system

Abstract

We provide the system. [Solution] In a computer-based management system that provides a method and apparatus for integrating the control of multiple devices from different manufacturers, A means for interpreting user instructions and transmitting signals to the corresponding device, A means of generating automation scenarios by analyzing usage data collected from devices within the home, A means of monitoring the power consumption of a device and sending notifications to the user recommending energy reduction, A means of monitoring anomalies detected by security sensors and notifying the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, a large number of devices provided by different manufacturers are used in households. However, since each device is managed individually, users are burdened with complicated operations and settings. In addition, the lack of a unified platform that can integrate and efficiently control devices has impaired user convenience. Furthermore, there is also concern due to the inability to efficiently manage functions related to energy consumption optimization and security. There is a need for an innovative management system to solve such problems.

Means for Solving the Problems

[0005] This invention provides a means for interpreting user instructions and transmitting signals to the relevant devices in order to integrally control multiple devices from different manufacturers. It also enables efficient device control based on the user's lifestyle by analyzing usage data collected from devices in the home and generating automation scenarios. Furthermore, it optimizes power usage by monitoring device power consumption and sending notifications to the user recommending energy reduction. In addition, it is a system that enhances safety by utilizing means to monitor anomalies detected by security sensors and notifying the user.

[0006] "Equipment" refers to various electrical products and electronic devices used in a home environment.

[0007] "Integrated control" means centrally managing and efficiently operating and configuring multiple devices provided by different manufacturers.

[0008] A "user" refers to a person who uses a system to operate equipment and enjoy its functions.

[0009] "Signal" refers to an electrical or electronic means of communication used to transmit data or instructions.

[0010] "Usage data" refers to information about the usage history and operating status of equipment, and analyzing this data forms the basis for identifying user usage patterns.

[0011] An "automation scenario" refers to a plan or procedure for automatically controlling equipment based on pre-designed logic and conditions.

[0012] "Notifications recommending energy reduction" refer to a means of providing users with information to encourage energy-saving behavior by informing them of the results of their power consumption analysis.

[0013] A "security sensor" refers to a sensor device used to detect abnormal behavior or events within or around a home.

[0014] An "anomaly" refers to an unexpected operation or event that deviates from normal operation or conditions, and is considered to potentially cause problems for safety or efficiency. [Brief explanation of the drawing]

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

Embodiment for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

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

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

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

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

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

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

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

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0036] The present invention is a system for integrating and controlling multiple devices from different manufacturers, and details of its embodiments are described below.

[0037] Overall structure

[0038] This system is comprised of three main components: a server, terminals, and users. The server plays a central role in controlling the entire system, while the terminals provide the user interface. Users use these to operate the equipment.

[0039] Integrated management of equipment

[0040] The server provides comprehensive management for various devices within the home. Even if the devices are from different manufacturers, the server integrates their respective communication protocols and control methods, enabling centralized control.

[0041] For example, a server can communicate with various devices through adapters that support different protocols, and then convert that communication into a standardized instruction set, allowing it to operate different devices simultaneously.

[0042] Voice and chat-based operation

[0043] The terminal accepts voice commands and chat input from the user. Voice commands are processed by the terminal using natural language processing and converted into text. These textualized commands are then forwarded to the server and executed.

[0044] As a concrete example, if a user gives a voice command saying, "Turn on the living room lights," the terminal analyzes the voice, generates a command, and sends it to the server. The server then sends a signal with the appropriate protocol to the lighting device, turning on the lights.

[0045] Learning and implementing automation scenarios

[0046] The server can analyze user usage history and schedules to generate optimized automation scenarios for each user. This allows users to automate many tasks in their daily lives without even realizing it.

[0047] For example, the server learns a pattern in which a user uses a coffee maker every morning and automatically activates the coffee maker at a specified time.

[0048] Optimizing energy efficiency

[0049] The server monitors the power consumption of the equipment and, based on the analysis results, notifies the user of suggestions that can lead to energy savings. For example, if an air conditioner has been running continuously for a long period of time, the server will suggest switching to eco mode to reduce power consumption.

[0050] Security monitoring function

[0051] The server receives information from security devices inside and outside the home and has the function to immediately notify the user of any anomalies it detects. For example, if unauthorized access is detected in the middle of the night, the server will issue an alarm and send a push notification to the user's device.

[0052] In this way, the present invention provides a system for effectively integrating and managing household appliances in order to improve user convenience, safety, and energy efficiency.

[0053] The following describes the processing flow.

[0054] Step 1:

[0055] The user sends instructions to the device they want to control via voice or chat. For example, they might say, "Turn on the living room lights."

[0056] Step 2:

[0057] The terminal converts the received voice commands into text using natural language processing technology and prepares to send it to the server. At this time, it verifies that the user's command is related to a specific device.

[0058] Step 3:

[0059] The server analyzes the text commands received from the terminal and identifies the operation instructions corresponding to the specific device. The server then verifies that these instructions conform to the protocol of the associated device.

[0060] Step 4:

[0061] The server sends signals to the target device based on the analyzed instructions, executing the desired operation (e.g., turning on the lights). The destination device is centrally controlled by an integrated management system, regardless of the manufacturer.

[0062] Step 5:

[0063] The server receives feedback from the device to confirm that the operation was successful. If feedback is received, the server proceeds to the next step. If no feedback is received, error handling is performed.

[0064] Step 6:

[0065] The server notifies the terminal that the operation was performed correctly. The terminal notifies the user of the success message, either visually or audibly.

[0066] Step 7:

[0067] The user can confirm the success of the operation through the terminal and then perform other operations or give new instructions. If no further instructions are given, the system returns to standby mode.

[0068] (Example 1)

[0069] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0070] Currently, various devices from different manufacturers used in homes have their own unique communication protocols and control methods, making integrated control difficult. Furthermore, ensuring user-friendly operation while efficiently consuming energy and maintaining safety are further challenges. To address this, an integrated management system is needed that centrally manages multiple devices and improves user experience.

[0071] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0072] In this invention, the server includes means for interpreting voice instructions or text input from a user using natural language processing technology and transmitting standardized commands to the corresponding device; means for analyzing natural language prompt sentences using a generated artificial intelligence model and converting them into control commands for the device; and means for analyzing operational data collected from devices in the home and generating automated operation procedures optimized for the user. This makes it possible to comprehensively control devices from different manufacturers and simultaneously provide efficient energy management and high convenience.

[0073] "Information processing equipment" is a general term for electronic devices used for data processing and communication.

[0074] "Natural language processing technology" is a technology that processes human knowledge about language on a computer, and includes functions for understanding and generating speech and text.

[0075] An "artificial intelligence model" is a statistical model that uses machine learning algorithms to automate specific tasks and is capable of self-improvement without relying on human knowledge.

[0076] A "prompt statement" is a sentence entered into an artificial intelligence model to give it instructions, and it functions as a trigger for the model to make an appropriate response or process.

[0077] "Operational data" refers to a collection of information generated when various devices in a household are in operation, including data such as usage status and energy consumption.

[0078] An "automated operation procedure" refers to a set of steps that a device performs automatically based on pre-set rules and conditions, without user intervention.

[0079] A "standardized command" is a unified command format designed to ensure compatibility between different devices, and is essential for a server to correctly control each device.

[0080] An "integrated management system" is a system for centrally controlling or monitoring multiple devices, and serves as a platform to improve user convenience and efficiency.

[0081] This invention is a system using an information processing device for the integrated management of household electrical appliances from different manufacturers. Users can operate the terminal via voice or text to efficiently control appliances within their home. The terminal receives user instructions, analyzes the input data using natural language processing technology, and extracts appropriate control commands from the prompt text using a generative AI model.

[0082] The terminal receives voice commands and text messages from the user and converts them into text data. The natural language processing technology used here consists of advanced software modules that perform speech recognition and text analysis. This analyzed data is then converted into a command format and sent to the server.

[0083] The server analyzes the commands received from the terminal and sends standardized commands to the target device. The server uses an internal database to check the protocol of each device and generates appropriate commands. In this process, a generative AI model plays a crucial role in accurately converting prompt statements into commands.

[0084] For example, if a user gives a voice command such as "Turn on the living room lights," the terminal converts this voice into text and sends the prompt "Turn on the lights" to the server. The server analyzes the received prompt and sends the appropriate control signal to the living room lighting fixture to turn on the lights.

[0085] Examples of prompt statements include the following:

[0086] "Turn off the air conditioner."

[0087] "Open the curtains at 7 AM."

[0088] "Turn off all the electricity at once."

[0089] In this way, the system can execute user instructions quickly and accurately, improving convenience and efficiency within the home. The coordinated operation of the server and terminals ensures a consistent user experience.

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

[0091] Step 1:

[0092] The user provides voice commands or text input to the device. This input includes voice commands such as "Turn on the air conditioner" or chat messages. The device receives this as voice or text data.

[0093] Step 2:

[0094] The terminal converts the received audio data into text using natural language processing technology. Specifically, a speech recognition module analyzes the audio waveform and outputs the text data "Turn on the air conditioner." Here, a generative AI model analyzes the meaning of the audio and converts it into a standardized command.

[0095] Step 3:

[0096] The terminal generates a prompt message from the text command obtained through natural language processing. This prompt message (e.g., "Turn on the air conditioner") is sent to the server.

[0097] Step 4:

[0098] The server parses the received prompt message and performs protocol translation for device identification and control. Here, it refers to the server's internal database to identify the device ID and communication protocol for the "air conditioner".

[0099] Step 5:

[0100] The server sends appropriately generated, standardized commands to the corresponding device. The specific signals are sent over the network to the air conditioner, causing it to start. The output is that the air conditioner is operating.

[0101] Step 6:

[0102] The server monitors the device's response and, once normal operation is confirmed, sends a completion notification to the user's terminal. For example, a message such as "Air conditioner turned on" might appear on the user's smartphone.

[0103] This series of processes allows users to efficiently control devices within their home via voice or text.

[0104] (Application Example 1)

[0105] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0106] In urban environments where equipment from different manufacturers coexists, there is a need to efficiently manage public infrastructure and provide consistent control and information to users. Energy efficiency and enhanced security are also crucial challenges.

[0107] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0108] In this invention, the server includes means for analyzing user instructions and transmitting signals to the corresponding devices, means for acquiring public infrastructure data and providing traffic and security information to users, and means for analyzing usage data and generating automated control scenarios. This enables integrated management of devices from different manufacturers in urban environments, leading to improved energy efficiency and information provision to users.

[0109] A "device" is a hardware component designed to perform a specific function or role.

[0110] A "user" is the entity that operates and utilizes a device or system.

[0111] "Infrastructure data" refers to information regarding the operational status of public facilities and systems in urban environments.

[0112] "Traffic information" refers to data including congestion, delays, and service status of public transportation and roads.

[0113] "Security information" refers to data regarding anomalies and safety issues monitored by security-related systems.

[0114] "Energy consumption" refers to the total amount of electricity and resources consumed when a device is in operation.

[0115] An "automated control scenario" is a set of procedures designed to operate a device or system automatically according to time and circumstances.

[0116] The system for carrying out this invention aims to integrate and control devices from different manufacturers. A typical embodiment is described in detail below.

[0117] The server plays a central role in controlling the entire system. Specifically, it uses speech recognition software and natural language processing engines to receive instructions from users, and sends the analyzed content as commands to the appropriate devices. In this process, it utilizes information services such as Google® Maps API to collect traffic information and energy consumption data.

[0118] The terminal uses smartphone applications or wearable device interfaces as its user interface. The terminal acquires public infrastructure data and displays traffic and security information required by the user. It also receives user voice commands via the terminal and transmits them to a server.

[0119] Users can interact with the interface using the terminal to obtain necessary information and control devices. For example, a user can enter a prompt such as "Suggest an alternative route for the delayed train" into the terminal and receive an immediate suggestion. This can greatly improve the convenience of life in urban environments.

[0120] In this way, seamless management between different devices and efficient support for urban life can be achieved by incorporating generative AI models.

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

[0122] Step 1:

[0123] The server receives voice or text instructions from the user via the terminal. The input is the prompt text entered by the user on the terminal. The server analyzes this input using speech recognition software and a natural language processing engine, converting it into standardized commands. The output is the analyzed commands.

[0124] Step 2:

[0125] The server uses the parsed command to check information about the relevant devices and systems. For example, in the case of traffic information, it uses the Google Maps API to obtain real-time data. The input is the parsed command and the endpoint of the relevant API. Data processing involves extracting the necessary information from the API. The output is specific instruction data to be sent to the device or system.

[0126] Step 3:

[0127] The server generates appropriate control signals based on the acquired information and transmits them to each device according to the instructions. The input is instruction data, and the output is the control signal to the controlled device. In this process, the server uses a standard protocol that is independent of the manufacturer of each device.

[0128] Step 4:

[0129] The server uses a generative AI model to generate optimal control scenarios based on user requests. Inputs include past user behavior data and system states. The data calculation involves analyzing behavioral patterns and generating scenarios based on these analyses. The output is a control scenario based on future predictions.

[0130] Step 5:

[0131] The terminal receives the final results and suggestions from the server and provides visual or audible feedback to the user. Input is the suggestions and information sent from the server. The terminal converts this into a user-friendly format and displays it. Output is the content of the interface provided to the user.

[0132] In this way, users can obtain information in real time and perform remote operations.

[0133] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0134] The present invention is a system for integrating and controlling multiple devices and emotion engines from different manufacturers, and its embodiments are described in detail below.

[0135] Overall structure

[0136] The system includes three main components: a server, a terminal, and a user, in addition to an emotion engine. The server manages the entire system, while the terminal acts as the interface between the user and the system. Users send instructions to the system through the terminal. The emotion engine is responsible for recognizing the user's emotions and reflecting them in the system's operation.

[0137] The function of the emotional engine

[0138] The device acquires the user's facial expressions, voice tone, language patterns, and other data through an emotion engine. This data is used by the system to recognize and respond to the user's emotional state in real time.

[0139] For example, if the emotion engine analyzes that the user is feeling stressed, the system can automatically play relaxing music and adjust the lighting to warmer tones.

[0140] Integrated device management and emotional reflection

[0141] The server monitors devices within the home and controls them integrally based on instructions. Based on sentiment data from the user, the server creates and executes optimal device operation scenarios.

[0142] For example, when the emotion engine recognizes that the user is in a happy mood, the server can activate the entertainment system, adjust the lighting to create a cheerful atmosphere.

[0143] Automation and personalized support

[0144] The server collects and analyzes user emotional data to generate personalized automated scenarios. This process works in conjunction with normal lifestyle habit learning to provide an experience adapted to the user's emotions.

[0145] For example, if the emotion engine detects fatigue when a user returns home from work, it will automatically adjust the room temperature to a comfortable level and implement measures to provide a calming environment.

[0146] Energy and security integration

[0147] The server monitors the device's power consumption in real time, and when the emotion engine detects the user's tension or anxiety, it switches from energy-saving mode to normal mode to provide a sense of security.

[0148] Regarding security features, we provide notifications and feedback that respond to the user's emotions, ensuring safety in the most appropriate way for the user by providing emotion-based information.

[0149] Thus, the present invention provides a system that manages the home environment comfortably and effectively based on the user's emotions.

[0150] The following describes the processing flow.

[0151] Step 1:

[0152] The user activates their device to utilize the emotion engine and initiates emotional input feedback as needed. This allows the emotion engine to acquire the user's state in real time.

[0153] Step 2:

[0154] The device collects emotional data in a non-invasive way, such as the user's facial expressions and tone of voice. This data is sent to an emotion engine, where it is analyzed to understand the user's emotional state.

[0155] Step 3:

[0156] The emotion engine analyzes the acquired data to identify the user's current emotional state. For example, consider a scenario where the system determines that the user is stressed.

[0157] Step 4:

[0158] The server receives the sentiment analysis results from the emotion engine and determines the optimal automation scenario based on them. For example, it might suggest relaxing lighting and music to a user experiencing stress.

[0159] Step 5:

[0160] The server sends appropriate instructions to devices in the home according to the determined automation scenario. For example, it might instruct devices to lower the color temperature of the lights or play music.

[0161] Step 6:

[0162] The device receives instructions from the server and provides feedback to the user. It notifies the user that the instructions have been carried out and asks if the user wishes to make further adjustments through interaction with the emotion engine.

[0163] Step 7:

[0164] Users help the system adapt further by reviewing feedback and instructing on additional adjustments as needed. At this stage, if there are new requests, the server and emotion engine processes are restarted.

[0165] (Example 2)

[0166] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0167] Modern homes and offices contain a wide variety of equipment from different manufacturers, creating a need for efficient systems to integrate and control them. Furthermore, it's crucial to provide a more comfortable and personalized environment by reflecting and adapting to the user's emotional state. However, few existing systems meet these complex requirements, and they often suffer from cumbersome management.

[0168] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0169] In this invention, the server includes means for interpreting instructions from users and transmitting signals to the corresponding equipment; means for analyzing usage data collected from equipment within a living space and generating automation scenarios; and means for analyzing the user's emotional state using an emotion recognition engine and optimizing the operation of the equipment based on that data. This enables integrated control of the equipment and the provision of a personalized environment.

[0170] "Equipment" refers to various devices and home appliances used in homes and offices.

[0171] A "data processing device" refers to a device or system for handling, analyzing, and controlling information.

[0172] "User" refers to a person who operates or uses this system.

[0173] "Instructions" refer to the operations or requests that users make to the system.

[0174] A "signal" refers to electrical or electronic communication information that a system transmits to equipment.

[0175] An "emotion recognition engine" refers to software or system functionality used to detect and analyze a user's emotional state.

[0176] "Optimizing operations" refers to adjusting equipment to function most efficiently based on the user's circumstances and feelings.

[0177] "Living space" refers to the place where users live, that is, the interior of a home or office.

[0178] An "automation scenario" refers to a set of operating procedures for equipment, generated by the system based on pre-set conditions.

[0179] This invention is a system that integrates and controls multiple pieces of equipment from different manufacturers, optimizing the environment based on user emotions.

[0180] System Configuration

[0181] The system primarily consists of a server, terminals, and users, and uses an emotion recognition engine to coordinate its overall operation. The server acts as a data processing unit, analyzing emotion data collected via the terminals. Users can give instructions to the system and control the operation of the equipment through their terminals.

[0182] Hardware and software

[0183] The server acts as a data processing unit, mediating communication with multiple devices and executing control scenarios. This includes software for monitoring energy consumption and detecting anomalies.

[0184] The device uses sensors and microphones to capture the user's facial expressions and voice tone, and transmits this data to the emotion recognition engine.

[0185] The emotion recognition engine uses a generative AI model to analyze data sent from the device and identify the user's emotional state.

[0186] Specific example

[0187] For example, when a user returns home, the device detects their facial expressions and tone of voice, and the emotion recognition engine detects "fatigue." Based on this data, the server controls the equipment to play relaxing music and adjust the lighting to calming colors.

[0188] Example of a prompt

[0189] An example of a prompt message is, "Please configure the settings so that the user can relax in the living room."

[0190] This invention makes it easier to adjust the home environment based on the user's emotions, thereby improving the quality of life.

[0191] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0192] Step 1:

[0193] The device uses sensors and a microphone to detect the user's facial expressions, voice tone, and language patterns. This data serves as input to identify the user's emotional state. The collected data is sent to an emotion recognition engine. Specific actions include the device taking a picture of the user's face with its camera and recording their voice with its microphone.

[0194] Step 2:

[0195] The server receives data sent from the terminal and performs data analysis using an AI model generated by the emotion recognition engine. This analysis identifies the user's emotional state (e.g., "relaxed," "stressed," etc.). This process includes facial expression analysis and voice analysis, and outputs an emotion recognition pattern.

[0196] Step 3:

[0197] The server generates an optimal control scenario tailored to the user's emotions, based on the output from the emotion recognition engine. Emotional state data is used as input, and specific instructions for controlling household equipment are generated as output. For example, the server might generate instructions to adjust lighting or play relaxing music.

[0198] Step 4:

[0199] The server sends the generated control scenario to the terminal and each piece of equipment in the home, prompting them to perform specific actions. This causes the equipment to adjust the environment according to the instructions from the server. For example, the audio system might play a specified song, or the lighting system might adjust to the specified color and brightness.

[0200] Step 5:

[0201] Users can experience an environment controlled by an emotion engine and provide feedback to the server. This feedback is then incorporated into subsequent scenario generation, resulting in even more personalized control. Specifically, users provide feedback to the system by inputting instructions such as "I'd like the lighting to be a little brighter" to their device.

[0202] (Application Example 2)

[0203] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0204] In modern urban spaces, actively adapting public facilities and living environments to the emotional states of users is crucial for improving the quality of life for residents. However, coordinating devices and systems from different manufacturers is difficult, making dynamic adjustments to the environment based on user emotions challenging. Therefore, there is a need for a system that can analyze users' emotional states in real time and adjust the environment accordingly to the optimal setting.

[0205] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0206] In this invention, the server includes means for interpreting user instructions and transmitting signals to the corresponding devices, means for analyzing usage data collected from devices in apartment buildings or urban spaces to generate automation scenarios, and means for analyzing user emotional data and dynamically adjusting the public environment and device status in the urban space. This makes it possible to integrally manage devices and systems from different manufacturers, and easily realize individualized responses and optimal environmental adjustments based on user emotions.

[0207] An "information processing device" is a computer system that collects, analyzes, and controls data, and enables communication between devices.

[0208] A "user" is a human interface that transmits instructions and provides emotional data through an information processing device.

[0209] A "device" is hardware installed in a home or urban space that has functions such as lighting, entertainment systems, or other functions.

[0210] "Emotional data" refers to information that represents the user's emotional state, and is composed of information such as facial expressions, voice tone, and behavioral patterns.

[0211] An "automation scenario" is a set of pre-configured procedures that define and execute the optimal operation of a device based on user instructions and emotional data.

[0212] "Power consumption" refers to the amount of electricity required for a device to function, and is a measure of energy efficiency.

[0213] A "safety sensor" is a security device that detects abnormal conditions in equipment or the environment and notifies an information processing device.

[0214] "Public environment" refers to the physical and functional settings of publicly used spaces in urban areas, such as parks, libraries, and streets.

[0215] This invention relates to a system centered on an information processing device for dynamically adjusting the environment based on the user's emotional state. In this system, a server plays a central role in comprehensively managing various devices.

[0216] The server receives emotional data sent from users and analyzes it in real time. This analysis utilizes cloud-based facial recognition technology and software that acts as a voice sensor. Specifically, it uses APIs such as Google Cloud Vision and AWS® Rekognition to identify emotions based on the user's facial expressions and voice tone.

[0217] Based on the analyzed emotional data, the server constructs an automated scenario. This scenario includes optimal device operation procedures that take into account the user's current emotional state. For example, if the server determines that the user is relaxed while strolling through a park, it sends a command to the relevant device via the smartphone to play soothing music through earphones and adjust the streetlights to a softer color tone.

[0218] As a concrete example, when sending a prompt to a generative AI model, it might be used in the form of, "Could you suggest background music that will help enhance a user's relaxed emotional state while walking through a public park, considering the current time of day and weather conditions?" This prompt is used by the generative AI model to select content appropriate to the user's state.

[0219] As described above, personalized services and adjustments tailored to the user's emotional needs can be provided through an automated system. This system can be widely applied in both urban spaces and homes.

[0220] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0221] Step 1:

[0222] The device captures the user's facial expressions and voice data and sends it to the server. Input is real-time data from the camera and microphone, which is converted into image and audio formats as needed. Output is sent to the server as a data stream.

[0223] Step 2:

[0224] The server analyzes the emotional data it receives. The input consists of facial expressions and voice data sent from the terminal. For data processing, APIs such as Google Cloud Vision and AWS Rekognition are used to output the user's emotional state as text or numerical data.

[0225] Step 3:

[0226] The server generates automated scenarios based on the analysis results. The input is information on the analyzed emotional state. As a data calculation, it combines existing scenario templates with the analysis results to select a scenario appropriate to the user's state and converts it into device control commands. The output is sent to each device as specific control commands.

[0227] Step 4:

[0228] The server sends control commands to the devices, causing them to make configuration changes and provide data on-site. The input consists of automated control commands, which are transmitted to each device using a communication protocol. The output is perceived by the user as changes in the operation of the corresponding devices or as new information provided.

[0229] Step 5:

[0230] The system receives environmental changes and information services provided to the user. Input consists of physical changes and information from the device. If the user provides feedback through the terminal, this information is also sent to the server and used to adjust scenarios for future use. Output is achieved as improvements in user comfort and satisfaction.

[0231] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0232] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0233] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0234] [Second Embodiment]

[0235] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0236] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0237] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0238] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0239] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0240] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0241] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0242] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0243] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0244] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0245] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0246] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0247] The present invention is a system for integrating and controlling multiple devices from different manufacturers, and details of its embodiments are described below.

[0248] Overall structure

[0249] This system is comprised of three main components: a server, terminals, and users. The server plays a central role in controlling the entire system, while the terminals provide the user interface. Users use these to operate the equipment.

[0250] Integrated management of equipment

[0251] The server provides comprehensive management for various devices within the home. Even if the devices are from different manufacturers, the server integrates their respective communication protocols and control methods, enabling centralized control.

[0252] For example, a server can communicate with various devices through adapters that support different protocols, and then convert that communication into a standardized instruction set, allowing it to operate different devices simultaneously.

[0253] Voice and chat-based operation

[0254] The terminal accepts voice commands and chat input from the user. Voice commands are processed by the terminal using natural language processing and converted into text. These textualized commands are then forwarded to the server and executed.

[0255] As a concrete example, if a user gives a voice command saying, "Turn on the living room lights," the terminal analyzes the voice, generates a command, and sends it to the server. The server then sends a signal with the appropriate protocol to the lighting device, turning on the lights.

[0256] Learning and implementing automation scenarios

[0257] The server can analyze user usage history and schedules to generate optimized automation scenarios for each user. This allows users to automate many tasks in their daily lives without even realizing it.

[0258] For example, the server learns a pattern in which a user uses a coffee maker every morning and automatically activates the coffee maker at a specified time.

[0259] Optimizing energy efficiency

[0260] The server monitors the power consumption of the equipment and, based on the analysis results, notifies the user of suggestions that can lead to energy savings. For example, if an air conditioner has been running continuously for a long period of time, the server will suggest switching to eco mode to reduce power consumption.

[0261] Security monitoring function

[0262] The server receives information from security devices inside and outside the home and has the function to immediately notify the user of any anomalies it detects. For example, if unauthorized access is detected in the middle of the night, the server will issue an alarm and send a push notification to the user's device.

[0263] In this way, the present invention provides a system for effectively integrating and managing household appliances in order to improve user convenience, safety, and energy efficiency.

[0264] The following describes the processing flow.

[0265] Step 1:

[0266] The user sends instructions to the device they want to control via voice or chat. For example, they might say, "Turn on the living room lights."

[0267] Step 2:

[0268] The terminal converts the received voice commands into text using natural language processing technology and prepares to send it to the server. At this time, it verifies that the user's command is related to a specific device.

[0269] Step 3:

[0270] The server analyzes the text commands received from the terminal and identifies the operation instructions corresponding to the specific device. The server then verifies that these instructions conform to the protocol of the associated device.

[0271] Step 4:

[0272] The server sends signals to the target device based on the analyzed instructions, executing the desired operation (e.g., turning on the lights). The destination device is centrally controlled by an integrated management system, regardless of the manufacturer.

[0273] Step 5:

[0274] The server receives feedback from the device to confirm that the operation was successful. If feedback is received, the server proceeds to the next step. If no feedback is received, error handling is performed.

[0275] Step 6:

[0276] The server notifies the terminal that the operation was performed correctly. The terminal notifies the user of the success message, either visually or audibly.

[0277] Step 7:

[0278] The user can confirm the success of the operation through the terminal and then perform other operations or give new instructions. If no further instructions are given, the system returns to standby mode.

[0279] (Example 1)

[0280] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0281] Currently, various devices from different manufacturers used in homes have their own unique communication protocols and control methods, making integrated control difficult. Furthermore, ensuring user-friendly operation while efficiently consuming energy and maintaining safety are further challenges. To address this, an integrated management system is needed that centrally manages multiple devices and improves user experience.

[0282] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Example 1 is realized by the following means.

[0283] In this invention, the server includes means for interpreting a voice instruction or character input from a user using natural language processing technology and transmitting a standardized command to the corresponding apparatus, means for analyzing a natural language prompt sentence using an artificial intelligence model generated and converting it into a control command of the apparatus, and means for analyzing operation data collected from apparatuses in the home and generating an automated operation procedure optimized for the user. Thereby, it becomes possible to comprehensively control apparatuses of different manufacturers and simultaneously provide efficient energy management and high convenience.

[0284] An "information processing apparatus" is a general term for electronic devices for processing data and performing communication.

[0285] "Natural language processing technology" is a technology for processing human knowledge related to language on a computer and includes functions for understanding and generating voice and text.

[0286] An "artificial intelligence model" is a statistical model that automates a specific task using a machine learning algorithm and can improve itself without relying on human knowledge.

[0287] A "prompt sentence" is a sentence input to give a command to an artificial intelligence model and functions as a trigger for the model to perform an appropriate response or processing.

[0288] "Operation data" is a set of information generated when various apparatuses in the home operate and includes data such as usage status and energy consumption.

[0289] An "automated operation procedure" is a procedure of operations that an apparatus automatically performs based on preset rules and conditions and executes processing without the intervention of the user's hand.

[0290] A "standardized command" is a unified command format designed to ensure compatibility between different devices, and is essential for a server to correctly control each device.

[0291] An "integrated management system" is a system for centrally controlling or monitoring multiple devices, and serves as a platform to improve user convenience and efficiency.

[0292] This invention is a system using an information processing device for the integrated management of household electrical appliances from different manufacturers. Users can operate the terminal via voice or text to efficiently control appliances within their home. The terminal receives user instructions, analyzes the input data using natural language processing technology, and extracts appropriate control commands from the prompt text using a generative AI model.

[0293] The terminal receives voice commands and text messages from the user and converts them into text data. The natural language processing technology used here consists of advanced software modules that perform speech recognition and text analysis. This analyzed data is then converted into a command format and sent to the server.

[0294] The server analyzes the commands received from the terminal and sends standardized commands to the target device. The server uses an internal database to check the protocol of each device and generates appropriate commands. In this process, a generative AI model plays a crucial role in accurately converting prompt statements into commands.

[0295] For example, if a user gives a voice command such as "Turn on the living room lights," the terminal converts this voice into text and sends the prompt "Turn on the lights" to the server. The server analyzes the received prompt and sends the appropriate control signal to the living room lighting fixture to turn on the lights.

[0296] Examples of prompt statements include the following:

[0297] "Turn off the air conditioner"

[0298] "Open the curtains at 7 am"

[0299] "Turn off all the electricity at once"

[0300] In this way, the system can accurately execute the user's instructions in a short time, improving the convenience and efficiency within the home. By the server and the terminal operating in cooperation, the user can obtain a consistent experience.

[0301] The flow of the specific process in Example 1 will be described using FIG. 11.

[0302] Step 1:

[0303] The user provides voice instructions or text input to the terminal. The input includes voices or chat messages such as "Turn on the air conditioner". The terminal receives this as voice data or text data.

[0304] Step 2:

[0305] The terminal converts the received voice data into text using natural language processing technology. Specifically, the voice recognition module analyzes the voice waveform and outputs text data such as "Turn on the air conditioner". Here, the generative AI model analyzes the meaning of the voice and converts it into a standardized command.

[0306] Step 3:

[0307] The terminal generates the text command obtained by natural language processing as a prompt sentence. This prompt sentence (e.g., "Operate the air conditioner") is sent to the server.

[0308] Step 4:

[0309] The server parses the received prompt message and performs protocol translation for device identification and control. Here, it refers to the server's internal database to identify the device ID and communication protocol for the "air conditioner".

[0310] Step 5:

[0311] The server sends appropriately generated, standardized commands to the corresponding device. The specific signals are sent over the network to the air conditioner, causing it to start. The output is that the air conditioner is operating.

[0312] Step 6:

[0313] The server monitors the device's response and, once normal operation is confirmed, sends a completion notification to the user's terminal. For example, a message such as "Air conditioner turned on" might appear on the user's smartphone.

[0314] This series of processes allows users to efficiently control devices within their home via voice or text.

[0315] (Application Example 1)

[0316] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0317] In urban environments where equipment from different manufacturers coexists, there is a need to efficiently manage public infrastructure and provide consistent control and information to users. Energy efficiency and enhanced security are also crucial challenges.

[0318] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0319] In this invention, the server includes means for analyzing user instructions and transmitting signals to the corresponding devices, means for acquiring public infrastructure data and providing traffic and security information to users, and means for analyzing usage data and generating automated control scenarios. This enables integrated management of devices from different manufacturers in urban environments, leading to improved energy efficiency and information provision to users.

[0320] A "device" is a hardware component designed to perform a specific function or role.

[0321] A "user" is the entity that operates and utilizes a device or system.

[0322] "Infrastructure data" refers to information regarding the operational status of public facilities and systems in urban environments.

[0323] "Traffic information" refers to data including congestion, delays, and service status of public transportation and roads.

[0324] "Security information" refers to data regarding anomalies and safety issues monitored by security-related systems.

[0325] "Energy consumption" refers to the total amount of electricity and resources consumed when a device is in operation.

[0326] An "automated control scenario" is a set of procedures designed to operate a device or system automatically according to time and circumstances.

[0327] The system for carrying out this invention aims to integrate and control devices from different manufacturers. A typical embodiment is described in detail below.

[0328] The server plays a central role in controlling the entire system. Specifically, it uses speech recognition software and natural language processing engines to receive instructions from users, and sends the analyzed content as commands to the appropriate devices. In this process, it utilizes information services such as the Google Maps API to collect traffic information and energy consumption data.

[0329] The terminal uses smartphone applications or wearable device interfaces as its user interface. The terminal acquires public infrastructure data and displays traffic and security information required by the user. It also receives user voice commands via the terminal and transmits them to a server.

[0330] Users can interact with the interface using the terminal to obtain necessary information and control devices. For example, a user can enter a prompt such as "Suggest an alternative route for the delayed train" into the terminal and receive an immediate suggestion. This can greatly improve the convenience of life in urban environments.

[0331] In this way, seamless management between different devices and efficient support for urban life can be achieved by incorporating generative AI models.

[0332] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0333] Step 1:

[0334] The server receives voice or text instructions from the user via the terminal. The input is the prompt text entered by the user on the terminal. The server analyzes this input using speech recognition software and a natural language processing engine, converting it into standardized commands. The output is the analyzed commands.

[0335] Step 2:

[0336] The server uses the parsed command to check information about the relevant devices and systems. For example, in the case of traffic information, it uses the Google Maps API to obtain real-time data. The input is the parsed command and the endpoint of the relevant API. Data processing involves extracting the necessary information from the API. The output is specific instruction data to be sent to the device or system.

[0337] Step 3:

[0338] The server generates appropriate control signals based on the acquired information and transmits them to each device according to the instructions. The input is instruction data, and the output is the control signal to the controlled device. In this process, the server uses a standard protocol that is independent of the manufacturer of each device.

[0339] Step 4:

[0340] The server uses a generative AI model to generate optimal control scenarios based on user requests. Inputs include past user behavior data and system states. The data calculation involves analyzing behavioral patterns and generating scenarios based on these analyses. The output is a control scenario based on future predictions.

[0341] Step 5:

[0342] The terminal receives the final results and suggestions from the server and provides visual or audible feedback to the user. Input is the suggestions and information sent from the server. The terminal converts this into a user-friendly format and displays it. Output is the content of the interface provided to the user.

[0343] In this way, users can obtain information in real time and perform remote operations.

[0344] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0345] The present invention is a system for integrating and controlling multiple devices and emotion engines from different manufacturers, and its embodiments are described in detail below.

[0346] Overall structure

[0347] The system includes three main components: a server, a terminal, and a user, in addition to an emotion engine. The server manages the entire system, while the terminal acts as the interface between the user and the system. Users send instructions to the system through the terminal. The emotion engine is responsible for recognizing the user's emotions and reflecting them in the system's operation.

[0348] The function of the emotional engine

[0349] The device acquires the user's facial expressions, voice tone, language patterns, and other data through an emotion engine. This data is used by the system to recognize and respond to the user's emotional state in real time.

[0350] For example, if the emotion engine analyzes that the user is feeling stressed, the system can automatically play relaxing music and adjust the lighting to warmer tones.

[0351] Integrated device management and emotional reflection

[0352] The server monitors devices within the home and controls them integrally based on instructions. Based on sentiment data from the user, the server creates and executes optimal device operation scenarios.

[0353] For example, when the emotion engine recognizes that the user is in a happy mood, the server can activate the entertainment system, adjust the lighting to create a cheerful atmosphere.

[0354] Automation and personalized support

[0355] The server collects and analyzes user emotional data to generate personalized automated scenarios. This process works in conjunction with normal lifestyle habit learning to provide an experience adapted to the user's emotions.

[0356] For example, if the emotion engine detects fatigue when a user returns home from work, it will automatically adjust the room temperature to a comfortable level and implement measures to provide a calming environment.

[0357] Energy and security integration

[0358] The server monitors the device's power consumption in real time, and when the emotion engine detects the user's tension or anxiety, it switches from energy-saving mode to normal mode to provide a sense of security.

[0359] Regarding security features, we provide notifications and feedback that respond to the user's emotions, ensuring safety in the most appropriate way for the user by providing emotion-based information.

[0360] Thus, the present invention provides a system that manages the home environment comfortably and effectively based on the user's emotions.

[0361] The following describes the processing flow.

[0362] Step 1:

[0363] The user activates their device to utilize the emotion engine and initiates emotional input feedback as needed. This allows the emotion engine to acquire the user's state in real time.

[0364] Step 2:

[0365] The device collects emotional data in a non-invasive way, such as the user's facial expressions and tone of voice. This data is sent to an emotion engine, where it is analyzed to understand the user's emotional state.

[0366] Step 3:

[0367] The emotion engine analyzes the acquired data to identify the user's current emotional state. For example, consider a scenario where the system determines that the user is stressed.

[0368] Step 4:

[0369] The server receives the sentiment analysis results from the emotion engine and determines the optimal automation scenario based on them. For example, it might suggest relaxing lighting and music to a user experiencing stress.

[0370] Step 5:

[0371] The server sends appropriate instructions to devices in the home according to the determined automation scenario. For example, it might instruct devices to lower the color temperature of the lights or play music.

[0372] Step 6:

[0373] The device receives instructions from the server and provides feedback to the user. It notifies the user that the instructions have been carried out and asks if the user wishes to make further adjustments through interaction with the emotion engine.

[0374] Step 7:

[0375] Users help the system adapt further by reviewing feedback and instructing on additional adjustments as needed. At this stage, if there are new requests, the server and emotion engine processes are restarted.

[0376] (Example 2)

[0377] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0378] Modern homes and offices contain a wide variety of equipment from different manufacturers, creating a need for efficient systems to integrate and control them. Furthermore, it's crucial to provide a more comfortable and personalized environment by reflecting and adapting to the user's emotional state. However, few existing systems meet these complex requirements, and they often suffer from cumbersome management.

[0379] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0380] In this invention, the server includes means for interpreting instructions from users and transmitting signals to the corresponding equipment; means for analyzing usage data collected from equipment within a living space and generating automation scenarios; and means for analyzing the user's emotional state using an emotion recognition engine and optimizing the operation of the equipment based on that data. This enables integrated control of the equipment and the provision of a personalized environment.

[0381] "Equipment" refers to various devices and home appliances used in homes and offices.

[0382] A "data processing device" refers to a device or system for handling, analyzing, and controlling information.

[0383] "User" refers to a person who operates or uses this system.

[0384] "Instructions" refer to the operations or requests that users make to the system.

[0385] A "signal" refers to electrical or electronic communication information that a system transmits to equipment.

[0386] An "emotion recognition engine" refers to software or system functionality used to detect and analyze a user's emotional state.

[0387] "Optimizing operations" refers to adjusting equipment to function most efficiently based on the user's circumstances and feelings.

[0388] "Living space" refers to the place where users live, that is, the interior of a home or office.

[0389] An "automation scenario" refers to a set of operating procedures for equipment, generated by the system based on pre-set conditions.

[0390] This invention is a system that integrates and controls multiple pieces of equipment from different manufacturers, optimizing the environment based on user emotions.

[0391] System Configuration

[0392] The system primarily consists of a server, terminals, and users, and uses an emotion recognition engine to coordinate its overall operation. The server acts as a data processing unit, analyzing emotion data collected via the terminals. Users can give instructions to the system and control the operation of the equipment through their terminals.

[0393] Hardware and software

[0394] The server acts as a data processing unit, mediating communication with multiple devices and executing control scenarios. This includes software for monitoring energy consumption and detecting anomalies.

[0395] The device uses sensors and microphones to capture the user's facial expressions and voice tone, and transmits this data to the emotion recognition engine.

[0396] The emotion recognition engine uses a generative AI model to analyze data sent from the device and identify the user's emotional state.

[0397] Specific example

[0398] For example, when a user returns home, the device detects their facial expressions and tone of voice, and the emotion recognition engine detects "fatigue." Based on this data, the server controls the equipment to play relaxing music and adjust the lighting to calming colors.

[0399] Example of a prompt

[0400] An example of a prompt message is, "Please configure the settings so that the user can relax in the living room."

[0401] This invention makes it easier to adjust the home environment based on the user's emotions, thereby improving the quality of life.

[0402] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0403] Step 1:

[0404] The device uses sensors and a microphone to detect the user's facial expressions, voice tone, and language patterns. This data serves as input to identify the user's emotional state. The collected data is sent to an emotion recognition engine. Specific actions include the device taking a picture of the user's face with its camera and recording their voice with its microphone.

[0405] Step 2:

[0406] The server receives data sent from the terminal and performs data analysis using an AI model generated by the emotion recognition engine. This analysis identifies the user's emotional state (e.g., "relaxed," "stressed," etc.). This process includes facial expression analysis and voice analysis, and outputs an emotion recognition pattern.

[0407] Step 3:

[0408] The server generates an optimal control scenario tailored to the user's emotions, based on the output from the emotion recognition engine. Emotional state data is used as input, and specific instructions for controlling household equipment are generated as output. For example, the server might generate instructions to adjust lighting or play relaxing music.

[0409] Step 4:

[0410] The server sends the generated control scenario to the terminal and each piece of equipment in the home, prompting them to perform specific actions. This causes the equipment to adjust the environment according to the instructions from the server. For example, the audio system might play a specified song, or the lighting system might adjust to the specified color and brightness.

[0411] Step 5:

[0412] Users can experience an environment controlled by an emotion engine and provide feedback to the server. This feedback is then incorporated into subsequent scenario generation, resulting in even more personalized control. Specifically, users provide feedback to the system by inputting instructions such as "I'd like the lighting to be a little brighter" to their device.

[0413] (Application Example 2)

[0414] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0415] In modern urban spaces, actively adapting public facilities and living environments to the emotional states of users is crucial for improving the quality of life for residents. However, coordinating devices and systems from different manufacturers is difficult, making dynamic adjustments to the environment based on user emotions challenging. Therefore, there is a need for a system that can analyze users' emotional states in real time and adjust the environment accordingly to the optimal setting.

[0416] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0417] In this invention, the server includes means for interpreting user instructions and transmitting signals to the corresponding devices, means for analyzing usage data collected from devices in apartment buildings or urban spaces to generate automation scenarios, and means for analyzing user emotional data and dynamically adjusting the public environment and device status in the urban space. This makes it possible to integrally manage devices and systems from different manufacturers, and easily realize individualized responses and optimal environmental adjustments based on user emotions.

[0418] An "information processing device" is a computer system that collects, analyzes, and controls data, and enables communication between devices.

[0419] A "user" is a human interface that transmits instructions and provides emotional data through an information processing device.

[0420] A "device" is hardware installed in a home or urban space that has functions such as lighting, entertainment systems, or other functions.

[0421] "Emotional data" refers to information that represents the user's emotional state, and is composed of information such as facial expressions, voice tone, and behavioral patterns.

[0422] An "automation scenario" is a set of pre-configured procedures that define and execute the optimal operation of a device based on user instructions and emotional data.

[0423] "Power consumption" refers to the amount of electricity required for a device to function, and is a measure of energy efficiency.

[0424] A "safety sensor" is a security device that detects abnormal conditions in equipment or the environment and notifies an information processing device.

[0425] "Public environment" refers to the physical and functional settings of publicly used spaces in urban areas, such as parks, libraries, and streets.

[0426] This invention relates to a system centered on an information processing device for dynamically adjusting the environment based on the user's emotional state. In this system, a server plays a central role in comprehensively managing various devices.

[0427] The server receives emotional data sent by users and analyzes it in real time. This analysis utilizes cloud-based facial recognition technology and software that acts as a voice sensor. Specifically, it uses APIs such as Google Cloud Vision and AWS Rekognition to identify emotions based on the user's facial expressions and voice tone.

[0428] Based on the analyzed emotional data, the server constructs an automated scenario. This scenario includes optimal device operation procedures that take into account the user's current emotional state. For example, if the server determines that the user is relaxed while strolling through a park, it sends a command to the relevant device via the smartphone to play soothing music through earphones and adjust the streetlights to a softer color tone.

[0429] As a concrete example, when sending a prompt to a generative AI model, it might be used in the form of, "Could you suggest background music that will help enhance a user's relaxed emotional state while walking through a public park, considering the current time of day and weather conditions?" This prompt is used by the generative AI model to select content appropriate to the user's state.

[0430] As described above, personalized services and adjustments tailored to the user's emotional needs can be provided through an automated system. This system can be widely applied in both urban spaces and homes.

[0431] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0432] Step 1:

[0433] The device captures the user's facial expressions and voice data and sends it to the server. Input is real-time data from the camera and microphone, which is converted into image and audio formats as needed. Output is sent to the server as a data stream.

[0434] Step 2:

[0435] The server analyzes the emotional data it receives. The input consists of facial expressions and voice data sent from the terminal. For data processing, APIs such as Google Cloud Vision and AWS Rekognition are used to output the user's emotional state as text or numerical data.

[0436] Step 3:

[0437] The server generates automated scenarios based on the analysis results. The input is information on the analyzed emotional state. As a data calculation, it combines existing scenario templates with the analysis results to select a scenario appropriate to the user's state and converts it into device control commands. The output is sent to each device as specific control commands.

[0438] Step 4:

[0439] The server sends control commands to the devices, causing them to make configuration changes and provide data on-site. The input consists of automated control commands, which are transmitted to each device using a communication protocol. The output is perceived by the user as changes in the operation of the corresponding devices or as new information provided.

[0440] Step 5:

[0441] The system receives environmental changes and information services provided to the user. Input consists of physical changes and information from the device. If the user provides feedback through the terminal, this information is also sent to the server and used to adjust scenarios for future use. Output is achieved as improvements in user comfort and satisfaction.

[0442] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0443] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0444] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0445] [Third Embodiment]

[0446] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0447] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0448] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0449] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0450] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0451] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0452] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0453] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0454] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0455] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0456] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0457] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0458] The present invention is a system for integrating and controlling multiple devices from different manufacturers, and details of its embodiments are described below.

[0459] Overall structure

[0460] This system is comprised of three main components: a server, terminals, and users. The server plays a central role in controlling the entire system, while the terminals provide the user interface. Users use these to operate the equipment.

[0461] Integrated management of equipment

[0462] The server provides comprehensive management for various devices within the home. Even if the devices are from different manufacturers, the server integrates their respective communication protocols and control methods, enabling centralized control.

[0463] For example, a server can communicate with various devices through adapters that support different protocols, and then convert that communication into a standardized instruction set, allowing it to operate different devices simultaneously.

[0464] Voice and chat-based operation

[0465] The terminal accepts voice commands and chat input from the user. Voice commands are processed by the terminal using natural language processing and converted into text. These textualized commands are then forwarded to the server and executed.

[0466] As a concrete example, if a user gives a voice command saying, "Turn on the living room lights," the terminal analyzes the voice, generates a command, and sends it to the server. The server then sends a signal with the appropriate protocol to the lighting device, turning on the lights.

[0467] Learning and implementing automation scenarios

[0468] The server can analyze user usage history and schedules to generate optimized automation scenarios for each user. This allows users to automate many tasks in their daily lives without even realizing it.

[0469] For example, the server learns a pattern in which a user uses a coffee maker every morning and automatically activates the coffee maker at a specified time.

[0470] Optimizing energy efficiency

[0471] The server monitors the power consumption of the equipment and, based on the analysis results, notifies the user of suggestions that can lead to energy savings. For example, if an air conditioner has been running continuously for a long period of time, the server will suggest switching to eco mode to reduce power consumption.

[0472] Security monitoring function

[0473] The server receives information from security devices inside and outside the home and has the function to immediately notify the user of any anomalies it detects. For example, if unauthorized access is detected in the middle of the night, the server will issue an alarm and send a push notification to the user's device.

[0474] In this way, the present invention provides a system for effectively integrating and managing household appliances in order to improve user convenience, safety, and energy efficiency.

[0475] The following describes the processing flow.

[0476] Step 1:

[0477] The user sends instructions to the device they want to control via voice or chat. For example, they might say, "Turn on the living room lights."

[0478] Step 2:

[0479] The terminal converts the received voice commands into text using natural language processing technology and prepares to send it to the server. At this time, it verifies that the user's command is related to a specific device.

[0480] Step 3:

[0481] The server analyzes the text commands received from the terminal and identifies the operation instructions corresponding to the specific device. The server then verifies that these instructions conform to the protocol of the associated device.

[0482] Step 4:

[0483] The server sends signals to the target device based on the analyzed instructions, executing the desired operation (e.g., turning on the lights). The destination device is centrally controlled by an integrated management system, regardless of the manufacturer.

[0484] Step 5:

[0485] The server receives feedback from the device to confirm that the operation was successful. If feedback is received, the server proceeds to the next step. If no feedback is received, error handling is performed.

[0486] Step 6:

[0487] The server notifies the terminal that the operation was performed correctly. The terminal notifies the user of the success message, either visually or audibly.

[0488] Step 7:

[0489] The user can confirm the success of the operation through the terminal and then perform other operations or give new instructions. If no further instructions are given, the system returns to standby mode.

[0490] (Example 1)

[0491] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0492] Currently, various devices from different manufacturers used in homes have their own unique communication protocols and control methods, making integrated control difficult. Furthermore, ensuring user-friendly operation while efficiently consuming energy and maintaining safety are further challenges. To address this, an integrated management system is needed that centrally manages multiple devices and improves user experience.

[0493] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0494] In this invention, the server includes means for interpreting voice instructions or text input from a user using natural language processing technology and transmitting standardized commands to the corresponding device; means for analyzing natural language prompt sentences using a generated artificial intelligence model and converting them into control commands for the device; and means for analyzing operational data collected from devices in the home and generating automated operation procedures optimized for the user. This makes it possible to comprehensively control devices from different manufacturers and simultaneously provide efficient energy management and high convenience.

[0495] "Information processing equipment" is a general term for electronic devices used for data processing and communication.

[0496] "Natural language processing technology" is a technology that processes human knowledge about language on a computer, and includes functions for understanding and generating speech and text.

[0497] An "artificial intelligence model" is a statistical model that uses machine learning algorithms to automate specific tasks and is capable of self-improvement without relying on human knowledge.

[0498] A "prompt statement" is a sentence entered into an artificial intelligence model to give it instructions, and it functions as a trigger for the model to make an appropriate response or process.

[0499] "Operational data" refers to a collection of information generated when various devices in a household are in operation, including data such as usage status and energy consumption.

[0500] An "automated operation procedure" refers to a set of steps that a device performs automatically based on pre-set rules and conditions, without user intervention.

[0501] A "standardized command" is a unified command format designed to ensure compatibility between different devices, and is essential for a server to correctly control each device.

[0502] An "integrated management system" is a system for centrally controlling or monitoring multiple devices, and serves as a platform to improve user convenience and efficiency.

[0503] This invention is a system using an information processing device for the integrated management of household electrical appliances from different manufacturers. Users can operate the terminal via voice or text to efficiently control appliances within their home. The terminal receives user instructions, analyzes the input data using natural language processing technology, and extracts appropriate control commands from the prompt text using a generative AI model.

[0504] The terminal receives voice commands and text messages from the user and converts them into text data. The natural language processing technology used here consists of advanced software modules that perform speech recognition and text analysis. This analyzed data is then converted into a command format and sent to the server.

[0505] The server analyzes the commands received from the terminal and sends standardized commands to the target device. The server uses an internal database to check the protocol of each device and generates appropriate commands. In this process, a generative AI model plays a crucial role in accurately converting prompt statements into commands.

[0506] For example, if a user gives a voice command such as "Turn on the living room lights," the terminal converts this voice into text and sends the prompt "Turn on the lights" to the server. The server analyzes the received prompt and sends the appropriate control signal to the living room lighting fixture to turn on the lights.

[0507] Examples of prompt statements include the following:

[0508] "Turn off the air conditioner."

[0509] "Open the curtains at 7 AM."

[0510] "Turn off all the electricity at once."

[0511] In this way, the system can execute user instructions quickly and accurately, improving convenience and efficiency within the home. The coordinated operation of the server and terminals ensures a consistent user experience.

[0512] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0513] Step 1:

[0514] The user provides voice commands or text input to the device. This input includes voice commands such as "Turn on the air conditioner" or chat messages. The device receives this as voice or text data.

[0515] Step 2:

[0516] The terminal converts the received audio data into text using natural language processing technology. Specifically, a speech recognition module analyzes the audio waveform and outputs the text data "Turn on the air conditioner." Here, a generative AI model analyzes the meaning of the audio and converts it into a standardized command.

[0517] Step 3:

[0518] The terminal generates a prompt message from the text command obtained through natural language processing. This prompt message (e.g., "Turn on the air conditioner") is sent to the server.

[0519] Step 4:

[0520] The server parses the received prompt message and performs protocol translation for device identification and control. Here, it refers to the server's internal database to identify the device ID and communication protocol for the "air conditioner".

[0521] Step 5:

[0522] The server sends appropriately generated, standardized commands to the corresponding device. The specific signals are sent over the network to the air conditioner, causing it to start. The output is that the air conditioner is operating.

[0523] Step 6:

[0524] The server monitors the device's response and, once normal operation is confirmed, sends a completion notification to the user's terminal. For example, a message such as "Air conditioner turned on" might appear on the user's smartphone.

[0525] This series of processes allows users to efficiently control devices within their home via voice or text.

[0526] (Application Example 1)

[0527] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0528] In urban environments where equipment from different manufacturers coexists, there is a need to efficiently manage public infrastructure and provide consistent control and information to users. Energy efficiency and enhanced security are also crucial challenges.

[0529] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0530] In this invention, the server includes means for analyzing user instructions and transmitting signals to the corresponding devices, means for acquiring public infrastructure data and providing traffic and security information to users, and means for analyzing usage data and generating automated control scenarios. This enables integrated management of devices from different manufacturers in urban environments, leading to improved energy efficiency and information provision to users.

[0531] A "device" is a hardware component designed to perform a specific function or role.

[0532] A "user" is the entity that operates and utilizes a device or system.

[0533] "Infrastructure data" refers to information regarding the operational status of public facilities and systems in urban environments.

[0534] "Traffic information" refers to data including congestion, delays, and service status of public transportation and roads.

[0535] "Security information" refers to data regarding anomalies and safety issues monitored by security-related systems.

[0536] "Energy consumption" refers to the total amount of electricity and resources consumed when a device is in operation.

[0537] An "automated control scenario" is a set of procedures designed to operate a device or system automatically according to time and circumstances.

[0538] The system for carrying out this invention aims to integrate and control devices from different manufacturers. A typical embodiment is described in detail below.

[0539] The server plays a central role in controlling the entire system. Specifically, it uses speech recognition software and natural language processing engines to receive instructions from users, and sends the analyzed content as commands to the appropriate devices. In this process, it utilizes information services such as the Google Maps API to collect traffic information and energy consumption data.

[0540] The terminal uses smartphone applications or wearable device interfaces as its user interface. The terminal acquires public infrastructure data and displays traffic and security information required by the user. It also receives user voice commands via the terminal and transmits them to a server.

[0541] Users can interact with the interface using the terminal to obtain necessary information and control devices. For example, a user can enter a prompt such as "Suggest an alternative route for the delayed train" into the terminal and receive an immediate suggestion. This can greatly improve the convenience of life in urban environments.

[0542] In this way, seamless management between different devices and efficient support for urban life can be achieved by incorporating generative AI models.

[0543] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0544] Step 1:

[0545] The server receives voice or text instructions from the user via the terminal. The input is the prompt text entered by the user on the terminal. The server analyzes this input using speech recognition software and a natural language processing engine, converting it into standardized commands. The output is the analyzed commands.

[0546] Step 2:

[0547] The server uses the parsed command to check information about the relevant devices and systems. For example, in the case of traffic information, it uses the Google Maps API to obtain real-time data. The input is the parsed command and the endpoint of the relevant API. Data processing involves extracting the necessary information from the API. The output is specific instruction data to be sent to the device or system.

[0548] Step 3:

[0549] The server generates appropriate control signals based on the acquired information and transmits them to each device according to the instructions. The input is instruction data, and the output is the control signal to the controlled device. In this process, the server uses a standard protocol that is independent of the manufacturer of each device.

[0550] Step 4:

[0551] The server uses a generative AI model to generate optimal control scenarios based on user requests. Inputs include past user behavior data and system states. The data calculation involves analyzing behavioral patterns and generating scenarios based on these analyses. The output is a control scenario based on future predictions.

[0552] Step 5:

[0553] The terminal receives the final results and suggestions from the server and provides visual or audible feedback to the user. Input is the suggestions and information sent from the server. The terminal converts this into a user-friendly format and displays it. Output is the content of the interface provided to the user.

[0554] In this way, users can obtain information in real time and perform remote operations.

[0555] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0556] The present invention is a system for integrating and controlling multiple devices and emotion engines from different manufacturers, and its embodiments are described in detail below.

[0557] Overall structure

[0558] The system includes three main components: a server, a terminal, and a user, in addition to an emotion engine. The server manages the entire system, while the terminal acts as the interface between the user and the system. Users send instructions to the system through the terminal. The emotion engine is responsible for recognizing the user's emotions and reflecting them in the system's operation.

[0559] The function of the emotional engine

[0560] The device acquires the user's facial expressions, voice tone, language patterns, and other data through an emotion engine. This data is used by the system to recognize and respond to the user's emotional state in real time.

[0561] For example, if the emotion engine analyzes that the user is feeling stressed, the system can automatically play relaxing music and adjust the lighting to warmer tones.

[0562] Integrated device management and emotional reflection

[0563] The server monitors devices within the home and controls them integrally based on instructions. Based on sentiment data from the user, the server creates and executes optimal device operation scenarios.

[0564] For example, when the emotion engine recognizes that the user is in a happy mood, the server can activate the entertainment system, adjust the lighting to create a cheerful atmosphere.

[0565] Automation and personalized support

[0566] The server collects and analyzes user emotional data to generate personalized automated scenarios. This process works in conjunction with normal lifestyle habit learning to provide an experience adapted to the user's emotions.

[0567] For example, if the emotion engine detects fatigue when a user returns home from work, it will automatically adjust the room temperature to a comfortable level and implement measures to provide a calming environment.

[0568] Energy and security integration

[0569] The server monitors the device's power consumption in real time, and when the emotion engine detects the user's tension or anxiety, it switches from energy-saving mode to normal mode to provide a sense of security.

[0570] Regarding security features, we provide notifications and feedback that respond to the user's emotions, ensuring safety in the most appropriate way for the user by providing emotion-based information.

[0571] Thus, the present invention provides a system that manages the home environment comfortably and effectively based on the user's emotions.

[0572] The following describes the processing flow.

[0573] Step 1:

[0574] The user activates their device to utilize the emotion engine and initiates emotional input feedback as needed. This allows the emotion engine to acquire the user's state in real time.

[0575] Step 2:

[0576] The device collects emotional data in a non-invasive way, such as the user's facial expressions and tone of voice. This data is sent to an emotion engine, where it is analyzed to understand the user's emotional state.

[0577] Step 3:

[0578] The emotion engine analyzes the acquired data to identify the user's current emotional state. For example, consider a scenario where the system determines that the user is stressed.

[0579] Step 4:

[0580] The server receives the sentiment analysis results from the emotion engine and determines the optimal automation scenario based on them. For example, it might suggest relaxing lighting and music to a user experiencing stress.

[0581] Step 5:

[0582] The server sends appropriate instructions to devices in the home according to the determined automation scenario. For example, it might instruct devices to lower the color temperature of the lights or play music.

[0583] Step 6:

[0584] The device receives instructions from the server and provides feedback to the user. It notifies the user that the instructions have been carried out and asks if the user wishes to make further adjustments through interaction with the emotion engine.

[0585] Step 7:

[0586] Users help the system adapt further by reviewing feedback and instructing on additional adjustments as needed. At this stage, if there are new requests, the server and emotion engine processes are restarted.

[0587] (Example 2)

[0588] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0589] Modern homes and offices contain a wide variety of equipment from different manufacturers, creating a need for efficient systems to integrate and control them. Furthermore, it's crucial to provide a more comfortable and personalized environment by reflecting and adapting to the user's emotional state. However, few existing systems meet these complex requirements, and they often suffer from cumbersome management.

[0590] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0591] In this invention, the server includes means for interpreting instructions from users and transmitting signals to the corresponding equipment; means for analyzing usage data collected from equipment within a living space and generating automation scenarios; and means for analyzing the user's emotional state using an emotion recognition engine and optimizing the operation of the equipment based on that data. This enables integrated control of the equipment and the provision of a personalized environment.

[0592] "Equipment" refers to various devices and home appliances used in homes and offices.

[0593] A "data processing device" refers to a device or system for handling, analyzing, and controlling information.

[0594] "User" refers to a person who operates or uses this system.

[0595] "Instructions" refer to the operations or requests that users make to the system.

[0596] A "signal" refers to electrical or electronic communication information that a system transmits to equipment.

[0597] An "emotion recognition engine" refers to software or system functionality used to detect and analyze a user's emotional state.

[0598] "Optimizing operations" refers to adjusting equipment to function most efficiently based on the user's circumstances and feelings.

[0599] "Living space" refers to the place where users live, that is, the interior of a home or office.

[0600] An "automation scenario" refers to a set of operating procedures for equipment, generated by the system based on pre-set conditions.

[0601] This invention is a system that integrates and controls multiple pieces of equipment from different manufacturers, optimizing the environment based on user emotions.

[0602] System Configuration

[0603] The system primarily consists of a server, terminals, and users, and uses an emotion recognition engine to coordinate its overall operation. The server acts as a data processing unit, analyzing emotion data collected via the terminals. Users can give instructions to the system and control the operation of the equipment through their terminals.

[0604] Hardware and software

[0605] The server acts as a data processing unit, mediating communication with multiple devices and executing control scenarios. This includes software for monitoring energy consumption and detecting anomalies.

[0606] The device uses sensors and microphones to capture the user's facial expressions and voice tone, and transmits this data to the emotion recognition engine.

[0607] The emotion recognition engine uses a generative AI model to analyze data sent from the device and identify the user's emotional state.

[0608] Specific example

[0609] For example, when a user returns home, the device detects their facial expressions and tone of voice, and the emotion recognition engine detects "fatigue." Based on this data, the server controls the equipment to play relaxing music and adjust the lighting to calming colors.

[0610] Example of a prompt

[0611] An example of a prompt message is, "Please configure the settings so that the user can relax in the living room."

[0612] This invention makes it easier to adjust the home environment based on the user's emotions, thereby improving the quality of life.

[0613] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0614] Step 1:

[0615] The device uses sensors and a microphone to detect the user's facial expressions, voice tone, and language patterns. This data serves as input to identify the user's emotional state. The collected data is sent to an emotion recognition engine. Specific actions include the device taking a picture of the user's face with its camera and recording their voice with its microphone.

[0616] Step 2:

[0617] The server receives data sent from the terminal and performs data analysis using an AI model generated by the emotion recognition engine. This analysis identifies the user's emotional state (e.g., "relaxed," "stressed," etc.). This process includes facial expression analysis and voice analysis, and outputs an emotion recognition pattern.

[0618] Step 3:

[0619] The server generates an optimal control scenario tailored to the user's emotions, based on the output from the emotion recognition engine. Emotional state data is used as input, and specific instructions for controlling household equipment are generated as output. For example, the server might generate instructions to adjust lighting or play relaxing music.

[0620] Step 4:

[0621] The server sends the generated control scenario to the terminal and each piece of equipment in the home, prompting them to perform specific actions. This causes the equipment to adjust the environment according to the instructions from the server. For example, the audio system might play a specified song, or the lighting system might adjust to the specified color and brightness.

[0622] Step 5:

[0623] Users can experience an environment controlled by an emotion engine and provide feedback to the server. This feedback is then incorporated into subsequent scenario generation, resulting in even more personalized control. Specifically, users provide feedback to the system by inputting instructions such as "I'd like the lighting to be a little brighter" to their device.

[0624] (Application Example 2)

[0625] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0626] In modern urban spaces, actively adapting public facilities and living environments to the emotional states of users is crucial for improving the quality of life for residents. However, coordinating devices and systems from different manufacturers is difficult, making dynamic adjustments to the environment based on user emotions challenging. Therefore, there is a need for a system that can analyze users' emotional states in real time and adjust the environment accordingly to the optimal setting.

[0627] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0628] In this invention, the server includes means for interpreting user instructions and transmitting signals to the corresponding devices, means for analyzing usage data collected from devices in apartment buildings or urban spaces to generate automation scenarios, and means for analyzing user emotional data and dynamically adjusting the public environment and device status in the urban space. This makes it possible to integrally manage devices and systems from different manufacturers, and easily realize individualized responses and optimal environmental adjustments based on user emotions.

[0629] An "information processing device" is a computer system that collects, analyzes, and controls data, and enables communication between devices.

[0630] A "user" is a human interface that transmits instructions and provides emotional data through an information processing device.

[0631] A "device" is hardware installed in a home or urban space that has functions such as lighting, entertainment systems, or other functions.

[0632] "Emotional data" refers to information that represents the user's emotional state, and is composed of information such as facial expressions, voice tone, and behavioral patterns.

[0633] An "automation scenario" is a set of pre-configured procedures that define and execute the optimal operation of a device based on user instructions and emotional data.

[0634] "Power consumption" refers to the amount of electricity required for a device to function, and is a measure of energy efficiency.

[0635] A "safety sensor" is a security device that detects abnormal conditions in equipment or the environment and notifies an information processing device.

[0636] "Public environment" refers to the physical and functional settings of publicly used spaces in urban areas, such as parks, libraries, and streets.

[0637] This invention relates to a system centered on an information processing device for dynamically adjusting the environment based on the user's emotional state. In this system, a server plays a central role in comprehensively managing various devices.

[0638] The server receives emotional data sent by users and analyzes it in real time. This analysis utilizes cloud-based facial recognition technology and software that acts as a voice sensor. Specifically, it uses APIs such as Google Cloud Vision and AWS Rekognition to identify emotions based on the user's facial expressions and voice tone.

[0639] Based on the analyzed emotional data, the server constructs an automated scenario. This scenario includes optimal device operation procedures that take into account the user's current emotional state. For example, if the server determines that the user is relaxed while strolling through a park, it sends a command to the relevant device via the smartphone to play soothing music through earphones and adjust the streetlights to a softer color tone.

[0640] As a concrete example, when sending a prompt to a generative AI model, it might be used in the form of, "Could you suggest background music that will help enhance a user's relaxed emotional state while walking through a public park, considering the current time of day and weather conditions?" This prompt is used by the generative AI model to select content appropriate to the user's state.

[0641] As described above, personalized services and adjustments tailored to the user's emotional needs can be provided through an automated system. This system can be widely applied in both urban spaces and homes.

[0642] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0643] Step 1:

[0644] The device captures the user's facial expressions and voice data and sends it to the server. Input is real-time data from the camera and microphone, which is converted into image and audio formats as needed. Output is sent to the server as a data stream.

[0645] Step 2:

[0646] The server analyzes the emotional data it receives. The input consists of facial expressions and voice data sent from the terminal. For data processing, APIs such as Google Cloud Vision and AWS Rekognition are used to output the user's emotional state as text or numerical data.

[0647] Step 3:

[0648] The server generates automated scenarios based on the analysis results. The input is information on the analyzed emotional state. As a data calculation, it combines existing scenario templates with the analysis results to select a scenario appropriate to the user's state and converts it into device control commands. The output is sent to each device as specific control commands.

[0649] Step 4:

[0650] The server sends control commands to the devices, causing them to make configuration changes and provide data on-site. The input consists of automated control commands, which are transmitted to each device using a communication protocol. The output is perceived by the user as changes in the operation of the corresponding devices or as new information provided.

[0651] Step 5:

[0652] The system receives environmental changes and information services provided to the user. Input consists of physical changes and information from the device. If the user provides feedback through the terminal, this information is also sent to the server and used to adjust scenarios for future use. Output is achieved as improvements in user comfort and satisfaction.

[0653] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0654] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0655] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0656] [Fourth Embodiment]

[0657] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0658] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0659] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0660] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0661] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0662] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0663] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0664] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0665] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0666] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0667] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0668] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0669] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0670] The present invention is a system for integrating and controlling multiple devices from different manufacturers, and details of its embodiments are described below.

[0671] Overall structure

[0672] This system is comprised of three main components: a server, terminals, and users. The server plays a central role in controlling the entire system, while the terminals provide the user interface. Users use these to operate the equipment.

[0673] Integrated management of equipment

[0674] The server provides comprehensive management for various devices within the home. Even if the devices are from different manufacturers, the server integrates their respective communication protocols and control methods, enabling centralized control.

[0675] For example, a server can communicate with various devices through adapters that support different protocols, and then convert that communication into a standardized instruction set, allowing it to operate different devices simultaneously.

[0676] Voice and chat-based operation

[0677] The terminal accepts voice commands and chat input from the user. Voice commands are processed by the terminal using natural language processing and converted into text. These textualized commands are then forwarded to the server and executed.

[0678] As a concrete example, if a user gives a voice command saying, "Turn on the living room lights," the terminal analyzes the voice, generates a command, and sends it to the server. The server then sends a signal with the appropriate protocol to the lighting device, turning on the lights.

[0679] Learning and implementing automation scenarios

[0680] The server can analyze user usage history and schedules to generate optimized automation scenarios for each user. This allows users to automate many tasks in their daily lives without even realizing it.

[0681] For example, the server learns a pattern in which a user uses a coffee maker every morning and automatically activates the coffee maker at a specified time.

[0682] Optimizing energy efficiency

[0683] The server monitors the power consumption of the equipment and, based on the analysis results, notifies the user of suggestions that can lead to energy savings. For example, if an air conditioner has been running continuously for a long period of time, the server will suggest switching to eco mode to reduce power consumption.

[0684] Security monitoring function

[0685] The server receives information from security devices inside and outside the home and has the function to immediately notify the user of any anomalies it detects. For example, if unauthorized access is detected in the middle of the night, the server will issue an alarm and send a push notification to the user's device.

[0686] In this way, the present invention provides a system for effectively integrating and managing household appliances in order to improve user convenience, safety, and energy efficiency.

[0687] The following describes the processing flow.

[0688] Step 1:

[0689] The user sends instructions to the device they want to control via voice or chat. For example, they might say, "Turn on the living room lights."

[0690] Step 2:

[0691] The terminal converts the received voice commands into text using natural language processing technology and prepares to send it to the server. At this time, it verifies that the user's command is related to a specific device.

[0692] Step 3:

[0693] The server analyzes the text commands received from the terminal and identifies the operation instructions corresponding to the specific device. The server then verifies that these instructions conform to the protocol of the associated device.

[0694] Step 4:

[0695] The server sends signals to the target device based on the analyzed instructions, executing the desired operation (e.g., turning on the lights). The destination device is centrally controlled by an integrated management system, regardless of the manufacturer.

[0696] Step 5:

[0697] The server receives feedback from the device to confirm that the operation was successful. If feedback is received, the server proceeds to the next step. If no feedback is received, error handling is performed.

[0698] Step 6:

[0699] The server notifies the terminal that the operation was performed correctly. The terminal notifies the user of the success message, either visually or audibly.

[0700] Step 7:

[0701] The user can confirm the success of the operation through the terminal and then perform other operations or give new instructions. If no further instructions are given, the system returns to standby mode.

[0702] (Example 1)

[0703] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0704] Currently, various devices from different manufacturers used in homes have their own unique communication protocols and control methods, making integrated control difficult. Furthermore, ensuring user-friendly operation while efficiently consuming energy and maintaining safety are further challenges. To address this, an integrated management system is needed that centrally manages multiple devices and improves user experience.

[0705] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0706] In this invention, the server includes means for interpreting voice instructions or text input from a user using natural language processing technology and transmitting standardized commands to the corresponding device; means for analyzing natural language prompt sentences using a generated artificial intelligence model and converting them into control commands for the device; and means for analyzing operational data collected from devices in the home and generating automated operation procedures optimized for the user. This makes it possible to comprehensively control devices from different manufacturers and simultaneously provide efficient energy management and high convenience.

[0707] "Information processing equipment" is a general term for electronic devices used for data processing and communication.

[0708] "Natural language processing technology" is a technology that processes human knowledge about language on a computer, and includes functions for understanding and generating speech and text.

[0709] An "artificial intelligence model" is a statistical model that uses machine learning algorithms to automate specific tasks and is capable of self-improvement without relying on human knowledge.

[0710] A "prompt statement" is a sentence entered into an artificial intelligence model to give it instructions, and it functions as a trigger for the model to make an appropriate response or process.

[0711] "Operational data" refers to a collection of information generated when various devices in a household are in operation, including data such as usage status and energy consumption.

[0712] An "automated operation procedure" refers to a set of steps that a device performs automatically based on pre-set rules and conditions, without user intervention.

[0713] A "standardized command" is a unified command format designed to ensure compatibility between different devices, and is essential for a server to correctly control each device.

[0714] An "integrated management system" is a system for centrally controlling or monitoring multiple devices, and serves as a platform to improve user convenience and efficiency.

[0715] This invention is a system using an information processing device for the integrated management of household electrical appliances from different manufacturers. Users can operate the terminal via voice or text to efficiently control appliances within their home. The terminal receives user instructions, analyzes the input data using natural language processing technology, and extracts appropriate control commands from the prompt text using a generative AI model.

[0716] The terminal receives voice commands and text messages from the user and converts them into text data. The natural language processing technology used here consists of advanced software modules that perform speech recognition and text analysis. This analyzed data is then converted into a command format and sent to the server.

[0717] The server analyzes the commands received from the terminal and sends standardized commands to the target device. The server uses an internal database to check the protocol of each device and generates appropriate commands. In this process, a generative AI model plays a crucial role in accurately converting prompt statements into commands.

[0718] For example, if a user gives a voice command such as "Turn on the living room lights," the terminal converts this voice into text and sends the prompt "Turn on the lights" to the server. The server analyzes the received prompt and sends the appropriate control signal to the living room lighting fixture to turn on the lights.

[0719] Examples of prompt statements include the following:

[0720] "Turn off the air conditioner."

[0721] "Open the curtains at 7 AM."

[0722] "Turn off all the electricity at once."

[0723] In this way, the system can execute user instructions quickly and accurately, improving convenience and efficiency within the home. The coordinated operation of the server and terminals ensures a consistent user experience.

[0724] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0725] Step 1:

[0726] The user provides voice commands or text input to the device. This input includes voice commands such as "Turn on the air conditioner" or chat messages. The device receives this as voice or text data.

[0727] Step 2:

[0728] The terminal converts the received audio data into text using natural language processing technology. Specifically, a speech recognition module analyzes the audio waveform and outputs the text data "Turn on the air conditioner." Here, a generative AI model analyzes the meaning of the audio and converts it into a standardized command.

[0729] Step 3:

[0730] The terminal generates a prompt message from the text command obtained through natural language processing. This prompt message (e.g., "Turn on the air conditioner") is sent to the server.

[0731] Step 4:

[0732] The server parses the received prompt message and performs protocol translation for device identification and control. Here, it refers to the server's internal database to identify the device ID and communication protocol for the "air conditioner".

[0733] Step 5:

[0734] The server sends appropriately generated, standardized commands to the corresponding device. The specific signals are sent over the network to the air conditioner, causing it to start. The output is that the air conditioner is operating.

[0735] Step 6:

[0736] The server monitors the device's response and, once normal operation is confirmed, sends a completion notification to the user's terminal. For example, a message such as "Air conditioner turned on" might appear on the user's smartphone.

[0737] This series of processes allows users to efficiently control devices within their home via voice or text.

[0738] (Application Example 1)

[0739] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0740] In urban environments where equipment from different manufacturers coexists, there is a need to efficiently manage public infrastructure and provide consistent control and information to users. Energy efficiency and enhanced security are also crucial challenges.

[0741] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0742] In this invention, the server includes means for analyzing user instructions and transmitting signals to the corresponding devices, means for acquiring public infrastructure data and providing traffic and security information to users, and means for analyzing usage data and generating automated control scenarios. This enables integrated management of devices from different manufacturers in urban environments, leading to improved energy efficiency and information provision to users.

[0743] A "device" is a hardware component designed to perform a specific function or role.

[0744] A "user" is the entity that operates and utilizes a device or system.

[0745] "Infrastructure data" refers to information regarding the operational status of public facilities and systems in urban environments.

[0746] "Traffic information" refers to data including congestion, delays, and service status of public transportation and roads.

[0747] "Security information" refers to data regarding anomalies and safety issues monitored by security-related systems.

[0748] "Energy consumption" refers to the total amount of electricity and resources consumed when a device is in operation.

[0749] An "automated control scenario" is a set of procedures designed to operate a device or system automatically according to time and circumstances.

[0750] The system for carrying out this invention aims to integrate and control devices from different manufacturers. A typical embodiment is described in detail below.

[0751] The server plays a central role in controlling the entire system. Specifically, it uses speech recognition software and natural language processing engines to receive instructions from users, and sends the analyzed content as commands to the appropriate devices. In this process, it utilizes information services such as the Google Maps API to collect traffic information and energy consumption data.

[0752] The terminal uses smartphone applications or wearable device interfaces as its user interface. The terminal acquires public infrastructure data and displays traffic and security information required by the user. It also receives user voice commands via the terminal and transmits them to a server.

[0753] Users can interact with the interface using the terminal to obtain necessary information and control devices. For example, a user can enter a prompt such as "Suggest an alternative route for the delayed train" into the terminal and receive an immediate suggestion. This can greatly improve the convenience of life in urban environments.

[0754] In this way, seamless management between different devices and efficient support for urban life can be achieved by incorporating generative AI models.

[0755] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0756] Step 1:

[0757] The server receives voice or text instructions from the user via the terminal. The input is the prompt text entered by the user on the terminal. The server analyzes this input using speech recognition software and a natural language processing engine, converting it into standardized commands. The output is the analyzed commands.

[0758] Step 2:

[0759] The server uses the parsed command to check information about the relevant devices and systems. For example, in the case of traffic information, it uses the Google Maps API to obtain real-time data. The input is the parsed command and the endpoint of the relevant API. Data processing involves extracting the necessary information from the API. The output is specific instruction data to be sent to the device or system.

[0760] Step 3:

[0761] The server generates appropriate control signals based on the acquired information and transmits them to each device according to the instructions. The input is instruction data, and the output is the control signal to the controlled device. In this process, the server uses a standard protocol that is independent of the manufacturer of each device.

[0762] Step 4:

[0763] The server uses a generative AI model to generate optimal control scenarios based on user requests. Inputs include past user behavior data and system states. The data calculation involves analyzing behavioral patterns and generating scenarios based on these analyses. The output is a control scenario based on future predictions.

[0764] Step 5:

[0765] The terminal receives the final results and suggestions from the server and provides visual or audible feedback to the user. Input is the suggestions and information sent from the server. The terminal converts this into a user-friendly format and displays it. Output is the content of the interface provided to the user.

[0766] In this way, users can obtain information in real time and perform remote operations.

[0767] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0768] The present invention is a system for integrating and controlling multiple devices and emotion engines from different manufacturers, and its embodiments are described in detail below.

[0769] Overall structure

[0770] The system includes three main components: a server, a terminal, and a user, in addition to an emotion engine. The server manages the entire system, while the terminal acts as the interface between the user and the system. Users send instructions to the system through the terminal. The emotion engine is responsible for recognizing the user's emotions and reflecting them in the system's operation.

[0771] The function of the emotional engine

[0772] The device acquires the user's facial expressions, voice tone, language patterns, and other data through an emotion engine. This data is used by the system to recognize and respond to the user's emotional state in real time.

[0773] For example, if the emotion engine analyzes that the user is feeling stressed, the system can automatically play relaxing music and adjust the lighting to warmer tones.

[0774] Integrated device management and emotional reflection

[0775] The server monitors devices within the home and controls them integrally based on instructions. Based on sentiment data from the user, the server creates and executes optimal device operation scenarios.

[0776] For example, when the emotion engine recognizes that the user is in a happy mood, the server can activate the entertainment system, adjust the lighting to create a cheerful atmosphere.

[0777] Automation and personalized support

[0778] The server collects and analyzes user emotional data to generate personalized automated scenarios. This process works in conjunction with normal lifestyle habit learning to provide an experience adapted to the user's emotions.

[0779] For example, if the emotion engine detects fatigue when a user returns home from work, it will automatically adjust the room temperature to a comfortable level and implement measures to provide a calming environment.

[0780] Energy and security integration

[0781] The server monitors the device's power consumption in real time, and when the emotion engine detects the user's tension or anxiety, it switches from energy-saving mode to normal mode to provide a sense of security.

[0782] Regarding security features, we provide notifications and feedback that respond to the user's emotions, ensuring safety in the most appropriate way for the user by providing emotion-based information.

[0783] Thus, the present invention provides a system that manages the home environment comfortably and effectively based on the user's emotions.

[0784] The following describes the processing flow.

[0785] Step 1:

[0786] The user activates their device to utilize the emotion engine and initiates emotional input feedback as needed. This allows the emotion engine to acquire the user's state in real time.

[0787] Step 2:

[0788] The device collects emotional data in a non-invasive way, such as the user's facial expressions and tone of voice. This data is sent to an emotion engine, where it is analyzed to understand the user's emotional state.

[0789] Step 3:

[0790] The emotion engine analyzes the acquired data to identify the user's current emotional state. For example, consider a scenario where the system determines that the user is stressed.

[0791] Step 4:

[0792] The server receives the sentiment analysis results from the emotion engine and determines the optimal automation scenario based on them. For example, it might suggest relaxing lighting and music to a user experiencing stress.

[0793] Step 5:

[0794] The server sends appropriate instructions to devices in the home according to the determined automation scenario. For example, it might instruct devices to lower the color temperature of the lights or play music.

[0795] Step 6:

[0796] The device receives instructions from the server and provides feedback to the user. It notifies the user that the instructions have been carried out and asks if the user wishes to make further adjustments through interaction with the emotion engine.

[0797] Step 7:

[0798] Users help the system adapt further by reviewing feedback and instructing on additional adjustments as needed. At this stage, if there are new requests, the server and emotion engine processes are restarted.

[0799] (Example 2)

[0800] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0801] Modern homes and offices contain a wide variety of equipment from different manufacturers, creating a need for efficient systems to integrate and control them. Furthermore, it's crucial to provide a more comfortable and personalized environment by reflecting and adapting to the user's emotional state. However, few existing systems meet these complex requirements, and they often suffer from cumbersome management.

[0802] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0803] In this invention, the server includes means for interpreting instructions from users and transmitting signals to the corresponding equipment; means for analyzing usage data collected from equipment within a living space and generating automation scenarios; and means for analyzing the user's emotional state using an emotion recognition engine and optimizing the operation of the equipment based on that data. This enables integrated control of the equipment and the provision of a personalized environment.

[0804] "Equipment" refers to various devices and home appliances used in homes and offices.

[0805] A "data processing device" refers to a device or system for handling, analyzing, and controlling information.

[0806] "User" refers to a person who operates or uses this system.

[0807] "Instructions" refer to the operations or requests that users make to the system.

[0808] A "signal" refers to electrical or electronic communication information that a system transmits to equipment.

[0809] An "emotion recognition engine" refers to software or system functionality used to detect and analyze a user's emotional state.

[0810] "Optimizing operations" refers to adjusting equipment to function most efficiently based on the user's circumstances and feelings.

[0811] "Living space" refers to the place where users live, that is, the interior of a home or office.

[0812] An "automation scenario" refers to a set of operating procedures for equipment, generated by the system based on pre-set conditions.

[0813] This invention is a system that integrates and controls multiple pieces of equipment from different manufacturers, optimizing the environment based on user emotions.

[0814] System Configuration

[0815] The system primarily consists of a server, terminals, and users, and uses an emotion recognition engine to coordinate its overall operation. The server acts as a data processing unit, analyzing emotion data collected via the terminals. Users can give instructions to the system and control the operation of the equipment through their terminals.

[0816] Hardware and software

[0817] The server acts as a data processing unit, mediating communication with multiple devices and executing control scenarios. This includes software for monitoring energy consumption and detecting anomalies.

[0818] The device uses sensors and microphones to capture the user's facial expressions and voice tone, and transmits this data to the emotion recognition engine.

[0819] The emotion recognition engine uses a generative AI model to analyze data sent from the device and identify the user's emotional state.

[0820] Specific example

[0821] For example, when a user returns home, the device detects their facial expressions and tone of voice, and the emotion recognition engine detects "fatigue." Based on this data, the server controls the equipment to play relaxing music and adjust the lighting to calming colors.

[0822] Example of a prompt

[0823] An example of a prompt message is, "Please configure the settings so that the user can relax in the living room."

[0824] This invention makes it easier to adjust the home environment based on the user's emotions, thereby improving the quality of life.

[0825] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0826] Step 1:

[0827] The device uses sensors and a microphone to detect the user's facial expressions, voice tone, and language patterns. This data serves as input to identify the user's emotional state. The collected data is sent to an emotion recognition engine. Specific actions include the device taking a picture of the user's face with its camera and recording their voice with its microphone.

[0828] Step 2:

[0829] The server receives data sent from the terminal and performs data analysis using an AI model generated by the emotion recognition engine. This analysis identifies the user's emotional state (e.g., "relaxed," "stressed," etc.). This process includes facial expression analysis and voice analysis, and outputs an emotion recognition pattern.

[0830] Step 3:

[0831] The server generates an optimal control scenario tailored to the user's emotions, based on the output from the emotion recognition engine. Emotional state data is used as input, and specific instructions for controlling household equipment are generated as output. For example, the server might generate instructions to adjust lighting or play relaxing music.

[0832] Step 4:

[0833] The server sends the generated control scenario to the terminal and each piece of equipment in the home, prompting them to perform specific actions. This causes the equipment to adjust the environment according to the instructions from the server. For example, the audio system might play a specified song, or the lighting system might adjust to the specified color and brightness.

[0834] Step 5:

[0835] Users can experience an environment controlled by an emotion engine and provide feedback to the server. This feedback is then incorporated into subsequent scenario generation, resulting in even more personalized control. Specifically, users provide feedback to the system by inputting instructions such as "I'd like the lighting to be a little brighter" to their device.

[0836] (Application Example 2)

[0837] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0838] In modern urban spaces, actively adapting public facilities and living environments to the emotional states of users is crucial for improving the quality of life for residents. However, coordinating devices and systems from different manufacturers is difficult, making dynamic adjustments to the environment based on user emotions challenging. Therefore, there is a need for a system that can analyze users' emotional states in real time and adjust the environment accordingly to the optimal setting.

[0839] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0840] In this invention, the server includes means for interpreting user instructions and transmitting signals to the corresponding devices, means for analyzing usage data collected from devices in apartment buildings or urban spaces to generate automation scenarios, and means for analyzing user emotional data and dynamically adjusting the public environment and device status in the urban space. This makes it possible to integrally manage devices and systems from different manufacturers, and easily realize individualized responses and optimal environmental adjustments based on user emotions.

[0841] An "information processing device" is a computer system that collects, analyzes, and controls data, and enables communication between devices.

[0842] A "user" is a human interface that transmits instructions and provides emotional data through an information processing device.

[0843] A "device" is hardware installed in a home or urban space that has functions such as lighting, entertainment systems, or other functions.

[0844] "Emotional data" refers to information that represents the user's emotional state, and is composed of information such as facial expressions, voice tone, and behavioral patterns.

[0845] An "automation scenario" is a set of pre-configured procedures that define and execute the optimal operation of a device based on user instructions and emotional data.

[0846] "Power consumption" refers to the amount of electricity required for a device to function, and is a measure of energy efficiency.

[0847] A "safety sensor" is a security device that detects abnormal conditions in equipment or the environment and notifies an information processing device.

[0848] "Public environment" refers to the physical and functional settings of publicly used spaces in urban areas, such as parks, libraries, and streets.

[0849] This invention relates to a system centered on an information processing device for dynamically adjusting the environment based on the user's emotional state. In this system, a server plays a central role in comprehensively managing various devices.

[0850] The server receives emotional data sent by users and analyzes it in real time. This analysis utilizes cloud-based facial recognition technology and software that acts as a voice sensor. Specifically, it uses APIs such as Google Cloud Vision and AWS Rekognition to identify emotions based on the user's facial expressions and voice tone.

[0851] Based on the analyzed emotional data, the server constructs an automated scenario. This scenario includes optimal device operation procedures that take into account the user's current emotional state. For example, if the server determines that the user is relaxed while strolling through a park, it sends a command to the relevant device via the smartphone to play soothing music through earphones and adjust the streetlights to a softer color tone.

[0852] As a concrete example, when sending a prompt to a generative AI model, it might be used in the form of, "Could you suggest background music that will help enhance a user's relaxed emotional state while walking through a public park, considering the current time of day and weather conditions?" This prompt is used by the generative AI model to select content appropriate to the user's state.

[0853] As described above, personalized services and adjustments tailored to the user's emotional needs can be provided through an automated system. This system can be widely applied in both urban spaces and homes.

[0854] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0855] Step 1:

[0856] The device captures the user's facial expressions and voice data and sends it to the server. Input is real-time data from the camera and microphone, which is converted into image and audio formats as needed. Output is sent to the server as a data stream.

[0857] Step 2:

[0858] The server analyzes the emotional data it receives. The input consists of facial expressions and voice data sent from the terminal. For data processing, APIs such as Google Cloud Vision and AWS Rekognition are used to output the user's emotional state as text or numerical data.

[0859] Step 3:

[0860] The server generates automated scenarios based on the analysis results. The input is information on the analyzed emotional state. As a data calculation, it combines existing scenario templates with the analysis results to select a scenario appropriate to the user's state and converts it into device control commands. The output is sent to each device as specific control commands.

[0861] Step 4:

[0862] The server sends control commands to the devices, causing them to make configuration changes and provide data on-site. The input consists of automated control commands, which are transmitted to each device using a communication protocol. The output is perceived by the user as changes in the operation of the corresponding devices or as new information provided.

[0863] Step 5:

[0864] The system receives environmental changes and information services provided to the user. Input consists of physical changes and information from the device. If the user provides feedback through the terminal, this information is also sent to the server and used to adjust scenarios for future use. Output is achieved as improvements in user comfort and satisfaction.

[0865] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0866] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0867] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0868] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0869] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0870] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0871] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0872] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0873] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0874] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0875] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0876] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0877] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0878] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0879] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0880] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0881] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0882] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0883] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0884] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0885] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0886] The following is further disclosed regarding the embodiments described above.

[0887] (Claim 1)

[0888] In a computer-based management system that provides a method and apparatus for integrating the control of multiple devices from different manufacturers,

[0889] A means for interpreting user instructions and transmitting signals to the corresponding device,

[0890] A means of generating automation scenarios by analyzing usage data collected from devices within the home,

[0891] A means of monitoring the power consumption of a device and sending notifications to the user recommending energy reduction,

[0892] A means of monitoring anomalies detected by security sensors and notifying the user,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, characterized in that it learns the user's lifestyle and automatically controls the device based on time and events.

[0896] (Claim 3)

[0897] The system according to claim 1, characterized in that it monitors the power consumption data of each device in real time and automatically adjusts it when it exceeds a threshold.

[0898] "Example 1"

[0899] (Claim 1)

[0900] In an integrated management system using an information processing device that provides a device and method for integratively controlling multiple devices from different manufacturers,

[0901] A means for interpreting voice instructions or text input from a user using natural language processing technology and transmitting standardized commands to the corresponding device,

[0902] A means for analyzing natural language prompt sentences using a generated artificial intelligence model and converting them into control commands for a device,

[0903] A means for analyzing operational data collected from devices within the home to generate automated operation procedures optimized for the user,

[0904] A means of monitoring the power consumption of the device and providing the user with notifications suggesting ways to reduce power consumption,

[0905] A means for detecting an anomaly detected by a security device or surveillance sensor and sending a warning notification to the user,

[0906] A system that includes this.

[0907] (Claim 2)

[0908] The system according to claim 1, characterized by learning user behavior patterns and automatically controlling the device based on time or events.

[0909] (Claim 3)

[0910] The system according to claim 1, characterized in that it monitors the power consumption information of each device in real time and automatically adjusts its operation when it exceeds a set threshold.

[0911] "Application Example 1"

[0912] (Claim 1)

[0913] In a computer-based management system that provides a method and apparatus for integrating the control of multiple devices from different manufacturers,

[0914] A means for analyzing user instructions and transmitting signals to the corresponding device,

[0915] A means of acquiring public infrastructure data and providing traffic information and security information to users,

[0916] A means for analyzing usage data to generate automated control scenarios,

[0917] A means of monitoring energy consumption and sending notifications to users to promote efficiency,

[0918] A means of monitoring anomalies detected by security detection devices and notifying users,

[0919] A system that includes this.

[0920] (Claim 2)

[0921] The system according to claim 1, characterized in that it learns the user's lifestyle information and automatically controls the device based on time and events.

[0922] (Claim 3)

[0923] The system according to claim 1, characterized in that it monitors the energy consumption data of each device in real time and automatically adjusts when it exceeds a threshold.

[0924] "Example 2 of combining an emotion engine"

[0925] (Claim 1)

[0926] In a data processing device that provides a method and apparatus for integrated control of multiple pieces of equipment from different manufacturers,

[0927] A means for interpreting instructions from the user and transmitting a signal to the corresponding equipment,

[0928] A means of generating automation scenarios by analyzing usage data collected from equipment within a living space,

[0929] A means of monitoring the energy consumption of equipment and sending notifications to users recommending energy reduction,

[0930] A means of analyzing the emotional state of users using an emotion recognition engine and optimizing the operation of equipment based on that data,

[0931] A means of monitoring anomalies detected by sensors and notifying users,

[0932] A system that includes this.

[0933] (Claim 2)

[0934] The system according to claim 1, characterized in that it learns the user's lifestyle habits and automatically controls the equipment based on time and events.

[0935] (Claim 3)

[0936] The system according to claim 1, characterized in that it monitors the energy consumption data of each piece of equipment in real time and automatically adjusts it when it exceeds a threshold.

[0937] "Application example 2 when combining with an emotional engine"

[0938] (Claim 1)

[0939] In an information processing apparatus that provides a method and apparatus for integrated control of multiple devices from different manufacturers,

[0940] A means for interpreting instructions from the user and transmitting a signal to the corresponding device,

[0941] A means for generating automation scenarios by analyzing usage data collected from devices in apartment buildings or urban spaces,

[0942] A means of monitoring the device's power consumption and sending notifications to the user recommending energy reduction,

[0943] A means of monitoring abnormalities detected by safety sensors and notifying users,

[0944] A means of analyzing users' emotional data and dynamically adjusting the state of public environments and devices in urban spaces,

[0945] A system that includes this.

[0946] (Claim 2)

[0947] The system according to claim 1, characterized in that it learns the user's lifestyle patterns and automatically controls the device based on time and circumstances.

[0948] (Claim 3)

[0949] The system according to claim 1, characterized in that it monitors the power consumption data of each device in real time, automatically adjusts when a threshold is exceeded, and provides appropriate environmental settings while taking into account the emotional state of the user. [Explanation of symbols]

[0950] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. In a computer-based management system that provides a method and apparatus for integrating the control of multiple devices from different manufacturers, A means for interpreting user instructions and transmitting signals to the corresponding device, A means of generating automation scenarios by analyzing usage data collected from devices within the home, A means of monitoring the power consumption of a device and sending notifications to the user recommending energy reduction, A means of monitoring anomalies detected by security sensors and notifying the user, A system that includes this.

2. The system according to claim 1, characterized in that it learns the user's lifestyle and automatically controls the device based on time and events.

3. The system according to claim 1, characterized in that it monitors the power consumption data of each device in real time and automatically adjusts it when it exceeds a threshold.

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