system

Abstract

We provide the system. [Solution] Analysis means for analyzing voice and messages and generating instructions for the controlled device, A control means that receives a control instruction and operates a home appliance based on the instruction, An anomaly detection means that collects sensor data and detects anomalies based on said data, A notification mechanism for notifying the user or a third-party organization when an anomaly is detected, A summarization and registration method that summarizes information and automatically registers it as calendar information, 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 character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, the use of smart devices in homes has been increasing. However, these devices do not have sufficient cooperation with each other, and it is necessary to operate multiple devices individually, which places a heavy burden on users. In addition, there is a lack of a unified system that all family members can easily access and operate, especially when family members are away, it is difficult to efficiently manage the home. Thus, it is difficult for existing home smart devices to achieve consistent management and control both inside and outside the home.

Means for Solving the Problems

[0005] This invention provides a communication system that can comprehensively manage home appliances and security devices. Specifically, it uses an analysis means that analyzes voice and messages and generates instructions for the controlled devices, thereby accurately determining user instructions and performing necessary operations. Furthermore, it is equipped with an anomaly detection means that collects sensor data and detects abnormalities, and when an abnormality is detected, it notifies the user or a third-party organization. This system realizes automatic control according to the user's lifestyle and improves the convenience of the home. It also has a function to summarize information and automatically register it as calendar information, allowing the user to quickly grasp important information. These means reduce the complexity of home management and enable the user to manage the situation of their home with peace of mind.

[0006] "Analysis means" refers to an element that has the function of analyzing voices and messages and generating appropriate instructions for the controlled device.

[0007] A "control means" is an element that has the function of operating home appliances and related hardware based on control instructions received from a server.

[0008] An "anomaly detection means" is an element that monitors data from sensors and has the function of detecting situations that are different from the normal state and setting a flag.

[0009] A "notification mechanism" is an element that has the function of promptly notifying the user or a third-party organization when an anomaly is detected.

[0010] "Summarization and registration means" refers to an element that has the function of analyzing received information, extracting important content, organizing it, and automatically registering it in a calendar or similar. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, the terms used in the following description will be explained.

[0014] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, a RAM (Random Access Memory) with a reference number is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, a storage with a reference number is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0017] In the following embodiments, a communication I / F (Interface) with a reference number is an interface that includes a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0018] 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."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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".

[0032] The present invention relates to a communication system that comprehensively manages various devices and systems within a home and automatically controls them based on user instructions. This system includes an analysis means for analyzing voice and messages and generating commands as appropriate; a control means for executing control instructions; an anomaly detection means for detecting abnormalities based on sensor data; a notification means for issuing notifications in the event of an anomaly; and a summarization and registration means for summarizing information and registering it in a calendar.

[0033] When the server receives a voice command or LINE message from a user, it uses analysis tools to analyze the instruction and determine the necessary action. For example, if a user says, "Turn off the lights," the server recognizes the keywords "lights" and "off" through analysis and generates a control command corresponding to the lighting device. The server then sends the generated command to the terminal to execute the control.

[0034] The terminal is responsible for directly operating home appliances according to control instructions received from the server. It sends appropriate control signals to hardware such as lights, air conditioners, and door locks. It can also automatically turn on lights when the user returns home, based on pre-set rules according to the user's lifestyle.

[0035] Users interact with this system using smartphones or tablets. A key feature is the ability to easily control various devices within the home even when away from home. When a user asks "What's my schedule for this week?" via LINE, the server queries calendar information, generates a concise schedule list using summarization and registration methods, and notifies the user.

[0036] As a concrete example, if a user receives an email one morning informing them of a PTA meeting schedule, the server summarizes the email's contents and automatically registers it in their calendar as "Tomorrow at 3 PM: PTA Meeting." A notification of this registration completion is sent to the user's smartphone via LINE, allowing the user to stay informed of important information in real time.

[0037] This invention dramatically improves the efficiency of household management and provides users with a highly convenient living environment.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The user sends a message via LINE from their smartphone saying, "Set the air conditioner to 21 degrees."

[0041] Step 2:

[0042] The server receives the LINE message and analyzes the content of the instructions using natural language processing. Here, the server extracts the keywords "air conditioner" and "21 degrees".

[0043] Step 3:

[0044] Based on the analysis results, the server generates the commands necessary to control the air conditioner. In this case, it creates a command to change the temperature setting of the air conditioner.

[0045] Step 4:

[0046] The server sends the generated control commands to the terminal. Assume the terminal is connected to an air conditioner control unit installed in the home.

[0047] Step 5:

[0048] The terminal analyzes the command received from the server and sends a specific operation signal to the air conditioning control unit. The air conditioning control unit changes the temperature setting to 21 degrees according to that signal.

[0049] Step 6:

[0050] The air conditioning control unit signals the terminal when processing is complete.

[0051] Step 7:

[0052] The terminal receives a completion signal from the air conditioner control unit and reports the completion of the operation to the server.

[0053] Step 8:

[0054] The server confirms the completion report from the terminal and sends a notification to the user's LINE account saying, "The air conditioner has been set to 21 degrees."

[0055] This allows users to easily control their home air conditioners remotely, even when they are away from home.

[0056] (Example 1)

[0057] 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."

[0058] There is a need to efficiently manage the operation of various devices and systems within the home and improve user convenience. The challenge lies in reducing the effort required for traditional direct operation, enabling rapid response to malfunctions, and achieving centralized information management.

[0059] 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.

[0060] In this invention, the server includes information processing means for analyzing voice and text instructions and generating control instructions, device control means for receiving the generated control instructions and operating in-home devices, and monitoring means for collecting environmental data and detecting anomalies. This enables efficient management of various devices in the home and rapid response in the event of anomalies.

[0061] "Voice and text instructions" refers to a form of instruction in which a user uses voice or text messages to control a home device.

[0062] "Information processing means" refers to devices or programs that have the function of interpreting instructions in the form of voice or text and generating appropriate control instructions.

[0063] "Control instructions" refer to the specific operational commands necessary to operate a household device based on the analyzed instructions.

[0064] "Device control means" refers to a device or program that has the function of directly operating various household devices based on the generated control instructions.

[0065] "Environmental data" refers to information about the operating status of devices and systems, such as temperature, humidity, and operating conditions within a home.

[0066] "Monitoring means" refers to devices or programs that have the function of continuously collecting environmental data and detecting anomalies based on predetermined criteria.

[0067] "Anomaly" refers to a state that deviates from the normal operation of a household device or system, or to an unexpected event.

[0068] This invention is a communication system for efficiently managing and controlling devices and systems within a home. It consists of server, terminal, and user elements, which work together to function.

[0069] The server is responsible for receiving and analyzing voice and text messages. Specifically, it uses speech recognition software to convert voice commands into text data and natural language processing techniques to extract necessary keywords. The server can utilize speech recognition APIs provided by Amazon and Google®. Furthermore, based on the analyzed data, it generates optimal control instructions using a generative AI model. These control instructions are then transmitted to the terminal via the home network.

[0070] The terminal directly operates various devices within the home based on control instructions received from the server. For example, it communicates with home appliances using Bluetooth or Zigbee protocols to control devices such as lighting and air conditioners. This allows users to enjoy an automated living environment.

[0071] Users access this system using mobile devices such as smartphones and tablets. This allows users to operate devices in their home even when they are away from home. For example, they can send voice or text instructions using messaging apps such as LINE and receive feedback on the situation in their home.

[0072] As a concrete example, consider a scenario where a user, while out and about, asks the system via LINE, "Tell me my schedule for this week." In this case, the server refers to the calendar information, creates a concise schedule list based on the analysis results, and notifies the user via LINE. An example of a prompt message could be, "As a new example, the user has instructed, 'Tell me the weather for this week.' The AI ​​model should use a web API to obtain weather information, summarize it in an easy-to-understand format, and notify the user via LINE." This is how the information could be input to the generating AI model.

[0073] This system significantly improves user convenience and enables flexible and efficient home management.

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] The server receives voice commands and text messages from users. Voice and text input via smartphones and tablets are transmitted to the server via the communication network. Specifically, this involves a process that converts voice into text data using speech recognition software. As a result, text data is output to analyze the user's intent.

[0077] Step 2:

[0078] The server analyzes the received text data to determine the appropriate action. Natural language processing techniques are used for text analysis to extract specific keywords and phrases. For data processing, a generative AI model is used to determine the most suitable instructions for the user's needs and generate control commands. This clarifies the target device and the specific actions to be performed.

[0079] Step 3:

[0080] The server sends the generated control commands to the terminal. The transmitted data reaches the terminal via the network, preparing it for operation of various devices in the home. The terminal converts the data format based on the received commands and generates signals for direct operation.

[0081] Step 4:

[0082] The terminal transmits the received signal to the home device and performs the actual operation. Specifically, it uses communication protocols such as Bluetooth and Zigbee to perform appropriate operations on home appliances. For example, it controls things like turning off smart lighting.

[0083] Step 5:

[0084] The server monitors the results of the operations performed and provides feedback to the user as needed. Once it confirms that the operation was successfully executed, the user is notified via LINE, email, or other means. A pre-designed response is generated in response to the input information, and output is sent to the user reporting the status. This allows the user to confirm that each operation was performed correctly.

[0085] (Application Example 1)

[0086] 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."

[0087] In recent years, with the increasing number of electrical appliances and systems in homes, there has been a growing need to efficiently manage them and provide users with a user-friendly living environment. However, conventional systems require operation for each individual device, making integrated management difficult. Furthermore, there is a lack of convenient means to control home devices remotely.

[0088] 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.

[0089] In this invention, the server includes analysis means for analyzing voice and information communication and generating instructions for the controlled system; control means for receiving control instructions and operating the device based on those instructions; and anomaly detection means for collecting data and detecting anomalies based on that data. This makes it possible for users to easily integrate and manage devices in their home even when away from home, thereby realizing a comfortable living environment.

[0090] "Voice and information communication" refers to data communication methods that analyze voice instructions and messages from users to extract information and operate the system based on that information.

[0091] "Analysis means" refers to a function that analyzes instructions obtained through voice or information communication and generates appropriate operation commands.

[0092] "Control means" refers to the function of managing and operating the device based on instructions generated by the analysis means.

[0093] An "anomaly detection mechanism" is a function that determines abnormalities in devices and systems based on collected data and prompts necessary actions.

[0094] A "notification mechanism" is a system that notifies users or external organizations of information when an anomaly is detected.

[0095] "Summarization and registration means" refers to a function that organizes information and registers it in a schedule or calendar as needed.

[0096] A "user" is a person who operates this system and manages devices inside and outside the home.

[0097] A "smart device" is a portable information terminal that can acquire and process information via a network.

[0098] "Integrated management" is the process of managing and efficiently controlling a variety of devices and systems in a unified manner.

[0099] "Environmental information" refers to data about the surrounding conditions, such as temperature, humidity, and lighting conditions inside and outside the home.

[0100] This invention aims to realize an integrated management system that automatically manages the environment inside and outside the home, providing users with a comfortable living environment. Its form is described below.

[0101] The server receives user voice commands and messages and uses analysis tools to analyze them. The analyzed commands are converted into specific control commands by control tools and sent to devices within the home via a terminal. Users can access this system remotely via smart devices such as smartphones and tablets to monitor and control the status of devices within their home.

[0102] The anomaly detection system collects data from sensors and detects environmental anomalies. If an anomaly is detected, a notification is sent to the user or a third-party organization through the notification system.

[0103] Furthermore, the summarization and registration features manage the user's schedule, summarizing necessary information and automatically registering it in the calendar. This ensures that important appointments are not missed.

[0104] For example, if a user gives a voice command saying "I'm leaving now" before going to work in the morning, the server will automatically turn off the lights and air conditioning. Also, if they give a command saying "I'll be home in 5 minutes" before returning home, the air conditioning will automatically turn on to maintain a comfortable room temperature.

[0105] This system is implemented using speech recognition technology with the Google Speech-to-Text API, cloud-based data processing using AWS® Lambda, and device-to-device communication using the MQTT protocol.

[0106] Using a generative AI model, the following example prompts are available:

[0107] "What factors should be considered when designing a control process for optimal home device management based on user voice commands?"

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The server receives voice commands from the user via a smartphone. Voice data is provided as input. The server converts this voice data into text data using the Google Speech-to-Text API. The output is a parseable command text.

[0111] Step 2:

[0112] The server processes the transcribed voice instructions using an analysis tool and generates appropriate control commands. It uses text data of user instructions as input. The server performs keyword extraction and semantic analysis, outputting command data for specific device operation. For example, the instruction "Turn on the lights" is converted into the command "Turn on lights".

[0113] Step 3:

[0114] The server sends the generated control command to the terminal. The control command is provided as input, and the command sent to the terminal is its output. The server uses the MQTT protocol for this communication.

[0115] Step 4:

[0116] The terminal operates the device based on the control commands it receives. It receives command data from the server as input. The terminal generates control signals for the device corresponding to the command, operating appliances such as home electronics. The output is the actual operation of the device (e.g., turning on a light).

[0117] Step 5:

[0118] The server collects data from various sensors and determines whether or not there are any abnormalities. The input is data from the sensors. The server detects abnormal values ​​and determines the abnormal state based on the results. The output is the determination of the occurrence of the abnormality.

[0119] Step 6:

[0120] If an anomaly is detected, the server will notify the user or a third party using a notification mechanism. The input is the result of the anomaly detection. The server generates a notification message and outputs the information via the communication platform.

[0121] Step 7:

[0122] When a user requests a schedule check, the server queries calendar information using summarization and registration methods. The input is the user's request. The server organizes the calendar information and outputs a summary. This information is sent to the user's smart device.

[0123] 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.

[0124] This invention relates to a communication system that integrates and manages various devices and systems within a home, and is equipped with an emotion analysis function that recognizes the user's emotions and automatically adjusts the environment. This system includes an analysis means that analyzes voice and messages and generates appropriate commands, a control means that executes control instructions, and an emotion analysis means that analyzes the user's emotions and sends control instructions according to those emotions.

[0125] The server receives voice commands and LINE messages sent by the user. Using emotion analysis technology, it analyzes the user's emotions from this information and tags them with emotions such as "joy," "sadness," and "anger." Then, it determines the optimal environment settings according to the user's emotions and generates corresponding control instructions.

[0126] For example, if a user says "I'm tired today" in an emotionally charged voice, the server tags it with the emotion "tired" and sends a command to the device to adjust the lighting to a warmer color to help it relax.

[0127] Based on commands received from the server, the terminal sends appropriate control signals to home hardware, such as lighting and music players. This control allows for adjustments to lighting brightness and color, or the playback of relaxing music.

[0128] Users can feel these environmental changes firsthand and enjoy a more comfortable home life. Furthermore, users' emotional history is recorded and analyzed using data analytics tools, allowing the service to be personalized over time and leading to greater satisfaction.

[0129] For example, if a user returns home late at night and says, "I feel uneasy," the server analyzes the emotion as "anxiety" or "tension," and instructs the device to change the lighting to a softer tone and play quiet background music.

[0130] In this way, the present invention instantly senses the user's emotions, provides an optimal home environment accordingly, and realizes a more comfortable life for the user.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The user uses their smartphone's microphone to say, "I'm tired today."

[0134] Step 2:

[0135] The server receives the audio data and first converts the audio into text using natural language processing. Then, it applies sentiment analysis to tag the user's emotion as "tired" based on the text "tired".

[0136] Step 3:

[0137] Based on emotion tagging, the server evaluates the optimal environment settings to help the user relax. In this case, for example, it might choose to change to a relaxing lighting color.

[0138] Step 4:

[0139] The server generates commands to change the color temperature of the lighting to a warm color and to play quiet background music on the music player, and sends them to the terminal.

[0140] Step 5:

[0141] Based on instructions from the server, the terminal sends appropriate control signals to the lighting control unit and the music playback unit. As a result, the color temperature of the lighting is adjusted to a warm color, and the music playback device begins playing quiet background music.

[0142] Step 6:

[0143] Users can sense the changes in lighting and music, allowing them to experience a relaxing environment.

[0144] This sequence of events allows the system to automatically adjust the home environment to match the user's emotions.

[0145] (Example 2)

[0146] 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".

[0147] In modern living environments, there is a need to comprehensively manage various devices within the home and automatically adjust the environment according to the user's emotions. However, existing systems struggle to effectively detect individual user emotions and optimize the environment based on them. This presents a challenge in ensuring that users can consistently enjoy a comfortable life.

[0148] 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.

[0149] In this invention, the server includes means for analyzing voice and text information to recognize the user's emotions and generate control instructions corresponding to those emotions; means for receiving the generated control instructions and operating a plurality of environmental devices based on those instructions; and analysis means for accumulating user emotion data and optimizing environmental settings based on past data. This makes it possible for the user to enjoy an optimal environment that corresponds to their emotions.

[0150] "Voice information" refers to data obtained by electrically converting the voice emitted by the user, and is one of the types of information that the system analyzes.

[0151] "Text information" refers to information expressed as character data, and includes user messages and transcripts of voice messages.

[0152] "Emotions" are a concept that represents the user's feelings and psychological state, and are treated as a target for analysis in this system.

[0153] A "control instruction" is a command that instructs a target device to perform an action based on its analyzed emotions.

[0154] "Emotional data" refers to data that records a user's emotional tendencies and history, and will be used for future personalization.

[0155] "Analysis means" refers to a mechanism that uses accumulated data to perform processes such as optimizing and predicting environmental settings.

[0156] "Environmental devices" refer to controllable devices within a home, including lighting fixtures and audio equipment.

[0157] This invention is a communication system that integrates and manages various environmental devices within the home and automatically adjusts the environment based on the user's emotions. The aim is to provide the user with a comfortable living environment.

[0158] The server handles voice input and message reception. Specifically, it uses speech recognition software to convert speech to text. A common cloud-based speech recognition API is available for this process, quickly generating text data from speech. Next, sentiment analysis software using natural language processing techniques runs to analyze this text data. In this analysis process, the user's emotions are categorized from the text into categories such as "joy," "sadness," and "anger." Based on this sentiment data, the server determines the most appropriate environment settings and generates specific control instructions.

[0159] Control instructions are sent to environmental devices within the home, such as lighting and music playback devices. The terminal receives these instructions and adjusts the color temperature and brightness of the lighting device. It also issues instructions to the music playback system to select and play music that suits the user's mood. These operations are performed using common protocols for smart device control.

[0160] For example, if a user says "I'm very tired today" at home, the server analyzes this as an emotion of "tiredness" and generates an instruction to change to relaxing warm-colored lighting. Upon receiving this instruction, the terminal operates the lighting and music systems to change the lighting to a warm color and play soothing music. In this way, the system provides the user with an optimal environment and enables a comfortable life.

[0161] An example of a prompt for a generative AI model is: "If the user says, 'I'm very tired today,' please show what kind of sentiment analysis and environmental adjustments the system would perform based on this information."

[0162] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0163] Step 1:

[0164] The server receives voice input from the user and converts it into text.

[0165] Input: User's voice command

[0166] Processing: A cloud-based speech recognition API is used to convert the speech signal into natural language text data.

[0167] Output: Text data converted from speech

[0168] Specifically, the server receives voice data from the voice input device in real time and processes it instantly through the voice recognition system.

[0169] Step 2:

[0170] The server performs sentiment analysis on the text data to identify the user's emotions.

[0171] Input: Converted text data

[0172] Processing: Using natural language processing techniques, emotions such as positive, negative, and neutral are analyzed from the text. An emotion analysis library is used to calculate an emotion score.

[0173] Output: Emotional labels (e.g., "joy", "sadness", "anger")

[0174] Specifically, the server sends text data to an analysis engine, instantly identifies the sentiment category, and stores the result in an internal database.

[0175] Step 3:

[0176] The server generates appropriate control instructions based on the identified emotions.

[0177] Input: Emotion Label

[0178] Processing: Based on emotion labels, the system references pre-configured response rules to assemble specific environmental control instructions, such as lighting and music settings.

[0179] Output: Environmental control instructions (e.g., instructions to set lighting to a warm color)

[0180] In terms of specific operations, the server uses emotion labels to perform analysis within the system to determine an appropriate response and generates a corresponding control code.

[0181] Step 4:

[0182] The terminal executes control instructions received from the server and operates environmental devices within the home.

[0183] Input: Environmental control instructions

[0184] Processing: Sends control instructions to lighting control devices and sound playback devices, causing them to perform actions accordingly.

[0185] Output: Adjusted environment (e.g., lighting chromaticity, music type)

[0186] In terms of specific operations, the terminal transmits signals to various smart devices via network communication, ensuring that lighting and audio systems operate as instructed.

[0187] (Application Example 2)

[0188] 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".

[0189] In modern homes, it is difficult to instantly provide the optimal environment settings that respond to the user's emotions. Furthermore, there is no system that analyzes the user's emotional state and automatically adjusts the environment. As a result, users must manually configure the environment themselves to achieve a comfortable home environment, which presents a challenge in terms of time and effort.

[0190] 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.

[0191] In this invention, the server includes analysis means for analyzing voice and messages and generating instructions for a controlled device; control means for receiving control instructions and operating household appliances based on those instructions; and emotion adjustment means for analyzing emotions and adjusting environmental elements based on the analysis results. This makes it possible to instantly analyze the user's emotions and automatically provide an appropriate environment.

[0192] "Sound" refers to sound waves or signals produced by human speech.

[0193] A "message" is a means of transmitting information to others using text or audio.

[0194] "Analysis means" refers to a device or software that has the function of breaking down speech or messages and extracting and interpreting useful information from them.

[0195] "Control means" refers to a device or software that has the function of operating and managing equipment or systems based on commands.

[0196] "Household appliances" refers to electrical appliances and equipment used within the home.

[0197] An "emotion adjustment device" is a device or software that analyzes a user's emotions and adjusts environmental elements accordingly.

[0198] "Environmental elements" refer to various elements within the home that affect the user's senses and comfort, such as lighting, music, and temperature.

[0199] The system realizing this invention aims to analyze voice and messages and automatically adjust the home environment according to the user's emotions. The server receives user commands via a robot equipped with a microphone and camera for capturing voice data. The voice is converted to text using the Google Cloud Speech-to-Text API, and the text data is analyzed for the user's emotional state using IBM Watson®'s Sentiment Analysis API. Based on the analysis results, commands are generated to adjust the environment to suit the user's emotions and sent to devices in the home. Specific control of home devices is performed through the Home Assistant platform, dynamically adjusting settings such as lighting and music.

[0200] The device controls various devices in the home based on emotion analysis results and control commands received from the server. It makes adjustments necessary to provide an environment that the user finds comfortable, such as adjusting the brightness and color of the lighting, and selecting and adjusting the volume of music. This allows the user to enjoy a relaxed space tailored to their emotional state.

[0201] Through the operation of such systems, users can avoid the hassle of manually configuring their environment and obtain a comfortable and personalized living space. For example, if a user says, "I'm tired today," the server can identify the emotion of "tiredness" and instruct it to change the lighting to a warm color and play relaxing music. This specific example helps to understand how the system works.

[0202] An example of an input prompt for a generative AI model is, "Analyze the user's emotions upon returning home and explain how to adjust the home environment accordingly." This prompt allows the system to refer to specific scenarios.

[0203] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0204] Step 1:

[0205] The server uses the robot's microphone and camera to capture user audio and video data. The input data consists of the user's speech and facial expressions. Based on this data, the audio data is converted to text using the Google Cloud Speech-to-Text API, and the video data is preprocessed for sentiment inference.

[0206] Step 2:

[0207] The server sends the text data generated in Step 1 to IBM Watson's sentiment analysis API. The input is text obtained from the user's utterance. At this stage, the sentiment analysis API analyzes the text data and outputs sentiment tags such as "joy," "sadness," and "fatigue." The analysis results are used as information indicating the user's current emotional state.

[0208] Step 3:

[0209] The server uses the emotion tags obtained in step 2 to create a plan for adjusting the home environment. The inputs are the emotion tags and data on the current home environment. It determines the optimal environmental settings (e.g., lighting brightness, music selection) based on a specific emotion and generates these as instructions. The output is a specific control command regarding the environmental settings.

[0210] Step 4:

[0211] The terminal transmits signals corresponding to home devices based on control commands received from the server. The input is the control command from the server. The terminal uses the Home Assistant platform to perform actions such as adjusting the color and brightness of lighting or selecting and playing appropriate music. The output is the environmental changes perceived by the user.

[0212] Step 5:

[0213] The user can enjoy their daily life in the home environment adjusted in Step 4. The user's comfort level, based on the matching of their emotions with the current environmental settings, is recorded and sent to the server as feedback. This feedback is used to improve the system. The input is the user's emotional response, and the output is long-term user satisfaction.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] [Second Embodiment]

[0218] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0219] 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.

[0220] 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).

[0221] 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.

[0222] 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.

[0223] 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).

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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".

[0230] The present invention relates to a communication system that comprehensively manages various devices and systems within a home and automatically controls them based on user instructions. This system includes an analysis means for analyzing voice and messages and generating commands as appropriate; a control means for executing control instructions; an anomaly detection means for detecting abnormalities based on sensor data; a notification means for issuing notifications in the event of an anomaly; and a summarization and registration means for summarizing information and registering it in a calendar.

[0231] When the server receives a voice command or LINE message from a user, it uses analysis tools to analyze the instruction and determine the necessary action. For example, if a user says, "Turn off the lights," the server recognizes the keywords "lights" and "off" through analysis and generates a control command corresponding to the lighting device. The server then sends the generated command to the terminal to execute the control.

[0232] The terminal is responsible for directly operating home appliances according to control instructions received from the server. It sends appropriate control signals to hardware such as lights, air conditioners, and door locks. It can also automatically turn on lights when the user returns home, based on pre-set rules according to the user's lifestyle.

[0233] Users interact with this system using smartphones or tablets. A key feature is the ability to easily control various devices within the home even when away from home. When a user asks "What's my schedule for this week?" via LINE, the server queries calendar information, generates a concise schedule list using summarization and registration methods, and notifies the user.

[0234] As a concrete example, if a user receives an email one morning informing them of a PTA meeting schedule, the server summarizes the email's contents and automatically registers it in their calendar as "Tomorrow at 3 PM: PTA Meeting." A notification of this registration completion is sent to the user's smartphone via LINE, allowing the user to stay informed of important information in real time.

[0235] This invention dramatically improves the efficiency of household management and provides users with a highly convenient living environment.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] The user sends a message via LINE from their smartphone saying, "Set the air conditioner to 21 degrees."

[0239] Step 2:

[0240] The server receives the LINE message and analyzes the content of the instructions using natural language processing. Here, the server extracts the keywords "air conditioner" and "21 degrees".

[0241] Step 3:

[0242] Based on the analysis results, the server generates the commands necessary to control the air conditioner. In this case, it creates a command to change the temperature setting of the air conditioner.

[0243] Step 4:

[0244] The server sends the generated control commands to the terminal. Assume the terminal is connected to an air conditioner control unit installed in the home.

[0245] Step 5:

[0246] The terminal analyzes the command received from the server and sends a specific operation signal to the air conditioning control unit. The air conditioning control unit changes the temperature setting to 21 degrees according to that signal.

[0247] Step 6:

[0248] The air conditioning control unit signals the terminal when processing is complete.

[0249] Step 7:

[0250] The terminal receives a completion signal from the air conditioner control unit and reports the completion of the operation to the server.

[0251] Step 8:

[0252] The server confirms the completion report from the terminal and sends a notification to the user's LINE account saying, "The air conditioner has been set to 21 degrees."

[0253] This allows users to easily control their home air conditioners remotely, even when they are away from home.

[0254] (Example 1)

[0255] 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."

[0256] There is a need to efficiently manage the operation of various devices and systems within the home and improve user convenience. The challenge lies in reducing the effort required for traditional direct operation, enabling rapid response to malfunctions, and achieving centralized information management.

[0257] 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.

[0258] In this invention, the server includes information processing means for analyzing voice and text instructions and generating control instructions, device control means for receiving the generated control instructions and operating in-home devices, and monitoring means for collecting environmental data and detecting anomalies. This enables efficient management of various devices in the home and rapid response in the event of anomalies.

[0259] "Voice and text instructions" refers to a form of instruction in which a user uses voice or text messages to control a home device.

[0260] "Information processing means" refers to devices or programs that have the function of interpreting instructions in the form of voice or text and generating appropriate control instructions.

[0261] "Control instructions" refer to the specific operational commands necessary to operate a household device based on the analyzed instructions.

[0262] "Device control means" refers to a device or program that has the function of directly operating various household devices based on the generated control instructions.

[0263] "Environmental data" refers to information about the operating status of devices and systems, such as temperature, humidity, and operating conditions within a home.

[0264] "Monitoring means" refers to devices or programs that have the function of continuously collecting environmental data and detecting anomalies based on predetermined criteria.

[0265] "Anomaly" refers to a state that deviates from the normal operation of a household device or system, or to an unexpected event.

[0266] This invention is a communication system for efficiently managing and controlling devices and systems within a home. It consists of server, terminal, and user elements, which work together to function.

[0267] The server is responsible for receiving and analyzing voice and text messages. Specifically, it uses speech recognition software to convert voice commands into text data and natural language processing techniques to extract necessary keywords. The server can utilize speech recognition APIs provided by Amazon and Google. Furthermore, based on the analyzed data, it generates optimal control commands using a generative AI model. These control commands are then transmitted to the terminal via the home network.

[0268] The terminal directly operates various devices within the home based on control instructions received from the server. For example, it communicates with home appliances using Bluetooth or Zigbee protocols to control devices such as lighting and air conditioners. This allows users to enjoy an automated living environment.

[0269] Users access this system using mobile devices such as smartphones and tablets. This allows users to operate devices in their home even when they are away from home. For example, they can send voice or text instructions using messaging apps such as LINE and receive feedback on the situation in their home.

[0270] As a concrete example, consider a scenario where a user, while out and about, asks the system via LINE, "Tell me my schedule for this week." In this case, the server refers to the calendar information, creates a concise schedule list based on the analysis results, and notifies the user via LINE. An example of a prompt message could be, "As a new example, the user has instructed, 'Tell me the weather for this week.' The AI ​​model should use a web API to obtain weather information, summarize it in an easy-to-understand format, and notify the user via LINE." This is how the information could be input to the generating AI model.

[0271] This system significantly improves user convenience and enables flexible and efficient home management.

[0272] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0273] Step 1:

[0274] The server receives voice commands and text messages from users. Voice and text input via smartphones and tablets are transmitted to the server via the communication network. Specifically, this involves a process that converts voice into text data using speech recognition software. As a result, text data is output to analyze the user's intent.

[0275] Step 2:

[0276] The server analyzes the received text data to determine an operation. Natural language processing technology is used for text analysis to extract specific keywords and phrases. As data processing, a generative AI model is used to determine instructions optimal for the user's needs and generate control commands. This clarifies the device to be operated and the specific operation content.

[0277] Step 3:

[0278] The server transmits the generated control commands to the terminal. The transmitted data reaches the terminal via the network, and preparations are made to operate various devices within the home. At the terminal, the data format is converted based on the received command, and a signal for direct operation is generated.

[0279] Step 4:

[0280] The terminal transmits the received signal to the in-home device and executes the actual operation. Specifically, communication protocols such as Bluetooth and Zigbee are utilized to perform appropriate operations on the home appliances. For example, controls such as turning off the power of smart lighting are performed here.

[0281] Step 5:

[0282] The server monitors the results of the executed operation and provides feedback to the user as necessary. When it is confirmed that the operation has been executed normally, the user is notified via LINE, email, etc. For the input information, a pre-designed response is generated, and an output reporting the situation to the user is provided. This allows the user to confirm that each operation has been reliably performed.

[0283] (Application Example 1)

[0284] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] In recent years, with the increase in various household electrical appliances and systems, there is a demand to efficiently manage them and provide a user-friendly living environment. However, conventional systems have the problem that each individual device requires operation, making integrated management difficult. There is also an issue that there is a lack of a convenient means for controlling devices in the home from outside the home.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0287] In this invention, the server includes an analysis means for analyzing voice and information communication and generating an instruction for the control target system, a control means for receiving the control instruction and operating the device based on the instruction, and an abnormality detection means for collecting data and detecting an abnormality based on the data. As a result, even when away from home, the user can easily perform integrated management of the devices in the home and realize a comfortable living environment.

[0288] "Voice and information communication" is a data communication method for analyzing voice instructions and messages from the user to extract information and operating the system based on it.

[0289] The "analysis means" is a function that performs a process of analyzing an instruction obtained by voice or information communication and generating an appropriate operation command.

[0290] The "control means" is a function for managing and operating a device based on an instruction generated by the analysis means.

[0291] The "abnormality detection means" is a function for judging an abnormality of a device or system based on the collected data and prompting necessary countermeasures.

[0292] The "notification means" is a mechanism for notifying information to the user or an external institution when an abnormality is detected.

[0293] "Summarization and registration means" refers to a function that organizes information and registers it in a schedule or calendar as needed.

[0294] A "user" is a person who operates this system and manages devices inside and outside the home.

[0295] A "smart device" is a portable information terminal that can acquire and process information via a network.

[0296] "Integrated management" is the process of managing and efficiently controlling a variety of devices and systems in a unified manner.

[0297] "Environmental information" refers to data about the surrounding conditions, such as temperature, humidity, and lighting conditions inside and outside the home.

[0298] This invention aims to realize an integrated management system that automatically manages the environment inside and outside the home, providing users with a comfortable living environment. Its form is described below.

[0299] The server receives user voice commands and messages and uses analysis tools to analyze them. The analyzed commands are converted into specific control commands by control tools and sent to devices within the home via a terminal. Users can access this system remotely via smart devices such as smartphones and tablets to monitor and control the status of devices within their home.

[0300] The anomaly detection system collects data from sensors and detects environmental anomalies. If an anomaly is detected, a notification is sent to the user or a third-party organization through the notification system.

[0301] Furthermore, the summarization and registration features manage the user's schedule, summarizing necessary information and automatically registering it in the calendar. This ensures that important appointments are not missed.

[0302] As a specific example, when the user gives a voice instruction of "I'm about to go out" before leaving for work in the morning, the server automatically turns off the lighting and air conditioning. Also, if the user gives an instruction of "I'll be home in 5 minutes" before returning home, the air conditioning will automatically turn on to maintain a comfortable room temperature.

[0303] This system is realized by voice recognition technology using the Google Speech-to-Text API, cloud-based data processing using AWS Lambda, and device-to-device communication using the MQTT protocol.

[0304] Using the generative AI model, the following are examples of prompt sentences that can be used:

[0305] "What are the elements to be considered when designing a control process for optimal in-home device management based on the user's voice instruction?"

[0306] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0307] Step 1:

[0308] The server receives the voice instruction from the user via the smartphone. As input, voice data is provided. The server converts this voice data into text data using the Google Speech-to-Text API. As output, an analyzable command text is generated.

[0309] Step 2:

[0310] The server processes the texturized voice instruction with an analysis means and generates an appropriate control command. As input, the text data of the user instruction is used. The server performs keyword extraction and semantic analysis and outputs command data for specific device operations. For example, an instruction of "Turn on the lighting" is converted into a "Lighting on" command.

[0311] Step 3:

[0312] The server sends the generated control command to the terminal. The control command is provided as input, and the command sent to the terminal is its output. The server uses the MQTT protocol for this communication.

[0313] Step 4:

[0314] The terminal operates the device based on the control commands it receives. It receives command data from the server as input. The terminal generates control signals for the device corresponding to the command, operating appliances such as home electronics. The output is the actual operation of the device (e.g., turning on a light).

[0315] Step 5:

[0316] The server collects data from various sensors and determines whether or not there are any abnormalities. The input is data from the sensors. The server detects abnormal values ​​and determines the abnormal state based on the results. The output is the determination of the occurrence of the abnormality.

[0317] Step 6:

[0318] If an anomaly is detected, the server will notify the user or a third party using a notification mechanism. The input is the result of the anomaly detection. The server generates a notification message and outputs the information via the communication platform.

[0319] Step 7:

[0320] When a user requests a schedule check, the server queries calendar information using summarization and registration methods. The input is the user's request. The server organizes the calendar information and outputs a summary. This information is sent to the user's smart device.

[0321] 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.

[0322] This invention relates to a communication system that integrates and manages various devices and systems within a home, and is equipped with an emotion analysis function that recognizes the user's emotions and automatically adjusts the environment. This system includes an analysis means that analyzes voice and messages and generates appropriate commands, a control means that executes control instructions, and an emotion analysis means that analyzes the user's emotions and sends control instructions according to those emotions.

[0323] The server receives voice commands and LINE messages sent by the user. Using emotion analysis technology, it analyzes the user's emotions from this information and tags them with emotions such as "joy," "sadness," and "anger." Then, it determines the optimal environment settings according to the user's emotions and generates corresponding control instructions.

[0324] For example, if a user says "I'm tired today" in an emotionally charged voice, the server tags it with the emotion "tired" and sends a command to the device to adjust the lighting to a warmer color to help it relax.

[0325] Based on commands received from the server, the terminal sends appropriate control signals to home hardware, such as lighting and music players. This control allows for adjustments to lighting brightness and color, or the playback of relaxing music.

[0326] Users can feel these environmental changes firsthand and enjoy a more comfortable home life. Furthermore, users' emotional history is recorded and analyzed using data analytics tools, allowing the service to be personalized over time and leading to greater satisfaction.

[0327] For example, if a user returns home late at night and says, "I feel uneasy," the server analyzes the emotion as "anxiety" or "tension," and instructs the device to change the lighting to a softer tone and play quiet background music.

[0328] In this way, the present invention instantly senses the user's emotions, provides an optimal home environment accordingly, and realizes a more comfortable life for the user.

[0329] The following describes the processing flow.

[0330] Step 1:

[0331] The user uses their smartphone's microphone to say, "I'm tired today."

[0332] Step 2:

[0333] The server receives the audio data and first converts the audio into text using natural language processing. Then, it applies sentiment analysis to tag the user's emotion as "tired" based on the text "tired".

[0334] Step 3:

[0335] Based on emotion tagging, the server evaluates the optimal environment settings to help the user relax. In this case, for example, it might choose to change to a relaxing lighting color.

[0336] Step 4:

[0337] The server generates commands to change the color temperature of the lighting to a warm color and to play quiet background music on the music player, and sends them to the terminal.

[0338] Step 5:

[0339] Based on instructions from the server, the terminal sends appropriate control signals to the lighting control unit and the music playback unit. As a result, the color temperature of the lighting is adjusted to a warm color, and the music playback device begins playing quiet background music.

[0340] Step 6:

[0341] Users can sense the changes in lighting and music, allowing them to experience a relaxing environment.

[0342] This sequence of events allows the system to automatically adjust the home environment to match the user's emotions.

[0343] (Example 2)

[0344] 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".

[0345] In modern living environments, there is a need to comprehensively manage various devices within the home and automatically adjust the environment according to the user's emotions. However, existing systems struggle to effectively detect individual user emotions and optimize the environment based on them. This presents a challenge in ensuring that users can consistently enjoy a comfortable life.

[0346] 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.

[0347] In this invention, the server includes means for analyzing voice and text information to recognize the user's emotions and generate control instructions corresponding to those emotions; means for receiving the generated control instructions and operating a plurality of environmental devices based on those instructions; and analysis means for accumulating user emotion data and optimizing environmental settings based on past data. This makes it possible for the user to enjoy an optimal environment that corresponds to their emotions.

[0348] "Voice information" refers to data obtained by electrically converting the voice emitted by the user, and is one of the types of information that the system analyzes.

[0349] "Text information" refers to information expressed as character data, and includes user messages and transcripts of voice messages.

[0350] "Emotions" are a concept that represents the user's feelings and psychological state, and are treated as a target for analysis in this system.

[0351] A "control instruction" is a command that instructs a target device to perform an action based on its analyzed emotions.

[0352] "Emotional data" refers to data that records a user's emotional tendencies and history, and will be used for future personalization.

[0353] "Analysis means" refers to a mechanism that uses accumulated data to perform processes such as optimizing and predicting environmental settings.

[0354] "Environmental devices" refer to controllable devices within a home, including lighting fixtures and audio equipment.

[0355] This invention is a communication system that integrates and manages various environmental devices within the home and automatically adjusts the environment based on the user's emotions. The aim is to provide the user with a comfortable living environment.

[0356] The server handles voice input and message reception. Specifically, it uses speech recognition software to convert speech to text. A common cloud-based speech recognition API is available for this process, quickly generating text data from speech. Next, sentiment analysis software using natural language processing techniques runs to analyze this text data. In this analysis process, the user's emotions are categorized from the text into categories such as "joy," "sadness," and "anger." Based on this sentiment data, the server determines the most appropriate environment settings and generates specific control instructions.

[0357] Control instructions are sent to environmental devices within the home, such as lighting and music playback devices. The terminal receives these instructions and adjusts the color temperature and brightness of the lighting device. It also issues instructions to the music playback system to select and play music that suits the user's mood. These operations are performed using common protocols for smart device control.

[0358] For example, if a user says "I'm very tired today" at home, the server analyzes this as an emotion of "tiredness" and generates an instruction to change to relaxing warm-colored lighting. Upon receiving this instruction, the terminal operates the lighting and music systems to change the lighting to a warm color and play soothing music. In this way, the system provides the user with an optimal environment and enables a comfortable life.

[0359] An example of a prompt for a generative AI model is: "If the user says, 'I'm very tired today,' please show what kind of sentiment analysis and environmental adjustments the system would perform based on this information."

[0360] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0361] Step 1:

[0362] The server receives voice input from the user and converts it into text.

[0363] Input: User's voice command

[0364] Processing: A cloud-based speech recognition API is used to convert the speech signal into natural language text data.

[0365] Output: Text data converted from speech

[0366] Specifically, the server receives voice data from the voice input device in real time and processes it instantly through the voice recognition system.

[0367] Step 2:

[0368] The server performs sentiment analysis on the text data to identify the user's emotions.

[0369] Input: Converted text data

[0370] Processing: Using natural language processing techniques, emotions such as positive, negative, and neutral are analyzed from the text. An emotion analysis library is used to calculate an emotion score.

[0371] Output: Emotional labels (e.g., "joy", "sadness", "anger")

[0372] Specifically, the server sends text data to an analysis engine, instantly identifies the sentiment category, and stores the result in an internal database.

[0373] Step 3:

[0374] The server generates appropriate control instructions based on the identified emotions.

[0375] Input: Emotion Label

[0376] Processing: Based on emotion labels, the system references pre-configured response rules to assemble specific environmental control instructions, such as lighting and music settings.

[0377] Output: Environmental control instructions (e.g., instructions to set lighting to a warm color)

[0378] In terms of specific operations, the server uses emotion labels to perform analysis within the system to determine an appropriate response and generates a corresponding control code.

[0379] Step 4:

[0380] The terminal executes control instructions received from the server and operates environmental devices within the home.

[0381] Input: Environmental control instructions

[0382] Processing: Sends control instructions to lighting control devices and sound playback devices, causing them to perform actions accordingly.

[0383] Output: Adjusted environment (e.g., lighting chromaticity, music type)

[0384] In terms of specific operations, the terminal transmits signals to various smart devices via network communication, ensuring that lighting and audio systems operate as instructed.

[0385] (Application Example 2)

[0386] 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."

[0387] In modern homes, it is difficult to instantly provide the optimal environment settings that respond to the user's emotions. Furthermore, there is no system that analyzes the user's emotional state and automatically adjusts the environment. As a result, users must manually configure the environment themselves to achieve a comfortable home environment, which presents a challenge in terms of time and effort.

[0388] 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.

[0389] In this invention, the server includes analysis means for analyzing voice and messages and generating instructions for a controlled device; control means for receiving control instructions and operating household appliances based on those instructions; and emotion adjustment means for analyzing emotions and adjusting environmental elements based on the analysis results. This makes it possible to instantly analyze the user's emotions and automatically provide an appropriate environment.

[0390] "Sound" refers to sound waves or signals produced by human speech.

[0391] A "message" is a means of transmitting information to others using text or audio.

[0392] "Analysis means" refers to a device or software that has the function of breaking down speech or messages and extracting and interpreting useful information from them.

[0393] "Control means" refers to a device or software that has the function of operating and managing equipment or systems based on commands.

[0394] "Household appliances" refers to electrical appliances and equipment used within the home.

[0395] An "emotion adjustment device" is a device or software that analyzes a user's emotions and adjusts environmental elements accordingly.

[0396] "Environmental elements" refer to various elements within the home that affect the user's senses and comfort, such as lighting, music, and temperature.

[0397] The system realizing this invention aims to analyze voice and messages and automatically adjust the home environment according to the user's emotions. The server receives user commands via a robot equipped with a microphone and camera for capturing voice data. The voice is converted to text using the Google Cloud Speech-to-Text API, and the text data is analyzed to determine the user's emotional state using IBM Watson's Sentiment Analysis API. Based on the analysis results, commands are generated to adjust the environment to suit the user's emotions and sent to devices in the home. Specific control of home devices is performed through the Home Assistant platform, dynamically adjusting settings such as lighting and music.

[0398] The device controls various devices in the home based on emotion analysis results and control commands received from the server. It makes adjustments necessary to provide an environment that the user finds comfortable, such as adjusting the brightness and color of the lighting, and selecting and adjusting the volume of music. This allows the user to enjoy a relaxed space tailored to their emotional state.

[0399] Through the operation of such systems, users can avoid the hassle of manually configuring their environment and obtain a comfortable and personalized living space. For example, if a user says, "I'm tired today," the server can identify the emotion of "tiredness" and instruct it to change the lighting to a warm color and play relaxing music. This specific example helps to understand how the system works.

[0400] An example of an input prompt for a generative AI model is, "Analyze the user's emotions upon returning home and explain how to adjust the home environment accordingly." This prompt allows the system to refer to specific scenarios.

[0401] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0402] Step 1:

[0403] The server uses the robot's microphone and camera to capture user audio and video data. The input data consists of the user's speech and facial expressions. Based on this data, the audio data is converted to text using the Google Cloud Speech-to-Text API, and the video data is preprocessed for sentiment inference.

[0404] Step 2:

[0405] The server sends the text data generated in Step 1 to IBM Watson's sentiment analysis API. The input is text obtained from the user's utterance. At this stage, the sentiment analysis API analyzes the text data and outputs sentiment tags such as "joy," "sadness," and "fatigue." The analysis results are used as information indicating the user's current emotional state.

[0406] Step 3:

[0407] The server uses the emotion tags obtained in step 2 to create a plan for adjusting the home environment. The inputs are the emotion tags and data on the current home environment. It determines the optimal environmental settings (e.g., lighting brightness, music selection) based on a specific emotion and generates these as instructions. The output is a specific control command regarding the environmental settings.

[0408] Step 4:

[0409] The terminal transmits signals corresponding to home devices based on control commands received from the server. The input is the control command from the server. The terminal uses the Home Assistant platform to perform actions such as adjusting the color and brightness of lighting or selecting and playing appropriate music. The output is the environmental changes perceived by the user.

[0410] Step 5:

[0411] The user can enjoy their daily life in the home environment adjusted in Step 4. The user's comfort level, based on the matching of their emotions with the current environmental settings, is recorded and sent to the server as feedback. This feedback is used to improve the system. The input is the user's emotional response, and the output is long-term user satisfaction.

[0412] 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.

[0413] 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.

[0414] 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.

[0415] [Third Embodiment]

[0416] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0417] 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.

[0418] 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).

[0419] 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.

[0420] 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.

[0421] 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).

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] 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".

[0428] The present invention relates to a communication system that comprehensively manages various devices and systems within a home and automatically controls them based on user instructions. This system includes an analysis means for analyzing voice and messages and generating commands as appropriate; a control means for executing control instructions; an anomaly detection means for detecting abnormalities based on sensor data; a notification means for issuing notifications in the event of an anomaly; and a summarization and registration means for summarizing information and registering it in a calendar.

[0429] When the server receives a voice command or LINE message from a user, it uses analysis tools to analyze the instruction and determine the necessary action. For example, if a user says, "Turn off the lights," the server recognizes the keywords "lights" and "off" through analysis and generates a control command corresponding to the lighting device. The server then sends the generated command to the terminal to execute the control.

[0430] The terminal is responsible for directly operating home appliances according to control instructions received from the server. It sends appropriate control signals to hardware such as lights, air conditioners, and door locks. It can also automatically turn on lights when the user returns home, based on pre-set rules according to the user's lifestyle.

[0431] Users interact with this system using smartphones or tablets. A key feature is the ability to easily control various devices within the home even when away from home. When a user asks "What's my schedule for this week?" via LINE, the server queries calendar information, generates a concise schedule list using summarization and registration methods, and notifies the user.

[0432] As a concrete example, if a user receives an email one morning informing them of a PTA meeting schedule, the server summarizes the email's contents and automatically registers it in their calendar as "Tomorrow at 3 PM: PTA Meeting." A notification of this registration completion is sent to the user's smartphone via LINE, allowing the user to stay informed of important information in real time.

[0433] This invention dramatically improves the efficiency of household management and provides users with a highly convenient living environment.

[0434] The following describes the processing flow.

[0435] Step 1:

[0436] The user sends a message via LINE from their smartphone saying, "Set the air conditioner to 21 degrees."

[0437] Step 2:

[0438] The server receives the LINE message and analyzes the content of the instructions using natural language processing. Here, the server extracts the keywords "air conditioner" and "21 degrees".

[0439] Step 3:

[0440] Based on the analysis results, the server generates the commands necessary to control the air conditioner. In this case, it creates a command to change the temperature setting of the air conditioner.

[0441] Step 4:

[0442] The server sends the generated control commands to the terminal. Assume the terminal is connected to an air conditioner control unit installed in the home.

[0443] Step 5:

[0444] The terminal analyzes the command received from the server and sends a specific operation signal to the air conditioning control unit. The air conditioning control unit changes the temperature setting to 21 degrees according to that signal.

[0445] Step 6:

[0446] The air conditioning control unit signals the terminal when processing is complete.

[0447] Step 7:

[0448] The terminal receives a completion signal from the air conditioner control unit and reports the completion of the operation to the server.

[0449] Step 8:

[0450] The server confirms the completion report from the terminal and sends a notification to the user's LINE account saying, "The air conditioner has been set to 21 degrees."

[0451] This allows users to easily control their home air conditioners remotely, even when they are away from home.

[0452] (Example 1)

[0453] 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."

[0454] There is a need to efficiently manage the operation of various devices and systems within the home and improve user convenience. The challenge lies in reducing the effort required for traditional direct operation, enabling rapid response to malfunctions, and achieving centralized information management.

[0455] 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.

[0456] In this invention, the server includes information processing means for analyzing voice and text instructions and generating control instructions, device control means for receiving the generated control instructions and operating in-home devices, and monitoring means for collecting environmental data and detecting anomalies. This enables efficient management of various devices in the home and rapid response in the event of anomalies.

[0457] "Voice and text instructions" refers to a form of instruction in which a user uses voice or text messages to control a home device.

[0458] "Information processing means" refers to devices or programs that have the function of interpreting instructions in the form of voice or text and generating appropriate control instructions.

[0459] "Control instructions" refer to the specific operational commands necessary to operate a household device based on the analyzed instructions.

[0460] "Device control means" refers to a device or program that has the function of directly operating various household devices based on the generated control instructions.

[0461] "Environmental data" refers to information about the operating status of devices and systems, such as temperature, humidity, and operating conditions within a home.

[0462] "Monitoring means" refers to devices or programs that have the function of continuously collecting environmental data and detecting anomalies based on predetermined criteria.

[0463] "Anomaly" refers to a state that deviates from the normal operation of a household device or system, or to an unexpected event.

[0464] This invention is a communication system for efficiently managing and controlling devices and systems within a home. It consists of server, terminal, and user elements, which work together to function.

[0465] The server is responsible for receiving and analyzing voice and text messages. Specifically, it uses speech recognition software to convert voice commands into text data and natural language processing techniques to extract necessary keywords. The server can utilize speech recognition APIs provided by Amazon and Google. Furthermore, based on the analyzed data, it generates optimal control commands using a generative AI model. These control commands are then transmitted to the terminal via the home network.

[0466] The terminal directly operates various devices within the home based on control instructions received from the server. For example, it communicates with home appliances using Bluetooth or Zigbee protocols to control devices such as lighting and air conditioners. This allows users to enjoy an automated living environment.

[0467] Users access this system using mobile devices such as smartphones and tablets. This allows users to operate devices in their home even when they are away from home. For example, they can send voice or text instructions using messaging apps such as LINE and receive feedback on the situation in their home.

[0468] As a concrete example, consider a scenario where a user, while out and about, asks the system via LINE, "Tell me my schedule for this week." In this case, the server refers to the calendar information, creates a concise schedule list based on the analysis results, and notifies the user via LINE. An example of a prompt message could be, "As a new example, the user has instructed, 'Tell me the weather for this week.' The AI ​​model should use a web API to obtain weather information, summarize it in an easy-to-understand format, and notify the user via LINE." This is how the information could be input to the generating AI model.

[0469] This system significantly improves user convenience and enables flexible and efficient home management.

[0470] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0471] Step 1:

[0472] The server receives voice commands and text messages from users. Voice and text input via smartphones and tablets are transmitted to the server via the communication network. Specifically, this involves a process that converts voice into text data using speech recognition software. As a result, text data is output to analyze the user's intent.

[0473] Step 2:

[0474] The server analyzes the received text data to determine the appropriate action. Natural language processing techniques are used for text analysis to extract specific keywords and phrases. For data processing, a generative AI model is used to determine the most suitable instructions for the user's needs and generate control commands. This clarifies the target device and the specific actions to be performed.

[0475] Step 3:

[0476] The server sends the generated control commands to the terminal. The transmitted data reaches the terminal via the network, preparing it for operation of various devices in the home. The terminal converts the data format based on the received commands and generates signals for direct operation.

[0477] Step 4:

[0478] The terminal transmits the received signal to the home device and performs the actual operation. Specifically, it uses communication protocols such as Bluetooth and Zigbee to perform appropriate operations on home appliances. For example, it controls things like turning off smart lighting.

[0479] Step 5:

[0480] The server monitors the results of the operations performed and provides feedback to the user as needed. Once it confirms that the operation was successfully executed, the user is notified via LINE, email, or other means. A pre-designed response is generated in response to the input information, and output is sent to the user reporting the status. This allows the user to confirm that each operation was performed correctly.

[0481] (Application Example 1)

[0482] 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."

[0483] In recent years, with the increasing number of electrical appliances and systems in homes, there has been a growing need to efficiently manage them and provide users with a user-friendly living environment. However, conventional systems require operation for each individual device, making integrated management difficult. Furthermore, there is a lack of convenient means to control home devices remotely.

[0484] 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.

[0485] In this invention, the server includes analysis means for analyzing voice and information communication and generating instructions for the controlled system; control means for receiving control instructions and operating the device based on those instructions; and anomaly detection means for collecting data and detecting anomalies based on that data. This makes it possible for users to easily integrate and manage devices in their home even when away from home, thereby realizing a comfortable living environment.

[0486] "Voice and information communication" refers to data communication methods that analyze voice instructions and messages from users to extract information and operate the system based on that information.

[0487] "Analysis means" refers to a function that analyzes instructions obtained through voice or information communication and generates appropriate operation commands.

[0488] "Control means" refers to the function of managing and operating the device based on instructions generated by the analysis means.

[0489] An "anomaly detection mechanism" is a function that determines abnormalities in devices and systems based on collected data and prompts necessary actions.

[0490] A "notification mechanism" is a system that notifies users or external organizations of information when an anomaly is detected.

[0491] "Summarization and registration means" refers to a function that organizes information and registers it in a schedule or calendar as needed.

[0492] A "user" is a person who operates this system and manages devices inside and outside the home.

[0493] A "smart device" is a portable information terminal that can acquire and process information via a network.

[0494] "Integrated management" is the process of managing and efficiently controlling a variety of devices and systems in a unified manner.

[0495] "Environmental information" refers to data about the surrounding conditions, such as temperature, humidity, and lighting conditions inside and outside the home.

[0496] This invention aims to realize an integrated management system that automatically manages the environment inside and outside the home, providing users with a comfortable living environment. Its form is described below.

[0497] The server receives user voice commands and messages and uses analysis tools to analyze them. The analyzed commands are converted into specific control commands by control tools and sent to devices within the home via a terminal. Users can access this system remotely via smart devices such as smartphones and tablets to monitor and control the status of devices within their home.

[0498] The anomaly detection system collects data from sensors and detects environmental anomalies. If an anomaly is detected, a notification is sent to the user or a third-party organization through the notification system.

[0499] Furthermore, the summarization and registration features manage the user's schedule, summarizing necessary information and automatically registering it in the calendar. This ensures that important appointments are not missed.

[0500] For example, if a user gives a voice command saying "I'm leaving now" before going to work in the morning, the server will automatically turn off the lights and air conditioning. Also, if they give a command saying "I'll be home in 5 minutes" before returning home, the air conditioning will automatically turn on to maintain a comfortable room temperature.

[0501] This system is implemented using speech recognition technology with the Google Speech-to-Text API, cloud-based data processing using AWS Lambda, and device-to-device communication using the MQTT protocol.

[0502] Using a generative AI model, the following example prompts are available:

[0503] "What factors should be considered when designing a control process for optimal home device management based on user voice commands?"

[0504] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0505] Step 1:

[0506] The server receives voice commands from the user via a smartphone. Voice data is provided as input. The server converts this voice data into text data using the Google Speech-to-Text API. The output is a parseable command text.

[0507] Step 2:

[0508] The server processes the transcribed voice instructions using an analysis tool and generates appropriate control commands. It uses text data of user instructions as input. The server performs keyword extraction and semantic analysis, outputting command data for specific device operation. For example, the instruction "Turn on the lights" is converted into the command "Turn on lights".

[0509] Step 3:

[0510] The server sends the generated control command to the terminal. The control command is provided as input, and the command sent to the terminal is its output. The server uses the MQTT protocol for this communication.

[0511] Step 4:

[0512] The terminal operates the device based on the control commands it receives. It receives command data from the server as input. The terminal generates control signals for the device corresponding to the command, operating appliances such as home electronics. The output is the actual operation of the device (e.g., turning on a light).

[0513] Step 5:

[0514] The server collects data from various sensors and determines whether or not there are any abnormalities. The input is data from the sensors. The server detects abnormal values ​​and determines the abnormal state based on the results. The output is the determination of the occurrence of the abnormality.

[0515] Step 6:

[0516] If an anomaly is detected, the server will notify the user or a third party using a notification mechanism. The input is the result of the anomaly detection. The server generates a notification message and outputs the information via the communication platform.

[0517] Step 7:

[0518] When a user requests a schedule check, the server queries calendar information using summarization and registration methods. The input is the user's request. The server organizes the calendar information and outputs a summary. This information is sent to the user's smart device.

[0519] 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.

[0520] This invention relates to a communication system that integrates and manages various devices and systems within a home, and is equipped with an emotion analysis function that recognizes the user's emotions and automatically adjusts the environment. This system includes an analysis means that analyzes voice and messages and generates appropriate commands, a control means that executes control instructions, and an emotion analysis means that analyzes the user's emotions and sends control instructions according to those emotions.

[0521] The server receives voice commands and LINE messages sent by the user. Using emotion analysis technology, it analyzes the user's emotions from this information and tags them with emotions such as "joy," "sadness," and "anger." Then, it determines the optimal environment settings according to the user's emotions and generates corresponding control instructions.

[0522] For example, if a user says "I'm tired today" in an emotionally charged voice, the server tags it with the emotion "tired" and sends a command to the device to adjust the lighting to a warmer color to help it relax.

[0523] Based on commands received from the server, the terminal sends appropriate control signals to home hardware, such as lighting and music players. This control allows for adjustments to lighting brightness and color, or the playback of relaxing music.

[0524] Users can feel these environmental changes firsthand and enjoy a more comfortable home life. Furthermore, users' emotional history is recorded and analyzed using data analytics tools, allowing the service to be personalized over time and leading to greater satisfaction.

[0525] For example, if a user returns home late at night and says, "I feel uneasy," the server analyzes the emotion as "anxiety" or "tension," and instructs the device to change the lighting to a softer tone and play quiet background music.

[0526] In this way, the present invention instantly senses the user's emotions, provides an optimal home environment accordingly, and realizes a more comfortable life for the user.

[0527] The following describes the processing flow.

[0528] Step 1:

[0529] The user uses their smartphone's microphone to say, "I'm tired today."

[0530] Step 2:

[0531] The server receives the audio data and first converts the audio into text using natural language processing. Then, it applies sentiment analysis to tag the user's emotion as "tired" based on the text "tired".

[0532] Step 3:

[0533] Based on emotion tagging, the server evaluates the optimal environment settings to help the user relax. In this case, for example, it might choose to change to a relaxing lighting color.

[0534] Step 4:

[0535] The server generates commands to change the color temperature of the lighting to a warm color and to play quiet background music on the music player, and sends them to the terminal.

[0536] Step 5:

[0537] Based on instructions from the server, the terminal sends appropriate control signals to the lighting control unit and the music playback unit. As a result, the color temperature of the lighting is adjusted to a warm color, and the music playback device begins playing quiet background music.

[0538] Step 6:

[0539] Users can sense the changes in lighting and music, allowing them to experience a relaxing environment.

[0540] This sequence of events allows the system to automatically adjust the home environment to match the user's emotions.

[0541] (Example 2)

[0542] 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."

[0543] In modern living environments, there is a need to comprehensively manage various devices within the home and automatically adjust the environment according to the user's emotions. However, existing systems struggle to effectively detect individual user emotions and optimize the environment based on them. This presents a challenge in ensuring that users can consistently enjoy a comfortable life.

[0544] 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.

[0545] In this invention, the server includes means for analyzing voice and text information to recognize the user's emotions and generate control instructions corresponding to those emotions; means for receiving the generated control instructions and operating a plurality of environmental devices based on those instructions; and analysis means for accumulating user emotion data and optimizing environmental settings based on past data. This makes it possible for the user to enjoy an optimal environment that corresponds to their emotions.

[0546] "Voice information" refers to data obtained by electrically converting the voice emitted by the user, and is one of the types of information that the system analyzes.

[0547] "Text information" refers to information expressed as character data, and includes user messages and transcripts of voice messages.

[0548] "Emotions" are a concept that represents the user's feelings and psychological state, and are treated as a target for analysis in this system.

[0549] A "control instruction" is a command that instructs a target device to perform an action based on its analyzed emotions.

[0550] "Emotional data" refers to data that records a user's emotional tendencies and history, and will be used for future personalization.

[0551] "Analysis means" refers to a mechanism that uses accumulated data to perform processes such as optimizing and predicting environmental settings.

[0552] "Environmental devices" refer to controllable devices within a home, including lighting fixtures and audio equipment.

[0553] This invention is a communication system that integrates and manages various environmental devices within the home and automatically adjusts the environment based on the user's emotions. The aim is to provide the user with a comfortable living environment.

[0554] The server handles voice input and message reception. Specifically, it uses speech recognition software to convert speech to text. A common cloud-based speech recognition API is available for this process, quickly generating text data from speech. Next, sentiment analysis software using natural language processing techniques runs to analyze this text data. In this analysis process, the user's emotions are categorized from the text into categories such as "joy," "sadness," and "anger." Based on this sentiment data, the server determines the most appropriate environment settings and generates specific control instructions.

[0555] Control instructions are sent to environmental devices within the home, such as lighting and music playback devices. The terminal receives these instructions and adjusts the color temperature and brightness of the lighting device. It also issues instructions to the music playback system to select and play music that suits the user's mood. These operations are performed using common protocols for smart device control.

[0556] For example, if a user says "I'm very tired today" at home, the server analyzes this as an emotion of "tiredness" and generates an instruction to change to relaxing warm-colored lighting. Upon receiving this instruction, the terminal operates the lighting and music systems to change the lighting to a warm color and play soothing music. In this way, the system provides the user with an optimal environment and enables a comfortable life.

[0557] An example of a prompt for a generative AI model is: "If the user says, 'I'm very tired today,' please show what kind of sentiment analysis and environmental adjustments the system would perform based on this information."

[0558] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0559] Step 1:

[0560] The server receives voice input from the user and converts it into text.

[0561] Input: User's voice command

[0562] Processing: A cloud-based speech recognition API is used to convert the speech signal into natural language text data.

[0563] Output: Text data converted from speech

[0564] Specifically, the server receives voice data from the voice input device in real time and processes it instantly through the voice recognition system.

[0565] Step 2:

[0566] The server performs sentiment analysis on the text data to identify the user's emotions.

[0567] Input: Converted text data

[0568] Processing: Using natural language processing techniques, emotions such as positive, negative, and neutral are analyzed from the text. An emotion analysis library is used to calculate an emotion score.

[0569] Output: Emotional labels (e.g., "joy", "sadness", "anger")

[0570] Specifically, the server sends text data to an analysis engine, instantly identifies the sentiment category, and stores the result in an internal database.

[0571] Step 3:

[0572] The server generates appropriate control instructions based on the identified emotions.

[0573] Input: Emotion Label

[0574] Processing: Based on emotion labels, the system references pre-configured response rules to assemble specific environmental control instructions, such as lighting and music settings.

[0575] Output: Environmental control instructions (e.g., instructions to set lighting to a warm color)

[0576] In terms of specific operations, the server uses emotion labels to perform analysis within the system to determine an appropriate response and generates a corresponding control code.

[0577] Step 4:

[0578] The terminal executes control instructions received from the server and operates environmental devices within the home.

[0579] Input: Environmental control instructions

[0580] Processing: Sends control instructions to lighting control devices and sound playback devices, causing them to perform actions accordingly.

[0581] Output: Adjusted environment (e.g., lighting chromaticity, music type)

[0582] In terms of specific operations, the terminal transmits signals to various smart devices via network communication, ensuring that lighting and audio systems operate as instructed.

[0583] (Application Example 2)

[0584] 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."

[0585] In modern homes, it is difficult to instantly provide the optimal environment settings that respond to the user's emotions. Furthermore, there is no system that analyzes the user's emotional state and automatically adjusts the environment. As a result, users must manually configure the environment themselves to achieve a comfortable home environment, which presents a challenge in terms of time and effort.

[0586] 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.

[0587] In this invention, the server includes analysis means for analyzing voice and messages and generating instructions for a controlled device; control means for receiving control instructions and operating household appliances based on those instructions; and emotion adjustment means for analyzing emotions and adjusting environmental elements based on the analysis results. This makes it possible to instantly analyze the user's emotions and automatically provide an appropriate environment.

[0588] "Sound" refers to sound waves or signals produced by human speech.

[0589] A "message" is a means of transmitting information to others using text or audio.

[0590] "Analysis means" refers to a device or software that has the function of breaking down speech or messages and extracting and interpreting useful information from them.

[0591] "Control means" refers to a device or software that has the function of operating and managing equipment or systems based on commands.

[0592] "Household appliances" refers to electrical appliances and equipment used within the home.

[0593] An "emotion adjustment device" is a device or software that analyzes a user's emotions and adjusts environmental elements accordingly.

[0594] "Environmental elements" refer to various elements within the home that affect the user's senses and comfort, such as lighting, music, and temperature.

[0595] The system realizing this invention aims to analyze voice and messages and automatically adjust the home environment according to the user's emotions. The server receives user commands via a robot equipped with a microphone and camera for capturing voice data. The voice is converted to text using the Google Cloud Speech-to-Text API, and the text data is analyzed to determine the user's emotional state using IBM Watson's Sentiment Analysis API. Based on the analysis results, commands are generated to adjust the environment to suit the user's emotions and sent to devices in the home. Specific control of home devices is performed through the Home Assistant platform, dynamically adjusting settings such as lighting and music.

[0596] The device controls various devices in the home based on emotion analysis results and control commands received from the server. It makes adjustments necessary to provide an environment that the user finds comfortable, such as adjusting the brightness and color of the lighting, and selecting and adjusting the volume of music. This allows the user to enjoy a relaxed space tailored to their emotional state.

[0597] Through the operation of such systems, users can avoid the hassle of manually configuring their environment and obtain a comfortable and personalized living space. For example, if a user says, "I'm tired today," the server can identify the emotion of "tiredness" and instruct it to change the lighting to a warm color and play relaxing music. This specific example helps to understand how the system works.

[0598] An example of an input prompt for a generative AI model is, "Analyze the user's emotions upon returning home and explain how to adjust the home environment accordingly." This prompt allows the system to refer to specific scenarios.

[0599] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0600] Step 1:

[0601] The server uses the robot's microphone and camera to capture user audio and video data. The input data consists of the user's speech and facial expressions. Based on this data, the audio data is converted to text using the Google Cloud Speech-to-Text API, and the video data is preprocessed for sentiment inference.

[0602] Step 2:

[0603] The server sends the text data generated in Step 1 to IBM Watson's sentiment analysis API. The input is text obtained from the user's utterance. At this stage, the sentiment analysis API analyzes the text data and outputs sentiment tags such as "joy," "sadness," and "fatigue." The analysis results are used as information indicating the user's current emotional state.

[0604] Step 3:

[0605] The server uses the emotion tags obtained in step 2 to create a plan for adjusting the home environment. The inputs are the emotion tags and data on the current home environment. It determines the optimal environmental settings (e.g., lighting brightness, music selection) based on a specific emotion and generates these as instructions. The output is a specific control command regarding the environmental settings.

[0606] Step 4:

[0607] The terminal transmits signals corresponding to home devices based on control commands received from the server. The input is the control command from the server. The terminal uses the Home Assistant platform to perform actions such as adjusting the color and brightness of lighting or selecting and playing appropriate music. The output is the environmental changes perceived by the user.

[0608] Step 5:

[0609] The user can enjoy their daily life in the home environment adjusted in Step 4. The user's comfort level, based on the matching of their emotions with the current environmental settings, is recorded and sent to the server as feedback. This feedback is used to improve the system. The input is the user's emotional response, and the output is long-term user satisfaction.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] [Fourth Embodiment]

[0614] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0615] 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.

[0616] 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).

[0617] 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.

[0618] 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.

[0619] 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).

[0620] 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.

[0621] 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.

[0622] 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.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] 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".

[0627] The present invention relates to a communication system that comprehensively manages various devices and systems within a home and automatically controls them based on user instructions. This system includes an analysis means for analyzing voice and messages and generating commands as appropriate; a control means for executing control instructions; an anomaly detection means for detecting abnormalities based on sensor data; a notification means for issuing notifications in the event of an anomaly; and a summarization and registration means for summarizing information and registering it in a calendar.

[0628] When the server receives a voice command or LINE message from a user, it uses analysis tools to analyze the instruction and determine the necessary action. For example, if a user says, "Turn off the lights," the server recognizes the keywords "lights" and "off" through analysis and generates a control command corresponding to the lighting device. The server then sends the generated command to the terminal to execute the control.

[0629] The terminal is responsible for directly operating home appliances according to control instructions received from the server. It sends appropriate control signals to hardware such as lights, air conditioners, and door locks. It can also automatically turn on lights when the user returns home, based on pre-set rules according to the user's lifestyle.

[0630] Users interact with this system using smartphones or tablets. A key feature is the ability to easily control various devices within the home even when away from home. When a user asks "What's my schedule for this week?" via LINE, the server queries calendar information, generates a concise schedule list using summarization and registration methods, and notifies the user.

[0631] As a concrete example, if a user receives an email one morning informing them of a PTA meeting schedule, the server summarizes the email's contents and automatically registers it in their calendar as "Tomorrow at 3 PM: PTA Meeting." A notification of this registration completion is sent to the user's smartphone via LINE, allowing the user to stay informed of important information in real time.

[0632] This invention dramatically improves the efficiency of household management and provides users with a highly convenient living environment.

[0633] The following describes the processing flow.

[0634] Step 1:

[0635] The user sends a message via LINE from their smartphone saying, "Set the air conditioner to 21 degrees."

[0636] Step 2:

[0637] The server receives the LINE message and analyzes the content of the instructions using natural language processing. Here, the server extracts the keywords "air conditioner" and "21 degrees".

[0638] Step 3:

[0639] Based on the analysis results, the server generates the commands necessary to control the air conditioner. In this case, it creates a command to change the temperature setting of the air conditioner.

[0640] Step 4:

[0641] The server sends the generated control commands to the terminal. Assume the terminal is connected to an air conditioner control unit installed in the home.

[0642] Step 5:

[0643] The terminal analyzes the command received from the server and sends a specific operation signal to the air conditioning control unit. The air conditioning control unit changes the temperature setting to 21 degrees according to that signal.

[0644] Step 6:

[0645] The air conditioning control unit signals the terminal when processing is complete.

[0646] Step 7:

[0647] The terminal receives a completion signal from the air conditioner control unit and reports the completion of the operation to the server.

[0648] Step 8:

[0649] The server confirms the completion report from the terminal and sends a notification to the user's LINE account saying, "The air conditioner has been set to 21 degrees."

[0650] This allows users to easily control their home air conditioners remotely, even when they are away from home.

[0651] (Example 1)

[0652] 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".

[0653] There is a need to efficiently manage the operation of various devices and systems within the home and improve user convenience. The challenge lies in reducing the effort required for traditional direct operation, enabling rapid response to malfunctions, and achieving centralized information management.

[0654] 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.

[0655] In this invention, the server includes information processing means for analyzing voice and text instructions and generating control instructions, device control means for receiving the generated control instructions and operating in-home devices, and monitoring means for collecting environmental data and detecting anomalies. This enables efficient management of various devices in the home and rapid response in the event of anomalies.

[0656] "Voice and text instructions" refers to a form of instruction in which a user uses voice or text messages to control a home device.

[0657] "Information processing means" refers to devices or programs that have the function of interpreting instructions in the form of voice or text and generating appropriate control instructions.

[0658] "Control instructions" refer to the specific operational commands necessary to operate a household device based on the analyzed instructions.

[0659] "Device control means" refers to a device or program that has the function of directly operating various household devices based on the generated control instructions.

[0660] "Environmental data" refers to information about the operating status of devices and systems, such as temperature, humidity, and operating conditions within a home.

[0661] "Monitoring means" refers to devices or programs that have the function of continuously collecting environmental data and detecting anomalies based on predetermined criteria.

[0662] "Anomaly" refers to a state that deviates from the normal operation of a household device or system, or to an unexpected event.

[0663] This invention is a communication system for efficiently managing and controlling devices and systems within a home. It consists of server, terminal, and user elements, which work together to function.

[0664] The server is responsible for receiving and analyzing voice and text messages. Specifically, it uses speech recognition software to convert voice commands into text data and natural language processing techniques to extract necessary keywords. The server can utilize speech recognition APIs provided by Amazon and Google. Furthermore, based on the analyzed data, it generates optimal control commands using a generative AI model. These control commands are then transmitted to the terminal via the home network.

[0665] The terminal directly operates various devices within the home based on control instructions received from the server. For example, it communicates with home appliances using Bluetooth or Zigbee protocols to control devices such as lighting and air conditioners. This allows users to enjoy an automated living environment.

[0666] Users access this system using mobile devices such as smartphones and tablets. This allows users to operate devices in their home even when they are away from home. For example, they can send voice or text instructions using messaging apps such as LINE and receive feedback on the situation in their home.

[0667] As a concrete example, consider a scenario where a user, while out and about, asks the system via LINE, "Tell me my schedule for this week." In this case, the server refers to the calendar information, creates a concise schedule list based on the analysis results, and notifies the user via LINE. An example of a prompt message could be, "As a new example, the user has instructed, 'Tell me the weather for this week.' The AI ​​model should use a web API to obtain weather information, summarize it in an easy-to-understand format, and notify the user via LINE." This is how the information could be input to the generating AI model.

[0668] This system significantly improves user convenience and enables flexible and efficient home management.

[0669] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0670] Step 1:

[0671] The server receives voice commands and text messages from users. Voice and text input via smartphones and tablets are transmitted to the server via the communication network. Specifically, this involves a process that converts voice into text data using speech recognition software. As a result, text data is output to analyze the user's intent.

[0672] Step 2:

[0673] The server analyzes the received text data to determine the appropriate action. Natural language processing techniques are used for text analysis to extract specific keywords and phrases. For data processing, a generative AI model is used to determine the most suitable instructions for the user's needs and generate control commands. This clarifies the target device and the specific actions to be performed.

[0674] Step 3:

[0675] The server sends the generated control commands to the terminal. The transmitted data reaches the terminal via the network, preparing it for operation of various devices in the home. The terminal converts the data format based on the received commands and generates signals for direct operation.

[0676] Step 4:

[0677] The terminal transmits the received signal to the home device and performs the actual operation. Specifically, it uses communication protocols such as Bluetooth and Zigbee to perform appropriate operations on home appliances. For example, it controls things like turning off smart lighting.

[0678] Step 5:

[0679] The server monitors the results of the operations performed and provides feedback to the user as needed. Once it confirms that the operation was successfully executed, the user is notified via LINE, email, or other means. A pre-designed response is generated in response to the input information, and output is sent to the user reporting the status. This allows the user to confirm that each operation was performed correctly.

[0680] (Application Example 1)

[0681] 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".

[0682] In recent years, with the increasing number of electrical appliances and systems in homes, there has been a growing need to efficiently manage them and provide users with a user-friendly living environment. However, conventional systems require operation for each individual device, making integrated management difficult. Furthermore, there is a lack of convenient means to control home devices remotely.

[0683] 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.

[0684] In this invention, the server includes analysis means for analyzing voice and information communication and generating instructions for the controlled system; control means for receiving control instructions and operating the device based on those instructions; and anomaly detection means for collecting data and detecting anomalies based on that data. This makes it possible for users to easily integrate and manage devices in their home even when away from home, thereby realizing a comfortable living environment.

[0685] "Voice and information communication" refers to data communication methods that analyze voice instructions and messages from users to extract information and operate the system based on that information.

[0686] "Analysis means" refers to a function that analyzes instructions obtained through voice or information communication and generates appropriate operation commands.

[0687] "Control means" refers to the function of managing and operating the device based on instructions generated by the analysis means.

[0688] An "anomaly detection mechanism" is a function that determines abnormalities in devices and systems based on collected data and prompts necessary actions.

[0689] A "notification mechanism" is a system that notifies users or external organizations of information when an anomaly is detected.

[0690] "Summarization and registration means" refers to a function that organizes information and registers it in a schedule or calendar as needed.

[0691] A "user" is a person who operates this system and manages devices inside and outside the home.

[0692] A "smart device" is a portable information terminal that can acquire and process information via a network.

[0693] "Integrated management" is the process of managing and efficiently controlling a variety of devices and systems in a unified manner.

[0694] "Environmental information" refers to data about the surrounding conditions, such as temperature, humidity, and lighting conditions inside and outside the home.

[0695] This invention aims to realize an integrated management system that automatically manages the environment inside and outside the home, providing users with a comfortable living environment. Its form is described below.

[0696] The server receives user voice commands and messages and uses analysis tools to analyze them. The analyzed commands are converted into specific control commands by control tools and sent to devices within the home via a terminal. Users can access this system remotely via smart devices such as smartphones and tablets to monitor and control the status of devices within their home.

[0697] The anomaly detection system collects data from sensors and detects environmental anomalies. If an anomaly is detected, a notification is sent to the user or a third-party organization through the notification system.

[0698] Furthermore, the summarization and registration features manage the user's schedule, summarizing necessary information and automatically registering it in the calendar. This ensures that important appointments are not missed.

[0699] For example, if a user gives a voice command saying "I'm leaving now" before going to work in the morning, the server will automatically turn off the lights and air conditioning. Also, if they give a command saying "I'll be home in 5 minutes" before returning home, the air conditioning will automatically turn on to maintain a comfortable room temperature.

[0700] This system is implemented using speech recognition technology with the Google Speech-to-Text API, cloud-based data processing using AWS Lambda, and device-to-device communication using the MQTT protocol.

[0701] Using a generative AI model, the following example prompts are available:

[0702] "What factors should be considered when designing a control process for optimal home device management based on user voice commands?"

[0703] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0704] Step 1:

[0705] The server receives voice commands from the user via a smartphone. Voice data is provided as input. The server converts this voice data into text data using the Google Speech-to-Text API. The output is a parseable command text.

[0706] Step 2:

[0707] The server processes the transcribed voice instructions using an analysis tool and generates appropriate control commands. It uses text data of user instructions as input. The server performs keyword extraction and semantic analysis, outputting command data for specific device operation. For example, the instruction "Turn on the lights" is converted into the command "Turn on lights".

[0708] Step 3:

[0709] The server sends the generated control command to the terminal. The control command is provided as input, and the command sent to the terminal is its output. The server uses the MQTT protocol for this communication.

[0710] Step 4:

[0711] The terminal operates the device based on the control commands it receives. It receives command data from the server as input. The terminal generates control signals for the device corresponding to the command, operating appliances such as home electronics. The output is the actual operation of the device (e.g., turning on a light).

[0712] Step 5:

[0713] The server collects data from various sensors and determines whether or not there are any abnormalities. The input is data from the sensors. The server detects abnormal values ​​and determines the abnormal state based on the results. The output is the determination of the occurrence of the abnormality.

[0714] Step 6:

[0715] If an anomaly is detected, the server will notify the user or a third party using a notification mechanism. The input is the result of the anomaly detection. The server generates a notification message and outputs the information via the communication platform.

[0716] Step 7:

[0717] When a user requests a schedule check, the server queries calendar information using summarization and registration methods. The input is the user's request. The server organizes the calendar information and outputs a summary. This information is sent to the user's smart device.

[0718] 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.

[0719] This invention relates to a communication system that integrates and manages various devices and systems within a home, and is equipped with an emotion analysis function that recognizes the user's emotions and automatically adjusts the environment. This system includes an analysis means that analyzes voice and messages and generates appropriate commands, a control means that executes control instructions, and an emotion analysis means that analyzes the user's emotions and sends control instructions according to those emotions.

[0720] The server receives voice commands and LINE messages sent by the user. Using emotion analysis technology, it analyzes the user's emotions from this information and tags them with emotions such as "joy," "sadness," and "anger." Then, it determines the optimal environment settings according to the user's emotions and generates corresponding control instructions.

[0721] For example, if a user says "I'm tired today" in an emotionally charged voice, the server tags it with the emotion "tired" and sends a command to the device to adjust the lighting to a warmer color to help it relax.

[0722] Based on commands received from the server, the terminal sends appropriate control signals to home hardware, such as lighting and music players. This control allows for adjustments to lighting brightness and color, or the playback of relaxing music.

[0723] Users can feel these environmental changes firsthand and enjoy a more comfortable home life. Furthermore, users' emotional history is recorded and analyzed using data analytics tools, allowing the service to be personalized over time and leading to greater satisfaction.

[0724] For example, if a user returns home late at night and says, "I feel uneasy," the server analyzes the emotion as "anxiety" or "tension," and instructs the device to change the lighting to a softer tone and play quiet background music.

[0725] In this way, the present invention instantly senses the user's emotions, provides an optimal home environment accordingly, and realizes a more comfortable life for the user.

[0726] The following describes the processing flow.

[0727] Step 1:

[0728] The user uses their smartphone's microphone to say, "I'm tired today."

[0729] Step 2:

[0730] The server receives the audio data and first converts the audio into text using natural language processing. Then, it applies sentiment analysis to tag the user's emotion as "tired" based on the text "tired".

[0731] Step 3:

[0732] Based on emotion tagging, the server evaluates the optimal environment settings to help the user relax. In this case, for example, it might choose to change to a relaxing lighting color.

[0733] Step 4:

[0734] The server generates commands to change the color temperature of the lighting to a warm color and to play quiet background music on the music player, and sends them to the terminal.

[0735] Step 5:

[0736] Based on instructions from the server, the terminal sends appropriate control signals to the lighting control unit and the music playback unit. As a result, the color temperature of the lighting is adjusted to a warm color, and the music playback device begins playing quiet background music.

[0737] Step 6:

[0738] Users can sense the changes in lighting and music, allowing them to experience a relaxing environment.

[0739] This sequence of events allows the system to automatically adjust the home environment to match the user's emotions.

[0740] (Example 2)

[0741] 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".

[0742] In modern living environments, there is a need to comprehensively manage various devices within the home and automatically adjust the environment according to the user's emotions. However, existing systems struggle to effectively detect individual user emotions and optimize the environment based on them. This presents a challenge in ensuring that users can consistently enjoy a comfortable life.

[0743] 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.

[0744] In this invention, the server includes means for analyzing voice and text information to recognize the user's emotions and generate control instructions corresponding to those emotions; means for receiving the generated control instructions and operating a plurality of environmental devices based on those instructions; and analysis means for accumulating user emotion data and optimizing environmental settings based on past data. This makes it possible for the user to enjoy an optimal environment that corresponds to their emotions.

[0745] "Voice information" refers to data obtained by electrically converting the voice emitted by the user, and is one of the types of information that the system analyzes.

[0746] "Text information" refers to information expressed as character data, and includes user messages and transcripts of voice messages.

[0747] "Emotions" are a concept that represents the user's feelings and psychological state, and are treated as a target for analysis in this system.

[0748] A "control instruction" is a command that instructs a target device to perform an action based on its analyzed emotions.

[0749] "Emotional data" refers to data that records a user's emotional tendencies and history, and will be used for future personalization.

[0750] "Analysis means" refers to a mechanism that uses accumulated data to perform processes such as optimizing and predicting environmental settings.

[0751] "Environmental devices" refer to controllable devices within a home, including lighting fixtures and audio equipment.

[0752] This invention is a communication system that integrates and manages various environmental devices within the home and automatically adjusts the environment based on the user's emotions. The aim is to provide the user with a comfortable living environment.

[0753] The server handles voice input and message reception. Specifically, it uses speech recognition software to convert speech to text. A common cloud-based speech recognition API is available for this process, quickly generating text data from speech. Next, sentiment analysis software using natural language processing techniques runs to analyze this text data. In this analysis process, the user's emotions are categorized from the text into categories such as "joy," "sadness," and "anger." Based on this sentiment data, the server determines the most appropriate environment settings and generates specific control instructions.

[0754] Control instructions are sent to environmental devices within the home, such as lighting and music playback devices. The terminal receives these instructions and adjusts the color temperature and brightness of the lighting device. It also issues instructions to the music playback system to select and play music that suits the user's mood. These operations are performed using common protocols for smart device control.

[0755] For example, if a user says "I'm very tired today" at home, the server analyzes this as an emotion of "tiredness" and generates an instruction to change to relaxing warm-colored lighting. Upon receiving this instruction, the terminal operates the lighting and music systems to change the lighting to a warm color and play soothing music. In this way, the system provides the user with an optimal environment and enables a comfortable life.

[0756] An example of a prompt for a generative AI model is: "If the user says, 'I'm very tired today,' please show what kind of sentiment analysis and environmental adjustments the system would perform based on this information."

[0757] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0758] Step 1:

[0759] The server receives voice input from the user and converts it into text.

[0760] Input: User's voice command

[0761] Processing: A cloud-based speech recognition API is used to convert the speech signal into natural language text data.

[0762] Output: Text data converted from speech

[0763] Specifically, the server receives voice data from the voice input device in real time and processes it instantly through the voice recognition system.

[0764] Step 2:

[0765] The server performs sentiment analysis on the text data to identify the user's emotions.

[0766] Input: Converted text data

[0767] Processing: Using natural language processing techniques, emotions such as positive, negative, and neutral are analyzed from the text. An emotion analysis library is used to calculate an emotion score.

[0768] Output: Emotional labels (e.g., "joy", "sadness", "anger")

[0769] Specifically, the server sends text data to an analysis engine, instantly identifies the sentiment category, and stores the result in an internal database.

[0770] Step 3:

[0771] The server generates appropriate control instructions based on the identified emotions.

[0772] Input: Emotion Label

[0773] Processing: Based on emotion labels, the system references pre-configured response rules to assemble specific environmental control instructions, such as lighting and music settings.

[0774] Output: Environmental control instructions (e.g., instructions to set lighting to a warm color)

[0775] In terms of specific operations, the server uses emotion labels to perform analysis within the system to determine an appropriate response and generates a corresponding control code.

[0776] Step 4:

[0777] The terminal executes control instructions received from the server and operates environmental devices within the home.

[0778] Input: Environmental control instructions

[0779] Processing: Sends control instructions to lighting control devices and sound playback devices, causing them to perform actions accordingly.

[0780] Output: Adjusted environment (e.g., lighting chromaticity, music type)

[0781] In terms of specific operations, the terminal transmits signals to various smart devices via network communication, ensuring that lighting and audio systems operate as instructed.

[0782] (Application Example 2)

[0783] 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".

[0784] In modern homes, it is difficult to instantly provide the optimal environment settings that respond to the user's emotions. Furthermore, there is no system that analyzes the user's emotional state and automatically adjusts the environment. As a result, users must manually configure the environment themselves to achieve a comfortable home environment, which presents a challenge in terms of time and effort.

[0785] 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.

[0786] In this invention, the server includes analysis means for analyzing voice and messages and generating instructions for a controlled device; control means for receiving control instructions and operating household appliances based on those instructions; and emotion adjustment means for analyzing emotions and adjusting environmental elements based on the analysis results. This makes it possible to instantly analyze the user's emotions and automatically provide an appropriate environment.

[0787] "Sound" refers to sound waves or signals produced by human speech.

[0788] A "message" is a means of transmitting information to others using text or audio.

[0789] "Analysis means" refers to a device or software that has the function of breaking down speech or messages and extracting and interpreting useful information from them.

[0790] "Control means" refers to a device or software that has the function of operating and managing equipment or systems based on commands.

[0791] "Household appliances" refers to electrical appliances and equipment used within the home.

[0792] An "emotion adjustment device" is a device or software that analyzes a user's emotions and adjusts environmental elements accordingly.

[0793] "Environmental elements" refer to various elements within the home that affect the user's senses and comfort, such as lighting, music, and temperature.

[0794] The system realizing this invention aims to analyze voice and messages and automatically adjust the home environment according to the user's emotions. The server receives user commands via a robot equipped with a microphone and camera for capturing voice data. The voice is converted to text using the Google Cloud Speech-to-Text API, and the text data is analyzed to determine the user's emotional state using IBM Watson's Sentiment Analysis API. Based on the analysis results, commands are generated to adjust the environment to suit the user's emotions and sent to devices in the home. Specific control of home devices is performed through the Home Assistant platform, dynamically adjusting settings such as lighting and music.

[0795] The device controls various devices in the home based on emotion analysis results and control commands received from the server. It makes adjustments necessary to provide an environment that the user finds comfortable, such as adjusting the brightness and color of the lighting, and selecting and adjusting the volume of music. This allows the user to enjoy a relaxed space tailored to their emotional state.

[0796] Through the operation of such systems, users can avoid the hassle of manually configuring their environment and obtain a comfortable and personalized living space. For example, if a user says, "I'm tired today," the server can identify the emotion of "tiredness" and instruct it to change the lighting to a warm color and play relaxing music. This specific example helps to understand how the system works.

[0797] An example of an input prompt for a generative AI model is, "Analyze the user's emotions upon returning home and explain how to adjust the home environment accordingly." This prompt allows the system to refer to specific scenarios.

[0798] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0799] Step 1:

[0800] The server uses the robot's microphone and camera to capture user audio and video data. The input data consists of the user's speech and facial expressions. Based on this data, the audio data is converted to text using the Google Cloud Speech-to-Text API, and the video data is preprocessed for sentiment inference.

[0801] Step 2:

[0802] The server sends the text data generated in Step 1 to IBM Watson's sentiment analysis API. The input is text obtained from the user's utterance. At this stage, the sentiment analysis API analyzes the text data and outputs sentiment tags such as "joy," "sadness," and "fatigue." The analysis results are used as information indicating the user's current emotional state.

[0803] Step 3:

[0804] The server uses the emotion tags obtained in step 2 to create a plan for adjusting the home environment. The inputs are the emotion tags and data on the current home environment. It determines the optimal environmental settings (e.g., lighting brightness, music selection) based on a specific emotion and generates these as instructions. The output is a specific control command regarding the environmental settings.

[0805] Step 4:

[0806] The terminal transmits signals corresponding to home devices based on control commands received from the server. The input is the control command from the server. The terminal uses the Home Assistant platform to perform actions such as adjusting the color and brightness of lighting or selecting and playing appropriate music. The output is the environmental changes perceived by the user.

[0807] Step 5:

[0808] The user can enjoy their daily life in the home environment adjusted in Step 4. The user's comfort level, based on the matching of their emotions with the current environmental settings, is recorded and sent to the server as feedback. This feedback is used to improve the system. The input is the user's emotional response, and the output is long-term user satisfaction.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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."

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] The following is further disclosed regarding the embodiments described above.

[0831] (Claim 1)

[0832] Analysis means for analyzing voice and messages and generating instructions for the controlled device,

[0833] A control means that receives a control instruction and operates a home appliance based on the instruction,

[0834] An anomaly detection means that collects sensor data and detects anomalies based on said data,

[0835] A notification mechanism for notifying the user or a third-party organization when an anomaly is detected,

[0836] A summarization and registration method that summarizes information and automatically registers it as calendar information,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, comprising control means for adjusting the set temperature of a temperature control device based on a voice command.

[0840] (Claim 3)

[0841] The system according to claim 1, comprising means for analyzing user email information, extracting important information, and registering it in a schedule.

[0842] "Example 1"

[0843] (Claim 1)

[0844] Information processing means for analyzing voice and text instructions and generating control instructions,

[0845] A device control means that receives generated control instructions and operates a household device,

[0846] A monitoring means for collecting environmental data and detecting anomalies,

[0847] A notification management system that issues warnings when an anomaly is detected,

[0848] A recording method that summarizes information and automatically registers it as schedule information,

[0849] A system that includes this.

[0850] (Claim 2)

[0851] The system according to claim 1, which has a function to change the settings of an air conditioning system based on voice commands.

[0852] (Claim 3)

[0853] The system according to claim 1, which has a function to analyze user message information, extract important information, and reflect it in the schedule plan.

[0854] "Application Example 1"

[0855] (Claim 1)

[0856] An analysis means for analyzing voice and information communications and generating instructions for a controlled system,

[0857] Control means that receive control instructions and operate the device based on those instructions,

[0858] An anomaly detection means that collects data and detects anomalies based on said data,

[0859] A notification system that notifies users or organizations when an abnormality is detected,

[0860] A summarization and registration means that summarizes information and automatically registers it as time management information,

[0861] A means of communication with a smart device that manages equipment and systems based on user instructions,

[0862] A means of obtaining information from any location and providing activity information and environmental information to users,

[0863] A system that includes this.

[0864] (Claim 2)

[0865] The system according to claim 1, comprising means for adjusting the settings of an environmental control device based on voice commands and for integrated management of devices inside and outside the home.

[0866] (Claim 3)

[0867] The system according to claim 1, comprising means for analyzing user information, extracting important information, and recording and managing it.

[0868] "Example 2 of combining an emotion engine"

[0869] (Claim 1)

[0870] A means for analyzing voice and text information to recognize the user's emotions and generate control instructions corresponding to those emotions,

[0871] A means for receiving generated control instructions and operating multiple environmental devices based on those instructions,

[0872] An analytical means that accumulates user sentiment data and optimizes environmental settings based on past data,

[0873] A feedback mechanism that dynamically adjusts the home environment based on the user's new emotions,

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, further comprising means for controlling the luminance and color tone of a lighting device based on user emotion analysis.

[0877] (Claim 3)

[0878] The system according to claim 1, comprising means for analyzing the user's emotional history and predicting future environmental settings.

[0879] "Application example 2 when combining with an emotional engine"

[0880] (Claim 1)

[0881] Analysis means for analyzing voice and messages and generating instructions for controlled devices,

[0882] Control means for receiving control instructions and operating household appliances based on those instructions,

[0883] An anomaly detection means that collects sensor data and detects anomalies based on said data,

[0884] A notification mechanism for notifying the user or a third-party organization when an abnormality is detected,

[0885] An emotion adjustment method that analyzes emotions and adjusts environmental elements based on the analysis results,

[0886] A summarization and registration method that summarizes information and automatically registers it as scheduled information,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, comprising control means for adjusting the set temperature of a climate control device based on voice commands.

[0890] (Claim 3)

[0891] The system according to claim 1, comprising means for analyzing a user's email information, extracting important information, and registering it for scheduling. [Explanation of Symbols]

[0892] 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. Analysis means for analyzing voice and messages and generating instructions for the controlled device, A control means that receives a control instruction and operates a home appliance based on the instruction, An anomaly detection means that collects sensor data and detects anomalies based on said data, A notification mechanism for notifying the user or a third-party organization when an anomaly is detected, A summarization and registration method that summarizes information and automatically registers it as calendar information, A system that includes this.

2. The system according to claim 1, comprising control means for adjusting the set temperature of a temperature control device based on a voice command.

3. The system according to claim 1, comprising means for analyzing user email information, extracting important information, and registering it in a schedule.

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