System

Abstract

A system is provided.SOLUTION: The system includes a sound inputting means, an image inputting means, a moving image inputting means, a artificial general intelligence means, a means for learning living habits, a means for automating housework in a house, a means for assisting going out, and a means for coping with emergencies.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The "Problem that the invention aims to solve" and "Means for solving the problem" of the document will be written in the following format.

[0005] In today's aging society, the number of elderly people and people with disabilities who require care is increasing. As a result, the nursing care industry is facing serious problems of labor shortages and workload, resulting in a decline in the quality of nursing care services and overwork among nursing staff. These issues not only reduce the quality of life for the elderly and disabled, but also have a negative impact on the working environment of nursing care staff. Therefore, there is a need to develop a new system that can efficiently support the daily lives of the elderly and disabled and reduce the burden on the nursing care industry. [Means for solving the problem]

[0006] The present invention is a system that includes voice input means, image input means, video input means, general artificial intelligence means, means for learning lifestyle habits, means for automating household chores at home, means for assisting with going out, and means for responding to emergencies. This system learns the lifestyle habits of elderly people and people with disabilities and automates the household chores necessary for daily life. For example, it performs tasks such as cleaning, cooking, and laundry based on voice instructions. It also assists with going out by providing weather and traffic information and preparing necessary items. Furthermore, it has a function to detect abnormalities using sensors in emergencies and quickly notify emergency contacts. This system can support the independent living of elderly people and people with disabilities, reduce the burden on care staff, and improve the quality of care services.

[0007] The "voice input means" is a device for detecting the user's voice and inputting the voice data into the system.

[0008] "Image input means" is a device for acquiring image data from a user and inputting the image data into the system.

[0009] "Video input means" is a device for acquiring a user's video data and inputting the video data into the system.

[0010] "General artificial intelligence means" is an artificial intelligence system that analyzes a variety of data and understands user behavior and needs.

[0011] "Means for learning lifestyle habits" refers to the process of collecting and analyzing the user's daily behavior patterns and habits.

[0012] "Means for automating household chores" refers to systems that automatically perform household tasks such as cleaning, cooking, and laundry.

[0013] "Means to assist going out" refers to a system that prepares the information and items a user needs when going out and supports the user in going out.

[0014] The "means for responding to an emergency" is a system that detects an emergency situation and takes appropriate action when an emergency occurs to the user.

[0015] The "sensor means" is a device that monitors the user's condition and environment and detects abnormalities.

[0016] "Means for notifying emergency contacts" refers to a process for reporting the situation to designated emergency contacts when an abnormality is detected in the user.

[0017] A "means for automatically executing cleaning tasks" is a system that automatically cleans the home using a cleaning robot or the like.

[0018] The "means for recognizing voice instructions" refers to a process of acquiring a user's voice instructions through a voice input means, and analyzing and understanding the contents of the instructions. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting people going out, and a means for responding to emergencies. Specific embodiments of the system are described below.

[0041] System Overview

[0042] When the user performs the initial system setup, the server stores basic information in a database and sends it to the device. The device uses voice, image, and video input to learn and analyze the user's lifestyle habits in real time. The general artificial intelligence device recognizes the user's behavioral patterns based on this data and provides optimal support for housework and outings. Additionally, if the sensor device detects an abnormality, it promptly notifies emergency contacts.

[0043] Housework support

[0044] For example, if a user issues a voice command such as "Please clean the living room," the device analyzes the voice data and executes the cleaning task. The server monitors the progress from the device and notifies the user when cleaning is complete. This cleaning task is then automatically executed by the cleaning robot.

[0045] Going out assistance

[0046] When the user instructs the device to "get ready to go out," the device receives the instruction via voice input means and sends a request to the server to check the weather and traffic conditions at the destination. The server obtains this information and sends it to the device, which then uses it to prepare items needed for going out (such as keys, a mobile phone, medicine, etc.). The device also notifies the user when these preparations are complete.

[0047] Emergency response

[0048] When the sensor means detects a fall or other abnormality, the device switches to emergency mode and confirms the user's condition by voice. It asks, "Mr. / Ms. XX, are you OK?" If there is no response or if the user responds with "Help me," the device sends an emergency notification to the server, which then automatically notifies the emergency contacts. The emergency contacts are provided with the user's current location and status in real time.

[0049] Example

[0050] For example, when a user starts their morning routine, the device will use a sensor to detect when the user wakes up and automatically start the coffee maker to brew coffee. It will also help prepare breakfast and get dressed. Before going out, it will obtain weather and traffic information and prepare the necessary equipment. Throughout this series of actions, the server constantly monitors the data and makes any necessary adjustments.

[0051] Through these functions, this system can support users in living independently and reduce the burden on the nursing care industry.

[0052] The processing flow will be explained below.

[0053] Housework support

[0054] Step 1:

[0055] The user issues a voice command such as "Please clean the living room."

[0056] Step 2:

[0057] The terminal detects the user's voice using the voice input means and performs voice recognition.

[0058] Step 3:

[0059] The device sends the recognized voice data to the server.

[0060] Step 4:

[0061] The server analyzes the voice commands and determines the "cleaning task."

[0062] Step 5:

[0063] The server issues instructions to the cleaning robot, which then starts cleaning the living room.

[0064] Step 6:

[0065] During cleaning, the server monitors the progress.

[0066] Step 7:

[0067] When cleaning is complete, the cleaning robot sends a completion report to the server.

[0068] Step 8:

[0069] The server receives the completion report and notifies the user via the terminal by voice, "The living room has been cleaned."

[0070] Going out assistance

[0071] Step 1:

[0072] The user issues a voice command such as "Get ready to go out."

[0073] Step 2:

[0074] The terminal detects the user's voice using the voice input means and performs voice recognition.

[0075] Step 3:

[0076] The device sends the recognized voice data to the server.

[0077] Step 4:

[0078] The server analyzes the voice instructions and retrieves information for going out (weather, traffic) from the Internet.

[0079] Step 5:

[0080] The server transmits the acquired information to the terminal.

[0081] Step 6:

[0082] The device prepares the necessary equipment for going out (e.g., keys, mobile phone, medicine, etc.).

[0083] Step 7:

[0084] The device notifies the user that it is ready to go, saying "You're ready to go out."

[0085] Emergency response

[0086] Step 1:

[0087] The device's sensor means detects an abnormality (e.g., a fall, prolonged inactivity).

[0088] Step 2:

[0089] The device will switch to emergency mode and ask a voice message asking, "Mr. / Ms. XX, are you okay?"

[0090] Step 3:

[0091] The user responds or does not respond.

[0092] Step 4:

[0093] If there is no response, the device sends an emergency notification to the server.

[0094] Step 5:

[0095] The server sends a notification to the emergency contact, which includes the user's current location and a description of the situation.

[0096] Step 6:

[0097] The server notifies the terminal of the completion of the contact and reports the information to the user by voice.

[0098] Learning about lifestyle habits

[0099] Step 1:

[0100] The user goes about their daily life.

[0101] Step 2:

[0102] The terminal observes and records the user's behavior using audio, image, and video input means.

[0103] Step 3:

[0104] The terminal transmits the recorded data to the server.

[0105] Step 4:

[0106] The server analyzes the data and uses AGI to learn user behavior patterns.

[0107] Step 5:

[0108] The server feeds the learning results back to the device and reflects them in the next support.

[0109] The above is a detailed description of the processing steps of the "AssistNext" system.

[0110] Example 1

[0111] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0112] Modern home life involves many tasks that require time and effort, such as housework, preparing to go out, and responding to emergencies. Performing these daily tasks independently is particularly difficult for the elderly and those with physical limitations. Furthermore, there is a lack of comprehensive systems for efficiently performing these tasks. Furthermore, the separate functions for housework support and emergency response pose a challenge, resulting in low user convenience.

[0113] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0114] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for analyzing and managing data for each processing step, a means for communicating with a cloud server, a means for notifying the user, and a means for automatically executing tasks. This allows the user to use multiple functions, such as support for household chores, preparation for going out, and emergency response, all in one system.

[0115] The "voice input means" is a device for recognizing the user's voice and converting it into digital data.

[0116] "Image input means" refers to a device for capturing still images and processing them as digital data.

[0117] "Video input means" is a device that captures a series of images and digitally processes them as video data.

[0118] "General artificial intelligence means" is a system that analyzes a variety of data, recognizes patterns using learning algorithms, and performs adaptive processing.

[0119] "Means for learning lifestyle habits" refers to technology that collects and analyzes data on the user's daily behavior and recognizes its patterns.

[0120] "Means for automating household chores" are devices or systems for mechanically performing household tasks such as cleaning and cooking.

[0121] The "means for assisting going out" is a system that provides information and prepares items to help the user prepare to go out.

[0122] "Means for responding to emergencies" refers to devices or systems that can quickly detect abnormalities and take appropriate action when a user is in an emergency.

[0123] "Means for analyzing and managing data at each processing step" refers to technology for analyzing and managing the data generated at each processing step.

[0124] "Means for communicating with a cloud server" refers to a device or system for sending and receiving data to and from a cloud server via the Internet.

[0125] "Means for notifying the user" refers to a technique for notifying the user of necessary information from the system.

[0126] A "means for automatically executing a task" is a system that automatically processes and executes a task based on a user's instructions and circumstances.

[0127] MODE FOR CARRYING OUT THE INVENTION

[0128] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting users when going out, and a means for responding to emergencies. The system aims to support and streamline the daily life of a user. Specific embodiments for carrying out the present invention will be described below.

[0129] Initial System Setup

[0130] The server collects basic information about the user and stores it in a database. This basic information includes name, age, address, contact details, etc. The server sends this information to the device, which then updates the system with the received information. The communication protocol is HTTP or WebSocket.

[0131] Learning about lifestyle habits

[0132] The device collects user behavior data in real time using audio input means (e.g., microphone), image input means (e.g., camera), and video input means (e.g., video camera). The general artificial intelligence means analyzes this data and learns the user's lifestyle habits. Specifically, it uses machine learning libraries such as TensorFlow and PyTorch. The analysis results are sent to a server and stored in a database.

[0133] Housework support

[0134] When a user makes a voice request such as "Please clean the living room," the device receives the voice data through the microphone. This data is analyzed by a voice recognition engine (e.g., Google Speech-to-Text API) and recognized as a cleaning task. The device then sends a command to a cleaning robot (e.g., Roomba) via Bluetooth or Wi-Fi to start cleaning the living room. The server monitors the cleaning robot's progress, and when the task is completed, it notifies the user that "cleaning of the living room is complete."

[0135] Going out assistance

[0136] When the user issues a voice command such as "Get ready to go out," the device receives the instruction through the microphone. The device then sends a request to the server to obtain weather and traffic information. The server obtains this information using the OpenWeatherMap API and Google Maps API and sends it to the device. Based on the obtained information, the device automatically prepares necessary items such as keys, a cell phone, and medicine. Once preparations are complete, the device notifies the user that "You're ready to go out."

[0137] Emergency response

[0138] When the sensor means detects that the user has fallen or something is wrong, the device switches to emergency mode. The device asks aloud, "Mr. / Ms. XX, are you OK?" and if there is no response or if the user responds with something like "Help me," it sends an emergency notification to the server. Based on this, the server automatically notifies emergency contacts, notifying them of the user's current location and situation in detail. During this process, emergency notifications are made via SMS, phone, and email.

[0139] Example

[0140] Let's take the example of a user starting their morning routine. The device uses sensors to detect that the user has woken up and automatically starts the coffee maker to brew coffee. It also helps the user prepare breakfast and get dressed, and obtains weather and traffic information to get ready to go out. The server monitors these actions and makes adjustments as necessary.

[0141] Prompt Sentence Examples

[0142] Examples of prompts to input into a generative AI model include:

[0143] Prompt statement:

[0144] "Please wake me up at 6am tomorrow morning, make me some coffee, check the weather and prepare the necessary items, and notify me before you leave."

[0145] This system will support users' independent and efficient lifestyles and help reduce the burden on the nursing care industry.

[0146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0147] Step 1:

[0148] The server collects the user's basic information (name, age, address, contact details) and stores it in a database. The input is the user's registration information, and the output is the user information in the database. Specifically, the user enters information in a web browser, and the server receives it via an HTTP request. The server processes this information and saves it in a database.

[0149] Step 2:

[0150] The server sends basic information to the terminal. The input is user information in the database, and the output is the basic information sent to the terminal. The communication protocol uses HTTP or WebSocket. The server reads information from the database and sends it to the terminal.

[0151] Step 3:

[0152] The terminal receives basic information and reflects it in the system. The input is the basic information received from the server, and the output is the settings within the terminal. The terminal analyzes the received information and saves it in its internal database.

[0153] Step 4:

[0154] The device collects data using voice input, image input, and video input. The input is data on the user's daily activities, and the output is collected digital data. Specifically, a microphone or camera records the user's activities, and the device collects that data.

[0155] Step 5:

[0156] A general-purpose artificial intelligence analyzes collected data and learns user behavior patterns. The input is the collected digital data, and the output is the analysis results. Python libraries (TensorFlow and PyTorch) are used to perform data analysis and pattern recognition.

[0157] Step 6:

[0158] The terminal sends the analysis results to the server. The input is the analysis result data, and the output is the data sent to the server. The terminal sends the results to the server using HTTP or WebSocket.

[0159] Step 7:

[0160] The user issues a voice request such as "Please clean the living room." The input is the user's voice request, and the output is voice data. The microphone receives the user's voice and converts it into digital data.

[0161] Step 8:

[0162] The device analyzes the voice data and recognizes it as a cleaning task. The input is the voice data and the output is task information. The voice data is analyzed using a voice recognition engine (Google Speech-to-Text API) and task information is generated.

[0163] Step 9:

[0164] The device sends a command to the cleaning robot to start cleaning the living room. The input is task information, and the output is a command to the cleaning robot. The command is sent to the cleaning robot via Bluetooth or Wi-Fi.

[0165] Step 10:

[0166] The server monitors the operation of the cleaning robot and checks its progress. The input is the status data of the cleaning robot and the output is a progress report. The server receives the operating status of the cleaning robot in real time via WebSocket and monitors its progress.

[0167] Step 11:

[0168] When cleaning is complete, the server notifies the user, "Cleaning of the living room is complete." The input is the cleaning completion status data, and the output is a notification to the user. The notification is sent via a smartphone app or email.

[0169] Step 12:

[0170] The user issues a voice request such as "Get ready to go out." The input is the user's voice request, and the output is voice data. The microphone captures the voice and processes it as digital data.

[0171] Step 13:

[0172] The device analyzes the voice data and recognizes it as a task for preparing to go out. The input is the voice data, and the output is the preparation task information. The device uses a voice recognition engine to recognize the task.

[0173] Step 14:

[0174] The device sends a request to the server to obtain weather and traffic information. The input is the preparation task information, and the output is the information acquisition request. The request is sent to the server via an HTTP request.

[0175] Step 15:

[0176] The server retrieves the necessary data using the weather information API and traffic information API. The input is an information retrieval request, and the output is weather and traffic information. The server retrieves information using the OpenWeatherMap API and Google Maps API.

[0177] Step 16:

[0178] The weather and traffic information acquired by the server is sent to the terminal. The input is weather and traffic information, and the output is sending information to the terminal. Information is sent to the terminal via HTTP or WebSocket.

[0179] Step 17:

[0180] Based on the information acquired by the terminal, items necessary for going out (e.g., keys, cell phone, medicine, etc.) are prepared. The input is weather information and preparation task information, and the output is a list of prepared items. The location of items is managed with tags, and an automatic picking system is used.

[0181] Step 18:

[0182] When the preparation is complete, the device notifies the user that "You're ready to go out." The input is the preparation status, and the output is a notification to the user. This is done via a smartphone app or a voice notification.

[0183] Step 19:

[0184] When the sensor detects the user falling or an abnormality, the device switches to emergency mode. The input is abnormal data from the sensor, and the output is switching to emergency mode. An abnormality is detected using the acceleration sensor.

[0185] Step 20:

[0186] The device asks the user by voice, "Hey, are you OK?" The input is emergency mode and the output is a voice message. The speaker is used to play the voice message.

[0187] Step 21:

[0188] The device receives and analyzes the user's response via a voice input means. The input is the user's voice response, and the output is the analysis result. A voice recognition engine is used to analyze the voice data and identify keywords such as "help."

[0189] Step 22:

[0190] If there is no response or if there is a response calling for help, the device will send an emergency notification to the server. The input is the analysis result and the output is the emergency notification. Real-time communication is used to contact the server immediately.

[0191] Step 23:

[0192] The server automatically notifies emergency contacts and provides detailed information about the user's current location and situation. The input is an emergency notification, and the output is a notification to the emergency contacts. Notifications are made via SMS, phone, email, etc.

[0193] This system allows users to efficiently perform various tasks while maintaining their independence, and ensures safety by responding quickly in emergencies.

[0194] (Application example 1)

[0195] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0196] This invention aims to solve the problem that current housekeeping support and food delivery systems have difficulty in effectively reflecting users' voice instructions and lifestyle habits, and in particular the lack of optimal menu suggestions that correspond to individual eating habits and health management. It is also necessary to solve the problem that there is a lack of functionality for tracking the progress of ingredients management and delivery in real time, providing advice on ingredients that are in short supply, and responding to emergencies.

[0197] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0198] In this invention, the server includes a voice input unit, an image input unit, an order history learning unit, an ingredient recognition unit, a delivery progress tracking unit, and a unit for supporting healthy eating habits. This allows for optimal menu suggestions and automatic task execution based on the user's voice instructions. It also enables real-time ingredient management and rapid response in emergencies, making it possible to effectively address individual eating habits and health management.

[0199] "Voice input means" refers to a device or software for converting a user's voice into digital data.

[0200] "Image input means" refers to a device or software for capturing still images and inputting them as digital data.

[0201] "Video input means" refers to a device or software for capturing video images and inputting them as digital data.

[0202] An "artificial general intelligence means" is an artificial intelligence system designed to handle a wide variety of tasks.

[0203] The "means for learning lifestyle habits" is a system for collecting and analyzing data on users' daily behavior and habits.

[0204] "Means for automating household chores" refers to devices or systems that automate everyday household tasks such as cleaning and cooking.

[0205] "Means to assist with going out" refers to a system that provides necessary information and assists with preparations when going out.

[0206] "Measures to respond in emergencies" refers to a system for responding quickly when an accident or abnormality occurs.

[0207] The "means for learning order history" is a system that analyzes a user's past order data and learns their preferences and tendencies.

[0208] The "means for recognizing ingredients" is a system that analyzes image and video data to identify the type of food.

[0209] "Means for tracking delivery progress" refers to a system that monitors the progress of delivery in real time and notifies the user.

[0210] The "means for supporting healthy eating habits" is a system that suggests nutritionally balanced meals based on the user's health condition and eating habits data.

[0211] The present invention is designed as a system to support the daily life of a user. A specific embodiment of this system is shown below. This system includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for learning order history, a means for recognizing ingredients, a means for tracking delivery progress, and a means for supporting healthy eating habits.

[0212] Hardware and software used

[0213] The main components of the system include:

[0214] Voice input method: Google Speech-to-Text API

[0215] Image input method: Smartphone camera, TensorFlow

[0216] Video input method: Smartphone video camera, TensorFlow

[0217] General artificial intelligence means: GPT-4 (Generative Pre-trained Transformer 4)

[0218] How we learn your habits: Firebase, Google Cloud Storage

[0219] Automating household chores: Robot vacuum cleaners (e.g., Roomba)

[0220] Ways to help you get out: Google Maps API, Weather API

[0221] Emergency Response: Twilio API

[0222] How to learn order history: Firebase, Google Cloud Storage

[0223] Methods for identifying ingredients: TensorFlow, image recognition algorithms

[0224] Ways to track delivery progress: Firebase, Realtime Database

[0225] A tool to support healthy eating habits: Nutritional Analysis API

[0226] System Operation

[0227] Voice instructions and order history learning

[0228] When a user speaks to their smartphone, saying "Order dinner," the smartphone's voice input device converts this speech into digital data. This data is then converted into text using the Google Speech-to-Text API. The text data is then analyzed by GPT-4, which uses a model trained on the user's past ordering history and preferences to suggest the optimal menu.

[0229] Ingredient recognition and management

[0230] When a user scans the inside of their refrigerator with their smartphone camera, the image input means sends the captured image to TensorFlow, which recognizes ingredients and determines what is missing. The recognized data is stored in Firebase and used to provide advice to the user.

[0231] Delivery progress tracking and emergency response

[0232] Once an order is placed, the server sends a request to the delivery service, and the delivery progress is tracked in real time via Firebase. Users can check the current delivery status through their smartphone app. Furthermore, if an emergency occurs during delivery, a notification will be sent to emergency contacts using the Twilio API.

[0233] Supporting healthy eating habits

[0234] A nutrition analysis API is used to analyze the user's eating habits data, allowing the system to suggest nutritionally balanced meals based on the user's health status and eating habits.

[0235] Specific examples

[0236] When User A says "Order dinner" via voice input, the GPT-4-based system references their past order history and suggests the most suitable menu for the user. For example, if they have frequently ordered Italian food in the past, menu items such as pizza and pasta will be suggested. When the user confirms "Order this," the order is confirmed and the delivery progress is tracked on Firebase.

[0237] Examples of prompt statements

[0238] Generate a response when a user asks for a dinner order, making menu suggestions that take into account their ordering history and preferences.

[0239] This seamlessly integrates a series of operations from voice instructions to delivery, greatly improving user convenience.

[0240] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0241] Step 1:

[0242] The user speaks to their smartphone and says, "Order dinner."

[0243] Input: User's voice data

[0244] How it works: The smartphone's voice input method captures audio.

[0245] Output: Converts audio data into digital data

[0246] Step 2:

[0247] The converted audio data is sent to the Google Speech-to-Text API and converted into text data.

[0248] Input: Digital audio data

[0249] How it works: Converts speech to text using the Google Speech-to-Text API

[0250] Output: Text data

[0251] Step 3:

[0252] Text data is input into GPT-4, and the optimal menu is suggested based on a model that has learned the user's past ordering history and preferences.

[0253] Input: User's instruction text data, past order history

[0254] How it works: The GPT-4 model analyzes text data and generates the optimal menu.

[0255] Output: Menu suggestion text

[0256] Step 4:

[0257] Menu suggestions are displayed to the user for selection or confirmation.

[0258] Input: Menu suggestion text

[0259] Behavior: Displays a menu on the smartphone screen and accepts user input.

[0260] Output: User selection or confirmation information

[0261] Step 5:

[0262] When the user selects or confirms a menu item, the information is sent to the server to confirm the order.

[0263] Input: User selection or confirmation information

[0264] How it works: The server receives the order information and sends a request to the delivery service.

[0265] Output: Confirmed order information

[0266] Step 6:

[0267] Based on the confirmed order information, the server stores delivery progress tracking information in Firebase and updates it in real time.

[0268] Input: Confirmed order information

[0269] How it works: Store order data in Firebase and get real-time progress information from the delivery service.

[0270] Output: Delivery progress information

[0271] Step 7:

[0272] Delivery progress information will be available to check on a smartphone app and notified to users.

[0273] Input: Delivery progress information

[0274] Behavior: Display progress on smartphone app and notify user

[0275] Output: Delivery progress notification

[0276] Step 8:

[0277] In the event of an emergency, the server uses the Twilio API to send a notification to emergency contacts.

[0278] Input: Emergency detection information

[0279] How it works: Sends SMS and phone calls to emergency contacts via the Twilio API

[0280] Output: Emergency notification sent

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

[0282] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting people going out, a means for responding to emergencies, and an emotion engine that recognizes the emotions of the user. Specific embodiments of this system are described below.

[0283] System Overview

[0284] When the user performs the initial system setup, the server stores basic information in a database and sends it to the device. The device uses voice, image, and video input to learn and analyze the user's lifestyle habits in real time. The general artificial intelligence means recognizes the user's behavioral patterns based on this data and provides optimal support for housework and outings. The emotion engine also recognizes the user's emotions and responds as needed. Furthermore, if the sensor means detects an abnormality, it promptly notifies emergency contacts.

[0285] Housework support

[0286] For example, if a user issues a voice command such as "Please clean the living room," the device analyzes the voice data and executes the cleaning task. The server monitors the progress from the device and notifies the user when cleaning is complete. This cleaning task is then automatically executed by the cleaning robot.

[0287] Going out assistance

[0288] When the user instructs the device to "get ready to go out," the device receives the instruction via voice input means and sends a request to the server to check the weather and traffic conditions at the destination. The server obtains this information and sends it to the device, which then uses it to prepare items needed for going out (such as keys, a mobile phone, medicine, etc.). The device also notifies the user when these preparations are complete.

[0289] Emergency response

[0290] When the sensor means detects a fall or other abnormality, the device switches to emergency mode and confirms the user's condition by voice. It asks, "Mr. / Ms. XX, are you OK?" If there is no response or if the user responds with "Help me," the device sends an emergency notification to the server, which then automatically notifies the emergency contacts. The emergency contacts are provided with the user's current location and status in real time.

[0291] Introducing the Emotion Engine

[0292] The emotion engine analyzes the user's emotions from their voice and facial expressions. For example, if a user says, "I'm a little tired," the device will analyze the user's tone of voice and facial expressions to recognize that emotion. If the emotion engine detects the user's stress or anxiety, it will play relaxing music or provide the necessary support.

[0293] Example

[0294] Housework support

[0295] When a user says in a tired voice, "Please clean the living room," the device uses its emotion engine to analyze the user's level of fatigue and sends the data to the server. The server then executes the cleaning task and gently notifies the user with a voice message saying, "The living room has been cleaned. Please take a short rest."

[0296] Going out assistance

[0297] When the user instructs the device to "get ready to go out" and the emotion engine detects that the user is stressed, the device will make suggestions to help the user relax (for example, by taking deep breaths beforehand or playing music to relieve stress), thereby helping the user to feel at ease when going out.

[0298] Emergency response

[0299] If the device's sensor detects a fall and the emotion engine analyzes the user's voice tone and determines that the user is in a panic, the server will notify emergency contacts of the situation and promptly notify caregivers and family members. The analysis results from the emotion engine are useful in determining the priority of emergency responses.

[0300] Through these functions, this system can support users in living independently and reduce the burden on the nursing care industry.

[0301] The processing flow will be explained below.

[0302] Housework support

[0303] Step 1:

[0304] The user issues a voice command such as "Please clean the living room."

[0305] Step 2:

[0306] The terminal detects the user's voice using the voice input means and performs voice recognition.

[0307] Step 3:

[0308] The device uses an emotion engine to analyze the user's voice tone and recognize that the user is tired.

[0309] Step 4:

[0310] The device sends the recognized voice data and emotion data to the server.

[0311] Step 5:

[0312] The server analyzes voice commands and emotional data to determine the "cleaning task" and considers responses that will help the user relax.

[0313] Step 6:

[0314] The server issues instructions to the cleaning robot, which then starts cleaning the living room.

[0315] Step 7:

[0316] During cleaning, the server monitors the progress.

[0317] Step 8:

[0318] When cleaning is complete, the cleaning robot sends a completion report to the server.

[0319] Step 9:

[0320] The server receives the completion report and gently notifies the user via the terminal with a voice message saying, "The living room has been cleaned. Please take a short rest."

[0321] Going out assistance

[0322] Step 1:

[0323] The user issues a voice command such as "Get ready to go out."

[0324] Step 2:

[0325] The terminal detects the user's voice using the voice input means and performs voice recognition.

[0326] Step 3:

[0327] The device uses an emotion engine to analyze the user's voice tone and recognize that they are feeling stressed.

[0328] Step 4:

[0329] The device sends the recognized voice data and emotion data to the server.

[0330] Step 5:

[0331] The server analyzes voice instructions and emotional data and obtains information for going out (weather, traffic) from the Internet.

[0332] Step 6:

[0333] The server transmits the acquired information to the terminal.

[0334] Step 7:

[0335] The device prepares the necessary equipment for going out (such as keys, cell phone, medicine, etc.) and also makes suggestions for relaxation (such as taking deep breaths beforehand or playing music to relieve stress).

[0336] Step 8:

[0337] The device will notify the user that it is ready to go, saying, "You're ready to go! Relax and enjoy your trip."

[0338] Emergency response

[0339] Step 1:

[0340] The device's sensor means detects an abnormality (e.g., a fall, prolonged inactivity).

[0341] Step 2:

[0342] The terminal uses an emotion engine to analyze the user's voice tone and determine the user's emotional state.

[0343] Step 3:

[0344] The device will ask aloud, "Mr. / Ms. XX, are you okay?"

[0345] Step 4:

[0346] The user responds or does not respond.

[0347] Step 5:

[0348] If there is no response, the device sends an emergency notification to the server, which also includes emotional data.

[0349] Step 6:

[0350] The server sends a notification to emergency contacts, which includes the user's current location, a description of the situation, and their emotional state.

[0351] Step 7:

[0352] The server notifies the terminal of the completion of the contact and reports the information to the user by voice.

[0353] Learning about lifestyle habits

[0354] Step 1:

[0355] The user goes about their daily life.

[0356] Step 2:

[0357] The terminal observes and records the user's behavior using audio, image, and video input means.

[0358] Step 3:

[0359] The device also uses an emotion engine to record the user's emotional state from their facial expressions and voice.

[0360] Step 4:

[0361] The device transmits the recorded data and emotion data to the server.

[0362] Step 5:

[0363] The server analyzes the data and uses AGI to learn the user's behavioral and emotional patterns.

[0364] Step 6:

[0365] The server feeds back the learning results to the device and reflects them in the next support session.

[0366] The above is a detailed description of the processing steps that combine the emotion engine in the "AssistNext" system.

[0367] Example 2

[0368] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0369] In modern society, with the increasing number of elderly people and busy families, there is a demand for systems to support daily life. Conventional systems are limited to automating specific tasks or providing partial support, and do not provide sufficient comprehensive support for daily life. In addition, they are unable to respond quickly in emergencies or understand the user's emotional state, leaving issues in improving user safety and quality of life.

[0370] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0371] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for recognizing a user's emotions, a means for monitoring the progress of tasks being performed and providing feedback, and a means for analyzing a user's instructions and executing tasks. This allows for comprehensive support of the user's daily life, enabling a rapid response in emergencies and appropriate support based on the user's emotional state.

[0372] Below are definitions of important words included in the rewritten claims.

[0373] "Voice input means" refers to a device or software that captures the user's voice and analyzes the voice data.

[0374] "Image input means" refers to a device or software that captures a still image of the user and analyzes it.

[0375] "Video input means" refers to a device or software that captures and analyzes dynamic video data of a user.

[0376] "General artificial intelligence means" is an artificial intelligence technology that learns and analyzes a user's behavioral patterns and lifestyle habits to provide optimal support.

[0377] The "means for learning lifestyle habits" is a device or software that observes the user's daily actions and habits and learns lifestyle patterns based on that data.

[0378] A "means for automating household chores" is a device or software for automatically performing household chores such as cleaning and laundry based on instructions from a user.

[0379] "Means for assisting going out" refers to devices or software that provide the user with the information they need when going out and support their preparations.

[0380] "Emergency response measures" refer to devices or software that detect emergencies based on sensors and analytical results and respond promptly.

[0381] The "means for recognizing the user's emotions" refers to a device or software for analyzing and recognizing the user's emotional state from their voice and facial expressions.

[0382] The "means for monitoring the progress of an executed task and providing feedback" refers to a device or software for monitoring the progress of a specified task in real time and providing feedback to the user at appropriate times.

[0383] "Means for analyzing user instructions and executing tasks" refers to a device or software that analyzes instructions from a user in the form of voice or other input and executes an appropriate task based on those instructions.

[0384] MODE FOR CARRYING OUT THE INVENTION

[0385] The present invention is a system that comprehensively supports a user's daily life. This system includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating housework, a means for assisting with going out, a means for responding to emergencies, a means for recognizing the user's emotions, a means for monitoring the progress of an executed task and providing feedback, and a means for analyzing the user's instructions and executing the task.

[0386] Hardware Configuration

[0387] Users use a device to input voice, images, and video. This device is equipped with a microphone, camera, and sensors. The device sends the data over a network to a server for further processing. The server is a computer system equipped with a high-performance CPU and a large amount of memory, and can run on a cloud platform.

[0388] Software Configuration

[0389] The device uses speech recognition APIs (e.g., Google Cloud Speech-to-Text or IBM Watson Speech to Text), image analysis APIs, and video analysis APIs. The server uses general artificial intelligence methods (e.g., TensorFlow or PyTorch) to learn the user's behavioral patterns and update a database (e.g., MongoDB or MySQL). The Microsoft Azure Emotion API can be used as an emotion engine. Kafka or RabbitMQ can be used as a real-time data streaming technology to monitor the progress of tasks.

[0390] Specific examples

[0391] Housework support

[0392] When a user issues a voice command such as "Please clean the living room," the device captures the voice and converts it into text data using a speech recognition API. The converted data is sent to a server, which analyzes the command and assigns a cleaning task to a cleaning robot (e.g., an iRobot Roomba). The cleaning progress is monitored in real time, and the user is notified when the cleaning is complete.

[0393] Going out assistance

[0394] When a user verbally commands "get ready to go out," the device captures the voice and converts it into text data using a speech recognition API. The converted data is sent to a server, which then uses an external API (e.g., OpenWeatherMap or Google Maps API) to obtain weather and traffic information for the destination. The device then prepares items needed for going out (e.g., keys, cell phone, medicine, etc.) based on the obtained information and notifies the user when they are ready.

[0395] Emergency response

[0396] When the device's built-in sensor detects an abnormality, such as a fall, the device switches to emergency mode. An emergency notification is sent to the server, which then automatically notifies emergency contacts using a business API (e.g., Twilio API). In the event of an emergency, the user's current location and status are provided in real time.

[0397] Introducing the Emotion Engine

[0398] If a user says, "I'm a little tired," the device will analyze their voice tone and facial expressions with its emotion engine to recognize their emotion. If it determines that the user is feeling stressed, the device will play relaxing music or provide appropriate support.

[0399] Prompt Sentence Examples

[0400] "User automation assistance system"

[0401] input:

[0402] User voice commands (e.g., "Please clean the living room")

[0403] The user's emotional state (e.g., "I feel a little tired")

[0404] Output:

[0405] Interprets voice commands and performs specific tasks

[0406] Analyze emotions with an emotion engine and provide optimal responses

[0407] As described above, this system can provide multifunctional and flexible support to help users live independently.

[0408] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0409] Step 1: User voice input

[0410] The user issues commands by voice. For example, the user might say to the device, "Please clean the living room."

[0411] Input: User's voice data

[0412] Output: Audio data is captured

[0413] What happens: The device's microphone captures audio data, which is temporarily stored on the device.

[0414] Step 2: Analyzing the audio data

[0415] The device converts the captured voice data into text data using a voice recognition API.

[0416] Input: Captured audio data

[0417] Output: Converted text data

[0418] How it works: The device calls the Google Cloud Speech-to-Text API to convert the voice data into text, which is then immediately sent to the server.

[0419] Step 3: Learning behavioral patterns and updating the database

[0420] The server analyzes the received text data and updates a database for learning user behavior patterns.

[0421] Input: Converted text data

[0422] Output: Updated database

[0423] Specific operation: The server uses TensorFlow to analyze the received text data, learn behavioral patterns, store the results in MongoDB, and update the database.

[0424] Step 4: Task execution instructions

[0425] The server sends instructions to the terminal to execute a task based on the analysis results.

[0426] Input: Analysis results

[0427] Output: Instructions to the terminal

[0428] Specific operation: The server uses the REST API to send specific execution instructions (e.g., "Send the cleaning robot to the living room") to the device.

[0429] Step 5: Monitoring and feedback on the execution of tasks

[0430] The server monitors the progress of the execution tasks received from the terminal and provides the information as feedback to the user in real time.

[0431] Input: Progress data of the execution task

[0432] Output: Feedback to the user

[0433] Specific operation: The device sends progress data from the cleaning robot to the server, which receives it and notifies the user that "cleaning is complete."

[0434] Step 6: Emergency response

[0435] If the device's sensor detects an abnormality, it switches to emergency mode and sends an emergency notification to the server.

[0436] Input: Anomaly detection data from sensors

[0437] Output: Send emergency notification

[0438] How it works: If a device's sensor detects, for example, a fall, it sends that data to a server via AWS IoT, which then uses the Twilio API to send an emergency notification to emergency contacts.

[0439] Step 7: Sentiment analysis and response

[0440] The device analyzes the user's voice and facial expression data using an emotion engine and responds appropriately based on the results.

[0441] Input: Voice data and facial expression data

[0442] Output: Sentiment analysis results and corresponding actions

[0443] How it works: The device uses the Microsoft Azure Emotion API to analyze voice tone and facial expressions to determine the user's emotional state. For example, if the user says, "I'm a little tired," the device will play relaxing music.

[0444] As described above, specific operations are performed at each step, and ultimately a system that comprehensively supports the user's life is realized.

[0445] (Application example 2)

[0446] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0447] Supporting the elderly and busy families is an important issue in modern society. However, existing support systems do not fully consider users' emotions and lifestyles, and lack comprehensive support for household chores, preparations for going out, and emergency response. Furthermore, their ability to analyze and respond to emotional states such as stress and fatigue is limited. Therefore, there is a need for systems that can support users' overall lifestyles and enable them to live their daily lives with peace of mind.

[0448] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0449] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores within the home, a means for assisting with going out, a means for responding to emergencies, an emotion engine means for recognizing a user's emotions and suggesting appropriate actions, a means for controlling a household robot to perform cleaning tasks based on voice input, a means for providing information to support going out based on voice input, and a means for analyzing the user's emotions based on voice input and responding appropriately. This enables the server to support the user's overall lifestyle, seamlessly supporting housework, going out, and responding to emergencies. Furthermore, analyzing the user's emotional state and responding appropriately can provide a more comfortable and secure daily life.

[0450] "Voice input means" refers to a device or system for recognizing a user's voice and processing it as data.

[0451] "Image input means" refers to a device or system for capturing still images and processing them as data.

[0452] "Video input means" refers to a device or system for capturing video and processing it as data.

[0453] "General artificial intelligence means" is a system that uses artificial intelligence technology that can handle a variety of tasks, and is used to analyze user behavior and lifestyle habits.

[0454] The "means for learning lifestyle habits" is a system that collects and analyzes the user's daily behavioral patterns and habits as data, and provides optimal support based on that data.

[0455] A "means for automating household chores" is a device or system for automatically performing household chores such as cleaning and laundry.

[0456] "Means for assisting users in going out" refers to a system that provides weather and traffic information and supports users in going out.

[0457] "Means for responding to emergencies" refers to a system that detects abnormalities or emergencies in users and responds quickly.

[0458] The "emotion engine means" is a system that analyzes the user's emotions from their voice and facial expressions and suggests appropriate actions.

[0459] The "means for controlling a household robot" is a mechanism for operating a household robot based on voice input to perform a specific task.

[0460] The "means for providing outing support information" is a system for providing outing support information such as weather and traffic based on voice input.

[0461] The "means for analyzing emotions and responding" is a system that analyzes emotions from the user's voice and suggests relaxation methods based on that.

[0462] System Overview

[0463] The system according to the present invention includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, an emotion engine means, a means for controlling a household robot, a means for providing information to support going out, and a means for analyzing emotions and responding accordingly. This enables the system to support the user's life in general, seamlessly supporting housework, going out, and responding to emergencies.

[0464] Hardware and Software Configuration

[0465] The system uses the following hardware and software:

[0466] Smartphone: Equipped with a built-in microphone for voice recognition and a camera for capturing images and videos.

[0467] Domestic robots: Robots designed to automatically perform cleaning and other household chores.

[0468] General artificial intelligence software: Software that analyzes a user's behavior and lifestyle habits and provides optimal actions.

[0469] Emotion analysis engine: Software that analyzes the user's voice and facial expressions to recognize and respond to emotions.

[0470] Emergency notification system: A notification system for rapid response in emergencies.

[0471] Example of a system

[0472] Automating Housework

[0473] When a user issues a voice command such as "Please clean the living room," the smartphone's voice input means recognizes this and sends the instruction to the home robot. When the cleaning is complete, the system notifies the user by voice or through an application. If the emotion engine detects that the user is tired, it will gently notify the user, saying, "The living room has been cleaned. Please take a short rest."

[0474] Assistance with going out

[0475] When a user instructs the system to "get ready to go out," the system retrieves weather and traffic information and prepares a list of items needed for going out. For example, if the weather forecast predicts rain, the system will notify the user, "Don't forget to take an umbrella." If the emotion engine detects the user's stress, the system will suggest deep breathing or play relaxing music.

[0476] Emergency response

[0477] The system constantly monitors sensors to respond to emergencies. For example, if the user falls, the system will ask aloud, "Are you OK?" If there is no response or if the user responds with "Help me," it will automatically notify pre-defined emergency contacts. At this time, the user's current location and status will also be provided in real time.

[0478] Emotional engine response

[0479] The system uses an emotion engine to analyze the user's emotions from their voice and facial expressions. For example, if a user says, "I'm a little tired," the device will analyze their voice tone and facial expressions to recognize that emotion. If the emotion engine detects stress or anxiety in the user, it will play relaxing music or provide the necessary support.

[0480] Specific examples

[0481] Prompt: "Please clean the living room. I'm tired, so please play some relaxing music."

[0482] Prompt: "Get ready to go out. Check the weather and tell me what you need."

[0483] This system allows users to receive support in all aspects of their daily lives, allowing them to live with peace of mind. It also improves the quality of life of users by providing appropriate responses through emotion analysis.

[0484] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0485] Step 1:

[0486] The user issues a voice command. The smartphone's microphone captures the voice input and prepares it for processing as audio data.

[0487] Input: User's voice

[0488] Output: Audio data

[0489] Step 2:

[0490] The device converts the voice data into text using speech recognition software (speech_recognition library).

[0491] Input: Audio data

[0492] Output: Recognized text

[0493] Step 3:

[0494] The device analyzes the recognized text and determines the content of the instruction. For example, if the keyword "cleaning" is included, it will be recognized as an instruction to control a household robot.

[0495] Input: Text data

[0496] Output: Command content

[0497] Step 4:

[0498] Based on the analysis results, the device sends the corresponding task (e.g., cleaning the living room) to the home robot, which then carries out the cleaning task according to the received instructions.

[0499] Input: Command content

[0500] Output: Instructions to execute the cleaning task

[0501] Step 5:

[0502] The home robot monitors the progress of the cleaning task and sends the status upon completion to the terminal, which receives the information and notifies the user.

[0503] Input: Cleaning task progress

[0504] Output: Completion notification

[0505] Step 6:

[0506] The device uses an emotion engine to analyze the user's voice tone and facial expressions. For example, if the device detects that the user is tired, it will suggest playing relaxing music.

[0507] Input: Speech and facial expression data

[0508] Output: Emotion analysis results

[0509] Step 7:

[0510] Based on the analysis results, the device will suggest and execute appropriate actions (e.g., playing relaxing music).

[0511] Input: Sentiment analysis results

[0512] Output: Suggestions and action taken

[0513] Step 8:

[0514] The user can then issue an additional voice command, which the device will then recognize, interpret, and execute again. For example, based on a command such as "Get ready to go out," the device will retrieve weather and traffic information and provide it to the user.

[0515] Input: New voice command

[0516] Output:Outing support information

[0517] Through this series of steps, the system can comprehensively support the user's daily life and provide a comfortable living environment.

[0518] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0519] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0520] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0521] [Second embodiment]

[0522] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0523] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0524] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0525] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0526] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0527] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0528] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0529] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0530] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0531] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0532] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0533] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0534] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting people going out, and a means for responding to emergencies. Specific embodiments of the system are described below.

[0535] System Overview

[0536] When the user performs the initial system setup, the server stores basic information in a database and sends it to the device. The device uses voice, image, and video input to learn and analyze the user's lifestyle habits in real time. The general artificial intelligence device recognizes the user's behavioral patterns based on this data and provides optimal support for housework and outings. Additionally, if the sensor device detects an abnormality, it promptly notifies emergency contacts.

[0537] Housework support

[0538] For example, if a user issues a voice command such as "Please clean the living room," the device analyzes the voice data and executes the cleaning task. The server monitors the progress from the device and notifies the user when cleaning is complete. This cleaning task is then automatically executed by the cleaning robot.

[0539] Going out assistance

[0540] When the user instructs the device to "get ready to go out," the device receives the instruction via voice input means and sends a request to the server to check the weather and traffic conditions at the destination. The server obtains this information and sends it to the device, which then uses it to prepare items needed for going out (such as keys, a mobile phone, medicine, etc.). The device also notifies the user when these preparations are complete.

[0541] Emergency response

[0542] When the sensor means detects a fall or other abnormality, the device switches to emergency mode and confirms the user's condition by voice. It asks, "Mr. / Ms. XX, are you OK?" If there is no response or if the user responds with "Help me," the device sends an emergency notification to the server, which then automatically notifies the emergency contacts. The emergency contacts are provided with the user's current location and status in real time.

[0543] Example

[0544] For example, when a user starts their morning routine, the device will use a sensor to detect when the user wakes up and automatically start the coffee maker to brew coffee. It will also help prepare breakfast and get dressed. Before going out, it will obtain weather and traffic information and prepare the necessary equipment. Throughout this series of actions, the server constantly monitors the data and makes any necessary adjustments.

[0545] Through these functions, this system can support users in living independently and reduce the burden on the nursing care industry.

[0546] The processing flow will be explained below.

[0547] Housework support

[0548] Step 1:

[0549] The user issues a voice command such as "Please clean the living room."

[0550] Step 2:

[0551] The terminal detects the user's voice using the voice input means and performs voice recognition.

[0552] Step 3:

[0553] The device sends the recognized voice data to the server.

[0554] Step 4:

[0555] The server analyzes the voice commands and determines the "cleaning task."

[0556] Step 5:

[0557] The server issues instructions to the cleaning robot, which then starts cleaning the living room.

[0558] Step 6:

[0559] During cleaning, the server monitors the progress.

[0560] Step 7:

[0561] When cleaning is complete, the cleaning robot sends a completion report to the server.

[0562] Step 8:

[0563] The server receives the completion report and notifies the user via the terminal by voice, "The living room has been cleaned."

[0564] Going out assistance

[0565] Step 1:

[0566] The user issues a voice command such as "Get ready to go out."

[0567] Step 2:

[0568] The terminal detects the user's voice using the voice input means and performs voice recognition.

[0569] Step 3:

[0570] The device sends the recognized voice data to the server.

[0571] Step 4:

[0572] The server analyzes the voice instructions and retrieves information for going out (weather, traffic) from the Internet.

[0573] Step 5:

[0574] The server transmits the acquired information to the terminal.

[0575] Step 6:

[0576] The device prepares the necessary equipment for going out (e.g., keys, mobile phone, medicine, etc.).

[0577] Step 7:

[0578] The device notifies the user that it is ready to go, saying "You're ready to go out."

[0579] Emergency response

[0580] Step 1:

[0581] The device's sensor means detects an abnormality (e.g., a fall, prolonged inactivity).

[0582] Step 2:

[0583] The device will switch to emergency mode and ask a voice message asking, "Mr. / Ms. XX, are you okay?"

[0584] Step 3:

[0585] The user responds or does not respond.

[0586] Step 4:

[0587] If there is no response, the device sends an emergency notification to the server.

[0588] Step 5:

[0589] The server sends a notification to the emergency contact, which includes the user's current location and a description of the situation.

[0590] Step 6:

[0591] The server notifies the terminal of the completion of the contact and reports the information to the user by voice.

[0592] Learning about lifestyle habits

[0593] Step 1:

[0594] The user goes about their daily life.

[0595] Step 2:

[0596] The terminal observes and records the user's behavior using audio, image, and video input means.

[0597] Step 3:

[0598] The terminal transmits the recorded data to the server.

[0599] Step 4:

[0600] The server analyzes the data and uses AGI to learn user behavior patterns.

[0601] Step 5:

[0602] The server feeds the learning results back to the device and reflects them in the next support.

[0603] The above is a detailed description of the processing steps of the "AssistNext" system.

[0604] Example 1

[0605] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0606] Modern home life involves many tasks that require time and effort, such as housework, preparing to go out, and responding to emergencies. Performing these daily tasks independently is particularly difficult for the elderly and those with physical limitations. Furthermore, there is a lack of comprehensive systems for efficiently performing these tasks. Furthermore, the separate functions for housework support and emergency response pose a challenge, resulting in low user convenience.

[0607] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0608] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for analyzing and managing data for each processing step, a means for communicating with a cloud server, a means for notifying the user, and a means for automatically executing tasks. This allows the user to use multiple functions, such as support for household chores, preparation for going out, and emergency response, all in one system.

[0609] The "voice input means" is a device for recognizing the user's voice and converting it into digital data.

[0610] "Image input means" refers to a device for capturing still images and processing them as digital data.

[0611] "Video input means" is a device that captures a series of images and digitally processes them as video data.

[0612] "General artificial intelligence means" is a system that analyzes a variety of data, recognizes patterns using learning algorithms, and performs adaptive processing.

[0613] "Means for learning lifestyle habits" refers to technology that collects and analyzes data on the user's daily behavior and recognizes its patterns.

[0614] "Means for automating household chores" are devices or systems for mechanically performing household tasks such as cleaning and cooking.

[0615] The "means for assisting going out" is a system that provides information and prepares items to help the user prepare to go out.

[0616] "Means for responding to emergencies" refers to devices or systems that can quickly detect abnormalities and take appropriate action when a user is in an emergency.

[0617] "Means for analyzing and managing data at each processing step" refers to technology for analyzing and managing the data generated at each processing step.

[0618] "Means for communicating with a cloud server" refers to a device or system for sending and receiving data to and from a cloud server via the Internet.

[0619] "Means for notifying the user" refers to a technique for notifying the user of necessary information from the system.

[0620] A "means for automatically executing a task" is a system that automatically processes and executes a task based on a user's instructions and circumstances.

[0621] MODE FOR CARRYING OUT THE INVENTION

[0622] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting users when going out, and a means for responding to emergencies. The system aims to support and streamline the daily life of a user. Specific embodiments for carrying out the present invention will be described below.

[0623] Initial System Setup

[0624] The server collects basic information about the user and stores it in a database. This basic information includes name, age, address, contact details, etc. The server sends this information to the device, which then updates the system with the received information. The communication protocol is HTTP or WebSocket.

[0625] Learning about lifestyle habits

[0626] The device collects user behavior data in real time using audio input means (e.g., microphone), image input means (e.g., camera), and video input means (e.g., video camera). The general artificial intelligence means analyzes this data and learns the user's lifestyle habits. Specifically, it uses machine learning libraries such as TensorFlow and PyTorch. The analysis results are sent to a server and stored in a database.

[0627] Housework support

[0628] When a user makes a voice request such as "Please clean the living room," the device receives the voice data through the microphone. This data is analyzed by a voice recognition engine (e.g., Google Speech-to-Text API) and recognized as a cleaning task. The device then sends a command to a cleaning robot (e.g., Roomba) via Bluetooth or Wi-Fi to start cleaning the living room. The server monitors the cleaning robot's progress, and when the task is completed, it notifies the user that "cleaning of the living room is complete."

[0629] Going out assistance

[0630] When the user issues a voice command such as "Get ready to go out," the device receives the instruction through the microphone. The device then sends a request to the server to obtain weather and traffic information. The server obtains this information using the OpenWeatherMap API and Google Maps API and sends it to the device. Based on the obtained information, the device automatically prepares necessary items such as keys, a cell phone, and medicine. Once preparations are complete, the device notifies the user that "You're ready to go out."

[0631] Emergency response

[0632] When the sensor means detects that the user has fallen or something is wrong, the device switches to emergency mode. The device asks aloud, "Mr. / Ms. XX, are you OK?" and if there is no response or if the user responds with something like "Help me," it sends an emergency notification to the server. Based on this, the server automatically notifies emergency contacts, notifying them of the user's current location and situation in detail. During this process, emergency notifications are made via SMS, phone, and email.

[0633] Example

[0634] Let's take the example of a user starting their morning routine. The device uses sensors to detect that the user has woken up and automatically starts the coffee maker to brew coffee. It also helps the user prepare breakfast and get dressed, and obtains weather and traffic information to get ready to go out. The server monitors these actions and makes adjustments as necessary.

[0635] Prompt Sentence Examples

[0636] Examples of prompts to input into a generative AI model include:

[0637] Prompt statement:

[0638] "Please wake me up at 6am tomorrow morning, make me some coffee, check the weather and prepare the necessary items, and notify me before you leave."

[0639] This system will support users' independent and efficient lifestyles and help reduce the burden on the nursing care industry.

[0640] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0641] Step 1:

[0642] The server collects the user's basic information (name, age, address, contact details) and stores it in a database. The input is the user's registration information, and the output is the user information in the database. Specifically, the user enters information in a web browser, and the server receives it via an HTTP request. The server processes this information and saves it in a database.

[0643] Step 2:

[0644] The server sends basic information to the terminal. The input is user information in the database, and the output is the basic information sent to the terminal. The communication protocol uses HTTP or WebSocket. The server reads information from the database and sends it to the terminal.

[0645] Step 3:

[0646] The terminal receives basic information and reflects it in the system. The input is the basic information received from the server, and the output is the settings within the terminal. The terminal analyzes the received information and saves it in its internal database.

[0647] Step 4:

[0648] The device collects data using voice input, image input, and video input. The input is data on the user's daily activities, and the output is collected digital data. Specifically, a microphone or camera records the user's activities, and the device collects that data.

[0649] Step 5:

[0650] A general-purpose artificial intelligence analyzes collected data and learns user behavior patterns. The input is the collected digital data, and the output is the analysis results. Python libraries (TensorFlow and PyTorch) are used to perform data analysis and pattern recognition.

[0651] Step 6:

[0652] The terminal sends the analysis results to the server. The input is the analysis result data, and the output is the data sent to the server. The terminal sends the results to the server using HTTP or WebSocket.

[0653] Step 7:

[0654] The user issues a voice request such as "Please clean the living room." The input is the user's voice request, and the output is voice data. The microphone receives the user's voice and converts it into digital data.

[0655] Step 8:

[0656] The device analyzes the voice data and recognizes it as a cleaning task. The input is the voice data and the output is task information. The voice data is analyzed using a voice recognition engine (Google Speech-to-Text API) and task information is generated.

[0657] Step 9:

[0658] The device sends a command to the cleaning robot to start cleaning the living room. The input is task information, and the output is a command to the cleaning robot. The command is sent to the cleaning robot via Bluetooth or Wi-Fi.

[0659] Step 10:

[0660] The server monitors the operation of the cleaning robot and checks its progress. The input is the status data of the cleaning robot and the output is a progress report. The server receives the operating status of the cleaning robot in real time via WebSocket and monitors its progress.

[0661] Step 11:

[0662] When cleaning is complete, the server notifies the user, "Cleaning of the living room is complete." The input is the cleaning completion status data, and the output is a notification to the user. The notification is sent via a smartphone app or email.

[0663] Step 12:

[0664] The user issues a voice request such as "Get ready to go out." The input is the user's voice request, and the output is voice data. The microphone captures the voice and processes it as digital data.

[0665] Step 13:

[0666] The device analyzes the voice data and recognizes it as a task for preparing to go out. The input is the voice data, and the output is the preparation task information. The device uses a voice recognition engine to recognize the task.

[0667] Step 14:

[0668] The device sends a request to the server to obtain weather and traffic information. The input is the preparation task information, and the output is the information acquisition request. The request is sent to the server via an HTTP request.

[0669] Step 15:

[0670] The server retrieves the necessary data using the weather information API and traffic information API. The input is an information retrieval request, and the output is weather and traffic information. The server retrieves information using the OpenWeatherMap API and Google Maps API.

[0671] Step 16:

[0672] The weather and traffic information acquired by the server is sent to the terminal. The input is weather and traffic information, and the output is sending information to the terminal. Information is sent to the terminal via HTTP or WebSocket.

[0673] Step 17:

[0674] Based on the information acquired by the terminal, items necessary for going out (e.g., keys, cell phone, medicine, etc.) are prepared. The input is weather information and preparation task information, and the output is a list of prepared items. The location of items is managed with tags, and an automatic picking system is used.

[0675] Step 18:

[0676] When the preparation is complete, the device notifies the user that "You're ready to go out." The input is the preparation status, and the output is a notification to the user. This is done via a smartphone app or a voice notification.

[0677] Step 19:

[0678] When the sensor detects the user falling or an abnormality, the device switches to emergency mode. The input is abnormal data from the sensor, and the output is switching to emergency mode. An abnormality is detected using the acceleration sensor.

[0679] Step 20:

[0680] The device asks the user by voice, "Hey, are you OK?" The input is emergency mode and the output is a voice message. The speaker is used to play the voice message.

[0681] Step 21:

[0682] The device receives and analyzes the user's response via a voice input means. The input is the user's voice response, and the output is the analysis result. A voice recognition engine is used to analyze the voice data and identify keywords such as "help."

[0683] Step 22:

[0684] If there is no response or if there is a response calling for help, the device will send an emergency notification to the server. The input is the analysis result and the output is the emergency notification. Real-time communication is used to contact the server immediately.

[0685] Step 23:

[0686] The server automatically notifies emergency contacts and provides detailed information about the user's current location and situation. The input is an emergency notification, and the output is a notification to the emergency contacts. Notifications are made via SMS, phone, email, etc.

[0687] This system allows users to efficiently perform various tasks while maintaining their independence, and ensures safety by responding quickly in emergencies.

[0688] (Application example 1)

[0689] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0690] This invention aims to solve the problem that current housekeeping support and food delivery systems have difficulty in effectively reflecting users' voice instructions and lifestyle habits, and in particular the lack of optimal menu suggestions that correspond to individual eating habits and health management. It is also necessary to solve the problem that there is a lack of functionality for tracking the progress of ingredients management and delivery in real time, providing advice on ingredients that are in short supply, and responding to emergencies.

[0691] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0692] In this invention, the server includes a voice input unit, an image input unit, an order history learning unit, an ingredient recognition unit, a delivery progress tracking unit, and a unit for supporting healthy eating habits. This allows for optimal menu suggestions and automatic task execution based on the user's voice instructions. It also enables real-time ingredient management and rapid response in emergencies, making it possible to effectively address individual eating habits and health management.

[0693] "Voice input means" refers to a device or software for converting a user's voice into digital data.

[0694] "Image input means" refers to a device or software for capturing still images and inputting them as digital data.

[0695] "Video input means" refers to a device or software for capturing video images and inputting them as digital data.

[0696] An "artificial general intelligence means" is an artificial intelligence system designed to handle a wide variety of tasks.

[0697] The "means for learning lifestyle habits" is a system for collecting and analyzing data on users' daily behavior and habits.

[0698] "Means for automating household chores" refers to devices or systems that automate everyday household tasks such as cleaning and cooking.

[0699] "Means to assist with going out" refers to a system that provides necessary information and assists with preparations when going out.

[0700] "Measures to respond in emergencies" refers to a system for responding quickly when an accident or abnormality occurs.

[0701] The "means for learning order history" is a system that analyzes a user's past order data and learns their preferences and tendencies.

[0702] The "means for recognizing ingredients" is a system that analyzes image and video data to identify the type of food.

[0703] "Means for tracking delivery progress" refers to a system that monitors the progress of delivery in real time and notifies the user.

[0704] The "means for supporting healthy eating habits" is a system that suggests nutritionally balanced meals based on the user's health condition and eating habits data.

[0705] The present invention is designed as a system to support the daily life of a user. A specific embodiment of this system is shown below. This system includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for learning order history, a means for recognizing ingredients, a means for tracking delivery progress, and a means for supporting healthy eating habits.

[0706] Hardware and software used

[0707] The main components of the system include:

[0708] Voice input method: Google Speech-to-Text API

[0709] Image input method: Smartphone camera, TensorFlow

[0710] Video input method: Smartphone video camera, TensorFlow

[0711] General artificial intelligence means: GPT-4 (Generative Pre-trained Transformer 4)

[0712] How we learn your habits: Firebase, Google Cloud Storage

[0713] Automating household chores: Robot vacuum cleaners (e.g., Roomba)

[0714] Ways to help you get out: Google Maps API, Weather API

[0715] Emergency Response: Twilio API

[0716] How to learn order history: Firebase, Google Cloud Storage

[0717] Methods for identifying ingredients: TensorFlow, image recognition algorithms

[0718] Ways to track delivery progress: Firebase, Realtime Database

[0719] A tool to support healthy eating habits: Nutritional Analysis API

[0720] System Operation

[0721] Voice instructions and order history learning

[0722] When a user speaks to their smartphone, saying "Order dinner," the smartphone's voice input device converts this speech into digital data. This data is then converted into text using the Google Speech-to-Text API. The text data is then analyzed by GPT-4, which uses a model trained on the user's past ordering history and preferences to suggest the optimal menu.

[0723] Ingredient recognition and management

[0724] When a user scans the inside of their refrigerator with their smartphone camera, the image input means sends the captured image to TensorFlow, which recognizes ingredients and determines what is missing. The recognized data is stored in Firebase and used to provide advice to the user.

[0725] Delivery progress tracking and emergency response

[0726] Once an order is placed, the server sends a request to the delivery service, and the delivery progress is tracked in real time via Firebase. Users can check the current delivery status through their smartphone app. Furthermore, if an emergency occurs during delivery, a notification will be sent to emergency contacts using the Twilio API.

[0727] Supporting healthy eating habits

[0728] A nutrition analysis API is used to analyze the user's eating habits data, allowing the system to suggest nutritionally balanced meals based on the user's health status and eating habits.

[0729] Specific examples

[0730] When User A says "Order dinner" via voice input, the GPT-4-based system references their past order history and suggests the most suitable menu for the user. For example, if they have frequently ordered Italian food in the past, menu items such as pizza and pasta will be suggested. When the user confirms "Order this," the order is confirmed and the delivery progress is tracked on Firebase.

[0731] Examples of prompt statements

[0732] Generate a response when a user asks for a dinner order, making menu suggestions that take into account their ordering history and preferences.

[0733] This seamlessly integrates a series of operations from voice instructions to delivery, greatly improving user convenience.

[0734] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0735] Step 1:

[0736] The user speaks to their smartphone and says, "Order dinner."

[0737] Input: User's voice data

[0738] How it works: The smartphone's voice input method captures audio.

[0739] Output: Converts audio data into digital data

[0740] Step 2:

[0741] The converted audio data is sent to the Google Speech-to-Text API and converted into text data.

[0742] Input: Digital audio data

[0743] How it works: Converts speech to text using the Google Speech-to-Text API

[0744] Output: Text data

[0745] Step 3:

[0746] Text data is input into GPT-4, and the optimal menu is suggested based on a model that has learned the user's past ordering history and preferences.

[0747] Input: User's instruction text data, past order history

[0748] How it works: The GPT-4 model analyzes text data and generates the optimal menu.

[0749] Output: Menu suggestion text

[0750] Step 4:

[0751] Menu suggestions are displayed to the user for selection or confirmation.

[0752] Input: Menu suggestion text

[0753] Behavior: Displays a menu on the smartphone screen and accepts user input.

[0754] Output: User selection or confirmation information

[0755] Step 5:

[0756] When the user selects or confirms a menu item, the information is sent to the server to confirm the order.

[0757] Input: User selection or confirmation information

[0758] How it works: The server receives the order information and sends a request to the delivery service.

[0759] Output: Confirmed order information

[0760] Step 6:

[0761] Based on the confirmed order information, the server stores delivery progress tracking information in Firebase and updates it in real time.

[0762] Input: Confirmed order information

[0763] How it works: Store order data in Firebase and get real-time progress information from the delivery service.

[0764] Output: Delivery progress information

[0765] Step 7:

[0766] Delivery progress information will be available to check on a smartphone app and notified to users.

[0767] Input: Delivery progress information

[0768] Behavior: Display progress on smartphone app and notify user

[0769] Output: Delivery progress notification

[0770] Step 8:

[0771] In the event of an emergency, the server uses the Twilio API to send a notification to emergency contacts.

[0772] Input: Emergency detection information

[0773] How it works: Sends SMS and phone calls to emergency contacts via the Twilio API

[0774] Output: Emergency notification sent

[0775] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0776] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting people going out, a means for responding to emergencies, and an emotion engine that recognizes the emotions of the user. Specific embodiments of this system are described below.

[0777] System Overview

[0778] When the user performs the initial system setup, the server stores basic information in a database and sends it to the device. The device uses voice, image, and video input to learn and analyze the user's lifestyle habits in real time. The general artificial intelligence means recognizes the user's behavioral patterns based on this data and provides optimal support for housework and outings. The emotion engine also recognizes the user's emotions and responds as needed. Furthermore, if the sensor means detects an abnormality, it promptly notifies emergency contacts.

[0779] Housework support

[0780] For example, if a user issues a voice command such as "Please clean the living room," the device analyzes the voice data and executes the cleaning task. The server monitors the progress from the device and notifies the user when cleaning is complete. This cleaning task is then automatically executed by the cleaning robot.

[0781] Going out assistance

[0782] When the user instructs the device to "get ready to go out," the device receives the instruction via voice input means and sends a request to the server to check the weather and traffic conditions at the destination. The server obtains this information and sends it to the device, which then uses it to prepare items needed for going out (such as keys, a mobile phone, medicine, etc.). The device also notifies the user when these preparations are complete.

[0783] Emergency response

[0784] When the sensor means detects a fall or other abnormality, the device switches to emergency mode and confirms the user's condition by voice. It asks, "Mr. / Ms. XX, are you OK?" If there is no response or if the user responds with "Help me," the device sends an emergency notification to the server, which then automatically notifies the emergency contacts. The emergency contacts are provided with the user's current location and status in real time.

[0785] Introducing the Emotion Engine

[0786] The emotion engine analyzes the user's emotions from their voice and facial expressions. For example, if a user says, "I'm a little tired," the device will analyze the user's tone of voice and facial expressions to recognize that emotion. If the emotion engine detects the user's stress or anxiety, it will play relaxing music or provide the necessary support.

[0787] Example

[0788] Housework support

[0789] When a user says in a tired voice, "Please clean the living room," the device uses its emotion engine to analyze the user's level of fatigue and sends the data to the server. The server then executes the cleaning task and gently notifies the user with a voice message saying, "The living room has been cleaned. Please take a short rest."

[0790] Going out assistance

[0791] When the user instructs the device to "get ready to go out" and the emotion engine detects that the user is stressed, the device will make suggestions to help the user relax (for example, by taking deep breaths beforehand or playing music to relieve stress), thereby helping the user to feel at ease when going out.

[0792] Emergency response

[0793] If the device's sensor detects a fall and the emotion engine analyzes the user's voice tone and determines that the user is in a panic, the server will notify emergency contacts of the situation and promptly notify caregivers and family members. The analysis results from the emotion engine are useful in determining the priority of emergency responses.

[0794] Through these functions, this system can support users in living independently and reduce the burden on the nursing care industry.

[0795] The processing flow will be explained below.

[0796] Housework support

[0797] Step 1:

[0798] The user issues a voice command such as "Please clean the living room."

[0799] Step 2:

[0800] The terminal detects the user's voice using the voice input means and performs voice recognition.

[0801] Step 3:

[0802] The device uses an emotion engine to analyze the user's voice tone and recognize that the user is tired.

[0803] Step 4:

[0804] The device sends the recognized voice data and emotion data to the server.

[0805] Step 5:

[0806] The server analyzes voice commands and emotional data to determine the "cleaning task" and considers responses that will help the user relax.

[0807] Step 6:

[0808] The server issues instructions to the cleaning robot, which then starts cleaning the living room.

[0809] Step 7:

[0810] During cleaning, the server monitors the progress.

[0811] Step 8:

[0812] When cleaning is complete, the cleaning robot sends a completion report to the server.

[0813] Step 9:

[0814] The server receives the completion report and gently notifies the user via the terminal with a voice message saying, "The living room has been cleaned. Please take a short rest."

[0815] Going out assistance

[0816] Step 1:

[0817] The user issues a voice command such as "Get ready to go out."

[0818] Step 2:

[0819] The terminal detects the user's voice using the voice input means and performs voice recognition.

[0820] Step 3:

[0821] The device uses an emotion engine to analyze the user's voice tone and recognize that they are feeling stressed.

[0822] Step 4:

[0823] The device sends the recognized voice data and emotion data to the server.

[0824] Step 5:

[0825] The server analyzes voice instructions and emotional data and obtains information for going out (weather, traffic) from the Internet.

[0826] Step 6:

[0827] The server transmits the acquired information to the terminal.

[0828] Step 7:

[0829] The device prepares the necessary equipment for going out (such as keys, cell phone, medicine, etc.) and also makes suggestions for relaxation (such as taking deep breaths beforehand or playing music to relieve stress).

[0830] Step 8:

[0831] The device will notify the user that it is ready to go, saying, "You're ready to go! Relax and enjoy your trip."

[0832] Emergency response

[0833] Step 1:

[0834] The device's sensor means detects an abnormality (e.g., a fall, prolonged inactivity).

[0835] Step 2:

[0836] The terminal uses an emotion engine to analyze the user's voice tone and determine the user's emotional state.

[0837] Step 3:

[0838] The device will ask aloud, "Mr. / Ms. XX, are you okay?"

[0839] Step 4:

[0840] The user responds or does not respond.

[0841] Step 5:

[0842] If there is no response, the device sends an emergency notification to the server, which also includes emotional data.

[0843] Step 6:

[0844] The server sends a notification to emergency contacts, which includes the user's current location, a description of the situation, and their emotional state.

[0845] Step 7:

[0846] The server notifies the terminal of the completion of the contact and reports the information to the user by voice.

[0847] Learning about lifestyle habits

[0848] Step 1:

[0849] The user goes about their daily life.

[0850] Step 2:

[0851] The terminal observes and records the user's behavior using audio, image, and video input means.

[0852] Step 3:

[0853] The device also uses an emotion engine to record the user's emotional state from their facial expressions and voice.

[0854] Step 4:

[0855] The device transmits the recorded data and emotion data to the server.

[0856] Step 5:

[0857] The server analyzes the data and uses AGI to learn the user's behavioral and emotional patterns.

[0858] Step 6:

[0859] The server feeds back the learning results to the device and reflects them in the next support session.

[0860] The above is a detailed description of the processing steps that combine the emotion engine in the "AssistNext" system.

[0861] Example 2

[0862] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0863] In modern society, with the increasing number of elderly people and busy families, there is a demand for systems to support daily life. Conventional systems are limited to automating specific tasks or providing partial support, and do not provide sufficient comprehensive support for daily life. In addition, they are unable to respond quickly in emergencies or understand the user's emotional state, leaving issues in improving user safety and quality of life.

[0864] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0865] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for recognizing a user's emotions, a means for monitoring the progress of tasks being performed and providing feedback, and a means for analyzing a user's instructions and executing tasks. This allows for comprehensive support of the user's daily life, enabling a rapid response in emergencies and appropriate support based on the user's emotional state.

[0866] Below are definitions of important words included in the rewritten claims.

[0867] "Voice input means" refers to a device or software that captures the user's voice and analyzes the voice data.

[0868] "Image input means" refers to a device or software that captures a still image of the user and analyzes it.

[0869] "Video input means" refers to a device or software that captures and analyzes dynamic video data of a user.

[0870] "General artificial intelligence means" is an artificial intelligence technology that learns and analyzes a user's behavioral patterns and lifestyle habits to provide optimal support.

[0871] The "means for learning lifestyle habits" is a device or software that observes the user's daily actions and habits and learns lifestyle patterns based on that data.

[0872] A "means for automating household chores" is a device or software for automatically performing household chores such as cleaning and laundry based on instructions from a user.

[0873] "Means for assisting going out" refers to devices or software that provide the user with the information they need when going out and support their preparations.

[0874] "Emergency response measures" refer to devices or software that detect emergencies based on sensors and analytical results and respond promptly.

[0875] The "means for recognizing the user's emotions" refers to a device or software for analyzing and recognizing the user's emotional state from their voice and facial expressions.

[0876] The "means for monitoring the progress of an executed task and providing feedback" refers to a device or software for monitoring the progress of a specified task in real time and providing feedback to the user at appropriate times.

[0877] "Means for analyzing user instructions and executing tasks" refers to a device or software that analyzes instructions from a user in the form of voice or other input and executes an appropriate task based on those instructions.

[0878] MODE FOR CARRYING OUT THE INVENTION

[0879] The present invention is a system that comprehensively supports a user's daily life. This system includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating housework, a means for assisting with going out, a means for responding to emergencies, a means for recognizing the user's emotions, a means for monitoring the progress of an executed task and providing feedback, and a means for analyzing the user's instructions and executing the task.

[0880] Hardware Configuration

[0881] Users use a device to input voice, images, and video. This device is equipped with a microphone, camera, and sensors. The device sends the data over a network to a server for further processing. The server is a computer system equipped with a high-performance CPU and a large amount of memory, and can run on a cloud platform.

[0882] Software Configuration

[0883] The device uses speech recognition APIs (e.g., Google Cloud Speech-to-Text or IBM Watson Speech to Text), image analysis APIs, and video analysis APIs. The server uses general artificial intelligence methods (e.g., TensorFlow or PyTorch) to learn the user's behavioral patterns and update a database (e.g., MongoDB or MySQL). The Microsoft Azure Emotion API can be used as an emotion engine. Kafka or RabbitMQ can be used as a real-time data streaming technology to monitor the progress of tasks.

[0884] Specific examples

[0885] Housework support

[0886] When a user issues a voice command such as "Please clean the living room," the device captures the voice and converts it into text data using a speech recognition API. The converted data is sent to a server, which analyzes the command and assigns a cleaning task to a cleaning robot (e.g., an iRobot Roomba). The cleaning progress is monitored in real time, and the user is notified when the cleaning is complete.

[0887] Going out assistance

[0888] When a user verbally commands "get ready to go out," the device captures the voice and converts it into text data using a speech recognition API. The converted data is sent to a server, which then uses an external API (e.g., OpenWeatherMap or Google Maps API) to obtain weather and traffic information for the destination. The device then prepares items needed for going out (e.g., keys, cell phone, medicine, etc.) based on the obtained information and notifies the user when they are ready.

[0889] Emergency response

[0890] When the device's built-in sensor detects an abnormality, such as a fall, the device switches to emergency mode. An emergency notification is sent to the server, which then automatically notifies emergency contacts using a business API (e.g., Twilio API). In the event of an emergency, the user's current location and status are provided in real time.

[0891] Introducing the Emotion Engine

[0892] If a user says, "I'm a little tired," the device will analyze their voice tone and facial expressions with its emotion engine to recognize their emotion. If it determines that the user is feeling stressed, the device will play relaxing music or provide appropriate support.

[0893] Prompt Sentence Examples

[0894] "User automation assistance system"

[0895] input:

[0896] User voice commands (e.g., "Please clean the living room")

[0897] The user's emotional state (e.g., "I feel a little tired")

[0898] Output:

[0899] Interprets voice commands and performs specific tasks

[0900] Analyze emotions with an emotion engine and provide optimal responses

[0901] As described above, this system can provide multifunctional and flexible support to help users live independently.

[0902] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0903] Step 1: User voice input

[0904] The user issues commands by voice. For example, the user might say to the device, "Please clean the living room."

[0905] Input: User's voice data

[0906] Output: Audio data is captured

[0907] What happens: The device's microphone captures audio data, which is temporarily stored on the device.

[0908] Step 2: Analyzing the audio data

[0909] The device converts the captured voice data into text data using a voice recognition API.

[0910] Input: Captured audio data

[0911] Output: Converted text data

[0912] How it works: The device calls the Google Cloud Speech-to-Text API to convert the voice data into text, which is then immediately sent to the server.

[0913] Step 3: Learning behavioral patterns and updating the database

[0914] The server analyzes the received text data and updates a database for learning user behavior patterns.

[0915] Input: Converted text data

[0916] Output: Updated database

[0917] Specific operation: The server uses TensorFlow to analyze the received text data, learn behavioral patterns, store the results in MongoDB, and update the database.

[0918] Step 4: Task execution instructions

[0919] The server sends instructions to the terminal to execute a task based on the analysis results.

[0920] Input: Analysis results

[0921] Output: Instructions to the terminal

[0922] Specific operation: The server uses the REST API to send specific execution instructions (e.g., "Send the cleaning robot to the living room") to the device.

[0923] Step 5: Monitoring and feedback on the execution of tasks

[0924] The server monitors the progress of the execution tasks received from the terminal and provides the information as feedback to the user in real time.

[0925] Input: Progress data of the execution task

[0926] Output: Feedback to the user

[0927] Specific operation: The device sends progress data from the cleaning robot to the server, which receives it and notifies the user that "cleaning is complete."

[0928] Step 6: Emergency response

[0929] If the device's sensor detects an abnormality, it switches to emergency mode and sends an emergency notification to the server.

[0930] Input: Anomaly detection data from sensors

[0931] Output: Send emergency notification

[0932] How it works: If a device's sensor detects, for example, a fall, it sends that data to a server via AWS IoT, which then uses the Twilio API to send an emergency notification to emergency contacts.

[0933] Step 7: Sentiment analysis and response

[0934] The device analyzes the user's voice and facial expression data using an emotion engine and responds appropriately based on the results.

[0935] Input: Voice data and facial expression data

[0936] Output: Sentiment analysis results and corresponding actions

[0937] How it works: The device uses the Microsoft Azure Emotion API to analyze voice tone and facial expressions to determine the user's emotional state. For example, if the user says, "I'm a little tired," the device will play relaxing music.

[0938] As described above, specific operations are performed at each step, and ultimately a system that comprehensively supports the user's life is realized.

[0939] (Application example 2)

[0940] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0941] Supporting the elderly and busy families is an important issue in modern society. However, existing support systems do not fully consider users' emotions and lifestyles, and lack comprehensive support for household chores, preparations for going out, and emergency response. Furthermore, their ability to analyze and respond to emotional states such as stress and fatigue is limited. Therefore, there is a need for systems that can support users' overall lifestyles and enable them to live their daily lives with peace of mind.

[0942] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0943] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores within the home, a means for assisting with going out, a means for responding to emergencies, an emotion engine means for recognizing a user's emotions and suggesting appropriate actions, a means for controlling a household robot to perform cleaning tasks based on voice input, a means for providing information to support going out based on voice input, and a means for analyzing the user's emotions based on voice input and responding appropriately. This enables the server to support the user's overall lifestyle, seamlessly supporting housework, going out, and responding to emergencies. Furthermore, analyzing the user's emotional state and responding appropriately can provide a more comfortable and secure daily life.

[0944] "Voice input means" refers to a device or system for recognizing a user's voice and processing it as data.

[0945] "Image input means" refers to a device or system for capturing still images and processing them as data.

[0946] "Video input means" refers to a device or system for capturing video and processing it as data.

[0947] "General artificial intelligence means" is a system that uses artificial intelligence technology that can handle a variety of tasks, and is used to analyze user behavior and lifestyle habits.

[0948] The "means for learning lifestyle habits" is a system that collects and analyzes the user's daily behavioral patterns and habits as data, and provides optimal support based on that data.

[0949] A "means for automating household chores" is a device or system for automatically performing household chores such as cleaning and laundry.

[0950] "Means for assisting users in going out" refers to a system that provides weather and traffic information and supports users in going out.

[0951] "Means for responding to emergencies" refers to a system that detects abnormalities or emergencies in users and responds quickly.

[0952] The "emotion engine means" is a system that analyzes the user's emotions from their voice and facial expressions and suggests appropriate actions.

[0953] The "means for controlling a household robot" is a mechanism for operating a household robot based on voice input to perform a specific task.

[0954] The "means for providing outing support information" is a system for providing outing support information such as weather and traffic based on voice input.

[0955] The "means for analyzing emotions and responding" is a system that analyzes emotions from the user's voice and suggests relaxation methods based on that.

[0956] System Overview

[0957] The system according to the present invention includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, an emotion engine means, a means for controlling a household robot, a means for providing information to support going out, and a means for analyzing emotions and responding accordingly. This enables the system to support the user's life in general, seamlessly supporting housework, going out, and responding to emergencies.

[0958] Hardware and Software Configuration

[0959] The system uses the following hardware and software:

[0960] Smartphone: Equipped with a built-in microphone for voice recognition and a camera for capturing images and videos.

[0961] Domestic robots: Robots designed to automatically perform cleaning and other household chores.

[0962] General artificial intelligence software: Software that analyzes a user's behavior and lifestyle habits and provides optimal actions.

[0963] Emotion analysis engine: Software that analyzes the user's voice and facial expressions to recognize and respond to emotions.

[0964] Emergency notification system: A notification system for rapid response in emergencies.

[0965] Example of a system

[0966] Automating Housework

[0967] When a user issues a voice command such as "Please clean the living room," the smartphone's voice input means recognizes this and sends the instruction to the home robot. When the cleaning is complete, the system notifies the user by voice or through an application. If the emotion engine detects that the user is tired, it will gently notify the user, saying, "The living room has been cleaned. Please take a short rest."

[0968] Assistance with going out

[0969] When a user instructs the system to "get ready to go out," the system retrieves weather and traffic information and prepares a list of items needed for going out. For example, if the weather forecast predicts rain, the system will notify the user, "Don't forget to take an umbrella." If the emotion engine detects the user's stress, the system will suggest deep breathing or play relaxing music.

[0970] Emergency response

[0971] The system constantly monitors sensors to respond to emergencies. For example, if the user falls, the system will ask aloud, "Are you OK?" If there is no response or if the user responds with "Help me," it will automatically notify pre-defined emergency contacts. At this time, the user's current location and status will also be provided in real time.

[0972] Emotional engine response

[0973] The system uses an emotion engine to analyze the user's emotions from their voice and facial expressions. For example, if a user says, "I'm a little tired," the device will analyze their voice tone and facial expressions to recognize that emotion. If the emotion engine detects stress or anxiety in the user, it will play relaxing music or provide the necessary support.

[0974] Specific examples

[0975] Prompt: "Please clean the living room. I'm tired, so please play some relaxing music."

[0976] Prompt: "Get ready to go out. Check the weather and tell me what you need."

[0977] This system allows users to receive support in all aspects of their daily lives, allowing them to live with peace of mind. It also improves the quality of life of users by providing appropriate responses through emotion analysis.

[0978] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0979] Step 1:

[0980] The user issues a voice command. The smartphone's microphone captures the voice input and prepares it for processing as audio data.

[0981] Input: User's voice

[0982] Output: Audio data

[0983] Step 2:

[0984] The device converts the voice data into text using speech recognition software (speech_recognition library).

[0985] Input: Audio data

[0986] Output: Recognized text

[0987] Step 3:

[0988] The device analyzes the recognized text and determines the content of the instruction. For example, if the keyword "cleaning" is included, it will be recognized as an instruction to control a household robot.

[0989] Input: Text data

[0990] Output: Command content

[0991] Step 4:

[0992] Based on the analysis results, the device sends the corresponding task (e.g., cleaning the living room) to the home robot, which then carries out the cleaning task according to the received instructions.

[0993] Input: Command content

[0994] Output: Instructions to execute the cleaning task

[0995] Step 5:

[0996] The home robot monitors the progress of the cleaning task and sends the status upon completion to the terminal, which receives the information and notifies the user.

[0997] Input: Cleaning task progress

[0998] Output: Completion notification

[0999] Step 6:

[1000] The device uses an emotion engine to analyze the user's voice tone and facial expressions. For example, if the device detects that the user is tired, it will suggest playing relaxing music.

[1001] Input: Speech and facial expression data

[1002] Output: Emotion analysis results

[1003] Step 7:

[1004] Based on the analysis results, the device will suggest and execute appropriate actions (e.g., playing relaxing music).

[1005] Input: Sentiment analysis results

[1006] Output: Suggestions and action taken

[1007] Step 8:

[1008] The user can then issue an additional voice command, which the device will then recognize, interpret, and execute again. For example, based on a command such as "Get ready to go out," the device will retrieve weather and traffic information and provide it to the user.

[1009] Input: New voice command

[1010] Output:Outing support information

[1011] Through this series of steps, the system can comprehensively support the user's daily life and provide a comfortable living environment.

[1012] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1013] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1014] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1015] [Third embodiment]

[1016] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1017] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1019] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1020] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1021] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1023] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1024] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1026] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1027] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1028] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting people going out, and a means for responding to emergencies. Specific embodiments of the system are described below.

[1029] System Overview

[1030] When the user performs the initial system setup, the server stores basic information in a database and sends it to the device. The device uses voice, image, and video input to learn and analyze the user's lifestyle habits in real time. The general artificial intelligence device recognizes the user's behavioral patterns based on this data and provides optimal support for housework and outings. Additionally, if the sensor device detects an abnormality, it promptly notifies emergency contacts.

[1031] Housework support

[1032] For example, if a user issues a voice command such as "Please clean the living room," the device analyzes the voice data and executes the cleaning task. The server monitors the progress from the device and notifies the user when cleaning is complete. This cleaning task is then automatically executed by the cleaning robot.

[1033] Going out assistance

[1034] When the user instructs the device to "get ready to go out," the device receives the instruction via voice input means and sends a request to the server to check the weather and traffic conditions at the destination. The server obtains this information and sends it to the device, which then uses it to prepare items needed for going out (such as keys, a mobile phone, medicine, etc.). The device also notifies the user when these preparations are complete.

[1035] Emergency response

[1036] When the sensor means detects a fall or other abnormality, the device switches to emergency mode and confirms the user's condition by voice. It asks, "Mr. / Ms. XX, are you OK?" If there is no response or if the user responds with "Help me," the device sends an emergency notification to the server, which then automatically notifies the emergency contacts. The emergency contacts are provided with the user's current location and status in real time.

[1037] Example

[1038] For example, when a user starts their morning routine, the device will use a sensor to detect when the user wakes up and automatically start the coffee maker to brew coffee. It will also help prepare breakfast and get dressed. Before going out, it will obtain weather and traffic information and prepare the necessary equipment. Throughout this series of actions, the server constantly monitors the data and makes any necessary adjustments.

[1039] Through these functions, this system can support users in living independently and reduce the burden on the nursing care industry.

[1040] The processing flow will be explained below.

[1041] Housework support

[1042] Step 1:

[1043] The user issues a voice command such as "Please clean the living room."

[1044] Step 2:

[1045] The terminal detects the user's voice using the voice input means and performs voice recognition.

[1046] Step 3:

[1047] The device sends the recognized voice data to the server.

[1048] Step 4:

[1049] The server analyzes the voice commands and determines the "cleaning task."

[1050] Step 5:

[1051] The server issues instructions to the cleaning robot, which then starts cleaning the living room.

[1052] Step 6:

[1053] During cleaning, the server monitors the progress.

[1054] Step 7:

[1055] When cleaning is complete, the cleaning robot sends a completion report to the server.

[1056] Step 8:

[1057] The server receives the completion report and notifies the user via the terminal by voice, "The living room has been cleaned."

[1058] Going out assistance

[1059] Step 1:

[1060] The user issues a voice command such as "Get ready to go out."

[1061] Step 2:

[1062] The terminal detects the user's voice using the voice input means and performs voice recognition.

[1063] Step 3:

[1064] The device sends the recognized voice data to the server.

[1065] Step 4:

[1066] The server analyzes the voice instructions and retrieves information for going out (weather, traffic) from the Internet.

[1067] Step 5:

[1068] The server transmits the acquired information to the terminal.

[1069] Step 6:

[1070] The device prepares the necessary equipment for going out (e.g., keys, mobile phone, medicine, etc.).

[1071] Step 7:

[1072] The device notifies the user that it is ready to go, saying "You're ready to go out."

[1073] Emergency response

[1074] Step 1:

[1075] The device's sensor means detects an abnormality (e.g., a fall, prolonged inactivity).

[1076] Step 2:

[1077] The device will switch to emergency mode and ask a voice message asking, "Mr. / Ms. XX, are you okay?"

[1078] Step 3:

[1079] The user responds or does not respond.

[1080] Step 4:

[1081] If there is no response, the device sends an emergency notification to the server.

[1082] Step 5:

[1083] The server sends a notification to the emergency contact, which includes the user's current location and a description of the situation.

[1084] Step 6:

[1085] The server notifies the terminal of the completion of the contact and reports the information to the user by voice.

[1086] Learning about lifestyle habits

[1087] Step 1:

[1088] The user goes about their daily life.

[1089] Step 2:

[1090] The terminal observes and records the user's behavior using audio, image, and video input means.

[1091] Step 3:

[1092] The terminal transmits the recorded data to the server.

[1093] Step 4:

[1094] The server analyzes the data and uses AGI to learn user behavior patterns.

[1095] Step 5:

[1096] The server feeds the learning results back to the device and reflects them in the next support.

[1097] The above is a detailed description of the processing steps of the "AssistNext" system.

[1098] Example 1

[1099] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1100] Modern home life involves many tasks that require time and effort, such as housework, preparing to go out, and responding to emergencies. Performing these daily tasks independently is particularly difficult for the elderly and those with physical limitations. Furthermore, there is a lack of comprehensive systems for efficiently performing these tasks. Furthermore, the separate functions for housework support and emergency response pose a challenge, resulting in low user convenience.

[1101] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1102] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for analyzing and managing data for each processing step, a means for communicating with a cloud server, a means for notifying the user, and a means for automatically executing tasks. This allows the user to use multiple functions, such as support for household chores, preparation for going out, and emergency response, all in one system.

[1103] The "voice input means" is a device for recognizing the user's voice and converting it into digital data.

[1104] "Image input means" refers to a device for capturing still images and processing them as digital data.

[1105] "Video input means" is a device that captures a series of images and digitally processes them as video data.

[1106] "General artificial intelligence means" is a system that analyzes a variety of data, recognizes patterns using learning algorithms, and performs adaptive processing.

[1107] "Means for learning lifestyle habits" refers to technology that collects and analyzes data on the user's daily behavior and recognizes its patterns.

[1108] "Means for automating household chores" are devices or systems for mechanically performing household tasks such as cleaning and cooking.

[1109] The "means for assisting going out" is a system that provides information and prepares items to help the user prepare to go out.

[1110] "Means for responding to emergencies" refers to devices or systems that can quickly detect abnormalities and take appropriate action when a user is in an emergency.

[1111] "Means for analyzing and managing data at each processing step" refers to technology for analyzing and managing the data generated at each processing step.

[1112] "Means for communicating with a cloud server" refers to a device or system for sending and receiving data to and from a cloud server via the Internet.

[1113] "Means for notifying the user" refers to a technique for notifying the user of necessary information from the system.

[1114] A "means for automatically executing a task" is a system that automatically processes and executes a task based on a user's instructions and circumstances.

[1115] MODE FOR CARRYING OUT THE INVENTION

[1116] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting users when going out, and a means for responding to emergencies. The system aims to support and streamline the daily life of a user. Specific embodiments for carrying out the present invention will be described below.

[1117] Initial System Setup

[1118] The server collects basic information about the user and stores it in a database. This basic information includes name, age, address, contact details, etc. The server sends this information to the device, which then updates the system with the received information. The communication protocol is HTTP or WebSocket.

[1119] Learning about lifestyle habits

[1120] The device collects user behavior data in real time using audio input means (e.g., microphone), image input means (e.g., camera), and video input means (e.g., video camera). The general artificial intelligence means analyzes this data and learns the user's lifestyle habits. Specifically, it uses machine learning libraries such as TensorFlow and PyTorch. The analysis results are sent to a server and stored in a database.

[1121] Housework support

[1122] When a user makes a voice request such as "Please clean the living room," the device receives the voice data through the microphone. This data is analyzed by a voice recognition engine (e.g., Google Speech-to-Text API) and recognized as a cleaning task. The device then sends a command to a cleaning robot (e.g., Roomba) via Bluetooth or Wi-Fi to start cleaning the living room. The server monitors the cleaning robot's progress, and when the task is completed, it notifies the user that "cleaning of the living room is complete."

[1123] Going out assistance

[1124] When the user issues a voice command such as "Get ready to go out," the device receives the instruction through the microphone. The device then sends a request to the server to obtain weather and traffic information. The server obtains this information using the OpenWeatherMap API and Google Maps API and sends it to the device. Based on the obtained information, the device automatically prepares necessary items such as keys, a cell phone, and medicine. Once preparations are complete, the device notifies the user that "You're ready to go out."

[1125] Emergency response

[1126] When the sensor means detects that the user has fallen or something is wrong, the device switches to emergency mode. The device asks aloud, "Mr. / Ms. XX, are you OK?" and if there is no response or if the user responds with something like "Help me," it sends an emergency notification to the server. Based on this, the server automatically notifies emergency contacts, notifying them of the user's current location and situation in detail. During this process, emergency notifications are made via SMS, phone, and email.

[1127] Example

[1128] Let's take the example of a user starting their morning routine. The device uses sensors to detect that the user has woken up and automatically starts the coffee maker to brew coffee. It also helps the user prepare breakfast and get dressed, and obtains weather and traffic information to get ready to go out. The server monitors these actions and makes adjustments as necessary.

[1129] Prompt Sentence Examples

[1130] Examples of prompts to input into a generative AI model include:

[1131] Prompt statement:

[1132] "Please wake me up at 6am tomorrow morning, make me some coffee, check the weather and prepare the necessary items, and notify me before you leave."

[1133] This system will support users' independent and efficient lifestyles and help reduce the burden on the nursing care industry.

[1134] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1135] Step 1:

[1136] The server collects the user's basic information (name, age, address, contact details) and stores it in a database. The input is the user's registration information, and the output is the user information in the database. Specifically, the user enters information in a web browser, and the server receives it via an HTTP request. The server processes this information and saves it in a database.

[1137] Step 2:

[1138] The server sends basic information to the terminal. The input is user information in the database, and the output is the basic information sent to the terminal. The communication protocol uses HTTP or WebSocket. The server reads information from the database and sends it to the terminal.

[1139] Step 3:

[1140] The terminal receives basic information and reflects it in the system. The input is the basic information received from the server, and the output is the settings within the terminal. The terminal analyzes the received information and saves it in its internal database.

[1141] Step 4:

[1142] The device collects data using voice input, image input, and video input. The input is data on the user's daily activities, and the output is collected digital data. Specifically, a microphone or camera records the user's activities, and the device collects that data.

[1143] Step 5:

[1144] A general-purpose artificial intelligence analyzes collected data and learns user behavior patterns. The input is the collected digital data, and the output is the analysis results. Python libraries (TensorFlow and PyTorch) are used to perform data analysis and pattern recognition.

[1145] Step 6:

[1146] The terminal sends the analysis results to the server. The input is the analysis result data, and the output is the data sent to the server. The terminal sends the results to the server using HTTP or WebSocket.

[1147] Step 7:

[1148] The user issues a voice request such as "Please clean the living room." The input is the user's voice request, and the output is voice data. The microphone receives the user's voice and converts it into digital data.

[1149] Step 8:

[1150] The device analyzes the voice data and recognizes it as a cleaning task. The input is the voice data and the output is task information. The voice data is analyzed using a voice recognition engine (Google Speech-to-Text API) and task information is generated.

[1151] Step 9:

[1152] The device sends a command to the cleaning robot to start cleaning the living room. The input is task information, and the output is a command to the cleaning robot. The command is sent to the cleaning robot via Bluetooth or Wi-Fi.

[1153] Step 10:

[1154] The server monitors the operation of the cleaning robot and checks its progress. The input is the status data of the cleaning robot and the output is a progress report. The server receives the operating status of the cleaning robot in real time via WebSocket and monitors its progress.

[1155] Step 11:

[1156] When cleaning is complete, the server notifies the user, "Cleaning of the living room is complete." The input is the cleaning completion status data, and the output is a notification to the user. The notification is sent via a smartphone app or email.

[1157] Step 12:

[1158] The user issues a voice request such as "Get ready to go out." The input is the user's voice request, and the output is voice data. The microphone captures the voice and processes it as digital data.

[1159] Step 13:

[1160] The device analyzes the voice data and recognizes it as a task for preparing to go out. The input is the voice data, and the output is the preparation task information. The device uses a voice recognition engine to recognize the task.

[1161] Step 14:

[1162] The device sends a request to the server to obtain weather and traffic information. The input is the preparation task information, and the output is the information acquisition request. The request is sent to the server via an HTTP request.

[1163] Step 15:

[1164] The server retrieves the necessary data using the weather information API and traffic information API. The input is an information retrieval request, and the output is weather and traffic information. The server retrieves information using the OpenWeatherMap API and Google Maps API.

[1165] Step 16:

[1166] The weather and traffic information acquired by the server is sent to the terminal. The input is weather and traffic information, and the output is sending information to the terminal. Information is sent to the terminal via HTTP or WebSocket.

[1167] Step 17:

[1168] Based on the information acquired by the terminal, items necessary for going out (e.g., keys, cell phone, medicine, etc.) are prepared. The input is weather information and preparation task information, and the output is a list of prepared items. The location of items is managed with tags, and an automatic picking system is used.

[1169] Step 18:

[1170] When the preparation is complete, the device notifies the user that "You're ready to go out." The input is the preparation status, and the output is a notification to the user. This is done via a smartphone app or a voice notification.

[1171] Step 19:

[1172] When the sensor detects the user falling or an abnormality, the device switches to emergency mode. The input is abnormal data from the sensor, and the output is switching to emergency mode. An abnormality is detected using the acceleration sensor.

[1173] Step 20:

[1174] The device asks the user by voice, "Hey, are you OK?" The input is emergency mode and the output is a voice message. The speaker is used to play the voice message.

[1175] Step 21:

[1176] The device receives and analyzes the user's response via a voice input means. The input is the user's voice response, and the output is the analysis result. A voice recognition engine is used to analyze the voice data and identify keywords such as "help."

[1177] Step 22:

[1178] If there is no response or if there is a response calling for help, the device will send an emergency notification to the server. The input is the analysis result and the output is the emergency notification. Real-time communication is used to contact the server immediately.

[1179] Step 23:

[1180] The server automatically notifies emergency contacts and provides detailed information about the user's current location and situation. The input is an emergency notification, and the output is a notification to the emergency contacts. Notifications are made via SMS, phone, email, etc.

[1181] This system allows users to efficiently perform various tasks while maintaining their independence, and ensures safety by responding quickly in emergencies.

[1182] (Application example 1)

[1183] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1184] This invention aims to solve the problem that current housekeeping support and food delivery systems have difficulty in effectively reflecting users' voice instructions and lifestyle habits, and in particular the lack of optimal menu suggestions that correspond to individual eating habits and health management. It is also necessary to solve the problem that there is a lack of functionality for tracking the progress of ingredients management and delivery in real time, providing advice on ingredients that are in short supply, and responding to emergencies.

[1185] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1186] In this invention, the server includes a voice input unit, an image input unit, an order history learning unit, an ingredient recognition unit, a delivery progress tracking unit, and a unit for supporting healthy eating habits. This allows for optimal menu suggestions and automatic task execution based on the user's voice instructions. It also enables real-time ingredient management and rapid response in emergencies, making it possible to effectively address individual eating habits and health management.

[1187] "Voice input means" refers to a device or software for converting a user's voice into digital data.

[1188] "Image input means" refers to a device or software for capturing still images and inputting them as digital data.

[1189] "Video input means" refers to a device or software for capturing video images and inputting them as digital data.

[1190] An "artificial general intelligence means" is an artificial intelligence system designed to handle a wide variety of tasks.

[1191] The "means for learning lifestyle habits" is a system for collecting and analyzing data on users' daily behavior and habits.

[1192] "Means for automating household chores" refers to devices or systems that automate everyday household tasks such as cleaning and cooking.

[1193] "Means to assist with going out" refers to a system that provides necessary information and assists with preparations when going out.

[1194] "Measures to respond in emergencies" refers to a system for responding quickly when an accident or abnormality occurs.

[1195] The "means for learning order history" is a system that analyzes a user's past order data and learns their preferences and tendencies.

[1196] The "means for recognizing ingredients" is a system that analyzes image and video data to identify the type of food.

[1197] "Means for tracking delivery progress" refers to a system that monitors the progress of delivery in real time and notifies the user.

[1198] The "means for supporting healthy eating habits" is a system that suggests nutritionally balanced meals based on the user's health condition and eating habits data.

[1199] The present invention is designed as a system to support the daily life of a user. A specific embodiment of this system is shown below. This system includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for learning order history, a means for recognizing ingredients, a means for tracking delivery progress, and a means for supporting healthy eating habits.

[1200] Hardware and software used

[1201] The main components of the system include:

[1202] Voice input method: Google Speech-to-Text API

[1203] Image input method: Smartphone camera, TensorFlow

[1204] Video input method: Smartphone video camera, TensorFlow

[1205] General artificial intelligence means: GPT-4 (Generative Pre-trained Transformer 4)

[1206] How we learn your habits: Firebase, Google Cloud Storage

[1207] Automating household chores: Robot vacuum cleaners (e.g., Roomba)

[1208] Ways to help you get out: Google Maps API, Weather API

[1209] Emergency Response: Twilio API

[1210] How to learn order history: Firebase, Google Cloud Storage

[1211] Methods for identifying ingredients: TensorFlow, image recognition algorithms

[1212] Ways to track delivery progress: Firebase, Realtime Database

[1213] A tool to support healthy eating habits: Nutritional Analysis API

[1214] System Operation

[1215] Voice instructions and order history learning

[1216] When a user speaks to their smartphone, saying "Order dinner," the smartphone's voice input device converts this speech into digital data. This data is then converted into text using the Google Speech-to-Text API. The text data is then analyzed by GPT-4, which uses a model trained on the user's past ordering history and preferences to suggest the optimal menu.

[1217] Ingredient recognition and management

[1218] When a user scans the inside of their refrigerator with their smartphone camera, the image input means sends the captured image to TensorFlow, which recognizes ingredients and determines what is missing. The recognized data is stored in Firebase and used to provide advice to the user.

[1219] Delivery progress tracking and emergency response

[1220] Once an order is placed, the server sends a request to the delivery service, and the delivery progress is tracked in real time via Firebase. Users can check the current delivery status through their smartphone app. Furthermore, if an emergency occurs during delivery, a notification will be sent to emergency contacts using the Twilio API.

[1221] Supporting healthy eating habits

[1222] A nutrition analysis API is used to analyze the user's eating habits data, allowing the system to suggest nutritionally balanced meals based on the user's health status and eating habits.

[1223] Specific examples

[1224] When User A says "Order dinner" via voice input, the GPT-4-based system references their past order history and suggests the most suitable menu for the user. For example, if they have frequently ordered Italian food in the past, menu items such as pizza and pasta will be suggested. When the user confirms "Order this," the order is confirmed and the delivery progress is tracked on Firebase.

[1225] Examples of prompt statements

[1226] Generate a response when a user asks for a dinner order, making menu suggestions that take into account their ordering history and preferences.

[1227] This seamlessly integrates a series of operations from voice instructions to delivery, greatly improving user convenience.

[1228] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1229] Step 1:

[1230] The user speaks to their smartphone and says, "Order dinner."

[1231] Input: User's voice data

[1232] How it works: The smartphone's voice input method captures audio.

[1233] Output: Converts audio data into digital data

[1234] Step 2:

[1235] The converted audio data is sent to the Google Speech-to-Text API and converted into text data.

[1236] Input: Digital audio data

[1237] How it works: Converts speech to text using the Google Speech-to-Text API

[1238] Output: Text data

[1239] Step 3:

[1240] Text data is input into GPT-4, and the optimal menu is suggested based on a model that has learned the user's past ordering history and preferences.

[1241] Input: User's instruction text data, past order history

[1242] How it works: The GPT-4 model analyzes text data and generates the optimal menu.

[1243] Output: Menu suggestion text

[1244] Step 4:

[1245] Menu suggestions are displayed to the user for selection or confirmation.

[1246] Input: Menu suggestion text

[1247] Behavior: Displays a menu on the smartphone screen and accepts user input.

[1248] Output: User selection or confirmation information

[1249] Step 5:

[1250] When the user selects or confirms a menu item, the information is sent to the server to confirm the order.

[1251] Input: User selection or confirmation information

[1252] How it works: The server receives the order information and sends a request to the delivery service.

[1253] Output: Confirmed order information

[1254] Step 6:

[1255] Based on the confirmed order information, the server stores delivery progress tracking information in Firebase and updates it in real time.

[1256] Input: Confirmed order information

[1257] How it works: Store order data in Firebase and get real-time progress information from the delivery service.

[1258] Output: Delivery progress information

[1259] Step 7:

[1260] Delivery progress information will be available to check on a smartphone app and notified to users.

[1261] Input: Delivery progress information

[1262] Behavior: Display progress on smartphone app and notify user

[1263] Output: Delivery progress notification

[1264] Step 8:

[1265] In the event of an emergency, the server uses the Twilio API to send a notification to emergency contacts.

[1266] Input: Emergency detection information

[1267] How it works: Sends SMS and phone calls to emergency contacts via the Twilio API

[1268] Output: Emergency notification sent

[1269] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1270] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting people going out, a means for responding to emergencies, and an emotion engine that recognizes the emotions of the user. Specific embodiments of this system are described below.

[1271] System Overview

[1272] When the user performs the initial system setup, the server stores basic information in a database and sends it to the device. The device uses voice, image, and video input to learn and analyze the user's lifestyle habits in real time. The general artificial intelligence means recognizes the user's behavioral patterns based on this data and provides optimal support for housework and outings. The emotion engine also recognizes the user's emotions and responds as needed. Furthermore, if the sensor means detects an abnormality, it promptly notifies emergency contacts.

[1273] Housework support

[1274] For example, if a user issues a voice command such as "Please clean the living room," the device analyzes the voice data and executes the cleaning task. The server monitors the progress from the device and notifies the user when cleaning is complete. This cleaning task is then automatically executed by the cleaning robot.

[1275] Going out assistance

[1276] When the user instructs the device to "get ready to go out," the device receives the instruction via voice input means and sends a request to the server to check the weather and traffic conditions at the destination. The server obtains this information and sends it to the device, which then uses it to prepare items needed for going out (such as keys, a mobile phone, medicine, etc.). The device also notifies the user when these preparations are complete.

[1277] Emergency response

[1278] When the sensor means detects a fall or other abnormality, the device switches to emergency mode and confirms the user's condition by voice. It asks, "Mr. / Ms. XX, are you OK?" If there is no response or if the user responds with "Help me," the device sends an emergency notification to the server, which then automatically notifies the emergency contacts. The emergency contacts are provided with the user's current location and status in real time.

[1279] Introducing the Emotion Engine

[1280] The emotion engine analyzes the user's emotions from their voice and facial expressions. For example, if a user says, "I'm a little tired," the device will analyze the user's tone of voice and facial expressions to recognize that emotion. If the emotion engine detects the user's stress or anxiety, it will play relaxing music or provide the necessary support.

[1281] Example

[1282] Housework support

[1283] When a user says in a tired voice, "Please clean the living room," the device uses its emotion engine to analyze the user's level of fatigue and sends the data to the server. The server then executes the cleaning task and gently notifies the user with a voice message saying, "The living room has been cleaned. Please take a short rest."

[1284] Going out assistance

[1285] When the user instructs the device to "get ready to go out" and the emotion engine detects that the user is stressed, the device will make suggestions to help the user relax (for example, by taking deep breaths beforehand or playing music to relieve stress), thereby helping the user to feel at ease when going out.

[1286] Emergency response

[1287] If the device's sensor detects a fall and the emotion engine analyzes the user's voice tone and determines that the user is in a panic, the server will notify emergency contacts of the situation and promptly notify caregivers and family members. The analysis results from the emotion engine are useful in determining the priority of emergency responses.

[1288] Through these functions, this system can support users in living independently and reduce the burden on the nursing care industry.

[1289] The processing flow will be explained below.

[1290] Housework support

[1291] Step 1:

[1292] The user issues a voice command such as "Please clean the living room."

[1293] Step 2:

[1294] The terminal detects the user's voice using the voice input means and performs voice recognition.

[1295] Step 3:

[1296] The device uses an emotion engine to analyze the user's voice tone and recognize that the user is tired.

[1297] Step 4:

[1298] The device sends the recognized voice data and emotion data to the server.

[1299] Step 5:

[1300] The server analyzes voice commands and emotional data to determine the "cleaning task" and considers responses that will help the user relax.

[1301] Step 6:

[1302] The server issues instructions to the cleaning robot, which then starts cleaning the living room.

[1303] Step 7:

[1304] During cleaning, the server monitors the progress.

[1305] Step 8:

[1306] When cleaning is complete, the cleaning robot sends a completion report to the server.

[1307] Step 9:

[1308] The server receives the completion report and gently notifies the user via the terminal with a voice message saying, "The living room has been cleaned. Please take a short rest."

[1309] Going out assistance

[1310] Step 1:

[1311] The user issues a voice command such as "Get ready to go out."

[1312] Step 2:

[1313] The terminal detects the user's voice using the voice input means and performs voice recognition.

[1314] Step 3:

[1315] The device uses an emotion engine to analyze the user's voice tone and recognize that they are feeling stressed.

[1316] Step 4:

[1317] The device sends the recognized voice data and emotion data to the server.

[1318] Step 5:

[1319] The server analyzes voice instructions and emotional data and obtains information for going out (weather, traffic) from the Internet.

[1320] Step 6:

[1321] The server transmits the acquired information to the terminal.

[1322] Step 7:

[1323] The device prepares the necessary equipment for going out (such as keys, cell phone, medicine, etc.) and also makes suggestions for relaxation (such as taking deep breaths beforehand or playing music to relieve stress).

[1324] Step 8:

[1325] The device will notify the user that it is ready to go, saying, "You're ready to go! Relax and enjoy your trip."

[1326] Emergency response

[1327] Step 1:

[1328] The device's sensor means detects an abnormality (e.g., a fall, prolonged inactivity).

[1329] Step 2:

[1330] The terminal uses an emotion engine to analyze the user's voice tone and determine the user's emotional state.

[1331] Step 3:

[1332] The device will ask aloud, "Mr. / Ms. XX, are you okay?"

[1333] Step 4:

[1334] The user responds or does not respond.

[1335] Step 5:

[1336] If there is no response, the device sends an emergency notification to the server, which also includes emotional data.

[1337] Step 6:

[1338] The server sends a notification to emergency contacts, which includes the user's current location, a description of the situation, and their emotional state.

[1339] Step 7:

[1340] The server notifies the terminal of the completion of the contact and reports the information to the user by voice.

[1341] Learning about lifestyle habits

[1342] Step 1:

[1343] The user goes about their daily life.

[1344] Step 2:

[1345] The terminal observes and records the user's behavior using audio, image, and video input means.

[1346] Step 3:

[1347] The device also uses an emotion engine to record the user's emotional state from their facial expressions and voice.

[1348] Step 4:

[1349] The device transmits the recorded data and emotion data to the server.

[1350] Step 5:

[1351] The server analyzes the data and uses AGI to learn the user's behavioral and emotional patterns.

[1352] Step 6:

[1353] The server feeds back the learning results to the device and reflects them in the next support session.

[1354] The above is a detailed description of the processing steps that combine the emotion engine in the "AssistNext" system.

[1355] Example 2

[1356] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1357] In modern society, with the increasing number of elderly people and busy families, there is a demand for systems to support daily life. Conventional systems are limited to automating specific tasks or providing partial support, and do not provide sufficient comprehensive support for daily life. In addition, they are unable to respond quickly in emergencies or understand the user's emotional state, leaving issues in improving user safety and quality of life.

[1358] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1359] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for recognizing a user's emotions, a means for monitoring the progress of tasks being performed and providing feedback, and a means for analyzing a user's instructions and executing tasks. This allows for comprehensive support of the user's daily life, enabling a rapid response in emergencies and appropriate support based on the user's emotional state.

[1360] Below are definitions of important words included in the rewritten claims.

[1361] "Voice input means" refers to a device or software that captures the user's voice and analyzes the voice data.

[1362] "Image input means" refers to a device or software that captures a still image of the user and analyzes it.

[1363] "Video input means" refers to a device or software that captures and analyzes dynamic video data of a user.

[1364] "General artificial intelligence means" is an artificial intelligence technology that learns and analyzes a user's behavioral patterns and lifestyle habits to provide optimal support.

[1365] The "means for learning lifestyle habits" is a device or software that observes the user's daily actions and habits and learns lifestyle patterns based on that data.

[1366] A "means for automating household chores" is a device or software for automatically performing household chores such as cleaning and laundry based on instructions from a user.

[1367] "Means for assisting going out" refers to devices or software that provide the user with the information they need when going out and support their preparations.

[1368] "Emergency response measures" refer to devices or software that detect emergencies based on sensors and analytical results and respond promptly.

[1369] The "means for recognizing the user's emotions" refers to a device or software for analyzing and recognizing the user's emotional state from their voice and facial expressions.

[1370] The "means for monitoring the progress of an executed task and providing feedback" refers to a device or software for monitoring the progress of a specified task in real time and providing feedback to the user at appropriate times.

[1371] "Means for analyzing user instructions and executing tasks" refers to a device or software that analyzes instructions from a user in the form of voice or other input and executes an appropriate task based on those instructions.

[1372] MODE FOR CARRYING OUT THE INVENTION

[1373] The present invention is a system that comprehensively supports a user's daily life. This system includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating housework, a means for assisting with going out, a means for responding to emergencies, a means for recognizing the user's emotions, a means for monitoring the progress of an executed task and providing feedback, and a means for analyzing the user's instructions and executing the task.

[1374] Hardware Configuration

[1375] Users use a device to input voice, images, and video. This device is equipped with a microphone, camera, and sensors. The device sends the data over a network to a server for further processing. The server is a computer system equipped with a high-performance CPU and a large amount of memory, and can run on a cloud platform.

[1376] Software Configuration

[1377] The device uses speech recognition APIs (e.g., Google Cloud Speech-to-Text or IBM Watson Speech to Text), image analysis APIs, and video analysis APIs. The server uses general artificial intelligence methods (e.g., TensorFlow or PyTorch) to learn the user's behavioral patterns and update a database (e.g., MongoDB or MySQL). The Microsoft Azure Emotion API can be used as an emotion engine. Kafka or RabbitMQ can be used as a real-time data streaming technology to monitor the progress of tasks.

[1378] Specific examples

[1379] Housework support

[1380] When a user issues a voice command such as "Please clean the living room," the device captures the voice and converts it into text data using a speech recognition API. The converted data is sent to a server, which analyzes the command and assigns a cleaning task to a cleaning robot (e.g., an iRobot Roomba). The cleaning progress is monitored in real time, and the user is notified when the cleaning is complete.

[1381] Going out assistance

[1382] When a user verbally commands "get ready to go out," the device captures the voice and converts it into text data using a speech recognition API. The converted data is sent to a server, which then uses an external API (e.g., OpenWeatherMap or Google Maps API) to obtain weather and traffic information for the destination. The device then prepares items needed for going out (e.g., keys, cell phone, medicine, etc.) based on the obtained information and notifies the user when they are ready.

[1383] Emergency response

[1384] When the device's built-in sensor detects an abnormality, such as a fall, the device switches to emergency mode. An emergency notification is sent to the server, which then automatically notifies emergency contacts using a business API (e.g., Twilio API). In the event of an emergency, the user's current location and status are provided in real time.

[1385] Introducing the Emotion Engine

[1386] If a user says, "I'm a little tired," the device will analyze their voice tone and facial expressions with its emotion engine to recognize their emotion. If it determines that the user is feeling stressed, the device will play relaxing music or provide appropriate support.

[1387] Prompt Sentence Examples

[1388] "User automation assistance system"

[1389] input:

[1390] User voice commands (e.g., "Please clean the living room")

[1391] The user's emotional state (e.g., "I feel a little tired")

[1392] Output:

[1393] Interprets voice commands and performs specific tasks

[1394] Analyze emotions with an emotion engine and provide optimal responses

[1395] As described above, this system can provide multifunctional and flexible support to help users live independently.

[1396] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1397] Step 1: User voice input

[1398] The user issues commands by voice. For example, the user might say to the device, "Please clean the living room."

[1399] Input: User's voice data

[1400] Output: Audio data is captured

[1401] What happens: The device's microphone captures audio data, which is temporarily stored on the device.

[1402] Step 2: Analyzing the audio data

[1403] The device converts the captured voice data into text data using a voice recognition API.

[1404] Input: Captured audio data

[1405] Output: Converted text data

[1406] How it works: The device calls the Google Cloud Speech-to-Text API to convert the voice data into text, which is then immediately sent to the server.

[1407] Step 3: Learning behavioral patterns and updating the database

[1408] The server analyzes the received text data and updates a database for learning user behavior patterns.

[1409] Input: Converted text data

[1410] Output: Updated database

[1411] Specific operation: The server uses TensorFlow to analyze the received text data, learn behavioral patterns, store the results in MongoDB, and update the database.

[1412] Step 4: Task execution instructions

[1413] The server sends instructions to the terminal to execute a task based on the analysis results.

[1414] Input: Analysis results

[1415] Output: Instructions to the terminal

[1416] Specific operation: The server uses the REST API to send specific execution instructions (e.g., "Send the cleaning robot to the living room") to the device.

[1417] Step 5: Monitoring and feedback on the execution of tasks

[1418] The server monitors the progress of the execution tasks received from the terminal and provides the information as feedback to the user in real time.

[1419] Input: Progress data of the execution task

[1420] Output: Feedback to the user

[1421] Specific operation: The device sends progress data from the cleaning robot to the server, which receives it and notifies the user that "cleaning is complete."

[1422] Step 6: Emergency response

[1423] If the device's sensor detects an abnormality, it switches to emergency mode and sends an emergency notification to the server.

[1424] Input: Anomaly detection data from sensors

[1425] Output: Send emergency notification

[1426] How it works: If a device's sensor detects, for example, a fall, it sends that data to a server via AWS IoT, which then uses the Twilio API to send an emergency notification to emergency contacts.

[1427] Step 7: Sentiment analysis and response

[1428] The device analyzes the user's voice and facial expression data using an emotion engine and responds appropriately based on the results.

[1429] Input: Voice data and facial expression data

[1430] Output: Sentiment analysis results and corresponding actions

[1431] How it works: The device uses the Microsoft Azure Emotion API to analyze voice tone and facial expressions to determine the user's emotional state. For example, if the user says, "I'm a little tired," the device will play relaxing music.

[1432] As described above, specific operations are performed at each step, and ultimately a system that comprehensively supports the user's life is realized.

[1433] (Application example 2)

[1434] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1435] Supporting the elderly and busy families is an important issue in modern society. However, existing support systems do not fully consider users' emotions and lifestyles, and lack comprehensive support for household chores, preparations for going out, and emergency response. Furthermore, their ability to analyze and respond to emotional states such as stress and fatigue is limited. Therefore, there is a need for systems that can support users' overall lifestyles and enable them to live their daily lives with peace of mind.

[1436] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1437] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores within the home, a means for assisting with going out, a means for responding to emergencies, an emotion engine means for recognizing a user's emotions and suggesting appropriate actions, a means for controlling a household robot to perform cleaning tasks based on voice input, a means for providing information to support going out based on voice input, and a means for analyzing the user's emotions based on voice input and responding appropriately. This enables the server to support the user's overall lifestyle, seamlessly supporting housework, going out, and responding to emergencies. Furthermore, analyzing the user's emotional state and responding appropriately can provide a more comfortable and secure daily life.

[1438] "Voice input means" refers to a device or system for recognizing a user's voice and processing it as data.

[1439] "Image input means" refers to a device or system for capturing still images and processing them as data.

[1440] "Video input means" refers to a device or system for capturing video and processing it as data.

[1441] "General artificial intelligence means" is a system that uses artificial intelligence technology that can handle a variety of tasks, and is used to analyze user behavior and lifestyle habits.

[1442] The "means for learning lifestyle habits" is a system that collects and analyzes the user's daily behavioral patterns and habits as data, and provides optimal support based on that data.

[1443] A "means for automating household chores" is a device or system for automatically performing household chores such as cleaning and laundry.

[1444] "Means for assisting users in going out" refers to a system that provides weather and traffic information and supports users in going out.

[1445] "Means for responding to emergencies" refers to a system that detects abnormalities or emergencies in users and responds quickly.

[1446] The "emotion engine means" is a system that analyzes the user's emotions from their voice and facial expressions and suggests appropriate actions.

[1447] The "means for controlling a household robot" is a mechanism for operating a household robot based on voice input to perform a specific task.

[1448] The "means for providing outing support information" is a system for providing outing support information such as weather and traffic based on voice input.

[1449] The "means for analyzing emotions and responding" is a system that analyzes emotions from the user's voice and suggests relaxation methods based on that.

[1450] System Overview

[1451] The system according to the present invention includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, an emotion engine means, a means for controlling a household robot, a means for providing information to support going out, and a means for analyzing emotions and responding accordingly. This enables the system to support the user's life in general, seamlessly supporting housework, going out, and responding to emergencies.

[1452] Hardware and Software Configuration

[1453] The system uses the following hardware and software:

[1454] Smartphone: Equipped with a built-in microphone for voice recognition and a camera for capturing images and videos.

[1455] Domestic robots: Robots designed to automatically perform cleaning and other household chores.

[1456] General artificial intelligence software: Software that analyzes a user's behavior and lifestyle habits and provides optimal actions.

[1457] Emotion analysis engine: Software that analyzes the user's voice and facial expressions to recognize and respond to emotions.

[1458] Emergency notification system: A notification system for rapid response in emergencies.

[1459] Example of a system

[1460] Automating Housework

[1461] When a user issues a voice command such as "Please clean the living room," the smartphone's voice input means recognizes this and sends the instruction to the home robot. When the cleaning is complete, the system notifies the user by voice or through an application. If the emotion engine detects that the user is tired, it will gently notify the user, saying, "The living room has been cleaned. Please take a short rest."

[1462] Assistance with going out

[1463] When a user instructs the system to "get ready to go out," the system retrieves weather and traffic information and prepares a list of items needed for going out. For example, if the weather forecast predicts rain, the system will notify the user, "Don't forget to take an umbrella." If the emotion engine detects the user's stress, the system will suggest deep breathing or play relaxing music.

[1464] Emergency response

[1465] The system constantly monitors sensors to respond to emergencies. For example, if the user falls, the system will ask aloud, "Are you OK?" If there is no response or if the user responds with "Help me," it will automatically notify pre-defined emergency contacts. At this time, the user's current location and status will also be provided in real time.

[1466] Emotional engine response

[1467] The system uses an emotion engine to analyze the user's emotions from their voice and facial expressions. For example, if a user says, "I'm a little tired," the device will analyze their voice tone and facial expressions to recognize that emotion. If the emotion engine detects stress or anxiety in the user, it will play relaxing music or provide the necessary support.

[1468] Specific examples

[1469] Prompt: "Please clean the living room. I'm tired, so please play some relaxing music."

[1470] Prompt: "Get ready to go out. Check the weather and tell me what you need."

[1471] This system allows users to receive support in all aspects of their daily lives, allowing them to live with peace of mind. It also improves the quality of life of users by providing appropriate responses through emotion analysis.

[1472] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1473] Step 1:

[1474] The user issues a voice command. The smartphone's microphone captures the voice input and prepares it for processing as audio data.

[1475] Input: User's voice

[1476] Output: Audio data

[1477] Step 2:

[1478] The device converts the voice data into text using speech recognition software (speech_recognition library).

[1479] Input: Audio data

[1480] Output: Recognized text

[1481] Step 3:

[1482] The device analyzes the recognized text and determines the content of the instruction. For example, if the keyword "cleaning" is included, it will be recognized as an instruction to control a household robot.

[1483] Input: Text data

[1484] Output: Command content

[1485] Step 4:

[1486] Based on the analysis results, the device sends the corresponding task (e.g., cleaning the living room) to the home robot, which then carries out the cleaning task according to the received instructions.

[1487] Input: Command content

[1488] Output: Instructions to execute the cleaning task

[1489] Step 5:

[1490] The home robot monitors the progress of the cleaning task and sends the status upon completion to the terminal, which receives the information and notifies the user.

[1491] Input: Cleaning task progress

[1492] Output: Completion notification

[1493] Step 6:

[1494] The device uses an emotion engine to analyze the user's voice tone and facial expressions. For example, if the device detects that the user is tired, it will suggest playing relaxing music.

[1495] Input: Speech and facial expression data

[1496] Output: Emotion analysis results

[1497] Step 7:

[1498] Based on the analysis results, the device will suggest and execute appropriate actions (e.g., playing relaxing music).

[1499] Input: Sentiment analysis results

[1500] Output: Suggestions and action taken

[1501] Step 8:

[1502] The user can then issue an additional voice command, which the device will then recognize, interpret, and execute again. For example, based on a command such as "Get ready to go out," the device will retrieve weather and traffic information and provide it to the user.

[1503] Input: New voice command

[1504] Output:Outing support information

[1505] Through this series of steps, the system can comprehensively support the user's daily life and provide a comfortable living environment.

[1506] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1507] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1508] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1509] [Fourth embodiment]

[1510] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1511] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1512] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1513] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1514] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1515] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1516] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1517] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1518] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1519] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1520] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1521] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1522] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1523] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting people going out, and a means for responding to emergencies. Specific embodiments of the system are described below.

[1524] System Overview

[1525] When the user performs the initial system setup, the server stores basic information in a database and sends it to the device. The device uses voice, image, and video input to learn and analyze the user's lifestyle habits in real time. The general artificial intelligence device recognizes the user's behavioral patterns based on this data and provides optimal support for housework and outings. Additionally, if the sensor device detects an abnormality, it promptly notifies emergency contacts.

[1526] Housework support

[1527] For example, if a user issues a voice command such as "Please clean the living room," the device analyzes the voice data and executes the cleaning task. The server monitors the progress from the device and notifies the user when cleaning is complete. This cleaning task is then automatically executed by the cleaning robot.

[1528] Going out assistance

[1529] When the user instructs the device to "get ready to go out," the device receives the instruction via voice input means and sends a request to the server to check the weather and traffic conditions at the destination. The server obtains this information and sends it to the device, which then uses it to prepare items needed for going out (such as keys, a mobile phone, medicine, etc.). The device also notifies the user when these preparations are complete.

[1530] Emergency response

[1531] When the sensor means detects a fall or other abnormality, the device switches to emergency mode and confirms the user's condition by voice. It asks, "Mr. / Ms. XX, are you OK?" If there is no response or if the user responds with "Help me," the device sends an emergency notification to the server, which then automatically notifies the emergency contacts. The emergency contacts are provided with the user's current location and status in real time.

[1532] Example

[1533] For example, when a user starts their morning routine, the device will use a sensor to detect when the user wakes up and automatically start the coffee maker to brew coffee. It will also help prepare breakfast and get dressed. Before going out, it will obtain weather and traffic information and prepare the necessary equipment. Throughout this series of actions, the server constantly monitors the data and makes any necessary adjustments.

[1534] Through these functions, this system can support users in living independently and reduce the burden on the nursing care industry.

[1535] The processing flow will be explained below.

[1536] Housework support

[1537] Step 1:

[1538] The user issues a voice command such as "Please clean the living room."

[1539] Step 2:

[1540] The terminal detects the user's voice using the voice input means and performs voice recognition.

[1541] Step 3:

[1542] The device sends the recognized voice data to the server.

[1543] Step 4:

[1544] The server analyzes the voice commands and determines the "cleaning task."

[1545] Step 5:

[1546] The server issues instructions to the cleaning robot, which then starts cleaning the living room.

[1547] Step 6:

[1548] During cleaning, the server monitors the progress.

[1549] Step 7:

[1550] When cleaning is complete, the cleaning robot sends a completion report to the server.

[1551] Step 8:

[1552] The server receives the completion report and notifies the user via the terminal by voice, "The living room has been cleaned."

[1553] Going out assistance

[1554] Step 1:

[1555] The user issues a voice command such as "Get ready to go out."

[1556] Step 2:

[1557] The terminal detects the user's voice using the voice input means and performs voice recognition.

[1558] Step 3:

[1559] The device sends the recognized voice data to the server.

[1560] Step 4:

[1561] The server analyzes the voice instructions and retrieves information for going out (weather, traffic) from the Internet.

[1562] Step 5:

[1563] The server transmits the acquired information to the terminal.

[1564] Step 6:

[1565] The device prepares the necessary equipment for going out (e.g., keys, mobile phone, medicine, etc.).

[1566] Step 7:

[1567] The device notifies the user that it is ready to go, saying "You're ready to go out."

[1568] Emergency response

[1569] Step 1:

[1570] The device's sensor means detects an abnormality (e.g., a fall, prolonged inactivity).

[1571] Step 2:

[1572] The device will switch to emergency mode and ask a voice message asking, "Mr. / Ms. XX, are you okay?"

[1573] Step 3:

[1574] The user responds or does not respond.

[1575] Step 4:

[1576] If there is no response, the device sends an emergency notification to the server.

[1577] Step 5:

[1578] The server sends a notification to the emergency contact, which includes the user's current location and a description of the situation.

[1579] Step 6:

[1580] The server notifies the terminal of the completion of the contact and reports the information to the user by voice.

[1581] Learning about lifestyle habits

[1582] Step 1:

[1583] The user goes about their daily life.

[1584] Step 2:

[1585] The terminal observes and records the user's behavior using audio, image, and video input means.

[1586] Step 3:

[1587] The terminal transmits the recorded data to the server.

[1588] Step 4:

[1589] The server analyzes the data and uses AGI to learn user behavior patterns.

[1590] Step 5:

[1591] The server feeds the learning results back to the device and reflects them in the next support.

[1592] The above is a detailed description of the processing steps of the "AssistNext" system.

[1593] Example 1

[1594] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1595] Modern home life involves many tasks that require time and effort, such as housework, preparing to go out, and responding to emergencies. Performing these daily tasks independently is particularly difficult for the elderly and those with physical limitations. Furthermore, there is a lack of comprehensive systems for efficiently performing these tasks. Furthermore, the separate functions for housework support and emergency response pose a challenge, resulting in low user convenience.

[1596] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1597] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for analyzing and managing data for each processing step, a means for communicating with a cloud server, a means for notifying the user, and a means for automatically executing tasks. This allows the user to use multiple functions, such as support for household chores, preparation for going out, and emergency response, all in one system.

[1598] The "voice input means" is a device for recognizing the user's voice and converting it into digital data.

[1599] "Image input means" refers to a device for capturing still images and processing them as digital data.

[1600] "Video input means" is a device that captures a series of images and digitally processes them as video data.

[1601] "General artificial intelligence means" is a system that analyzes a variety of data, recognizes patterns using learning algorithms, and performs adaptive processing.

[1602] "Means for learning lifestyle habits" refers to technology that collects and analyzes data on the user's daily behavior and recognizes its patterns.

[1603] "Means for automating household chores" are devices or systems for mechanically performing household tasks such as cleaning and cooking.

[1604] The "means for assisting going out" is a system that provides information and prepares items to help the user prepare to go out.

[1605] "Means for responding to emergencies" refers to devices or systems that can quickly detect abnormalities and take appropriate action when a user is in an emergency.

[1606] "Means for analyzing and managing data at each processing step" refers to technology for analyzing and managing the data generated at each processing step.

[1607] "Means for communicating with a cloud server" refers to a device or system for sending and receiving data to and from a cloud server via the Internet.

[1608] "Means for notifying the user" refers to a technique for notifying the user of necessary information from the system.

[1609] A "means for automatically executing a task" is a system that automatically processes and executes a task based on a user's instructions and circumstances.

[1610] MODE FOR CARRYING OUT THE INVENTION

[1611] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting users when going out, and a means for responding to emergencies. The system aims to support and streamline the daily life of a user. Specific embodiments for carrying out the present invention will be described below.

[1612] Initial System Setup

[1613] The server collects basic information about the user and stores it in a database. This basic information includes name, age, address, contact details, etc. The server sends this information to the device, which then updates the system with the received information. The communication protocol is HTTP or WebSocket.

[1614] Learning about lifestyle habits

[1615] The device collects user behavior data in real time using audio input means (e.g., microphone), image input means (e.g., camera), and video input means (e.g., video camera). The general artificial intelligence means analyzes this data and learns the user's lifestyle habits. Specifically, it uses machine learning libraries such as TensorFlow and PyTorch. The analysis results are sent to a server and stored in a database.

[1616] Housework support

[1617] When a user makes a voice request such as "Please clean the living room," the device receives the voice data through the microphone. This data is analyzed by a voice recognition engine (e.g., Google Speech-to-Text API) and recognized as a cleaning task. The device then sends a command to a cleaning robot (e.g., Roomba) via Bluetooth or Wi-Fi to start cleaning the living room. The server monitors the cleaning robot's progress, and when the task is completed, it notifies the user that "cleaning of the living room is complete."

[1618] Going out assistance

[1619] When the user issues a voice command such as "Get ready to go out," the device receives the instruction through the microphone. The device then sends a request to the server to obtain weather and traffic information. The server obtains this information using the OpenWeatherMap API and Google Maps API and sends it to the device. Based on the obtained information, the device automatically prepares necessary items such as keys, a cell phone, and medicine. Once preparations are complete, the device notifies the user that "You're ready to go out."

[1620] Emergency response

[1621] When the sensor means detects that the user has fallen or something is wrong, the device switches to emergency mode. The device asks aloud, "Mr. / Ms. XX, are you OK?" and if there is no response or if the user responds with something like "Help me," it sends an emergency notification to the server. Based on this, the server automatically notifies emergency contacts, notifying them of the user's current location and situation in detail. During this process, emergency notifications are made via SMS, phone, and email.

[1622] Example

[1623] Let's take the example of a user starting their morning routine. The device uses sensors to detect that the user has woken up and automatically starts the coffee maker to brew coffee. It also helps the user prepare breakfast and get dressed, and obtains weather and traffic information to get ready to go out. The server monitors these actions and makes adjustments as necessary.

[1624] Prompt Sentence Examples

[1625] Examples of prompts to input into a generative AI model include:

[1626] Prompt statement:

[1627] "Please wake me up at 6am tomorrow morning, make me some coffee, check the weather and prepare the necessary items, and notify me before you leave."

[1628] This system will support users' independent and efficient lifestyles and help reduce the burden on the nursing care industry.

[1629] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1630] Step 1:

[1631] The server collects the user's basic information (name, age, address, contact details) and stores it in a database. The input is the user's registration information, and the output is the user information in the database. Specifically, the user enters information in a web browser, and the server receives it via an HTTP request. The server processes this information and saves it in a database.

[1632] Step 2:

[1633] The server sends basic information to the terminal. The input is user information in the database, and the output is the basic information sent to the terminal. The communication protocol uses HTTP or WebSocket. The server reads information from the database and sends it to the terminal.

[1634] Step 3:

[1635] The terminal receives basic information and reflects it in the system. The input is the basic information received from the server, and the output is the settings within the terminal. The terminal analyzes the received information and saves it in its internal database.

[1636] Step 4:

[1637] The device collects data using voice input, image input, and video input. The input is data on the user's daily activities, and the output is collected digital data. Specifically, a microphone or camera records the user's activities, and the device collects that data.

[1638] Step 5:

[1639] A general-purpose artificial intelligence analyzes collected data and learns user behavior patterns. The input is the collected digital data, and the output is the analysis results. Python libraries (TensorFlow and PyTorch) are used to perform data analysis and pattern recognition.

[1640] Step 6:

[1641] The terminal sends the analysis results to the server. The input is the analysis result data, and the output is the data sent to the server. The terminal sends the results to the server using HTTP or WebSocket.

[1642] Step 7:

[1643] The user issues a voice request such as "Please clean the living room." The input is the user's voice request, and the output is voice data. The microphone receives the user's voice and converts it into digital data.

[1644] Step 8:

[1645] The device analyzes the voice data and recognizes it as a cleaning task. The input is the voice data and the output is task information. The voice data is analyzed using a voice recognition engine (Google Speech-to-Text API) and task information is generated.

[1646] Step 9:

[1647] The device sends a command to the cleaning robot to start cleaning the living room. The input is task information, and the output is a command to the cleaning robot. The command is sent to the cleaning robot via Bluetooth or Wi-Fi.

[1648] Step 10:

[1649] The server monitors the operation of the cleaning robot and checks its progress. The input is the status data of the cleaning robot and the output is a progress report. The server receives the operating status of the cleaning robot in real time via WebSocket and monitors its progress.

[1650] Step 11:

[1651] When cleaning is complete, the server notifies the user, "Cleaning of the living room is complete." The input is the cleaning completion status data, and the output is a notification to the user. The notification is sent via a smartphone app or email.

[1652] Step 12:

[1653] The user issues a voice request such as "Get ready to go out." The input is the user's voice request, and the output is voice data. The microphone captures the voice and processes it as digital data.

[1654] Step 13:

[1655] The device analyzes the voice data and recognizes it as a task for preparing to go out. The input is the voice data, and the output is the preparation task information. The device uses a voice recognition engine to recognize the task.

[1656] Step 14:

[1657] The device sends a request to the server to obtain weather and traffic information. The input is the preparation task information, and the output is the information acquisition request. The request is sent to the server via an HTTP request.

[1658] Step 15:

[1659] The server retrieves the necessary data using the weather information API and traffic information API. The input is an information retrieval request, and the output is weather and traffic information. The server retrieves information using the OpenWeatherMap API and Google Maps API.

[1660] Step 16:

[1661] The weather and traffic information acquired by the server is sent to the terminal. The input is weather and traffic information, and the output is sending information to the terminal. Information is sent to the terminal via HTTP or WebSocket.

[1662] Step 17:

[1663] Based on the information acquired by the terminal, items necessary for going out (e.g., keys, cell phone, medicine, etc.) are prepared. The input is weather information and preparation task information, and the output is a list of prepared items. The location of items is managed with tags, and an automatic picking system is used.

[1664] Step 18:

[1665] When the preparation is complete, the device notifies the user that "You're ready to go out." The input is the preparation status, and the output is a notification to the user. This is done via a smartphone app or a voice notification.

[1666] Step 19:

[1667] When the sensor detects the user falling or an abnormality, the device switches to emergency mode. The input is abnormal data from the sensor, and the output is switching to emergency mode. An abnormality is detected using the acceleration sensor.

[1668] Step 20:

[1669] The device asks the user by voice, "Hey, are you OK?" The input is emergency mode and the output is a voice message. The speaker is used to play the voice message.

[1670] Step 21:

[1671] The device receives and analyzes the user's response via a voice input means. The input is the user's voice response, and the output is the analysis result. A voice recognition engine is used to analyze the voice data and identify keywords such as "help."

[1672] Step 22:

[1673] If there is no response or if there is a response calling for help, the device will send an emergency notification to the server. The input is the analysis result and the output is the emergency notification. Real-time communication is used to contact the server immediately.

[1674] Step 23:

[1675] The server automatically notifies emergency contacts and provides detailed information about the user's current location and situation. The input is an emergency notification, and the output is a notification to the emergency contacts. Notifications are made via SMS, phone, email, etc.

[1676] This system allows users to efficiently perform various tasks while maintaining their independence, and ensures safety by responding quickly in emergencies.

[1677] (Application example 1)

[1678] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1679] This invention aims to solve the problem that current housekeeping support and food delivery systems have difficulty in effectively reflecting users' voice instructions and lifestyle habits, and in particular the lack of optimal menu suggestions that correspond to individual eating habits and health management. It is also necessary to solve the problem that there is a lack of functionality for tracking the progress of ingredients management and delivery in real time, providing advice on ingredients that are in short supply, and responding to emergencies.

[1680] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1681] In this invention, the server includes a voice input unit, an image input unit, an order history learning unit, an ingredient recognition unit, a delivery progress tracking unit, and a unit for supporting healthy eating habits. This allows for optimal menu suggestions and automatic task execution based on the user's voice instructions. It also enables real-time ingredient management and rapid response in emergencies, making it possible to effectively address individual eating habits and health management.

[1682] "Voice input means" refers to a device or software for converting a user's voice into digital data.

[1683] "Image input means" refers to a device or software for capturing still images and inputting them as digital data.

[1684] "Video input means" refers to a device or software for capturing video images and inputting them as digital data.

[1685] An "artificial general intelligence means" is an artificial intelligence system designed to handle a wide variety of tasks.

[1686] The "means for learning lifestyle habits" is a system for collecting and analyzing data on users' daily behavior and habits.

[1687] "Means for automating household chores" refers to devices or systems that automate everyday household tasks such as cleaning and cooking.

[1688] "Means to assist with going out" refers to a system that provides necessary information and assists with preparations when going out.

[1689] "Measures to respond in emergencies" refers to a system for responding quickly when an accident or abnormality occurs.

[1690] The "means for learning order history" is a system that analyzes a user's past order data and learns their preferences and tendencies.

[1691] The "means for recognizing ingredients" is a system that analyzes image and video data to identify the type of food.

[1692] "Means for tracking delivery progress" refers to a system that monitors the progress of delivery in real time and notifies the user.

[1693] The "means for supporting healthy eating habits" is a system that suggests nutritionally balanced meals based on the user's health condition and eating habits data.

[1694] The present invention is designed as a system to support the daily life of a user. A specific embodiment of this system is shown below. This system includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for learning order history, a means for recognizing ingredients, a means for tracking delivery progress, and a means for supporting healthy eating habits.

[1695] Hardware and software used

[1696] The main components of the system include:

[1697] Voice input method: Google Speech-to-Text API

[1698] Image input method: Smartphone camera, TensorFlow

[1699] Video input method: Smartphone video camera, TensorFlow

[1700] General artificial intelligence means: GPT-4 (Generative Pre-trained Transformer 4)

[1701] How we learn your habits: Firebase, Google Cloud Storage

[1702] Automating household chores: Robot vacuum cleaners (e.g., Roomba)

[1703] Ways to help you get out: Google Maps API, Weather API

[1704] Emergency Response: Twilio API

[1705] How to learn order history: Firebase, Google Cloud Storage

[1706] Methods for identifying ingredients: TensorFlow, image recognition algorithms

[1707] Ways to track delivery progress: Firebase, Realtime Database

[1708] A tool to support healthy eating habits: Nutritional Analysis API

[1709] System Operation

[1710] Voice instructions and order history learning

[1711] When a user speaks to their smartphone, saying "Order dinner," the smartphone's voice input device converts this speech into digital data. This data is then converted into text using the Google Speech-to-Text API. The text data is then analyzed by GPT-4, which uses a model trained on the user's past ordering history and preferences to suggest the optimal menu.

[1712] Ingredient recognition and management

[1713] When a user scans the inside of their refrigerator with their smartphone camera, the image input means sends the captured image to TensorFlow, which recognizes ingredients and determines what is missing. The recognized data is stored in Firebase and used to provide advice to the user.

[1714] Delivery progress tracking and emergency response

[1715] Once an order is placed, the server sends a request to the delivery service, and the delivery progress is tracked in real time via Firebase. Users can check the current delivery status through their smartphone app. Furthermore, if an emergency occurs during delivery, a notification will be sent to emergency contacts using the Twilio API.

[1716] Supporting healthy eating habits

[1717] A nutrition analysis API is used to analyze the user's eating habits data, allowing the system to suggest nutritionally balanced meals based on the user's health status and eating habits.

[1718] Specific examples

[1719] When User A says "Order dinner" via voice input, the GPT-4-based system references their past order history and suggests the most suitable menu for the user. For example, if they have frequently ordered Italian food in the past, menu items such as pizza and pasta will be suggested. When the user confirms "Order this," the order is confirmed and the delivery progress is tracked on Firebase.

[1720] Examples of prompt statements

[1721] Generate a response when a user asks for a dinner order, making menu suggestions that take into account their ordering history and preferences.

[1722] This seamlessly integrates a series of operations from voice instructions to delivery, greatly improving user convenience.

[1723] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1724] Step 1:

[1725] The user speaks to their smartphone and says, "Order dinner."

[1726] Input: User's voice data

[1727] How it works: The smartphone's voice input method captures audio.

[1728] Output: Converts audio data into digital data

[1729] Step 2:

[1730] The converted audio data is sent to the Google Speech-to-Text API and converted into text data.

[1731] Input: Digital audio data

[1732] How it works: Converts speech to text using the Google Speech-to-Text API

[1733] Output: Text data

[1734] Step 3:

[1735] Text data is input into GPT-4, and the optimal menu is suggested based on a model that has learned the user's past ordering history and preferences.

[1736] Input: User's instruction text data, past order history

[1737] How it works: The GPT-4 model analyzes text data and generates the optimal menu.

[1738] Output: Menu suggestion text

[1739] Step 4:

[1740] Menu suggestions are displayed to the user for selection or confirmation.

[1741] Input: Menu suggestion text

[1742] Behavior: Displays a menu on the smartphone screen and accepts user input.

[1743] Output: User selection or confirmation information

[1744] Step 5:

[1745] When the user selects or confirms a menu item, the information is sent to the server to confirm the order.

[1746] Input: User selection or confirmation information

[1747] How it works: The server receives the order information and sends a request to the delivery service.

[1748] Output: Confirmed order information

[1749] Step 6:

[1750] Based on the confirmed order information, the server stores delivery progress tracking information in Firebase and updates it in real time.

[1751] Input: Confirmed order information

[1752] How it works: Store order data in Firebase and get real-time progress information from the delivery service.

[1753] Output: Delivery progress information

[1754] Step 7:

[1755] Delivery progress information will be available to check on a smartphone app and notified to users.

[1756] Input: Delivery progress information

[1757] Behavior: Display progress on smartphone app and notify user

[1758] Output: Delivery progress notification

[1759] Step 8:

[1760] In the event of an emergency, the server uses the Twilio API to send a notification to emergency contacts.

[1761] Input: Emergency detection information

[1762] How it works: Sends SMS and phone calls to emergency contacts via the Twilio API

[1763] Output: Emergency notification sent

[1764] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1765] The present invention is a system that includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting people going out, a means for responding to emergencies, and an emotion engine that recognizes the emotions of the user. Specific embodiments of this system are described below.

[1766] System Overview

[1767] When the user performs the initial system setup, the server stores basic information in a database and sends it to the device. The device uses voice, image, and video input to learn and analyze the user's lifestyle habits in real time. The general artificial intelligence means recognizes the user's behavioral patterns based on this data and provides optimal support for housework and outings. The emotion engine also recognizes the user's emotions and responds as needed. Furthermore, if the sensor means detects an abnormality, it promptly notifies emergency contacts.

[1768] Housework support

[1769] For example, if a user issues a voice command such as "Please clean the living room," the device analyzes the voice data and executes the cleaning task. The server monitors the progress from the device and notifies the user when cleaning is complete. This cleaning task is then automatically executed by the cleaning robot.

[1770] Going out assistance

[1771] When the user instructs the device to "get ready to go out," the device receives the instruction via voice input means and sends a request to the server to check the weather and traffic conditions at the destination. The server obtains this information and sends it to the device, which then uses it to prepare items needed for going out (such as keys, a mobile phone, medicine, etc.). The device also notifies the user when these preparations are complete.

[1772] Emergency response

[1773] When the sensor means detects a fall or other abnormality, the device switches to emergency mode and confirms the user's condition by voice. It asks, "Mr. / Ms. XX, are you OK?" If there is no response or if the user responds with "Help me," the device sends an emergency notification to the server, which then automatically notifies the emergency contacts. The emergency contacts are provided with the user's current location and status in real time.

[1774] Introducing the Emotion Engine

[1775] The emotion engine analyzes the user's emotions from their voice and facial expressions. For example, if a user says, "I'm a little tired," the device will analyze the user's tone of voice and facial expressions to recognize that emotion. If the emotion engine detects the user's stress or anxiety, it will play relaxing music or provide the necessary support.

[1776] Example

[1777] Housework support

[1778] When a user says in a tired voice, "Please clean the living room," the device uses its emotion engine to analyze the user's level of fatigue and sends the data to the server. The server then executes the cleaning task and gently notifies the user with a voice message saying, "The living room has been cleaned. Please take a short rest."

[1779] Going out assistance

[1780] When the user instructs the device to "get ready to go out" and the emotion engine detects that the user is stressed, the device will make suggestions to help the user relax (for example, by taking deep breaths beforehand or playing music to relieve stress), thereby helping the user to feel at ease when going out.

[1781] Emergency response

[1782] If the device's sensor detects a fall and the emotion engine analyzes the user's voice tone and determines that the user is in a panic, the server will notify emergency contacts of the situation and promptly notify caregivers and family members. The analysis results from the emotion engine are useful in determining the priority of emergency responses.

[1783] Through these functions, this system can support users in living independently and reduce the burden on the nursing care industry.

[1784] The processing flow will be explained below.

[1785] Housework support

[1786] Step 1:

[1787] The user issues a voice command such as "Please clean the living room."

[1788] Step 2:

[1789] The terminal detects the user's voice using the voice input means and performs voice recognition.

[1790] Step 3:

[1791] The device uses an emotion engine to analyze the user's voice tone and recognize that the user is tired.

[1792] Step 4:

[1793] The device sends the recognized voice data and emotion data to the server.

[1794] Step 5:

[1795] The server analyzes voice commands and emotional data to determine the "cleaning task" and considers responses that will help the user relax.

[1796] Step 6:

[1797] The server issues instructions to the cleaning robot, which then starts cleaning the living room.

[1798] Step 7:

[1799] During cleaning, the server monitors the progress.

[1800] Step 8:

[1801] When cleaning is complete, the cleaning robot sends a completion report to the server.

[1802] Step 9:

[1803] The server receives the completion report and gently notifies the user via the terminal with a voice message saying, "The living room has been cleaned. Please take a short rest."

[1804] Going out assistance

[1805] Step 1:

[1806] The user issues a voice command such as "Get ready to go out."

[1807] Step 2:

[1808] The terminal detects the user's voice using the voice input means and performs voice recognition.

[1809] Step 3:

[1810] The device uses an emotion engine to analyze the user's voice tone and recognize that they are feeling stressed.

[1811] Step 4:

[1812] The device sends the recognized voice data and emotion data to the server.

[1813] Step 5:

[1814] The server analyzes voice instructions and emotional data and obtains information for going out (weather, traffic) from the Internet.

[1815] Step 6:

[1816] The server transmits the acquired information to the terminal.

[1817] Step 7:

[1818] The device prepares the necessary equipment for going out (such as keys, cell phone, medicine, etc.) and also makes suggestions for relaxation (such as taking deep breaths beforehand or playing music to relieve stress).

[1819] Step 8:

[1820] The device will notify the user that it is ready to go, saying, "You're ready to go! Relax and enjoy your trip."

[1821] Emergency response

[1822] Step 1:

[1823] The device's sensor means detects an abnormality (e.g., a fall, prolonged inactivity).

[1824] Step 2:

[1825] The terminal uses an emotion engine to analyze the user's voice tone and determine the user's emotional state.

[1826] Step 3:

[1827] The device will ask aloud, "Mr. / Ms. XX, are you okay?"

[1828] Step 4:

[1829] The user responds or does not respond.

[1830] Step 5:

[1831] If there is no response, the device sends an emergency notification to the server, which also includes emotional data.

[1832] Step 6:

[1833] The server sends a notification to emergency contacts, which includes the user's current location, a description of the situation, and their emotional state.

[1834] Step 7:

[1835] The server notifies the terminal of the completion of the contact and reports the information to the user by voice.

[1836] Learning about lifestyle habits

[1837] Step 1:

[1838] The user goes about their daily life.

[1839] Step 2:

[1840] The terminal observes and records the user's behavior using audio, image, and video input means.

[1841] Step 3:

[1842] The device also uses an emotion engine to record the user's emotional state from their facial expressions and voice.

[1843] Step 4:

[1844] The device transmits the recorded data and emotion data to the server.

[1845] Step 5:

[1846] The server analyzes the data and uses AGI to learn the user's behavioral and emotional patterns.

[1847] Step 6:

[1848] The server feeds back the learning results to the device and reflects them in the next support session.

[1849] The above is a detailed description of the processing steps that combine the emotion engine in the "AssistNext" system.

[1850] Example 2

[1851] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1852] In modern society, with the increasing number of elderly people and busy families, there is a demand for systems to support daily life. Conventional systems are limited to automating specific tasks or providing partial support, and do not provide sufficient comprehensive support for daily life. In addition, they are unable to respond quickly in emergencies or understand the user's emotional state, leaving issues in improving user safety and quality of life.

[1853] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1854] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, a means for recognizing a user's emotions, a means for monitoring the progress of tasks being performed and providing feedback, and a means for analyzing a user's instructions and executing tasks. This allows for comprehensive support of the user's daily life, enabling a rapid response in emergencies and appropriate support based on the user's emotional state.

[1855] Below are definitions of important words included in the rewritten claims.

[1856] "Voice input means" refers to a device or software that captures the user's voice and analyzes the voice data.

[1857] "Image input means" refers to a device or software that captures a still image of the user and analyzes it.

[1858] "Video input means" refers to a device or software that captures and analyzes dynamic video data of a user.

[1859] "General artificial intelligence means" is an artificial intelligence technology that learns and analyzes a user's behavioral patterns and lifestyle habits to provide optimal support.

[1860] The "means for learning lifestyle habits" is a device or software that observes the user's daily actions and habits and learns lifestyle patterns based on that data.

[1861] A "means for automating household chores" is a device or software for automatically performing household chores such as cleaning and laundry based on instructions from a user.

[1862] "Means for assisting going out" refers to devices or software that provide the user with the information they need when going out and support their preparations.

[1863] "Emergency response measures" refer to devices or software that detect emergencies based on sensors and analytical results and respond promptly.

[1864] The "means for recognizing the user's emotions" refers to a device or software for analyzing and recognizing the user's emotional state from their voice and facial expressions.

[1865] The "means for monitoring the progress of an executed task and providing feedback" refers to a device or software for monitoring the progress of a specified task in real time and providing feedback to the user at appropriate times.

[1866] "Means for analyzing user instructions and executing tasks" refers to a device or software that analyzes instructions from a user in the form of voice or other input and executes an appropriate task based on those instructions.

[1867] MODE FOR CARRYING OUT THE INVENTION

[1868] The present invention is a system that comprehensively supports a user's daily life. This system includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating housework, a means for assisting with going out, a means for responding to emergencies, a means for recognizing the user's emotions, a means for monitoring the progress of an executed task and providing feedback, and a means for analyzing the user's instructions and executing the task.

[1869] Hardware Configuration

[1870] Users use a device to input voice, images, and video. This device is equipped with a microphone, camera, and sensors. The device sends the data over a network to a server for further processing. The server is a computer system equipped with a high-performance CPU and a large amount of memory, and can run on a cloud platform.

[1871] Software Configuration

[1872] The device uses speech recognition APIs (e.g., Google Cloud Speech-to-Text or IBM Watson Speech to Text), image analysis APIs, and video analysis APIs. The server uses general artificial intelligence methods (e.g., TensorFlow or PyTorch) to learn the user's behavioral patterns and update a database (e.g., MongoDB or MySQL). The Microsoft Azure Emotion API can be used as an emotion engine. Kafka or RabbitMQ can be used as a real-time data streaming technology to monitor the progress of tasks.

[1873] Specific examples

[1874] Housework support

[1875] When a user issues a voice command such as "Please clean the living room," the device captures the voice and converts it into text data using a speech recognition API. The converted data is sent to a server, which analyzes the command and assigns a cleaning task to a cleaning robot (e.g., an iRobot Roomba). The cleaning progress is monitored in real time, and the user is notified when the cleaning is complete.

[1876] Going out assistance

[1877] When a user verbally commands "get ready to go out," the device captures the voice and converts it into text data using a speech recognition API. The converted data is sent to a server, which then uses an external API (e.g., OpenWeatherMap or Google Maps API) to obtain weather and traffic information for the destination. The device then prepares items needed for going out (e.g., keys, cell phone, medicine, etc.) based on the obtained information and notifies the user when they are ready.

[1878] Emergency response

[1879] When the device's built-in sensor detects an abnormality, such as a fall, the device switches to emergency mode. An emergency notification is sent to the server, which then automatically notifies emergency contacts using a business API (e.g., Twilio API). In the event of an emergency, the user's current location and status are provided in real time.

[1880] Introducing the Emotion Engine

[1881] If a user says, "I'm a little tired," the device will analyze their voice tone and facial expressions with its emotion engine to recognize their emotion. If it determines that the user is feeling stressed, the device will play relaxing music or provide appropriate support.

[1882] Prompt Sentence Examples

[1883] "User automation assistance system"

[1884] input:

[1885] User voice commands (e.g., "Please clean the living room")

[1886] The user's emotional state (e.g., "I feel a little tired")

[1887] Output:

[1888] Interprets voice commands and performs specific tasks

[1889] Analyze emotions with an emotion engine and provide optimal responses

[1890] As described above, this system can provide multifunctional and flexible support to help users live independently.

[1891] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1892] Step 1: User voice input

[1893] The user issues commands by voice. For example, the user might say to the device, "Please clean the living room."

[1894] Input: User's voice data

[1895] Output: Audio data is captured

[1896] What happens: The device's microphone captures audio data, which is temporarily stored on the device.

[1897] Step 2: Analyzing the audio data

[1898] The device converts the captured voice data into text data using a voice recognition API.

[1899] Input: Captured audio data

[1900] Output: Converted text data

[1901] How it works: The device calls the Google Cloud Speech-to-Text API to convert the voice data into text, which is then immediately sent to the server.

[1902] Step 3: Learning behavioral patterns and updating the database

[1903] The server analyzes the received text data and updates a database for learning user behavior patterns.

[1904] Input: Converted text data

[1905] Output: Updated database

[1906] Specific operation: The server uses TensorFlow to analyze the received text data, learn behavioral patterns, store the results in MongoDB, and update the database.

[1907] Step 4: Task execution instructions

[1908] The server sends instructions to the terminal to execute a task based on the analysis results.

[1909] Input: Analysis results

[1910] Output: Instructions to the terminal

[1911] Specific operation: The server uses the REST API to send specific execution instructions (e.g., "Send the cleaning robot to the living room") to the device.

[1912] Step 5: Monitoring and feedback on the execution of tasks

[1913] The server monitors the progress of the execution tasks received from the terminal and provides the information as feedback to the user in real time.

[1914] Input: Progress data of the execution task

[1915] Output: Feedback to the user

[1916] Specific operation: The device sends progress data from the cleaning robot to the server, which receives it and notifies the user that "cleaning is complete."

[1917] Step 6: Emergency response

[1918] If the device's sensor detects an abnormality, it switches to emergency mode and sends an emergency notification to the server.

[1919] Input: Anomaly detection data from sensors

[1920] Output: Send emergency notification

[1921] How it works: If a device's sensor detects, for example, a fall, it sends that data to a server via AWS IoT, which then uses the Twilio API to send an emergency notification to emergency contacts.

[1922] Step 7: Sentiment analysis and response

[1923] The device analyzes the user's voice and facial expression data using an emotion engine and responds appropriately based on the results.

[1924] Input: Voice data and facial expression data

[1925] Output: Sentiment analysis results and corresponding actions

[1926] How it works: The device uses the Microsoft Azure Emotion API to analyze voice tone and facial expressions to determine the user's emotional state. For example, if the user says, "I'm a little tired," the device will play relaxing music.

[1927] As described above, specific operations are performed at each step, and ultimately a system that comprehensively supports the user's life is realized.

[1928] (Application example 2)

[1929] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1930] Supporting the elderly and busy families is an important issue in modern society. However, existing support systems do not fully consider users' emotions and lifestyles, and lack comprehensive support for household chores, preparations for going out, and emergency response. Furthermore, their ability to analyze and respond to emotional states such as stress and fatigue is limited. Therefore, there is a need for systems that can support users' overall lifestyles and enable them to live their daily lives with peace of mind.

[1931] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1932] In this invention, the server includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores within the home, a means for assisting with going out, a means for responding to emergencies, an emotion engine means for recognizing a user's emotions and suggesting appropriate actions, a means for controlling a household robot to perform cleaning tasks based on voice input, a means for providing information to support going out based on voice input, and a means for analyzing the user's emotions based on voice input and responding appropriately. This enables the server to support the user's overall lifestyle, seamlessly supporting housework, going out, and responding to emergencies. Furthermore, analyzing the user's emotional state and responding appropriately can provide a more comfortable and secure daily life.

[1933] "Voice input means" refers to a device or system for recognizing a user's voice and processing it as data.

[1934] "Image input means" refers to a device or system for capturing still images and processing them as data.

[1935] "Video input means" refers to a device or system for capturing video and processing it as data.

[1936] "General artificial intelligence means" is a system that uses artificial intelligence technology that can handle a variety of tasks, and is used to analyze user behavior and lifestyle habits.

[1937] The "means for learning lifestyle habits" is a system that collects and analyzes the user's daily behavioral patterns and habits as data, and provides optimal support based on that data.

[1938] A "means for automating household chores" is a device or system for automatically performing household chores such as cleaning and laundry.

[1939] "Means for assisting users in going out" refers to a system that provides weather and traffic information and supports users in going out.

[1940] "Means for responding to emergencies" refers to a system that detects abnormalities or emergencies in users and responds quickly.

[1941] The "emotion engine means" is a system that analyzes the user's emotions from their voice and facial expressions and suggests appropriate actions.

[1942] The "means for controlling a household robot" is a mechanism for operating a household robot based on voice input to perform a specific task.

[1943] The "means for providing outing support information" is a system for providing outing support information such as weather and traffic based on voice input.

[1944] The "means for analyzing emotions and responding" is a system that analyzes emotions from the user's voice and suggests relaxation methods based on that.

[1945] System Overview

[1946] The system according to the present invention includes a voice input means, an image input means, a video input means, a general artificial intelligence means, a means for learning lifestyle habits, a means for automating household chores at home, a means for assisting with going out, a means for responding to emergencies, an emotion engine means, a means for controlling a household robot, a means for providing information to support going out, and a means for analyzing emotions and responding accordingly. This enables the system to support the user's life in general, seamlessly supporting housework, going out, and responding to emergencies.

[1947] Hardware and Software Configuration

[1948] The system uses the following hardware and software:

[1949] Smartphone: Equipped with a built-in microphone for voice recognition and a camera for capturing images and videos.

[1950] Domestic robots: Robots designed to automatically perform cleaning and other household chores.

[1951] General artificial intelligence software: Software that analyzes a user's behavior and lifestyle habits and provides optimal actions.

[1952] Emotion analysis engine: Software that analyzes the user's voice and facial expressions to recognize and respond to emotions.

[1953] Emergency notification system: A notification system for rapid response in emergencies.

[1954] Example of a system

[1955] Automating Housework

[1956] When a user issues a voice command such as "Please clean the living room," the smartphone's voice input means recognizes this and sends the instruction to the home robot. When the cleaning is complete, the system notifies the user by voice or through an application. If the emotion engine detects that the user is tired, it will gently notify the user, saying, "The living room has been cleaned. Please take a short rest."

[1957] Assistance with going out

[1958] When a user instructs the system to "get ready to go out," the system retrieves weather and traffic information and prepares a list of items needed for going out. For example, if the weather forecast predicts rain, the system will notify the user, "Don't forget to take an umbrella." If the emotion engine detects the user's stress, the system will suggest deep breathing or play relaxing music.

[1959] Emergency response

[1960] The system constantly monitors sensors to respond to emergencies. For example, if the user falls, the system will ask aloud, "Are you OK?" If there is no response or if the user responds with "Help me," it will automatically notify pre-defined emergency contacts. At this time, the user's current location and status will also be provided in real time.

[1961] Emotional engine response

[1962] The system uses an emotion engine to analyze the user's emotions from their voice and facial expressions. For example, if a user says, "I'm a little tired," the device will analyze their voice tone and facial expressions to recognize that emotion. If the emotion engine detects stress or anxiety in the user, it will play relaxing music or provide the necessary support.

[1963] Specific examples

[1964] Prompt: "Please clean the living room. I'm tired, so please play some relaxing music."

[1965] Prompt: "Get ready to go out. Check the weather and tell me what you need."

[1966] This system allows users to receive support in all aspects of their daily lives, allowing them to live with peace of mind. It also improves the quality of life of users by providing appropriate responses through emotion analysis.

[1967] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1968] Step 1:

[1969] The user issues a voice command. The smartphone's microphone captures the voice input and prepares it for processing as audio data.

[1970] Input: User's voice

[1971] Output: Audio data

[1972] Step 2:

[1973] The device converts the voice data into text using speech recognition software (speech_recognition library).

[1974] Input: Audio data

[1975] Output: Recognized text

[1976] Step 3:

[1977] The device analyzes the recognized text and determines the content of the instruction. For example, if the keyword "cleaning" is included, it will be recognized as an instruction to control a household robot.

[1978] Input: Text data

[1979] Output: Command content

[1980] Step 4:

[1981] Based on the analysis results, the device sends the corresponding task (e.g., cleaning the living room) to the home robot, which then carries out the cleaning task according to the received instructions.

[1982] Input: Command content

[1983] Output: Instructions to execute the cleaning task

[1984] Step 5:

[1985] The home robot monitors the progress of the cleaning task and sends the status upon completion to the terminal, which receives the information and notifies the user.

[1986] Input: Cleaning task progress

[1987] Output: Completion notification

[1988] Step 6:

[1989] The device uses an emotion engine to analyze the user's voice tone and facial expressions. For example, if the device detects that the user is tired, it will suggest playing relaxing music.

[1990] Input: Speech and facial expression data

[1991] Output: Emotion analysis results

[1992] Step 7:

[1993] Based on the analysis results, the device will suggest and execute appropriate actions (e.g., playing relaxing music).

[1994] Input: Sentiment analysis results

[1995] Output: Suggestions and action taken

[1996] Step 8:

[1997] The user can then issue an additional voice command, which the device will then recognize, interpret, and execute again. For example, based on a command such as "Get ready to go out," the device will retrieve weather and traffic information and provide it to the user.

[1998] Input: New voice command

[1999] Output:Outing support information

[2000] Through this series of steps, the system can comprehensively support the user's daily life and provide a comfortable living environment.

[2001] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2002] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2003] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2004] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2005] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2006] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2007] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2008] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2009] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2010] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2011] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2012] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2013] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2014] 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.

[2015] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2016] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2017] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2018] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2019] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2020] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2021] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2022] The following is further disclosed regarding the above embodiment.

[2023] (Claim 1)

[2024] A voice input means;

[2025] Image input means;

[2026] A video input means;

[2027]

[0023] an artificial general intelligence means;

[2028] A means of learning lifestyle habits,

[2029] A means of automating household chores within the home;

[2030] Assistance for going out,

[2031] A system that includes emergency response measures.

[2032] (Claim 2)

[2033] 10. The system of claim 1, further comprising means for automatically performing cleaning tasks within a household.

[2034] (Claim 3)

[2035] 10. The system of claim 1, further comprising means for recognizing a user's voice instructions and automatically performing a task based on the instructions.

[2036] (Claim 4)

[2037] a sensor means for detecting the user's situation in an emergency;

[2038] 10. The system of claim 1, further comprising means for notifying an emergency contact in response to the detection result.

[2039] (Claim 5)

[2040] 2. The system according to claim 1, further comprising means for recording a user's lifestyle habits and providing optimal support based on those patterns.

[2041] (Claim 6)

[2042] 2. The system according to claim 1, further comprising means for accurately determining the needs of the user using information acquired by the audio, image, and video input means.

[2043] (Claim 7)

[2044] A means for preparing equipment to assist the user in going out;

[2045] 2. The system according to claim 1, further comprising means for obtaining weather and traffic information for a location outside the home and providing the information to the user.

[2046] "Example 1"

[2047] (Claim 1)

[2048] A voice input means;

[2049] Image input means;

[2050] A video input means;

[2051]

[0023] an artificial general intelligence means;

[2052] A means of learning lifestyle habits,

[2053] A means of automating household chores within the home;

[2054] Assistance for going out,

[2055] How to respond in an emergency; and

[2056] A means of analyzing and managing data at each processing step,

[2057] means for communicating with a cloud server;

[2058] a means for notifying a user;

[2059] a means for automatically executing the task;

[2060] A system including:

[2061] (Claim 2)

[2062] 10. The system of claim 1, further comprising means for automatically performing cleaning tasks within a household.

[2063] (Claim 3)

[2064] 10. The system of claim 1, further comprising means for recognizing a user's voice instructions and automatically performing a task based on the instructions.

[2065] "Application Example 1"

[2066] (Claim 1)

[2067] A voice input means;

[2068] Image input means;

[2069] A video input means;

[2070]

[0023] an artificial general intelligence means;

[2071] A means of learning lifestyle habits,

[2072] A means of automating household chores within the home;

[2073] Assistance for going out,

[2074] How to respond in an emergency; and

[2075] a means of learning order history;

[2076] A means of recognizing ingredients;

[2077] a means of tracking delivery progress;

[2078] A system that includes measures to support healthy eating habits.

[2079] (Claim 2)

[2080] A means of automatically performing cleaning tasks within the home;

[2081] 10. The system of claim 1, further comprising means for advising of shortage of ingredients.

[2082] (Claim 3)

[2083] means for recognizing a user's voice instructions and automatically performing a task based on the instructions;

[2084] 10. The system of claim 1, further comprising means for suggesting an optimal menu based on user preferences.

[2085] "Example 2: Combining Emotion Engines"

[2086] (Claim 1)

[2087] A voice input means;

[2088] Image input means;

[2089] A video input means;

[2090]

[0023] an artificial general intelligence means;

[2091] A means of learning lifestyle habits,

[2092] A means of automating household chores within the home;

[2093] Assistance for going out,

[2094] How to respond in an emergency; and

[2095] means for recognizing a user's emotion;

[2096] a means of monitoring and providing feedback on the progress of the execution task;

[2097] A means of parsing user instructions and performing tasks

[2098] A system including:

[2099] (Claim 2)

[2100] 10. The system of claim 1, further comprising means for automatically performing cleaning tasks within a household.

[2101] (Claim 3)

[2102] 10. The system of claim 1, further comprising means for recognizing a user's voice instructions and automatically performing a task based on the instructions.

[2103] "Application example 2 when combining emotion engines"

[2104] (Claim 1)

[2105] A voice input means;

[2106] Image input means;

[2107] A video input means;

[2108]

[0023] an artificial general intelligence means;

[2109] A means of learning lifestyle habits,

[2110] A means of automating household chores within the home;

[2111] Assistance for going out,

[2112] How to respond in an emergency; and

[2113] an emotion engine means for recognizing a user's emotion and suggesting an appropriate action;

[2114] a means for controlling a household robot to perform cleaning tasks through voice input;

[2115] A means for providing outing support information through voice input;

[2116] A system that includes a means for analyzing a user's emotions from their voice and taking appropriate action.

[2117] (Claim 2)

[2118] 10. The system of claim 1, further comprising means for automatically performing cleaning tasks within the home based on voice commands.

[2119] (Claim 3)

[2120] 10. The system according to claim 1, further comprising means for recognizing a user's voice instruction, providing outing support information based on the instruction, and analyzing emotions from the voice input to make relaxation suggestions. [Explanation of symbols]

[2121] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A voice input means; Image input means; A video input means; [0023] an artificial general intelligence means; A means of learning lifestyle habits, A means of automating household chores within the home; Assistance for going out, A system that includes emergency response measures.

2. 10. The system of claim 1, further comprising means for automatically performing cleaning tasks within a home.

3. 10. The system of claim 1, further comprising means for recognizing a user's voice instructions and automatically performing a task based on the instructions.

4. a sensor means for detecting the user's situation in an emergency; The system according to claim 1, further comprising means for notifying an emergency contact in response to the detection result.

5. 2. The system according to claim 1, further comprising means for recording the user's lifestyle habits and providing optimal support based on the patterns.

6. 2. The system according to claim 1, further comprising means for accurately determining the needs of the user using information acquired by the audio, image and video input means.

7. A means for preparing equipment to assist the user in going out; 2. The system according to claim 1, further comprising means for obtaining weather and traffic information for a location outside the home and providing the information to the user.

Images