system

Abstract

We provide the system. [Solution] A means of receiving schedule information, A means of analyzing received schedule information and setting priorities, A means of storing schedule information in a database and detecting duplicates and conflicts, A means for generating reminders and suggestions based on schedule information, A means of notifying the device of reminders and suggestions, A means of collecting health information and generating suggestions regarding health management, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The management of the schedules, tasks, shopping lists, and important family events of all family members has become complicated, and there are problems such as overlapping or missing personal schedules. In addition, many families feel anxious about the health management of the elderly who do not yet require care, and there is a need to provide appropriate health maintenance methods. These problems make it difficult to smooth the adjustments and communications within the family and lead to a decline in the quality of life.

Means for Solving the Problems

[0005] This invention provides a means for receiving and analyzing schedule information, and has functions for automatically setting priorities and detecting overlaps and conflicts. It also has a function to generate reminders and individual suggestions based on the schedule and notify the terminal. Furthermore, it reduces the burden of care by collecting health information and generating suggestions according to the health status. It also has a function to learn the user's preferences and tendencies and optimize suggestions. In this way, it provides a system that streamlines schedule management for the entire family and improves the quality of life.

[0006] "Schedule information" refers to data entered or automatically collected by users to show details of their personal or family appointments, tasks, and events.

[0007] "Analysis" refers to the process of understanding received schedule information and extracting and processing elements such as time, date, and importance.

[0008] "Priority" refers to the criteria used to rearrange or emphasize tasks and events within a schedule based on their importance and urgency.

[0009] A "database" refers to a storage system that systematically stores schedule information and related data, making it available for retrieval and use as needed.

[0010] A "reminder" refers to a message that notifies a user about a specific event or task based on a set time or condition, and serves to draw their attention to it.

[0011] "Suggestions" refer to schedules and improvement advice automatically generated by the system based on the user's past behavior and trends.

[0012] A "terminal" refers to a device that a user uses to access a system and receive input and notifications.

[0013] "Health information" refers to data about the user's or their family's health status, as well as health-related data collected by the system.

[0014] A "learning algorithm" refers to a computational method for recognizing patterns from past data and making future suggestions or decisions. [Brief explanation of the drawing]

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

Modes for Carrying Out the Invention

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

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

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

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

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

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

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

[0023] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0036] As an embodiment of this invention, an AI agent system that centrally manages the schedules and tasks of all family members is described. The system operates through the interaction of a server, terminals, and users, smoothly realizing each of its functions.

[0037] The server plays a central role in the system, receiving and storing schedule information sent from users and terminals. The server analyzes this information and sets priorities to achieve efficient schedule management. Specifically, it compares entered schedules with other tasks to detect duplicates and conflicts. If a conflict occurs, it generates an alert and notifies the user.

[0038] The terminal is a device that allows users to input schedule information and receive reminders and suggestions. Users can input schedule information via voice or text, and the terminal sends this information to the server. Upon receiving reminders and suggestions from the server, the terminal displays them to the user as push notifications. This feature ensures that users do not miss important tasks or events.

[0039] Furthermore, the server also provides functionality in terms of health management. It collects health information entered by users through their devices and generates health management suggestions based on this information. For the elderly, it provides reminders for regular health checks and suggestions for appropriate exercise, thereby helping to prevent the burden of caregiving.

[0040] For example, if a user wants to add a remote meeting to the following Tuesday, they would input the information into their device via voice, and that information would be sent to the server. The server would check for conflicts with other appointments and generate a reminder based on the importance of the meeting. The day before, the device would receive a notification saying, "Prepare for tomorrow's remote meeting." In addition, a suggestion for health management, such as "Let's do 15 minutes of stretching today," would also be sent.

[0041] In this way, the invention efficiently manages the schedules and provides health suggestions for the entire family, improving the quality of life at home.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user enters schedule information using voice or text via the device. The device receives the entered information, converts it to text if it was entered via voice, and temporarily stores it locally.

[0045] Step 2:

[0046] The terminal sends the entered schedule information to the server. Here, the data is securely transferred over the network.

[0047] Step 3:

[0048] The server analyzes the received schedule information. Using natural language processing, it extracts elements such as date, time, location, and content.

[0049] Step 4:

[0050] The server saves the analyzed schedule information to a database and checks for duplication and conflicts with existing tasks and events.

[0051] Step 5:

[0052] The server prioritizes schedule information. It evaluates tasks based on importance and urgency and determines the reminder schedule.

[0053] Step 6:

[0054] The server generates a reminder and sends it to the user's device at the specified time. The notification is delivered via push at a specific time, informing the user visually or audibly.

[0055] Step 7:

[0056] The server learns the user's past behavioral patterns and generates optimized suggestions based on that. Suggestions for health management and shopping lists are also made in this step.

[0057] Step 8:

[0058] The device receives reminders and suggestions from the server and displays them to the user. The user reviews them and adjusts their schedule as needed.

[0059] Step 9:

[0060] Users input their daily physical condition and health information through their device. This data is sent to a server and used for health management functions.

[0061] Step 10:

[0062] The server analyzes the user's health status based on the collected health information and provides appropriate health maintenance suggestions. If necessary, it sets reminders for the next health check.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] In modern households, it is difficult to centrally manage the individual schedules and health information of each member. Furthermore, there is a need for features that can adapt to rapidly changing schedules and appropriately resolve conflicts and overlaps. Additionally, there is a need for methods to suggest appropriate health management practices to users and improve their quality of daily life.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and setting priorities, and means for storing the schedule information in a storage device and detecting overlaps and conflicts. This makes it possible to comprehensively manage the schedules of each member of the household and efficiently resolve overlaps and conflicts. Furthermore, by collecting health indicators and generating appropriate health management suggestions, it is possible to improve the quality of life.

[0068] "Schedule information" refers to data about appointments and tasks specified by each user, including information such as date and time, content, location, and participants.

[0069] "Means of receiving" refers to the complete set of hardware and software necessary to acquire information from the outside via a network.

[0070] "Means of analysis" refers to a process or device for analyzing received data using a specific algorithm and scrutinizing its contents.

[0071] A "means for setting priorities" is a mechanism for determining the importance and urgency of tasks based on analyzed schedule information, and then deciding the order in which they will be processed.

[0072] A "storage device" is a device or system for storing information long-term, and includes databases, etc.

[0073] "Means for detecting overlaps and conflicts" refers to a process or apparatus for comparing schedule information to find out if any identical or conflicting appointments exist.

[0074] A "reminder" is an alert function that notifies users in advance of appointments they tend to forget.

[0075] A "means for generating suggestions" refers to a system that analyzes data to derive optimal conclusions in order to provide users with suggestions for optimizing their schedules and managing their health.

[0076] A "terminal" is an electronic device used by a user to input or receive information, and includes smartphones, tablets, and other similar devices.

[0077] "Health indicators" are data used to evaluate a user's health status, and include things like body temperature and blood pressure.

[0078] "Health management suggestions" refer to advice and information provided to help users maintain better health, taking their current health status into consideration.

[0079] A "generative AI model" is an algorithm trained using machine learning to generate the optimal output for a specific task.

[0080] This invention is a system that integrates scheduling and health management for all family members, with the server, terminals, and users working together in a coordinated manner.

[0081] server

[0082] The server plays a central role in the system, receiving, analyzing, and storing schedule information. The received schedule information is processed by software using programming languages ​​such as Python. This allows for the detection of schedule overlaps and conflicts in the database, and the setting of priorities based on the analysis results. Furthermore, it can utilize a generative AI model to generate optimal reminders and health management suggestions for the user.

[0083] terminal

[0084] The terminal is a user device such as a smartphone or tablet, which accepts schedule information input from the user. This includes voice input or text input, and this data is sent to the server. Reminders and suggestions from the server are also displayed on the terminal as push notifications, and the user can receive and check this information in real time through the terminal.

[0085] User

[0086] As a system user, the user inputs schedule information and health indicators into a terminal. This allows the server to process information related to the user's lifestyle, enabling efficient schedule management and health suggestions. For example, if a user voice-inputs, "I want to set up a remote meeting next Tuesday," that information is transmitted to the server via the terminal and processed accordingly.

[0087] For example, if a user enters a prompt into their device such as, "We have a family dinner tonight. Please check for conflicts with other schedules," this information is analyzed by the server and a reminder is generated. In this way, each user can be helped to avoid missing important events and improve their quality of life at home.

[0088] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0089] Step 1:

[0090] The user enters schedule information into the terminal via voice or text. User input is performed through the terminal's microphone or keyboard. The input data includes specific appointments, such as "Remote meeting next Tuesday at 3pm." Based on this, the terminal generates schedule information in digital format and prepares it for transmission to the server.

[0091] Step 2:

[0092] The terminal sends the schedule information received from the user to the server. The data is transmitted using a secure protocol. The input data is the user's schedule information, and the output data is in a format suitable for transmission to the server. The terminal confirms that this process has completed successfully and waits for the data to arrive at the server.

[0093] Step 3:

[0094] When the server receives schedule information, the analysis software processes the data. The input data is schedule information sent from the terminal. The server analyzes the data using a generative AI model and sets priorities. The output is a schedule that has been checked for conflicts and overlaps. Specific operations include checking the time slots of the schedule and verifying that they do not overlap with other appointments.

[0095] Step 4:

[0096] The server generates necessary alerts and reminders based on the analysis results. A generative AI model is involved in this process to produce the most appropriate messages. The output includes reminders and suggestions to be sent to the user. For example, it might perform a specific action such as "send a preparation notification the day before a remote meeting."

[0097] Step 5:

[0098] The device displays reminders and suggestions received from the server to the user. The input data includes notification information sent from the server. The device displays this information as push notifications and on-screen alerts. This allows the user to efficiently manage their schedule. Specific actions include controlling notification sounds and banner displays on the device.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] In modern society, managing the schedules and health of elderly individuals places a significant burden on caregivers. To alleviate this burden and provide more efficient and personalized support, a flexible and accurate information management system is necessary. Conventional systems have not fully utilized voice input or compatibility with diverse devices, and have been inadequate in addressing the unique needs of the elderly.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and setting priorities, and means for storing the schedule information in a data storage device and detecting duplicates and conflicts. This makes it possible to identify and manage the schedules and health information of elderly people. By also providing means for registering information on a terminal using voice input and cross-platform compatible communication means, smooth communication between caregivers and those receiving care and personalized health management support can be realized.

[0104] "Schedule information" refers to data representing the user's schedule, including the time and place of planned activities and appointments.

[0105] "Priority" is a criterion used to rank multiple schedules and tasks based on their importance and urgency.

[0106] A "data storage device" is a device for electronically storing information, and includes databases and cloud storage.

[0107] "Duplicate" refers to a situation where multiple schedule entries exist that require the same time or resources.

[0108] "Conflict" refers to a situation where different schedule information interferes with each other, and it is necessary to determine priorities.

[0109] "Recommendations" refer to suggested actions or task options presented to the user based on the analysis results.

[0110] A "terminal" refers to a device used by a user to directly input information or receive notifications from a system.

[0111] "Health information" refers to data that indicates the user's physical condition, including biometric information such as body temperature, blood pressure, and exercise level.

[0112] "Health maintenance and management" is a general term for management activities aimed at keeping users in good health.

[0113] "Elderly people" refers to individuals above a certain age, and usually includes those aged 60 and over.

[0114] "Voice input" is an interface technology that allows users to provide information to a device using their voice.

[0115] "Cross-platform" means that the same application or functionality can be run on different platforms.

[0116] "Communication means" refers to functions and technologies that enable the transmission and reception of information, and includes wired and wireless technologies.

[0117] For this invention to be implemented, the interaction between the server, terminal, and user is crucial. The server utilizes cloud infrastructure to receive and analyze schedule information. The server is built using Amazon Web Services (AWS®), and Amazon S3 is used for data storage. In addition, Google® Cloud Speech-to-Text API is utilized to implement voice input functionality. A cross-platform application using React Native is developed to support ubiquitous devices.

[0118] The device receives voice and text input from the user and sends it to the server in real time. Real-time data synchronization is performed via Firebase, so schedule entries made by the user are immediately reflected on the server. In addition, schedule reminders and health management suggestions are displayed to the user as push notifications. Firebase Cloud Messaging is used for this purpose.

[0119] Users input their daily activities into their device via voice or text, and their schedules and health-related data are updated accordingly. For example, if a user voice-instructs, "I will take my medicine at 10 AM tomorrow," that information is sent to the server, which checks for conflicts and generates reminders as needed. Furthermore, for seniors, the system can provide appropriate exercise suggestions to support their daily health management. For instance, a push notification might say, "Based on your recent activity log, we suggest a 20-minute walk today."

[0120] As a concrete example, a possible prompt for a generative AI model would be, "Please provide schedule management and health suggestions for tomorrow." Based on this prompt, the AI ​​agent would provide a schedule and health suggestions optimized for the user.

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

[0122] Step 1:

[0123] The user inputs schedule information into the device via voice. The device uses the Google Cloud Speech-to-Text API to convert the voice data into text data. The input voice is something like "Take my medicine at 10 AM tomorrow," and the output is generated in text format.

[0124] Step 2:

[0125] The device sends the converted text data to the server in real time via Firebase. The input contains text data, which the server receives and stores in a database as schedule information. The output is the stored schedule information.

[0126] Step 3:

[0127] The server stores the received schedule information in Amazon S3 and simultaneously analyzes that information. The analysis checks for any overlaps with existing schedules and sets priorities. The input is schedule information, and the output provides information on whether there are any conflicts and their priorities.

[0128] Step 4:

[0129] The server generates a reminder based on the analysis results. If there are no conflicts, the generated reminder will be a notification such as "Don't forget to take your medicine at 10 AM tomorrow." The input includes the analysis results, and the output is the generated reminder information.

[0130] Step 5:

[0131] The server uses Firebase Cloud Messaging to push reminders generated to the device. By receiving reminder information as input and sending it to the user's device, the user can receive notifications in real time. The output includes push notifications.

[0132] Step 6:

[0133] The user checks the reminder notification displayed on their device and makes any necessary changes to the schedule or adds health information. This allows for re-entry of the information, which is then sent back to the server from step 1, and processing continues.

[0134] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0135] To implement this invention, a system combining an AI agent with an emotion engine is used. This system provides a comprehensive home management solution that integrates emotion detection and response, in addition to scheduling and health management for all family members. The server, terminals, and users work together to effectively realize the system's functions.

[0136] First, users input their daily schedule information through their device, but this is then combined with an emotion-based element. For example, a user might say in voice, "I'm not really looking forward to tomorrow's meeting, but I'll have to attend." This voice data is analyzed by an emotion engine, which determines that the user may be feeling anxious about the meeting.

[0137] The server analyzes the received schedule information and sentiment data. Meeting priorities are assigned based on the already set schedule, but the content of suggestions and reminders is adjusted as needed, taking into account the sentiment engine's corrections. For example, a reminder might be sent just before a meeting saying, "Take a deep breath before the meeting to help you feel relaxed."

[0138] The device receives reminders and suggestions from the server and notifies the user. The user can use these notifications to adjust their schedule and prepare themselves mentally. Emotional data is also used to improve communication within the family. For example, if a family member is feeling stressed, a supportive message tailored to that situation will automatically appear on the device.

[0139] Thus, this invention provides a system that improves the quality of life for families by utilizing an emotion engine to not only manage schedules but also to provide support that is tailored to each individual's emotional state. This emotion-responsive function enables detailed support that is suited to each individual's situation and contributes to the overall improvement of the home environment.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] The user inputs schedule information using voice or text via a device. The device receives the input information, converts the voice data into text, and prepares it for analysis by an emotion engine.

[0143] Step 2:

[0144] The device sends emotional information extracted from voice and text to the server. At this time, schedule information and emotional data are sent together.

[0145] Step 3:

[0146] The server analyzes the received schedule information and uses natural language processing techniques to extract details such as the date, time, and event name. The emotion engine also analyzes the emotion data and evaluates the user's emotional state.

[0147] Step 4:

[0148] The server stores schedule information in a database and sets schedule priorities. It also takes emotional states into consideration and adjusts priorities as needed.

[0149] Step 5:

[0150] The server generates optimal reminders and suggestions based on schedule information and sentiment analysis. It creates appropriate support messages tailored to the user's emotions and incorporates them into the reminders.

[0151] Step 6:

[0152] Reminders and suggestions generated by the server are sent to the device. The device receives them and provides them to the user as visual or auditory notifications.

[0153] Step 7:

[0154] Users can review received reminders and emotionally-driven suggestions and take action based on them. They can also adjust their schedules if necessary.

[0155] Step 8:

[0156] To support communication among family members, an emotion-based messaging function is utilized on the device. Messages are automatically generated and displayed on the device according to the family's stress levels and emotional state.

[0157] Through these steps, a system is created that integrates and manages emotions and schedules, providing appropriate support.

[0158] (Example 2)

[0159] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0160] In today's family environment, managing each member's schedule and health has become a crucial issue. Furthermore, it is necessary to appropriately understand emotional fluctuations and mental states, and to promote smooth communication among family members. However, managing and supporting these aspects individually is burdensome and inefficient. Therefore, there is a need for a system that provides emotionally-based support in addition to schedule and health management, thereby improving the quality of life for families.

[0161] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0162] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and emotional data, setting priorities and adjusting them, and means for detecting the emotional state of family members and generating messages to facilitate communication among family members. This makes it possible to improve the overall quality of life for the family by effectively managing the family's schedule and health and providing emotional support.

[0163] "Schedule information" refers to time-based information such as appointments, tasks, and events related to an individual or group.

[0164] "Emotional analysis" is the process of analyzing voice and text data to determine the user's emotional state.

[0165] A "reminder" is an alert or notification that alerts users to appointments or tasks that are easily forgotten.

[0166] A "suggestion" is a recommendation of actions or advice provided based on the user's schedule and status.

[0167] A "database" is an information storage system that allows for the systematic management and access of digital data as needed.

[0168] "Health information" refers to data that indicates an individual's health status, including, for example, heart rate, sleep duration, and stress level.

[0169] A "message" is a written or electronic means of communication used to transmit information.

[0170] A "learning algorithm" is a computational method that finds patterns and rules from past data and applies them to new data to make predictions and classifications.

[0171] This invention provides a system that integrates household schedule management, health management, and emotional support. The components necessary to implement this include a server, terminals, an emotion engine, and a database. Specific examples using these elements are described below.

[0172] The server operates on a cloud-based platform. The server receives schedule information sent from users via their devices. These devices are smartphones and tablets, and they use voice input to send information about the user's daily schedule and emotions to the server.

[0173] The server uses existing natural language processing APIs as its sentiment engine to analyze this audio data. For example, Google Cloud's Natural Language API is used. This API analyzes audio and text data and generates sentiment scores and categories.

[0174] The analyzed emotional data is integrated with schedule information by the server. Based on this, the server prioritizes daily appointments and generates reminders and suggestions as needed. The server also uses the emotional data to send appropriate messages to facilitate communication among family members.

[0175] For example, if a user voice-inputs, "I'm not really looking forward to tomorrow's meeting, but I'll attend," the system's emotion engine will analyze that the user is anxious about the meeting and generate a suggestion such as, "Try taking a deep breath before the meeting so you can approach it feeling more relaxed."

[0176] An example of a prompt for a generative AI model might be, "Please provide ideas for using the emotion engine to detect the user's emotional state and suggest specific actions." This prompt is used by the generative AI model when developing new features.

[0177] Through these means, the system of the present invention can improve the quality of life for families and provide detailed support tailored to individual schedules and emotional states.

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] The user uses their device to perform voice input. This input includes schedule information and the user's emotions. Specifically, the user uses their smartphone's voice input function to say, "I'm not really looking forward to it, but I'll attend the meeting tomorrow." This voice data is recorded on the device.

[0181] Step 2:

[0182] The terminal converts recorded audio data into text and sends it to the server. The input is audio data, and the output is text data. The terminal uses speech recognition technology to perform this conversion, and the result is sent to the server via the network.

[0183] Step 3:

[0184] The server passes the received text data to the sentiment engine, which then performs sentiment analysis. The input is text data, and the output is sentiment scores or categories. The server calls a natural language processing API to obtain numerical data representing the emotional state.

[0185] Step 4:

[0186] The server integrates the sentiment analysis results into the schedule information and resets priorities. The input is existing schedule data and sentiment data, and the output is a priority-adjusted schedule. The server accesses the database and updates the task rankings, taking priorities into account.

[0187] Step 5:

[0188] The server generates reminders and suggestions based on emotional data. The input is a prioritized schedule, and the output is a message containing a specific action. For example, a suggestion might be generated: "Take a deep breath before the meeting to help you feel relaxed."

[0189] Step 6:

[0190] The server sends generated reminders and suggestions to the terminal. The input is message data, and the output is a notification to the terminal. The server dispatches the notification to the terminal via a communication method.

[0191] Step 7:

[0192] The terminal displays notifications received from the server to the user. Input is received data, and output is a visual or auditory notification to the user. The terminal displays messages on the screen and provides alerts to the user through sound or vibration.

[0193] (Application Example 2)

[0194] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0195] In modern households, managing family schedules and health has become increasingly complex, and there is a need for lifestyle support that is tailored to each individual's mental state. However, conventional technologies have made it difficult to address these issues comprehensively. Furthermore, there is a lack of means to facilitate communication among family members and improve their quality of life.

[0196] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0197] In this invention, the server includes means for receiving schedule information, means for analyzing emotions from voice data and generating suggestions according to the user's emotional state, and means for providing emotion-based feedback and suggestions via an operating device. This makes it possible to manage the schedules and health of the entire family, provide individual suggestions and support based on emotional states, and facilitate communication among family members.

[0198] "Schedule information" refers to data related to daily appointments and events, and is used for planning and managing individual and group activities.

[0199] "Priority" refers to the ranking of the importance and urgency of performing multiple tasks or appointments.

[0200] A "database" is a system that systematically stores and manages various types of data and information, making it easy to access and manipulate.

[0201] "Overlap or conflict" refers to a situation where multiple appointments or tasks exist that are allocated to the same time or resources.

[0202] A "reminder" is a feature that notifies users based on specific times or conditions to remind them of tasks or appointments.

[0203] "Health information" refers to data about an individual's health status, used to assess their physical and mental condition.

[0204] "Audio data" refers to data that records audio signals, and it forms the basis for the analysis and recognition of acoustic information.

[0205] "Emotional analysis" is the process of evaluating and identifying an individual's emotional state from voice and behavioral data.

[0206] "Operational devices" refer to equipment or devices that control physical movement and provide users with an interactive experience.

[0207] "Feedback" refers to information returned as a response to an action or input, providing an appropriate response depending on the user's actions and state.

[0208] This system analyzes the user's emotional state based on their schedule and health information to improve their quality of life at home, and provides appropriate feedback and suggestions. Specifically, the server, terminal, and user work together to perform the following processes.

[0209] The server receives voice data input from the user and analyzes the user's emotions using speech recognition technology and a generative AI model for sentiment analysis (e.g., Google Cloud's Natural Language API). The analyzed sentiment data is stored in a database along with schedule information and health data. Based on this information, the server generates reminders and suggestions tailored to the user's current state and sends them to the device.

[0210] The device notifies the user of reminders and suggestions received from the server. Notifications are sent via a smartphone or a home device (e.g., a home robot), allowing the user to adjust their schedule and prepare themselves accordingly.

[0211] Based on the suggestions received, users can improve their lifestyle habits and enhance communication within their families. As a concrete example of this system, if an elementary school child comes home from school and says, "I'm too tired to do my homework today," the robot will sense this and suggest, "Why don't you take a 15-minute break before starting your homework?"

[0212] Examples of prompts for the generating AI model include, "Assuming the user is feeling anxious, please give advice on preparing for tomorrow's meeting," and "If a child is complaining of fatigue, please generate advice to encourage relaxation." In this way, the system aims to comprehensively improve the quality of life by addressing the emotional needs of the entire family.

[0213] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0214] Step 1:

[0215] The server receives audio data from the user. This input data contains the user's speech. Speech recognition software is used to convert this data into text. Once the audio-to-text conversion is complete, the data is passed on to sentiment analysis.

[0216] Step 2:

[0217] The server uses a generative AI model to analyze the user's emotions from text data. The input contains converted text data, which the emotion analysis engine processes to obtain an output in the form of an emotional state (e.g., "anxiety" or "fatigue"). This emotional state is the information needed for subsequent processing.

[0218] Step 3:

[0219] The server combines analyzed emotional states with pre-registered schedule information to generate appropriate reminders and suggestions. This input data includes emotional states and schedule information. Based on this, the server determines what kind of support the user needs and generates a corresponding message.

[0220] Step 4:

[0221] The device receives reminders and suggestions sent from the server and notifies the user. The input for this step is the message provided by the server. The notification function is activated on the device, and as a concrete action, the user receives a visual or audible notification.

[0222] Step 5:

[0223] Users review notifications and suggestions received through their devices to help adjust their lives and improve their emotions. The output in this step represents the results of users actually adjusting their behavior based on the suggestions. This is a specific step in which users receive notifications from their devices and decide how to change their behavior.

[0224] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0225] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0226] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0230] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0231] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0232] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0233] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0234] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0235] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0236] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0237] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0238] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0239] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0240] As an embodiment of this invention, an AI agent system that centrally manages the schedules and tasks of all family members is described. The system operates through the interaction of a server, terminals, and users, smoothly realizing each of its functions.

[0241] The server plays a central role in the system, receiving and storing schedule information sent from users and terminals. The server analyzes this information and sets priorities to achieve efficient schedule management. Specifically, it compares entered schedules with other tasks to detect duplicates and conflicts. If a conflict occurs, it generates an alert and notifies the user.

[0242] The terminal is a device that allows users to input schedule information and receive reminders and suggestions. Users can input schedule information via voice or text, and the terminal sends this information to the server. Upon receiving reminders and suggestions from the server, the terminal displays them to the user as push notifications. This feature ensures that users do not miss important tasks or events.

[0243] Furthermore, the server also provides functionality in terms of health management. It collects health information entered by users through their devices and generates health management suggestions based on this information. For the elderly, it provides reminders for regular health checks and suggestions for appropriate exercise, thereby helping to prevent the burden of caregiving.

[0244] For example, if a user wants to add a remote meeting to the following Tuesday, they would input the information into their device via voice, and that information would be sent to the server. The server would check for conflicts with other appointments and generate a reminder based on the importance of the meeting. The day before, the device would receive a notification saying, "Prepare for tomorrow's remote meeting." In addition, a suggestion for health management, such as "Let's do 15 minutes of stretching today," would also be sent.

[0245] In this way, the invention efficiently manages the schedules and provides health suggestions for the entire family, improving the quality of life at home.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user enters schedule information using voice or text via the device. The device receives the entered information, converts it to text if it was entered via voice, and temporarily stores it locally.

[0249] Step 2:

[0250] The terminal sends the entered schedule information to the server. Here, the data is securely transferred over the network.

[0251] Step 3:

[0252] The server analyzes the received schedule information. Using natural language processing, it extracts elements such as date, time, location, and content.

[0253] Step 4:

[0254] The server saves the analyzed schedule information to a database and checks for duplication and conflicts with existing tasks and events.

[0255] Step 5:

[0256] The server prioritizes schedule information. It evaluates tasks based on importance and urgency and determines the reminder schedule.

[0257] Step 6:

[0258] The server generates a reminder and sends it to the user's device at the specified time. The notification is delivered via push at a specific time, informing the user visually or audibly.

[0259] Step 7:

[0260] The server learns the user's past behavioral patterns and generates optimized suggestions based on that. Suggestions for health management and shopping lists are also made in this step.

[0261] Step 8:

[0262] The device receives reminders and suggestions from the server and displays them to the user. The user reviews them and adjusts their schedule as needed.

[0263] Step 9:

[0264] Users input their daily physical condition and health information through their device. This data is sent to a server and used for health management functions.

[0265] Step 10:

[0266] The server analyzes the user's health status based on the collected health information and provides appropriate health maintenance suggestions. If necessary, it sets reminders for the next health check.

[0267] (Example 1)

[0268] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0269] In modern households, it is difficult to centrally manage the individual schedules and health information of each member. Furthermore, there is a need for features that can adapt to rapidly changing schedules and appropriately resolve conflicts and overlaps. Additionally, there is a need for methods to suggest appropriate health management practices to users and improve their quality of daily life.

[0270] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0271] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and setting priorities, and means for storing the schedule information in a storage device and detecting overlaps and conflicts. This makes it possible to comprehensively manage the schedules of each member of the household and efficiently resolve overlaps and conflicts. Furthermore, by collecting health indicators and generating appropriate health management suggestions, it is possible to improve the quality of life.

[0272] "Schedule information" refers to data about appointments and tasks specified by each user, including information such as date and time, content, location, and participants.

[0273] "Means of receiving" refers to the complete set of hardware and software necessary to acquire information from the outside via a network.

[0274] "Means of analysis" refers to a process or device for analyzing received data using a specific algorithm and scrutinizing its contents.

[0275] A "means for setting priorities" is a mechanism for determining the importance and urgency of tasks based on analyzed schedule information, and then deciding the order in which they will be processed.

[0276] A "storage device" is a device or system for storing information long-term, and includes databases, etc.

[0277] "Means for detecting overlaps and conflicts" refers to a process or apparatus for comparing schedule information to find out if any identical or conflicting appointments exist.

[0278] A "reminder" is an alert function that notifies users in advance of appointments they tend to forget.

[0279] A "means for generating suggestions" refers to a system that analyzes data to derive optimal conclusions in order to provide users with suggestions for optimizing their schedules and managing their health.

[0280] The "terminal" is an electronic device that a user uses to input or receive information, including smartphones, tablets, etc.

[0281] The "health indicator" is data for evaluating the user's health condition, including body temperature, blood pressure, etc.

[0282] The "proposal regarding health management" is something that provides advice and information for maintaining a better health condition considering the user's health status.

[0283] The "generative AI model" is an algorithm trained using machine learning to generate optimal outputs for specific tasks.

[0284] This invention is a system for integrally managing the schedules and health of all family members, in which the server, terminal, and user operate in cooperation with each other.

[0285] Server

[0286] The server plays the core role of the system, receiving, analyzing, and storing schedule information. The received schedule information is processed by software using programming languages such as Python. Thereby, duplicate schedules and conflicts are detected on the database, and priorities are set based on the analysis results. Furthermore, by utilizing the generative AI model, optimal reminders and health management proposals can be generated for the user.

[0287] Terminal

[0288] The terminal is a user device such as a smartphone or a tablet, and it receives the input of schedule information from the user. This includes voice input or text input, and that data is sent to the server. Also, reminders and proposals from the server are displayed on the terminal as push notifications, and the user can receive and confirm this information in real time through the terminal.

[0289] User

[0290] As a system user, the user inputs schedule information and health indicators into a terminal. This allows the server to process information related to the user's lifestyle, enabling efficient schedule management and health suggestions. For example, if a user voice-inputs, "I want to set up a remote meeting next Tuesday," that information is transmitted to the server via the terminal and processed accordingly.

[0291] For example, if a user enters a prompt into their device such as, "We have a family dinner tonight. Please check for conflicts with other schedules," this information is analyzed by the server and a reminder is generated. In this way, each user can be helped to avoid missing important events and improve their quality of life at home.

[0292] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0293] Step 1:

[0294] The user enters schedule information into the terminal via voice or text. User input is performed through the terminal's microphone or keyboard. The input data includes specific appointments, such as "Remote meeting next Tuesday at 3pm." Based on this, the terminal generates schedule information in digital format and prepares it for transmission to the server.

[0295] Step 2:

[0296] The terminal sends the schedule information received from the user to the server. The data is transmitted using a secure protocol. The input data is the user's schedule information, and the output data is in a format suitable for transmission to the server. The terminal confirms that this process has completed successfully and waits for the data to arrive at the server.

[0297] Step 3:

[0298] When the server receives schedule information, the analysis software processes the data. The input data is schedule information sent from the terminal. The server analyzes the data using a generative AI model and sets priorities. The output is a schedule that has been checked for conflicts and overlaps. Specific operations include checking the time slots of the schedule and verifying that they do not overlap with other appointments.

[0299] Step 4:

[0300] The server generates necessary alerts and reminders based on the analysis results. A generative AI model is involved in this process to produce the most appropriate messages. The output includes reminders and suggestions to be sent to the user. For example, it might perform a specific action such as "send a preparation notification the day before a remote meeting."

[0301] Step 5:

[0302] The device displays reminders and suggestions received from the server to the user. The input data includes notification information sent from the server. The device displays this information as push notifications and on-screen alerts. This allows the user to efficiently manage their schedule. Specific actions include controlling notification sounds and banner displays on the device.

[0303] (Application Example 1)

[0304] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0305] In modern society, managing the schedules and health of the elderly has become a significant burden for caregivers. To reduce this burden and provide more efficient and personalized support, a flexible and accurate information management system is necessary. Conventional systems have not been able to fully utilize voice input and support various devices, and have also been insufficient in addressing the specific needs of the elderly.

[0306] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0307] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and setting priorities, and means for storing the schedule information in a data storage device and detecting duplicates and conflicts. This makes it possible to identify and manage the schedules and health information of the elderly. By providing means for registering information in the terminal using voice input and communication means compatible with cross-platforms, smooth communication between caregivers and care recipients and personalized health management support can be realized.

[0308] "Schedule information" is data representing the user's schedule and includes the time and place of planned activities and appointments.

[0309] "Priority" is a criterion for ranking multiple schedule information or tasks based on importance or urgency.

[0310] "Data storage device" is a device for electronically storing information and includes databases and cloud storage.

[0311] "Duplicate" refers to a state where there are multiple schedule information that require the same time or resources.

[0312] "Conflict" refers to a situation where different schedule information interferes with each other and is a state where it is necessary to determine priorities.

[0313] "Recommendations" refer to suggested actions or task options presented to the user based on the analysis results.

[0314] A "terminal" refers to a device used by a user to directly input information or receive notifications from a system.

[0315] "Health information" refers to data that indicates the user's physical condition, including biometric information such as body temperature, blood pressure, and exercise level.

[0316] "Health maintenance and management" is a general term for management activities aimed at keeping users in good health.

[0317] "Elderly people" refers to individuals above a certain age, and usually includes those aged 60 and over.

[0318] "Voice input" is an interface technology that allows users to provide information to a device using their voice.

[0319] "Cross-platform" means that the same application or functionality can be run on different platforms.

[0320] "Communication means" refers to functions and technologies that enable the transmission and reception of information, and includes wired and wireless technologies.

[0321] For this invention to be implemented, the interaction between the server, terminal, and user is crucial. The server utilizes cloud infrastructure to receive and analyze schedule information. The server will be built using Amazon Web Services (AWS), and Amazon S3 will be used for data storage. In addition, the Google Cloud Speech-to-Text API will be used to implement voice input functionality. A cross-platform application will be developed using React Native to support ubiquitous devices.

[0322] The device receives voice and text input from the user and sends it to the server in real time. Real-time data synchronization is performed via Firebase, so schedule entries made by the user are immediately reflected on the server. In addition, schedule reminders and health management suggestions are displayed to the user as push notifications. Firebase Cloud Messaging is used for this purpose.

[0323] Users input their daily activities into their device via voice or text, and their schedules and health-related data are updated accordingly. For example, if a user voice-instructs, "I will take my medicine at 10 AM tomorrow," that information is sent to the server, which checks for conflicts and generates reminders as needed. Furthermore, for seniors, the system can provide appropriate exercise suggestions to support their daily health management. For instance, a push notification might say, "Based on your recent activity log, we suggest a 20-minute walk today."

[0324] As a concrete example, a possible prompt for a generative AI model would be, "Please provide schedule management and health suggestions for tomorrow." Based on this prompt, the AI ​​agent would provide a schedule and health suggestions optimized for the user.

[0325] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0326] Step 1:

[0327] The user inputs schedule information into the device via voice. The device uses the Google Cloud Speech-to-Text API to convert the voice data into text data. The input voice is something like "Take my medicine at 10 AM tomorrow," and the output is generated in text format.

[0328] Step 2:

[0329] The device sends the converted text data to the server in real time via Firebase. The input contains text data, which the server receives and stores in a database as schedule information. The output is the stored schedule information.

[0330] Step 3:

[0331] The server stores the received schedule information in Amazon S3 and simultaneously analyzes that information. The analysis checks for any overlaps with existing schedules and sets priorities. The input is schedule information, and the output provides information on whether there are any conflicts and their priorities.

[0332] Step 4:

[0333] The server generates a reminder based on the analysis results. If there are no conflicts, the generated reminder will be a notification such as "Don't forget to take your medicine at 10 AM tomorrow." The input includes the analysis results, and the output is the generated reminder information.

[0334] Step 5:

[0335] The server uses Firebase Cloud Messaging to push reminders generated to the device. By receiving reminder information as input and sending it to the user's device, the user can receive notifications in real time. The output includes push notifications.

[0336] Step 6:

[0337] The user checks the reminder notification displayed on their device and makes any necessary changes to the schedule or adds health information. This allows for re-entry of the information, which is then sent back to the server from step 1, and processing continues.

[0338] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0339] To implement this invention, a system combining an AI agent with an emotion engine is used. This system provides a comprehensive home management solution that integrates emotion detection and response, in addition to scheduling and health management for all family members. The server, terminals, and users work together to effectively realize the system's functions.

[0340] First, users input their daily schedule information through their device, but this is then combined with an emotion-based element. For example, a user might say in voice, "I'm not really looking forward to tomorrow's meeting, but I'll have to attend." This voice data is analyzed by an emotion engine, which determines that the user may be feeling anxious about the meeting.

[0341] The server analyzes the received schedule information and sentiment data. Meeting priorities are assigned based on the already set schedule, but the content of suggestions and reminders is adjusted as needed, taking into account the sentiment engine's corrections. For example, a reminder might be sent just before a meeting saying, "Take a deep breath before the meeting to help you feel relaxed."

[0342] The device receives reminders and suggestions from the server and notifies the user. The user can use these notifications to adjust their schedule and prepare themselves mentally. Emotional data is also used to improve communication within the family. For example, if a family member is feeling stressed, a supportive message tailored to that situation will automatically appear on the device.

[0343] Thus, this invention provides a system that improves the quality of life for families by utilizing an emotion engine to not only manage schedules but also to provide support that is tailored to each individual's emotional state. This emotion-responsive function enables detailed support that is suited to each individual's situation and contributes to the overall improvement of the home environment.

[0344] The following describes the processing flow.

[0345] Step 1:

[0346] The user inputs schedule information using voice or text via a device. The device receives the input information, converts the voice data into text, and prepares it for analysis by an emotion engine.

[0347] Step 2:

[0348] The device sends emotional information extracted from voice and text to the server. At this time, schedule information and emotional data are sent together.

[0349] Step 3:

[0350] The server analyzes the received schedule information and uses natural language processing techniques to extract details such as the date, time, and event name. The emotion engine also analyzes the emotion data and evaluates the user's emotional state.

[0351] Step 4:

[0352] The server stores schedule information in a database and sets schedule priorities. It also takes emotional states into consideration and adjusts priorities as needed.

[0353] Step 5:

[0354] The server generates optimal reminders and suggestions based on schedule information and sentiment analysis. It creates appropriate support messages tailored to the user's emotions and incorporates them into the reminders.

[0355] Step 6:

[0356] Reminders and suggestions generated by the server are sent to the device. The device receives them and provides them to the user as visual or auditory notifications.

[0357] Step 7:

[0358] Users can review received reminders and emotionally-driven suggestions and take action based on them. They can also adjust their schedules if necessary.

[0359] Step 8:

[0360] To support communication among family members, an emotion-based messaging function is utilized on the device. Messages are automatically generated and displayed on the device according to the family's stress levels and emotional state.

[0361] Through these steps, a system is created that integrates and manages emotions and schedules, providing appropriate support.

[0362] (Example 2)

[0363] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0364] In today's family environment, managing each member's schedule and health has become a crucial issue. Furthermore, it is necessary to appropriately understand emotional fluctuations and mental states, and to promote smooth communication among family members. However, managing and supporting these aspects individually is burdensome and inefficient. Therefore, there is a need for a system that provides emotionally-based support in addition to schedule and health management, thereby improving the quality of life for families.

[0365] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0366] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and emotional data, setting priorities and adjusting them, and means for detecting the emotional state of family members and generating messages to facilitate communication among family members. This makes it possible to improve the overall quality of life for the family by effectively managing the family's schedule and health and providing emotional support.

[0367] "Schedule information" refers to time-based information such as appointments, tasks, and events related to an individual or group.

[0368] "Emotional analysis" is the process of analyzing voice and text data to determine the user's emotional state.

[0369] A "reminder" is an alert or notification that alerts users to appointments or tasks that are easily forgotten.

[0370] A "suggestion" is a recommendation of actions or advice provided based on the user's schedule and status.

[0371] A "database" is an information storage system that allows for the systematic management and access of digital data as needed.

[0372] "Health information" refers to data that indicates an individual's health status, including, for example, heart rate, sleep duration, and stress level.

[0373] A "message" is a written or electronic means of communication used to transmit information.

[0374] A "learning algorithm" is a computational method that finds patterns and rules from past data and applies them to new data to make predictions and classifications.

[0375] This invention provides a system that integrates household schedule management, health management, and emotional support. The components necessary to implement this include a server, terminals, an emotion engine, and a database. Specific examples using these elements are described below.

[0376] The server operates on a cloud-based platform. The server receives schedule information sent from users via their devices. These devices are smartphones and tablets, and they use voice input to send information about the user's daily schedule and emotions to the server.

[0377] The server uses existing natural language processing APIs as its sentiment engine to analyze this audio data. For example, Google Cloud's Natural Language API is used. This API analyzes audio and text data and generates sentiment scores and categories.

[0378] The analyzed emotional data is integrated with schedule information by the server. Based on this, the server prioritizes daily appointments and generates reminders and suggestions as needed. The server also uses the emotional data to send appropriate messages to facilitate communication among family members.

[0379] For example, if a user voice-inputs, "I'm not really looking forward to tomorrow's meeting, but I'll attend," the system's emotion engine will analyze that the user is anxious about the meeting and generate a suggestion such as, "Try taking a deep breath before the meeting so you can approach it feeling more relaxed."

[0380] An example of a prompt for a generative AI model might be, "Please provide ideas for using the emotion engine to detect the user's emotional state and suggest specific actions." This prompt is used by the generative AI model when developing new features.

[0381] Through these means, the system of the present invention can improve the quality of life for families and provide detailed support tailored to individual schedules and emotional states.

[0382] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0383] Step 1:

[0384] The user uses their device to perform voice input. This input includes schedule information and the user's emotions. Specifically, the user uses their smartphone's voice input function to say, "I'm not really looking forward to it, but I'll attend the meeting tomorrow." This voice data is recorded on the device.

[0385] Step 2:

[0386] The terminal converts recorded audio data into text and sends it to the server. The input is audio data, and the output is text data. The terminal uses speech recognition technology to perform this conversion, and the result is sent to the server via the network.

[0387] Step 3:

[0388] The server passes the received text data to the sentiment engine, which then performs sentiment analysis. The input is text data, and the output is sentiment scores or categories. The server calls a natural language processing API to obtain numerical data representing the emotional state.

[0389] Step 4:

[0390] The server integrates the sentiment analysis results into the schedule information and resets priorities. The input is existing schedule data and sentiment data, and the output is a priority-adjusted schedule. The server accesses the database and updates the task rankings, taking priorities into account.

[0391] Step 5:

[0392] The server generates reminders and suggestions based on emotional data. The input is a prioritized schedule, and the output is a message containing a specific action. For example, a suggestion might be generated: "Take a deep breath before the meeting to help you feel relaxed."

[0393] Step 6:

[0394] The server sends generated reminders and suggestions to the terminal. The input is message data, and the output is a notification to the terminal. The server dispatches the notification to the terminal via a communication method.

[0395] Step 7:

[0396] The terminal displays notifications received from the server to the user. Input is received data, and output is a visual or auditory notification to the user. The terminal displays messages on the screen and provides alerts to the user through sound or vibration.

[0397] (Application Example 2)

[0398] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0399] In modern households, managing family schedules and health has become increasingly complex, and there is a need for lifestyle support that is tailored to each individual's mental state. However, conventional technologies have made it difficult to address these issues comprehensively. Furthermore, there is a lack of means to facilitate communication among family members and improve their quality of life.

[0400] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0401] In this invention, the server includes means for receiving schedule information, means for analyzing emotions from voice data and generating suggestions according to the user's emotional state, and means for providing emotion-based feedback and suggestions via an operating device. This makes it possible to manage the schedules and health of the entire family, provide individual suggestions and support based on emotional states, and facilitate communication among family members.

[0402] "Schedule information" refers to data related to daily appointments and events, and is used for planning and managing individual and group activities.

[0403] "Priority" refers to the ranking of the importance and urgency of performing multiple tasks or appointments.

[0404] A "database" is a system that systematically stores and manages various types of data and information, making it easy to access and manipulate.

[0405] "Overlap or conflict" refers to a situation where multiple appointments or tasks exist that are allocated to the same time or resources.

[0406] A "reminder" is a feature that notifies users based on specific times or conditions to remind them of tasks or appointments.

[0407] "Health information" refers to data about an individual's health status, used to assess their physical and mental condition.

[0408] "Audio data" refers to data that records audio signals, and it forms the basis for the analysis and recognition of acoustic information.

[0409] "Emotional analysis" is the process of evaluating and identifying an individual's emotional state from voice and behavioral data.

[0410] "Operational devices" refer to equipment or devices that control physical movement and provide users with an interactive experience.

[0411] "Feedback" refers to information returned as a response to an action or input, providing an appropriate response depending on the user's actions and state.

[0412] This system analyzes the user's emotional state based on their schedule and health information to improve their quality of life at home, and provides appropriate feedback and suggestions. Specifically, the server, terminal, and user work together to perform the following processes.

[0413] The server receives voice data input from the user and analyzes the user's emotions using speech recognition technology and a generative AI model for sentiment analysis (e.g., Google Cloud's Natural Language API). The analyzed sentiment data is stored in a database along with schedule information and health data. Based on this information, the server generates reminders and suggestions tailored to the user's current state and sends them to the device.

[0414] The device notifies the user of reminders and suggestions received from the server. Notifications are sent via a smartphone or a home device (e.g., a home robot), allowing the user to adjust their schedule and prepare themselves accordingly.

[0415] Based on the suggestions received, users can improve their lifestyle habits and enhance communication within their families. As a concrete example of this system, if an elementary school child comes home from school and says, "I'm too tired to do my homework today," the robot will sense this and suggest, "Why don't you take a 15-minute break before starting your homework?"

[0416] Examples of prompts for the generating AI model include, "Assuming the user is feeling anxious, please give advice on preparing for tomorrow's meeting," and "If a child is complaining of fatigue, please generate advice to encourage relaxation." In this way, the system aims to comprehensively improve the quality of life by addressing the emotional needs of the entire family.

[0417] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0418] Step 1:

[0419] The server receives audio data from the user. This input data contains the user's speech. Speech recognition software is used to convert this data into text. Once the audio-to-text conversion is complete, the data is passed on to sentiment analysis.

[0420] Step 2:

[0421] The server uses a generative AI model to analyze the user's emotions from text data. The input contains converted text data, which the emotion analysis engine processes to obtain an output in the form of an emotional state (e.g., "anxiety" or "fatigue"). This emotional state is the information needed for subsequent processing.

[0422] Step 3:

[0423] The server combines analyzed emotional states with pre-registered schedule information to generate appropriate reminders and suggestions. This input data includes emotional states and schedule information. Based on this, the server determines what kind of support the user needs and generates a corresponding message.

[0424] Step 4:

[0425] The device receives reminders and suggestions sent from the server and notifies the user. The input for this step is the message provided by the server. The notification function is activated on the device, and as a concrete action, the user receives a visual or audible notification.

[0426] Step 5:

[0427] Users review notifications and suggestions received through their devices to help adjust their lives and improve their emotions. The output in this step represents the results of users actually adjusting their behavior based on the suggestions. This is a specific step in which users receive notifications from their devices and decide how to change their behavior.

[0428] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0429] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0430] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0431] [Third Embodiment]

[0432] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0433] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0434] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0435] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0436] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0437] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0438] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0439] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0440] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0441] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0442] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0443] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0444] As an embodiment of this invention, an AI agent system that centrally manages the schedules and tasks of all family members is described. The system operates through the interaction of a server, terminals, and users, smoothly realizing each of its functions.

[0445] The server plays a central role in the system, receiving and storing schedule information sent from users and terminals. The server analyzes this information and sets priorities to achieve efficient schedule management. Specifically, it compares entered schedules with other tasks to detect duplicates and conflicts. If a conflict occurs, it generates an alert and notifies the user.

[0446] The terminal is a device that allows users to input schedule information and receive reminders and suggestions. Users can input schedule information via voice or text, and the terminal sends this information to the server. Upon receiving reminders and suggestions from the server, the terminal displays them to the user as push notifications. This feature ensures that users do not miss important tasks or events.

[0447] Furthermore, the server also provides functionality in terms of health management. It collects health information entered by users through their devices and generates health management suggestions based on this information. For the elderly, it provides reminders for regular health checks and suggestions for appropriate exercise, thereby helping to prevent the burden of caregiving.

[0448] For example, if a user wants to add a remote meeting to the following Tuesday, they would input the information into their device via voice, and that information would be sent to the server. The server would check for conflicts with other appointments and generate a reminder based on the importance of the meeting. The day before, the device would receive a notification saying, "Prepare for tomorrow's remote meeting." In addition, a suggestion for health management, such as "Let's do 15 minutes of stretching today," would also be sent.

[0449] In this way, the invention efficiently manages the schedules and provides health suggestions for the entire family, improving the quality of life at home.

[0450] The following describes the processing flow.

[0451] Step 1:

[0452] The user enters schedule information using voice or text via the device. The device receives the entered information, converts it to text if it was entered via voice, and temporarily stores it locally.

[0453] Step 2:

[0454] The terminal sends the entered schedule information to the server. Here, the data is securely transferred over the network.

[0455] Step 3:

[0456] The server analyzes the received schedule information. Using natural language processing, it extracts elements such as date, time, location, and content.

[0457] Step 4:

[0458] The server saves the analyzed schedule information to a database and checks for duplication and conflicts with existing tasks and events.

[0459] Step 5:

[0460] The server prioritizes schedule information. It evaluates tasks based on importance and urgency and determines the reminder schedule.

[0461] Step 6:

[0462] The server generates a reminder and sends it to the user's device at the specified time. The notification is delivered via push at a specific time, informing the user visually or audibly.

[0463] Step 7:

[0464] The server learns the user's past behavioral patterns and generates optimized suggestions based on that. Suggestions for health management and shopping lists are also made in this step.

[0465] Step 8:

[0466] The device receives reminders and suggestions from the server and displays them to the user. The user reviews them and adjusts their schedule as needed.

[0467] Step 9:

[0468] Users input their daily physical condition and health information through their device. This data is sent to a server and used for health management functions.

[0469] Step 10:

[0470] The server analyzes the user's health status based on the collected health information and provides appropriate health maintenance suggestions. If necessary, it sets reminders for the next health check.

[0471] (Example 1)

[0472] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0473] In modern households, it is difficult to centrally manage the individual schedules and health information of each member. Furthermore, there is a need for features that can adapt to rapidly changing schedules and appropriately resolve conflicts and overlaps. Additionally, there is a need for methods to suggest appropriate health management practices to users and improve their quality of daily life.

[0474] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0475] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and setting priorities, and means for storing the schedule information in a storage device and detecting overlaps and conflicts. This makes it possible to comprehensively manage the schedules of each member of the household and efficiently resolve overlaps and conflicts. Furthermore, by collecting health indicators and generating appropriate health management suggestions, it is possible to improve the quality of life.

[0476] "Schedule information" refers to data about appointments and tasks specified by each user, including information such as date and time, content, location, and participants.

[0477] "Means of receiving" refers to the complete set of hardware and software necessary to acquire information from the outside via a network.

[0478] "Means of analysis" refers to a process or device for analyzing received data using a specific algorithm and scrutinizing its contents.

[0479] A "means for setting priorities" is a mechanism for determining the importance and urgency of tasks based on analyzed schedule information, and then deciding the order in which they will be processed.

[0480] A "storage device" is a device or system for storing information long-term, and includes databases, etc.

[0481] "Means for detecting overlaps and conflicts" refers to a process or apparatus for comparing schedule information to find out if any identical or conflicting appointments exist.

[0482] A "reminder" is an alert function that notifies users in advance of appointments they tend to forget.

[0483] A "means for generating suggestions" refers to a system that analyzes data to derive optimal conclusions in order to provide users with suggestions for optimizing their schedules and managing their health.

[0484] A "terminal" is an electronic device used by a user to input or receive information, and includes smartphones, tablets, and other similar devices.

[0485] "Health indicators" are data used to evaluate a user's health status, and include things like body temperature and blood pressure.

[0486] "Health management suggestions" refer to advice and information provided to help users maintain better health, taking their current health status into consideration.

[0487] A "generative AI model" is an algorithm trained using machine learning to generate the optimal output for a specific task.

[0488] This invention is a system that integrates scheduling and health management for all family members, with the server, terminals, and users working together in a coordinated manner.

[0489] server

[0490] The server plays a central role in the system, receiving, analyzing, and storing schedule information. The received schedule information is processed by software using programming languages ​​such as Python. This allows for the detection of schedule overlaps and conflicts in the database, and the setting of priorities based on the analysis results. Furthermore, it can utilize a generative AI model to generate optimal reminders and health management suggestions for the user.

[0491] terminal

[0492] The terminal is a user device such as a smartphone or tablet, which accepts schedule information input from the user. This includes voice input or text input, and this data is sent to the server. Reminders and suggestions from the server are also displayed on the terminal as push notifications, and the user can receive and check this information in real time through the terminal.

[0493] User

[0494] As a system user, the user inputs schedule information and health indicators into a terminal. This allows the server to process information related to the user's lifestyle, enabling efficient schedule management and health suggestions. For example, if a user voice-inputs, "I want to set up a remote meeting next Tuesday," that information is transmitted to the server via the terminal and processed accordingly.

[0495] For example, if a user enters a prompt into their device such as, "We have a family dinner tonight. Please check for conflicts with other schedules," this information is analyzed by the server and a reminder is generated. In this way, each user can be helped to avoid missing important events and improve their quality of life at home.

[0496] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0497] Step 1:

[0498] The user enters schedule information into the terminal via voice or text. User input is performed through the terminal's microphone or keyboard. The input data includes specific appointments, such as "Remote meeting next Tuesday at 3pm." Based on this, the terminal generates schedule information in digital format and prepares it for transmission to the server.

[0499] Step 2:

[0500] The terminal sends the schedule information received from the user to the server. The data is transmitted using a secure protocol. The input data is the user's schedule information, and the output data is in a format suitable for transmission to the server. The terminal confirms that this process has completed successfully and waits for the data to arrive at the server.

[0501] Step 3:

[0502] When the server receives schedule information, the analysis software processes the data. The input data is schedule information sent from the terminal. The server analyzes the data using a generative AI model and sets priorities. The output is a schedule that has been checked for conflicts and overlaps. Specific operations include checking the time slots of the schedule and verifying that they do not overlap with other appointments.

[0503] Step 4:

[0504] The server generates necessary alerts and reminders based on the analysis results. A generative AI model is involved in this process to produce the most appropriate messages. The output includes reminders and suggestions to be sent to the user. For example, it might perform a specific action such as "send a preparation notification the day before a remote meeting."

[0505] Step 5:

[0506] The device displays reminders and suggestions received from the server to the user. The input data includes notification information sent from the server. The device displays this information as push notifications and on-screen alerts. This allows the user to efficiently manage their schedule. Specific actions include controlling notification sounds and banner displays on the device.

[0507] (Application Example 1)

[0508] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0509] In modern society, managing the schedules and health of elderly individuals places a significant burden on caregivers. To alleviate this burden and provide more efficient and personalized support, a flexible and accurate information management system is necessary. Conventional systems have not fully utilized voice input or compatibility with diverse devices, and have been inadequate in addressing the unique needs of the elderly.

[0510] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0511] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and setting priorities, and means for storing the schedule information in a data storage device and detecting duplicates and conflicts. This makes it possible to identify and manage the schedules and health information of elderly people. By also providing means for registering information on a terminal using voice input and cross-platform compatible communication means, smooth communication between caregivers and those receiving care and personalized health management support can be realized.

[0512] "Schedule information" refers to data representing the user's schedule, including the time and place of planned activities and appointments.

[0513] "Priority" is a criterion used to rank multiple schedules and tasks based on their importance and urgency.

[0514] A "data storage device" is a device for electronically storing information, and includes databases and cloud storage.

[0515] "Duplicate" refers to a situation where multiple schedule entries exist that require the same time or resources.

[0516] "Conflict" refers to a situation where different schedule information interferes with each other, and it is necessary to determine priorities.

[0517] "Recommendations" refer to suggested actions or task options presented to the user based on the analysis results.

[0518] A "terminal" refers to a device used by a user to directly input information or receive notifications from a system.

[0519] "Health information" refers to data that indicates the user's physical condition, including biometric information such as body temperature, blood pressure, and exercise level.

[0520] "Health maintenance and management" is a general term for management activities aimed at keeping users in good health.

[0521] "Elderly people" refers to individuals above a certain age, and usually includes those aged 60 and over.

[0522] "Voice input" is an interface technology that allows users to provide information to a device using their voice.

[0523] "Cross-platform" means that the same application or functionality can be run on different platforms.

[0524] "Communication means" refers to functions and technologies that enable the transmission and reception of information, and includes wired and wireless technologies.

[0525] For this invention to be implemented, the interaction between the server, terminal, and user is crucial. The server utilizes cloud infrastructure to receive and analyze schedule information. The server will be built using Amazon Web Services (AWS), and Amazon S3 will be used for data storage. In addition, the Google Cloud Speech-to-Text API will be used to implement voice input functionality. A cross-platform application will be developed using React Native to support ubiquitous devices.

[0526] The device receives voice and text input from the user and sends it to the server in real time. Real-time data synchronization is performed via Firebase, so schedule entries made by the user are immediately reflected on the server. In addition, schedule reminders and health management suggestions are displayed to the user as push notifications. Firebase Cloud Messaging is used for this purpose.

[0527] Users input their daily activities into their device via voice or text, and their schedules and health-related data are updated accordingly. For example, if a user voice-instructs, "I will take my medicine at 10 AM tomorrow," that information is sent to the server, which checks for conflicts and generates reminders as needed. Furthermore, for seniors, the system can provide appropriate exercise suggestions to support their daily health management. For instance, a push notification might say, "Based on your recent activity log, we suggest a 20-minute walk today."

[0528] As a concrete example, a possible prompt for a generative AI model would be, "Please provide schedule management and health suggestions for tomorrow." Based on this prompt, the AI ​​agent would provide a schedule and health suggestions optimized for the user.

[0529] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0530] Step 1:

[0531] The user inputs schedule information into the device via voice. The device uses the Google Cloud Speech-to-Text API to convert the voice data into text data. The input voice is something like "Take my medicine at 10 AM tomorrow," and the output is generated in text format.

[0532] Step 2:

[0533] The device sends the converted text data to the server in real time via Firebase. The input contains text data, which the server receives and stores in a database as schedule information. The output is the stored schedule information.

[0534] Step 3:

[0535] The server stores the received schedule information in Amazon S3 and simultaneously analyzes that information. The analysis checks for any overlaps with existing schedules and sets priorities. The input is schedule information, and the output provides information on whether there are any conflicts and their priorities.

[0536] Step 4:

[0537] The server generates a reminder based on the analysis results. If there are no conflicts, the generated reminder will be a notification such as "Don't forget to take your medicine at 10 AM tomorrow." The input includes the analysis results, and the output is the generated reminder information.

[0538] Step 5:

[0539] The server uses Firebase Cloud Messaging to push reminders generated to the device. By receiving reminder information as input and sending it to the user's device, the user can receive notifications in real time. The output includes push notifications.

[0540] Step 6:

[0541] The user checks the reminder notification displayed on their device and makes any necessary changes to the schedule or adds health information. This allows for re-entry of the information, which is then sent back to the server from step 1, and processing continues.

[0542] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0543] To implement this invention, a system combining an AI agent with an emotion engine is used. This system provides a comprehensive home management solution that integrates emotion detection and response, in addition to scheduling and health management for all family members. The server, terminals, and users work together to effectively realize the system's functions.

[0544] First, users input their daily schedule information through their device, but this is then combined with an emotion-based element. For example, a user might say in voice, "I'm not really looking forward to tomorrow's meeting, but I'll have to attend." This voice data is analyzed by an emotion engine, which determines that the user may be feeling anxious about the meeting.

[0545] The server analyzes the received schedule information and sentiment data. Meeting priorities are assigned based on the already set schedule, but the content of suggestions and reminders is adjusted as needed, taking into account the sentiment engine's corrections. For example, a reminder might be sent just before a meeting saying, "Take a deep breath before the meeting to help you feel relaxed."

[0546] The device receives reminders and suggestions from the server and notifies the user. The user can use these notifications to adjust their schedule and prepare themselves mentally. Emotional data is also used to improve communication within the family. For example, if a family member is feeling stressed, a supportive message tailored to that situation will automatically appear on the device.

[0547] Thus, this invention provides a system that improves the quality of life for families by utilizing an emotion engine to not only manage schedules but also to provide support that is tailored to each individual's emotional state. This emotion-responsive function enables detailed support that is suited to each individual's situation and contributes to the overall improvement of the home environment.

[0548] The following describes the processing flow.

[0549] Step 1:

[0550] The user inputs schedule information using voice or text via a device. The device receives the input information, converts the voice data into text, and prepares it for analysis by an emotion engine.

[0551] Step 2:

[0552] The device sends emotional information extracted from voice and text to the server. At this time, schedule information and emotional data are sent together.

[0553] Step 3:

[0554] The server analyzes the received schedule information and uses natural language processing techniques to extract details such as the date, time, and event name. The emotion engine also analyzes the emotion data and evaluates the user's emotional state.

[0555] Step 4:

[0556] The server stores schedule information in a database and sets schedule priorities. It also takes emotional states into consideration and adjusts priorities as needed.

[0557] Step 5:

[0558] The server generates optimal reminders and suggestions based on schedule information and sentiment analysis. It creates appropriate support messages tailored to the user's emotions and incorporates them into the reminders.

[0559] Step 6:

[0560] Reminders and suggestions generated by the server are sent to the device. The device receives them and provides them to the user as visual or auditory notifications.

[0561] Step 7:

[0562] Users can review received reminders and emotionally-driven suggestions and take action based on them. They can also adjust their schedules if necessary.

[0563] Step 8:

[0564] To support communication among family members, an emotion-based messaging function is utilized on the device. Messages are automatically generated and displayed on the device according to the family's stress levels and emotional state.

[0565] Through these steps, a system is created that integrates and manages emotions and schedules, providing appropriate support.

[0566] (Example 2)

[0567] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0568] In today's family environment, managing each member's schedule and health has become a crucial issue. Furthermore, it is necessary to appropriately understand emotional fluctuations and mental states, and to promote smooth communication among family members. However, managing and supporting these aspects individually is burdensome and inefficient. Therefore, there is a need for a system that provides emotionally-based support in addition to schedule and health management, thereby improving the quality of life for families.

[0569] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0570] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and emotional data, setting priorities and adjusting them, and means for detecting the emotional state of family members and generating messages to facilitate communication among family members. This makes it possible to improve the overall quality of life for the family by effectively managing the family's schedule and health and providing emotional support.

[0571] "Schedule information" refers to time-based information such as appointments, tasks, and events related to an individual or group.

[0572] "Emotional analysis" is the process of analyzing voice and text data to determine the user's emotional state.

[0573] A "reminder" is an alert or notification that alerts users to appointments or tasks that are easily forgotten.

[0574] A "suggestion" is a recommendation of actions or advice provided based on the user's schedule and status.

[0575] A "database" is an information storage system that allows for the systematic management and access of digital data as needed.

[0576] "Health information" refers to data that indicates an individual's health status, including, for example, heart rate, sleep duration, and stress level.

[0577] A "message" is a written or electronic means of communication used to transmit information.

[0578] A "learning algorithm" is a computational method that finds patterns and rules from past data and applies them to new data to make predictions and classifications.

[0579] This invention provides a system that integrates household schedule management, health management, and emotional support. The components necessary to implement this include a server, terminals, an emotion engine, and a database. Specific examples using these elements are described below.

[0580] The server operates on a cloud-based platform. The server receives schedule information sent from users via their devices. These devices are smartphones and tablets, and they use voice input to send information about the user's daily schedule and emotions to the server.

[0581] The server uses existing natural language processing APIs as its sentiment engine to analyze this audio data. For example, Google Cloud's Natural Language API is used. This API analyzes audio and text data and generates sentiment scores and categories.

[0582] The analyzed emotional data is integrated with schedule information by the server. Based on this, the server prioritizes daily appointments and generates reminders and suggestions as needed. The server also uses the emotional data to send appropriate messages to facilitate communication among family members.

[0583] For example, if a user voice-inputs, "I'm not really looking forward to tomorrow's meeting, but I'll attend," the system's emotion engine will analyze that the user is anxious about the meeting and generate a suggestion such as, "Try taking a deep breath before the meeting so you can approach it feeling more relaxed."

[0584] An example of a prompt for a generative AI model might be, "Please provide ideas for using the emotion engine to detect the user's emotional state and suggest specific actions." This prompt is used by the generative AI model when developing new features.

[0585] Through these means, the system of the present invention can improve the quality of life for families and provide detailed support tailored to individual schedules and emotional states.

[0586] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0587] Step 1:

[0588] The user uses their device to perform voice input. This input includes schedule information and the user's emotions. Specifically, the user uses their smartphone's voice input function to say, "I'm not really looking forward to it, but I'll attend the meeting tomorrow." This voice data is recorded on the device.

[0589] Step 2:

[0590] The terminal converts recorded audio data into text and sends it to the server. The input is audio data, and the output is text data. The terminal uses speech recognition technology to perform this conversion, and the result is sent to the server via the network.

[0591] Step 3:

[0592] The server passes the received text data to the sentiment engine, which then performs sentiment analysis. The input is text data, and the output is sentiment scores or categories. The server calls a natural language processing API to obtain numerical data representing the emotional state.

[0593] Step 4:

[0594] The server integrates the sentiment analysis results into the schedule information and resets priorities. The input is existing schedule data and sentiment data, and the output is a priority-adjusted schedule. The server accesses the database and updates the task rankings, taking priorities into account.

[0595] Step 5:

[0596] The server generates reminders and suggestions based on emotional data. The input is a prioritized schedule, and the output is a message containing a specific action. For example, a suggestion might be generated: "Take a deep breath before the meeting to help you feel relaxed."

[0597] Step 6:

[0598] The server sends generated reminders and suggestions to the terminal. The input is message data, and the output is a notification to the terminal. The server dispatches the notification to the terminal via a communication method.

[0599] Step 7:

[0600] The terminal displays notifications received from the server to the user. Input is received data, and output is a visual or auditory notification to the user. The terminal displays messages on the screen and provides alerts to the user through sound or vibration.

[0601] (Application Example 2)

[0602] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0603] In modern households, managing family schedules and health has become increasingly complex, and there is a need for lifestyle support that is tailored to each individual's mental state. However, conventional technologies have made it difficult to address these issues comprehensively. Furthermore, there is a lack of means to facilitate communication among family members and improve their quality of life.

[0604] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0605] In this invention, the server includes means for receiving schedule information, means for analyzing emotions from voice data and generating suggestions according to the user's emotional state, and means for providing emotion-based feedback and suggestions via an operating device. This makes it possible to manage the schedules and health of the entire family, provide individual suggestions and support based on emotional states, and facilitate communication among family members.

[0606] "Schedule information" refers to data related to daily appointments and events, and is used for planning and managing individual and group activities.

[0607] "Priority" refers to the ranking of the importance and urgency of performing multiple tasks or appointments.

[0608] A "database" is a system that systematically stores and manages various types of data and information, making it easy to access and manipulate.

[0609] "Overlap or conflict" refers to a situation where multiple appointments or tasks exist that are allocated to the same time or resources.

[0610] A "reminder" is a feature that notifies users based on specific times or conditions to remind them of tasks or appointments.

[0611] "Health information" refers to data about an individual's health status, used to assess their physical and mental condition.

[0612] "Audio data" refers to data that records audio signals, and it forms the basis for the analysis and recognition of acoustic information.

[0613] "Emotional analysis" is the process of evaluating and identifying an individual's emotional state from voice and behavioral data.

[0614] "Operational devices" refer to equipment or devices that control physical movement and provide users with an interactive experience.

[0615] "Feedback" refers to information returned as a response to an action or input, providing an appropriate response depending on the user's actions and state.

[0616] This system analyzes the user's emotional state based on their schedule and health information to improve their quality of life at home, and provides appropriate feedback and suggestions. Specifically, the server, terminal, and user work together to perform the following processes.

[0617] The server receives voice data input from the user and analyzes the user's emotions using speech recognition technology and a generative AI model for sentiment analysis (e.g., Google Cloud's Natural Language API). The analyzed sentiment data is stored in a database along with schedule information and health data. Based on this information, the server generates reminders and suggestions tailored to the user's current state and sends them to the device.

[0618] The device notifies the user of reminders and suggestions received from the server. Notifications are sent via a smartphone or a home device (e.g., a home robot), allowing the user to adjust their schedule and prepare themselves accordingly.

[0619] Based on the suggestions received, users can improve their lifestyle habits and enhance communication within their families. As a concrete example of this system, if an elementary school child comes home from school and says, "I'm too tired to do my homework today," the robot will sense this and suggest, "Why don't you take a 15-minute break before starting your homework?"

[0620] Examples of prompts for the generating AI model include, "Assuming the user is feeling anxious, please give advice on preparing for tomorrow's meeting," and "If a child is complaining of fatigue, please generate advice to encourage relaxation." In this way, the system aims to comprehensively improve the quality of life by addressing the emotional needs of the entire family.

[0621] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0622] Step 1:

[0623] The server receives audio data from the user. This input data contains the user's speech. Speech recognition software is used to convert this data into text. Once the audio-to-text conversion is complete, the data is passed on to sentiment analysis.

[0624] Step 2:

[0625] The server uses a generative AI model to analyze the user's emotions from text data. The input contains converted text data, which the emotion analysis engine processes to obtain an output in the form of an emotional state (e.g., "anxiety" or "fatigue"). This emotional state is the information needed for subsequent processing.

[0626] Step 3:

[0627] The server combines analyzed emotional states with pre-registered schedule information to generate appropriate reminders and suggestions. This input data includes emotional states and schedule information. Based on this, the server determines what kind of support the user needs and generates a corresponding message.

[0628] Step 4:

[0629] The device receives reminders and suggestions sent from the server and notifies the user. The input for this step is the message provided by the server. The notification function is activated on the device, and as a concrete action, the user receives a visual or audible notification.

[0630] Step 5:

[0631] Users review notifications and suggestions received through their devices to help adjust their lives and improve their emotions. The output in this step represents the results of users actually adjusting their behavior based on the suggestions. This is a specific step in which users receive notifications from their devices and decide how to change their behavior.

[0632] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0633] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0634] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0635] [Fourth Embodiment]

[0636] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0637] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0638] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0639] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0640] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0641] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0642] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0643] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0644] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0645] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0646] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0647] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0648] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0649] As an embodiment of this invention, an AI agent system that centrally manages the schedules and tasks of all family members is described. The system operates through the interaction of a server, terminals, and users, smoothly realizing each of its functions.

[0650] The server plays a central role in the system, receiving and storing schedule information sent from users and terminals. The server analyzes this information and sets priorities to achieve efficient schedule management. Specifically, it compares entered schedules with other tasks to detect duplicates and conflicts. If a conflict occurs, it generates an alert and notifies the user.

[0651] The terminal is a device that allows users to input schedule information and receive reminders and suggestions. Users can input schedule information via voice or text, and the terminal sends this information to the server. Upon receiving reminders and suggestions from the server, the terminal displays them to the user as push notifications. This feature ensures that users do not miss important tasks or events.

[0652] Furthermore, the server also provides functionality in terms of health management. It collects health information entered by users through their devices and generates health management suggestions based on this information. For the elderly, it provides reminders for regular health checks and suggestions for appropriate exercise, thereby helping to prevent the burden of caregiving.

[0653] For example, if a user wants to add a remote meeting to the following Tuesday, they would input the information into their device via voice, and that information would be sent to the server. The server would check for conflicts with other appointments and generate a reminder based on the importance of the meeting. The day before, the device would receive a notification saying, "Prepare for tomorrow's remote meeting." In addition, a suggestion for health management, such as "Let's do 15 minutes of stretching today," would also be sent.

[0654] In this way, the invention efficiently manages the schedules and provides health suggestions for the entire family, improving the quality of life at home.

[0655] The following describes the processing flow.

[0656] Step 1:

[0657] The user enters schedule information using voice or text via the device. The device receives the entered information, converts it to text if it was entered via voice, and temporarily stores it locally.

[0658] Step 2:

[0659] The terminal sends the entered schedule information to the server. Here, the data is securely transferred over the network.

[0660] Step 3:

[0661] The server analyzes the received schedule information. Using natural language processing, it extracts elements such as date, time, location, and content.

[0662] Step 4:

[0663] The server saves the analyzed schedule information to a database and checks for duplication and conflicts with existing tasks and events.

[0664] Step 5:

[0665] The server prioritizes schedule information. It evaluates tasks based on importance and urgency and determines the reminder schedule.

[0666] Step 6:

[0667] The server generates a reminder and sends it to the user's device at the specified time. The notification is delivered via push at a specific time, informing the user visually or audibly.

[0668] Step 7:

[0669] The server learns the user's past behavioral patterns and generates optimized suggestions based on that. Suggestions for health management and shopping lists are also made in this step.

[0670] Step 8:

[0671] The device receives reminders and suggestions from the server and displays them to the user. The user reviews them and adjusts their schedule as needed.

[0672] Step 9:

[0673] Users input their daily physical condition and health information through their device. This data is sent to a server and used for health management functions.

[0674] Step 10:

[0675] The server analyzes the user's health status based on the collected health information and provides appropriate health maintenance suggestions. If necessary, it sets reminders for the next health check.

[0676] (Example 1)

[0677] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0678] In modern households, it is difficult to centrally manage the individual schedules and health information of each member. Furthermore, there is a need for features that can adapt to rapidly changing schedules and appropriately resolve conflicts and overlaps. Additionally, there is a need for methods to suggest appropriate health management practices to users and improve their quality of daily life.

[0679] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0680] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and setting priorities, and means for storing the schedule information in a storage device and detecting overlaps and conflicts. This makes it possible to comprehensively manage the schedules of each member of the household and efficiently resolve overlaps and conflicts. Furthermore, by collecting health indicators and generating appropriate health management suggestions, it is possible to improve the quality of life.

[0681] "Schedule information" refers to data about appointments and tasks specified by each user, including information such as date and time, content, location, and participants.

[0682] "Means of receiving" refers to the complete set of hardware and software necessary to acquire information from the outside via a network.

[0683] "Means of analysis" refers to a process or device for analyzing received data using a specific algorithm and scrutinizing its contents.

[0684] A "means for setting priorities" is a mechanism for determining the importance and urgency of tasks based on analyzed schedule information, and then deciding the order in which they will be processed.

[0685] A "storage device" is a device or system for storing information long-term, and includes databases, etc.

[0686] "Means for detecting overlaps and conflicts" refers to a process or apparatus for comparing schedule information to find out if any identical or conflicting appointments exist.

[0687] A "reminder" is an alert function that notifies users in advance of appointments they tend to forget.

[0688] A "means for generating suggestions" refers to a system that analyzes data to derive optimal conclusions in order to provide users with suggestions for optimizing their schedules and managing their health.

[0689] A "terminal" is an electronic device used by a user to input or receive information, and includes smartphones, tablets, and other similar devices.

[0690] "Health indicators" are data used to evaluate a user's health status, and include things like body temperature and blood pressure.

[0691] "Health management suggestions" refer to advice and information provided to help users maintain better health, taking their current health status into consideration.

[0692] A "generative AI model" is an algorithm trained using machine learning to generate the optimal output for a specific task.

[0693] This invention is a system that integrates scheduling and health management for all family members, with the server, terminals, and users working together in a coordinated manner.

[0694] server

[0695] The server plays a central role in the system, receiving, analyzing, and storing schedule information. The received schedule information is processed by software using programming languages ​​such as Python. This allows for the detection of schedule overlaps and conflicts in the database, and the setting of priorities based on the analysis results. Furthermore, it can utilize a generative AI model to generate optimal reminders and health management suggestions for the user.

[0696] terminal

[0697] The terminal is a user device such as a smartphone or tablet, which accepts schedule information input from the user. This includes voice input or text input, and this data is sent to the server. Reminders and suggestions from the server are also displayed on the terminal as push notifications, and the user can receive and check this information in real time through the terminal.

[0698] User

[0699] As a system user, the user inputs schedule information and health indicators into a terminal. This allows the server to process information related to the user's lifestyle, enabling efficient schedule management and health suggestions. For example, if a user voice-inputs, "I want to set up a remote meeting next Tuesday," that information is transmitted to the server via the terminal and processed accordingly.

[0700] For example, if a user enters a prompt into their device such as, "We have a family dinner tonight. Please check for conflicts with other schedules," this information is analyzed by the server and a reminder is generated. In this way, each user can be helped to avoid missing important events and improve their quality of life at home.

[0701] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0702] Step 1:

[0703] The user enters schedule information into the terminal via voice or text. User input is performed through the terminal's microphone or keyboard. The input data includes specific appointments, such as "Remote meeting next Tuesday at 3pm." Based on this, the terminal generates schedule information in digital format and prepares it for transmission to the server.

[0704] Step 2:

[0705] The terminal sends the schedule information received from the user to the server. The data is transmitted using a secure protocol. The input data is the user's schedule information, and the output data is in a format suitable for transmission to the server. The terminal confirms that this process has completed successfully and waits for the data to arrive at the server.

[0706] Step 3:

[0707] When the server receives schedule information, the analysis software processes the data. The input data is schedule information sent from the terminal. The server analyzes the data using a generative AI model and sets priorities. The output is a schedule that has been checked for conflicts and overlaps. Specific operations include checking the time slots of the schedule and verifying that they do not overlap with other appointments.

[0708] Step 4:

[0709] The server generates necessary alerts and reminders based on the analysis results. A generative AI model is involved in this process to produce the most appropriate messages. The output includes reminders and suggestions to be sent to the user. For example, it might perform a specific action such as "send a preparation notification the day before a remote meeting."

[0710] Step 5:

[0711] The device displays reminders and suggestions received from the server to the user. The input data includes notification information sent from the server. The device displays this information as push notifications and on-screen alerts. This allows the user to efficiently manage their schedule. Specific actions include controlling notification sounds and banner displays on the device.

[0712] (Application Example 1)

[0713] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0714] In modern society, managing the schedules and health of elderly individuals places a significant burden on caregivers. To alleviate this burden and provide more efficient and personalized support, a flexible and accurate information management system is necessary. Conventional systems have not fully utilized voice input or compatibility with diverse devices, and have been inadequate in addressing the unique needs of the elderly.

[0715] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0716] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and setting priorities, and means for storing the schedule information in a data storage device and detecting duplicates and conflicts. This makes it possible to identify and manage the schedules and health information of elderly people. By also providing means for registering information on a terminal using voice input and cross-platform compatible communication means, smooth communication between caregivers and those receiving care and personalized health management support can be realized.

[0717] "Schedule information" refers to data representing the user's schedule, including the time and place of planned activities and appointments.

[0718] "Priority" is a criterion used to rank multiple schedules and tasks based on their importance and urgency.

[0719] A "data storage device" is a device for electronically storing information, and includes databases and cloud storage.

[0720] "Duplicate" refers to a situation where multiple schedule entries exist that require the same time or resources.

[0721] "Conflict" refers to a situation where different schedule information interferes with each other, and it is necessary to determine priorities.

[0722] "Recommendations" refer to suggested actions or task options presented to the user based on the analysis results.

[0723] A "terminal" refers to a device used by a user to directly input information or receive notifications from a system.

[0724] "Health information" refers to data that indicates the user's physical condition, including biometric information such as body temperature, blood pressure, and exercise level.

[0725] "Health maintenance and management" is a general term for management activities aimed at keeping users in good health.

[0726] "Elderly people" refers to individuals above a certain age, and usually includes those aged 60 and over.

[0727] "Voice input" is an interface technology that allows users to provide information to a device using their voice.

[0728] "Cross-platform" means that the same application or functionality can be run on different platforms.

[0729] "Communication means" refers to functions and technologies that enable the transmission and reception of information, and includes wired and wireless technologies.

[0730] For this invention to be implemented, the interaction between the server, terminal, and user is crucial. The server utilizes cloud infrastructure to receive and analyze schedule information. The server will be built using Amazon Web Services (AWS), and Amazon S3 will be used for data storage. In addition, the Google Cloud Speech-to-Text API will be used to implement voice input functionality. A cross-platform application will be developed using React Native to support ubiquitous devices.

[0731] The device receives voice and text input from the user and sends it to the server in real time. Real-time data synchronization is performed via Firebase, so schedule entries made by the user are immediately reflected on the server. In addition, schedule reminders and health management suggestions are displayed to the user as push notifications. Firebase Cloud Messaging is used for this purpose.

[0732] Users input their daily activities into their device via voice or text, and their schedules and health-related data are updated accordingly. For example, if a user voice-instructs, "I will take my medicine at 10 AM tomorrow," that information is sent to the server, which checks for conflicts and generates reminders as needed. Furthermore, for seniors, the system can provide appropriate exercise suggestions to support their daily health management. For instance, a push notification might say, "Based on your recent activity log, we suggest a 20-minute walk today."

[0733] As a concrete example, a possible prompt for a generative AI model would be, "Please provide schedule management and health suggestions for tomorrow." Based on this prompt, the AI ​​agent would provide a schedule and health suggestions optimized for the user.

[0734] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0735] Step 1:

[0736] The user inputs schedule information into the device via voice. The device uses the Google Cloud Speech-to-Text API to convert the voice data into text data. The input voice is something like "Take my medicine at 10 AM tomorrow," and the output is generated in text format.

[0737] Step 2:

[0738] The device sends the converted text data to the server in real time via Firebase. The input contains text data, which the server receives and stores in a database as schedule information. The output is the stored schedule information.

[0739] Step 3:

[0740] The server stores the received schedule information in Amazon S3 and simultaneously analyzes that information. The analysis checks for any overlaps with existing schedules and sets priorities. The input is schedule information, and the output provides information on whether there are any conflicts and their priorities.

[0741] Step 4:

[0742] The server generates a reminder based on the analysis results. If there are no conflicts, the generated reminder will be a notification such as "Don't forget to take your medicine at 10 AM tomorrow." The input includes the analysis results, and the output is the generated reminder information.

[0743] Step 5:

[0744] The server uses Firebase Cloud Messaging to push reminders generated to the device. By receiving reminder information as input and sending it to the user's device, the user can receive notifications in real time. The output includes push notifications.

[0745] Step 6:

[0746] The user checks the reminder notification displayed on their device and makes any necessary changes to the schedule or adds health information. This allows for re-entry of the information, which is then sent back to the server from step 1, and processing continues.

[0747] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0748] To implement this invention, a system combining an AI agent with an emotion engine is used. This system provides a comprehensive home management solution that integrates emotion detection and response, in addition to scheduling and health management for all family members. The server, terminals, and users work together to effectively realize the system's functions.

[0749] First, users input their daily schedule information through their device, but this is then combined with an emotion-based element. For example, a user might say in voice, "I'm not really looking forward to tomorrow's meeting, but I'll have to attend." This voice data is analyzed by an emotion engine, which determines that the user may be feeling anxious about the meeting.

[0750] The server analyzes the received schedule information and sentiment data. Meeting priorities are assigned based on the already set schedule, but the content of suggestions and reminders is adjusted as needed, taking into account the sentiment engine's corrections. For example, a reminder might be sent just before a meeting saying, "Take a deep breath before the meeting to help you feel relaxed."

[0751] The device receives reminders and suggestions from the server and notifies the user. The user can use these notifications to adjust their schedule and prepare themselves mentally. Emotional data is also used to improve communication within the family. For example, if a family member is feeling stressed, a supportive message tailored to that situation will automatically appear on the device.

[0752] Thus, this invention provides a system that improves the quality of life for families by utilizing an emotion engine to not only manage schedules but also to provide support that is tailored to each individual's emotional state. This emotion-responsive function enables detailed support that is suited to each individual's situation and contributes to the overall improvement of the home environment.

[0753] The following describes the processing flow.

[0754] Step 1:

[0755] The user inputs schedule information using voice or text via a device. The device receives the input information, converts the voice data into text, and prepares it for analysis by an emotion engine.

[0756] Step 2:

[0757] The device sends emotional information extracted from voice and text to the server. At this time, schedule information and emotional data are sent together.

[0758] Step 3:

[0759] The server analyzes the received schedule information and uses natural language processing techniques to extract details such as the date, time, and event name. The emotion engine also analyzes the emotion data and evaluates the user's emotional state.

[0760] Step 4:

[0761] The server stores schedule information in a database and sets schedule priorities. It also takes emotional states into consideration and adjusts priorities as needed.

[0762] Step 5:

[0763] The server generates optimal reminders and suggestions based on schedule information and sentiment analysis. It creates appropriate support messages tailored to the user's emotions and incorporates them into the reminders.

[0764] Step 6:

[0765] Reminders and suggestions generated by the server are sent to the device. The device receives them and provides them to the user as visual or auditory notifications.

[0766] Step 7:

[0767] Users can review received reminders and emotionally-driven suggestions and take action based on them. They can also adjust their schedules if necessary.

[0768] Step 8:

[0769] To support communication among family members, an emotion-based messaging function is utilized on the device. Messages are automatically generated and displayed on the device according to the family's stress levels and emotional state.

[0770] Through these steps, a system is created that integrates and manages emotions and schedules, providing appropriate support.

[0771] (Example 2)

[0772] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0773] In today's family environment, managing each member's schedule and health has become a crucial issue. Furthermore, it is necessary to appropriately understand emotional fluctuations and mental states, and to promote smooth communication among family members. However, managing and supporting these aspects individually is burdensome and inefficient. Therefore, there is a need for a system that provides emotionally-based support in addition to schedule and health management, thereby improving the quality of life for families.

[0774] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0775] In this invention, the server includes means for receiving schedule information, means for analyzing the received schedule information and emotional data, setting priorities and adjusting them, and means for detecting the emotional state of family members and generating messages to facilitate communication among family members. This makes it possible to improve the overall quality of life for the family by effectively managing the family's schedule and health and providing emotional support.

[0776] "Schedule information" refers to time-based information such as appointments, tasks, and events related to an individual or group.

[0777] "Emotional analysis" is the process of analyzing voice and text data to determine the user's emotional state.

[0778] A "reminder" is an alert or notification that alerts users to appointments or tasks that are easily forgotten.

[0779] A "suggestion" is a recommendation of actions or advice provided based on the user's schedule and status.

[0780] A "database" is an information storage system that allows for the systematic management and access of digital data as needed.

[0781] "Health information" refers to data that indicates an individual's health status, including, for example, heart rate, sleep duration, and stress level.

[0782] A "message" is a written or electronic means of communication used to transmit information.

[0783] A "learning algorithm" is a computational method that finds patterns and rules from past data and applies them to new data to make predictions and classifications.

[0784] This invention provides a system that integrates household schedule management, health management, and emotional support. The components necessary to implement this include a server, terminals, an emotion engine, and a database. Specific examples using these elements are described below.

[0785] The server operates on a cloud-based platform. The server receives schedule information sent from users via their devices. These devices are smartphones and tablets, and they use voice input to send information about the user's daily schedule and emotions to the server.

[0786] The server uses existing natural language processing APIs as its sentiment engine to analyze this audio data. For example, Google Cloud's Natural Language API is used. This API analyzes audio and text data and generates sentiment scores and categories.

[0787] The analyzed emotional data is integrated with schedule information by the server. Based on this, the server prioritizes daily appointments and generates reminders and suggestions as needed. The server also uses the emotional data to send appropriate messages to facilitate communication among family members.

[0788] For example, if a user voice-inputs, "I'm not really looking forward to tomorrow's meeting, but I'll attend," the system's emotion engine will analyze that the user is anxious about the meeting and generate a suggestion such as, "Try taking a deep breath before the meeting so you can approach it feeling more relaxed."

[0789] An example of a prompt for a generative AI model might be, "Please provide ideas for using the emotion engine to detect the user's emotional state and suggest specific actions." This prompt is used by the generative AI model when developing new features.

[0790] Through these means, the system of the present invention can improve the quality of life for families and provide detailed support tailored to individual schedules and emotional states.

[0791] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0792] Step 1:

[0793] The user uses their device to perform voice input. This input includes schedule information and the user's emotions. Specifically, the user uses their smartphone's voice input function to say, "I'm not really looking forward to it, but I'll attend the meeting tomorrow." This voice data is recorded on the device.

[0794] Step 2:

[0795] The terminal converts recorded audio data into text and sends it to the server. The input is audio data, and the output is text data. The terminal uses speech recognition technology to perform this conversion, and the result is sent to the server via the network.

[0796] Step 3:

[0797] The server passes the received text data to the sentiment engine, which then performs sentiment analysis. The input is text data, and the output is sentiment scores or categories. The server calls a natural language processing API to obtain numerical data representing the emotional state.

[0798] Step 4:

[0799] The server integrates the sentiment analysis results into the schedule information and resets priorities. The input is existing schedule data and sentiment data, and the output is a priority-adjusted schedule. The server accesses the database and updates the task rankings, taking priorities into account.

[0800] Step 5:

[0801] The server generates reminders and suggestions based on emotional data. The input is a prioritized schedule, and the output is a message containing a specific action. For example, a suggestion might be generated: "Take a deep breath before the meeting to help you feel relaxed."

[0802] Step 6:

[0803] The server sends generated reminders and suggestions to the terminal. The input is message data, and the output is a notification to the terminal. The server dispatches the notification to the terminal via a communication method.

[0804] Step 7:

[0805] The terminal displays notifications received from the server to the user. Input is received data, and output is a visual or auditory notification to the user. The terminal displays messages on the screen and provides alerts to the user through sound or vibration.

[0806] (Application Example 2)

[0807] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0808] In modern households, managing family schedules and health has become increasingly complex, and there is a need for lifestyle support that is tailored to each individual's mental state. However, conventional technologies have made it difficult to address these issues comprehensively. Furthermore, there is a lack of means to facilitate communication among family members and improve their quality of life.

[0809] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0810] In this invention, the server includes means for receiving schedule information, means for analyzing emotions from voice data and generating suggestions according to the user's emotional state, and means for providing emotion-based feedback and suggestions via an operating device. This makes it possible to manage the schedules and health of the entire family, provide individual suggestions and support based on emotional states, and facilitate communication among family members.

[0811] "Schedule information" refers to data related to daily appointments and events, and is used for planning and managing individual and group activities.

[0812] "Priority" refers to the ranking of the importance and urgency of performing multiple tasks or appointments.

[0813] A "database" is a system that systematically stores and manages various types of data and information, making it easy to access and manipulate.

[0814] "Overlap or conflict" refers to a situation where multiple appointments or tasks exist that are allocated to the same time or resources.

[0815] A "reminder" is a feature that notifies users based on specific times or conditions to remind them of tasks or appointments.

[0816] "Health information" refers to data about an individual's health status, used to assess their physical and mental condition.

[0817] "Audio data" refers to data that records audio signals, and it forms the basis for the analysis and recognition of acoustic information.

[0818] "Emotional analysis" is the process of evaluating and identifying an individual's emotional state from voice and behavioral data.

[0819] "Operational devices" refer to equipment or devices that control physical movement and provide users with an interactive experience.

[0820] "Feedback" refers to information returned as a response to an action or input, providing an appropriate response depending on the user's actions and state.

[0821] This system analyzes the user's emotional state based on their schedule and health information to improve their quality of life at home, and provides appropriate feedback and suggestions. Specifically, the server, terminal, and user work together to perform the following processes.

[0822] The server receives voice data input from the user and analyzes the user's emotions using speech recognition technology and a generative AI model for sentiment analysis (e.g., Google Cloud's Natural Language API). The analyzed sentiment data is stored in a database along with schedule information and health data. Based on this information, the server generates reminders and suggestions tailored to the user's current state and sends them to the device.

[0823] The device notifies the user of reminders and suggestions received from the server. Notifications are sent via a smartphone or a home device (e.g., a home robot), allowing the user to adjust their schedule and prepare themselves accordingly.

[0824] Based on the suggestions received, users can improve their lifestyle habits and enhance communication within their families. As a concrete example of this system, if an elementary school child comes home from school and says, "I'm too tired to do my homework today," the robot will sense this and suggest, "Why don't you take a 15-minute break before starting your homework?"

[0825] Examples of prompts for the generating AI model include, "Assuming the user is feeling anxious, please give advice on preparing for tomorrow's meeting," and "If a child is complaining of fatigue, please generate advice to encourage relaxation." In this way, the system aims to comprehensively improve the quality of life by addressing the emotional needs of the entire family.

[0826] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0827] Step 1:

[0828] The server receives audio data from the user. This input data contains the user's speech. Speech recognition software is used to convert this data into text. Once the audio-to-text conversion is complete, the data is passed on to sentiment analysis.

[0829] Step 2:

[0830] The server uses a generative AI model to analyze the user's emotions from text data. The input contains converted text data, which the emotion analysis engine processes to obtain an output in the form of an emotional state (e.g., "anxiety" or "fatigue"). This emotional state is the information needed for subsequent processing.

[0831] Step 3:

[0832] The server combines analyzed emotional states with pre-registered schedule information to generate appropriate reminders and suggestions. This input data includes emotional states and schedule information. Based on this, the server determines what kind of support the user needs and generates a corresponding message.

[0833] Step 4:

[0834] The device receives reminders and suggestions sent from the server and notifies the user. The input for this step is the message provided by the server. The notification function is activated on the device, and as a concrete action, the user receives a visual or audible notification.

[0835] Step 5:

[0836] Users review notifications and suggestions received through their devices to help adjust their lives and improve their emotions. The output in this step represents the results of users actually adjusting their behavior based on the suggestions. This is a specific step in which users receive notifications from their devices and decide how to change their behavior.

[0837] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0838] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0839] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0840] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0841] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0842] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0843] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0844] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0845] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0846] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0847] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0848] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0849] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0850] 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.

[0851] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0852] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0853] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0854] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0855] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0856] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0857] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0858] The following is further disclosed regarding the embodiments described above.

[0859] (Claim 1)

[0860] A means of receiving schedule information,

[0861] A means of analyzing received schedule information and setting priorities,

[0862] A means of storing schedule information in a database and detecting duplicates and conflicts,

[0863] A means for generating reminders and suggestions based on schedule information,

[0864] A means of notifying the device of reminders and suggestions,

[0865] A means of collecting health information and generating suggestions regarding health management,

[0866] A system that includes this.

[0867] (Claim 2)

[0868] The system according to claim 1, which provides a messaging function to support communication among family members.

[0869] (Claim 3)

[0870] The system according to claim 1, which uses a learning algorithm to learn user preferences and tendencies from past data and customizes suggestions.

[0871] "Example 1"

[0872] (Claim 1)

[0873] A means of receiving schedule information,

[0874] A means of analyzing received schedule information and setting priorities,

[0875] A means for storing schedule information in a storage device and detecting duplication and conflicts,

[0876] A means for generating reminders and suggestions based on schedule information,

[0877] A means of notifying the device of reminders and suggestions,

[0878] A means of collecting health indicators and generating suggestions for health management,

[0879] A means of creating optimal notification messages using a generative AI model,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, which provides a communication function to support communication within the household.

[0883] (Claim 3)

[0884] The system according to claim 1, which learns the user's preferences and tendencies from past data using a learning algorithm and personalizes suggestions.

[0885] "Application Example 1"

[0886] (Claim 1)

[0887] A means of receiving schedule information,

[0888] A means of analyzing received schedule information and setting priorities,

[0889] A means for storing schedule information in a data storage device and detecting duplication and conflicts,

[0890] A means for generating reminders and recommendations based on schedule information,

[0891] A means of notifying the device of reminders and recommendations,

[0892] A means of collecting health information and generating recommendations for health maintenance and management,

[0893] A means of identifying and managing the schedules and health information of the elderly,

[0894] A method for registering information on a terminal using voice input,

[0895] A means of providing cross-platform communication methods,

[0896] A system that includes this.

[0897] (Claim 2)

[0898] The system according to claim 1, which provides a communication function to support communication between a caregiver and a person receiving care.

[0899] (Claim 3)

[0900] The system according to claim 1, which uses a learning method to analyze the user's preferences and tendencies from past information and personalizes the suggestions.

[0901] "Example 2 of combining an emotion engine"

[0902] (Claim 1)

[0903] A means of receiving schedule information,

[0904] A means of analyzing received schedule information and setting priorities,

[0905] A means of storing schedule information in a database and detecting duplicates and conflicts,

[0906] A means for generating reminders and suggestions based on schedule information,

[0907] A means of notifying the device of reminders and suggestions,

[0908] A means of collecting health information and generating suggestions regarding health management,

[0909] A means of performing emotion analysis and adjusting schedules and proposals based on the results,

[0910] A means for detecting the emotional state of family members and generating messages to promote communication among family members,

[0911] A system that includes this.

[0912] (Claim 2)

[0913] The system according to claim 1, which provides a messaging function to support communication among family members.

[0914] (Claim 3)

[0915] The system according to claim 1, which uses a learning algorithm to learn user preferences and tendencies from past data and customizes suggestions.

[0916] "Application example 2 when combining with an emotional engine"

[0917] (Claim 1)

[0918] A means of receiving schedule information,

[0919] A means of analyzing received schedule information and setting priorities,

[0920] A means of storing schedule information in a database and detecting duplicates and conflicts,

[0921] A means for generating reminders and suggestions based on schedule information,

[0922] A means of notifying the device of reminders and suggestions,

[0923] A means of collecting health information and generating suggestions regarding health management,

[0924] A means for analyzing emotions from voice data and generating suggestions tailored to the user's emotional state,

[0925] A means of generating messages that improve communication among family members using emotional data,

[0926] A means of providing emotion-based feedback and suggestions via an operating device,

[0927] A system that includes this.

[0928] (Claim 2)

[0929] The system according to claim 1, which provides a messaging function to support communication among family members.

[0930] (Claim 3)

[0931] The system according to claim 1, which uses a learning algorithm to learn user preferences and tendencies from past data and customizes suggestions. [Explanation of symbols]

[0932] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving schedule information, A means of analyzing received schedule information and setting priorities, A means of storing schedule information in a database and detecting duplicates and conflicts, A means for generating reminders and suggestions based on schedule information, A means of notifying the device of reminders and suggestions, A means of collecting health information and generating suggestions regarding health management, A system that includes this.

2. The system according to claim 1, which provides a messaging function to support communication among family members.

3. The system according to claim 1, which uses a learning algorithm to learn user preferences and tendencies from past data and customizes suggestions.

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