system

Abstract

We provide the system. [Solution] A data collection means for collecting biological data and environmental parameters from various electronic devices in the home, An analytical means for analyzing the collected data and evaluating health status and environmental status, A control means for optimizing the operation of the electronic device and adjusting the environment inside the residence based on the results of the analysis, Energy management means for controlling the power supply to the electronic device by wireless energy supply, A notification means for providing users with incentives related to energy and health management, A monitoring means that allows residents to check data and incentive information through mobile communication devices and viewing / optical equipment, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Modern households require a large number of electronic devices and complex data management, so it takes a great deal of effort to maintain a comfortable and healthy life. In particular, manually adjusting the optimal environment according to the rhythm of life and health status is cumbersome, and it is difficult to flexibly respond to lifestyle changes for efficient energy use. Furthermore, wireless power supply for power management of home appliances has many technically very difficult problems. There is a need for a new system to solve such problems and realize a healthy and efficient life.

Means for Solving the Problems

[0005] This invention is realized through data collection means for collecting health and environmental data from various electronic devices in the home, and analysis means for analyzing this data in real time and evaluating health status and the home environment. Furthermore, it has control means for dynamically controlling electronic devices and adjusting the environment based on these analysis results. The control means can optimize the power supply to electronic devices using wireless power supply. In addition, it also has notification means that have a function to provide incentives according to the results of energy and health management. As a result, the user can enjoy an automated, healthy, and efficient living environment.

[0006] "Data collection means" refers to devices or systems that collect health data and environmental data from various electronic devices within the home.

[0007] "Analysis means" refers to a device or system that analyzes collected health and environmental data to evaluate health and environmental conditions within the home.

[0008] "Control means" refers to a device or system that controls various electronic devices to automatically optimize the home environment based on evaluation results from analysis means.

[0009] A "power management device" is a device or system that efficiently controls the power supply to various electronic devices in the home using wireless power supply.

[0010] A "notification means" is a device or system that provides users with information regarding data analysis results and incentives.

[0011] "Wireless power supply" is a technology that supplies power to electronic devices without using cables.

[0012] An "incentive" is a reward or perk offered to users for improving their health management or energy efficiency. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is a system that automatically creates a healthy and comfortable environment by collecting data from various electronic devices placed in the home, analyzing it in real time, and more. The main components of this system include a server, terminals, and users, and it is effective only when all these elements work together in coordination.

[0035] The server periodically collects health and environmental data from various electronic devices and sensors within the home. This includes heart rate data from smartwatches and environmental information obtained from room temperature and humidity sensors. The server analyzes this data using analytical tools to evaluate the user's health status and the comfort level of the environment.

[0036] For example, the server assesses the user's stress level based on their heart rate data and sends instructions to the terminal to adjust the room temperature and lighting accordingly. It also uses environmental information to change the air conditioner's temperature setting or adjust the lighting brightness to provide the user with the optimal environment.

[0037] The terminal receives control instructions from the server and manages the energy supply to home appliances wirelessly. This enables efficient use of electricity and reduces energy consumption. For example, it can adjust the power supply according to lighting usage and supply power only when needed, thereby improving energy efficiency.

[0038] Users receive feedback on their health status and energy efficiency based on the server's analysis. This includes providing incentives; for example, points are awarded for achieving health goals, which are then reflected in their next electricity bill.

[0039] This invention, through the aforementioned components and their interactions, enables the realization of a system that automatically controls the home environment and maintains health and comfort.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The server collects health and environmental data from various electronic devices and sensors within the home. This data includes the user's heart rate obtained from a smartwatch and indoor environmental information from temperature and humidity sensors. The server centrally manages this data and stores it as foundational data for analysis.

[0043] Step 2:

[0044] The server analyzes the collected data to assess health status and environmental comfort. The generating AI analyzes heart rate variability to estimate the user's stress level. From temperature and humidity data, it determines the level of comfort in the room and derives the optimal environment for that location.

[0045] Step 3:

[0046] Based on the analysis results, the server sends control instructions to the terminal to adjust the home environment. For example, if the user's stress level is high, it may instruct the terminal to play relaxation music or change the air conditioner setting to a comfortable temperature.

[0047] Step 4:

[0048] The terminal receives control instructions from the server and appropriately controls home appliances and lighting. To ensure efficient energy consumption, the terminal adjusts wireless power supply according to the operating status of the appliances. The terminal also notifies the user of energy warnings as needed.

[0049] Step 5:

[0050] Users receive feedback from the server, including changes in their health status and energy efficiency results. Based on this feedback, users can gain guidance for improving their daily lifestyle and be further motivated by receiving incentive information.

[0051] (Example 1)

[0052] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0053] There is a challenge in achieving efficient energy use while maintaining health and comfort within the home. Furthermore, automatic environmental adjustments based on users' stress levels and other health conditions are insufficient, creating a need for solutions optimized for individual lifestyles.

[0054] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0055] In this invention, the server includes information gathering means for collecting biometric and environmental data, evaluation means for analyzing the collected data to evaluate health status and environmental conditions, and adjustment means for optimizing the operation of the equipment and adjusting the environment based on the evaluation results. This makes it possible to construct a system that dynamically adjusts the home environment according to the user's health status and lifestyle while enabling efficient energy use.

[0056] "Information gathering means" refers to methods for collecting biometric and environmental data from various devices within the home.

[0057] "Evaluation means" refers to methods for analyzing collected biological and environmental data to evaluate health status and environmental conditions.

[0058] "Adjustment means" are methods for optimizing the operation of equipment and adjusting the home environment based on evaluation results.

[0059] A "power supply management system" is a means of controlling the power supply to household appliances through wireless power supply.

[0060] "Notification means" refers to means of providing users with rewards related to electricity and health management.

[0061] In an embodiment of this invention, the system includes three main elements: a server, a terminal, and a user, each of which operates in cooperation with one another.

[0062] The server collects biometric and environmental data from various electronic devices and sensors within the home. Specifically, it acquires heart rate data from wearable devices such as smartwatches and collects data on indoor temperature and humidity from environmental sensors. This data is stored in a database on the server.

[0063] Next, the server uses software to analyze the collected data. Specifically, it utilizes libraries such as Python's Pandas and NumPy to analyze heart rate variability and statistically evaluate environmental information. This evaluation clarifies the user's health status and environmental conditions.

[0064] Based on the evaluation results, the server creates and sends control instructions to the terminal to optimize the home environment. For example, if the user's stress level is high, it will issue instructions to lower the air conditioner temperature appropriately and change the lighting color to a warm, relaxing color. This control is made possible through efficient device operation via an in-home IoT hub or similar device.

[0065] The terminal receives instructions from the server and manages the power supply via wireless communication. The terminal adjusts the power requirements of household appliances, enabling them to operate with the minimum necessary energy. For example, it can adjust lighting usage time and brightness to optimize energy consumption.

[0066] Users receive feedback on their health status and energy conservation based on the server's analysis results. Through a dedicated application, users can check incentive information, such as points earned by achieving health goals being reflected in their next electricity bill.

[0067] For example, if a user exercises regularly, heart rate data is collected, and a decrease in stress levels is detected, the system will automatically provide an environment that promotes relaxation. It is also possible to use a generative AI model to generate optimal prompt messages tailored to the user's lifestyle. Another example of an AI-powered prompt message is: "My home smart system uses my heart rate data to monitor my stress levels and adjusts the room temperature and lighting to make me comfortable. Could you please give me some specific advice on how to reduce stress?"

[0068] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0069] Step 1:

[0070] The server collects data from various devices and sensors. Inputs include heart rate data from smartwatches and environmental data from temperature and humidity sensors. This data is aggregated on the server. Data processing includes format conversion and noise reduction, and the output is stored in a database.

[0071] Step 2:

[0072] The server analyzes the collected data. The input data consists of heart rate and environmental data stored in a database on the server. Using analysis tools such as Python's Pandas and NumPy, the server calculates stress levels from time-series heart rate data and determines the average and fluctuation values ​​of environmental data. The analysis results output indicators for evaluating the user's stress level and the indoor environment.

[0073] Step 3:

[0074] The server generates control instructions based on the analysis results. The inputs are the evaluation results of heart rate and environmental data. Using control logic, it generates instructions such as lowering the air conditioner temperature or changing the lighting to a warmer color if the stress level is high. These control instructions are generated as output and sent to the terminal.

[0075] Step 4:

[0076] The terminal processes control instructions received from the server. The input is specific appliance control instructions from the server. Based on the received instructions, the terminal sends signals to each appliance via the IoT hub, adjusting the operation of appliances such as air conditioners and lighting. This provides the user with an optimal living environment, which is the output of the processing.

[0077] Step 5:

[0078] Users receive feedback from the server. This feedback includes their health status assessment and energy-saving performance. This information is communicated to the user via a dedicated app. The notifications include reports on health achievements and points awarded based on energy savings. As a result, users can increase their motivation for managing their health and saving energy.

[0079] (Application Example 1)

[0080] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0081] In modern homes, it is becoming common to manage environmental and biometric data using various electronic devices and sensors. However, these systems operate independently, and integrated data handling and effective feedback to users are not fully realized. Furthermore, improving energy efficiency and providing concrete incentives for residents' health management remain challenges. In addition, there is a need for means to appropriately control the living environment through real-time data monitoring.

[0082] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0083] In this invention, the server includes data collection means for collecting biometric data and environmental parameters from various electronic devices within the home, analysis means for analyzing the collected data and evaluating health and environmental conditions, and energy management means for controlling the power supply to the electronic devices via wireless energy supply. This enables integrated data management and optimized environmental control throughout the entire residence. Furthermore, residents can monitor their data and receive incentives through mobile communication terminals and viewing / optical equipment, enabling them to pursue a comfortable and healthy living environment.

[0084] "Data collection means" refers to devices that acquire biometric data and environmental parameters from various electronic devices and sensors installed in the home.

[0085] "Analysis means" refers to a processing device used to evaluate health status and environmental conditions based on collected biological data and environmental parameters.

[0086] A "control device" is a device that optimizes the operation of electronic devices in the home and adjusts the living environment based on the analyzed results.

[0087] An "energy management device" is a device that controls the power supply to electronic devices in a home through wireless energy supply.

[0088] A "notification device" is a device that informs users of incentives related to energy and health management.

[0089] "Monitoring means" refers to devices that allow residents to check data and incentive information through mobile communication terminals or viewing / optical equipment.

[0090] A system implementing this invention includes data acquisition means, analysis means, control means, energy management means, notification means, and monitoring means.

[0091] The server collects biometric data and environmental parameters from various electronic devices and sensors within the home. This includes data from wearable devices to acquire health data and information from temperature and humidity sensors to understand environmental conditions. A cloud service database (e.g., Amazon Web Services RDS) is used for data collection, and the information is updated regularly.

[0092] The server analyzes the collected data and uses Pandas, a Python data processing library, to evaluate health status and comfort indices. This allows it to calculate the health status and comfort level of residents and generate data to provide an optimal environment.

[0093] The terminal controls electronic devices within the home based on instructions from the server, providing an optimal living environment. Specifically, it can dynamically adjust settings for air conditioners and lighting via wireless communication. AWS® IoT services are used for energy management, enabling efficient power consumption.

[0094] Users can check the operating status of these systems and receive real-time feedback on their health status via mobile communication devices and viewing / optical devices. The user interface uses React Native and is compatible with iOS and Android® platforms. Health goal achievement status and incentive information for energy saving are displayed in an easy-to-understand manner.

[0095] For example, if the system analyzes that a user is fatigued, the room lighting will be adjusted to a relaxing brightness. An example of a prompt to the generative AI model for this system would be, "How can I calculate stress levels from health data collected using AWS Lambda?"

[0096] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0097] Step 1:

[0098] The server collects biometric data and environmental parameters from various sensors and wearable devices installed in the home. The input is real-time data from sensors and devices, and the output is a formatted dataset. The server stores the acquired data in a cloud-based database.

[0099] Step 2:

[0100] The server analyzes the collected data and uses the Python Pandas library to calculate evaluation metrics such as stress levels and comfort indices. The input consists of biometric data and environmental parameters retrieved from a database, while the output consists of user health metrics and environmental evaluation metrics.

[0101] Step 3:

[0102] The server generates control instructions based on the analysis results and sends them to electronic devices in the home. The inputs are health indicators and environmental assessment indicators, and the output is a control signal. Specifically, this allows for automatic adjustment of things like air conditioner temperature settings and lighting brightness.

[0103] Step 4:

[0104] The terminal receives control instructions from the server and operates the electronic devices accordingly. The input is the control signal from the server, and the output is the new configuration state of each device.

[0105] Step 5:

[0106] Users check the system's operating status and their own health indicators using mobile communication devices or viewing / optical equipment. Input is data displayed on the device, and output is feedback based on the user's understanding and choices.

[0107] Step 6:

[0108] The server optimizes data analysis algorithms based on user feedback and behavioral patterns, and uses a generative AI model to improve future operations and incentive provision. Inputs are user feedback data and previous data analysis results, while output is the updated algorithm model.

[0109] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0110] This invention is a system for automatically creating a healthy and comfortable environment within the home using various data. This system collects data in conjunction with electronic devices and sensors in the home and adjusts the environment based on the user's health and emotional state. By including an emotion engine, it can also operate while considering the user's psychological comfort. To implement this invention, a server, terminal, emotion engine, and user function as the respective elements.

[0111] The server collects health and environmental data, as well as audio and video data, from various electronic devices and sensors within the home. In particular, the emotion engine uses this data to analyze the user's emotions and generate emotional data. As a result, it can estimate the user's current psychological state.

[0112] For example, if the emotion engine determines that a user has been under high stress for an extended period, the server can automatically adjust the environment to reduce stress by changing the lighting settings. It can also change the music playlist and send a command to the device to play more relaxing music.

[0113] The terminal receives control instructions from the server and automatically adjusts the status of home appliances and lighting to perform effective energy management. For example, it optimizes the temperature setting of an air conditioner and supplies power only when needed using wireless power supply.

[0114] Users can receive feedback from the server, which includes information on their emotional state, health status, and energy efficiency. This allows users to review their lifestyle habits and gain guidance for improvement.

[0115] Thus, the present invention is a system that supports a comfortable and efficient lifestyle by optimizing the indoor environment while taking into account both the user's physical and emotional state.

[0116] The following describes the processing flow.

[0117] Step 1:

[0118] The server collects health data, environmental data, audio data, and video data in real time from various sensors and electronic devices within the home. This data collection is scheduled and adjusted as needed based on the user's lifestyle patterns.

[0119] Step 2:

[0120] The server sends the collected data to the emotion engine, which analyzes the user's emotional state. The emotion engine evaluates whether the user is stressed or relaxed through voice and facial expression analysis, and generates emotional data.

[0121] Step 3:

[0122] The server combines the generated emotional and health data to determine the optimal environment settings for the user. For example, if it determines that the user needs to relax, the server will instruct the system to change the lighting to warmer colors and play relaxing music.

[0123] Step 4:

[0124] The terminal receives control instructions from the server and adjusts home appliances and lighting systems. This allows it to perform actions such as changing the temperature of the air conditioner or playing relaxing music on a music player as needed. Efficient energy management is also implemented through wireless power supply.

[0125] Step 5:

[0126] Users receive feedback from the server via their smart devices. This feedback includes their current emotional state, health indicators, and energy usage information, allowing users to objectively evaluate their lifestyle habits.

[0127] Step 6:

[0128] The server applies an incentive system based on the analysis data from the emotion engine, notifying users of points and benefits to promote healthy lifestyle habits. This is expected to increase user engagement and sustained use.

[0129] (Example 2)

[0130] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0131] To achieve a comfortable life within the home, flexible environmental adjustments tailored to the health and emotional states of individual residents are necessary. However, conventional technologies have limited capabilities for individual emotional analysis and dynamic environmental control, making it difficult to realize true user comfort. Furthermore, while optimizing energy consumption is also important, systems capable of real-time, detailed monitoring and control have been limited.

[0132] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0133] In this invention, the server includes means for collecting biometric data and ambient environmental data from measuring devices within the home, means for analyzing the collected data and estimating the individual's psychological and physical state, and means for adjusting the settings of the information processing device based on the analysis results to optimize the indoor environment within the home. This enables flexible, real-time environmental adjustments to the health and emotional state of the residents, as well as efficient management of energy consumption.

[0134] A "household measuring device" is a device installed in a home to collect biological data and ambient environmental data.

[0135] "Biometric data" refers to information about the user's health and physiological state, including heart rate and body temperature.

[0136] "Environmental data" refers to information that indicates environmental conditions such as indoor temperature, humidity, and light intensity.

[0137] "Analysis" is the process of using collected data to analyze and evaluate information, and to estimate the psychological and physical state of individual users.

[0138] An "information processing device" is an electronic device used to control the environment based on various data and instructions, and specifically includes household electrical appliances and lighting equipment.

[0139] "Wireless power transfer technology" is a technology that supplies power without using cables, and in most cases utilizes electromagnetic induction or electromagnetic resonance.

[0140] An "incentive" is something that provides users with benefits or incentives for biometric monitoring or energy consumption.

[0141] "Sequential monitoring" refers to the act of continuously observing and recording data as time progresses.

[0142] For this invention to be implemented, it is essential that the server, terminal, and user function in coordination with each other. The server efficiently collects biometric and ambient environmental data from in-home measuring devices. For this purpose, temperature sensors, humidity sensors, heart rate monitors, etc., are used. Specifically, it is recommended to use a general-purpose small computer or a specialized data acquisition appliance to centrally manage the data using a connected network.

[0143] The server implements advanced data analysis techniques to analyze the collected data. Machine learning libraries using programming languages ​​such as Python are employed here. This analysis is crucial for estimating the user's psychological and physical state.

[0144] The terminal adjusts the settings of the home's information processing devices based on analysis results from the server. Specifically, it improves user comfort by sending control signals to smart home appliances and lighting systems. It utilizes smart device APIs to automatically perform actions such as adjusting air conditioner temperature settings and changing lighting color tones.

[0145] Users experience the resulting environmental changes and receive feedback. This feedback includes improvements in energy efficiency and analysis of their health status through biometric monitoring. This allows users to obtain useful information to optimize their lifestyle.

[0146] For example, if a user returns home after working for a long time and the system analyzes that their heart rate and body temperature are high, the server will send instructions to the terminal to adjust the environment to a more relaxing state. This might include changing the lighting to warmer colors, playing soothing music, and adjusting the air conditioning to provide a comfortable temperature.

[0147] Examples of prompts to input into a generative AI model include instructions such as, "Please suggest optimal environment settings based on the user's current emotional state." These prompts help guide the AI ​​in making adjustments that are appropriate for the user.

[0148] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0149] Step 1:

[0150] The server collects biometric and environmental data from in-home measurement devices. Input data includes room temperature from a temperature sensor, humidity from a humidity sensor, and heart rate from a heart rate monitor. This data is received via the network and recorded in a database. The server also receives and centrally manages data periodically transmitted from sensors, and performs a process to verify data integrity. The output is organized biometric and environmental data.

[0151] Step 2:

[0152] The server processes the collected data using a machine learning library for analysis. The input includes biometric and environmental data organized in Step 1. The machine learning model analyzes the data to estimate the user's psychological and physical state. Specifically, it preprocesses the data and inputs it into an emotion analysis model to classify stress levels and health status. The output is the estimated results of the user's emotional and health status.

[0153] Step 3:

[0154] The server generates instructions to adjust the settings of the information processing device based on the analysis results. The input is the estimated results of the user's emotional and health states obtained in step 2. Based on the analysis results, it generates prompt statements to determine how the environment should be adjusted and inputs them into the generating AI model. The model then generates instructions for the optimal environment settings. The output consists of specific environment adjustment instructions, such as lighting color, music selection, and air conditioning settings.

[0155] Step 4:

[0156] The terminal executes environmental adjustment instructions sent from the server. The input is the environmental adjustment instructions generated in step 3. The terminal calls smart home APIs to change the temperature settings of air conditioners, uses music streaming services to play specific music playlists, and controls the lighting system to change the color tone. The output is the realization of the adjusted indoor environment, which is a setting that leads to improved user comfort.

[0157] Step 5:

[0158] The user experiences a tuned environment and receives feedback from the server. The inputs are the changes in the indoor environment realized in step 4 and the feedback information from the server. The feedback includes analysis information on energy efficiency and health status. Based on this, the user attempts to improve their lifestyle. The output is the awareness gained from the feedback and the actions taken to improve their lifestyle.

[0159] (Application Example 2)

[0160] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0161] In modern urban life, managing stress both inside and outside the home and maintaining a comfortable environment are crucial, but effectively managing these based on the emotional and health states of individual users is difficult. Furthermore, even in smart cities, providing information and managing energy to optimize residents' living environments is complex, necessitating more integrated and efficient systems.

[0162] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0163] In this invention, the server includes information gathering means for collecting health and environmental information from various electronic devices and detectors within the home, analysis means for analyzing the collected information and evaluating the health and environmental conditions, and urban information linking means for cooperating with smartphones and computer vision devices to provide information on stress-reducing spots and urban services. This makes it possible to provide information in an integrated manner based on the user's health and emotional state, and to optimize the environment inside and outside the home.

[0164] "Information gathering means" refers to a mechanism for collecting health information and environmental information from various electronic devices and detectors within the home.

[0165] "Analysis means" refers to a mechanism for analyzing collected information and evaluating the user's health status and environmental conditions.

[0166] A "control mechanism" is a system that optimizes the operation of electronic devices based on the results of analysis and adjusts the environment inside and outside the home.

[0167] An "energy management means" is a mechanism for controlling the energy supply to electronic devices through wireless energy supply.

[0168] A "notification mechanism" is a mechanism for communicating information to provide users with rewards related to energy and health status.

[0169] A "city information linkage system" is a mechanism that works in conjunction with smartphones and computer vision devices to provide users with information on stress-reducing spots and urban services.

[0170] This invention is an integrated system for providing a comfortable living environment both inside and outside the home, based on the user's health and emotional state. Specific embodiments are described below.

[0171] The server collects user health and environmental information from a wide variety of electronic devices and detectors installed in the home. This includes temperature sensors, humidity sensors, voice input devices, and video input devices. The server uses Python and Raspberry Pi to analyze this data. As an analysis method, it uses the natural language processing library NLTK and the machine learning framework TENSORFLOW® to estimate the user's psychological and physiological state.

[0172] Using these analysis results, the device controls various household devices to provide an optimal environment. For example, it can change the brightness of lights or play specific music. Furthermore, as an energy management tool, it optimizes energy consumption and supplies energy at the necessary times. This function works in conjunction with energy management software and runs on a Raspberry Pi.

[0173] Furthermore, through urban information sharing mechanisms, the system provides users with real-time information on stress-reducing spots and urban services using smartphones and computer vision devices. This function allows users to receive information, for example, about relaxation events in nearby parks or availability at the nearest cafe.

[0174] Users receive feedback from the server. This feedback includes information on changes in emotional state, health history, and energy efficiency. Based on this information, users can reflect on their lifestyle habits and make improvements as needed.

[0175] For example, if a user is determined to be stressed immediately after waking up in the morning, the server will provide information on smooth commuting routes within their residential area and cafeterias best suited for breakfast, so that they can start their daily life more quickly.

[0176] Example prompt: "If a user is determined to be experiencing stress, what activities or suggestions would be effective? Please provide specific examples."

[0177] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0178] Step 1:

[0179] The server collects health and environmental information from electronic devices and detectors within the home. This includes data such as temperature, humidity, sound, and video. The input data is obtained from each sensor and sent to the server in JSON format. The server stores this data in a database.

[0180] Step 2:

[0181] The server analyzes the collected data. It utilizes a natural language processing library (NLTK) and a machine learning framework (TensorFlow) to estimate the user's psychological and physiological state. The input data consists of information obtained from sensors, and an emotion engine is used to output the emotional state as a profile.

[0182] Step 3:

[0183] The terminal controls electronic devices in the home based on analysis results from the server. Specifically, it adjusts the brightness and color temperature of lighting and selects relaxing music on a music player. It receives analysis results as input and transmits operation instructions to each home appliance using an optimization algorithm.

[0184] Step 4:

[0185] As an energy management tool, the server monitors energy consumption in real time and supplies energy only when needed. Input energy data is obtained from smart meters, and a time-based energy allocation plan is generated as output.

[0186] Step 5:

[0187] Using urban information sharing technology, the server connects with smartphones and computer vision devices to provide users with information on stress-reducing spots and urban services. It receives the user's location information and current emotional profile as input, and notifies them of the most suitable service information as output.

[0188] Step 6:

[0189] The user receives feedback from the server, which includes information on changes in emotional state, health history, and energy efficiency. The input is feedback data from the server, and the output is the visualization of this information within the application.

[0190] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0191] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0192] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0193] [Second Embodiment]

[0194] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0195] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0196] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0197] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0198] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0199] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0200] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0201] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0202] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0203] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0204] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0205] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0206] This invention is a system that automatically creates a healthy and comfortable environment by collecting data from various electronic devices placed in the home, analyzing it in real time, and more. The main components of this system include a server, terminals, and users, and it is effective only when all these elements work together in coordination.

[0207] The server periodically collects health and environmental data from various electronic devices and sensors within the home. This includes heart rate data from smartwatches and environmental information obtained from room temperature and humidity sensors. The server analyzes this data using analytical tools to evaluate the user's health status and the comfort level of the environment.

[0208] For example, the server assesses the user's stress level based on their heart rate data and sends instructions to the terminal to adjust the room temperature and lighting accordingly. It also uses environmental information to change the air conditioner's temperature setting or adjust the lighting brightness to provide the user with the optimal environment.

[0209] The terminal receives control instructions from the server and manages the energy supply to home appliances wirelessly. This enables efficient use of electricity and reduces energy consumption. For example, it can adjust the power supply according to lighting usage and supply power only when needed, thereby improving energy efficiency.

[0210] Users receive feedback on their health status and energy efficiency based on the server's analysis. This includes providing incentives; for example, points are awarded for achieving health goals, which are then reflected in their next electricity bill.

[0211] This invention, through the aforementioned components and their interactions, enables the realization of a system that automatically controls the home environment and maintains health and comfort.

[0212] The following describes the processing flow.

[0213] Step 1:

[0214] The server collects health and environmental data from various electronic devices and sensors within the home. This data includes the user's heart rate obtained from a smartwatch and indoor environmental information from temperature and humidity sensors. The server centrally manages this data and stores it as foundational data for analysis.

[0215] Step 2:

[0216] The server analyzes the collected data to assess health status and environmental comfort. The generating AI analyzes heart rate variability to estimate the user's stress level. From temperature and humidity data, it determines the level of comfort in the room and derives the optimal environment for that location.

[0217] Step 3:

[0218] Based on the analysis results, the server sends control instructions to the terminal to adjust the home environment. For example, if the user's stress level is high, it may instruct the terminal to play relaxation music or change the air conditioner setting to a comfortable temperature.

[0219] Step 4:

[0220] The terminal receives control instructions from the server and appropriately controls home appliances and lighting. To ensure efficient energy consumption, the terminal adjusts wireless power supply according to the operating status of the appliances. The terminal also notifies the user of energy warnings as needed.

[0221] Step 5:

[0222] Users receive feedback from the server, including changes in their health status and energy efficiency results. Based on this feedback, users can gain guidance for improving their daily lifestyle and be further motivated by receiving incentive information.

[0223] (Example 1)

[0224] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0225] There is a challenge in achieving efficient energy use while maintaining health and comfort within the home. Furthermore, automatic environmental adjustments based on users' stress levels and other health conditions are insufficient, creating a need for solutions optimized for individual lifestyles.

[0226] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0227] In this invention, the server includes information gathering means for collecting biometric and environmental data, evaluation means for analyzing the collected data to evaluate health status and environmental conditions, and adjustment means for optimizing the operation of the equipment and adjusting the environment based on the evaluation results. This makes it possible to construct a system that dynamically adjusts the home environment according to the user's health status and lifestyle while enabling efficient energy use.

[0228] "Information gathering means" refers to methods for collecting biometric and environmental data from various devices within the home.

[0229] "Evaluation means" refers to methods for analyzing collected biological and environmental data to evaluate health status and environmental conditions.

[0230] "Adjustment means" are methods for optimizing the operation of equipment and adjusting the home environment based on evaluation results.

[0231] A "power supply management system" is a means of controlling the power supply to household appliances through wireless power supply.

[0232] "Notification means" refers to means of providing users with rewards related to electricity and health management.

[0233] In an embodiment of this invention, the system includes three main elements: a server, a terminal, and a user, each of which operates in cooperation with one another.

[0234] The server collects biometric and environmental data from various electronic devices and sensors within the home. Specifically, it acquires heart rate data from wearable devices such as smartwatches and collects data on indoor temperature and humidity from environmental sensors. This data is stored in a database on the server.

[0235] Next, the server uses software to analyze the collected data. Specifically, it utilizes libraries such as Python's Pandas and NumPy to analyze heart rate variability and statistically evaluate environmental information. This evaluation clarifies the user's health status and environmental conditions.

[0236] Based on the evaluation results, the server creates and sends control instructions to the terminal to optimize the home environment. For example, if the user's stress level is high, it will issue instructions to lower the air conditioner temperature appropriately and change the lighting color to a warm, relaxing color. This control is made possible through efficient device operation via an in-home IoT hub or similar device.

[0237] The terminal receives instructions from the server and manages the power supply via wireless communication. The terminal adjusts the power requirements of household appliances, enabling them to operate with the minimum necessary energy. For example, it can adjust lighting usage time and brightness to optimize energy consumption.

[0238] Users receive feedback on their health status and energy conservation based on the server's analysis results. Through a dedicated application, users can check incentive information, such as points earned by achieving health goals being reflected in their next electricity bill.

[0239] For example, if a user exercises regularly, heart rate data is collected, and a decrease in stress levels is detected, the system will automatically provide an environment that promotes relaxation. It is also possible to use a generative AI model to generate optimal prompt messages tailored to the user's lifestyle. Another example of an AI-powered prompt message is: "My home smart system uses my heart rate data to monitor my stress levels and adjusts the room temperature and lighting to make me comfortable. Could you please give me some specific advice on how to reduce stress?"

[0240] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0241] Step 1:

[0242] The server collects data from various devices and sensors. Inputs include heart rate data from smartwatches and environmental data from temperature and humidity sensors. This data is aggregated on the server. Data processing includes format conversion and noise reduction, and the output is stored in a database.

[0243] Step 2:

[0244] The server analyzes the collected data. The input data consists of heart rate and environmental data stored in a database on the server. Using analysis tools such as Python's Pandas and NumPy, the server calculates stress levels from time-series heart rate data and determines the average and fluctuation values ​​of environmental data. The analysis results output indicators for evaluating the user's stress level and the indoor environment.

[0245] Step 3:

[0246] The server generates control instructions based on the analysis results. The inputs are the evaluation results of heart rate and environmental data. Using control logic, it generates instructions such as lowering the air conditioner temperature or changing the lighting to a warmer color if the stress level is high. These control instructions are generated as output and sent to the terminal.

[0247] Step 4:

[0248] The terminal processes control instructions received from the server. The input is specific appliance control instructions from the server. Based on the received instructions, the terminal sends signals to each appliance via the IoT hub, adjusting the operation of appliances such as air conditioners and lighting. This provides the user with an optimal living environment, which is the output of the processing.

[0249] Step 5:

[0250] Users receive feedback from the server. This feedback includes their health status assessment and energy-saving performance. This information is communicated to the user via a dedicated app. The notifications include reports on health achievements and points awarded based on energy savings. As a result, users can increase their motivation for managing their health and saving energy.

[0251] (Application Example 1)

[0252] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0253] In modern homes, it is becoming common to manage environmental and biometric data using various electronic devices and sensors. However, these systems operate independently, and integrated data handling and effective feedback to users are not fully realized. Furthermore, improving energy efficiency and providing concrete incentives for residents' health management remain challenges. In addition, there is a need for means to appropriately control the living environment through real-time data monitoring.

[0254] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0255] In this invention, the server includes data collection means for collecting biometric data and environmental parameters from various electronic devices within the home, analysis means for analyzing the collected data and evaluating health and environmental conditions, and energy management means for controlling the power supply to the electronic devices via wireless energy supply. This enables integrated data management and optimized environmental control throughout the entire residence. Furthermore, residents can monitor their data and receive incentives through mobile communication terminals and viewing / optical equipment, enabling them to pursue a comfortable and healthy living environment.

[0256] "Data collection means" refers to devices that acquire biometric data and environmental parameters from various electronic devices and sensors installed in the home.

[0257] "Analysis means" refers to a processing device used to evaluate health status and environmental conditions based on collected biological data and environmental parameters.

[0258] A "control device" is a device that optimizes the operation of electronic devices in the home and adjusts the living environment based on the analyzed results.

[0259] An "energy management device" is a device that controls the power supply to electronic devices in a home through wireless energy supply.

[0260] A "notification device" is a device that informs users of incentives related to energy and health management.

[0261] "Monitoring means" refers to devices that allow residents to check data and incentive information through mobile communication terminals or viewing / optical equipment.

[0262] A system implementing this invention includes data acquisition means, analysis means, control means, energy management means, notification means, and monitoring means.

[0263] The server collects biometric data and environmental parameters from various electronic devices and sensors within the home. This includes data from wearable devices to acquire health data and information from temperature and humidity sensors to understand environmental conditions. A cloud service database (e.g., Amazon Web Services RDS) is used for data collection, and the information is updated regularly.

[0264] The server analyzes the collected data and uses Pandas, a Python data processing library, to evaluate health status and comfort indices. This allows it to calculate the health status and comfort level of residents and generate data to provide an optimal environment.

[0265] The terminal controls electronic devices within the home based on instructions from the server, providing an optimal living environment. Specifically, it can dynamically adjust settings for air conditioners and lighting via wireless communication. AWS IoT services are used for energy management, enabling efficient power consumption.

[0266] Users can check the operating status of these systems and receive real-time feedback on their health status via mobile communication devices and viewing / optical devices. The user interface uses React Native and is compatible with iOS and Android platforms. Health goal achievement status and incentive information for energy saving are displayed in an easy-to-understand manner.

[0267] For example, if the system analyzes that a user is fatigued, the room lighting will be adjusted to a relaxing brightness. An example of a prompt to the generative AI model for this system would be, "How can I calculate stress levels from health data collected using AWS Lambda?"

[0268] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0269] Step 1:

[0270] The server collects biometric data and environmental parameters from various sensors and wearable devices installed in the home. The input is real-time data from sensors and devices, and the output is a formatted dataset. The server stores the acquired data in a cloud-based database.

[0271] Step 2:

[0272] The server analyzes the collected data and uses the Python Pandas library to calculate evaluation metrics such as stress levels and comfort indices. The input consists of biometric data and environmental parameters retrieved from a database, while the output consists of user health metrics and environmental evaluation metrics.

[0273] Step 3:

[0274] The server generates control instructions based on the analysis results and sends them to electronic devices in the home. The inputs are health indicators and environmental assessment indicators, and the output is a control signal. Specifically, this allows for automatic adjustment of things like air conditioner temperature settings and lighting brightness.

[0275] Step 4:

[0276] The terminal receives control instructions from the server and operates the electronic devices accordingly. The input is the control signal from the server, and the output is the new configuration state of each device.

[0277] Step 5:

[0278] Users check the system's operating status and their own health indicators using mobile communication devices or viewing / optical equipment. Input is data displayed on the device, and output is feedback based on the user's understanding and choices.

[0279] Step 6:

[0280] The server optimizes data analysis algorithms based on user feedback and behavioral patterns, and uses a generative AI model to improve future operations and incentive provision. Inputs are user feedback data and previous data analysis results, while output is the updated algorithm model.

[0281] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0282] This invention is a system for automatically creating a healthy and comfortable environment within the home using various data. This system collects data in conjunction with electronic devices and sensors in the home and adjusts the environment based on the user's health and emotional state. By including an emotion engine, it can also operate while considering the user's psychological comfort. To implement this invention, a server, terminal, emotion engine, and user function as the respective elements.

[0283] The server collects health data, environmental data, as well as voice and video data from various electronic devices and sensors within the home. In particular, the emotion engine analyzes the user's emotions using this data and generates emotion data. As a result, it is possible to estimate the current psychological state of the user.

[0284] For example, when the emotion engine determines that the user is in a high-stress state for a long time, the server automatically adjusts the environment to a lighting setting for stress reduction. It can also change the music playlist and send an instruction to the terminal to play more relaxing music.

[0285] The terminal receives the control instructions sent from the server and performs effective energy management by automatically adjusting the states of home appliances and lighting. For example, it optimizes the temperature setting of the air conditioner and supplies power only for the necessary time using wireless power supply.

[0286] The user can receive the feedback provided by the server, which includes information on the transition of the emotional state, health status, and energy efficiency. Thus, the user can review their lifestyle and obtain guidelines for improvement.

[0287] In this way, the present invention is a system that supports a comfortable and efficient life by considering both the user's health status and emotional state and optimizing the indoor environment.

[0288] The following describes the processing flow.

[0289] Step 1:

[0290] The server collects health data, environmental data, voice data, and video data in real time from various sensors and electronic devices within the home. This data collection is scheduled based on the user's lifestyle pattern and adjusted as appropriate.

[0291] Step 2:

[0292] The server sends the collected data to the emotion engine, which analyzes the user's emotional state. The emotion engine evaluates whether the user is stressed or relaxed through voice and facial expression analysis, and generates emotional data.

[0293] Step 3:

[0294] The server combines the generated emotional and health data to determine the optimal environment settings for the user. For example, if it determines that the user needs to relax, the server will instruct the system to change the lighting to warmer colors and play relaxing music.

[0295] Step 4:

[0296] The terminal receives control instructions from the server and adjusts home appliances and lighting systems. This allows it to perform actions such as changing the temperature of the air conditioner or playing relaxing music on a music player as needed. Efficient energy management is also implemented through wireless power supply.

[0297] Step 5:

[0298] Users receive feedback from the server via their smart devices. This feedback includes their current emotional state, health indicators, and energy usage information, allowing users to objectively evaluate their lifestyle habits.

[0299] Step 6:

[0300] The server applies an incentive system based on the analysis data from the emotion engine, notifying users of points and benefits to promote healthy lifestyle habits. This is expected to increase user engagement and sustained use.

[0301] (Example 2)

[0302] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0303] In order to pursue a comfortable life within a home, flexible environmental adjustment according to the health and emotional states of individual residents is necessary. However, in conventional technologies, the capabilities of individual emotion analysis and dynamic environmental control are limited, making it difficult to achieve the true comfort of users. Furthermore, although optimization of energy consumption is also important, systems capable of fine monitoring and control in real time have been limited.

[0304] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0305] In this invention, the server includes means for collecting biometric data and ambient environmental data from measurement devices within a home, means for analyzing the collected data and estimating individual psychological and physical states, and means for adjusting the settings of the information processing device based on the analysis results and optimizing the indoor environment within the home. Thereby, flexible flexible environmental adjustment in real time with respect to the health and emotional states of residents and efficient management of energy consumption become possible.

[0306] The "measurement device within a home" is a device installed within a home for collecting biometric data and ambient environmental data. [[ID=第十七]]

[0307] "Biometric data" refers to information regarding the health and physiological states of users, including heart rate, body temperature, and the like.

[0308] "Ambient environmental data" is information indicating environmental conditions such as indoor temperature, humidity, and light quantity.

[0309] "Analysis" is a process of analyzing and evaluating information using the collected data to estimate the psychological and physical states of individual users.

[0310] An "information processing device" is an electronic device used to control the environment based on various data and instructions, and specifically includes household electrical appliances and lighting equipment.

[0311] "Wireless power transfer technology" is a technology that supplies power without using cables, and in most cases utilizes electromagnetic induction or electromagnetic resonance.

[0312] An "incentive" is something that provides users with benefits or incentives for biometric monitoring or energy consumption.

[0313] "Sequential monitoring" refers to the act of continuously observing and recording data as time progresses.

[0314] For this invention to be implemented, it is essential that the server, terminal, and user function in coordination with each other. The server efficiently collects biometric and ambient environmental data from in-home measuring devices. For this purpose, temperature sensors, humidity sensors, heart rate monitors, etc., are used. Specifically, it is recommended to use a general-purpose small computer or a specialized data acquisition appliance to centrally manage the data using a connected network.

[0315] The server implements advanced data analysis techniques to analyze the collected data. Machine learning libraries using programming languages ​​such as Python are employed here. This analysis is crucial for estimating the user's psychological and physical state.

[0316] The terminal adjusts the settings of the home's information processing devices based on analysis results from the server. Specifically, it improves user comfort by sending control signals to smart home appliances and lighting systems. It utilizes smart device APIs to automatically perform actions such as adjusting air conditioner temperature settings and changing lighting color tones.

[0317] Users experience the resulting environmental changes and receive feedback. This feedback includes improvements in energy efficiency and analysis of their health status through biometric monitoring. This allows users to obtain useful information to optimize their lifestyle.

[0318] For example, if a user returns home after working for a long time and the system analyzes that their heart rate and body temperature are high, the server will send instructions to the terminal to adjust the environment to a more relaxing state. This might include changing the lighting to warmer colors, playing soothing music, and adjusting the air conditioning to provide a comfortable temperature.

[0319] Examples of prompts to input into a generative AI model include instructions such as, "Please suggest optimal environment settings based on the user's current emotional state." These prompts help guide the AI ​​in making adjustments that are appropriate for the user.

[0320] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0321] Step 1:

[0322] The server collects biometric and environmental data from in-home measurement devices. Input data includes room temperature from a temperature sensor, humidity from a humidity sensor, and heart rate from a heart rate monitor. This data is received via the network and recorded in a database. The server also receives and centrally manages data periodically transmitted from sensors, and performs a process to verify data integrity. The output is organized biometric and environmental data.

[0323] Step 2:

[0324] The server processes the collected data using a machine learning library for analysis. The input includes biometric and environmental data organized in Step 1. The machine learning model analyzes the data to estimate the user's psychological and physical state. Specifically, it preprocesses the data and inputs it into an emotion analysis model to classify stress levels and health status. The output is the estimated results of the user's emotional and health status.

[0325] Step 3:

[0326] The server generates instructions to adjust the settings of the information processing device based on the analysis results. The input is the estimated results of the user's emotional and health states obtained in step 2. Based on the analysis results, it generates prompt statements to determine how the environment should be adjusted and inputs them into the generating AI model. The model then generates instructions for the optimal environment settings. The output consists of specific environment adjustment instructions, such as lighting color, music selection, and air conditioning settings.

[0327] Step 4:

[0328] The terminal executes environmental adjustment instructions sent from the server. The input is the environmental adjustment instructions generated in step 3. The terminal calls smart home APIs to change the temperature settings of air conditioners, uses music streaming services to play specific music playlists, and controls the lighting system to change the color tone. The output is the realization of the adjusted indoor environment, which is a setting that leads to improved user comfort.

[0329] Step 5:

[0330] The user experiences a tuned environment and receives feedback from the server. The inputs are the changes in the indoor environment realized in step 4 and the feedback information from the server. The feedback includes analysis information on energy efficiency and health status. Based on this, the user attempts to improve their lifestyle. The output is the awareness gained from the feedback and the actions taken to improve their lifestyle.

[0331] (Application Example 2)

[0332] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0333] In modern urban life, managing stress both inside and outside the home and maintaining a comfortable environment are crucial, but effectively managing these based on the emotional and health states of individual users is difficult. Furthermore, even in smart cities, providing information and managing energy to optimize residents' living environments is complex, necessitating more integrated and efficient systems.

[0334] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0335] In this invention, the server includes information gathering means for collecting health and environmental information from various electronic devices and detectors within the home, analysis means for analyzing the collected information and evaluating the health and environmental conditions, and urban information linking means for cooperating with smartphones and computer vision devices to provide information on stress-reducing spots and urban services. This makes it possible to provide information in an integrated manner based on the user's health and emotional state, and to optimize the environment inside and outside the home.

[0336] "Information gathering means" refers to a mechanism for collecting health information and environmental information from various electronic devices and detectors within the home.

[0337] "Analysis means" refers to a mechanism for analyzing collected information and evaluating the user's health status and environmental conditions.

[0338] A "control mechanism" is a system that optimizes the operation of electronic devices based on the results of analysis and adjusts the environment inside and outside the home.

[0339] An "energy management means" is a mechanism for controlling the energy supply to electronic devices through wireless energy supply.

[0340] A "notification mechanism" is a mechanism for communicating information to provide users with rewards related to energy and health status.

[0341] A "city information linkage system" is a mechanism that works in conjunction with smartphones and computer vision devices to provide users with information on stress-reducing spots and urban services.

[0342] This invention is an integrated system for providing a comfortable living environment both inside and outside the home, based on the user's health and emotional state. Specific embodiments are described below.

[0343] The server collects user health and environmental information from a wide variety of electronic devices and detectors installed in the home. This includes temperature sensors, humidity sensors, voice input devices, and video input devices. The server uses Python and Raspberry Pi to analyze this data. As an analysis method, it uses the natural language processing library NLTK and the machine learning framework TensorFlow to estimate the user's psychological and physiological state.

[0344] Using these analysis results, the device controls various household devices to provide an optimal environment. For example, it can change the brightness of lights or play specific music. Furthermore, as an energy management tool, it optimizes energy consumption and supplies energy at the necessary times. This function works in conjunction with energy management software and runs on a Raspberry Pi.

[0345] Furthermore, through urban information sharing mechanisms, the system provides users with real-time information on stress-reducing spots and urban services using smartphones and computer vision devices. This function allows users to receive information, for example, about relaxation events in nearby parks or availability at the nearest cafe.

[0346] Users receive feedback from the server. This feedback includes information on changes in emotional state, health history, and energy efficiency. Based on this information, users can reflect on their lifestyle habits and make improvements as needed.

[0347] For example, if a user is determined to be stressed immediately after waking up in the morning, the server will provide information on smooth commuting routes within their residential area and cafeterias best suited for breakfast, so that they can start their daily life more quickly.

[0348] Example prompt: "If a user is determined to be experiencing stress, what activities or suggestions would be effective? Please provide specific examples."

[0349] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0350] Step 1:

[0351] The server collects health and environmental information from electronic devices and detectors within the home. This includes data such as temperature, humidity, sound, and video. The input data is obtained from each sensor and sent to the server in JSON format. The server stores this data in a database.

[0352] Step 2:

[0353] The server analyzes the collected data. It utilizes a natural language processing library (NLTK) and a machine learning framework (TensorFlow) to estimate the user's psychological and physiological state. The input data consists of information obtained from sensors, and an emotion engine is used to output the emotional state as a profile.

[0354] Step 3:

[0355] The terminal controls electronic devices in the home based on analysis results from the server. Specifically, it adjusts the brightness and color temperature of lighting and selects relaxing music on a music player. It receives analysis results as input and transmits operation instructions to each home appliance using an optimization algorithm.

[0356] Step 4:

[0357] As an energy management tool, the server monitors energy consumption in real time and supplies energy only when needed. Input energy data is obtained from smart meters, and a time-based energy allocation plan is generated as output.

[0358] Step 5:

[0359] Using urban information sharing technology, the server connects with smartphones and computer vision devices to provide users with information on stress-reducing spots and urban services. It receives the user's location information and current emotional profile as input, and notifies them of the most suitable service information as output.

[0360] Step 6:

[0361] The user receives feedback from the server, which includes information on changes in emotional state, health history, and energy efficiency. The input is feedback data from the server, and the output is the visualization of this information within the application.

[0362] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0363] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0364] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0365] [Third Embodiment]

[0366] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0367] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0368] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0369] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0370] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0371] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0372] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0373] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0374] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0375] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0376] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0377] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0378] This invention is a system that automatically creates a healthy and comfortable environment by collecting data from various electronic devices placed in the home, analyzing it in real time, and more. The main components of this system include a server, terminals, and users, and it is effective only when all these elements work together in coordination.

[0379] The server periodically collects health and environmental data from various electronic devices and sensors within the home. This includes heart rate data from smartwatches and environmental information obtained from room temperature and humidity sensors. The server analyzes this data using analytical tools to evaluate the user's health status and the comfort level of the environment.

[0380] For example, the server assesses the user's stress level based on their heart rate data and sends instructions to the terminal to adjust the room temperature and lighting accordingly. It also uses environmental information to change the air conditioner's temperature setting or adjust the lighting brightness to provide the user with the optimal environment.

[0381] The terminal receives control instructions from the server and manages the energy supply to home appliances wirelessly. This enables efficient use of electricity and reduces energy consumption. For example, it can adjust the power supply according to lighting usage and supply power only when needed, thereby improving energy efficiency.

[0382] Users receive feedback on their health status and energy efficiency based on the server's analysis. This includes providing incentives; for example, points are awarded for achieving health goals, which are then reflected in their next electricity bill.

[0383] This invention, through the aforementioned components and their interactions, enables the realization of a system that automatically controls the home environment and maintains health and comfort.

[0384] The following describes the processing flow.

[0385] Step 1:

[0386] The server collects health and environmental data from various electronic devices and sensors within the home. This data includes the user's heart rate obtained from a smartwatch and indoor environmental information from temperature and humidity sensors. The server centrally manages this data and stores it as foundational data for analysis.

[0387] Step 2:

[0388] The server analyzes the collected data to assess health status and environmental comfort. The generating AI analyzes heart rate variability to estimate the user's stress level. From temperature and humidity data, it determines the level of comfort in the room and derives the optimal environment for that location.

[0389] Step 3:

[0390] Based on the analysis results, the server sends control instructions to the terminal to adjust the home environment. For example, if the user's stress level is high, it may instruct the terminal to play relaxation music or change the air conditioner setting to a comfortable temperature.

[0391] Step 4:

[0392] The terminal receives control instructions from the server and appropriately controls home appliances and lighting. To ensure efficient energy consumption, the terminal adjusts wireless power supply according to the operating status of the appliances. The terminal also notifies the user of energy warnings as needed.

[0393] Step 5:

[0394] Users receive feedback from the server, including changes in their health status and energy efficiency results. Based on this feedback, users can gain guidance for improving their daily lifestyle and be further motivated by receiving incentive information.

[0395] (Example 1)

[0396] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0397] There is a challenge in achieving efficient energy use while maintaining health and comfort within the home. Furthermore, automatic environmental adjustments based on users' stress levels and other health conditions are insufficient, creating a need for solutions optimized for individual lifestyles.

[0398] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0399] In this invention, the server includes information gathering means for collecting biometric and environmental data, evaluation means for analyzing the collected data to evaluate health status and environmental conditions, and adjustment means for optimizing the operation of the equipment and adjusting the environment based on the evaluation results. This makes it possible to construct a system that dynamically adjusts the home environment according to the user's health status and lifestyle while enabling efficient energy use.

[0400] "Information gathering means" refers to methods for collecting biometric and environmental data from various devices within the home.

[0401] "Evaluation means" refers to methods for analyzing collected biological and environmental data to evaluate health status and environmental conditions.

[0402] "Adjustment means" are methods for optimizing the operation of equipment and adjusting the home environment based on evaluation results.

[0403] A "power supply management system" is a means of controlling the power supply to household appliances through wireless power supply.

[0404] "Notification means" refers to means of providing users with rewards related to electricity and health management.

[0405] In an embodiment of this invention, the system includes three main elements: a server, a terminal, and a user, each of which operates in cooperation with one another.

[0406] The server collects biometric and environmental data from various electronic devices and sensors within the home. Specifically, it acquires heart rate data from wearable devices such as smartwatches and collects data on indoor temperature and humidity from environmental sensors. This data is stored in a database on the server.

[0407] Next, the server uses software to analyze the collected data. Specifically, it utilizes libraries such as Python's Pandas and NumPy to analyze heart rate variability and statistically evaluate environmental information. This evaluation clarifies the user's health status and environmental conditions.

[0408] Based on the evaluation results, the server creates and sends control instructions to the terminal to optimize the home environment. For example, if the user's stress level is high, it will issue instructions to lower the air conditioner temperature appropriately and change the lighting color to a warm, relaxing color. This control is made possible through efficient device operation via an in-home IoT hub or similar device.

[0409] The terminal receives instructions from the server and manages the power supply via wireless communication. The terminal adjusts the power requirements of household appliances, enabling them to operate with the minimum necessary energy. For example, it can adjust lighting usage time and brightness to optimize energy consumption.

[0410] Users receive feedback on their health status and energy conservation based on the server's analysis results. Through a dedicated application, users can check incentive information, such as points earned by achieving health goals being reflected in their next electricity bill.

[0411] For example, if a user exercises regularly, heart rate data is collected, and a decrease in stress levels is detected, the system will automatically provide an environment that promotes relaxation. It is also possible to use a generative AI model to generate optimal prompt messages tailored to the user's lifestyle. Another example of an AI-powered prompt message is: "My home smart system uses my heart rate data to monitor my stress levels and adjusts the room temperature and lighting to make me comfortable. Could you please give me some specific advice on how to reduce stress?"

[0412] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0413] Step 1:

[0414] The server collects data from various devices and sensors. Inputs include heart rate data from smartwatches and environmental data from temperature and humidity sensors. This data is aggregated on the server. Data processing includes format conversion and noise reduction, and the output is stored in a database.

[0415] Step 2:

[0416] The server analyzes the collected data. The input data consists of heart rate and environmental data stored in a database on the server. Using analysis tools such as Python's Pandas and NumPy, the server calculates stress levels from time-series heart rate data and determines the average and fluctuation values ​​of environmental data. The analysis results output indicators for evaluating the user's stress level and the indoor environment.

[0417] Step 3:

[0418] The server generates control instructions based on the analysis results. The inputs are the evaluation results of heart rate and environmental data. Using control logic, it generates instructions such as lowering the air conditioner temperature or changing the lighting to a warmer color if the stress level is high. These control instructions are generated as output and sent to the terminal.

[0419] Step 4:

[0420] The terminal processes control instructions received from the server. The input is specific appliance control instructions from the server. Based on the received instructions, the terminal sends signals to each appliance via the IoT hub, adjusting the operation of appliances such as air conditioners and lighting. This provides the user with an optimal living environment, which is the output of the processing.

[0421] Step 5:

[0422] Users receive feedback from the server. This feedback includes their health status assessment and energy-saving performance. This information is communicated to the user via a dedicated app. The notifications include reports on health achievements and points awarded based on energy savings. As a result, users can increase their motivation for managing their health and saving energy.

[0423] (Application Example 1)

[0424] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0425] In modern homes, it is becoming common to manage environmental and biometric data using various electronic devices and sensors. However, these systems operate independently, and integrated data handling and effective feedback to users are not fully realized. Furthermore, improving energy efficiency and providing concrete incentives for residents' health management remain challenges. In addition, there is a need for means to appropriately control the living environment through real-time data monitoring.

[0426] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0427] In this invention, the server includes data collection means for collecting biometric data and environmental parameters from various electronic devices within the home, analysis means for analyzing the collected data and evaluating health and environmental conditions, and energy management means for controlling the power supply to the electronic devices via wireless energy supply. This enables integrated data management and optimized environmental control throughout the entire residence. Furthermore, residents can monitor their data and receive incentives through mobile communication terminals and viewing / optical equipment, enabling them to pursue a comfortable and healthy living environment.

[0428] "Data collection means" refers to devices that acquire biometric data and environmental parameters from various electronic devices and sensors installed in the home.

[0429] "Analysis means" refers to a processing device used to evaluate health status and environmental conditions based on collected biological data and environmental parameters.

[0430] A "control device" is a device that optimizes the operation of electronic devices in the home and adjusts the living environment based on the analyzed results.

[0431] An "energy management device" is a device that controls the power supply to electronic devices in a home through wireless energy supply.

[0432] A "notification device" is a device that informs users of incentives related to energy and health management.

[0433] "Monitoring means" refers to devices that allow residents to check data and incentive information through mobile communication terminals or viewing / optical equipment.

[0434] A system implementing this invention includes data acquisition means, analysis means, control means, energy management means, notification means, and monitoring means.

[0435] The server collects biometric data and environmental parameters from various electronic devices and sensors within the home. This includes data from wearable devices to acquire health data and information from temperature and humidity sensors to understand environmental conditions. A cloud service database (e.g., Amazon Web Services RDS) is used for data collection, and the information is updated regularly.

[0436] The server analyzes the collected data and uses Pandas, a Python data processing library, to evaluate health status and comfort indices. This allows it to calculate the health status and comfort level of residents and generate data to provide an optimal environment.

[0437] The terminal controls electronic devices within the home based on instructions from the server, providing an optimal living environment. Specifically, it can dynamically adjust settings for air conditioners and lighting via wireless communication. AWS IoT services are used for energy management, enabling efficient power consumption.

[0438] Users can check the operating status of these systems and receive real-time feedback on their health status via mobile communication devices and viewing / optical devices. The user interface uses React Native and is compatible with iOS and Android platforms. Health goal achievement status and incentive information for energy saving are displayed in an easy-to-understand manner.

[0439] For example, if the system analyzes that a user is fatigued, the room lighting will be adjusted to a relaxing brightness. An example of a prompt to the generative AI model for this system would be, "How can I calculate stress levels from health data collected using AWS Lambda?"

[0440] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0441] Step 1:

[0442] The server collects biometric data and environmental parameters from various sensors and wearable devices installed in the home. The input is real-time data from sensors and devices, and the output is a formatted dataset. The server stores the acquired data in a cloud-based database.

[0443] Step 2:

[0444] The server analyzes the collected data and uses the Python Pandas library to calculate evaluation metrics such as stress levels and comfort indices. The input consists of biometric data and environmental parameters retrieved from a database, while the output consists of user health metrics and environmental evaluation metrics.

[0445] Step 3:

[0446] The server generates control instructions based on the analysis results and sends them to electronic devices in the home. The inputs are health indicators and environmental assessment indicators, and the output is a control signal. Specifically, this allows for automatic adjustment of things like air conditioner temperature settings and lighting brightness.

[0447] Step 4:

[0448] The terminal receives control instructions from the server and operates the electronic devices accordingly. The input is the control signal from the server, and the output is the new configuration state of each device.

[0449] Step 5:

[0450] Users check the system's operating status and their own health indicators using mobile communication devices or viewing / optical equipment. Input is data displayed on the device, and output is feedback based on the user's understanding and choices.

[0451] Step 6:

[0452] The server optimizes data analysis algorithms based on user feedback and behavioral patterns, and uses a generative AI model to improve future operations and incentive provision. Inputs are user feedback data and previous data analysis results, while output is the updated algorithm model.

[0453] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0454] This invention is a system for automatically creating a healthy and comfortable environment within the home using various data. This system collects data in conjunction with electronic devices and sensors in the home and adjusts the environment based on the user's health and emotional state. By including an emotion engine, it can also operate while considering the user's psychological comfort. To implement this invention, a server, terminal, emotion engine, and user function as the respective elements.

[0455] The server collects health and environmental data, as well as audio and video data, from various electronic devices and sensors within the home. In particular, the emotion engine uses this data to analyze the user's emotions and generate emotional data. As a result, it can estimate the user's current psychological state.

[0456] For example, if the emotion engine determines that a user has been under high stress for an extended period, the server can automatically adjust the environment to reduce stress by changing the lighting settings. It can also change the music playlist and send a command to the device to play more relaxing music.

[0457] The terminal receives control instructions from the server and automatically adjusts the status of home appliances and lighting to perform effective energy management. For example, it optimizes the temperature setting of an air conditioner and supplies power only when needed using wireless power supply.

[0458] Users can receive feedback from the server, which includes information on their emotional state, health status, and energy efficiency. This allows users to review their lifestyle habits and gain guidance for improvement.

[0459] Thus, the present invention is a system that supports a comfortable and efficient lifestyle by optimizing the indoor environment while taking into account both the user's physical and emotional state.

[0460] The following describes the processing flow.

[0461] Step 1:

[0462] The server collects health data, environmental data, audio data, and video data in real time from various sensors and electronic devices within the home. This data collection is scheduled and adjusted as needed based on the user's lifestyle patterns.

[0463] Step 2:

[0464] The server sends the collected data to the emotion engine, which analyzes the user's emotional state. The emotion engine evaluates whether the user is stressed or relaxed through voice and facial expression analysis, and generates emotional data.

[0465] Step 3:

[0466] The server combines the generated emotional and health data to determine the optimal environment settings for the user. For example, if it determines that the user needs to relax, the server will instruct the system to change the lighting to warmer colors and play relaxing music.

[0467] Step 4:

[0468] The terminal receives control instructions from the server and adjusts home appliances and lighting systems. This allows it to perform actions such as changing the temperature of the air conditioner or playing relaxing music on a music player as needed. Efficient energy management is also implemented through wireless power supply.

[0469] Step 5:

[0470] Users receive feedback from the server via their smart devices. This feedback includes their current emotional state, health indicators, and energy usage information, allowing users to objectively evaluate their lifestyle habits.

[0471] Step 6:

[0472] The server applies an incentive system based on the analysis data from the emotion engine, notifying users of points and benefits to promote healthy lifestyle habits. This is expected to increase user engagement and sustained use.

[0473] (Example 2)

[0474] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0475] To achieve a comfortable life within the home, flexible environmental adjustments tailored to the health and emotional states of individual residents are necessary. However, conventional technologies have limited capabilities for individual emotional analysis and dynamic environmental control, making it difficult to realize true user comfort. Furthermore, while optimizing energy consumption is also important, systems capable of real-time, detailed monitoring and control have been limited.

[0476] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0477] In this invention, the server includes means for collecting biometric data and ambient environmental data from measuring devices within the home, means for analyzing the collected data and estimating the individual's psychological and physical state, and means for adjusting the settings of the information processing device based on the analysis results to optimize the indoor environment within the home. This enables flexible, real-time environmental adjustments to the health and emotional state of the residents, as well as efficient management of energy consumption.

[0478] A "household measuring device" is a device installed in a home to collect biological data and ambient environmental data.

[0479] "Biometric data" refers to information about the user's health and physiological state, including heart rate and body temperature.

[0480] "Environmental data" refers to information that indicates environmental conditions such as indoor temperature, humidity, and light intensity.

[0481] "Analysis" is the process of using collected data to analyze and evaluate information, and to estimate the psychological and physical state of individual users.

[0482] An "information processing device" is an electronic device used to control the environment based on various data and instructions, and specifically includes household electrical appliances and lighting equipment.

[0483] "Wireless power transfer technology" is a technology that supplies power without using cables, and in most cases utilizes electromagnetic induction or electromagnetic resonance.

[0484] An "incentive" is something that provides users with benefits or incentives for biometric monitoring or energy consumption.

[0485] "Sequential monitoring" refers to the act of continuously observing and recording data as time progresses.

[0486] For this invention to be implemented, it is essential that the server, terminal, and user function in coordination with each other. The server efficiently collects biometric and ambient environmental data from in-home measuring devices. For this purpose, temperature sensors, humidity sensors, heart rate monitors, etc., are used. Specifically, it is recommended to use a general-purpose small computer or a specialized data acquisition appliance to centrally manage the data using a connected network.

[0487] The server implements advanced data analysis techniques to analyze the collected data. Machine learning libraries using programming languages ​​such as Python are employed here. This analysis is crucial for estimating the user's psychological and physical state.

[0488] The terminal adjusts the settings of the home's information processing devices based on analysis results from the server. Specifically, it improves user comfort by sending control signals to smart home appliances and lighting systems. It utilizes smart device APIs to automatically perform actions such as adjusting air conditioner temperature settings and changing lighting color tones.

[0489] Users experience the resulting environmental changes and receive feedback. This feedback includes improvements in energy efficiency and analysis of their health status through biometric monitoring. This allows users to obtain useful information to optimize their lifestyle.

[0490] For example, if a user returns home after working for a long time and the system analyzes that their heart rate and body temperature are high, the server will send instructions to the terminal to adjust the environment to a more relaxing state. This might include changing the lighting to warmer colors, playing soothing music, and adjusting the air conditioning to provide a comfortable temperature.

[0491] Examples of prompts to input into a generative AI model include instructions such as, "Please suggest optimal environment settings based on the user's current emotional state." These prompts help guide the AI ​​in making adjustments that are appropriate for the user.

[0492] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0493] Step 1:

[0494] The server collects biometric and environmental data from in-home measurement devices. Input data includes room temperature from a temperature sensor, humidity from a humidity sensor, and heart rate from a heart rate monitor. This data is received via the network and recorded in a database. The server also receives and centrally manages data periodically transmitted from sensors, and performs a process to verify data integrity. The output is organized biometric and environmental data.

[0495] Step 2:

[0496] The server processes the collected data using a machine learning library for analysis. The input includes biometric and environmental data organized in Step 1. The machine learning model analyzes the data to estimate the user's psychological and physical state. Specifically, it preprocesses the data and inputs it into an emotion analysis model to classify stress levels and health status. The output is the estimated results of the user's emotional and health status.

[0497] Step 3:

[0498] The server generates instructions to adjust the settings of the information processing device based on the analysis results. The input is the estimated results of the user's emotional and health states obtained in step 2. Based on the analysis results, it generates prompt statements to determine how the environment should be adjusted and inputs them into the generating AI model. The model then generates instructions for the optimal environment settings. The output consists of specific environment adjustment instructions, such as lighting color, music selection, and air conditioning settings.

[0499] Step 4:

[0500] The terminal executes environmental adjustment instructions sent from the server. The input is the environmental adjustment instructions generated in step 3. The terminal calls smart home APIs to change the temperature settings of air conditioners, uses music streaming services to play specific music playlists, and controls the lighting system to change the color tone. The output is the realization of the adjusted indoor environment, which is a setting that leads to improved user comfort.

[0501] Step 5:

[0502] The user experiences a tuned environment and receives feedback from the server. The inputs are the changes in the indoor environment realized in step 4 and the feedback information from the server. The feedback includes analysis information on energy efficiency and health status. Based on this, the user attempts to improve their lifestyle. The output is the awareness gained from the feedback and the actions taken to improve their lifestyle.

[0503] (Application Example 2)

[0504] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0505] In modern urban life, managing stress both inside and outside the home and maintaining a comfortable environment are crucial, but effectively managing these based on the emotional and health states of individual users is difficult. Furthermore, even in smart cities, providing information and managing energy to optimize residents' living environments is complex, necessitating more integrated and efficient systems.

[0506] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0507] In this invention, the server includes information gathering means for collecting health and environmental information from various electronic devices and detectors within the home, analysis means for analyzing the collected information and evaluating the health and environmental conditions, and urban information linking means for cooperating with smartphones and computer vision devices to provide information on stress-reducing spots and urban services. This makes it possible to provide information in an integrated manner based on the user's health and emotional state, and to optimize the environment inside and outside the home.

[0508] "Information gathering means" refers to a mechanism for collecting health information and environmental information from various electronic devices and detectors within the home.

[0509] "Analysis means" refers to a mechanism for analyzing collected information and evaluating the user's health status and environmental conditions.

[0510] A "control mechanism" is a system that optimizes the operation of electronic devices based on the results of analysis and adjusts the environment inside and outside the home.

[0511] An "energy management means" is a mechanism for controlling the energy supply to electronic devices through wireless energy supply.

[0512] A "notification mechanism" is a mechanism for communicating information to provide users with rewards related to energy and health status.

[0513] A "city information linkage system" is a mechanism that works in conjunction with smartphones and computer vision devices to provide users with information on stress-reducing spots and urban services.

[0514] This invention is an integrated system for providing a comfortable living environment both inside and outside the home, based on the user's health and emotional state. Specific embodiments are described below.

[0515] The server collects user health and environmental information from a wide variety of electronic devices and detectors installed in the home. This includes temperature sensors, humidity sensors, voice input devices, and video input devices. The server uses Python and Raspberry Pi to analyze this data. As an analysis method, it uses the natural language processing library NLTK and the machine learning framework TensorFlow to estimate the user's psychological and physiological state.

[0516] Using these analysis results, the device controls various household devices to provide an optimal environment. For example, it can change the brightness of lights or play specific music. Furthermore, as an energy management tool, it optimizes energy consumption and supplies energy at the necessary times. This function works in conjunction with energy management software and runs on a Raspberry Pi.

[0517] Furthermore, through urban information sharing mechanisms, the system provides users with real-time information on stress-reducing spots and urban services using smartphones and computer vision devices. This function allows users to receive information, for example, about relaxation events in nearby parks or availability at the nearest cafe.

[0518] Users receive feedback from the server. This feedback includes information on changes in emotional state, health history, and energy efficiency. Based on this information, users can reflect on their lifestyle habits and make improvements as needed.

[0519] For example, if a user is determined to be stressed immediately after waking up in the morning, the server will provide information on smooth commuting routes within their residential area and cafeterias best suited for breakfast, so that they can start their daily life more quickly.

[0520] Example prompt: "If a user is determined to be experiencing stress, what activities or suggestions would be effective? Please provide specific examples."

[0521] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0522] Step 1:

[0523] The server collects health and environmental information from electronic devices and detectors within the home. This includes data such as temperature, humidity, sound, and video. The input data is obtained from each sensor and sent to the server in JSON format. The server stores this data in a database.

[0524] Step 2:

[0525] The server analyzes the collected data. It utilizes a natural language processing library (NLTK) and a machine learning framework (TensorFlow) to estimate the user's psychological and physiological state. The input data consists of information obtained from sensors, and an emotion engine is used to output the emotional state as a profile.

[0526] Step 3:

[0527] The terminal controls electronic devices in the home based on analysis results from the server. Specifically, it adjusts the brightness and color temperature of lighting and selects relaxing music on a music player. It receives analysis results as input and transmits operation instructions to each home appliance using an optimization algorithm.

[0528] Step 4:

[0529] As an energy management tool, the server monitors energy consumption in real time and supplies energy only when needed. Input energy data is obtained from smart meters, and a time-based energy allocation plan is generated as output.

[0530] Step 5:

[0531] Using urban information sharing technology, the server connects with smartphones and computer vision devices to provide users with information on stress-reducing spots and urban services. It receives the user's location information and current emotional profile as input, and notifies them of the most suitable service information as output.

[0532] Step 6:

[0533] The user receives feedback from the server, which includes information on changes in emotional state, health history, and energy efficiency. The input is feedback data from the server, and the output is the visualization of this information within the application.

[0534] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0535] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0536] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0537] [Fourth Embodiment]

[0538] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0539] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0540] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0541] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0542] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0543] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0544] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0545] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0546] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0547] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0548] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0549] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0550] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0551] This invention is a system that automatically creates a healthy and comfortable environment by collecting data from various electronic devices placed in the home, analyzing it in real time, and more. The main components of this system include a server, terminals, and users, and it is effective only when all these elements work together in coordination.

[0552] The server periodically collects health and environmental data from various electronic devices and sensors within the home. This includes heart rate data from smartwatches and environmental information obtained from room temperature and humidity sensors. The server analyzes this data using analytical tools to evaluate the user's health status and the comfort level of the environment.

[0553] For example, the server assesses the user's stress level based on their heart rate data and sends instructions to the terminal to adjust the room temperature and lighting accordingly. It also uses environmental information to change the air conditioner's temperature setting or adjust the lighting brightness to provide the user with the optimal environment.

[0554] The terminal receives control instructions from the server and manages the energy supply to home appliances wirelessly. This enables efficient use of electricity and reduces energy consumption. For example, it can adjust the power supply according to lighting usage and supply power only when needed, thereby improving energy efficiency.

[0555] Users receive feedback on their health status and energy efficiency based on the server's analysis. This includes providing incentives; for example, points are awarded for achieving health goals, which are then reflected in their next electricity bill.

[0556] This invention, through the aforementioned components and their interactions, enables the realization of a system that automatically controls the home environment and maintains health and comfort.

[0557] The following describes the processing flow.

[0558] Step 1:

[0559] The server collects health and environmental data from various electronic devices and sensors within the home. This data includes the user's heart rate obtained from a smartwatch and indoor environmental information from temperature and humidity sensors. The server centrally manages this data and stores it as foundational data for analysis.

[0560] Step 2:

[0561] The server analyzes the collected data to assess health status and environmental comfort. The generating AI analyzes heart rate variability to estimate the user's stress level. From temperature and humidity data, it determines the level of comfort in the room and derives the optimal environment for that location.

[0562] Step 3:

[0563] Based on the analysis results, the server sends control instructions to the terminal to adjust the home environment. For example, if the user's stress level is high, it may instruct the terminal to play relaxation music or change the air conditioner setting to a comfortable temperature.

[0564] Step 4:

[0565] The terminal receives control instructions from the server and appropriately controls home appliances and lighting. To ensure efficient energy consumption, the terminal adjusts wireless power supply according to the operating status of the appliances. The terminal also notifies the user of energy warnings as needed.

[0566] Step 5:

[0567] Users receive feedback from the server, including changes in their health status and energy efficiency results. Based on this feedback, users can gain guidance for improving their daily lifestyle and be further motivated by receiving incentive information.

[0568] (Example 1)

[0569] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0570] There is a challenge in achieving efficient energy use while maintaining health and comfort within the home. Furthermore, automatic environmental adjustments based on users' stress levels and other health conditions are insufficient, creating a need for solutions optimized for individual lifestyles.

[0571] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0572] In this invention, the server includes information gathering means for collecting biometric and environmental data, evaluation means for analyzing the collected data to evaluate health status and environmental conditions, and adjustment means for optimizing the operation of the equipment and adjusting the environment based on the evaluation results. This makes it possible to construct a system that dynamically adjusts the home environment according to the user's health status and lifestyle while enabling efficient energy use.

[0573] "Information gathering means" refers to methods for collecting biometric and environmental data from various devices within the home.

[0574] "Evaluation means" refers to methods for analyzing collected biological and environmental data to evaluate health status and environmental conditions.

[0575] "Adjustment means" are methods for optimizing the operation of equipment and adjusting the home environment based on evaluation results.

[0576] A "power supply management system" is a means of controlling the power supply to household appliances through wireless power supply.

[0577] "Notification means" refers to means of providing users with rewards related to electricity and health management.

[0578] In an embodiment of this invention, the system includes three main elements: a server, a terminal, and a user, each of which operates in cooperation with one another.

[0579] The server collects biometric and environmental data from various electronic devices and sensors within the home. Specifically, it acquires heart rate data from wearable devices such as smartwatches and collects data on indoor temperature and humidity from environmental sensors. This data is stored in a database on the server.

[0580] Next, the server uses software to analyze the collected data. Specifically, it utilizes libraries such as Python's Pandas and NumPy to analyze heart rate variability and statistically evaluate environmental information. This evaluation clarifies the user's health status and environmental conditions.

[0581] Based on the evaluation results, the server creates and sends control instructions to the terminal to optimize the home environment. For example, if the user's stress level is high, it will issue instructions to lower the air conditioner temperature appropriately and change the lighting color to a warm, relaxing color. This control is made possible through efficient device operation via an in-home IoT hub or similar device.

[0582] The terminal receives instructions from the server and manages the power supply via wireless communication. The terminal adjusts the power requirements of household appliances, enabling them to operate with the minimum necessary energy. For example, it can adjust lighting usage time and brightness to optimize energy consumption.

[0583] Users receive feedback on their health status and energy conservation based on the server's analysis results. Through a dedicated application, users can check incentive information, such as points earned by achieving health goals being reflected in their next electricity bill.

[0584] For example, if a user exercises regularly, heart rate data is collected, and a decrease in stress levels is detected, the system will automatically provide an environment that promotes relaxation. It is also possible to use a generative AI model to generate optimal prompt messages tailored to the user's lifestyle. Another example of an AI-powered prompt message is: "My home smart system uses my heart rate data to monitor my stress levels and adjusts the room temperature and lighting to make me comfortable. Could you please give me some specific advice on how to reduce stress?"

[0585] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0586] Step 1:

[0587] The server collects data from various devices and sensors. Inputs include heart rate data from smartwatches and environmental data from temperature and humidity sensors. This data is aggregated on the server. Data processing includes format conversion and noise reduction, and the output is stored in a database.

[0588] Step 2:

[0589] The server analyzes the collected data. The input data consists of heart rate and environmental data stored in a database on the server. Using analysis tools such as Python's Pandas and NumPy, the server calculates stress levels from time-series heart rate data and determines the average and fluctuation values ​​of environmental data. The analysis results output indicators for evaluating the user's stress level and the indoor environment.

[0590] Step 3:

[0591] The server generates control instructions based on the analysis results. The inputs are the evaluation results of heart rate and environmental data. Using control logic, it generates instructions such as lowering the air conditioner temperature or changing the lighting to a warmer color if the stress level is high. These control instructions are generated as output and sent to the terminal.

[0592] Step 4:

[0593] The terminal processes control instructions received from the server. The input is specific appliance control instructions from the server. Based on the received instructions, the terminal sends signals to each appliance via the IoT hub, adjusting the operation of appliances such as air conditioners and lighting. This provides the user with an optimal living environment, which is the output of the processing.

[0594] Step 5:

[0595] Users receive feedback from the server. This feedback includes their health status assessment and energy-saving performance. This information is communicated to the user via a dedicated app. The notifications include reports on health achievements and points awarded based on energy savings. As a result, users can increase their motivation for managing their health and saving energy.

[0596] (Application Example 1)

[0597] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0598] In modern homes, it is becoming common to manage environmental and biometric data using various electronic devices and sensors. However, these systems operate independently, and integrated data handling and effective feedback to users are not fully realized. Furthermore, improving energy efficiency and providing concrete incentives for residents' health management remain challenges. In addition, there is a need for means to appropriately control the living environment through real-time data monitoring.

[0599] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0600] In this invention, the server includes data collection means for collecting biometric data and environmental parameters from various electronic devices within the home, analysis means for analyzing the collected data and evaluating health and environmental conditions, and energy management means for controlling the power supply to the electronic devices via wireless energy supply. This enables integrated data management and optimized environmental control throughout the entire residence. Furthermore, residents can monitor their data and receive incentives through mobile communication terminals and viewing / optical equipment, enabling them to pursue a comfortable and healthy living environment.

[0601] "Data collection means" refers to devices that acquire biometric data and environmental parameters from various electronic devices and sensors installed in the home.

[0602] "Analysis means" refers to a processing device used to evaluate health status and environmental conditions based on collected biological data and environmental parameters.

[0603] A "control device" is a device that optimizes the operation of electronic devices in the home and adjusts the living environment based on the analyzed results.

[0604] An "energy management device" is a device that controls the power supply to electronic devices in a home through wireless energy supply.

[0605] A "notification device" is a device that informs users of incentives related to energy and health management.

[0606] "Monitoring means" refers to devices that allow residents to check data and incentive information through mobile communication terminals or viewing / optical equipment.

[0607] A system implementing this invention includes data acquisition means, analysis means, control means, energy management means, notification means, and monitoring means.

[0608] The server collects biometric data and environmental parameters from various electronic devices and sensors within the home. This includes data from wearable devices to acquire health data and information from temperature and humidity sensors to understand environmental conditions. A cloud service database (e.g., Amazon Web Services RDS) is used for data collection, and the information is updated regularly.

[0609] The server analyzes the collected data and uses Pandas, a Python data processing library, to evaluate health status and comfort indices. This allows it to calculate the health status and comfort level of residents and generate data to provide an optimal environment.

[0610] The terminal controls electronic devices within the home based on instructions from the server, providing an optimal living environment. Specifically, it can dynamically adjust settings for air conditioners and lighting via wireless communication. AWS IoT services are used for energy management, enabling efficient power consumption.

[0611] Users can check the operating status of these systems and receive real-time feedback on their health status via mobile communication devices and viewing / optical devices. The user interface uses React Native and is compatible with iOS and Android platforms. Health goal achievement status and incentive information for energy saving are displayed in an easy-to-understand manner.

[0612] For example, if the system analyzes that a user is fatigued, the room lighting will be adjusted to a relaxing brightness. An example of a prompt to the generative AI model for this system would be, "How can I calculate stress levels from health data collected using AWS Lambda?"

[0613] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0614] Step 1:

[0615] The server collects biometric data and environmental parameters from various sensors and wearable devices installed in the home. The input is real-time data from sensors and devices, and the output is a formatted dataset. The server stores the acquired data in a cloud-based database.

[0616] Step 2:

[0617] The server analyzes the collected data and uses the Python Pandas library to calculate evaluation metrics such as stress levels and comfort indices. The input consists of biometric data and environmental parameters retrieved from a database, while the output consists of user health metrics and environmental evaluation metrics.

[0618] Step 3:

[0619] The server generates control instructions based on the analysis results and sends them to electronic devices in the home. The inputs are health indicators and environmental assessment indicators, and the output is a control signal. Specifically, this allows for automatic adjustment of things like air conditioner temperature settings and lighting brightness.

[0620] Step 4:

[0621] The terminal receives control instructions from the server and operates the electronic devices accordingly. The input is the control signal from the server, and the output is the new configuration state of each device.

[0622] Step 5:

[0623] Users check the system's operating status and their own health indicators using mobile communication devices or viewing / optical equipment. Input is data displayed on the device, and output is feedback based on the user's understanding and choices.

[0624] Step 6:

[0625] The server optimizes data analysis algorithms based on user feedback and behavioral patterns, and uses a generative AI model to improve future operations and incentive provision. Inputs are user feedback data and previous data analysis results, while output is the updated algorithm model.

[0626] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0627] This invention is a system for automatically creating a healthy and comfortable environment within the home using various data. This system collects data in conjunction with electronic devices and sensors in the home and adjusts the environment based on the user's health and emotional state. By including an emotion engine, it can also operate while considering the user's psychological comfort. To implement this invention, a server, terminal, emotion engine, and user function as the respective elements.

[0628] The server collects health and environmental data, as well as audio and video data, from various electronic devices and sensors within the home. In particular, the emotion engine uses this data to analyze the user's emotions and generate emotional data. As a result, it can estimate the user's current psychological state.

[0629] For example, if the emotion engine determines that a user has been under high stress for an extended period, the server can automatically adjust the environment to reduce stress by changing the lighting settings. It can also change the music playlist and send a command to the device to play more relaxing music.

[0630] The terminal receives control instructions from the server and automatically adjusts the status of home appliances and lighting to perform effective energy management. For example, it optimizes the temperature setting of an air conditioner and supplies power only when needed using wireless power supply.

[0631] Users can receive feedback from the server, which includes information on their emotional state, health status, and energy efficiency. This allows users to review their lifestyle habits and gain guidance for improvement.

[0632] Thus, the present invention is a system that supports a comfortable and efficient lifestyle by optimizing the indoor environment while taking into account both the user's physical and emotional state.

[0633] The following describes the processing flow.

[0634] Step 1:

[0635] The server collects health data, environmental data, audio data, and video data in real time from various sensors and electronic devices within the home. This data collection is scheduled and adjusted as needed based on the user's lifestyle patterns.

[0636] Step 2:

[0637] The server sends the collected data to the emotion engine, which analyzes the user's emotional state. The emotion engine evaluates whether the user is stressed or relaxed through voice and facial expression analysis, and generates emotional data.

[0638] Step 3:

[0639] The server combines the generated emotional and health data to determine the optimal environment settings for the user. For example, if it determines that the user needs to relax, the server will instruct the system to change the lighting to warmer colors and play relaxing music.

[0640] Step 4:

[0641] The terminal receives control instructions from the server and adjusts home appliances and lighting systems. This allows it to perform actions such as changing the temperature of the air conditioner or playing relaxing music on a music player as needed. Efficient energy management is also implemented through wireless power supply.

[0642] Step 5:

[0643] Users receive feedback from the server via their smart devices. This feedback includes their current emotional state, health indicators, and energy usage information, allowing users to objectively evaluate their lifestyle habits.

[0644] Step 6:

[0645] The server applies an incentive system based on the analysis data from the emotion engine, notifying users of points and benefits to promote healthy lifestyle habits. This is expected to increase user engagement and sustained use.

[0646] (Example 2)

[0647] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0648] To achieve a comfortable life within the home, flexible environmental adjustments tailored to the health and emotional states of individual residents are necessary. However, conventional technologies have limited capabilities for individual emotional analysis and dynamic environmental control, making it difficult to realize true user comfort. Furthermore, while optimizing energy consumption is also important, systems capable of real-time, detailed monitoring and control have been limited.

[0649] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0650] In this invention, the server includes means for collecting biometric data and ambient environmental data from measuring devices within the home, means for analyzing the collected data and estimating the individual's psychological and physical state, and means for adjusting the settings of the information processing device based on the analysis results to optimize the indoor environment within the home. This enables flexible, real-time environmental adjustments to the health and emotional state of the residents, as well as efficient management of energy consumption.

[0651] A "household measuring device" is a device installed in a home to collect biological data and ambient environmental data.

[0652] "Biometric data" refers to information about the user's health and physiological state, including heart rate and body temperature.

[0653] "Environmental data" refers to information that indicates environmental conditions such as indoor temperature, humidity, and light intensity.

[0654] "Analysis" is the process of using collected data to analyze and evaluate information, and to estimate the psychological and physical state of individual users.

[0655] An "information processing device" is an electronic device used to control the environment based on various data and instructions, and specifically includes household electrical appliances and lighting equipment.

[0656] "Wireless power transfer technology" is a technology that supplies power without using cables, and in most cases utilizes electromagnetic induction or electromagnetic resonance.

[0657] An "incentive" is something that provides users with benefits or incentives for biometric monitoring or energy consumption.

[0658] "Sequential monitoring" refers to the act of continuously observing and recording data as time progresses.

[0659] For this invention to be implemented, it is essential that the server, terminal, and user function in coordination with each other. The server efficiently collects biometric and ambient environmental data from in-home measuring devices. For this purpose, temperature sensors, humidity sensors, heart rate monitors, etc., are used. Specifically, it is recommended to use a general-purpose small computer or a specialized data acquisition appliance to centrally manage the data using a connected network.

[0660] The server implements advanced data analysis techniques to analyze the collected data. Machine learning libraries using programming languages ​​such as Python are employed here. This analysis is crucial for estimating the user's psychological and physical state.

[0661] The terminal adjusts the settings of the home's information processing devices based on analysis results from the server. Specifically, it improves user comfort by sending control signals to smart home appliances and lighting systems. It utilizes smart device APIs to automatically perform actions such as adjusting air conditioner temperature settings and changing lighting color tones.

[0662] Users experience the resulting environmental changes and receive feedback. This feedback includes improvements in energy efficiency and analysis of their health status through biometric monitoring. This allows users to obtain useful information to optimize their lifestyle.

[0663] For example, if a user returns home after working for a long time and the system analyzes that their heart rate and body temperature are high, the server will send instructions to the terminal to adjust the environment to a more relaxing state. This might include changing the lighting to warmer colors, playing soothing music, and adjusting the air conditioning to provide a comfortable temperature.

[0664] Examples of prompts to input into a generative AI model include instructions such as, "Please suggest optimal environment settings based on the user's current emotional state." These prompts help guide the AI ​​in making adjustments that are appropriate for the user.

[0665] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0666] Step 1:

[0667] The server collects biometric and environmental data from in-home measurement devices. Input data includes room temperature from a temperature sensor, humidity from a humidity sensor, and heart rate from a heart rate monitor. This data is received via the network and recorded in a database. The server also receives and centrally manages data periodically transmitted from sensors, and performs a process to verify data integrity. The output is organized biometric and environmental data.

[0668] Step 2:

[0669] The server processes the collected data using a machine learning library for analysis. The input includes biometric and environmental data organized in Step 1. The machine learning model analyzes the data to estimate the user's psychological and physical state. Specifically, it preprocesses the data and inputs it into an emotion analysis model to classify stress levels and health status. The output is the estimated results of the user's emotional and health status.

[0670] Step 3:

[0671] The server generates instructions to adjust the settings of the information processing device based on the analysis results. The input is the estimated results of the user's emotional and health states obtained in step 2. Based on the analysis results, it generates prompt statements to determine how the environment should be adjusted and inputs them into the generating AI model. The model then generates instructions for the optimal environment settings. The output consists of specific environment adjustment instructions, such as lighting color, music selection, and air conditioning settings.

[0672] Step 4:

[0673] The terminal executes environmental adjustment instructions sent from the server. The input is the environmental adjustment instructions generated in step 3. The terminal calls smart home APIs to change the temperature settings of air conditioners, uses music streaming services to play specific music playlists, and controls the lighting system to change the color tone. The output is the realization of the adjusted indoor environment, which is a setting that leads to improved user comfort.

[0674] Step 5:

[0675] The user experiences a tuned environment and receives feedback from the server. The inputs are the changes in the indoor environment realized in step 4 and the feedback information from the server. The feedback includes analysis information on energy efficiency and health status. Based on this, the user attempts to improve their lifestyle. The output is the awareness gained from the feedback and the actions taken to improve their lifestyle.

[0676] (Application Example 2)

[0677] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0678] In modern urban life, managing stress both inside and outside the home and maintaining a comfortable environment are crucial, but effectively managing these based on the emotional and health states of individual users is difficult. Furthermore, even in smart cities, providing information and managing energy to optimize residents' living environments is complex, necessitating more integrated and efficient systems.

[0679] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0680] In this invention, the server includes information gathering means for collecting health and environmental information from various electronic devices and detectors within the home, analysis means for analyzing the collected information and evaluating the health and environmental conditions, and urban information linking means for cooperating with smartphones and computer vision devices to provide information on stress-reducing spots and urban services. This makes it possible to provide information in an integrated manner based on the user's health and emotional state, and to optimize the environment inside and outside the home.

[0681] "Information gathering means" refers to a mechanism for collecting health information and environmental information from various electronic devices and detectors within the home.

[0682] "Analysis means" refers to a mechanism for analyzing collected information and evaluating the user's health status and environmental conditions.

[0683] A "control mechanism" is a system that optimizes the operation of electronic devices based on the results of analysis and adjusts the environment inside and outside the home.

[0684] An "energy management means" is a mechanism for controlling the energy supply to electronic devices through wireless energy supply.

[0685] A "notification mechanism" is a mechanism for communicating information to provide users with rewards related to energy and health status.

[0686] A "city information linkage system" is a mechanism that works in conjunction with smartphones and computer vision devices to provide users with information on stress-reducing spots and urban services.

[0687] This invention is an integrated system for providing a comfortable living environment both inside and outside the home, based on the user's health and emotional state. Specific embodiments are described below.

[0688] The server collects user health and environmental information from a wide variety of electronic devices and detectors installed in the home. This includes temperature sensors, humidity sensors, voice input devices, and video input devices. The server uses Python and Raspberry Pi to analyze this data. As an analysis method, it uses the natural language processing library NLTK and the machine learning framework TensorFlow to estimate the user's psychological and physiological state.

[0689] Using these analysis results, the device controls various household devices to provide an optimal environment. For example, it can change the brightness of lights or play specific music. Furthermore, as an energy management tool, it optimizes energy consumption and supplies energy at the necessary times. This function works in conjunction with energy management software and runs on a Raspberry Pi.

[0690] Furthermore, through urban information sharing mechanisms, the system provides users with real-time information on stress-reducing spots and urban services using smartphones and computer vision devices. This function allows users to receive information, for example, about relaxation events in nearby parks or availability at the nearest cafe.

[0691] Users receive feedback from the server. This feedback includes information on changes in emotional state, health history, and energy efficiency. Based on this information, users can reflect on their lifestyle habits and make improvements as needed.

[0692] For example, if a user is determined to be stressed immediately after waking up in the morning, the server will provide information on smooth commuting routes within their residential area and cafeterias best suited for breakfast, so that they can start their daily life more quickly.

[0693] Example prompt: "If a user is determined to be experiencing stress, what activities or suggestions would be effective? Please provide specific examples."

[0694] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0695] Step 1:

[0696] The server collects health and environmental information from electronic devices and detectors within the home. This includes data such as temperature, humidity, sound, and video. The input data is obtained from each sensor and sent to the server in JSON format. The server stores this data in a database.

[0697] Step 2:

[0698] The server analyzes the collected data. It utilizes a natural language processing library (NLTK) and a machine learning framework (TensorFlow) to estimate the user's psychological and physiological state. The input data consists of information obtained from sensors, and an emotion engine is used to output the emotional state as a profile.

[0699] Step 3:

[0700] The terminal controls electronic devices in the home based on analysis results from the server. Specifically, it adjusts the brightness and color temperature of lighting and selects relaxing music on a music player. It receives analysis results as input and transmits operation instructions to each home appliance using an optimization algorithm.

[0701] Step 4:

[0702] As an energy management tool, the server monitors energy consumption in real time and supplies energy only when needed. Input energy data is obtained from smart meters, and a time-based energy allocation plan is generated as output.

[0703] Step 5:

[0704] Using urban information sharing technology, the server connects with smartphones and computer vision devices to provide users with information on stress-reducing spots and urban services. It receives the user's location information and current emotional profile as input, and notifies them of the most suitable service information as output.

[0705] Step 6:

[0706] The user receives feedback from the server, which includes information on changes in emotional state, health history, and energy efficiency. The input is feedback data from the server, and the output is the visualization of this information within the application.

[0707] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0708] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0709] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0710] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0711] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0712] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0713] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0714] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0715] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0716] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0717] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0718] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0719] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0720] 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.

[0721] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0722] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0723] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0724] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0725] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0726] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0727] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0728] The following is further disclosed regarding the embodiments described above.

[0729] (Claim 1)

[0730] A data collection method for collecting health data and environmental data from various electronic devices in the home,

[0731] Analytical means for analyzing the collected data and evaluating health status and environmental status,

[0732] Based on the results of the above analysis, a control means for optimizing the operation of the electronic device and adjusting the environment within the home,

[0733] A power management means that controls the power supply to the electronic device by wireless power supply,

[0734] A notification means for providing users with incentives related to the aforementioned power and health management,

[0735] A system that includes this.

[0736] (Claim 2)

[0737] The system according to claim 1, characterized in that the data collection means has a function to dynamically change the data collection schedule according to the user's lifestyle pattern.

[0738] (Claim 3)

[0739] The system according to claim 1, characterized in that the power management means includes a function to monitor power consumption in real time in order to optimize energy consumption within the household.

[0740] "Example 1"

[0741] (Claim 1)

[0742] Information collection means for collecting biometric and environmental data from various devices in the home,

[0743] An evaluation means for analyzing the collected data and evaluating health status and environmental conditions,

[0744] Based on the results of the aforementioned evaluation, an adjustment means for optimizing the operation of the equipment and adjusting the environment within the home,

[0745] A power supply management means that controls the power supply to the equipment by wireless power supply,

[0746] A notification means for providing the user with the aforementioned electricity and health management-related compensation,

[0747] A means of evaluating stress levels using biometric data and dynamically adjusting environmental characteristics,

[0748] A system that includes this.

[0749] (Claim 2)

[0750] The system according to claim 1, characterized in that the information gathering means has a function to dynamically change the data collection plan according to the user's lifestyle.

[0751] (Claim 3)

[0752] The system according to claim 1, characterized in that the supply management means includes a function to monitor electricity usage in real time in order to optimize energy use within the household.

[0753] "Application Example 1"

[0754] (Claim 1)

[0755] A data collection means for collecting biological data and environmental parameters from various electronic devices in the home,

[0756] An analytical means for analyzing the collected data and evaluating health status and environmental status,

[0757] A control means for optimizing the operation of the electronic device and adjusting the environment inside the residence based on the results of the analysis,

[0758] Energy management means for controlling the power supply to the electronic device by wireless energy supply,

[0759] A notification means for providing users with incentives related to energy and health management,

[0760] A monitoring means that allows residents to check data and incentive information through mobile communication devices and viewing / optical equipment,

[0761] A system that includes this.

[0762] (Claim 2)

[0763] The system according to claim 1, characterized in that the data collection means has a function to dynamically change the data collection schedule according to the user's behavior pattern.

[0764] (Claim 3)

[0765] The system according to claim 1, characterized in that the energy management means includes a function to monitor energy usage in real time in order to optimize energy consumption within the residence.

[0766] "Example 2 of combining an emotion engine"

[0767] (Claim 1)

[0768] A means for collecting biological data and ambient environmental data from measuring devices within the home,

[0769] The collected data is analyzed and means are used to estimate the individual's psychological and physical state.

[0770] A means for adjusting the settings of the information processing device based on the analysis results and optimizing the indoor environment within the home,

[0771] Means for managing the power supply to the information processing device using wireless power transfer technology,

[0772] Means for informing the user of the aforementioned benefits related to power and biomonitoring,

[0773] A system that includes this.

[0774] (Claim 2)

[0775] The system according to claim 1, characterized in that the collection means has a function to adjust the collection time in accordance with the user's behavior pattern.

[0776] (Claim 3)

[0777] The system according to claim 1, characterized in that the management means has a function to continuously monitor consumption in order to improve household energy use.

[0778] "Application example 2 when combining with an emotional engine"

[0779] (Claim 1)

[0780] Information gathering means for collecting health information and environmental information from various electronic devices and detectors in the home,

[0781] An analytical means for analyzing the collected information and evaluating health status and environmental status,

[0782] Based on the results of the analysis, a control means optimizes the operation of the electronic device and adjusts the environment inside and outside the home,

[0783] Energy management means for controlling the supply of energy to the electronic device by wireless energy supply,

[0784] A notification means for providing users with the aforementioned energy and health-related rewards,

[0785] A means of urban information sharing that works in conjunction with smartphones and computer vision devices to provide information on stress-reducing spots and urban services,

[0786] A system that includes this.

[0787] (Claim 2)

[0788] The system according to claim 1, characterized in that the information gathering means has a function to dynamically change the information gathering plan according to the user's lifestyle.

[0789] (Claim 3)

[0790] The system according to claim 1, characterized in that the energy management means includes a function for monitoring energy consumption in real time in order to optimize energy use within the household. [Explanation of Symbols]

[0791] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data collection means for collecting biological data and environmental parameters from various electronic devices in the home, An analytical means for analyzing the collected data and evaluating health status and environmental status, A control means for optimizing the operation of the electronic device and adjusting the environment inside the residence based on the results of the analysis, Energy management means for controlling the power supply to the electronic device by wireless energy supply, A notification means for providing users with incentives related to energy and health management, A monitoring means that allows residents to check data and incentive information through mobile communication devices and viewing / optical equipment, A system that includes this.

2. The system according to claim 1, characterized in that the data collection means has a function to dynamically change the data collection schedule according to the user's behavior pattern.

3. The system according to claim 1, characterized in that the energy management means includes a function to monitor energy usage in real time in order to optimize energy consumption within the residence.

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