air conditioners, humidifiers, and lighting) based on the environmental setting data received from the server. This automatically optimizes the temperature, humidity, and illuminance. The input is the environmental setting parameters from the server, and the output is the new settings for the air conditioner, humidifier, and lighting. Specifically, the terminal uses the IoT device control library to send commands to control each piece of equipment.

[1242] Step 6:

[1243] The server periodically sends cheering messages to users and staff using the "Go for it mode." For example, the message "Go for it!" is displayed every five seconds. The input is the cheering message data on the server, and the output is the message displayed on the smartwatch or smart glasses. Specifically, the server executes the message sending protocol using a periodic timer.

[1244] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1245] This invention is a system that collects and analyzes the user's vital signs in real time, and combines this with an emotion engine that recognizes the user's emotions to provide an optimal indoor environment. It can also send encouraging messages to the user through a "Go for it" mode to increase their motivation. An example of how this system can be implemented is shown below.

[1246] System Configuration

[1247] The system consists of the following main components:

[1248] 1. Vital Signs Collection Device

[1249] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[1250] 2. Emotion Recognition Engine

[1251] The device collects emotional data from the user through voice input and facial expression analysis. Voice input is analyzed through a microphone to capture the user's tone of voice and emotional state, while facial expression analysis is performed using a camera.

[1252] 3. Data Collection and Transfer

[1253] The device encrypts the collected vital sign and emotion data and transmits it to a server via the internet, using encryption protocols to ensure data transmission is secure.

[1254] 4. Data Analysis Server

[1255] The server analyzes the received vital sign data and emotion data to evaluate the user's physical and emotional state. The server can analyze the data using machine learning algorithms and perform statistical analysis.

[1256] 5. Smart appliances

[1257] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[1258] 6. Support message function

[1259] The server uses the "Ganbare Mode" to send users cheering messages that change dynamically based on their emotional data. This feature was introduced to motivate users and help them maintain their concentration.

[1260] Program processing

[1261] 1. Data Collection

[1262] The terminal acquires vital sign data such as the user's body temperature, heart rate, and blood pressure from the wearable device. At the same time, it uses a microphone and camera to collect the user's emotional data. For example, if the user's body temperature is 36.8 degrees, the emotional state is recognized as "relaxed."

[1263] 2. Data Transmission

[1264] The device transmits the collected vital sign data and emotion data in real time to a server, where the data is securely stored.

[1265] 3. Data analysis

[1266] The server analyzes the received vital sign data and emotional data to evaluate the user's physical and emotional state. For example, if the body temperature is over 37.2 degrees and the emotional state is recognized as "stressed," the server adjusts the environmental settings to be more lenient.

[1267] 4. Determine your environment settings

[1268] The server then determines the optimal indoor environmental settings based on the analysis results, for example, setting the temperature between 24 and 22 degrees Celsius, maintaining humidity at 50%, and setting the illumination to 500 lux.

[1269] 5. Controlling smart appliances

[1270] The device adjusts the air conditioner, humidifier, and lighting based on the environmental setting data received from the server, allowing the user to work in a comfortable environment.

[1271] 6. Send a message of support

[1272] The server periodically sends encouraging messages based on the user's emotional data through the "Ganbare Mode." For example, the message "Ganbare!" is displayed every five seconds, or the message "Relax!" is displayed to motivate the user.

[1273] Specific examples

[1274] The user uses a system that combines a wearable device with an emotion recognition engine. The device collects vital signs and emotion data and sends this data to a server. If the server determines that the user's body temperature is 37.2 degrees and that the user is feeling stressed, it will operate the air conditioner to set the room temperature to 22 degrees, use a humidifier to keep the humidity at 50%, and adjust the lighting to 500 lux. At the same time, it sends a supportive message saying, "Relax!" This allows the user to continue working in a comfortable environment, maintaining their health and concentration.

[1275] The above is an embodiment of the present invention, which allows users to optimize their health and emotional state and perform at their best.

[1276] The processing flow will be explained below.

[1277] Step 1:

[1278] The device collects vital sign data, such as body temperature, heart rate, and blood pressure, in real time through wearable devices worn by the user, such as audio glasses or a smartwatch.

[1279] Step 2:

[1280] The device collects the user's voice input and facial expressions using a camera and microphone, and then uses an emotion recognition engine to analyze the user's emotional data, recognizing, for example, emotions such as joy, anger, sadness, and happiness.

[1281] Step 3:

[1282] The device encrypts the collected vital sign data and emotional data and transmits it to a server in real time via the Internet.

[1283] Step 4:

[1284] The server analyzes the received vital sign and emotion data using machine learning algorithms and statistical analysis tools to assess the user's physical and emotional state.

[1285] Step 5:

[1286] The server calculates the optimal room environment settings based on the analysis results. For example, if the user's body temperature exceeds 37.2 degrees Celsius or their emotional state is recognized as "stressed," the server will adjust the room temperature from 24 degrees Celsius to 22 degrees Celsius.

[1287] Step 6:

[1288] The server then transmits the determined environmental settings to the device, including parameters such as temperature, humidity, and illuminance.

[1289] Step 7:

[1290] The device controls smart home appliances such as air conditioners, humidifiers, and lighting based on the environmental settings received from the server, setting the room temperature to 22 degrees, humidity to 50%, and illuminance to 500 lux.

[1291] Step 8:

[1292] The server activates the "Go for it" mode and dynamically generates a supportive message based on the user's vital sign data and emotional data, and sends it to the device. For example, if the user is feeling stressed, the server sends a message saying, "Relax!"

[1293] Step 9:

[1294] The device displays the cheering message received from the server to the user, allowing the user to receive a motivational message at an appropriate time.

[1295] Step 10:

[1296] The terminal repeats the processes from step 1 to step 9 at regular time intervals, for example, every 30 seconds.

[1297] Step 11:

[1298] Users continue working while receiving regular, optimized environments and encouraging messages, which help them optimize their health and emotional state and perform at their best.

[1299] Example 2

[1300] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1301] In modern society, users are constantly exposed to stress, which can lead to deterioration in their health. It is difficult for users to manually adjust their indoor environment to create an optimal one. Furthermore, it is necessary to adjust the environment to respond to emotional changes and improve motivation. However, existing systems lack the ability to analyze a user's vital signs and emotional state in real time, adjust the indoor environment accordingly, or generate and send personalized support messages.

[1302] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1303] In this invention, the server includes means for collecting the user's vital signs, means for analyzing the collected vital sign data and emotional data, means for adjusting the indoor environment based on the analysis results, and means for sending a cheering message using a generative AI model based on the user's emotional state. This allows the user to optimize both their health and emotional state in real time, enabling them to perform at a high level in a comfortable environment.

[1304] "User" refers to an individual who uses this system.

[1305] "Vital signs" refers to basic vital indicators of the human body, such as body temperature, heart rate, and blood pressure.

[1306] "Data" refers to vital signs and emotional information collected from sensors and devices.

[1307] "Emotional data" refers to information about the user's emotional state obtained from voice input and facial expression analysis.

[1308] "Collection means" refers to the devices and methods for acquiring vital signs and emotional data using wearable devices and sensors.

[1309] "Analysis means" refers to algorithms or software that analyze the collected data and assess the user's physical and emotional state.

[1310] "Adjustment means" refers to a device or method that automatically adjusts the indoor temperature, humidity, illuminance, etc. based on the analysis results.

[1311] "Generative AI model" refers to an artificial intelligence model that dynamically generates cheering messages based on the user's emotional state.

[1312] "Support messages" refer to text that encourages or motivates users to increase their motivation.

[1313] MODE FOR CARRYING OUT THE INVENTION

[1314] This invention is a system that collects and analyzes a user's vital signs in real time, and integrates a means of recognizing the user's emotions to provide an optimal indoor environment. Furthermore, through the "Go for it" mode, a generative AI model can be used to send encouraging messages based on the user's emotional state, increasing the user's motivation. An example of how this system can be implemented is shown below.

[1315] System Configuration

[1316] The system consists of the following main components:

[1317] 1. Vital Signs Collection Device

[1318] The terminal collects the user's vital signs using wearable devices such as audio glasses and smartwatches, which capture data such as body temperature, heart rate, and blood pressure in real time.

[1319] 2. Emotion Recognition Engine

[1320] The device collects emotional data from the user through voice input and facial expression analysis. Voice input is analyzed through a microphone to capture the user's tone of voice and emotional state, while facial expression analysis is performed using a camera.

[1321] 3. Data Collection and Transfer

[1322] The device encrypts the collected vital sign and emotion data and sends it to a server via the Internet, using the TLS / SSL protocol to ensure secure data transfer.

[1323] 4. Data Analysis Server

[1324] The server analyzes the received vital sign data and emotion data to evaluate the user's physical and emotional state. The server can analyze the data using machine learning algorithms (e.g., TensorFlow and scikit-learn) and perform statistical analysis.

[1325] 5. Smart appliances

[1326] The device controls smart home appliances such as air conditioners, humidifiers, and lighting in the room based on the optimal environmental settings received from the server, automatically adjusting temperature, humidity, and light levels.

[1327] 6. Support message function

[1328] The server uses "Go for it" mode to send dynamically changing cheering messages to users based on their emotional data. Prompts for the generative AI model (e.g., GPT-3) include, "The user's body temperature is 37.2 degrees and their emotional state is stressed. Please tell me what kind of cheering message would be appropriate in this case."

[1329] Specific examples

[1330] The user wears audio glasses and a smartwatch. The device captures the user's body temperature and heart rate in real time, and also collects emotional data (e.g., "stress" state) via a microphone and camera. This data is encrypted and sent to a server.

[1331] The server analyzes this data and evaluates the user's health condition. For example, if the server determines that the user's body temperature is 37.2 degrees, indicating stress, it will operate the air conditioner to set the room temperature to 22 degrees, use a humidifier to keep the humidity at 50%, and adjust the lighting to 500 lux. At the same time, it will use a generative AI model to generate a supportive message such as "Relax!" and send it to the device.

[1332] Based on this, the device will set the air conditioner to 22 degrees, adjust the humidifier to 50% humidity, and display a message to the user saying "Relax!", allowing the user to continue working in a comfortable environment, maintaining their health and concentration.

[1333] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1334] Step 1:

[1335] Data collection

[1336] The device acquires vital sign data such as the user's body temperature, heart rate, and blood pressure using sensors in wearable devices (audio glasses or smartwatches). For example, the device reads the body temperature and heart rate from the sensors every second.

[1337] The device uses a microphone to pick up the user's tone of voice and emotional state and saves the audio data. It also uses a camera to capture the user's facial expressions and performs real-time emotion analysis. For example, it uses facial recognition technology to distinguish between smiling and angry expressions.

[1338] Input: Vital sign data from sensors, audio data from microphones, video data from cameras

[1339] Output: Collected vital sign data and emotional data (voice analysis results and facial expression analysis results)

[1340] Step 2:

[1341] Data transmission

[1342] The device encrypts the collected vital sign and emotion data in real time and transmits it to a server over the Internet using the TLS / SSL protocol via HTTPS. For example, the data is sent in packets every 10 seconds.

[1343] Input: Collected vital signs and emotion data

[1344] Output: Encrypted data sent to the server

[1345] Step 3:

[1346] Data analysis

[1347] The server analyzes the received vital sign data and emotion data. The received data is stored in a database and a dedicated analysis algorithm (e.g., TensorFlow, scikit-learn) is used for analysis. The data is preprocessed and inconsistencies are removed before it is used for analysis.

[1348] The server evaluates the user's health condition (hyperthermia, normal body temperature, etc.) and emotional state (relaxed, stressed, etc.) based on the analysis results. For example, if the body temperature is 37.2 degrees and the emotional state is determined to be stressed, it will determine that relaxation is necessary.

[1349] Input: Encrypted data sent to the server

[1350] Output: Assessment of health and emotional state based on analyzed vital signs and emotion data.

[1351] Step 4:

[1352] Determining your environment settings

[1353] The server then recommends the optimal indoor environment based on the analysis results. For example, if a user has a body temperature of 37.2 degrees and is in a state of stress, it will recommend setting the air conditioner to 22 degrees and the humidifier to 50% humidity. The settings are determined taking into account past data and weather data.

[1354] Input: Analyzed health and emotional state ratings

[1355] Output: Recommended indoor environment setting data

[1356] Step 5:

[1357] Smart home appliance control

[1358] The terminal controls smart home appliances in the room based on the environmental setting data sent from the server, for example, sending control commands to set the air conditioner to 22 degrees and the humidifier to 50% humidity.

[1359] The terminal checks whether the sent control command was successful and reports success or failure to the server. For example, it sends a command via an API for air conditioner settings and checks whether the setting was successful.

[1360] Input: Preference data sent from the server

[1361] Output: Controlled smart appliances and confirmation of successful control

[1362] Step 6:

[1363] Send a message of support

[1364] The server activates the "Go for it" mode and uses a generative AI model (e.g., GPT-3) to create a cheering message based on the user's emotional data. The prompt used is, "The user's body temperature is 37.2 degrees and their emotional state is stressed. In this case, please tell us what kind of cheering message would be appropriate."

[1365] The server sends the generated cheer message to the device, which then displays it to the user. For example, an automatically generated message like "Relax!" is displayed as a pop-up every five minutes.

[1366] Input: User emotion data and prompt sentence

[1367] Output: Generated cheer message and its display

[1368] (Application example 2)

[1369] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1370] This invention relates to a system that collects and analyzes a user's biosignals and emotional data in real time and provides an optimal environment based on this data. However, conventional systems have insufficient means for ensuring user safety and are unable to respond appropriately when the user experiences stress or abnormalities in their biosignals. Therefore, a system is needed that uses a user's biosignals and emotional data to instantly assess security risks and send appropriate warnings and emergency notifications.

[1371] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting biosignal and emotional data of the user, means for analyzing the collected biosignal and emotional data, means for adjusting the environment based on the analysis results, means for sending a cheering message to motivate the user, means for assessing security risks using the biosignal and emotional data of the user, and means for issuing an alert and sending an emergency notification when a risk is detected. This not only optimizes the user's health and emotional state and enables high performance, but also makes it possible to ensure the user's safety in real time and respond quickly to emergencies.

[1372] "User" means an individual using the System.

[1373] "Biological signals" refer to data that indicates the state of the body, such as body temperature, heart rate, and blood pressure.

[1374] "Emotional data" refers to data that indicates the user's emotional state through voice and facial expression analysis.

[1375] "Analysis" refers to the process of evaluating and interpreting collected biosignal and emotional data.

[1376] "Environmental adjustment" refers to the operation of optimizing the indoor environment, such as temperature, humidity, and lighting, based on the analysis results.

[1377] "Motivation" refers to efforts to increase the user's motivation and enthusiasm.

[1378] A "support message" refers to words of encouragement or instructions sent to motivate a user.

[1379] "Security risk" refers to a potential threat or danger to the safety of a user.

[1380] "Warning" refers to a notification sent to users and other relevant parties when a danger or abnormality is detected.

[1381] "Emergency notifications" refer to alerts or messages sent immediately when an abnormality occurs.

[1382] This invention is a real-time security risk assessment system that collects and analyzes a user's biometric and emotional data to ensure their safety. This system shares data with smart glasses, a server, and the Internet, and can adjust the environment as needed, issue warnings, and send emergency notifications according to the user's situation. The specific configuration and operation of this system are described below.

[1383] System Configuration Overview

[1384] Hardware

[1385] 1. Smart Glasses

[1386] Camera: Records the user's facial expressions in real time and collects emotional data.

[1387] Microphone: Records the user's voice and provides data for emotional analysis.

[1388] Various sensors: Measure vital signs such as body temperature, heart rate, and blood pressure.

[1389] 2. Server

[1390] Data analysis engine: Analyzes collected bio-signals and emotional data to assess the user's condition.

[1391] Machine learning algorithms: Machine learning algorithms are used to generate accurate analysis results from biometric and emotional data.

[1392] Cheer message generation module: Generates cheer messages according to the situation.

[1393] software

[1394] Python program: The main program for data collection, data transmission, and security risk assessment.

[1395] Rest API: A standard API for communicating with the server.

[1396] Encryption protocol: Encrypts data to ensure security during transmission.

[1397] Process Details

[1398] The server receives data sent from the smart glasses. The smart glasses use a camera, microphone, and various sensors to collect the user's biometric and emotional data. The collected data is sent to the server in real time and analyzed using machine learning algorithms. Based on the analysis results, the server evaluates the user's current health and emotional state.

[1399] Based on the evaluation results, the server can issue instructions to adjust the indoor environment. For example, if a user's body temperature is rising, the server can lower the air conditioner temperature setting or adjust the lighting. If the user is feeling stressed, the server can also send a message of encouragement such as "Relax!"

[1400] It also assesses security risks based on the user's health and emotional state: if the user is stressed and has a high body temperature, for example, the system will issue an alert, adjust the environment as needed, and send an emergency notification to security staff.

[1401] Specific examples

[1402] For example, when a user is wearing smart glasses, if the system detects a body temperature of 37.3 degrees, a heart rate of 90, a blood pressure of 120 / 80, and an emotional state of "stress," it will lower the air conditioning temperature setting, display a supportive message saying "Relax!", and automatically send an emergency notification to security staff.

[1403] Example prompt sentence:

[1404] "Temperature is 37.3°C, emotional state is recognized as 'stressed'. These are abnormal values. Please implement emergency response."

[1405] This allows the system to optimize the user's health and emotional state, providing a comfortable and safe environment for the user.

[1406] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1407] Step 1:

[1408] The device uses the camera, microphone, and various sensors in the smart glasses to collect the user's biometric signals (body temperature, heart rate, blood pressure) and emotional data (facial expressions, voice). Specific data collected includes a body temperature of 36.8 degrees, a heart rate of 85, and an emotional state of "relaxed."

[1409] Step 2:

[1410] The device transmits the collected biometric and emotional data to a server in real time. The data is encrypted using an encryption protocol to ensure security. Input data includes body temperature, heart rate, and emotional state.

[1411] Step 3:

[1412] The server analyzes the received biometric and emotional data. It uses machine learning algorithms to evaluate the data and determine the user's current health and emotional state. For example, if the body temperature is 37.2 degrees and the emotional state is "stressed," the user is diagnosed with high stress. The input data is analyzed, and the user's health and emotional state are obtained as outputs.

[1413] Step 4:

[1414] The server then adjusts the environment based on the analysis results. For example, it may change the air conditioner's temperature setting from 24 degrees to 22 degrees and adjust the lighting brightness to 500 lux. The analysis results are used as input for this process, and environmental setting data (temperature, illuminance, etc.) is obtained as output.

[1415] Step 5:

[1416] The device controls smart home appliances such as air conditioners and lighting based on the configuration data received from the server. The device receives the configuration data as input and executes specific home appliance control commands (such as changing the temperature setting of the air conditioner or adjusting the brightness of the lights) as output.

[1417] Step 6:

[1418] The server uses a "Ganbare Mode" to send encouraging messages to motivate the user. For example, if the user is feeling stressed, the server sends a message saying "Relax!". This process uses emotional state data as input, and generates and sends encouraging messages as output.

[1419] Step 7:

[1420] The server evaluates the security risk based on the user's health and emotional state. If the user's body temperature rises and the emotional state is judged to be "stressed," it issues an alert and sends an emergency notification to security staff. The input to this process is the health and emotional state data, and the output is a warning message and an emergency notification.

[1421] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1422] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1423] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1424] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1425] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1426] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1427] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1428] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1429] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1430] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1431] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1432] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1433] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1434] 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.

[1435] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1436] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1437] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1438] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1439] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1440] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1441] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1442] The following is further disclosed regarding the above embodiment.

[1443] (Claim 1)

[1444] a means for collecting vital signs of a user;

[1445] a means for analyzing the collected vital signs data;

[1446] a means for adjusting the indoor environment based on the analysis results;

[1447] a means for sending a cheering message to motivate the user;

[1448] A system including:

[1449] (Claim 2)

[1450] The system of claim 1, further comprising means for suggesting optimal rest times and hydration when the user's vital signs meet certain conditions.

[1451] (Claim 3)

[1452] 10. The system of claim 1, further comprising means for monitoring the user's health condition in real time from the collected vital sign data and automatically adjusting the indoor environment.

[1453] (Claim 4)

[1454] 10. The system of claim 1, further comprising means for evaluating correlation between vital sign data and performance and suggesting optimal work environments and tasks.

[1455] (Claim 5)

[1456] 10. The system of claim 1, further comprising means for collecting vital signs using audio glasses or a smartwatch.

[1457] "Example 1"

[1458] (Claim 1)

[1459] A means for collecting physical information of a user;

[1460] a means for analyzing the collected physical information;

[1461] a means for adjusting the indoor environment based on the analysis results;

[1462] means for sending a cheering message to motivate the user;

[1463] A system including:

[1464] (Claim 2)

[1465] The system according to claim 1, further comprising means for suggesting optimal rest times and hydration when the user's physical information satisfies certain conditions.

[1466] (Claim 3)

[1467] The system of claim 1, further comprising means for monitoring the user's health condition in real time from the collected physical information and automatically adjusting the indoor environment.

[1468] "Application Example 1"

[1469] (Claim 1)

[1470] a means for collecting vital signs of a user;

[1471] a means for analyzing the collected vital signs data;

[1472] a means for adjusting the indoor environment based on the analysis results;

[1473] a means for sending a cheering message to motivate the user;

[1474] A means of collecting vital signs of store staff and customers to provide an optimal store environment,

[1475] A means for automatically controlling smart equipment using vital sign data;

[1476] A means to send messages of support to staff and customers in real time;

[1477] A system including:

[1478] (Claim 2)

[1479] The system of claim 1, further comprising means for suggesting optimal rest times and hydration when the user's vital signs meet certain conditions.

[1480] (Claim 3)

[1481] 10. The system of claim 1, further comprising means for monitoring the user's health condition in real time from the collected vital sign data and automatically adjusting the indoor environment.

[1482] "Example 2: Combining Emotion Engines"

[1483] (Claim 1)

[1484] a means for collecting vital signs of a user;

[1485] means for analyzing the collected vital sign data and emotion data;

[1486] a means for adjusting the indoor environment based on the analysis results;

[1487] A means for sending a cheering message using a generative AI model based on the emotional state of the user;

[1488] A system including:

[1489] (Claim 2)

[1490] The system of claim 1, further comprising means for suggesting optimal rest times and hydration when the user's vital signs meet certain conditions.

[1491] (Claim 3)

[1492] 10. The system of claim 1, further comprising means for monitoring the user's health and emotional state in real time from the collected vital sign data and emotional data and automatically adjusting the indoor environment.

[1493] "Application example 2 when combining emotion engines"

[1494] (Claim 1)

[1495] means for collecting a biometric signal of a user;

[1496] means for analyzing the collected biosignal data and emotion data;

[1497] a means for adjusting the environment based on the analysis results;

[1498] means for sending a cheering message to motivate the user;

[1499] a means for assessing security risks using biometric and emotional data of a user;

[1500] A means of issuing alerts and sending emergency notifications when risks are detected;

[1501] A system including:

[1502] (Claim 2)

[1503] The system according to claim 1, further comprising means for suggesting optimal rest times and hydration when the user's biosignals satisfy certain conditions.

[1504] (Claim 3)

[1505] 10. The system of claim 1, further comprising means for monitoring a user's health status in real time from collected biosignal data and automatically adjusting the environment. [Explanation of symbols]

[1506] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for collecting vital signs of a user; a means for analyzing the collected vital signs data; a means for adjusting the indoor environment based on the analysis results; a means for sending a cheering message to motivate the user; A system including:

2. The system according to claim 1 , further comprising means for suggesting optimal rest times and hydration when the user's vital signs meet certain conditions.

3. The system according to claim 1 , further comprising means for monitoring the user's health condition in real time from the collected vital sign data and automatically adjusting the indoor environment.

4. The system of claim 1 , further comprising means for evaluating the correlation between vital sign data and performance and suggesting an optimal work environment and task.

5. The system of claim 1 , further comprising means for collecting vital signs using audio glasses or a smart watch.

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