System

Abstract

To provide a system capable of providing a comfortable living environment while suppressing the waste of energy by optimizing the use of electric equipment and resources according to an environment and the health condition of a user.SOLUTION: A means for acquiring operation status and setting information from various electrical devices in a house, a means for acquiring usage amounts of water and gas, a means for acquiring personal health data from a wearable device, a means for acquiring position information and activity data from a mobile terminal, a means for acquiring temperature and weather forecast via the Internet, an analysis means including a generation AI for predicting an operation pattern of the electrical devices using an optimization algorithm based on the acquired data and performing optimal adjustment, and a means for notifying a user of an optimization result obtained by the analysis means.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Recently, electricity bills and other resource consumption in homes have skyrocketed, increasing environmental and economic burdens. Effective and sustainable solutions are needed to address this issue. Conventional home environment optimization systems only utilize limited devices and data sources, and are limited to controlling individual appliances, making it difficult to achieve comprehensive optimization. Another issue is the difficulty of dynamic control that takes into account the user's health status and external environmental information. Therefore, a system is needed that can reduce energy waste while providing a comfortable living environment for users. [Means for solving the problem]

[0005] To address this issue, we provide a system that includes: means for acquiring operating status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile device; and means for acquiring temperature and weather forecasts via the Internet. The system also includes an analysis means (including a generation AI) that uses an optimization algorithm based on the acquired data to predict the operating patterns of the electrical appliances and make optimal adjustments; means for notifying the user of the optimization results obtained by the analysis means; and means for automatically controlling each electrical appliance based on the user's approval. This system optimizes the use of electrical appliances and resources in accordance with the environment and the user's health condition, reducing energy waste and providing a comfortable living environment.

[0006] "Electrical equipment" refers to various household appliances that use electricity to operate within a home, including air conditioners, water heaters, air purifiers, lighting, etc.

[0007] The "operating status" indicates the operating status of the electrical equipment, including whether the equipment is currently operating or stopped, and its operating mode and setting parameters.

[0008] "Setting information" refers to various parameters that are used when an electrical device operates, such as temperature settings, operation modes (cooling, heating, etc.), and operation times.

[0009] "Usage" refers to data on water and gas consumption measured in real time or periodically.

[0010] A "wearable device" is a device worn on the body that primarily collects data such as heart rate, sleep time, and exercise volume for health management and fitness tracking.

[0011] "Health data" refers to data about an individual's physiological condition collected from wearable devices and other health management devices, including, for example, heart rate, sleep duration, and exercise volume.

[0012] "Mobile device" refers to a portable device, such as a mobile phone, smartphone, or tablet, that has the ability to collect and transmit location and activity data.

[0013] "Activity data" refers to data relating to the user's movements and exercise acquired from a mobile device, and specifically includes location information, number of steps, distance traveled, and the like.

[0014] "Temperature" is external weather information obtained via the Internet, and indicates the outside air temperature in a specific area and at a specific time.

[0015] "Weather forecast" refers to meteorological information provided via the Internet, and is predictive data on current and future weather conditions, including the probability of precipitation, humidity, wind speed, etc.

[0016] "Optimization algorithm" refers to a program that includes calculation methods and logic for optimizing the operating patterns of electrical equipment based on collected data.

[0017] "Generative AI" refers to a system that uses artificial intelligence technology to analyze and predict data, and then performs various optimizations based on the results.

[0018] "Analysis means" refers to the system components and programs that analyze collected data using generation AI and predict optimal operating patterns.

[0019] The "notification means" is a means for notifying the user of optimization suggestions based on the analysis results, and specifically uses voice, text, notification messages, etc.

[0020] "Control means" refers to system components and programs that automatically operate each electrical device based on user approval and adjust it to an optimal setting state. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0023] First, the terms used in the following description will be explained.

[0024] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0025] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0026] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0027] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0032] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0034] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] The present invention is a system for optimizing the home environment efficiently and comfortably, integrating various electrical appliances, devices, and external information to perform optimization. The system includes the following steps and elements:

[0043] Data collection

[0044] Data collection from devices:

[0045] The server continuously collects operating status and setting information from each electrical device in the home (e.g., air conditioner, water heater, air purifier, lighting). This allows the server to grasp the on / off status, temperature setting, operation mode, etc. of each device in real time. It also collects usage data from water and gas meters.

[0046] Data collection from wearable devices:

[0047] The server acquires the user's health data from the wearable device (e.g., smart watch), specifically, heart rate, sleep time, exercise amount, etc., and grasps the user's health condition.

[0048] Mobile data collection:

[0049] The server obtains location information and activity data from the mobile device (e.g., smartphone), which determines whether the user is at home or out, and also tracks the amount of activity, such as the number of steps taken and the distance traveled.

[0050] Data collection from the Internet:

[0051] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[0052] Data Analysis and Optimization

[0053] Data preprocessing and analysis:

[0054] The server inputs the collected data into the AI ​​generator for specific analysis. After removing noise and normalizing the data, the AI ​​calculates the optimal operating pattern for electrical equipment, taking into account the user's past behavioral patterns, health status, and external environment.

[0055] Use of optimization algorithms:

[0056] The server uses generative AI to run algorithms that optimize the use of electrical equipment and resources, automatically determining things like air conditioner temperature settings and water heater operation schedules, enabling efficient energy use.

[0057] Suggestions and User Notifications

[0058] Optimization results suggestion:

[0059] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification may be displayed on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[0060] Automatic Control

[0061] User consent and control:

[0062] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it, for example, to change the temperature setting of an air conditioner, and then monitors and confirms the results.

[0063] Specific examples

[0064] 1. Morning scenario:

[0065] When the user wakes up in the morning, the server retrieves the user's sleep time and heart rate data from the smartwatch and, based on this, suggests optimizing the air conditioner temperature setting to maintain a comfortable room temperature. If the user approves, the air conditioner temperature setting will be automatically adjusted.

[0066] 2. Shower scenario:

[0067] The server detects when a user is about to take a shower from their smartphone and checks the current temperature of the water heater. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees, and if the user agrees, the set temperature is automatically adjusted.

[0068] This system enables efficient energy use and provides users with a comfortable living environment. Repeating these steps will help build a sustainable living environment.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] The server acquires operating status and setting information from each electrical device in the home. For example, it acquires the current temperature setting, operating mode, and operating status from the air conditioner. Similarly, it acquires the current temperature setting and operating status from the water heater.

[0072] Step 2:

[0073] The server acquires and records usage data from the water meter and gas meter, for example, the amount of water and gas used every hour.

[0074] Step 3:

[0075] The server acquires the user's health data from the wearable device, specifically information such as heart rate, sleep time, and exercise amount, and uses this information to understand the user's current health condition.

[0076] Step 4:

[0077] The server acquires location information and activity data from the mobile device, confirms whether the user is at home or out, and also acquires activity data such as the number of steps taken and distance traveled.

[0078] Step 5:

[0079] The server receives weather forecasts and temperature information via the Internet, providing information such as the maximum and minimum temperatures, probability of precipitation, and humidity for the day.

[0080] Step 6:

[0081] The server denoises and normalizes the collected data, correcting outliers and missing values, and formatting the data into a form that is easy to analyze.

[0082] Step 7:

[0083] The server inputs the formatted data into the AI ​​generator for analysis. Specifically, it predicts the optimal operating pattern for electrical equipment by taking into account the user's past behavioral patterns, health status, and current environmental information.

[0084] Step 8:

[0085] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[0086] Step 9:

[0087] The server compiles all the analysis results and generates a notification that suggests optimization to the user, such as "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[0088] Step 10:

[0089] The device sends a notification to the user's mobile device and displays the optimization suggestion, and the user can check the notification and choose to accept or reject the suggestion.

[0090] Step 11:

[0091] If the user selects approval, the server sends an instruction to the electrical appliance to automatically control it, for example, to an air conditioner to change the temperature setting.

[0092] Step 12:

[0093] The server checks whether electrical equipment is working properly, for example, checking whether the air conditioner has started operating at the specified temperature setting.

[0094] Step 13:

[0095] The server continuously monitors the operating status and energy consumption of each electrical device. If an abnormality is detected, it notifies the user and suggests further optimization if necessary.

[0096] By repeating this series of steps, the home's environment and energy consumption can be dynamically optimized.

[0097] Example 1

[0098] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0099] The efficient operation of various electrical appliances and devices in homes and the maintenance of a comfortable and healthy living environment for individuals are required. The present invention solves the problem of improving energy efficiency and ensuring user convenience by providing a system that manages these in an integrated manner and proposes and executes optimal operation patterns.

[0100] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0101] In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile device; means for acquiring temperature and weather forecasts via the Internet; analysis means including a generation AI that uses an optimization algorithm to predict operation patterns of the electrical appliances based on the acquired data and makes optimal adjustments; means for notifying the user of the optimization results obtained by the analysis means; means for automatically controlling each electrical appliance based on the user's approval; means for denoising and normalizing the collected data; means for integrating the operation status of the target appliances with external environmental data to calculate optimal operation patterns of the electrical appliances and generate proposals; and means for notifying the user of the generated proposals to the user's mobile device. This makes it possible to optimize the user's living environment and improve energy efficiency.

[0102] - "Various electrical appliances" refers to electrical machinery and equipment used in homes, such as air conditioners, water heaters, air purifiers, and lighting.

[0103] "Operating status" refers to information about whether an electrical device is currently operating or in what mode it is operating.

[0104] "Setting information" refers to information relating to operating conditions and parameters designated by the user for the electrical device, such as temperature settings and operation modes.

[0105] "Usage data" is information about the consumption of resources such as water and gas.

[0106] A "wearable device" is an electronic device that is designed to be worn by the user, and includes smartwatches and the like.

[0107] "Health data" is information that indicates the user's health condition, such as heart rate, sleep time, and amount of exercise.

[0108] A "mobile device" is a portable communication device such as a smartphone that is capable of collecting location information and activity data.

[0109] "Location information" is information about the current location obtained by the GPS function of the mobile terminal.

[0110] "Activity data" is information indicating the amount of physical activity of the user, such as the number of steps taken and the distance traveled.

[0111] "Temperature" refers to the temperature in the atmosphere, and is information indicating the temperature conditions of the external environment.

[0112] "Weather forecast" is information about upcoming weather changes and current weather.

[0113] An "optimization algorithm" is a mathematical method for calculating efficient operating patterns for electrical equipment based on collected data.

[0114] "Generative AI" is a type of artificial intelligence that uses machine learning and deep learning techniques to analyze data and generate optimal operating patterns.

[0115] "Analysis means" refers to the techniques and devices used to perform analysis based on collected data.

[0116] The "optimization result" is information that indicates an efficient method of using and operation pattern of the electrical equipment, derived by the analysis means.

[0117] "Notification means" refers to a means for informing the user of information, and includes notifications to smartphones, etc.

[0118] "Automatic control" is a mechanism for automatically adjusting the operation of each electrical device after obtaining user approval.

[0119] "Noise removal" is the process of removing unnecessary or erroneous data in data analysis.

[0120] "Normalization" is the process of converting the range of data to a certain scale.

[0121] The "suggestion content" is information about the settings and operation patterns of electrical appliances that are recommended to the user based on the optimization algorithm.

[0122] This invention is a system for optimizing the home environment efficiently and comfortably. The system integrates various electrical appliances, devices, and external information to perform optimization.

[0123] Data collection

[0124] Collecting data from devices

[0125] The server collects operating status and setting information from each electrical device in the home, such as the air conditioner, water heater, air purifier, and lighting. Specifically, it obtains data such as the air conditioner's on / off status, temperature setting, and operation mode. It also obtains usage data from water and gas meters.

[0126] Data collection from wearable devices

[0127] The server collects user health data from wearable devices such as smartwatches, including heart rate, sleep duration, and exercise volume.

[0128] Data collection from mobile devices

[0129] The server collects location information and activity data from mobile devices such as smartphones, which allows it to determine whether the user is at home or out, as well as the amount of activity such as the number of steps taken and distance traveled.

[0130] Data collection from the internet

[0131] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[0132] Data Analysis and Optimization

[0133] Data Preprocessing

[0134] The server performs noise removal and normalization on the various collected data. Specifically, it complements missing values ​​in the data and removes outliers. It also performs normalization to make the data range consistent. This is done using a data preprocessing library (e.g., pandas, NumPy).

[0135] Using generative AI models

[0136] The server uses a generative AI model to calculate the optimal operating pattern for each electrical device. Specifically, normalized data is input into the generative AI model (e.g., TensorFlow, PyTorch) to predict the optimal energy consumption pattern.

[0137] Suggestions and User Notifications

[0138] Optimization results suggestions

[0139] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification might be displayed on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree." This is done using a notification service (e.g., Firebase Cloud Messaging).

[0140] Automatic Control

[0141] User Authorization and Control

[0142] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it. For example, it sends an instruction to change the temperature setting of an air conditioner and then monitors and confirms the results. This is done using the smart home control API.

[0143] Specific examples

[0144] 1. Morning Scenario

[0145] The server receives the user's sleep data from the smartwatch and analyzes it together with the outside temperature data. As a result, it sends a notification to the smartphone suggesting that the current room temperature be raised by 1 degree. If the user approves, the server sends a command to change the set temperature to the air conditioner.

[0146] 2. Shower scenario

[0147] The server detects from the smartphone sensor that the user is about to take a shower. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees and notifies the smartphone. If the user agrees, the server sends a command to change the set temperature to the water heater.

[0148] Prompt Sentence Examples

[0149] Example prompt 1: Morning optimization suggestions

[0150] "Good morning. According to your recent sleep data, it appears that you have not been spending much time in deep sleep. Raising the current room temperature by 1 degree will help you wake up more comfortably. Would you like to change the air conditioner temperature setting?"

[0151] Example prompt 2: Shower optimization suggestions

[0152] "The outside temperature is dropping. We suggest you increase the water heater temperature by 2 degrees to make showering more comfortable. Would you like to do this?"

[0153] This makes it possible to use energy efficiently and provide users with a comfortable living environment.

[0154] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0155] Step 1:

[0156] Collecting data from devices

[0157] The server collects operating status and setting information from various electrical devices in the home. Specifically, it obtains information such as the air conditioner's on / off status, temperature setting, and operation mode. The server sends requests at regular intervals and receives current status information from the electrical devices.

[0158] Input: Request responses from various electrical devices

[0159] Output: Operational data of each device (on / off status, temperature setting, operation mode)

[0160] Step 2:

[0161] Data collection from wearable devices

[0162] The server collects user health data from wearable devices such as smartwatches, and periodically uploads the data from the wearable devices to the server.

[0163] Input: Health data from a smartwatch

[0164] Output: User's health data (heart rate, sleep time, exercise amount)

[0165] Step 3:

[0166] Data collection from mobile devices

[0167] The server collects location information and activity data from mobile devices such as smartphones, and determines whether the user is at home or out. The server periodically transmits the location information and activity data to the server using the mobile device's GPS and activity tracking functions.

[0168] Input: Location and activity data from your smartphone

[0169] Output: User location and activity data

[0170] Step 4:

[0171] Data collection from the internet

[0172] The server retrieves weather forecasts and current temperatures via the Internet, sends a request to the weather API, and stores the retrieved data internally.

[0173] Input: Request response from the weather API

[0174] Output: Weather forecast data and current temperature data

[0175] Step 5:

[0176] Data preprocessing and analysis

[0177] The server performs noise removal and normalization on the various collected data. Specifically, it complements missing values ​​in the collected data and removes outliers. It also performs normalization to make the data range consistent. This is done using a data preprocessing library (e.g., pandas, NumPy).

[0178] Input: Various collected data (electrical equipment operation data, health data, location information, weather data)

[0179] Output: Normalized data

[0180] Step 6:

[0181] Using generative AI models

[0182] The server uses a generative AI model to calculate the optimal operating pattern for each electrical device. The normalized data is input into the generative AI model (e.g., TensorFlow, PyTorch) to predict the optimal energy consumption pattern.

[0183] Input: Normalized data

[0184] Output: Optimized operating pattern

[0185] Step 7:

[0186] Optimization results suggestions

[0187] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification such as "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree" is displayed on the user's smartphone. This is achieved using a notification service (e.g., Firebase Cloud Messaging).

[0188] Input: Optimized operating pattern

[0189] Output: Proposal notification to user

[0190] Step 8:

[0191] User Authorization and Control

[0192] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it. For example, it sends an instruction to change the temperature setting of an air conditioner and then monitors and confirms the results. This is done using the smart home control API.

[0193] Input: User approval

[0194] Output: Control instructions to electrical devices

[0195] (Application example 1)

[0196] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0197] This invention relates to a system that comprehensively monitors and controls the operating status and environmental data of various equipment and machines in a factory, improving energy efficiency and optimizing productivity. Conventional systems manage each piece of equipment individually, without proper data integration or analysis, which often results in a lack of overall efficiency. Furthermore, insufficient coordination between each piece of equipment makes it difficult to optimize overall energy consumption. This leads to problems such as increased energy costs and reduced productivity.

[0198] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0199] In this invention, the server includes means for acquiring operation status and setting information from various electrical appliances in the home, means for acquiring water and gas usage, means for acquiring personal health data from a wearable device, means for acquiring location information and activity data from a mobile terminal, means for acquiring temperature and weather forecasts via the Internet, means for acquiring operation status and environmental data from various pieces of equipment in the factory, analysis means including a generation AI that uses an optimization algorithm based on the acquired data to predict the operation pattern of the factory equipment and make optimal adjustments, means for notifying workers of the optimization results obtained by the analysis means, and means for automatically controlling each piece of equipment based on the worker's approval, thereby enabling collaboration between equipment in the factory and optimization of energy consumption.

[0200] "Various electrical appliances in the home" refers to household electrical appliances such as air conditioners, water heaters, air purifiers, and lighting.

[0201] "Operating status" refers to information that indicates the status of each device, such as its on / off status, the currently set operating mode, and temperature setting.

[0202] "Setting information" refers to parameters and values ​​that are set in advance to control the operation of an electrical device.

[0203] "Water and gas usage" refers to data that indicates the amount of tap water and gas consumed within a home.

[0204] "Wearable devices" refers to electronic devices that can be worn by a user and that can collect health and activity data. Examples include smartwatches and fitness trackers.

[0205] "Health data" refers to data that includes information about an individual's health status, such as heart rate, sleep duration, and amount of exercise.

[0206] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[0207] "Location Information" means geographic location data obtained from a mobile or other device.

[0208] "Activity data" refers to data that includes information about the user's daily activities, such as the number of steps taken, distance traveled, and time spent at a destination.

[0209] "Temperature and weather forecast via the Internet" refers to current temperature and future weather forecast information obtained using an Internet connection.

[0210] "Various facilities within the factory" includes production facilities and environmental control devices used within the factory, such as robotic arms, conveyors, and HVAC systems.

[0211] "Environmental data" refers to data that includes information about the surrounding environment within a factory or home, such as temperature, humidity, and illuminance.

[0212] "Optimization algorithm" refers to an algorithm that calculates the best operation to achieve a specific goal based on collected data.

[0213] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and suggest optimal ways to operate devices and systems.

[0214] "Analysis means" refers to a device or process for analyzing collected data and outputting optimization results.

[0215] "Worker" refers to a person who performs work in a factory or other facility.

[0216] "Automatic control means" refers to a system that includes a control device or program for automatically changing the settings or operation of equipment based on the optimized results.

[0217] This invention is a system for efficiently and optimally managing and controlling various equipment and environments within a factory, and is implemented through the procedures of data collection, analysis, optimization, notification, and control from various equipment. This system includes the following procedures and elements.

[0218] Data collection

[0219] The server continuously collects operational status and setting information from various pieces of equipment in the factory (robot arms, conveyors, HVAC systems, etc.). This allows information such as the operating status, set temperature, and operating mode of each piece of equipment to be sent to the server in real time. Environmental data such as temperature, humidity, and illuminance are also collected via sensors.

[0220] Data Analysis and Optimization

[0221] The server uses a generative AI model to analyze the various collected data, removes noise and normalizes the data, and then calculates the optimal equipment operating pattern taking into account past operating patterns and environmental conditions.

[0222] Proposals and worker notifications

[0223] Based on the analysis results, the server will suggest optimization measures to the worker. For example, a notification such as "We recommend lowering the current room temperature by 2 degrees" will be displayed on the worker's device.

[0224] Automatic Control

[0225] Once the worker approves the optimization proposal, the server sends automatic control instructions to each piece of equipment, such as adjusting the robot arm's operating schedule or changing the temperature setting of the HVAC system.

[0226] Specific examples

[0227] 1. Production line optimization: The server collects robot arm movement data and proposes optimal movement timing and patterns. Once approved by the worker, the robot arm's movement pattern is automatically changed.

[0228] 2. Managing the factory environment: The server collects data from temperature and humidity sensors and makes recommendations to optimize the temperature and humidity settings of the HVAC system. Once the worker approves the recommendations, the HVAC system settings are automatically adjusted.

[0229] Hardware and software used

[0230] Hardware: Various sensors in the factory (temperature, humidity, light, etc.), robotic arms, HVAC systems, servers, and worker terminals.

[0231] Software: Data collection, analysis, notification and control program using Python. Interface with devices using REST API.

[0232] Prompt Sentence Examples

[0233] As an example, data is collected from a temperature sensor, and the prompt text sent by the server to the generative AI model when the temperature is 25 degrees and the humidity is 60% is shown below:

[0234] "Here is the environmental data for the factory. Temperature: 25°C, humidity: 60%. Please suggest the optimal operating pattern for each piece of equipment."

[0235] This system enables coordination between equipment within a factory and optimizes energy consumption, resulting in improved efficiency and cost reduction.

[0236] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0237] Step 1:

[0238] Starting data collection and acquiring input

[0239] The server collects real-time operational status and environmental data from various sensors and equipment in the factory. Specifically, it collects current temperature data from temperature sensors and current humidity data from humidity sensors. It also collects operational status and setting information from robotic arms and HVAC systems. This allows data on temperature, humidity, and equipment operational status to be collected and input to the server.

[0240] Step 2:

[0241] Data preprocessing and denoising

[0242] The server performs preprocessing on the collected data. In this step, it removes noise and normalizes the data. For example, if data obtained from a temperature sensor contains outliers, it removes them. The input is the collected environmental data and equipment data, and the output is the data that has been denoised and normalized.

[0243] Step 3:

[0244] Data input and analysis for generative AI models

[0245] The server inputs the preprocessed data into a generative AI model for analysis. The generative AI model used here predicts optimal equipment operating patterns based on past data and current conditions. For example, when temperature and humidity data is input, the optimal settings for an HVAC system are calculated based on that data. The input is noise-removed data, and the output is optimized equipment settings and operating patterns.

[0246] Step 4:

[0247] Notifying the workers of the analysis results

[0248] The server notifies the worker of optimization suggestions based on the analysis results. This notification is displayed on the worker's device. For example, a message such as "We recommend lowering the current room temperature by 2 degrees" is displayed. The input is the analysis result from the generative AI model, and the output is a notification message sent to the worker's device.

[0249] Step 5:

[0250] Operator approval and start of automatic control

[0251] When an operator approves an optimization proposal, the server sends automatic control instructions to each piece of equipment. For example, these instructions include changing the temperature setting of an HVAC system or adjusting the operation schedule of a robot arm. The input is the operator's approval, and the output is a control instruction for each piece of equipment.

[0252] Step 6:

[0253] Retrieval Monitoring and Feedback

[0254] After issuing the control command, the server monitors the equipment and environmental data again and re-optimizes as necessary. This allows for continuous optimization of equipment efficiency and energy consumption. The input is the latest operating status and environmental data, and the output is the re-optimized settings.

[0255] The above steps will enable coordination between equipment within the factory and optimize energy consumption, improving efficiency and reducing costs.

[0256] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0257] The present invention is a system for optimizing the home environment efficiently and comfortably, integrating various electrical appliances, devices, and external information to perform optimization. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, optimization can be performed that is adapted to the user's emotional state. This system includes the following procedures and elements.

[0258] Data collection

[0259] Data collection from devices:

[0260] The server collects operating status and setting information from each electrical device in the home (e.g., air conditioner, water heater, air purifier, lighting). This allows the server to grasp the on / off status, temperature setting, operation mode, etc. of each device in real time. It also collects usage data from water and gas meters.

[0261] Data collection from wearable devices:

[0262] The server acquires the user's health data from the wearable device (e.g., smart watch), specifically, heart rate, sleep time, exercise amount, etc., and grasps the user's current health condition.

[0263] Mobile data collection:

[0264] The server obtains location information and activity data from the mobile device (e.g., smartphone), which determines whether the user is at home or out, and also tracks the amount of activity, such as the number of steps taken and distance traveled.

[0265] Data collection from the Internet:

[0266] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[0267] Emotion recognition by emotion engine

[0268] Emotion data collection:

[0269] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and recognizes the user's emotional state based on this data.

[0270] Emotional Data Analysis:

[0271] The server uses an emotion engine to analyze the collected physiological and audio data and evaluate the user's stress level and emotional state. For example, if the user's heart rate is high, the server determines that the user is feeling stressed.

[0272] Data Analysis and Optimization

[0273] Data preprocessing and analysis:

[0274] The server inputs the collected data into the AI ​​generator for specific analysis. After removing noise and normalizing the data, the AI ​​calculates the optimal operating pattern for the electrical equipment, taking into account the user's past behavioral patterns, health status, current environmental information, and emotional data.

[0275] Use of optimization algorithms:

[0276] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[0277] Suggestions and User Notifications

[0278] Optimization results suggestion:

[0279] The server then makes optimization suggestions to the user based on the analysis results. For example, it may display a notification on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[0280] Automatic Control

[0281] User consent and control:

[0282] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it, for example, to change the temperature setting of an air conditioner, and then monitors and confirms the results.

[0283] Specific examples

[0284] 1. Morning scenario:

[0285] When the user wakes up in the morning, the server retrieves the user's sleep duration and heart rate data from the smartwatch and, based on this, suggests optimizing the air conditioner temperature setting to maintain a comfortable room temperature. If the user's heart rate is high, it also suggests playing specific music to help with stress. If the user approves, the air conditioner's temperature setting will be automatically adjusted and music will be played.

[0286] 2. Shower scenario:

[0287] The server detects when a user is about to take a shower from their smartphone and checks the current temperature of the water heater. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees. It also suggests playing ambient music to help the user relax. If the user approves, the water heater temperature is automatically adjusted and ambient music is played.

[0288] This system enables efficient energy use that takes into account the user's emotional state, providing a more comfortable living environment. By repeating this series of steps, we can help build a sustainable and emotionally sensitive living environment.

[0289] The processing flow will be explained below.

[0290] Step 1:

[0291] The server obtains the operating status and setting information from each electrical device in the home. Specifically, it obtains the current temperature setting, operating mode, and operating status from the air conditioner. Similarly, it obtains the current temperature setting and operating status from the water heater.

[0292] Step 2:

[0293] The server acquires and records usage data from the water meter and gas meter, for example, by periodically acquiring and recording the amount of water and gas usage every hour.

[0294] Step 3:

[0295] The server acquires the user's health data from the wearable device, specifically information such as heart rate, sleep time, and exercise amount, and uses this information to understand the user's current health condition.

[0296] Step 4:

[0297] The server obtains location information and activity data from the mobile device, confirming whether the user is at home or out, and also obtains activity data such as the number of steps taken and distance traveled.

[0298] Step 5:

[0299] The server receives weather forecasts and temperature information via the Internet, providing information such as the maximum and minimum temperatures, probability of precipitation, and humidity for the day.

[0300] Step 6:

[0301] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and recognizes the user's emotional state based on this data.

[0302] Step 7:

[0303] The server analyzes the collected physiological and voice data using an emotion engine to assess the user's stress level and emotional state. For example, if the user's heart rate is high, the server determines that the user is feeling stressed.

[0304] Step 8:

[0305] The server combines the obtained emotional state data with other collected data (health data, location information, weather information, etc.) and inputs it into the generation AI. After removing noise and normalizing the data, the optimal operating pattern is calculated.

[0306] Step 9:

[0307] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[0308] Step 10:

[0309] Based on the analysis results, the server generates notification content suggesting optimization to the user. For example, it generates a suggestion such as, "Based on the current outside temperature and your health data, we recommend lowering the air conditioner temperature setting by 1 degree."

[0310] Step 11:

[0311] The device sends a notification to the user's mobile device and displays the optimization suggestion, and the user can check the notification and choose to accept or reject the suggestion.

[0312] Step 12:

[0313] If the user approves the proposal, the server sends an instruction to the electrical appliance to automatically control it, for example, to change the temperature setting of the air conditioner.

[0314] Step 13:

[0315] The server checks whether electrical equipment is working properly, for example, checking whether the air conditioner has started operating at the specified temperature setting.

[0316] Step 14:

[0317] The server continuously monitors the operating status and energy consumption of each electrical device. If an abnormality is detected, it notifies the user and suggests further optimization if necessary.

[0318] By repeating this series of steps, the home environment and energy consumption can be dynamically optimized. Furthermore, it is possible to make suggestions and control that take into account the user's emotional state, providing a more comfortable and healthy living environment.

[0319] Example 2

[0320] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0321] Conventional home electrical appliance and resource management systems typically control the operating status and settings of individual devices independently, limiting their ability to provide an optimal environment that takes into account the user's health and emotional state. It is also difficult to effectively integrate and adaptively manage the diverse data obtained from multiple devices. Therefore, an integrated system is needed to maintain an efficient and comfortable home environment.

[0322] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile terminal; means for acquiring temperature and weather forecasts via the Internet; means for recognizing an emotional state based on the acquired data, physiological data from the wearable device, and voice data from the mobile terminal; analysis means including a generation AI that predicts the operation pattern of the electrical appliances using an optimization algorithm based on the acquired data and the recognized emotional state and performs optimal adjustments; means for notifying the user of the optimization results obtained by the analysis means; and means for automatically controlling each electrical appliance based on the user's approval. This enables integrated and efficient optimization of the home environment, taking into account the user's health and emotional state.

[0323] "Various electrical appliances in homes" refers to all electrical and electronic devices used in homes, such as air conditioners, water heaters, air purifiers, and lighting.

[0324] "Operating status and setting information" refers to all information related to the operation of each electrical device, such as its on / off status, current set temperature, and operating mode.

[0325] "Water and gas usage" refers to the amount of water and gas consumed within a home.

[0326] "Wearable devices" refers to devices such as smartwatches and fitness trackers that can collect health data when worn by the user.

[0327] "Personal health data" refers to physiological and health information about a user, such as their heart rate, sleep duration, and activity level.

[0328] "Mobile device" refers to a mobile device such as a smartphone or tablet.

[0329] "Location information and activity data" refers to information such as current location, number of steps, and distance traveled provided by the mobile device via GPS.

[0330] "Means of obtaining temperature and weather forecasts via the Internet" refers to means of connecting to the Internet and obtaining local temperature and weather forecasts from web services or APIs that provide weather information.

[0331] "Physiological data" refers to data relating to the physiological state of the body, such as the user's heart rate and body temperature.

[0332] "Voice data" refers to data relating to a user's vocalizations and tone of voice collected through the microphone of a mobile device.

[0333] "Means for recognizing emotional state" refers to means for analyzing collected physiological data and voice data to recognize the stress level and emotional state of the user.

[0334] An "optimization algorithm" refers to a calculation procedure or method for analyzing a wide variety of data and optimizing the operating patterns and settings of electrical equipment in a home.

[0335] "Generative AI" refers to algorithms that use artificial intelligence technology to analyze data and generate optimal plans and proposals.

[0336] "Analysis means" refers to the equipment and software used to process and analyze collected data.

[0337] "Means for notifying the user of the optimization results" refers to means for displaying suggestions and instructions generated based on the analysis results on the user's terminal.

[0338] "Automatic control means" refers to a means for automatically changing the settings of an electrical device based on user approval.

[0339] The present invention is a system that integrates various electrical appliances and devices in a home with external information to efficiently and comfortably optimize the home environment. This system includes various elements that recognize the user's emotional state and adjust the environment optimally based on that state.

[0340] Data collection

[0341] The server obtains operating status and setting information from various electrical devices in the home. For example, the server can monitor the on / off status, temperature settings, and operation mode of devices such as air conditioners, water heaters, air purifiers, and lighting in real time. This information is obtained through sensors and communication modules built into each device.

[0342] The server also obtains usage data from water and gas meters to understand water and gas consumption, allowing for monitoring of overall resource usage efficiency within the home.

[0343] In addition, the server acquires user health data from wearable devices (e.g., smart watches), allowing the server to obtain information such as heart rate, sleep time, and exercise volume, enabling real-time monitoring of the user's health status.

[0344] The server can also obtain location information and activity data from mobile devices (e.g., smartphones), which can determine whether the user is at home or out and track activity such as the number of steps taken and distance traveled.

[0345] The server can also obtain temperature and weather forecasts via the Internet, thereby predicting changes in the external environment and collecting data to maintain an optimal indoor environment.

[0346] Emotion recognition by emotion engine

[0347] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and uses this data to recognize the user's emotional state. For example, a high heart rate can be determined to indicate a high likelihood of stress. Furthermore, the server can analyze the tone and tempo of the voice from the voice data to understand the user's emotional state in more detail.

[0348] Data Analysis and Optimization

[0349] The server inputs the collected data into a generative AI model for specific analysis. After removing noise and normalizing the data, it calculates the optimal operating pattern for electrical equipment by taking into account the user's past behavioral patterns, health status, current environmental information, and emotional data.

[0350] For example, the server uses the generative AI model to calculate the optimal temperature setting and operating time for an air conditioner, the temperature setting for a water heater, etc., thereby improving energy efficiency while maintaining user comfort.

[0351] Suggestions and User Notifications

[0352] Based on the analysis results, the server makes optimization suggestions to the user. For example, a notification might be displayed on the user's smartphone stating, "The current outside temperature is low, so we recommend lowering the air conditioner's set temperature by 1 degree." If the user accepts the suggestion, the server sends automatic control instructions to each electrical device and changes the air conditioner's set temperature.

[0353] Automatic Control and Examples

[0354] The server receives user approval and sends instructions for automatic control to each electrical device. For example, if the user approves a suggestion to lower the air conditioner's temperature setting by 1 degree, the server automatically adjusts the temperature setting to 22 degrees and then monitors and confirms the result again.

[0355] Below are some example prompts to input to a generative AI model:

[0356] "For this home optimization system, please suggest the optimal settings using the following data: current status of the air conditioner, water heater temperature, user's heart rate and sleep data, and outside temperature. Please suggest the optimal air conditioner setting temperature and water heater temperature setting."

[0357] This system enables efficient energy use that takes into account the user's health and emotional state, creating a comfortable living environment within the home. Furthermore, by repeating this series of steps, the creation of a sustainable and emotionally sensitive living environment is supported.

[0358] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0359] Step 1:

[0360] Input: Operation status and setting information of various electrical devices

[0361] Specific operation: The server obtains operating status and setting information (on / off status, temperature setting, operation mode, etc.) from various electrical devices in the home.

[0362] Data processing and calculation: The acquired data is collated to obtain an overall picture of the current home environment and recorded in a database.

[0363] Output: A list of successfully retrieved health and configuration information

[0364] Step 2:

[0365] Input: Health data from wearable devices

[0366] Specific operation: The server collects data such as the user's heart rate, sleep time, and exercise volume from the wearable device.

[0367] Data processing and calculation: Analyze the acquired data and normalize the user's health status and vital signs.

[0368] Output: Successfully acquired and normalized health data

[0369] Step 3:

[0370] Input: Location and activity data from your smartphone

[0371] Specific operation: The server obtains location information (GPS data) and activity data (number of steps, distance traveled, etc.) from the mobile device.

[0372] Data processing and calculation: Based on the acquired location information, the system determines whether the user is at home or out and compiles the amount of activity.

[0373] Output: Successfully acquired location and activity data, and the result of determining the user's current location.

[0374] Step 4:

[0375] Input: Temperature and weather forecast data from the internet

[0376] What it does: The server retrieves temperature and weather forecast data via the Internet.

[0377] Data processing and calculation: Analyze acquired weather forecast data and predict future climate conditions.

[0378] Output: Successfully retrieved temperature and weather forecast data, predicted weather conditions

[0379] Step 5:

[0380] Input: Health data, voice data

[0381] Specific operation: The server collects physiological data such as heart rate from the wearable device and audio data from the mobile device.

[0382] Data processing and calculation: Analyzes heart rate and voice data to recognize the user's emotional state.

[0383] Output: Perceived user emotional state (e.g., stress level, emotional tendency, etc.)

[0384] Step 6:

[0385] Input: Various data (electrical device data, health data, location information, temperature data, emotional data)

[0386] Specific operation: The server inputs the collected data into the generative AI model.

[0387] Data processing and calculation: Data is denoised and normalised, and an optimisation algorithm is used to predict the optimal operating pattern for each piece of electrical equipment.

[0388] Output: Optimal operating patterns and adjustment parameters

[0389] Step 7:

[0390] Input: Optimization results

[0391] Specific operation: Based on the analysis results, the server notifies the user of optimization suggestions.

[0392] Data processing and calculation: The analysis results are converted into a format that is easy for users to understand and displayed on devices such as smartphones.

[0393] Output: Optimization suggestions communicated to the user

[0394] Step 8:

[0395] Input: User approval result

[0396] Specific operation: When the user approves the proposal, the server sends instructions for automatic control to each electrical device.

[0397] Data processing and calculation: Generates control instructions for each electrical device and sends them to the corresponding device.

[0398] Output: Automatic control instructions are sent to change the settings of each electrical device.

[0399] (Application example 2)

[0400] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0401] Currently, environmental management in homes and factories is often based on only a few electrical appliances and devices. This makes comprehensive and efficient environmental optimization difficult, and adaptation based on the user's individual health and emotional state is lacking. Furthermore, data analysis and suggestion functions for improving work efficiency and safety are still limited. The present invention aims to achieve comprehensive and individually adaptive optimization of the environment and work conditions in homes and factories, thereby improving energy efficiency and work safety and comfort.

[0402] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0403] In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile terminal; means for acquiring temperature and weather forecasts via the Internet; means for recognizing an individual's emotional state using an emotion engine; analysis means including a generation AI that predicts operation patterns of electrical appliances using an optimization algorithm based on the acquired data and makes optimal adjustments; means for notifying a user of the optimization results obtained by the analysis means; means for automatically controlling each electrical appliance based on the user's approval; means for acquiring operation status and setting information from industrial machinery; means for acquiring health data and emotional states from workers' wearable devices; means for acquiring external environment data via the Internet; analysis means including a generation AI that predicts operation patterns using an optimization algorithm based on the acquired data and makes optimal adjustments; means for notifying a manager and a worker of the optimization results obtained by the analysis means; and means for automatically controlling industrial machinery based on the manager and a worker's approval. This makes it possible to individually optimize the environment and working conditions within homes and factories, improving energy efficiency, work efficiency, and safety.

[0404] "Various electrical equipment" refers to electrical equipment used in homes and factories, such as air conditioners, water heaters, air purifiers, and lighting.

[0405] "Operation status" is information that indicates the current operating state of electrical equipment and industrial machinery.

[0406] "Setting information" refers to information relating to the operating parameters and operating modes of electrical equipment and industrial machinery.

[0407] "Water and gas usage" is data measuring the amount of water and gas consumed within homes and factories.

[0408] A "wearable device" is a device that measures health data by being worn, such as a smartwatch or fitness tracker.

[0409] "Health data" is data that indicates an individual's health status, such as heart rate, body temperature, and sleep patterns.

[0410] A "mobile terminal" is a mobile device such as a smartphone or tablet.

[0411] "Location information" is information that indicates the current location of the user and is collected by the mobile terminal.

[0412] "Activity data" is data that indicates the user's movement and activity status, such as the number of steps, distance traveled, and calories burned.

[0413] "Means for obtaining temperature and weather forecast via the Internet" is a function for obtaining outside temperature and weather information via the Internet.

[0414] An "emotion engine" is an algorithm or function that analyzes physiological and audio data to recognize the user's emotional state.

[0415] An "optimization algorithm" is a series of calculation methods for calculating optimal equipment operating patterns and settings based on collected data.

[0416] "Generative AI" is an artificial intelligence technology that analyzes large amounts of data and performs efficient optimization.

[0417] The "analysis means" is the part of the system that includes functions ranging from data preprocessing to the execution of optimization algorithms.

[0418] "Notification means" is a function for notifying users and administrators of optimization results and other important information.

[0419] "Automatic control means" refers to a function for automatically changing the settings of electrical equipment or industrial machinery after obtaining user approval.

[0420] "Industrial machinery" refers to equipment such as production line machines and robots used in factories.

[0421] "External environmental data" refers to data related to the environment, such as temperature, humidity, and weather information inside and outside the factory.

[0422] An "administrator" is a person whose role is to oversee the operation of a factory or system and make optimization proposals and approve controls.

[0423] "Worker" means an employee who performs work in a factory.

[0424] "Noise removal" is the process of removing unnecessary information and errors from collected data.

[0425] "Normalization" is the process of converting collected data into a unified scale or format.

[0426] The present invention relates to a system for comprehensively and efficiently optimizing the environment and working conditions in homes and factories. This system uses multiple data collection and analysis methods to automatically control equipment while taking into account the individual health and emotional states of users.

[0427] 1. System Configuration

[0428] The system consists of the following main components:

[0429] 1. Data collection methods:

[0430] A means of acquiring operating status and setting information from various electrical devices and industrial machines in homes and factories.

[0431] A means of obtaining water and gas usage figures.

[0432] A means of obtaining health data (e.g., heart rate, body temperature, sleep patterns) from wearable devices (e.g., smartwatches).

[0433] A means of obtaining location and activity data from mobile devices (e.g., smartphones).

[0434] A means of obtaining temperature and weather forecasts via the Internet.

[0435] A means of recognizing an individual's emotional state using an emotion engine.

[0436] 2. Analysis method:

[0437] A means of denoising and normalising the data.

[0438] A method of using generative AI models to run optimization algorithms based on collected data, predicting operating patterns of electrical equipment and industrial machinery, and making optimal adjustments.

[0439] 3. Means of notification:

[0440] A means for notifying the user or administrator of the optimization results obtained by the analysis means.

[0441] 4. Automatic control means:

[0442] A means of automatically controlling electrical equipment and industrial machinery based on user or administrator approval.

[0443] 2. Hardware and Software Used

[0444] Hardware:

[0445] Smartwatches and smartphones for data collection.

[0446] Various sensors (temperature, humidity, electricity meter, water meter, etc.).

[0447] Industrial machinery in a factory.

[0448] software:

[0449] Generative AI models that include data analysis and optimization algorithms.

[0450] Emotion recognition algorithm using emotion engine.

[0451] Notification systems (e.g. smartphone apps).

[0452] Software that uses an Internet API to obtain temperature and weather forecast data.

[0453] 3. Data processing and calculation

[0454] The server preprocesses the data collected from various devices, removing noise and normalizing it. The preprocessed data is then input into a generative AI model, which calculates optimal operating patterns based on the user's past behavioral patterns, current environmental information, health status, and emotional state.

[0455] Here are some specific examples of data processing:

[0456] Temperature control within the home: The server collects indoor temperature data from temperature sensors, compares it with weather forecast data, and makes suggestions to optimize the air conditioner temperature setting.

[0457] Machine operation patterns within the factory: The server analyzes the operation data of industrial machines and, in conjunction with the health data of workers, suggests optimal operating times and settings for the equipment.

[0458] 4. Examples of prompts

[0459] The following prompt demonstrates how this system works:

[0460] You are the developer of a system that integrates worker health and environmental data in a factory to make optimization suggestions.

[0461] If a worker's heart rate data exceeds 80, it is determined that the worker is stressed.

[0462] Generate suggestions to adjust machine settings based on weather data.

[0463] The above is an embodiment of the invention. The present invention individually optimizes the environment and working conditions in a house or factory, making it possible to improve energy efficiency, work efficiency, and safety.

[0464] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0465] Step 1:

[0466] The server acquires operating status and setting information from various electrical devices and industrial machines in homes and factories.

[0467] Input: Operational data and setting information from each device

[0468] Data Processing: Collecting data and converting it into a centralized format.

[0469] Specific operation: The server periodically calls the API of each device to obtain its operating status and settings, such as the temperature setting and operation mode of an air conditioner, or the operating time and load of industrial machinery.

[0470] Step 2:

[0471] The server obtains usage data from water and gas meters.

[0472] Input: Consumption data from water and gas meters

[0473] Data processing: Data is aggregated over time to analyze usage patterns.

[0474] Specific operation: The server collects consumption data from water meters and gas meters and compiles the data on a daily or monthly basis.

[0475] Step 3:

[0476] The server acquires the personal health data from the wearable device.

[0477] Input: Heart rate, body temperature, sleep data from smartwatch etc.

[0478] Data processing: Organize the data by individual and store it as time-series data.

[0479] Specific operation: The server periodically collects data from the wearable device via an API and stores the heart rate, body temperature, and sleep data for each individual.

[0480] Step 4:

[0481] The server obtains location information and activity data from the mobile device.

[0482] Input: Location information and activity data from your smartphone (number of steps, distance traveled, etc.)

[0483] Data processing: Plot location information on a map and organize activity data along a timeline.

[0484] Specific operation: The server collects GPS data and activity records from the smartphone and analyzes the movement route and activity level.

[0485] Step 5:

[0486] The server retrieves the temperature and weather forecast via the Internet.

[0487] Input: Real-time weather data from a weather data provider

[0488] Data processing: Organize data as local area information and extract predictive data.

[0489] Specific operation: The server calls the weather data API to obtain and store the current temperature and future weather forecast.

[0490] Step 6:

[0491] The server uses an emotion engine to recognize the emotional state of the individual.

[0492] Input: Heart rate and audio data from wearable devices

[0493] Data processing: Analyze the data with the emotion engine and evaluate the emotional state.

[0494] Specific operation: The server inputs heart rate and voice data into the emotion engine to determine stress levels and emotional states.

[0495] Step 7:

[0496] The server uses an optimization algorithm based on the acquired data to predict the operating patterns of electrical equipment and operates an analysis means including a generation AI that makes optimal adjustments.

[0497] Input: Operating status data, health data, activity data, weather data, emotion data

[0498] Data calculation: Using a generative AI model, optimal operating patterns are calculated.

[0499] How it works: The server inputs various data into the generative AI and calculates the optimal settings to maximize energy efficiency and comfort.

[0500] Step 8:

[0501] The server notifies the user of the optimization results obtained by the analysis means.

[0502] Input: Optimized operation patterns and adjustment proposals

[0503] Output: Notification to the user's smartphone and the administrator's device

[0504] Specific operation: The server notifies the user or administrator of the generated optimization proposal on their device. Example: "The current outside temperature is low, so we recommend lowering the air conditioner setting by 1 degree."

[0505] Step 9:

[0506] Based on the user's approval, the server automatically controls each electrical device.

[0507] Input: User or administrator approval

[0508] Output: Changing the settings of electrical equipment and industrial machines

[0509] Specific operation: After obtaining the user's approval, the server automatically sends instructions to change the settings to each device and performs the actual operation.

[0510] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0511] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0512] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0513] [Second embodiment]

[0514] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0515] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0516] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0517] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0518] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0519] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0520] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0521] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0522] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0523] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0524] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0525] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0526] The present invention is a system for optimizing the home environment efficiently and comfortably, integrating various electrical appliances, devices, and external information to perform optimization. The system includes the following steps and elements:

[0527] Data collection

[0528] Data collection from devices:

[0529] The server continuously collects operating status and setting information from each electrical device in the home (e.g., air conditioner, water heater, air purifier, lighting). This allows the server to grasp the on / off status, temperature setting, operation mode, etc. of each device in real time. It also collects usage data from water and gas meters.

[0530] Data collection from wearable devices:

[0531] The server acquires the user's health data from the wearable device (e.g., smart watch), specifically, heart rate, sleep time, exercise amount, etc., and grasps the user's health condition.

[0532] Mobile data collection:

[0533] The server obtains location information and activity data from the mobile device (e.g., smartphone), which determines whether the user is at home or out, and also tracks the amount of activity, such as the number of steps taken and the distance traveled.

[0534] Data collection from the Internet:

[0535] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[0536] Data Analysis and Optimization

[0537] Data preprocessing and analysis:

[0538] The server inputs the collected data into the AI ​​generator for specific analysis. After removing noise and normalizing the data, the AI ​​calculates the optimal operating pattern for electrical equipment, taking into account the user's past behavioral patterns, health status, and external environment.

[0539] Use of optimization algorithms:

[0540] The server uses generative AI to run algorithms that optimize the use of electrical equipment and resources, automatically determining things like air conditioner temperature settings and water heater operation schedules, enabling efficient energy use.

[0541] Suggestions and User Notifications

[0542] Optimization results suggestion:

[0543] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification may be displayed on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[0544] Automatic Control

[0545] User consent and control:

[0546] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it, for example, to change the temperature setting of an air conditioner, and then monitors and confirms the results.

[0547] Specific examples

[0548] 1. Morning scenario:

[0549] When the user wakes up in the morning, the server retrieves the user's sleep time and heart rate data from the smartwatch and, based on this, suggests optimizing the air conditioner temperature setting to maintain a comfortable room temperature. If the user approves, the air conditioner temperature setting will be automatically adjusted.

[0550] 2. Shower scenario:

[0551] The server detects when a user is about to take a shower from their smartphone and checks the current temperature of the water heater. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees, and if the user agrees, the set temperature is automatically adjusted.

[0552] This system enables efficient energy use and provides users with a comfortable living environment. Repeating these steps will help build a sustainable living environment.

[0553] The processing flow will be explained below.

[0554] Step 1:

[0555] The server acquires operating status and setting information from each electrical device in the home. For example, it acquires the current temperature setting, operating mode, and operating status from the air conditioner. Similarly, it acquires the current temperature setting and operating status from the water heater.

[0556] Step 2:

[0557] The server acquires and records usage data from the water meter and gas meter, for example, the amount of water and gas used every hour.

[0558] Step 3:

[0559] The server acquires the user's health data from the wearable device, specifically information such as heart rate, sleep time, and exercise amount, and uses this information to understand the user's current health condition.

[0560] Step 4:

[0561] The server acquires location information and activity data from the mobile device, confirms whether the user is at home or out, and also acquires activity data such as the number of steps taken and distance traveled.

[0562] Step 5:

[0563] The server receives weather forecasts and temperature information via the Internet, providing information such as the maximum and minimum temperatures, probability of precipitation, and humidity for the day.

[0564] Step 6:

[0565] The server denoises and normalizes the collected data, correcting outliers and missing values, and formatting the data into a form that is easy to analyze.

[0566] Step 7:

[0567] The server inputs the formatted data into the AI ​​generator for analysis. Specifically, it predicts the optimal operating pattern for electrical equipment by taking into account the user's past behavioral patterns, health status, and current environmental information.

[0568] Step 8:

[0569] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[0570] Step 9:

[0571] The server compiles all the analysis results and generates a notification that suggests optimization to the user, such as "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[0572] Step 10:

[0573] The device sends a notification to the user's mobile device and displays the optimization suggestion, and the user can check the notification and choose to accept or reject the suggestion.

[0574] Step 11:

[0575] If the user selects approval, the server sends an instruction to the electrical appliance to automatically control it, for example, to an air conditioner to change the temperature setting.

[0576] Step 12:

[0577] The server checks whether electrical equipment is working properly, for example, checking whether the air conditioner has started operating at the specified temperature setting.

[0578] Step 13:

[0579] The server continuously monitors the operating status and energy consumption of each electrical device. If an abnormality is detected, it notifies the user and suggests further optimization if necessary.

[0580] By repeating this series of steps, the home's environment and energy consumption can be dynamically optimized.

[0581] Example 1

[0582] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0583] The efficient operation of various electrical appliances and devices in homes and the maintenance of a comfortable and healthy living environment for individuals are required. The present invention solves the problem of improving energy efficiency and ensuring user convenience by providing a system that manages these in an integrated manner and proposes and executes optimal operation patterns.

[0584] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0585] In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile device; means for acquiring temperature and weather forecasts via the Internet; analysis means including a generation AI that uses an optimization algorithm to predict operation patterns of the electrical appliances based on the acquired data and makes optimal adjustments; means for notifying the user of the optimization results obtained by the analysis means; means for automatically controlling each electrical appliance based on the user's approval; means for denoising and normalizing the collected data; means for integrating the operation status of the target appliances with external environmental data to calculate optimal operation patterns of the electrical appliances and generate proposals; and means for notifying the user of the generated proposals to the user's mobile device. This makes it possible to optimize the user's living environment and improve energy efficiency.

[0586] - "Various electrical appliances" refers to electrical machinery and equipment used in homes, such as air conditioners, water heaters, air purifiers, and lighting.

[0587] "Operating status" refers to information about whether an electrical device is currently operating or in what mode it is operating.

[0588] "Setting information" refers to information relating to operating conditions and parameters designated by the user for the electrical device, such as temperature settings and operation modes.

[0589] "Usage data" is information about the consumption of resources such as water and gas.

[0590] A "wearable device" is an electronic device that is designed to be worn by the user, and includes smartwatches and the like.

[0591] "Health data" is information that indicates the user's health condition, such as heart rate, sleep time, and amount of exercise.

[0592] A "mobile device" is a portable communication device such as a smartphone that is capable of collecting location information and activity data.

[0593] "Location information" is information about the current location obtained by the GPS function of the mobile terminal.

[0594] "Activity data" is information indicating the amount of physical activity of the user, such as the number of steps taken and the distance traveled.

[0595] "Temperature" refers to the temperature in the atmosphere, and is information indicating the temperature conditions of the external environment.

[0596] "Weather forecast" is information about upcoming weather changes and current weather.

[0597] An "optimization algorithm" is a mathematical method for calculating efficient operating patterns for electrical equipment based on collected data.

[0598] "Generative AI" is a type of artificial intelligence that uses machine learning and deep learning techniques to analyze data and generate optimal operating patterns.

[0599] "Analysis means" refers to the techniques and devices used to perform analysis based on collected data.

[0600] The "optimization result" is information that indicates an efficient method of using and operation pattern of the electrical equipment, derived by the analysis means.

[0601] "Notification means" refers to a means for informing the user of information, and includes notifications to smartphones, etc.

[0602] "Automatic control" is a mechanism for automatically adjusting the operation of each electrical device after obtaining user approval.

[0603] "Noise removal" is the process of removing unnecessary or erroneous data in data analysis.

[0604] "Normalization" is the process of converting the range of data to a certain scale.

[0605] The "suggestion content" is information about the settings and operation patterns of electrical appliances that are recommended to the user based on the optimization algorithm.

[0606] This invention is a system for optimizing the home environment efficiently and comfortably. The system integrates various electrical appliances, devices, and external information to perform optimization.

[0607] Data collection

[0608] Collecting data from devices

[0609] The server collects operating status and setting information from each electrical device in the home, such as the air conditioner, water heater, air purifier, and lighting. Specifically, it obtains data such as the air conditioner's on / off status, temperature setting, and operation mode. It also obtains usage data from water and gas meters.

[0610] Data collection from wearable devices

[0611] The server collects user health data from wearable devices such as smartwatches, including heart rate, sleep duration, and exercise volume.

[0612] Data collection from mobile devices

[0613] The server collects location information and activity data from mobile devices such as smartphones, which allows it to determine whether the user is at home or out, as well as the amount of activity such as the number of steps taken and distance traveled.

[0614] Data collection from the internet

[0615] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[0616] Data Analysis and Optimization

[0617] Data Preprocessing

[0618] The server performs noise removal and normalization on the various collected data. Specifically, it complements missing values ​​in the data and removes outliers. It also performs normalization to make the data range consistent. This is done using a data preprocessing library (e.g., pandas, NumPy).

[0619] Using generative AI models

[0620] The server uses a generative AI model to calculate the optimal operating pattern for each electrical device. Specifically, normalized data is input into the generative AI model (e.g., TensorFlow, PyTorch) to predict the optimal energy consumption pattern.

[0621] Suggestions and User Notifications

[0622] Optimization results suggestions

[0623] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification might be displayed on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree." This is done using a notification service (e.g., Firebase Cloud Messaging).

[0624] Automatic Control

[0625] User Authorization and Control

[0626] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it. For example, it sends an instruction to change the temperature setting of an air conditioner and then monitors and confirms the results. This is done using the smart home control API.

[0627] Specific examples

[0628] 1. Morning Scenario

[0629] The server receives the user's sleep data from the smartwatch and analyzes it together with the outside temperature data. As a result, it sends a notification to the smartphone suggesting that the current room temperature be raised by 1 degree. If the user approves, the server sends a command to change the set temperature to the air conditioner.

[0630] 2. Shower scenario

[0631] The server detects from the smartphone sensor that the user is about to take a shower. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees and notifies the smartphone. If the user agrees, the server sends a command to change the set temperature to the water heater.

[0632] Prompt Sentence Examples

[0633] Example prompt 1: Morning optimization suggestions

[0634] "Good morning. According to your recent sleep data, it appears that you have not been spending much time in deep sleep. Raising the current room temperature by 1 degree will help you wake up more comfortably. Would you like to change the air conditioner temperature setting?"

[0635] Example prompt 2: Shower optimization suggestions

[0636] "The outside temperature is dropping. We suggest you increase the water heater temperature by 2 degrees to make showering more comfortable. Would you like to do this?"

[0637] This makes it possible to use energy efficiently and provide users with a comfortable living environment.

[0638] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0639] Step 1:

[0640] Collecting data from devices

[0641] The server collects operating status and setting information from various electrical devices in the home. Specifically, it obtains information such as the air conditioner's on / off status, temperature setting, and operation mode. The server sends requests at regular intervals and receives current status information from the electrical devices.

[0642] Input: Request responses from various electrical devices

[0643] Output: Operational data of each device (on / off status, temperature setting, operation mode)

[0644] Step 2:

[0645] Data collection from wearable devices

[0646] The server collects user health data from wearable devices such as smartwatches, and periodically uploads the data from the wearable devices to the server.

[0647] Input: Health data from a smartwatch

[0648] Output: User's health data (heart rate, sleep time, exercise amount)

[0649] Step 3:

[0650] Data collection from mobile devices

[0651] The server collects location information and activity data from mobile devices such as smartphones, and determines whether the user is at home or out. The server periodically transmits the location information and activity data to the server using the mobile device's GPS and activity tracking functions.

[0652] Input: Location and activity data from your smartphone

[0653] Output: User location and activity data

[0654] Step 4:

[0655] Data collection from the internet

[0656] The server retrieves weather forecasts and current temperatures via the Internet, sends a request to the weather API, and stores the retrieved data internally.

[0657] Input: Request response from the weather API

[0658] Output: Weather forecast data and current temperature data

[0659] Step 5:

[0660] Data preprocessing and analysis

[0661] The server performs noise removal and normalization on the various collected data. Specifically, it complements missing values ​​in the collected data and removes outliers. It also performs normalization to make the data range consistent. This is done using a data preprocessing library (e.g., pandas, NumPy).

[0662] Input: Various collected data (electrical equipment operation data, health data, location information, weather data)

[0663] Output: Normalized data

[0664] Step 6:

[0665] Using generative AI models

[0666] The server uses a generative AI model to calculate the optimal operating pattern for each electrical device. The normalized data is input into the generative AI model (e.g., TensorFlow, PyTorch) to predict the optimal energy consumption pattern.

[0667] Input: Normalized data

[0668] Output: Optimized operating pattern

[0669] Step 7:

[0670] Optimization results suggestions

[0671] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification such as "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree" is displayed on the user's smartphone. This is achieved using a notification service (e.g., Firebase Cloud Messaging).

[0672] Input: Optimized operating pattern

[0673] Output: Proposal notification to user

[0674] Step 8:

[0675] User Authorization and Control

[0676] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it. For example, it sends an instruction to change the temperature setting of an air conditioner and then monitors and confirms the results. This is done using the smart home control API.

[0677] Input: User approval

[0678] Output: Control instructions to electrical devices

[0679] (Application example 1)

[0680] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0681] This invention relates to a system that comprehensively monitors and controls the operating status and environmental data of various equipment and machines in a factory, improving energy efficiency and optimizing productivity. Conventional systems manage each piece of equipment individually, without proper data integration or analysis, which often results in a lack of overall efficiency. Furthermore, insufficient coordination between each piece of equipment makes it difficult to optimize overall energy consumption. This leads to problems such as increased energy costs and reduced productivity.

[0682] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0683] In this invention, the server includes means for acquiring operation status and setting information from various electrical appliances in the home, means for acquiring water and gas usage, means for acquiring personal health data from a wearable device, means for acquiring location information and activity data from a mobile terminal, means for acquiring temperature and weather forecasts via the Internet, means for acquiring operation status and environmental data from various pieces of equipment in the factory, analysis means including a generation AI that uses an optimization algorithm based on the acquired data to predict the operation pattern of the factory equipment and make optimal adjustments, means for notifying workers of the optimization results obtained by the analysis means, and means for automatically controlling each piece of equipment based on the worker's approval, thereby enabling collaboration between equipment in the factory and optimization of energy consumption.

[0684] "Various electrical appliances in the home" refers to household electrical appliances such as air conditioners, water heaters, air purifiers, and lighting.

[0685] "Operating status" refers to information that indicates the status of each device, such as its on / off status, the currently set operating mode, and temperature setting.

[0686] "Setting information" refers to parameters and values ​​that are set in advance to control the operation of an electrical device.

[0687] "Water and gas usage" refers to data that indicates the amount of tap water and gas consumed within a home.

[0688] "Wearable devices" refers to electronic devices that can be worn by a user and that can collect health and activity data. Examples include smartwatches and fitness trackers.

[0689] "Health data" refers to data that includes information about an individual's health status, such as heart rate, sleep duration, and amount of exercise.

[0690] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[0691] "Location Information" means geographic location data obtained from a mobile or other device.

[0692] "Activity data" refers to data that includes information about the user's daily activities, such as the number of steps taken, distance traveled, and time spent at a destination.

[0693] "Temperature and weather forecast via the Internet" refers to current temperature and future weather forecast information obtained using an Internet connection.

[0694] "Various facilities within the factory" includes production facilities and environmental control devices used within the factory, such as robotic arms, conveyors, and HVAC systems.

[0695] "Environmental data" refers to data that includes information about the surrounding environment within a factory or home, such as temperature, humidity, and illuminance.

[0696] "Optimization algorithm" refers to an algorithm that calculates the best operation to achieve a specific goal based on collected data.

[0697] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and suggest optimal ways to operate devices and systems.

[0698] "Analysis means" refers to a device or process for analyzing collected data and outputting optimization results.

[0699] "Worker" refers to a person who performs work in a factory or other facility.

[0700] "Automatic control means" refers to a system that includes a control device or program for automatically changing the settings or operation of equipment based on the optimized results.

[0701] This invention is a system for efficiently and optimally managing and controlling various equipment and environments within a factory, and is implemented through the procedures of data collection, analysis, optimization, notification, and control from various equipment. This system includes the following procedures and elements.

[0702] Data collection

[0703] The server continuously collects operational status and setting information from various pieces of equipment in the factory (robot arms, conveyors, HVAC systems, etc.). This allows information such as the operating status, set temperature, and operating mode of each piece of equipment to be sent to the server in real time. Environmental data such as temperature, humidity, and illuminance are also collected via sensors.

[0704] Data Analysis and Optimization

[0705] The server uses a generative AI model to analyze the various collected data, removes noise and normalizes the data, and then calculates the optimal equipment operating pattern taking into account past operating patterns and environmental conditions.

[0706] Proposals and worker notifications

[0707] Based on the analysis results, the server will suggest optimization measures to the worker. For example, a notification such as "We recommend lowering the current room temperature by 2 degrees" will be displayed on the worker's device.

[0708] Automatic Control

[0709] Once the worker approves the optimization proposal, the server sends automatic control instructions to each piece of equipment, such as adjusting the robot arm's operating schedule or changing the temperature setting of the HVAC system.

[0710] Specific examples

[0711] 1. Production line optimization: The server collects robot arm movement data and proposes optimal movement timing and patterns. Once approved by the worker, the robot arm's movement pattern is automatically changed.

[0712] 2. Managing the factory environment: The server collects data from temperature and humidity sensors and makes recommendations to optimize the temperature and humidity settings of the HVAC system. Once the worker approves the recommendations, the HVAC system settings are automatically adjusted.

[0713] Hardware and software used

[0714] Hardware: Various sensors in the factory (temperature, humidity, light, etc.), robotic arms, HVAC systems, servers, and worker terminals.

[0715] Software: Data collection, analysis, notification and control program using Python. Interface with devices using REST API.

[0716] Prompt Sentence Examples

[0717] As an example, data is collected from a temperature sensor, and the prompt text sent by the server to the generative AI model when the temperature is 25 degrees and the humidity is 60% is shown below:

[0718] "Here is the environmental data for the factory. Temperature: 25°C, humidity: 60%. Please suggest the optimal operating pattern for each piece of equipment."

[0719] This system enables coordination between equipment within a factory and optimizes energy consumption, resulting in improved efficiency and cost reduction.

[0720] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0721] Step 1:

[0722] Starting data collection and acquiring input

[0723] The server collects real-time operational status and environmental data from various sensors and equipment in the factory. Specifically, it collects current temperature data from temperature sensors and current humidity data from humidity sensors. It also collects operational status and setting information from robotic arms and HVAC systems. This allows data on temperature, humidity, and equipment operational status to be collected and input to the server.

[0724] Step 2:

[0725] Data preprocessing and denoising

[0726] The server performs preprocessing on the collected data. In this step, it removes noise and normalizes the data. For example, if data obtained from a temperature sensor contains outliers, it removes them. The input is the collected environmental data and equipment data, and the output is the data that has been denoised and normalized.

[0727] Step 3:

[0728] Data input and analysis for generative AI models

[0729] The server inputs the preprocessed data into a generative AI model for analysis. The generative AI model used here predicts optimal equipment operating patterns based on past data and current conditions. For example, when temperature and humidity data is input, the optimal settings for an HVAC system are calculated based on that data. The input is noise-removed data, and the output is optimized equipment settings and operating patterns.

[0730] Step 4:

[0731] Notifying the workers of the analysis results

[0732] The server notifies the worker of optimization suggestions based on the analysis results. This notification is displayed on the worker's device. For example, a message such as "We recommend lowering the current room temperature by 2 degrees" is displayed. The input is the analysis result from the generative AI model, and the output is a notification message sent to the worker's device.

[0733] Step 5:

[0734] Operator approval and start of automatic control

[0735] When an operator approves an optimization proposal, the server sends automatic control instructions to each piece of equipment. For example, these instructions include changing the temperature setting of an HVAC system or adjusting the operation schedule of a robot arm. The input is the operator's approval, and the output is a control instruction for each piece of equipment.

[0736] Step 6:

[0737] Retrieval Monitoring and Feedback

[0738] After issuing the control command, the server monitors the equipment and environmental data again and re-optimizes as necessary. This allows for continuous optimization of equipment efficiency and energy consumption. The input is the latest operating status and environmental data, and the output is the re-optimized settings.

[0739] The above steps will enable coordination between equipment within the factory and optimize energy consumption, improving efficiency and reducing costs.

[0740] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0741] The present invention is a system for optimizing the home environment efficiently and comfortably, integrating various electrical appliances, devices, and external information to perform optimization. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, optimization can be performed that is adapted to the user's emotional state. This system includes the following procedures and elements.

[0742] Data collection

[0743] Data collection from devices:

[0744] The server collects operating status and setting information from each electrical device in the home (e.g., air conditioner, water heater, air purifier, lighting). This allows the server to grasp the on / off status, temperature setting, operation mode, etc. of each device in real time. It also collects usage data from water and gas meters.

[0745] Data collection from wearable devices:

[0746] The server acquires the user's health data from the wearable device (e.g., smart watch), specifically, heart rate, sleep time, exercise amount, etc., and grasps the user's current health condition.

[0747] Mobile data collection:

[0748] The server obtains location information and activity data from the mobile device (e.g., smartphone), which determines whether the user is at home or out, and also tracks the amount of activity, such as the number of steps taken and distance traveled.

[0749] Data collection from the Internet:

[0750] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[0751] Emotion recognition by emotion engine

[0752] Emotion data collection:

[0753] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and recognizes the user's emotional state based on this data.

[0754] Emotional Data Analysis:

[0755] The server uses an emotion engine to analyze the collected physiological and audio data and evaluate the user's stress level and emotional state. For example, if the user's heart rate is high, the server determines that the user is feeling stressed.

[0756] Data Analysis and Optimization

[0757] Data preprocessing and analysis:

[0758] The server inputs the collected data into the AI ​​generator for specific analysis. After removing noise and normalizing the data, the AI ​​calculates the optimal operating pattern for the electrical equipment, taking into account the user's past behavioral patterns, health status, current environmental information, and emotional data.

[0759] Use of optimization algorithms:

[0760] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[0761] Suggestions and User Notifications

[0762] Optimization results suggestion:

[0763] The server then makes optimization suggestions to the user based on the analysis results. For example, it may display a notification on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[0764] Automatic Control

[0765] User consent and control:

[0766] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it, for example, to change the temperature setting of an air conditioner, and then monitors and confirms the results.

[0767] Specific examples

[0768] 1. Morning scenario:

[0769] When the user wakes up in the morning, the server retrieves the user's sleep duration and heart rate data from the smartwatch and, based on this, suggests optimizing the air conditioner temperature setting to maintain a comfortable room temperature. If the user's heart rate is high, it also suggests playing specific music to help with stress. If the user approves, the air conditioner's temperature setting will be automatically adjusted and music will be played.

[0770] 2. Shower scenario:

[0771] The server detects when a user is about to take a shower from their smartphone and checks the current temperature of the water heater. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees. It also suggests playing ambient music to help the user relax. If the user approves, the water heater temperature is automatically adjusted and ambient music is played.

[0772] This system enables efficient energy use that takes into account the user's emotional state, providing a more comfortable living environment. By repeating this series of steps, we can help build a sustainable and emotionally sensitive living environment.

[0773] The processing flow will be explained below.

[0774] Step 1:

[0775] The server obtains the operating status and setting information from each electrical device in the home. Specifically, it obtains the current temperature setting, operating mode, and operating status from the air conditioner. Similarly, it obtains the current temperature setting and operating status from the water heater.

[0776] Step 2:

[0777] The server acquires and records usage data from the water meter and gas meter, for example, by periodically acquiring and recording the amount of water and gas usage every hour.

[0778] Step 3:

[0779] The server acquires the user's health data from the wearable device, specifically information such as heart rate, sleep time, and exercise amount, and uses this information to understand the user's current health condition.

[0780] Step 4:

[0781] The server obtains location information and activity data from the mobile device, confirming whether the user is at home or out, and also obtains activity data such as the number of steps taken and distance traveled.

[0782] Step 5:

[0783] The server receives weather forecasts and temperature information via the Internet, providing information such as the maximum and minimum temperatures, probability of precipitation, and humidity for the day.

[0784] Step 6:

[0785] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and recognizes the user's emotional state based on this data.

[0786] Step 7:

[0787] The server analyzes the collected physiological and voice data using an emotion engine to assess the user's stress level and emotional state. For example, if the user's heart rate is high, the server determines that the user is feeling stressed.

[0788] Step 8:

[0789] The server combines the obtained emotional state data with other collected data (health data, location information, weather information, etc.) and inputs it into the generation AI. After removing noise and normalizing the data, the optimal operating pattern is calculated.

[0790] Step 9:

[0791] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[0792] Step 10:

[0793] Based on the analysis results, the server generates notification content suggesting optimization to the user. For example, it generates a suggestion such as, "Based on the current outside temperature and your health data, we recommend lowering the air conditioner temperature setting by 1 degree."

[0794] Step 11:

[0795] The device sends a notification to the user's mobile device and displays the optimization suggestion, and the user can check the notification and choose to accept or reject the suggestion.

[0796] Step 12:

[0797] If the user approves the proposal, the server sends an instruction to the electrical appliance to automatically control it, for example, to change the temperature setting of the air conditioner.

[0798] Step 13:

[0799] The server checks whether electrical equipment is working properly, for example, checking whether the air conditioner has started operating at the specified temperature setting.

[0800] Step 14:

[0801] The server continuously monitors the operating status and energy consumption of each electrical device. If an abnormality is detected, it notifies the user and suggests further optimization if necessary.

[0802] By repeating this series of steps, the home environment and energy consumption can be dynamically optimized. Furthermore, it is possible to make suggestions and control that take into account the user's emotional state, providing a more comfortable and healthy living environment.

[0803] Example 2

[0804] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0805] Conventional home electrical appliance and resource management systems typically control the operating status and settings of individual devices independently, limiting their ability to provide an optimal environment that takes into account the user's health and emotional state. It is also difficult to effectively integrate and adaptively manage the diverse data obtained from multiple devices. Therefore, an integrated system is needed to maintain an efficient and comfortable home environment.

[0806] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile terminal; means for acquiring temperature and weather forecasts via the Internet; means for recognizing an emotional state based on the acquired data, physiological data from the wearable device, and voice data from the mobile terminal; analysis means including a generation AI that predicts the operation pattern of the electrical appliances using an optimization algorithm based on the acquired data and the recognized emotional state and performs optimal adjustments; means for notifying the user of the optimization results obtained by the analysis means; and means for automatically controlling each electrical appliance based on the user's approval. This enables integrated and efficient optimization of the home environment, taking into account the user's health and emotional state.

[0807] "Various electrical appliances in homes" refers to all electrical and electronic devices used in homes, such as air conditioners, water heaters, air purifiers, and lighting.

[0808] "Operating status and setting information" refers to all information related to the operation of each electrical device, such as its on / off status, current set temperature, and operating mode.

[0809] "Water and gas usage" refers to the amount of water and gas consumed within a home.

[0810] "Wearable devices" refers to devices such as smartwatches and fitness trackers that can collect health data when worn by the user.

[0811] "Personal health data" refers to physiological and health information about a user, such as their heart rate, sleep duration, and activity level.

[0812] "Mobile device" refers to a mobile device such as a smartphone or tablet.

[0813] "Location information and activity data" refers to information such as current location, number of steps, and distance traveled provided by the mobile device via GPS.

[0814] "Means of obtaining temperature and weather forecasts via the Internet" refers to means of connecting to the Internet and obtaining local temperature and weather forecasts from web services or APIs that provide weather information.

[0815] "Physiological data" refers to data relating to the physiological state of the body, such as the user's heart rate and body temperature.

[0816] "Voice data" refers to data relating to a user's vocalizations and tone of voice collected through the microphone of a mobile device.

[0817] "Means for recognizing emotional state" refers to means for analyzing collected physiological data and voice data to recognize the stress level and emotional state of the user.

[0818] An "optimization algorithm" refers to a calculation procedure or method for analyzing a wide variety of data and optimizing the operating patterns and settings of electrical equipment in a home.

[0819] "Generative AI" refers to algorithms that use artificial intelligence technology to analyze data and generate optimal plans and proposals.

[0820] "Analysis means" refers to the equipment and software used to process and analyze collected data.

[0821] "Means for notifying the user of the optimization results" refers to means for displaying suggestions and instructions generated based on the analysis results on the user's terminal.

[0822] "Automatic control means" refers to a means for automatically changing the settings of an electrical device based on user approval.

[0823] The present invention is a system that integrates various electrical appliances and devices in a home with external information to efficiently and comfortably optimize the home environment. This system includes various elements that recognize the user's emotional state and adjust the environment optimally based on that state.

[0824] Data collection

[0825] The server obtains operating status and setting information from various electrical devices in the home. For example, the server can monitor the on / off status, temperature settings, and operation mode of devices such as air conditioners, water heaters, air purifiers, and lighting in real time. This information is obtained through sensors and communication modules built into each device.

[0826] The server also obtains usage data from water and gas meters to understand water and gas consumption, allowing for monitoring of overall resource usage efficiency within the home.

[0827] In addition, the server acquires user health data from wearable devices (e.g., smart watches), allowing the server to obtain information such as heart rate, sleep time, and exercise volume, enabling real-time monitoring of the user's health status.

[0828] The server can also obtain location information and activity data from mobile devices (e.g., smartphones), which can determine whether the user is at home or out and track activity such as the number of steps taken and distance traveled.

[0829] The server can also obtain temperature and weather forecasts via the Internet, thereby predicting changes in the external environment and collecting data to maintain an optimal indoor environment.

[0830] Emotion recognition by emotion engine

[0831] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and uses this data to recognize the user's emotional state. For example, a high heart rate can be determined to indicate a high likelihood of stress. Furthermore, the server can analyze the tone and tempo of the voice from the voice data to understand the user's emotional state in more detail.

[0832] Data Analysis and Optimization

[0833] The server inputs the collected data into a generative AI model for specific analysis. After removing noise and normalizing the data, it calculates the optimal operating pattern for electrical equipment by taking into account the user's past behavioral patterns, health status, current environmental information, and emotional data.

[0834] For example, the server uses the generative AI model to calculate the optimal temperature setting and operating time for an air conditioner, the temperature setting for a water heater, etc., thereby improving energy efficiency while maintaining user comfort.

[0835] Suggestions and User Notifications

[0836] Based on the analysis results, the server makes optimization suggestions to the user. For example, a notification might be displayed on the user's smartphone stating, "The current outside temperature is low, so we recommend lowering the air conditioner's set temperature by 1 degree." If the user accepts the suggestion, the server sends automatic control instructions to each electrical device and changes the air conditioner's set temperature.

[0837] Automatic Control and Examples

[0838] The server receives user approval and sends instructions for automatic control to each electrical device. For example, if the user approves a suggestion to lower the air conditioner's temperature setting by 1 degree, the server automatically adjusts the temperature setting to 22 degrees and then monitors and confirms the result again.

[0839] Below are some example prompts to input to a generative AI model:

[0840] "For this home optimization system, please suggest the optimal settings using the following data: current status of the air conditioner, water heater temperature, user's heart rate and sleep data, and outside temperature. Please suggest the optimal air conditioner setting temperature and water heater temperature setting."

[0841] This system enables efficient energy use that takes into account the user's health and emotional state, creating a comfortable living environment within the home. Furthermore, by repeating this series of steps, the creation of a sustainable and emotionally sensitive living environment is supported.

[0842] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0843] Step 1:

[0844] Input: Operation status and setting information of various electrical devices

[0845] Specific operation: The server obtains operating status and setting information (on / off status, temperature setting, operation mode, etc.) from various electrical devices in the home.

[0846] Data processing and calculation: The acquired data is collated to obtain an overall picture of the current home environment and recorded in a database.

[0847] Output: A list of successfully retrieved health and configuration information

[0848] Step 2:

[0849] Input: Health data from wearable devices

[0850] Specific operation: The server collects data such as the user's heart rate, sleep time, and exercise volume from the wearable device.

[0851] Data processing and calculation: Analyze the acquired data and normalize the user's health status and vital signs.

[0852] Output: Successfully acquired and normalized health data

[0853] Step 3:

[0854] Input: Location and activity data from your smartphone

[0855] Specific operation: The server obtains location information (GPS data) and activity data (number of steps, distance traveled, etc.) from the mobile device.

[0856] Data processing and calculation: Based on the acquired location information, the system determines whether the user is at home or out and compiles the amount of activity.

[0857] Output: Successfully acquired location and activity data, and the result of determining the user's current location.

[0858] Step 4:

[0859] Input: Temperature and weather forecast data from the internet

[0860] What it does: The server retrieves temperature and weather forecast data via the Internet.

[0861] Data processing and calculation: Analyze acquired weather forecast data and predict future climate conditions.

[0862] Output: Successfully retrieved temperature and weather forecast data, predicted weather conditions

[0863] Step 5:

[0864] Input: Health data, voice data

[0865] Specific operation: The server collects physiological data such as heart rate from the wearable device and audio data from the mobile device.

[0866] Data processing and calculation: Analyzes heart rate and voice data to recognize the user's emotional state.

[0867] Output: Perceived user emotional state (e.g., stress level, emotional tendency, etc.)

[0868] Step 6:

[0869] Input: Various data (electrical device data, health data, location information, temperature data, emotional data)

[0870] Specific operation: The server inputs the collected data into the generative AI model.

[0871] Data processing and calculation: Data is denoised and normalised, and an optimisation algorithm is used to predict the optimal operating pattern for each piece of electrical equipment.

[0872] Output: Optimal operating patterns and adjustment parameters

[0873] Step 7:

[0874] Input: Optimization results

[0875] Specific operation: Based on the analysis results, the server notifies the user of optimization suggestions.

[0876] Data processing and calculation: The analysis results are converted into a format that is easy for users to understand and displayed on devices such as smartphones.

[0877] Output: Optimization suggestions communicated to the user

[0878] Step 8:

[0879] Input: User approval result

[0880] Specific operation: When the user approves the proposal, the server sends instructions for automatic control to each electrical device.

[0881] Data processing and calculation: Generates control instructions for each electrical device and sends them to the corresponding device.

[0882] Output: Automatic control instructions are sent to change the settings of each electrical device.

[0883] (Application example 2)

[0884] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0885] Currently, environmental management in homes and factories is often based on only a few electrical appliances and devices. This makes comprehensive and efficient environmental optimization difficult, and adaptation based on the user's individual health and emotional state is lacking. Furthermore, data analysis and suggestion functions for improving work efficiency and safety are still limited. The present invention aims to achieve comprehensive and individually adaptive optimization of the environment and work conditions in homes and factories, thereby improving energy efficiency and work safety and comfort.

[0886] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0887] In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile terminal; means for acquiring temperature and weather forecasts via the Internet; means for recognizing an individual's emotional state using an emotion engine; analysis means including a generation AI that predicts operation patterns of electrical appliances using an optimization algorithm based on the acquired data and makes optimal adjustments; means for notifying a user of the optimization results obtained by the analysis means; means for automatically controlling each electrical appliance based on the user's approval; means for acquiring operation status and setting information from industrial machinery; means for acquiring health data and emotional states from workers' wearable devices; means for acquiring external environment data via the Internet; analysis means including a generation AI that predicts operation patterns using an optimization algorithm based on the acquired data and makes optimal adjustments; means for notifying a manager and a worker of the optimization results obtained by the analysis means; and means for automatically controlling industrial machinery based on the manager and a worker's approval. This makes it possible to individually optimize the environment and working conditions within homes and factories, improving energy efficiency, work efficiency, and safety.

[0888] "Various electrical equipment" refers to electrical equipment used in homes and factories, such as air conditioners, water heaters, air purifiers, and lighting.

[0889] "Operation status" is information that indicates the current operating state of electrical equipment and industrial machinery.

[0890] "Setting information" refers to information relating to the operating parameters and operating modes of electrical equipment and industrial machinery.

[0891] "Water and gas usage" is data measuring the amount of water and gas consumed within homes and factories.

[0892] A "wearable device" is a device that measures health data by being worn, such as a smartwatch or fitness tracker.

[0893] "Health data" is data that indicates an individual's health status, such as heart rate, body temperature, and sleep patterns.

[0894] A "mobile terminal" is a mobile device such as a smartphone or tablet.

[0895] "Location information" is information that indicates the current location of the user and is collected by the mobile terminal.

[0896] "Activity data" is data that indicates the user's movement and activity status, such as the number of steps, distance traveled, and calories burned.

[0897] "Means for obtaining temperature and weather forecast via the Internet" is a function for obtaining outside temperature and weather information via the Internet.

[0898] An "emotion engine" is an algorithm or function that analyzes physiological and audio data to recognize the user's emotional state.

[0899] An "optimization algorithm" is a series of calculation methods for calculating optimal equipment operating patterns and settings based on collected data.

[0900] "Generative AI" is an artificial intelligence technology that analyzes large amounts of data and performs efficient optimization.

[0901] The "analysis means" is the part of the system that includes functions ranging from data preprocessing to the execution of optimization algorithms.

[0902] "Notification means" is a function for notifying users and administrators of optimization results and other important information.

[0903] "Automatic control means" refers to a function for automatically changing the settings of electrical equipment or industrial machinery after obtaining user approval.

[0904] "Industrial machinery" refers to equipment such as production line machines and robots used in factories.

[0905] "External environmental data" refers to data related to the environment, such as temperature, humidity, and weather information inside and outside the factory.

[0906] An "administrator" is a person whose role is to oversee the operation of a factory or system and make optimization proposals and approve controls.

[0907] "Worker" means an employee who performs work in a factory.

[0908] "Noise removal" is the process of removing unnecessary information and errors from collected data.

[0909] "Normalization" is the process of converting collected data into a unified scale or format.

[0910] The present invention relates to a system for comprehensively and efficiently optimizing the environment and working conditions in homes and factories. This system uses multiple data collection and analysis methods to automatically control equipment while taking into account the individual health and emotional states of users.

[0911] 1. System Configuration

[0912] The system consists of the following main components:

[0913] 1. Data collection methods:

[0914] A means of acquiring operating status and setting information from various electrical devices and industrial machines in homes and factories.

[0915] A means of obtaining water and gas usage figures.

[0916] A means of obtaining health data (e.g., heart rate, body temperature, sleep patterns) from wearable devices (e.g., smartwatches).

[0917] A means of obtaining location and activity data from mobile devices (e.g., smartphones).

[0918] A means of obtaining temperature and weather forecasts via the Internet.

[0919] A means of recognizing an individual's emotional state using an emotion engine.

[0920] 2. Analysis method:

[0921] A means of denoising and normalising the data.

[0922] A method of using generative AI models to run optimization algorithms based on collected data, predicting operating patterns of electrical equipment and industrial machinery, and making optimal adjustments.

[0923] 3. Means of notification:

[0924] A means for notifying the user or administrator of the optimization results obtained by the analysis means.

[0925] 4. Automatic control means:

[0926] A means of automatically controlling electrical equipment and industrial machinery based on user or administrator approval.

[0927] 2. Hardware and Software Used

[0928] Hardware:

[0929] Smartwatches and smartphones for data collection.

[0930] Various sensors (temperature, humidity, electricity meter, water meter, etc.).

[0931] Industrial machinery in a factory.

[0932] software:

[0933] Generative AI models that include data analysis and optimization algorithms.

[0934] Emotion recognition algorithm using emotion engine.

[0935] Notification systems (e.g. smartphone apps).

[0936] Software that uses an Internet API to obtain temperature and weather forecast data.

[0937] 3. Data processing and calculation

[0938] The server preprocesses the data collected from various devices, removing noise and normalizing it. The preprocessed data is then input into a generative AI model, which calculates optimal operating patterns based on the user's past behavioral patterns, current environmental information, health status, and emotional state.

[0939] Here are some specific examples of data processing:

[0940] Temperature control within the home: The server collects indoor temperature data from temperature sensors, compares it with weather forecast data, and makes suggestions to optimize the air conditioner temperature setting.

[0941] Machine operation patterns within the factory: The server analyzes the operation data of industrial machines and, in conjunction with the health data of workers, suggests optimal operating times and settings for the equipment.

[0942] 4. Examples of prompts

[0943] The following prompt demonstrates how this system works:

[0944] You are the developer of a system that integrates worker health and environmental data in a factory to make optimization suggestions.

[0945] If a worker's heart rate data exceeds 80, it is determined that the worker is stressed.

[0946] Generate suggestions to adjust machine settings based on weather data.

[0947] The above is an embodiment of the invention. The present invention individually optimizes the environment and working conditions in a house or factory, making it possible to improve energy efficiency, work efficiency, and safety.

[0948] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0949] Step 1:

[0950] The server acquires operating status and setting information from various electrical devices and industrial machines in homes and factories.

[0951] Input: Operational data and setting information from each device

[0952] Data Processing: Collecting data and converting it into a centralized format.

[0953] Specific operation: The server periodically calls the API of each device to obtain its operating status and settings, such as the temperature setting and operation mode of an air conditioner, or the operating time and load of industrial machinery.

[0954] Step 2:

[0955] The server obtains usage data from water and gas meters.

[0956] Input: Consumption data from water and gas meters

[0957] Data processing: Data is aggregated over time to analyze usage patterns.

[0958] Specific operation: The server collects consumption data from water meters and gas meters and compiles the data on a daily or monthly basis.

[0959] Step 3:

[0960] The server acquires the personal health data from the wearable device.

[0961] Input: Heart rate, body temperature, sleep data from smartwatch etc.

[0962] Data processing: Organize the data by individual and store it as time-series data.

[0963] Specific operation: The server periodically collects data from the wearable device via an API and stores the heart rate, body temperature, and sleep data for each individual.

[0964] Step 4:

[0965] The server obtains location information and activity data from the mobile device.

[0966] Input: Location information and activity data from your smartphone (number of steps, distance traveled, etc.)

[0967] Data processing: Plot location information on a map and organize activity data along a timeline.

[0968] Specific operation: The server collects GPS data and activity records from the smartphone and analyzes the movement route and activity level.

[0969] Step 5:

[0970] The server retrieves the temperature and weather forecast via the Internet.

[0971] Input: Real-time weather data from a weather data provider

[0972] Data processing: Organize data as local area information and extract predictive data.

[0973] Specific operation: The server calls the weather data API to obtain and store the current temperature and future weather forecast.

[0974] Step 6:

[0975] The server uses an emotion engine to recognize the emotional state of the individual.

[0976] Input: Heart rate and audio data from wearable devices

[0977] Data processing: Analyze the data with the emotion engine and evaluate the emotional state.

[0978] Specific operation: The server inputs heart rate and voice data into the emotion engine to determine stress levels and emotional states.

[0979] Step 7:

[0980] The server uses an optimization algorithm based on the acquired data to predict the operating patterns of electrical equipment and operates an analysis means including a generation AI that makes optimal adjustments.

[0981] Input: Operating status data, health data, activity data, weather data, emotion data

[0982] Data calculation: Using a generative AI model, optimal operating patterns are calculated.

[0983] How it works: The server inputs various data into the generative AI and calculates the optimal settings to maximize energy efficiency and comfort.

[0984] Step 8:

[0985] The server notifies the user of the optimization results obtained by the analysis means.

[0986] Input: Optimized operation patterns and adjustment proposals

[0987] Output: Notification to the user's smartphone and the administrator's device

[0988] Specific operation: The server notifies the user or administrator of the generated optimization proposal on their device. Example: "The current outside temperature is low, so we recommend lowering the air conditioner setting by 1 degree."

[0989] Step 9:

[0990] Based on the user's approval, the server automatically controls each electrical device.

[0991] Input: User or administrator approval

[0992] Output: Changing the settings of electrical equipment and industrial machines

[0993] Specific operation: After obtaining the user's approval, the server automatically sends instructions to change the settings to each device and performs the actual operation.

[0994] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0995] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0996] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0997] [Third embodiment]

[0998] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0999] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1000] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1001] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1002] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1003] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1004] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1005] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1006] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1007] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1008] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1009] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1010] The present invention is a system for optimizing the home environment efficiently and comfortably, integrating various electrical appliances, devices, and external information to perform optimization. The system includes the following steps and elements:

[1011] Data collection

[1012] Data collection from devices:

[1013] The server continuously collects operating status and setting information from each electrical device in the home (e.g., air conditioner, water heater, air purifier, lighting). This allows the server to grasp the on / off status, temperature setting, operation mode, etc. of each device in real time. It also collects usage data from water and gas meters.

[1014] Data collection from wearable devices:

[1015] The server acquires the user's health data from the wearable device (e.g., smart watch), specifically, heart rate, sleep time, exercise amount, etc., and grasps the user's health condition.

[1016] Mobile data collection:

[1017] The server obtains location information and activity data from the mobile device (e.g., smartphone), which determines whether the user is at home or out, and also tracks the amount of activity, such as the number of steps taken and the distance traveled.

[1018] Data collection from the Internet:

[1019] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[1020] Data Analysis and Optimization

[1021] Data preprocessing and analysis:

[1022] The server inputs the collected data into the AI ​​generator for specific analysis. After removing noise and normalizing the data, the AI ​​calculates the optimal operating pattern for electrical equipment, taking into account the user's past behavioral patterns, health status, and external environment.

[1023] Use of optimization algorithms:

[1024] The server uses generative AI to run algorithms that optimize the use of electrical equipment and resources, automatically determining things like air conditioner temperature settings and water heater operation schedules, enabling efficient energy use.

[1025] Suggestions and User Notifications

[1026] Optimization results suggestion:

[1027] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification may be displayed on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[1028] Automatic Control

[1029] User consent and control:

[1030] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it, for example, to change the temperature setting of an air conditioner, and then monitors and confirms the results.

[1031] Specific examples

[1032] 1. Morning scenario:

[1033] When the user wakes up in the morning, the server retrieves the user's sleep time and heart rate data from the smartwatch and, based on this, suggests optimizing the air conditioner temperature setting to maintain a comfortable room temperature. If the user approves, the air conditioner temperature setting will be automatically adjusted.

[1034] 2. Shower scenario:

[1035] The server detects when a user is about to take a shower from their smartphone and checks the current temperature of the water heater. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees, and if the user agrees, the set temperature is automatically adjusted.

[1036] This system enables efficient energy use and provides users with a comfortable living environment. Repeating these steps will help build a sustainable living environment.

[1037] The processing flow will be explained below.

[1038] Step 1:

[1039] The server acquires operating status and setting information from each electrical device in the home. For example, it acquires the current temperature setting, operating mode, and operating status from the air conditioner. Similarly, it acquires the current temperature setting and operating status from the water heater.

[1040] Step 2:

[1041] The server acquires and records usage data from the water meter and gas meter, for example, the amount of water and gas used every hour.

[1042] Step 3:

[1043] The server acquires the user's health data from the wearable device, specifically information such as heart rate, sleep time, and exercise amount, and uses this information to understand the user's current health condition.

[1044] Step 4:

[1045] The server acquires location information and activity data from the mobile device, confirms whether the user is at home or out, and also acquires activity data such as the number of steps taken and distance traveled.

[1046] Step 5:

[1047] The server receives weather forecasts and temperature information via the Internet, providing information such as the maximum and minimum temperatures, probability of precipitation, and humidity for the day.

[1048] Step 6:

[1049] The server denoises and normalizes the collected data, correcting outliers and missing values, and formatting the data into a form that is easy to analyze.

[1050] Step 7:

[1051] The server inputs the formatted data into the AI ​​generator for analysis. Specifically, it predicts the optimal operating pattern for electrical equipment by taking into account the user's past behavioral patterns, health status, and current environmental information.

[1052] Step 8:

[1053] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[1054] Step 9:

[1055] The server compiles all the analysis results and generates a notification that suggests optimization to the user, such as "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[1056] Step 10:

[1057] The device sends a notification to the user's mobile device and displays the optimization suggestion, and the user can check the notification and choose to accept or reject the suggestion.

[1058] Step 11:

[1059] If the user selects approval, the server sends an instruction to the electrical appliance to automatically control it, for example, to an air conditioner to change the temperature setting.

[1060] Step 12:

[1061] The server checks whether electrical equipment is working properly, for example, checking whether the air conditioner has started operating at the specified temperature setting.

[1062] Step 13:

[1063] The server continuously monitors the operating status and energy consumption of each electrical device. If an abnormality is detected, it notifies the user and suggests further optimization if necessary.

[1064] By repeating this series of steps, the home's environment and energy consumption can be dynamically optimized.

[1065] Example 1

[1066] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1067] The efficient operation of various electrical appliances and devices in homes and the maintenance of a comfortable and healthy living environment for individuals are required. The present invention solves the problem of improving energy efficiency and ensuring user convenience by providing a system that manages these in an integrated manner and proposes and executes optimal operation patterns.

[1068] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1069] In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile device; means for acquiring temperature and weather forecasts via the Internet; analysis means including a generation AI that uses an optimization algorithm to predict operation patterns of the electrical appliances based on the acquired data and makes optimal adjustments; means for notifying the user of the optimization results obtained by the analysis means; means for automatically controlling each electrical appliance based on the user's approval; means for denoising and normalizing the collected data; means for integrating the operation status of the target appliances with external environmental data to calculate optimal operation patterns of the electrical appliances and generate proposals; and means for notifying the user of the generated proposals to the user's mobile device. This makes it possible to optimize the user's living environment and improve energy efficiency.

[1070] - "Various electrical appliances" refers to electrical machinery and equipment used in homes, such as air conditioners, water heaters, air purifiers, and lighting.

[1071] "Operating status" refers to information about whether an electrical device is currently operating or in what mode it is operating.

[1072] "Setting information" refers to information relating to operating conditions and parameters designated by the user for the electrical device, such as temperature settings and operation modes.

[1073] "Usage data" is information about the consumption of resources such as water and gas.

[1074] A "wearable device" is an electronic device that is designed to be worn by the user, and includes smartwatches and the like.

[1075] "Health data" is information that indicates the user's health condition, such as heart rate, sleep time, and amount of exercise.

[1076] A "mobile device" is a portable communication device such as a smartphone that is capable of collecting location information and activity data.

[1077] "Location information" is information about the current location obtained by the GPS function of the mobile terminal.

[1078] "Activity data" is information indicating the amount of physical activity of the user, such as the number of steps taken and the distance traveled.

[1079] "Temperature" refers to the temperature in the atmosphere, and is information indicating the temperature conditions of the external environment.

[1080] "Weather forecast" is information about upcoming weather changes and current weather.

[1081] An "optimization algorithm" is a mathematical method for calculating efficient operating patterns for electrical equipment based on collected data.

[1082] "Generative AI" is a type of artificial intelligence that uses machine learning and deep learning techniques to analyze data and generate optimal operating patterns.

[1083] "Analysis means" refers to the techniques and devices used to perform analysis based on collected data.

[1084] The "optimization result" is information that indicates an efficient method of using and operation pattern of the electrical equipment, derived by the analysis means.

[1085] "Notification means" refers to a means for informing the user of information, and includes notifications to smartphones, etc.

[1086] "Automatic control" is a mechanism for automatically adjusting the operation of each electrical device after obtaining user approval.

[1087] "Noise removal" is the process of removing unnecessary or erroneous data in data analysis.

[1088] "Normalization" is the process of converting the range of data to a certain scale.

[1089] The "suggestion content" is information about the settings and operation patterns of electrical appliances that are recommended to the user based on the optimization algorithm.

[1090] This invention is a system for optimizing the home environment efficiently and comfortably. The system integrates various electrical appliances, devices, and external information to perform optimization.

[1091] Data collection

[1092] Collecting data from devices

[1093] The server collects operating status and setting information from each electrical device in the home, such as the air conditioner, water heater, air purifier, and lighting. Specifically, it obtains data such as the air conditioner's on / off status, temperature setting, and operation mode. It also obtains usage data from water and gas meters.

[1094] Data collection from wearable devices

[1095] The server collects user health data from wearable devices such as smartwatches, including heart rate, sleep duration, and exercise volume.

[1096] Data collection from mobile devices

[1097] The server collects location information and activity data from mobile devices such as smartphones, which allows it to determine whether the user is at home or out, as well as the amount of activity such as the number of steps taken and distance traveled.

[1098] Data collection from the internet

[1099] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[1100] Data Analysis and Optimization

[1101] Data Preprocessing

[1102] The server performs noise removal and normalization on the various collected data. Specifically, it complements missing values ​​in the data and removes outliers. It also performs normalization to make the data range consistent. This is done using a data preprocessing library (e.g., pandas, NumPy).

[1103] Using generative AI models

[1104] The server uses a generative AI model to calculate the optimal operating pattern for each electrical device. Specifically, normalized data is input into the generative AI model (e.g., TensorFlow, PyTorch) to predict the optimal energy consumption pattern.

[1105] Suggestions and User Notifications

[1106] Optimization results suggestions

[1107] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification might be displayed on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree." This is done using a notification service (e.g., Firebase Cloud Messaging).

[1108] Automatic Control

[1109] User Authorization and Control

[1110] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it. For example, it sends an instruction to change the temperature setting of an air conditioner and then monitors and confirms the results. This is done using the smart home control API.

[1111] Specific examples

[1112] 1. Morning Scenario

[1113] The server receives the user's sleep data from the smartwatch and analyzes it together with the outside temperature data. As a result, it sends a notification to the smartphone suggesting that the current room temperature be raised by 1 degree. If the user approves, the server sends a command to change the set temperature to the air conditioner.

[1114] 2. Shower scenario

[1115] The server detects from the smartphone sensor that the user is about to take a shower. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees and notifies the smartphone. If the user agrees, the server sends a command to change the set temperature to the water heater.

[1116] Prompt Sentence Examples

[1117] Example prompt 1: Morning optimization suggestions

[1118] "Good morning. According to your recent sleep data, it appears that you have not been spending much time in deep sleep. Raising the current room temperature by 1 degree will help you wake up more comfortably. Would you like to change the air conditioner temperature setting?"

[1119] Example prompt 2: Shower optimization suggestions

[1120] "The outside temperature is dropping. We suggest you increase the water heater temperature by 2 degrees to make showering more comfortable. Would you like to do this?"

[1121] This makes it possible to use energy efficiently and provide users with a comfortable living environment.

[1122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1123] Step 1:

[1124] Collecting data from devices

[1125] The server collects operating status and setting information from various electrical devices in the home. Specifically, it obtains information such as the air conditioner's on / off status, temperature setting, and operation mode. The server sends requests at regular intervals and receives current status information from the electrical devices.

[1126] Input: Request responses from various electrical devices

[1127] Output: Operational data of each device (on / off status, temperature setting, operation mode)

[1128] Step 2:

[1129] Data collection from wearable devices

[1130] The server collects user health data from wearable devices such as smartwatches, and periodically uploads the data from the wearable devices to the server.

[1131] Input: Health data from a smartwatch

[1132] Output: User's health data (heart rate, sleep time, exercise amount)

[1133] Step 3:

[1134] Data collection from mobile devices

[1135] The server collects location information and activity data from mobile devices such as smartphones, and determines whether the user is at home or out. The server periodically transmits the location information and activity data to the server using the mobile device's GPS and activity tracking functions.

[1136] Input: Location and activity data from your smartphone

[1137] Output: User location and activity data

[1138] Step 4:

[1139] Data collection from the internet

[1140] The server retrieves weather forecasts and current temperatures via the Internet, sends a request to the weather API, and stores the retrieved data internally.

[1141] Input: Request response from the weather API

[1142] Output: Weather forecast data and current temperature data

[1143] Step 5:

[1144] Data preprocessing and analysis

[1145] The server performs noise removal and normalization on the various collected data. Specifically, it complements missing values ​​in the collected data and removes outliers. It also performs normalization to make the data range consistent. This is done using a data preprocessing library (e.g., pandas, NumPy).

[1146] Input: Various collected data (electrical equipment operation data, health data, location information, weather data)

[1147] Output: Normalized data

[1148] Step 6:

[1149] Using generative AI models

[1150] The server uses a generative AI model to calculate the optimal operating pattern for each electrical device. The normalized data is input into the generative AI model (e.g., TensorFlow, PyTorch) to predict the optimal energy consumption pattern.

[1151] Input: Normalized data

[1152] Output: Optimized operating pattern

[1153] Step 7:

[1154] Optimization results suggestions

[1155] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification such as "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree" is displayed on the user's smartphone. This is achieved using a notification service (e.g., Firebase Cloud Messaging).

[1156] Input: Optimized operating pattern

[1157] Output: Proposal notification to user

[1158] Step 8:

[1159] User Authorization and Control

[1160] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it. For example, it sends an instruction to change the temperature setting of an air conditioner and then monitors and confirms the results. This is done using the smart home control API.

[1161] Input: User approval

[1162] Output: Control instructions to electrical devices

[1163] (Application example 1)

[1164] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1165] This invention relates to a system that comprehensively monitors and controls the operating status and environmental data of various equipment and machines in a factory, improving energy efficiency and optimizing productivity. Conventional systems manage each piece of equipment individually, without proper data integration or analysis, which often results in a lack of overall efficiency. Furthermore, insufficient coordination between each piece of equipment makes it difficult to optimize overall energy consumption. This leads to problems such as increased energy costs and reduced productivity.

[1166] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1167] In this invention, the server includes means for acquiring operation status and setting information from various electrical appliances in the home, means for acquiring water and gas usage, means for acquiring personal health data from a wearable device, means for acquiring location information and activity data from a mobile terminal, means for acquiring temperature and weather forecasts via the Internet, means for acquiring operation status and environmental data from various pieces of equipment in the factory, analysis means including a generation AI that uses an optimization algorithm based on the acquired data to predict the operation pattern of the factory equipment and make optimal adjustments, means for notifying workers of the optimization results obtained by the analysis means, and means for automatically controlling each piece of equipment based on the worker's approval, thereby enabling collaboration between equipment in the factory and optimization of energy consumption.

[1168] "Various electrical appliances in the home" refers to household electrical appliances such as air conditioners, water heaters, air purifiers, and lighting.

[1169] "Operating status" refers to information that indicates the status of each device, such as its on / off status, the currently set operating mode, and temperature setting.

[1170] "Setting information" refers to parameters and values ​​that are set in advance to control the operation of an electrical device.

[1171] "Water and gas usage" refers to data that indicates the amount of tap water and gas consumed within a home.

[1172] "Wearable devices" refers to electronic devices that can be worn by a user and that can collect health and activity data. Examples include smartwatches and fitness trackers.

[1173] "Health data" refers to data that includes information about an individual's health status, such as heart rate, sleep duration, and amount of exercise.

[1174] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[1175] "Location Information" means geographic location data obtained from a mobile or other device.

[1176] "Activity data" refers to data that includes information about the user's daily activities, such as the number of steps taken, distance traveled, and time spent at a destination.

[1177] "Temperature and weather forecast via the Internet" refers to current temperature and future weather forecast information obtained using an Internet connection.

[1178] "Various facilities within the factory" includes production facilities and environmental control devices used within the factory, such as robotic arms, conveyors, and HVAC systems.

[1179] "Environmental data" refers to data that includes information about the surrounding environment within a factory or home, such as temperature, humidity, and illuminance.

[1180] "Optimization algorithm" refers to an algorithm that calculates the best operation to achieve a specific goal based on collected data.

[1181] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and suggest optimal ways to operate devices and systems.

[1182] "Analysis means" refers to a device or process for analyzing collected data and outputting optimization results.

[1183] "Worker" refers to a person who performs work in a factory or other facility.

[1184] "Automatic control means" refers to a system that includes a control device or program for automatically changing the settings or operation of equipment based on the optimized results.

[1185] This invention is a system for efficiently and optimally managing and controlling various equipment and environments within a factory, and is implemented through the procedures of data collection, analysis, optimization, notification, and control from various equipment. This system includes the following procedures and elements.

[1186] Data collection

[1187] The server continuously collects operational status and setting information from various pieces of equipment in the factory (robot arms, conveyors, HVAC systems, etc.). This allows information such as the operating status, set temperature, and operating mode of each piece of equipment to be sent to the server in real time. Environmental data such as temperature, humidity, and illuminance are also collected via sensors.

[1188] Data Analysis and Optimization

[1189] The server uses a generative AI model to analyze the various collected data, removes noise and normalizes the data, and then calculates the optimal equipment operating pattern taking into account past operating patterns and environmental conditions.

[1190] Proposals and worker notifications

[1191] Based on the analysis results, the server will suggest optimization measures to the worker. For example, a notification such as "We recommend lowering the current room temperature by 2 degrees" will be displayed on the worker's device.

[1192] Automatic Control

[1193] Once the worker approves the optimization proposal, the server sends automatic control instructions to each piece of equipment, such as adjusting the robot arm's operating schedule or changing the temperature setting of the HVAC system.

[1194] Specific examples

[1195] 1. Production line optimization: The server collects robot arm movement data and proposes optimal movement timing and patterns. Once approved by the worker, the robot arm's movement pattern is automatically changed.

[1196] 2. Managing the factory environment: The server collects data from temperature and humidity sensors and makes recommendations to optimize the temperature and humidity settings of the HVAC system. Once the worker approves the recommendations, the HVAC system settings are automatically adjusted.

[1197] Hardware and software used

[1198] Hardware: Various sensors in the factory (temperature, humidity, light, etc.), robotic arms, HVAC systems, servers, and worker terminals.

[1199] Software: Data collection, analysis, notification and control program using Python. Interface with devices using REST API.

[1200] Prompt Sentence Examples

[1201] As an example, data is collected from a temperature sensor, and the prompt text sent by the server to the generative AI model when the temperature is 25 degrees and the humidity is 60% is shown below:

[1202] "Here is the environmental data for the factory. Temperature: 25°C, humidity: 60%. Please suggest the optimal operating pattern for each piece of equipment."

[1203] This system enables coordination between equipment within a factory and optimizes energy consumption, resulting in improved efficiency and cost reduction.

[1204] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1205] Step 1:

[1206] Starting data collection and acquiring input

[1207] The server collects real-time operational status and environmental data from various sensors and equipment in the factory. Specifically, it collects current temperature data from temperature sensors and current humidity data from humidity sensors. It also collects operational status and setting information from robotic arms and HVAC systems. This allows data on temperature, humidity, and equipment operational status to be collected and input to the server.

[1208] Step 2:

[1209] Data preprocessing and denoising

[1210] The server performs preprocessing on the collected data. In this step, it removes noise and normalizes the data. For example, if data obtained from a temperature sensor contains outliers, it removes them. The input is the collected environmental data and equipment data, and the output is the data that has been denoised and normalized.

[1211] Step 3:

[1212] Data input and analysis for generative AI models

[1213] The server inputs the preprocessed data into a generative AI model for analysis. The generative AI model used here predicts optimal equipment operating patterns based on past data and current conditions. For example, when temperature and humidity data is input, the optimal settings for an HVAC system are calculated based on that data. The input is noise-removed data, and the output is optimized equipment settings and operating patterns.

[1214] Step 4:

[1215] Notifying the workers of the analysis results

[1216] The server notifies the worker of optimization suggestions based on the analysis results. This notification is displayed on the worker's device. For example, a message such as "We recommend lowering the current room temperature by 2 degrees" is displayed. The input is the analysis result from the generative AI model, and the output is a notification message sent to the worker's device.

[1217] Step 5:

[1218] Operator approval and start of automatic control

[1219] When an operator approves an optimization proposal, the server sends automatic control instructions to each piece of equipment. For example, these instructions include changing the temperature setting of an HVAC system or adjusting the operation schedule of a robot arm. The input is the operator's approval, and the output is a control instruction for each piece of equipment.

[1220] Step 6:

[1221] Retrieval Monitoring and Feedback

[1222] After issuing the control command, the server monitors the equipment and environmental data again and re-optimizes as necessary. This allows for continuous optimization of equipment efficiency and energy consumption. The input is the latest operating status and environmental data, and the output is the re-optimized settings.

[1223] The above steps will enable coordination between equipment within the factory and optimize energy consumption, improving efficiency and reducing costs.

[1224] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1225] The present invention is a system for optimizing the home environment efficiently and comfortably, integrating various electrical appliances, devices, and external information to perform optimization. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, optimization can be performed that is adapted to the user's emotional state. This system includes the following procedures and elements.

[1226] Data collection

[1227] Data collection from devices:

[1228] The server collects operating status and setting information from each electrical device in the home (e.g., air conditioner, water heater, air purifier, lighting). This allows the server to grasp the on / off status, temperature setting, operation mode, etc. of each device in real time. It also collects usage data from water and gas meters.

[1229] Data collection from wearable devices:

[1230] The server acquires the user's health data from the wearable device (e.g., smart watch), specifically, heart rate, sleep time, exercise amount, etc., and grasps the user's current health condition.

[1231] Mobile data collection:

[1232] The server obtains location information and activity data from the mobile device (e.g., smartphone), which determines whether the user is at home or out, and also tracks the amount of activity, such as the number of steps taken and distance traveled.

[1233] Data collection from the Internet:

[1234] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[1235] Emotion recognition by emotion engine

[1236] Emotion data collection:

[1237] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and recognizes the user's emotional state based on this data.

[1238] Emotional Data Analysis:

[1239] The server uses an emotion engine to analyze the collected physiological and audio data and evaluate the user's stress level and emotional state. For example, if the user's heart rate is high, the server determines that the user is feeling stressed.

[1240] Data Analysis and Optimization

[1241] Data preprocessing and analysis:

[1242] The server inputs the collected data into the AI ​​generator for specific analysis. After removing noise and normalizing the data, the AI ​​calculates the optimal operating pattern for the electrical equipment, taking into account the user's past behavioral patterns, health status, current environmental information, and emotional data.

[1243] Use of optimization algorithms:

[1244] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[1245] Suggestions and User Notifications

[1246] Optimization results suggestion:

[1247] The server then makes optimization suggestions to the user based on the analysis results. For example, it may display a notification on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[1248] Automatic Control

[1249] User consent and control:

[1250] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it, for example, to change the temperature setting of an air conditioner, and then monitors and confirms the results.

[1251] Specific examples

[1252] 1. Morning scenario:

[1253] When the user wakes up in the morning, the server retrieves the user's sleep duration and heart rate data from the smartwatch and, based on this, suggests optimizing the air conditioner temperature setting to maintain a comfortable room temperature. If the user's heart rate is high, it also suggests playing specific music to help with stress. If the user approves, the air conditioner's temperature setting will be automatically adjusted and music will be played.

[1254] 2. Shower scenario:

[1255] The server detects when a user is about to take a shower from their smartphone and checks the current temperature of the water heater. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees. It also suggests playing ambient music to help the user relax. If the user approves, the water heater temperature is automatically adjusted and ambient music is played.

[1256] This system enables efficient energy use that takes into account the user's emotional state, providing a more comfortable living environment. By repeating this series of steps, we can help build a sustainable and emotionally sensitive living environment.

[1257] The processing flow will be explained below.

[1258] Step 1:

[1259] The server obtains the operating status and setting information from each electrical device in the home. Specifically, it obtains the current temperature setting, operating mode, and operating status from the air conditioner. Similarly, it obtains the current temperature setting and operating status from the water heater.

[1260] Step 2:

[1261] The server acquires and records usage data from the water meter and gas meter, for example, by periodically acquiring and recording the amount of water and gas usage every hour.

[1262] Step 3:

[1263] The server acquires the user's health data from the wearable device, specifically information such as heart rate, sleep time, and exercise amount, and uses this information to understand the user's current health condition.

[1264] Step 4:

[1265] The server obtains location information and activity data from the mobile device, confirming whether the user is at home or out, and also obtains activity data such as the number of steps taken and distance traveled.

[1266] Step 5:

[1267] The server receives weather forecasts and temperature information via the Internet, providing information such as the maximum and minimum temperatures, probability of precipitation, and humidity for the day.

[1268] Step 6:

[1269] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and recognizes the user's emotional state based on this data.

[1270] Step 7:

[1271] The server analyzes the collected physiological and voice data using an emotion engine to assess the user's stress level and emotional state. For example, if the user's heart rate is high, the server determines that the user is feeling stressed.

[1272] Step 8:

[1273] The server combines the obtained emotional state data with other collected data (health data, location information, weather information, etc.) and inputs it into the generation AI. After removing noise and normalizing the data, the optimal operating pattern is calculated.

[1274] Step 9:

[1275] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[1276] Step 10:

[1277] Based on the analysis results, the server generates notification content suggesting optimization to the user. For example, it generates a suggestion such as, "Based on the current outside temperature and your health data, we recommend lowering the air conditioner temperature setting by 1 degree."

[1278] Step 11:

[1279] The device sends a notification to the user's mobile device and displays the optimization suggestion, and the user can check the notification and choose to accept or reject the suggestion.

[1280] Step 12:

[1281] If the user approves the proposal, the server sends an instruction to the electrical appliance to automatically control it, for example, to change the temperature setting of the air conditioner.

[1282] Step 13:

[1283] The server checks whether electrical equipment is working properly, for example, checking whether the air conditioner has started operating at the specified temperature setting.

[1284] Step 14:

[1285] The server continuously monitors the operating status and energy consumption of each electrical device. If an abnormality is detected, it notifies the user and suggests further optimization if necessary.

[1286] By repeating this series of steps, the home environment and energy consumption can be dynamically optimized. Furthermore, it is possible to make suggestions and control that take into account the user's emotional state, providing a more comfortable and healthy living environment.

[1287] Example 2

[1288] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1289] Conventional home electrical appliance and resource management systems typically control the operating status and settings of individual devices independently, limiting their ability to provide an optimal environment that takes into account the user's health and emotional state. It is also difficult to effectively integrate and adaptively manage the diverse data obtained from multiple devices. Therefore, an integrated system is needed to maintain an efficient and comfortable home environment.

[1290] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile terminal; means for acquiring temperature and weather forecasts via the Internet; means for recognizing an emotional state based on the acquired data, physiological data from the wearable device, and voice data from the mobile terminal; analysis means including a generation AI that predicts the operation pattern of the electrical appliances using an optimization algorithm based on the acquired data and the recognized emotional state and performs optimal adjustments; means for notifying the user of the optimization results obtained by the analysis means; and means for automatically controlling each electrical appliance based on the user's approval. This enables integrated and efficient optimization of the home environment, taking into account the user's health and emotional state.

[1291] "Various electrical appliances in homes" refers to all electrical and electronic devices used in homes, such as air conditioners, water heaters, air purifiers, and lighting.

[1292] "Operating status and setting information" refers to all information related to the operation of each electrical device, such as its on / off status, current set temperature, and operating mode.

[1293] "Water and gas usage" refers to the amount of water and gas consumed within a home.

[1294] "Wearable devices" refers to devices such as smartwatches and fitness trackers that can collect health data when worn by the user.

[1295] "Personal health data" refers to physiological and health information about a user, such as their heart rate, sleep duration, and activity level.

[1296] "Mobile device" refers to a mobile device such as a smartphone or tablet.

[1297] "Location information and activity data" refers to information such as current location, number of steps, and distance traveled provided by the mobile device via GPS.

[1298] "Means of obtaining temperature and weather forecasts via the Internet" refers to means of connecting to the Internet and obtaining local temperature and weather forecasts from web services or APIs that provide weather information.

[1299] "Physiological data" refers to data relating to the physiological state of the body, such as the user's heart rate and body temperature.

[1300] "Voice data" refers to data relating to a user's vocalizations and tone of voice collected through the microphone of a mobile device.

[1301] "Means for recognizing emotional state" refers to means for analyzing collected physiological data and voice data to recognize the stress level and emotional state of the user.

[1302] An "optimization algorithm" refers to a calculation procedure or method for analyzing a wide variety of data and optimizing the operating patterns and settings of electrical equipment in a home.

[1303] "Generative AI" refers to algorithms that use artificial intelligence technology to analyze data and generate optimal plans and proposals.

[1304] "Analysis means" refers to the equipment and software used to process and analyze collected data.

[1305] "Means for notifying the user of the optimization results" refers to means for displaying suggestions and instructions generated based on the analysis results on the user's terminal.

[1306] "Automatic control means" refers to a means for automatically changing the settings of an electrical device based on user approval.

[1307] The present invention is a system that integrates various electrical appliances and devices in a home with external information to efficiently and comfortably optimize the home environment. This system includes various elements that recognize the user's emotional state and adjust the environment optimally based on that state.

[1308] Data collection

[1309] The server obtains operating status and setting information from various electrical devices in the home. For example, the server can monitor the on / off status, temperature settings, and operation mode of devices such as air conditioners, water heaters, air purifiers, and lighting in real time. This information is obtained through sensors and communication modules built into each device.

[1310] The server also obtains usage data from water and gas meters to understand water and gas consumption, allowing for monitoring of overall resource usage efficiency within the home.

[1311] In addition, the server acquires user health data from wearable devices (e.g., smart watches), allowing the server to obtain information such as heart rate, sleep time, and exercise volume, enabling real-time monitoring of the user's health status.

[1312] The server can also obtain location information and activity data from mobile devices (e.g., smartphones), which can determine whether the user is at home or out and track activity such as the number of steps taken and distance traveled.

[1313] The server can also obtain temperature and weather forecasts via the Internet, thereby predicting changes in the external environment and collecting data to maintain an optimal indoor environment.

[1314] Emotion recognition by emotion engine

[1315] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and uses this data to recognize the user's emotional state. For example, a high heart rate can be determined to indicate a high likelihood of stress. Furthermore, the server can analyze the tone and tempo of the voice from the voice data to understand the user's emotional state in more detail.

[1316] Data Analysis and Optimization

[1317] The server inputs the collected data into a generative AI model for specific analysis. After removing noise and normalizing the data, it calculates the optimal operating pattern for electrical equipment by taking into account the user's past behavioral patterns, health status, current environmental information, and emotional data.

[1318] For example, the server uses the generative AI model to calculate the optimal temperature setting and operating time for an air conditioner, the temperature setting for a water heater, etc., thereby improving energy efficiency while maintaining user comfort.

[1319] Suggestions and User Notifications

[1320] Based on the analysis results, the server makes optimization suggestions to the user. For example, a notification might be displayed on the user's smartphone stating, "The current outside temperature is low, so we recommend lowering the air conditioner's set temperature by 1 degree." If the user accepts the suggestion, the server sends automatic control instructions to each electrical device and changes the air conditioner's set temperature.

[1321] Automatic Control and Examples

[1322] The server receives user approval and sends instructions for automatic control to each electrical device. For example, if the user approves a suggestion to lower the air conditioner's temperature setting by 1 degree, the server automatically adjusts the temperature setting to 22 degrees and then monitors and confirms the result again.

[1323] Below are some example prompts to input to a generative AI model:

[1324] "For this home optimization system, please suggest the optimal settings using the following data: current status of the air conditioner, water heater temperature, user's heart rate and sleep data, and outside temperature. Please suggest the optimal air conditioner setting temperature and water heater temperature setting."

[1325] This system enables efficient energy use that takes into account the user's health and emotional state, creating a comfortable living environment within the home. Furthermore, by repeating this series of steps, the creation of a sustainable and emotionally sensitive living environment is supported.

[1326] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1327] Step 1:

[1328] Input: Operation status and setting information of various electrical devices

[1329] Specific operation: The server obtains operating status and setting information (on / off status, temperature setting, operation mode, etc.) from various electrical devices in the home.

[1330] Data processing and calculation: The acquired data is collated to obtain an overall picture of the current home environment and recorded in a database.

[1331] Output: A list of successfully retrieved health and configuration information

[1332] Step 2:

[1333] Input: Health data from wearable devices

[1334] Specific operation: The server collects data such as the user's heart rate, sleep time, and exercise volume from the wearable device.

[1335] Data processing and calculation: Analyze the acquired data and normalize the user's health status and vital signs.

[1336] Output: Successfully acquired and normalized health data

[1337] Step 3:

[1338] Input: Location and activity data from your smartphone

[1339] Specific operation: The server obtains location information (GPS data) and activity data (number of steps, distance traveled, etc.) from the mobile device.

[1340] Data processing and calculation: Based on the acquired location information, the system determines whether the user is at home or out and compiles the amount of activity.

[1341] Output: Successfully acquired location and activity data, and the result of determining the user's current location.

[1342] Step 4:

[1343] Input: Temperature and weather forecast data from the internet

[1344] What it does: The server retrieves temperature and weather forecast data via the Internet.

[1345] Data processing and calculation: Analyze acquired weather forecast data and predict future climate conditions.

[1346] Output: Successfully retrieved temperature and weather forecast data, predicted weather conditions

[1347] Step 5:

[1348] Input: Health data, voice data

[1349] Specific operation: The server collects physiological data such as heart rate from the wearable device and audio data from the mobile device.

[1350] Data processing and calculation: Analyzes heart rate and voice data to recognize the user's emotional state.

[1351] Output: Perceived user emotional state (e.g., stress level, emotional tendency, etc.)

[1352] Step 6:

[1353] Input: Various data (electrical device data, health data, location information, temperature data, emotional data)

[1354] Specific operation: The server inputs the collected data into the generative AI model.

[1355] Data processing and calculation: Data is denoised and normalised, and an optimisation algorithm is used to predict the optimal operating pattern for each piece of electrical equipment.

[1356] Output: Optimal operating patterns and adjustment parameters

[1357] Step 7:

[1358] Input: Optimization results

[1359] Specific operation: Based on the analysis results, the server notifies the user of optimization suggestions.

[1360] Data processing and calculation: The analysis results are converted into a format that is easy for users to understand and displayed on devices such as smartphones.

[1361] Output: Optimization suggestions communicated to the user

[1362] Step 8:

[1363] Input: User approval result

[1364] Specific operation: When the user approves the proposal, the server sends instructions for automatic control to each electrical device.

[1365] Data processing and calculation: Generates control instructions for each electrical device and sends them to the corresponding device.

[1366] Output: Automatic control instructions are sent to change the settings of each electrical device.

[1367] (Application example 2)

[1368] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1369] Currently, environmental management in homes and factories is often based on only a few electrical appliances and devices. This makes comprehensive and efficient environmental optimization difficult, and adaptation based on the user's individual health and emotional state is lacking. Furthermore, data analysis and suggestion functions for improving work efficiency and safety are still limited. The present invention aims to achieve comprehensive and individually adaptive optimization of the environment and work conditions in homes and factories, thereby improving energy efficiency and work safety and comfort.

[1370] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1371] In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile terminal; means for acquiring temperature and weather forecasts via the Internet; means for recognizing an individual's emotional state using an emotion engine; analysis means including a generation AI that predicts operation patterns of electrical appliances using an optimization algorithm based on the acquired data and makes optimal adjustments; means for notifying a user of the optimization results obtained by the analysis means; means for automatically controlling each electrical appliance based on the user's approval; means for acquiring operation status and setting information from industrial machinery; means for acquiring health data and emotional states from workers' wearable devices; means for acquiring external environment data via the Internet; analysis means including a generation AI that predicts operation patterns using an optimization algorithm based on the acquired data and makes optimal adjustments; means for notifying a manager and a worker of the optimization results obtained by the analysis means; and means for automatically controlling industrial machinery based on the manager and a worker's approval. This makes it possible to individually optimize the environment and working conditions within homes and factories, improving energy efficiency, work efficiency, and safety.

[1372] "Various electrical equipment" refers to electrical equipment used in homes and factories, such as air conditioners, water heaters, air purifiers, and lighting.

[1373] "Operation status" is information that indicates the current operating state of electrical equipment and industrial machinery.

[1374] "Setting information" refers to information relating to the operating parameters and operating modes of electrical equipment and industrial machinery.

[1375] "Water and gas usage" is data measuring the amount of water and gas consumed within homes and factories.

[1376] A "wearable device" is a device that measures health data by being worn, such as a smartwatch or fitness tracker.

[1377] "Health data" is data that indicates an individual's health status, such as heart rate, body temperature, and sleep patterns.

[1378] A "mobile terminal" is a mobile device such as a smartphone or tablet.

[1379] "Location information" is information that indicates the current location of the user and is collected by the mobile terminal.

[1380] "Activity data" is data that indicates the user's movement and activity status, such as the number of steps, distance traveled, and calories burned.

[1381] "Means for obtaining temperature and weather forecast via the Internet" is a function for obtaining outside temperature and weather information via the Internet.

[1382] An "emotion engine" is an algorithm or function that analyzes physiological and audio data to recognize the user's emotional state.

[1383] An "optimization algorithm" is a series of calculation methods for calculating optimal equipment operating patterns and settings based on collected data.

[1384] "Generative AI" is an artificial intelligence technology that analyzes large amounts of data and performs efficient optimization.

[1385] The "analysis means" is the part of the system that includes functions ranging from data preprocessing to the execution of optimization algorithms.

[1386] "Notification means" is a function for notifying users and administrators of optimization results and other important information.

[1387] "Automatic control means" refers to a function for automatically changing the settings of electrical equipment or industrial machinery after obtaining user approval.

[1388] "Industrial machinery" refers to equipment such as production line machines and robots used in factories.

[1389] "External environmental data" refers to data related to the environment, such as temperature, humidity, and weather information inside and outside the factory.

[1390] An "administrator" is a person whose role is to oversee the operation of a factory or system and make optimization proposals and approve controls.

[1391] "Worker" means an employee who performs work in a factory.

[1392] "Noise removal" is the process of removing unnecessary information and errors from collected data.

[1393] "Normalization" is the process of converting collected data into a unified scale or format.

[1394] The present invention relates to a system for comprehensively and efficiently optimizing the environment and working conditions in homes and factories. This system uses multiple data collection and analysis methods to automatically control equipment while taking into account the individual health and emotional states of users.

[1395] 1. System Configuration

[1396] The system consists of the following main components:

[1397] 1. Data collection methods:

[1398] A means of acquiring operating status and setting information from various electrical devices and industrial machines in homes and factories.

[1399] A means of obtaining water and gas usage figures.

[1400] A means of obtaining health data (e.g., heart rate, body temperature, sleep patterns) from wearable devices (e.g., smartwatches).

[1401] A means of obtaining location and activity data from mobile devices (e.g., smartphones).

[1402] A means of obtaining temperature and weather forecasts via the Internet.

[1403] A means of recognizing an individual's emotional state using an emotion engine.

[1404] 2. Analysis method:

[1405] A means of denoising and normalising the data.

[1406] A method of using generative AI models to run optimization algorithms based on collected data, predicting operating patterns of electrical equipment and industrial machinery, and making optimal adjustments.

[1407] 3. Means of notification:

[1408] A means for notifying the user or administrator of the optimization results obtained by the analysis means.

[1409] 4. Automatic control means:

[1410] A means of automatically controlling electrical equipment and industrial machinery based on user or administrator approval.

[1411] 2. Hardware and Software Used

[1412] Hardware:

[1413] Smartwatches and smartphones for data collection.

[1414] Various sensors (temperature, humidity, electricity meter, water meter, etc.).

[1415] Industrial machinery in a factory.

[1416] software:

[1417] Generative AI models that include data analysis and optimization algorithms.

[1418] Emotion recognition algorithm using emotion engine.

[1419] Notification systems (e.g. smartphone apps).

[1420] Software that uses an Internet API to obtain temperature and weather forecast data.

[1421] 3. Data processing and calculation

[1422] The server preprocesses the data collected from various devices, removing noise and normalizing it. The preprocessed data is then input into a generative AI model, which calculates optimal operating patterns based on the user's past behavioral patterns, current environmental information, health status, and emotional state.

[1423] Here are some specific examples of data processing:

[1424] Temperature control within the home: The server collects indoor temperature data from temperature sensors, compares it with weather forecast data, and makes suggestions to optimize the air conditioner temperature setting.

[1425] Machine operation patterns within the factory: The server analyzes the operation data of industrial machines and, in conjunction with the health data of workers, suggests optimal operating times and settings for the equipment.

[1426] 4. Examples of prompts

[1427] The following prompt demonstrates how this system works:

[1428] You are the developer of a system that integrates worker health and environmental data in a factory to make optimization suggestions.

[1429] If a worker's heart rate data exceeds 80, it is determined that the worker is stressed.

[1430] Generate suggestions to adjust machine settings based on weather data.

[1431] The above is an embodiment of the invention. The present invention individually optimizes the environment and working conditions in a house or factory, making it possible to improve energy efficiency, work efficiency, and safety.

[1432] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1433] Step 1:

[1434] The server acquires operating status and setting information from various electrical devices and industrial machines in homes and factories.

[1435] Input: Operational data and setting information from each device

[1436] Data Processing: Collecting data and converting it into a centralized format.

[1437] Specific operation: The server periodically calls the API of each device to obtain its operating status and settings, such as the temperature setting and operation mode of an air conditioner, or the operating time and load of industrial machinery.

[1438] Step 2:

[1439] The server obtains usage data from water and gas meters.

[1440] Input: Consumption data from water and gas meters

[1441] Data processing: Data is aggregated over time to analyze usage patterns.

[1442] Specific operation: The server collects consumption data from water meters and gas meters and compiles the data on a daily or monthly basis.

[1443] Step 3:

[1444] The server acquires the personal health data from the wearable device.

[1445] Input: Heart rate, body temperature, sleep data from smartwatch etc.

[1446] Data processing: Organize the data by individual and store it as time-series data.

[1447] Specific operation: The server periodically collects data from the wearable device via an API and stores the heart rate, body temperature, and sleep data for each individual.

[1448] Step 4:

[1449] The server obtains location information and activity data from the mobile device.

[1450] Input: Location information and activity data from your smartphone (number of steps, distance traveled, etc.)

[1451] Data processing: Plot location information on a map and organize activity data along a timeline.

[1452] Specific operation: The server collects GPS data and activity records from the smartphone and analyzes the movement route and activity level.

[1453] Step 5:

[1454] The server retrieves the temperature and weather forecast via the Internet.

[1455] Input: Real-time weather data from a weather data provider

[1456] Data processing: Organize data as local area information and extract predictive data.

[1457] Specific operation: The server calls the weather data API to obtain and store the current temperature and future weather forecast.

[1458] Step 6:

[1459] The server uses an emotion engine to recognize the emotional state of the individual.

[1460] Input: Heart rate and audio data from wearable devices

[1461] Data processing: Analyze the data with the emotion engine and evaluate the emotional state.

[1462] Specific operation: The server inputs heart rate and voice data into the emotion engine to determine stress levels and emotional states.

[1463] Step 7:

[1464] The server uses an optimization algorithm based on the acquired data to predict the operating patterns of electrical equipment and operates an analysis means including a generation AI that makes optimal adjustments.

[1465] Input: Operating status data, health data, activity data, weather data, emotion data

[1466] Data calculation: Using a generative AI model, optimal operating patterns are calculated.

[1467] How it works: The server inputs various data into the generative AI and calculates the optimal settings to maximize energy efficiency and comfort.

[1468] Step 8:

[1469] The server notifies the user of the optimization results obtained by the analysis means.

[1470] Input: Optimized operation patterns and adjustment proposals

[1471] Output: Notification to the user's smartphone and the administrator's device

[1472] Specific operation: The server notifies the user or administrator of the generated optimization proposal on their device. Example: "The current outside temperature is low, so we recommend lowering the air conditioner setting by 1 degree."

[1473] Step 9:

[1474] Based on the user's approval, the server automatically controls each electrical device.

[1475] Input: User or administrator approval

[1476] Output: Changing the settings of electrical equipment and industrial machines

[1477] Specific operation: After obtaining the user's approval, the server automatically sends instructions to change the settings to each device and performs the actual operation.

[1478] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1479] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1480] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1481] [Fourth embodiment]

[1482] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1483] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1484] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1485] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1486] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1487] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1488] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1489] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1490] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1491] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1492] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1493] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1494] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1495] The present invention is a system for optimizing the home environment efficiently and comfortably, integrating various electrical appliances, devices, and external information to perform optimization. The system includes the following steps and elements:

[1496] Data collection

[1497] Data collection from devices:

[1498] The server continuously collects operating status and setting information from each electrical device in the home (e.g., air conditioner, water heater, air purifier, lighting). This allows the server to grasp the on / off status, temperature setting, operation mode, etc. of each device in real time. It also collects usage data from water and gas meters.

[1499] Data collection from wearable devices:

[1500] The server acquires the user's health data from the wearable device (e.g., smart watch), specifically, heart rate, sleep time, exercise amount, etc., and grasps the user's health condition.

[1501] Mobile data collection:

[1502] The server obtains location information and activity data from the mobile device (e.g., smartphone), which determines whether the user is at home or out, and also tracks the amount of activity, such as the number of steps taken and the distance traveled.

[1503] Data collection from the Internet:

[1504] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[1505] Data Analysis and Optimization

[1506] Data preprocessing and analysis:

[1507] The server inputs the collected data into the AI ​​generator for specific analysis. After removing noise and normalizing the data, the AI ​​calculates the optimal operating pattern for electrical equipment, taking into account the user's past behavioral patterns, health status, and external environment.

[1508] Use of optimization algorithms:

[1509] The server uses generative AI to run algorithms that optimize the use of electrical equipment and resources, automatically determining things like air conditioner temperature settings and water heater operation schedules, enabling efficient energy use.

[1510] Suggestions and User Notifications

[1511] Optimization results suggestion:

[1512] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification may be displayed on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[1513] Automatic Control

[1514] User consent and control:

[1515] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it, for example, to change the temperature setting of an air conditioner, and then monitors and confirms the results.

[1516] Specific examples

[1517] 1. Morning scenario:

[1518] When the user wakes up in the morning, the server retrieves the user's sleep time and heart rate data from the smartwatch and, based on this, suggests optimizing the air conditioner temperature setting to maintain a comfortable room temperature. If the user approves, the air conditioner temperature setting will be automatically adjusted.

[1519] 2. Shower scenario:

[1520] The server detects when a user is about to take a shower from their smartphone and checks the current temperature of the water heater. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees, and if the user agrees, the set temperature is automatically adjusted.

[1521] This system enables efficient energy use and provides users with a comfortable living environment. Repeating these steps will help build a sustainable living environment.

[1522] The processing flow will be explained below.

[1523] Step 1:

[1524] The server acquires operating status and setting information from each electrical device in the home. For example, it acquires the current temperature setting, operating mode, and operating status from the air conditioner. Similarly, it acquires the current temperature setting and operating status from the water heater.

[1525] Step 2:

[1526] The server acquires and records usage data from the water meter and gas meter, for example, the amount of water and gas used every hour.

[1527] Step 3:

[1528] The server acquires the user's health data from the wearable device, specifically information such as heart rate, sleep time, and exercise amount, and uses this information to understand the user's current health condition.

[1529] Step 4:

[1530] The server acquires location information and activity data from the mobile device, confirms whether the user is at home or out, and also acquires activity data such as the number of steps taken and distance traveled.

[1531] Step 5:

[1532] The server receives weather forecasts and temperature information via the Internet, providing information such as the maximum and minimum temperatures, probability of precipitation, and humidity for the day.

[1533] Step 6:

[1534] The server denoises and normalizes the collected data, correcting outliers and missing values, and formatting the data into a form that is easy to analyze.

[1535] Step 7:

[1536] The server inputs the formatted data into the AI ​​generator for analysis. Specifically, it predicts the optimal operating pattern for electrical equipment by taking into account the user's past behavioral patterns, health status, and current environmental information.

[1537] Step 8:

[1538] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[1539] Step 9:

[1540] The server compiles all the analysis results and generates a notification that suggests optimization to the user, such as "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[1541] Step 10:

[1542] The device sends a notification to the user's mobile device and displays the optimization suggestion, and the user can check the notification and choose to accept or reject the suggestion.

[1543] Step 11:

[1544] If the user selects approval, the server sends an instruction to the electrical appliance to automatically control it, for example, to an air conditioner to change the temperature setting.

[1545] Step 12:

[1546] The server checks whether electrical equipment is working properly, for example, checking whether the air conditioner has started operating at the specified temperature setting.

[1547] Step 13:

[1548] The server continuously monitors the operating status and energy consumption of each electrical device. If an abnormality is detected, it notifies the user and suggests further optimization if necessary.

[1549] By repeating this series of steps, the home's environment and energy consumption can be dynamically optimized.

[1550] Example 1

[1551] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1552] The efficient operation of various electrical appliances and devices in homes and the maintenance of a comfortable and healthy living environment for individuals are required. The present invention solves the problem of improving energy efficiency and ensuring user convenience by providing a system that manages these in an integrated manner and proposes and executes optimal operation patterns.

[1553] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1554] In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile device; means for acquiring temperature and weather forecasts via the Internet; analysis means including a generation AI that uses an optimization algorithm to predict operation patterns of the electrical appliances based on the acquired data and makes optimal adjustments; means for notifying the user of the optimization results obtained by the analysis means; means for automatically controlling each electrical appliance based on the user's approval; means for denoising and normalizing the collected data; means for integrating the operation status of the target appliances with external environmental data to calculate optimal operation patterns of the electrical appliances and generate proposals; and means for notifying the user of the generated proposals to the user's mobile device. This makes it possible to optimize the user's living environment and improve energy efficiency.

[1555] - "Various electrical appliances" refers to electrical machinery and equipment used in homes, such as air conditioners, water heaters, air purifiers, and lighting.

[1556] "Operating status" refers to information about whether an electrical device is currently operating or in what mode it is operating.

[1557] "Setting information" refers to information relating to operating conditions and parameters designated by the user for the electrical device, such as temperature settings and operation modes.

[1558] "Usage data" is information about the consumption of resources such as water and gas.

[1559] A "wearable device" is an electronic device that is designed to be worn by the user, and includes smartwatches and the like.

[1560] "Health data" is information that indicates the user's health condition, such as heart rate, sleep time, and amount of exercise.

[1561] A "mobile device" is a portable communication device such as a smartphone that is capable of collecting location information and activity data.

[1562] "Location information" is information about the current location obtained by the GPS function of the mobile terminal.

[1563] "Activity data" is information indicating the amount of physical activity of the user, such as the number of steps taken and the distance traveled.

[1564] "Temperature" refers to the temperature in the atmosphere, and is information indicating the temperature conditions of the external environment.

[1565] "Weather forecast" is information about upcoming weather changes and current weather.

[1566] An "optimization algorithm" is a mathematical method for calculating efficient operating patterns for electrical equipment based on collected data.

[1567] "Generative AI" is a type of artificial intelligence that uses machine learning and deep learning techniques to analyze data and generate optimal operating patterns.

[1568] "Analysis means" refers to the techniques and devices used to perform analysis based on collected data.

[1569] The "optimization result" is information that indicates an efficient method of using and operation pattern of the electrical equipment, derived by the analysis means.

[1570] "Notification means" refers to a means for informing the user of information, and includes notifications to smartphones, etc.

[1571] "Automatic control" is a mechanism for automatically adjusting the operation of each electrical device after obtaining user approval.

[1572] "Noise removal" is the process of removing unnecessary or erroneous data in data analysis.

[1573] "Normalization" is the process of converting the range of data to a certain scale.

[1574] The "suggestion content" is information about the settings and operation patterns of electrical appliances that are recommended to the user based on the optimization algorithm.

[1575] This invention is a system for optimizing the home environment efficiently and comfortably. The system integrates various electrical appliances, devices, and external information to perform optimization.

[1576] Data collection

[1577] Collecting data from devices

[1578] The server collects operating status and setting information from each electrical device in the home, such as the air conditioner, water heater, air purifier, and lighting. Specifically, it obtains data such as the air conditioner's on / off status, temperature setting, and operation mode. It also obtains usage data from water and gas meters.

[1579] Data collection from wearable devices

[1580] The server collects user health data from wearable devices such as smartwatches, including heart rate, sleep duration, and exercise volume.

[1581] Data collection from mobile devices

[1582] The server collects location information and activity data from mobile devices such as smartphones, which allows it to determine whether the user is at home or out, as well as the amount of activity such as the number of steps taken and distance traveled.

[1583] Data collection from the internet

[1584] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[1585] Data Analysis and Optimization

[1586] Data Preprocessing

[1587] The server performs noise removal and normalization on the various collected data. Specifically, it complements missing values ​​in the data and removes outliers. It also performs normalization to make the data range consistent. This is done using a data preprocessing library (e.g., pandas, NumPy).

[1588] Using generative AI models

[1589] The server uses a generative AI model to calculate the optimal operating pattern for each electrical device. Specifically, normalized data is input into the generative AI model (e.g., TensorFlow, PyTorch) to predict the optimal energy consumption pattern.

[1590] Suggestions and User Notifications

[1591] Optimization results suggestions

[1592] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification might be displayed on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree." This is done using a notification service (e.g., Firebase Cloud Messaging).

[1593] Automatic Control

[1594] User Authorization and Control

[1595] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it. For example, it sends an instruction to change the temperature setting of an air conditioner and then monitors and confirms the results. This is done using the smart home control API.

[1596] Specific examples

[1597] 1. Morning Scenario

[1598] The server receives the user's sleep data from the smartwatch and analyzes it together with the outside temperature data. As a result, it sends a notification to the smartphone suggesting that the current room temperature be raised by 1 degree. If the user approves, the server sends a command to change the set temperature to the air conditioner.

[1599] 2. Shower scenario

[1600] The server detects from the smartphone sensor that the user is about to take a shower. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees and notifies the smartphone. If the user agrees, the server sends a command to change the set temperature to the water heater.

[1601] Prompt Sentence Examples

[1602] Example prompt 1: Morning optimization suggestions

[1603] "Good morning. According to your recent sleep data, it appears that you have not been spending much time in deep sleep. Raising the current room temperature by 1 degree will help you wake up more comfortably. Would you like to change the air conditioner temperature setting?"

[1604] Example prompt 2: Shower optimization suggestions

[1605] "The outside temperature is dropping. We suggest you increase the water heater temperature by 2 degrees to make showering more comfortable. Would you like to do this?"

[1606] This makes it possible to use energy efficiently and provide users with a comfortable living environment.

[1607] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1608] Step 1:

[1609] Collecting data from devices

[1610] The server collects operating status and setting information from various electrical devices in the home. Specifically, it obtains information such as the air conditioner's on / off status, temperature setting, and operation mode. The server sends requests at regular intervals and receives current status information from the electrical devices.

[1611] Input: Request responses from various electrical devices

[1612] Output: Operational data of each device (on / off status, temperature setting, operation mode)

[1613] Step 2:

[1614] Data collection from wearable devices

[1615] The server collects user health data from wearable devices such as smartwatches, and periodically uploads the data from the wearable devices to the server.

[1616] Input: Health data from a smartwatch

[1617] Output: User's health data (heart rate, sleep time, exercise amount)

[1618] Step 3:

[1619] Data collection from mobile devices

[1620] The server collects location information and activity data from mobile devices such as smartphones, and determines whether the user is at home or out. The server periodically transmits the location information and activity data to the server using the mobile device's GPS and activity tracking functions.

[1621] Input: Location and activity data from your smartphone

[1622] Output: User location and activity data

[1623] Step 4:

[1624] Data collection from the internet

[1625] The server retrieves weather forecasts and current temperatures via the Internet, sends a request to the weather API, and stores the retrieved data internally.

[1626] Input: Request response from the weather API

[1627] Output: Weather forecast data and current temperature data

[1628] Step 5:

[1629] Data preprocessing and analysis

[1630] The server performs noise removal and normalization on the various collected data. Specifically, it complements missing values ​​in the collected data and removes outliers. It also performs normalization to make the data range consistent. This is done using a data preprocessing library (e.g., pandas, NumPy).

[1631] Input: Various collected data (electrical equipment operation data, health data, location information, weather data)

[1632] Output: Normalized data

[1633] Step 6:

[1634] Using generative AI models

[1635] The server uses a generative AI model to calculate the optimal operating pattern for each electrical device. The normalized data is input into the generative AI model (e.g., TensorFlow, PyTorch) to predict the optimal energy consumption pattern.

[1636] Input: Normalized data

[1637] Output: Optimized operating pattern

[1638] Step 7:

[1639] Optimization results suggestions

[1640] The server then makes optimization suggestions to the user based on the analysis results. For example, a notification such as "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree" is displayed on the user's smartphone. This is achieved using a notification service (e.g., Firebase Cloud Messaging).

[1641] Input: Optimized operating pattern

[1642] Output: Proposal notification to user

[1643] Step 8:

[1644] User Authorization and Control

[1645] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it. For example, it sends an instruction to change the temperature setting of an air conditioner and then monitors and confirms the results. This is done using the smart home control API.

[1646] Input: User approval

[1647] Output: Control instructions to electrical devices

[1648] (Application example 1)

[1649] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1650] This invention relates to a system that comprehensively monitors and controls the operating status and environmental data of various equipment and machines in a factory, improving energy efficiency and optimizing productivity. Conventional systems manage each piece of equipment individually, without proper data integration or analysis, which often results in a lack of overall efficiency. Furthermore, insufficient coordination between each piece of equipment makes it difficult to optimize overall energy consumption. This leads to problems such as increased energy costs and reduced productivity.

[1651] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1652] In this invention, the server includes means for acquiring operation status and setting information from various electrical appliances in the home, means for acquiring water and gas usage, means for acquiring personal health data from a wearable device, means for acquiring location information and activity data from a mobile terminal, means for acquiring temperature and weather forecasts via the Internet, means for acquiring operation status and environmental data from various pieces of equipment in the factory, analysis means including a generation AI that uses an optimization algorithm based on the acquired data to predict the operation pattern of the factory equipment and make optimal adjustments, means for notifying workers of the optimization results obtained by the analysis means, and means for automatically controlling each piece of equipment based on the worker's approval, thereby enabling collaboration between equipment in the factory and optimization of energy consumption.

[1653] "Various electrical appliances in the home" refers to household electrical appliances such as air conditioners, water heaters, air purifiers, and lighting.

[1654] "Operating status" refers to information that indicates the status of each device, such as its on / off status, the currently set operating mode, and temperature setting.

[1655] "Setting information" refers to parameters and values ​​that are set in advance to control the operation of an electrical device.

[1656] "Water and gas usage" refers to data that indicates the amount of tap water and gas consumed within a home.

[1657] "Wearable devices" refers to electronic devices that can be worn by a user and that can collect health and activity data. Examples include smartwatches and fitness trackers.

[1658] "Health data" refers to data that includes information about an individual's health status, such as heart rate, sleep duration, and amount of exercise.

[1659] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[1660] "Location Information" means geographic location data obtained from a mobile or other device.

[1661] "Activity data" refers to data that includes information about the user's daily activities, such as the number of steps taken, distance traveled, and time spent at a destination.

[1662] "Temperature and weather forecast via the Internet" refers to current temperature and future weather forecast information obtained using an Internet connection.

[1663] "Various facilities within the factory" includes production facilities and environmental control devices used within the factory, such as robotic arms, conveyors, and HVAC systems.

[1664] "Environmental data" refers to data that includes information about the surrounding environment within a factory or home, such as temperature, humidity, and illuminance.

[1665] "Optimization algorithm" refers to an algorithm that calculates the best operation to achieve a specific goal based on collected data.

[1666] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and suggest optimal ways to operate devices and systems.

[1667] "Analysis means" refers to a device or process for analyzing collected data and outputting optimization results.

[1668] "Worker" refers to a person who performs work in a factory or other facility.

[1669] "Automatic control means" refers to a system that includes a control device or program for automatically changing the settings or operation of equipment based on the optimized results.

[1670] This invention is a system for efficiently and optimally managing and controlling various equipment and environments within a factory, and is implemented through the procedures of data collection, analysis, optimization, notification, and control from various equipment. This system includes the following procedures and elements.

[1671] Data collection

[1672] The server continuously collects operational status and setting information from various pieces of equipment in the factory (robot arms, conveyors, HVAC systems, etc.). This allows information such as the operating status, set temperature, and operating mode of each piece of equipment to be sent to the server in real time. Environmental data such as temperature, humidity, and illuminance are also collected via sensors.

[1673] Data Analysis and Optimization

[1674] The server uses a generative AI model to analyze the various collected data, removes noise and normalizes the data, and then calculates the optimal equipment operating pattern taking into account past operating patterns and environmental conditions.

[1675] Proposals and worker notifications

[1676] Based on the analysis results, the server will suggest optimization measures to the worker. For example, a notification such as "We recommend lowering the current room temperature by 2 degrees" will be displayed on the worker's device.

[1677] Automatic Control

[1678] Once the worker approves the optimization proposal, the server sends automatic control instructions to each piece of equipment, such as adjusting the robot arm's operating schedule or changing the temperature setting of the HVAC system.

[1679] Specific examples

[1680] 1. Production line optimization: The server collects robot arm movement data and proposes optimal movement timing and patterns. Once approved by the worker, the robot arm's movement pattern is automatically changed.

[1681] 2. Managing the factory environment: The server collects data from temperature and humidity sensors and makes recommendations to optimize the temperature and humidity settings of the HVAC system. Once the worker approves the recommendations, the HVAC system settings are automatically adjusted.

[1682] Hardware and software used

[1683] Hardware: Various sensors in the factory (temperature, humidity, light, etc.), robotic arms, HVAC systems, servers, and worker terminals.

[1684] Software: Data collection, analysis, notification and control program using Python. Interface with devices using REST API.

[1685] Prompt Sentence Examples

[1686] As an example, data is collected from a temperature sensor, and the prompt text sent by the server to the generative AI model when the temperature is 25 degrees and the humidity is 60% is shown below:

[1687] "Here is the environmental data for the factory. Temperature: 25°C, humidity: 60%. Please suggest the optimal operating pattern for each piece of equipment."

[1688] This system enables coordination between equipment within a factory and optimizes energy consumption, resulting in improved efficiency and cost reduction.

[1689] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1690] Step 1:

[1691] Starting data collection and acquiring input

[1692] The server collects real-time operational status and environmental data from various sensors and equipment in the factory. Specifically, it collects current temperature data from temperature sensors and current humidity data from humidity sensors. It also collects operational status and setting information from robotic arms and HVAC systems. This allows data on temperature, humidity, and equipment operational status to be collected and input to the server.

[1693] Step 2:

[1694] Data preprocessing and denoising

[1695] The server performs preprocessing on the collected data. In this step, it removes noise and normalizes the data. For example, if data obtained from a temperature sensor contains outliers, it removes them. The input is the collected environmental data and equipment data, and the output is the data that has been denoised and normalized.

[1696] Step 3:

[1697] Data input and analysis for generative AI models

[1698] The server inputs the preprocessed data into a generative AI model for analysis. The generative AI model used here predicts optimal equipment operating patterns based on past data and current conditions. For example, when temperature and humidity data is input, the optimal settings for an HVAC system are calculated based on that data. The input is noise-removed data, and the output is optimized equipment settings and operating patterns.

[1699] Step 4:

[1700] Notifying the workers of the analysis results

[1701] The server notifies the worker of optimization suggestions based on the analysis results. This notification is displayed on the worker's device. For example, a message such as "We recommend lowering the current room temperature by 2 degrees" is displayed. The input is the analysis result from the generative AI model, and the output is a notification message sent to the worker's device.

[1702] Step 5:

[1703] Operator approval and start of automatic control

[1704] When an operator approves an optimization proposal, the server sends automatic control instructions to each piece of equipment. For example, these instructions include changing the temperature setting of an HVAC system or adjusting the operation schedule of a robot arm. The input is the operator's approval, and the output is a control instruction for each piece of equipment.

[1705] Step 6:

[1706] Retrieval Monitoring and Feedback

[1707] After issuing the control command, the server monitors the equipment and environmental data again and re-optimizes as necessary. This allows for continuous optimization of equipment efficiency and energy consumption. The input is the latest operating status and environmental data, and the output is the re-optimized settings.

[1708] The above steps will enable coordination between equipment within the factory and optimize energy consumption, improving efficiency and reducing costs.

[1709] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1710] The present invention is a system for optimizing the home environment efficiently and comfortably, integrating various electrical appliances, devices, and external information to perform optimization. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, optimization can be performed that is adapted to the user's emotional state. This system includes the following procedures and elements.

[1711] Data collection

[1712] Data collection from devices:

[1713] The server collects operating status and setting information from each electrical device in the home (e.g., air conditioner, water heater, air purifier, lighting). This allows the server to grasp the on / off status, temperature setting, operation mode, etc. of each device in real time. It also collects usage data from water and gas meters.

[1714] Data collection from wearable devices:

[1715] The server acquires the user's health data from the wearable device (e.g., smart watch), specifically, heart rate, sleep time, exercise amount, etc., and grasps the user's current health condition.

[1716] Mobile data collection:

[1717] The server obtains location information and activity data from the mobile device (e.g., smartphone), which determines whether the user is at home or out, and also tracks the amount of activity, such as the number of steps taken and distance traveled.

[1718] Data collection from the Internet:

[1719] The server receives weather forecasts and current temperatures via the Internet, which allows it to predict changes in the external environment and obtain data to maintain an optimal indoor environment.

[1720] Emotion recognition by emotion engine

[1721] Emotion data collection:

[1722] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and recognizes the user's emotional state based on this data.

[1723] Emotional Data Analysis:

[1724] The server uses an emotion engine to analyze the collected physiological and audio data and evaluate the user's stress level and emotional state. For example, if the user's heart rate is high, the server determines that the user is feeling stressed.

[1725] Data Analysis and Optimization

[1726] Data preprocessing and analysis:

[1727] The server inputs the collected data into the AI ​​generator for specific analysis. After removing noise and normalizing the data, the AI ​​calculates the optimal operating pattern for the electrical equipment, taking into account the user's past behavioral patterns, health status, current environmental information, and emotional data.

[1728] Use of optimization algorithms:

[1729] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[1730] Suggestions and User Notifications

[1731] Optimization results suggestion:

[1732] The server then makes optimization suggestions to the user based on the analysis results. For example, it may display a notification on the user's smartphone saying, "The current outside temperature is low, so we recommend lowering the air conditioner temperature setting by 1 degree."

[1733] Automatic Control

[1734] User consent and control:

[1735] If the user approves the proposal, the server sends instructions to each electrical device to automatically control it, for example, to change the temperature setting of an air conditioner, and then monitors and confirms the results.

[1736] Specific examples

[1737] 1. Morning scenario:

[1738] When the user wakes up in the morning, the server retrieves the user's sleep duration and heart rate data from the smartwatch and, based on this, suggests optimizing the air conditioner temperature setting to maintain a comfortable room temperature. If the user's heart rate is high, it also suggests playing specific music to help with stress. If the user approves, the air conditioner's temperature setting will be automatically adjusted and music will be played.

[1739] 2. Shower scenario:

[1740] The server detects when a user is about to take a shower from their smartphone and checks the current temperature of the water heater. If the outside temperature is low, it suggests raising the water heater temperature by a few degrees. It also suggests playing ambient music to help the user relax. If the user approves, the water heater temperature is automatically adjusted and ambient music is played.

[1741] This system enables efficient energy use that takes into account the user's emotional state, providing a more comfortable living environment. By repeating this series of steps, we can help build a sustainable and emotionally sensitive living environment.

[1742] The processing flow will be explained below.

[1743] Step 1:

[1744] The server obtains the operating status and setting information from each electrical device in the home. Specifically, it obtains the current temperature setting, operating mode, and operating status from the air conditioner. Similarly, it obtains the current temperature setting and operating status from the water heater.

[1745] Step 2:

[1746] The server acquires and records usage data from the water meter and gas meter, for example, by periodically acquiring and recording the amount of water and gas usage every hour.

[1747] Step 3:

[1748] The server acquires the user's health data from the wearable device, specifically information such as heart rate, sleep time, and exercise amount, and uses this information to understand the user's current health condition.

[1749] Step 4:

[1750] The server obtains location information and activity data from the mobile device, confirming whether the user is at home or out, and also obtains activity data such as the number of steps taken and distance traveled.

[1751] Step 5:

[1752] The server receives weather forecasts and temperature information via the Internet, providing information such as the maximum and minimum temperatures, probability of precipitation, and humidity for the day.

[1753] Step 6:

[1754] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and recognizes the user's emotional state based on this data.

[1755] Step 7:

[1756] The server analyzes the collected physiological and voice data using an emotion engine to assess the user's stress level and emotional state. For example, if the user's heart rate is high, the server determines that the user is feeling stressed.

[1757] Step 8:

[1758] The server combines the obtained emotional state data with other collected data (health data, location information, weather information, etc.) and inputs it into the generation AI. After removing noise and normalizing the data, the optimal operating pattern is calculated.

[1759] Step 9:

[1760] The server uses generative AI to run optimization algorithms and determine adjustment parameters to optimize the use of each electrical device and resource, such as calculating the optimal temperature and operating time for an air conditioner or the temperature setting for a water heater.

[1761] Step 10:

[1762] Based on the analysis results, the server generates notification content suggesting optimization to the user. For example, it generates a suggestion such as, "Based on the current outside temperature and your health data, we recommend lowering the air conditioner temperature setting by 1 degree."

[1763] Step 11:

[1764] The device sends a notification to the user's mobile device and displays the optimization suggestion, and the user can check the notification and choose to accept or reject the suggestion.

[1765] Step 12:

[1766] If the user approves the proposal, the server sends an instruction to the electrical appliance to automatically control it, for example, to change the temperature setting of the air conditioner.

[1767] Step 13:

[1768] The server checks whether electrical equipment is working properly, for example, checking whether the air conditioner has started operating at the specified temperature setting.

[1769] Step 14:

[1770] The server continuously monitors the operating status and energy consumption of each electrical device. If an abnormality is detected, it notifies the user and suggests further optimization if necessary.

[1771] By repeating this series of steps, the home environment and energy consumption can be dynamically optimized. Furthermore, it is possible to make suggestions and control that take into account the user's emotional state, providing a more comfortable and healthy living environment.

[1772] Example 2

[1773] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1774] Conventional home electrical appliance and resource management systems typically control the operating status and settings of individual devices independently, limiting their ability to provide an optimal environment that takes into account the user's health and emotional state. It is also difficult to effectively integrate and adaptively manage the diverse data obtained from multiple devices. Therefore, an integrated system is needed to maintain an efficient and comfortable home environment.

[1775] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile terminal; means for acquiring temperature and weather forecasts via the Internet; means for recognizing an emotional state based on the acquired data, physiological data from the wearable device, and voice data from the mobile terminal; analysis means including a generation AI that predicts the operation pattern of the electrical appliances using an optimization algorithm based on the acquired data and the recognized emotional state and performs optimal adjustments; means for notifying the user of the optimization results obtained by the analysis means; and means for automatically controlling each electrical appliance based on the user's approval. This enables integrated and efficient optimization of the home environment, taking into account the user's health and emotional state.

[1776] "Various electrical appliances in homes" refers to all electrical and electronic devices used in homes, such as air conditioners, water heaters, air purifiers, and lighting.

[1777] "Operating status and setting information" refers to all information related to the operation of each electrical device, such as its on / off status, current set temperature, and operating mode.

[1778] "Water and gas usage" refers to the amount of water and gas consumed within a home.

[1779] "Wearable devices" refers to devices such as smartwatches and fitness trackers that can collect health data when worn by the user.

[1780] "Personal health data" refers to physiological and health information about a user, such as their heart rate, sleep duration, and activity level.

[1781] "Mobile device" refers to a mobile device such as a smartphone or tablet.

[1782] "Location information and activity data" refers to information such as current location, number of steps, and distance traveled provided by the mobile device via GPS.

[1783] "Means of obtaining temperature and weather forecasts via the Internet" refers to means of connecting to the Internet and obtaining local temperature and weather forecasts from web services or APIs that provide weather information.

[1784] "Physiological data" refers to data relating to the physiological state of the body, such as the user's heart rate and body temperature.

[1785] "Voice data" refers to data relating to a user's vocalizations and tone of voice collected through the microphone of a mobile device.

[1786] "Means for recognizing emotional state" refers to means for analyzing collected physiological data and voice data to recognize the stress level and emotional state of the user.

[1787] An "optimization algorithm" refers to a calculation procedure or method for analyzing a wide variety of data and optimizing the operating patterns and settings of electrical equipment in a home.

[1788] "Generative AI" refers to algorithms that use artificial intelligence technology to analyze data and generate optimal plans and proposals.

[1789] "Analysis means" refers to the equipment and software used to process and analyze collected data.

[1790] "Means for notifying the user of the optimization results" refers to means for displaying suggestions and instructions generated based on the analysis results on the user's terminal.

[1791] "Automatic control means" refers to a means for automatically changing the settings of an electrical device based on user approval.

[1792] The present invention is a system that integrates various electrical appliances and devices in a home with external information to efficiently and comfortably optimize the home environment. This system includes various elements that recognize the user's emotional state and adjust the environment optimally based on that state.

[1793] Data collection

[1794] The server obtains operating status and setting information from various electrical devices in the home. For example, the server can monitor the on / off status, temperature settings, and operation mode of devices such as air conditioners, water heaters, air purifiers, and lighting in real time. This information is obtained through sensors and communication modules built into each device.

[1795] The server also obtains usage data from water and gas meters to understand water and gas consumption, allowing for monitoring of overall resource usage efficiency within the home.

[1796] In addition, the server acquires user health data from wearable devices (e.g., smart watches), allowing the server to obtain information such as heart rate, sleep time, and exercise volume, enabling real-time monitoring of the user's health status.

[1797] The server can also obtain location information and activity data from mobile devices (e.g., smartphones), which can determine whether the user is at home or out and track activity such as the number of steps taken and distance traveled.

[1798] The server can also obtain temperature and weather forecasts via the Internet, thereby predicting changes in the external environment and collecting data to maintain an optimal indoor environment.

[1799] Emotion recognition by emotion engine

[1800] The server collects physiological data such as heart rate from the wearable device and voice data from the mobile device, and uses this data to recognize the user's emotional state. For example, a high heart rate can be determined to indicate a high likelihood of stress. Furthermore, the server can analyze the tone and tempo of the voice from the voice data to understand the user's emotional state in more detail.

[1801] Data Analysis and Optimization

[1802] The server inputs the collected data into a generative AI model for specific analysis. After removing noise and normalizing the data, it calculates the optimal operating pattern for electrical equipment by taking into account the user's past behavioral patterns, health status, current environmental information, and emotional data.

[1803] For example, the server uses the generative AI model to calculate the optimal temperature setting and operating time for an air conditioner, the temperature setting for a water heater, etc., thereby improving energy efficiency while maintaining user comfort.

[1804] Suggestions and User Notifications

[1805] Based on the analysis results, the server makes optimization suggestions to the user. For example, a notification might be displayed on the user's smartphone stating, "The current outside temperature is low, so we recommend lowering the air conditioner's set temperature by 1 degree." If the user accepts the suggestion, the server sends automatic control instructions to each electrical device and changes the air conditioner's set temperature.

[1806] Automatic Control and Examples

[1807] The server receives user approval and sends instructions for automatic control to each electrical device. For example, if the user approves a suggestion to lower the air conditioner's temperature setting by 1 degree, the server automatically adjusts the temperature setting to 22 degrees and then monitors and confirms the result again.

[1808] Below are some example prompts to input to a generative AI model:

[1809] "For this home optimization system, please suggest the optimal settings using the following data: current status of the air conditioner, water heater temperature, user's heart rate and sleep data, and outside temperature. Please suggest the optimal air conditioner setting temperature and water heater temperature setting."

[1810] This system enables efficient energy use that takes into account the user's health and emotional state, creating a comfortable living environment within the home. Furthermore, by repeating this series of steps, the creation of a sustainable and emotionally sensitive living environment is supported.

[1811] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1812] Step 1:

[1813] Input: Operation status and setting information of various electrical devices

[1814] Specific operation: The server obtains operating status and setting information (on / off status, temperature setting, operation mode, etc.) from various electrical devices in the home.

[1815] Data processing and calculation: The acquired data is collated to obtain an overall picture of the current home environment and recorded in a database.

[1816] Output: A list of successfully retrieved health and configuration information

[1817] Step 2:

[1818] Input: Health data from wearable devices

[1819] Specific operation: The server collects data such as the user's heart rate, sleep time, and exercise volume from the wearable device.

[1820] Data processing and calculation: Analyze the acquired data and normalize the user's health status and vital signs.

[1821] Output: Successfully acquired and normalized health data

[1822] Step 3:

[1823] Input: Location and activity data from your smartphone

[1824] Specific operation: The server obtains location information (GPS data) and activity data (number of steps, distance traveled, etc.) from the mobile device.

[1825] Data processing and calculation: Based on the acquired location information, the system determines whether the user is at home or out and compiles the amount of activity.

[1826] Output: Successfully acquired location and activity data, and the result of determining the user's current location.

[1827] Step 4:

[1828] Input: Temperature and weather forecast data from the internet

[1829] What it does: The server retrieves temperature and weather forecast data via the Internet.

[1830] Data processing and calculation: Analyze acquired weather forecast data and predict future climate conditions.

[1831] Output: Successfully retrieved temperature and weather forecast data, predicted weather conditions

[1832] Step 5:

[1833] Input: Health data, voice data

[1834] Specific operation: The server collects physiological data such as heart rate from the wearable device and audio data from the mobile device.

[1835] Data processing and calculation: Analyzes heart rate and voice data to recognize the user's emotional state.

[1836] Output: Perceived user emotional state (e.g., stress level, emotional tendency, etc.)

[1837] Step 6:

[1838] Input: Various data (electrical device data, health data, location information, temperature data, emotional data)

[1839] Specific operation: The server inputs the collected data into the generative AI model.

[1840] Data processing and calculation: Data is denoised and normalised, and an optimisation algorithm is used to predict the optimal operating pattern for each piece of electrical equipment.

[1841] Output: Optimal operating patterns and adjustment parameters

[1842] Step 7:

[1843] Input: Optimization results

[1844] Specific operation: Based on the analysis results, the server notifies the user of optimization suggestions.

[1845] Data processing and calculation: The analysis results are converted into a format that is easy for users to understand and displayed on devices such as smartphones.

[1846] Output: Optimization suggestions communicated to the user

[1847] Step 8:

[1848] Input: User approval result

[1849] Specific operation: When the user approves the proposal, the server sends instructions for automatic control to each electrical device.

[1850] Data processing and calculation: Generates control instructions for each electrical device and sends them to the corresponding device.

[1851] Output: Automatic control instructions are sent to change the settings of each electrical device.

[1852] (Application example 2)

[1853] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1854] Currently, environmental management in homes and factories is often based on only a few electrical appliances and devices. This makes comprehensive and efficient environmental optimization difficult, and adaptation based on the user's individual health and emotional state is lacking. Furthermore, data analysis and suggestion functions for improving work efficiency and safety are still limited. The present invention aims to achieve comprehensive and individually adaptive optimization of the environment and work conditions in homes and factories, thereby improving energy efficiency and work safety and comfort.

[1855] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1856] In this invention, the server includes: means for acquiring operation status and setting information from various electrical appliances in the home; means for acquiring water and gas usage; means for acquiring personal health data from a wearable device; means for acquiring location information and activity data from a mobile terminal; means for acquiring temperature and weather forecasts via the Internet; means for recognizing an individual's emotional state using an emotion engine; analysis means including a generation AI that predicts operation patterns of electrical appliances using an optimization algorithm based on the acquired data and makes optimal adjustments; means for notifying a user of the optimization results obtained by the analysis means; means for automatically controlling each electrical appliance based on the user's approval; means for acquiring operation status and setting information from industrial machinery; means for acquiring health data and emotional states from workers' wearable devices; means for acquiring external environment data via the Internet; analysis means including a generation AI that predicts operation patterns using an optimization algorithm based on the acquired data and makes optimal adjustments; means for notifying a manager and a worker of the optimization results obtained by the analysis means; and means for automatically controlling industrial machinery based on the manager and a worker's approval. This makes it possible to individually optimize the environment and working conditions within homes and factories, improving energy efficiency, work efficiency, and safety.

[1857] "Various electrical equipment" refers to electrical equipment used in homes and factories, such as air conditioners, water heaters, air purifiers, and lighting.

[1858] "Operation status" is information that indicates the current operating state of electrical equipment and industrial machinery.

[1859] "Setting information" refers to information relating to the operating parameters and operating modes of electrical equipment and industrial machinery.

[1860] "Water and gas usage" is data measuring the amount of water and gas consumed within homes and factories.

[1861] A "wearable device" is a device that measures health data by being worn, such as a smartwatch or fitness tracker.

[1862] "Health data" is data that indicates an individual's health status, such as heart rate, body temperature, and sleep patterns.

[1863] A "mobile terminal" is a mobile device such as a smartphone or tablet.

[1864] "Location information" is information that indicates the current location of the user and is collected by the mobile terminal.

[1865] "Activity data" is data that indicates the user's movement and activity status, such as the number of steps, distance traveled, and calories burned.

[1866] "Means for obtaining temperature and weather forecast via the Internet" is a function for obtaining outside temperature and weather information via the Internet.

[1867] An "emotion engine" is an algorithm or function that analyzes physiological and audio data to recognize the user's emotional state.

[1868] An "optimization algorithm" is a series of calculation methods for calculating optimal equipment operating patterns and settings based on collected data.

[1869] "Generative AI" is an artificial intelligence technology that analyzes large amounts of data and performs efficient optimization.

[1870] The "analysis means" is the part of the system that includes functions ranging from data preprocessing to the execution of optimization algorithms.

[1871] "Notification means" is a function for notifying users and administrator...

Claims

1. A means for acquiring operating status and setting information from various electrical devices in the home; A means of obtaining water and gas usage data; a means for acquiring personal health data from the wearable device; means for acquiring location information and activity data from the mobile device; means for obtaining temperature and weather forecasts via the Internet; An analysis means including a generation AI that predicts the operation pattern of the electrical equipment using an optimization algorithm based on the acquired data and performs optimal adjustments; means for notifying a user of the optimization results obtained by the analysis means; A means of automatically controlling each electrical device based on user approval A system including:

2. 2. The system of claim 1, wherein the analyzing means further comprises means for denoising and normalizing the data.

3. The system according to claim 1 , further comprising means for continuously monitoring the operating status and resource consumption of each of said electrical devices and for re-optimizing as necessary.

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