system

Abstract

We provide the system. [Solution] A means for collecting schedule information using data communication means, A means for analyzing the aforementioned schedule information to detect duplication and inconsistencies, A means to automatically optimize the schedule based on priority, Means for obtaining weather information and considering factors that may affect the schedule, A means of automatically contacting the operating organization and coordinating the schedule, A means of notifying users and collecting feedback, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, the schedule management of children's cram schools and hobbies has required parents to do it manually, and there have been problems such as frequent schedule overlaps and mistakes. In addition, it has been difficult to flexibly adjust the schedule according to the weather and the situation of the operating institution, which has been a great burden on parents. Furthermore, since there has been no appropriate system for efficiently managing such schedules, parents have had to manage them themselves, depriving them of mental and time leeway.

Means for Solving the Problems

[0005] This invention provides a system that uses data communication to collect schedule information, analyzes that information, and automatically detects duplicates and inconsistencies. Based on the collected data, it automatically optimizes the schedule considering priorities, and further determines the impact on the schedule by referring to weather information. In addition, it automates communication with the operating organization to quickly make necessary adjustments. Furthermore, by building a mechanism to obtain feedback through notifications to users, it reduces the burden on parents, improves the accuracy of schedules, and provides a means to provide an optimal learning environment for children.

[0006] "Data communication methods" is a general term for technologies and protocols used to collect, send, and receive various types of digital information from external services and systems via the internet.

[0007] "Schedule information" refers to detailed data about schedules related to time and place, such as cram school, extracurricular activities, school events, and family events.

[0008] "Analysis" is the process of examining and analyzing information based on collected data in order to understand the information and identify problems and patterns.

[0009] "Duplicate or contradictory" refers to scheduling inconsistencies where multiple appointments are set at the same time, or where one of the appointments cannot be carried out.

[0010] "Automatic schedule optimization" is a process that uses information technology to efficiently rearrange and adjust appointments based on pre-set priorities and external conditions.

[0011] "Weather information" refers to data related to meteorological conditions, such as weather forecasts, temperature, precipitation, and wind speed, and is particularly relevant to outdoor activities.

[0012] "Operating organization" refers to organizations that provide various educational and activity-related services, such as cram schools, extracurricular activity organizers, and schools.

[0013] "Automation" refers to setting up systems or machines to independently perform certain tasks or processes without human intervention.

[0014] "Notifications" refer to messages and alerts used to convey important information and reminders to users.

[0015] "Feedback" refers to information provided by users, including opinions, evaluations, and suggestions for improvement, which are useful for improving and adjusting the system. [Brief explanation of the drawing]

[0016] [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] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when 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.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] 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.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention provides a schedule management system that reduces the burden on users and smoothly supports children's activities. Specifically, it is a system that collects schedule information from various sources using data communication means, analyzes it, and performs an optimization process.

[0038] Users can input information about their household schedules and children's extracurricular activities using a dedicated application on their device. This information is sent to a server where it is integrated. The server also collects schedule information from external calendar services and educational institutions via APIs and aggregates this information in one place.

[0039] The server analyzes the collected data to detect duplicate appointments and inconsistencies. An AI agent then optimizes the schedule based on historical data, taking appointment priorities into consideration. Furthermore, it includes a function to acquire weather forecast data and suggest adjustments to mitigate potential impacts on outdoor activities.

[0040] For example, when a user registers the date of their child's sports day, the server checks the weather forecast and, if it detects a possibility of bad weather on the day, automatically suggests alternative dates and notifies the organizing body. If communication with the organizing body is possible, it then uses an API to propose a rescheduled date and automatically submits the application.

[0041] Regarding notifications, the device will send push notifications to the user with the most relevant information related to their schedule. This includes event details, packing lists, and weather-related changes. Users can also provide feedback through the app, and this information is collected on the server and used to optimize future events.

[0042] By combining these functions, the system can reduce the management burden on users and improve the accuracy of schedules, thereby efficiently creating an environment that supports children's learning and experiences.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The server periodically collects data from external calendar services and educational institutions using APIs. It also obtains new schedule information via email and notifications.

[0046] Step 2:

[0047] The terminal provides an interface for users to input information about household schedules and children's extracurricular activities. Users input this information through this interface, and the terminal transmits it to the server.

[0048] Step 3:

[0049] The server integrates all collected schedule information and stores it in a database. Next, it analyzes this information to detect events occurring at the same time or conflicting schedules.

[0050] Step 4:

[0051] The server prioritizes and automatically optimizes schedules based on schedule data analyzed using an AI agent. This includes calculating the optimal placement to maximize the efficiency of children's learning and activities.

[0052] Step 5:

[0053] The server uses a weather forecast API to retrieve weather data for the near future, assesses its impact on planned activities, especially those involving outdoor activities, and develops adjustment plans.

[0054] Step 6:

[0055] The server automatically contacts the operating organization according to pre-configured conditions and initiates transfer or cancellation procedures if necessary. It responds quickly using APIs and email.

[0056] Step 7:

[0057] The device notifies the user of an optimized schedule and provides important information such as what to bring and important points via push notifications. The user can then make the necessary preparations based on this information.

[0058] Step 8:

[0059] Users provide feedback on the provided schedule through a terminal app, and this information is sent to the server. The server collects user feedback and uses it to optimize the AI ​​agent for future improvements.

[0060] (Example 1)

[0061] 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."

[0062] In modern households, managing children's diverse activities and events is a significant burden for parents. In particular, overlapping schedules, schedule changes due to weather, and coordination with external organizations are time-consuming and require efficient management. Furthermore, comprehensively managing all this information and creating an efficient schedule is difficult.

[0063] 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.

[0064] In this invention, the server includes means for aggregating schedule information using digital communication technology, means for analyzing the schedule information and identifying duplicates and inconsistencies, and means for automatically optimizing the schedule based on priority. This reduces the management burden on users and enables the setting of an optimal schedule.

[0065] "Digital communication technology" refers to technologies that transmit information electrically or electronically, and is a means of enabling the collection and transmission of scheduled information.

[0066] "Means for aggregating schedule information" refers to methods and technologies for organizing, integrating, and centrally managing schedule-related information obtained from multiple sources.

[0067] "Methods for analyzing schedule information and identifying overlaps and inconsistencies" refers to technologies that analyze aggregated schedule information to detect cases where the same or different schedules overlap.

[0068] "A method for automatically optimizing schedules based on priority" refers to a technology that evaluates the importance and urgency of each appointment and generates an efficient schedule based on that information.

[0069] "Means of acquiring weather data and considering factors that affect activities" refers to methods of collecting weather information and using that information to provide information on the impact on plans and alternative options.

[0070] "A means of automatically contacting the operating organization and adjusting the schedule" refers to technology that communicates with the organization and, if necessary, automatically proposes or confirms schedule changes.

[0071] "Means of notifying users of information and collecting feedback" refers to methods of notifying users of the latest information and changes through their devices and collecting the feedback received.

[0072] "A means by which users input information using a terminal" refers to an interface that allows users to directly input schedules and other related information via a device.

[0073] "A method of using AI models to propose optimizations based on past information" refers to a method that utilizes artificial intelligence technology to analyze data accumulated in the past and generate proposals to optimize future schedules.

[0074] This invention is a schedule management system designed to streamline family management. The system is primarily implemented through the exchange of information via a server, terminals, and users.

[0075] The server utilizes digital communication technology to aggregate schedule information from diverse sources. For example, it not only collects household schedule information entered by users on their devices, but also retrieves information from external systems such as calendars and event management services via APIs. The server analyzes the aggregated information and automatically detects schedule overlaps and inconsistencies.

[0076] Next, the server optimizes the schedule based on priority. It utilizes an AI model to compare with past data and propose the optimal schedule. Specifically, it evaluates the priority and importance of extracurricular activities and family events, and adjusts the schedule accordingly.

[0077] Furthermore, the server acquires weather data and takes into account weather factors that may affect the schedule. For example, if the date of an outdoor activity needs to be changed due to weather, it can automatically propose alternative dates and automatically contact the organizing body.

[0078] The device notifies the user of the latest information and sends push notifications as needed. Users can easily check appointment details and provide feedback using the device. This feedback is collected on the server and used to optimize future schedules.

[0079] For example, if a user enters the date of their child's sports day via their device, the server will compare it with the weather forecast and proactively suggest alternative dates in case of rain, then contact the organizing body. An example of a prompt might be, "Please show me how to automatically notify me of an alternative date if it rains on my child's sports day."

[0080] With the above configuration, the present invention can reduce the management burden on users and achieve effective schedule management.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] Users use a dedicated application on their device to input information about family schedules and their children's extracurricular activities. Specific inputs include the event name, date and time, location, and necessary items. The entered information is sent directly from the device to the server. The server records this information in a database, preparing it for subsequent processing.

[0084] Step 2:

[0085] The server collects additional schedule information through external calendar services and educational institution APIs. It sends API requests and retrieves information in a defined format. The data obtained from the APIs is transformed, organized, and integrated into existing databases. This ensures that accurate information is aggregated in real time.

[0086] Step 3:

[0087] The server analyzes the aggregated schedule information. This analysis checks for duplicate or inconsistent schedules and identifies them if found. Specifically, if there are different schedules at the same time, the server compiles them into a list and prepares to notify the user. The analysis results are stored in an internal log.

[0088] Step 4:

[0089] The server optimizes the schedule by considering priority. Based on the input information and aggregated data, the AI ​​agent refers to past data and proposes the most efficient schedule while evaluating the priority of each appointment. The AI ​​model enables rapid schedule creation. This proposal is stored within the system and used for subsequent notifications.

[0090] Step 5:

[0091] The server retrieves weather data using a weather forecast API. This retrieves information such as the forecasted weather, temperature, and probability of precipitation. The retrieved data is used to determine whether adjustments are necessary, especially for outdoor activities. A weather-based adjustment plan is generated, and the schedule is readjusted as needed.

[0092] Step 6:

[0093] The server will automatically contact the operating organization if necessary to have them consider the proposed adjustments. This contact will be made via API or email, automating the confirmation of transfer dates and other details. The response from the operating organization will be fed back into the next step.

[0094] Step 7:

[0095] The device receives organized information from the server and notifies the user via push notification. The notification includes details such as the latest event status, changes, and important notes. Users can also submit feedback, which the device sends back to the server to be used for optimizing future schedules.

[0096] (Application Example 1)

[0097] 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."

[0098] In modern society, managing household schedules and coordinating children's activity schedules requires considerable time and effort, and is particularly burdensome for working parents. Furthermore, information sharing to quickly respond to schedule changes due to weather or external factors is often inefficient. Under these circumstances, there is a need for efficient schedule management and smooth support for children's activities.

[0099] 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.

[0100] In this invention, the server includes means for collecting schedule information using data communication means, means for analyzing the schedule information to detect duplication and inconsistencies, means for automatically optimizing the schedule based on priority, means for acquiring weather information and considering factors that affect the schedule, means for automatically contacting the operating organization and adjusting the schedule, means for notifying the user and collecting feedback, and means for providing information according to the situation in the physical environment using physical machines for supporting human life. This reduces the burden on the user and enables efficient schedule management that smoothly supports children's activities.

[0101] "Data communication methods" is a general term for communication technologies and protocols used to collect scheduled information from external sources.

[0102] "Means for analyzing schedule information to detect duplication and inconsistencies" refers to a function that analyzes collected schedule data to find duplication and inconsistencies in its content.

[0103] "Automatically optimizing schedules based on priority" refers to a function that creates the most efficient schedule according to the importance and priority of each appointment.

[0104] "Means of acquiring weather information and considering factors that affect the schedule" refers to a function that uses weather data to make adjustments in order to minimize the impact of weather on the schedule.

[0105] "A means of automatically contacting the operating organization and adjusting the schedule" refers to a function that automatically contacts the relevant organizations and institutions and adjusts the schedule when changes to the schedule are necessary.

[0106] "Means of notifying users and collecting feedback" refers to functions that send push notifications and alerts to users and collect their opinions and responses.

[0107] "Means of providing information in accordance with the situation in the physical environment using physical machines for human life support" refers to functions that provide information based on the real environment using robots and assistant devices to support people's lives.

[0108] One embodiment of this invention is an integrated system for streamlining household schedule management and supporting children's daily activities. The server collects schedule information entered by users using data communication means. This includes household schedule information collected via a dedicated application on a smartphone or tablet. Furthermore, it obtains calendar information from external services and schedule information from educational institutions via APIs.

[0109] The server analyzes the collected schedule information to detect duplicates and inconsistencies. Using machine learning algorithms, it optimizes the schedule based on past data and user feedback. This process ensures effective schedule adjustments according to priority and importance.

[0110] Furthermore, the server acquires weather information and makes suggestions considering the impact of weather on the schedule. For example, in the case of outdoor activities, if bad weather is predicted, it can suggest a backup date and automatically contact the organizing body via API to adjust the schedule.

[0111] The device sends push notifications to the user, containing schedule updates and changes, lists of necessary preparations, and alerts about weather-related changes. Users can provide feedback, which will be used to optimize future services.

[0112] The server has the function of providing information tailored to the physical living environment, for example, using a robot designed to support human life. This robot presents appropriate information to the user in real time via voice and display.

[0113] As a concrete example, if a child's school trip is postponed due to rain, the system will suggest alternative dates and send a push notification to the parent's device. An example of a prompt message would be, "Your child's school trip this weekend has been postponed due to rain. Please suggest possible alternative dates."

[0114] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0115] Step 1:

[0116] The server collects schedule information from users using data communication methods. Schedules entered by users via a dedicated application on smartphones or tablets are sent to the server. This input information is received by the server as JSON data.

[0117] Step 2:

[0118] The server uses external APIs to retrieve additional appointment information from external calendar services and educational institutions. This information retrieved through the APIs is stored in an integrated data store, ensuring consistency between internal and external data.

[0119] Step 3:

[0120] The server analyzes the collected schedule information and detects duplicates and inconsistencies. For each entered schedule, it applies an algorithm that matches it using a specific identifier to detect duplicate items and conflicts. The output is formatted so that the analysis results can be used to improve scheduling.

[0121] Step 4:

[0122] The server uses machine learning algorithms to optimize the schedule. It adjusts the schedule according to priority, taking into account historical data and feedback. The resulting optimization becomes the basis data for the next calculation step.

[0123] Step 5:

[0124] The server retrieves weather information from external sources and evaluates factors that may affect the schedule. It analyzes the weather data and incorporates it as a variable to consider rescheduling activities if there is a possibility of impact on outdoor activities.

[0125] Step 6:

[0126] The server automatically contacts the operating organization as needed to adjust the schedule. Using the API, it proposes new dates based on weather and internal requirements. This confirms the adjustment of the plan and generates detailed contact information.

[0127] Step 7:

[0128] The device sends push notifications to the user regarding schedule changes and important information. The generated notification information is delivered to the device, allowing the user to stay informed of necessary information in real time.

[0129] Step 8:

[0130] The user reviews the notification and sends feedback to the server. The feedback information is then stored again in the database on the server and referenced for future schedule optimizations.

[0131] 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.

[0132] This invention provides a schedule management system that takes user emotions into account. By combining it with an emotion engine, it can meet more sophisticated user needs than conventional systems.

[0133] First, the user enters their schedule information via a dedicated application on their device. In the background of this input screen, an emotion engine analyzes data obtained from the user interface, evaluating the user's emotions in real time. For example, it determines whether the user is stressed or relaxed based on factors such as input speed, input content, and even idle time.

[0134] The server continuously collects schedule information using external calendar services and educational institution APIs, while simultaneously receiving user sentiment data sent from the device, and integrates all the data. This not only detects schedule overlaps and inconsistencies, but also enables prioritization that reflects the user's current sentiment state.

[0135] Furthermore, the server uses an AI agent to automatically optimize the schedule based on the collected data. In this process, it also takes into account the user's emotional data recognized by the emotion engine, and takes care not to overschedule the user during times when they are likely to feel stressed. Notifications are also adjusted based on the user's emotional state. For example, when the user is relaxed, new notifications are sent in a gentle tone, while when the user is stressed, the system avoids sending many notifications in a short period of time.

[0136] For example, if a user receives multiple notifications during a busy day, the emotion engine will detect that their stress levels are high and adjust the server to omit non-urgent notifications and deliver them all together later.

[0137] The emotion engine analyzes the user's emotions during feedback, and the AI ​​agent uses this data to improve future schedule optimization processes. This gives the system the ability to continuously improve the user experience and provide personalized schedule management.

[0138] Thus, by incorporating an emotion engine, this invention enables advanced schedule management that responds to the user's actual emotions, providing a richer learning and activity environment.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] Users enter new appointments using a dedicated application on their device. During this process, an emotion engine operates in the background, analyzing input speed, tone, and writing style to evaluate the user's emotional state in real time. The evaluation results are generated on the device as parameters such as stress, satisfaction, and anxiety.

[0142] Step 2:

[0143] The terminal sends the entered schedule information and sentiment data to the server. The server simultaneously collects schedule information from multiple external services and integrates and stores it in a database. The information is sorted by priority and time, and sentiment data is also recorded in association with it.

[0144] Step 3:

[0145] The server analyzes the schedule information collected using an AI agent to check for duplicates or inconsistencies. If detected, the AI ​​agent prioritizes events based on sentiment data to minimize user stress. It also refers to weather information and considers alternatives if outdoor events are expected to be affected.

[0146] Step 4:

[0147] The server configures notifications based on the optimization schedule created. Here, it utilizes parameters detected by the emotion engine to determine the optimal timing for receiving notifications. For example, if a user is stressed, the frequency of notifications is reduced and they are all sent at once.

[0148] Step 5:

[0149] The device delivers optimized schedules and tailored notifications to the user. Users can use the device's feedback interface to provide information about their actual experience and feelings. This feedback includes a wide range of factors, such as the appropriateness of notifications and satisfaction with the schedule.

[0150] Step 6:

[0151] The server incorporates user feedback and sentiment data into the AI ​​agent, which is then used to optimize future schedules. This allows the system to continuously learn and improve, enabling it to provide a more personalized user experience.

[0152] (Example 2)

[0153] 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".

[0154] Conventional schedule management systems have difficulty considering the emotional state of users, and do not adequately respond to users' stress levels or relaxation states. As a result, they cannot present schedules that are optimal for users' lives and work, which hinders the improvement of the user experience.

[0155] 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.

[0156] In this invention, the server includes means for collecting user schedule information using data communication means, means for analyzing the schedule information and emotional information to detect overlaps and inconsistencies, and means for automatically optimizing the schedule based on emotional information and priority. This enables flexible schedule management tailored to the user's emotional state.

[0157] "Data communication means" refers to communication technology used to send and receive user schedule information to and from a server, and involves data transmission via the internet or local network.

[0158] "Emotional information" refers to data that indicates the user's psychological and emotional state, and includes information obtained from factors such as input speed and idle time.

[0159] "Automatic schedule optimization" refers to the process of efficiently and appropriately organizing a user's schedule, taking into account priorities and emotional information.

[0160] "Weather information" refers to data that indicates weather conditions that may affect the execution of planned activities, and is obtained from weather forecasts and other sources.

[0161] "Operating organization" refers to an external organization or service provider involved in the user's schedule, and is the entity responsible for changing or adjusting the schedule.

[0162] "Notifications" refer to messages that inform users of schedules and related important information, and are provided by voice, text, or other means.

[0163] A "machine learning algorithm" is a mathematical method for efficiently performing analysis and prediction using past data and feedback.

[0164] "External systems" refer to external computer systems or services that interact with the system to retrieve or synchronize the user's schedule information.

[0165] To implement this invention, the user first inputs their schedule information using a dedicated application on their device. An emotion engine operates on the device, analyzing the user's emotional information from the speed and content of keyboard input, as well as the idle time. The hardware used is a general-purpose computer or smartphone, and the software includes an emotion engine module for performing emotion analysis.

[0166] The server collects user sentiment information sent from terminals via data communication methods and retrieves schedule information through interfaces with external calendar services and educational systems. The collected data is stored in a database, where it is processed to detect schedule overlaps and inconsistencies. The server is equipped with an AI agent that uses machine learning algorithms to optimize schedules based on past data and feedback.

[0167] Specifically, if the server detects that a user is under high stress during a busy period, it will refrain from sending non-urgent notifications and adjust its distribution to deliver them in bulk at an appropriate time. Furthermore, in its automatic schedule optimization, it selects times when users are less likely to experience stress and schedules appointments accordingly.

[0168] An example of a prompt message would be, "Please suggest the optimal notification schedule when the user is in a high-stress state." This instruction would be sent to the AI ​​model to generate an appropriate scheduling pattern.

[0169] This system allows users to enjoy personalized schedule management tailored to their individual emotional state, enabling them to live a less stressful and more efficient life.

[0170] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0171] Step 1:

[0172] The user enters their schedule information into a dedicated application on their device.

[0173] Specific operation: The user enters the title, date, time, and location of the appointment into text boxes on the application screen and clicks the submit button.

[0174] Input and Output: In this process, the input is text data entered by the user, and the output is schedule information stored in a temporary database on the terminal.

[0175] Step 2:

[0176] The device analyzes emotional data based on factors such as input speed and idle time.

[0177] Specific operation: The device uses an emotion engine to measure keyboard input speed and the amount of time the user spends looking at the screen. Based on this, it infers the user's emotional state.

[0178] Input and Output: The input consists of keyboard usage and elapsed time. Based on this, the data is analyzed, and the output is data indicating the user's emotional state.

[0179] Step 3:

[0180] The device sends the analyzed emotion data and schedule information to the server.

[0181] Specific operation: The device uploads data to the server via the internet.

[0182] Input and Output: The input is a set of emotion data and schedule information, and the output is a confirmation message indicating whether the data was successfully delivered to the server.

[0183] Step 4:

[0184] The server stores the received data and collects information about additional planned data from external systems.

[0185] Specific operation: The server stores sentiment data and schedule information in the database and calls an external API to retrieve further schedule information.

[0186] Input and Output: Input consists of data submitted by users and schedule information from external systems, while output is an integrated schedule information database.

[0187] Step 5:

[0188] The server automatically optimizes the schedule based on the collected data.

[0189] Specific operation: The server's AI agent applies machine learning algorithms and reorganizes the schedule, taking sentiment data into consideration.

[0190] Input and Output: Input consists of integrated database information and historical feedback, while output consists of optimized scheduling information.

[0191] Step 6:

[0192] The server adjusts notifications to the user based on their emotional state.

[0193] Specific operation: When the server suspects that the user is in a high-stress state, it performs a process to change the timing and content of notifications.

[0194] Input and Output: The input is the user's current emotional state data, and the output is a personalized notification message based on a schedule.

[0195] By using a generative AI model at each step, flexible and efficient scheduling is achieved.

[0196] (Application Example 2)

[0197] 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".

[0198] Traditional schedule management systems automatically optimize schedules without considering user emotions, often failing to address situations that cause stress or mental strain. Therefore, there is a need to improve the convenience of schedule management and make adjustments based on the user's emotional state.

[0199] 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.

[0200] In this invention, the server includes means for collecting schedule information using data communication means, means for analyzing the schedule information to detect duplication and inconsistencies, means for automatically optimizing the schedule based on priority, means for acquiring weather information and considering factors that affect the schedule, means for automatically contacting the operating organization and adjusting the schedule, means for notifying the user and collecting feedback, and means for performing schedule optimization and notification adjustment using an emotion engine that analyzes the user's emotional state. This makes it possible to adjust the schedule based on the stress level and emotional state felt by the user.

[0201] A "data communication means" is an interface for sending and receiving data over a network.

[0202] "Schedule information" refers to data related to the schedule entered by the user.

[0203] "Analysis" is the act of extracting useful information from obtained data.

[0204] "Detecting duplication and inconsistencies" means checking for multiple appointments at the same time or for any conflicting information.

[0205] "Automatically optimizing the schedule based on priority" means rationally organizing the schedule based on the importance and urgency of each item.

[0206] "Acquiring weather information and considering factors that may affect the plan" means collecting weather-related data and making decisions based on how it will affect the plan.

[0207] "Automatically contacting the operating organization and adjusting the schedule" means contacting the appropriate organization and making changes to the schedule.

[0208] "Notifying users and collecting feedback" refers to methods for informing users and obtaining their responses.

[0209] An "emotion engine" is an algorithm or program used to analyze a user's emotional state.

[0210] "Optimizing schedules and adjusting notifications" means streamlining schedules and setting appropriate notification frequencies and content.

[0211] The system for implementing this invention provides a schedule management application that takes user emotions into consideration. The server forms the core of this system, optimizing the user's schedule using various means and making adjustments according to their emotions.

[0212] The server collects schedule information entered from the user's terminal via data communication. This schedule information includes appointments entered directly by the user and information obtained through integration with external calendar systems. APIs are used for integration with external systems.

[0213] This data is analyzed on the server to detect duplicates and inconsistencies. Prioritized, automated optimization mechanisms streamline the schedule, ensuring efficient management of users' appointments.

[0214] Furthermore, the server acquires weather information and considers factors that may affect the schedule. This minimizes the impact of external factors such as weather on the schedule. It also automates communication with relevant organizations and adjusts the schedule as needed.

[0215] The emotion engine analyzes the user's emotional state and uses that data to optimize schedules and adjust notifications. This analysis utilizes data obtained from the interface, such as the user's input speed and idle time, to evaluate their stress and relaxation levels.

[0216] The server aggregates this data and delivers notifications to the user in the most optimal way. By collecting feedback and incorporating it into machine learning algorithms, the system is continuously improved, enabling a higher level of personalization.

[0217] For example, on busy workdays, the emotion engine can detect stress and reduce the user's burden by delivering only important notifications at the appropriate time. An example of a prompt for the generating AI model would be, "Please propose a method to optimize the schedule based on the user's emotional state and deliver important notifications at the appropriate time."

[0218] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0219] Step 1:

[0220] The terminal receives and collects schedule information entered by the user. This schedule information includes details such as date, time, location, and content. This information is transmitted to the server via data communication.

[0221] Step 2:

[0222] The server analyzes the received schedule information and detects duplicates and inconsistencies. The input for the analysis is the schedule information sent from the terminal, and the output includes the results of the judgment regarding the presence or absence of duplicates and inconsistencies. At this time, text analysis technology is used to verify the consistency of the data.

[0223] Step 3:

[0224] The server automatically optimizes the schedule based on priority. The input is the analysis results and the user's priority settings, and the output is the optimized schedule. It utilizes machine learning algorithms to achieve task arrangement according to importance.

[0225] Step 4:

[0226] The server acquires weather information and considers factors that may affect the schedule. The input is weather data obtained from an external API, and the server adjusts the schedule based on this data. The output is the affected schedule information.

[0227] Step 5:

[0228] The server automatically contacts the operating organization to coordinate the schedule. The input is the schedule coordinated within the server, and the output is a confirmation notification that the communication has been completed. The server uses a communication protocol to ensure appropriate communication is carried out.

[0229] Step 6:

[0230] The server uses an emotion engine to analyze the user's emotional state. Input consists of user usage data obtained from the terminal and external schedule information, and it outputs stress levels and relaxation levels. An emotion recognition algorithm is applied to this analysis.

[0231] Step 7:

[0232] The server adjusts notifications based on sentiment data. The input is analyzed sentiment data and a prioritized schedule, and the output is the adjusted notification plan. The frequency and timing of notifications are optimized according to sentiment.

[0233] Step 8:

[0234] Users receive notifications from the server and review their contents. The server collects feedback from these notifications and uses it to improve future services. Based on this feedback, the goal is to further optimize the notification strategy.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] [Second Embodiment]

[0239] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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).

[0245] 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.

[0246] 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.

[0247] 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.

[0248] 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.

[0249] 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.

[0250] 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".

[0251] This invention provides a schedule management system that reduces the burden on users and smoothly supports children's activities. Specifically, it is a system that collects schedule information from various sources using data communication means, analyzes it, and performs an optimization process.

[0252] Users can input information about their household schedules and children's extracurricular activities using a dedicated application on their device. This information is sent to a server where it is integrated. The server also collects schedule information from external calendar services and educational institutions via APIs and aggregates this information in one place.

[0253] The server analyzes the collected data to detect duplicate appointments and inconsistencies. An AI agent then optimizes the schedule based on historical data, taking appointment priorities into consideration. Furthermore, it includes a function to acquire weather forecast data and suggest adjustments to mitigate potential impacts on outdoor activities.

[0254] For example, when a user registers the date of their child's sports day, the server checks the weather forecast and, if it detects a possibility of bad weather on the day, automatically suggests alternative dates and notifies the organizing body. If communication with the organizing body is possible, it then uses an API to propose a rescheduled date and automatically submits the application.

[0255] Regarding notifications, the device will send push notifications to the user with the most relevant information related to their schedule. This includes event details, packing lists, and weather-related changes. Users can also provide feedback through the app, and this information is collected on the server and used to optimize future events.

[0256] By combining these functions, the system can reduce the management burden on users and improve the accuracy of schedules, thereby efficiently creating an environment that supports children's learning and experiences.

[0257] The following describes the processing flow.

[0258] Step 1:

[0259] The server periodically collects data from external calendar services and educational institutions using APIs. It also obtains new schedule information via email and notifications.

[0260] Step 2:

[0261] The terminal provides an interface for users to input information about household schedules and children's extracurricular activities. Users input this information through this interface, and the terminal transmits it to the server.

[0262] Step 3:

[0263] The server integrates all collected schedule information and stores it in a database. Next, it analyzes this information to detect events occurring at the same time or conflicting schedules.

[0264] Step 4:

[0265] The server prioritizes and automatically optimizes schedules based on schedule data analyzed using an AI agent. This includes calculating the optimal placement to maximize the efficiency of children's learning and activities.

[0266] Step 5:

[0267] The server uses a weather forecast API to retrieve weather data for the near future, assesses its impact on planned activities, especially those involving outdoor activities, and develops adjustment plans.

[0268] Step 6:

[0269] The server automatically contacts the operating organization according to pre-configured conditions and initiates transfer or cancellation procedures if necessary. It responds quickly using APIs and email.

[0270] Step 7:

[0271] The device notifies the user of an optimized schedule and provides important information such as what to bring and important points via push notifications. The user can then make the necessary preparations based on this information.

[0272] Step 8:

[0273] Users provide feedback on the provided schedule through a terminal app, and this information is sent to the server. The server collects user feedback and uses it to optimize the AI ​​agent for future improvements.

[0274] (Example 1)

[0275] 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."

[0276] In modern households, managing children's diverse activities and events is a significant burden for parents. In particular, overlapping schedules, schedule changes due to weather, and coordination with external organizations are time-consuming and require efficient management. Furthermore, comprehensively managing all this information and creating an efficient schedule is difficult.

[0277] 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.

[0278] In this invention, the server includes means for aggregating schedule information using digital communication technology, means for analyzing the schedule information and identifying duplicates and inconsistencies, and means for automatically optimizing the schedule based on priority. This reduces the management burden on users and enables the setting of an optimal schedule.

[0279] "Digital communication technology" refers to technologies that transmit information electrically or electronically, and is a means of enabling the collection and transmission of scheduled information.

[0280] "Means for aggregating schedule information" refers to methods and technologies for organizing, integrating, and centrally managing schedule-related information obtained from multiple sources.

[0281] "Methods for analyzing schedule information and identifying overlaps and inconsistencies" refers to technologies that analyze aggregated schedule information to detect cases where the same or different schedules overlap.

[0282] The means for automatically optimizing the schedule based on priority is a technology for evaluating the importance and urgency of each schedule and generating an efficient schedule based on that information.

[0283] The means for obtaining weather data and considering elements that affect activities is a method for collecting weather information and providing impacts on schedules and alternatives based on that information.

[0284] The means for automatically contacting the operating agency and adjusting the schedule is a technology for communicating with the agency and automatically proposing and confirming schedule changes if necessary.

[0285] The means for notifying users of information and aggregating feedback is a method for notifying users of the latest information and changes through a terminal and collecting the received feedback.

[0286] The means for users to input information using a terminal is an interface for users to directly input schedules and other related information through a device.

[0287] The means for using an AI model to propose optimizations based on past information is a method for generating proposals for optimizing future schedules by leveraging artificial intelligence technology and analyzing data accumulated in the past.

[0288] This invention is a schedule management system for improving family management efficiency. The system is mainly realized through the exchange of information among the server, terminal, and user.

[0289] The server has a function of aggregating schedule information from various information sources using digital communication technology. For example, it not only collects the schedule information within the family input by the user through the terminal, but also obtains information from the calendars and event management services of external systems through APIs. The server analyzes the aggregated information and automatically detects schedule duplicates and conflicts.

[0290] Next, the server optimizes the schedule based on priority. It utilizes an AI model to compare with past data and propose the optimal schedule. Specifically, it evaluates the priority and importance of extracurricular activities and family events, and adjusts the schedule accordingly.

[0291] Furthermore, the server acquires weather data and takes into account weather factors that may affect the schedule. For example, if the date of an outdoor activity needs to be changed due to weather, it can automatically propose alternative dates and automatically contact the organizing body.

[0292] The device notifies the user of the latest information and sends push notifications as needed. Users can easily check appointment details and provide feedback using the device. This feedback is collected on the server and used to optimize future schedules.

[0293] For example, if a user enters the date of their child's sports day via their device, the server will compare it with the weather forecast and proactively suggest alternative dates in case of rain, then contact the organizing body. An example of a prompt might be, "Please show me how to automatically notify me of an alternative date if it rains on my child's sports day."

[0294] With the above configuration, the present invention can reduce the management burden on users and achieve effective schedule management.

[0295] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0296] Step 1:

[0297] Users use a dedicated application on their device to input information about family schedules and their children's extracurricular activities. Specific inputs include the event name, date and time, location, and necessary items. The entered information is sent directly from the device to the server. The server records this information in a database, preparing it for subsequent processing.

[0298] Step 2:

[0299] The server collects additional schedule information through external calendar services and educational institution APIs. It sends API requests and retrieves information in a defined format. The data obtained from the APIs is transformed, organized, and integrated into existing databases. This ensures that accurate information is aggregated in real time.

[0300] Step 3:

[0301] The server analyzes the aggregated schedule information. This analysis checks for duplicate or inconsistent schedules and identifies them if found. Specifically, if there are different schedules at the same time, the server compiles them into a list and prepares to notify the user. The analysis results are stored in an internal log.

[0302] Step 4:

[0303] The server optimizes the schedule by considering priority. Based on the input information and aggregated data, the AI ​​agent refers to past data and proposes the most efficient schedule while evaluating the priority of each appointment. The AI ​​model enables rapid schedule creation. This proposal is stored within the system and used for subsequent notifications.

[0304] Step 5:

[0305] The server acquires meteorological data using a weather forecast API. In this acquisition, information such as the forecasted weather, temperature, and precipitation probability is confirmed. The acquired data is used to determine whether adjustments necessary for outdoor activities are required. An adjustment plan based on the weather is generated, and the schedule is readjusted if necessary.

[0306] Step 6:

[0307] If necessary, the server automatically contacts the operating agency and asks them to consider the proposed adjustment plan. This contact is made using the API or email, and automates the confirmation of rescheduling dates and the like. The response from the operating agency is fed back to the next step.

[0308] Step 7:

[0309] The terminal receives the organized information from the server and notifies the user as a push notification. The notification includes details such as the latest status, changes, and precautions of the event. Also, the user can send feedback, and the terminal returns this to the server to be utilized for the next schedule optimization.

[0310] (Application Example 1)

[0311] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0312] In modern society, managing schedules within the family and adjusting children's activity schedules require a lot of time and effort, especially when both parents are working, which places a heavy burden. Also, when schedule changes occur due to weather or external factors, information sharing for quickly responding to them is not smoothly carried out. Under such circumstances, there is a need to efficiently manage schedules and smoothly support children's activities.

[0313] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0314] In this invention, the server includes means for collecting schedule information using data communication means, means for analyzing the schedule information to detect duplication and inconsistencies, means for automatically optimizing the schedule based on priority, means for acquiring weather information and considering factors that affect the schedule, means for automatically contacting the operating organization and adjusting the schedule, means for notifying the user and collecting feedback, and means for providing information according to the situation in the physical environment using physical machines for supporting human life. This reduces the burden on the user and enables efficient schedule management that smoothly supports children's activities.

[0315] "Data communication methods" is a general term for communication technologies and protocols used to collect scheduled information from external sources.

[0316] "Means for analyzing schedule information to detect duplication and inconsistencies" refers to a function that analyzes collected schedule data to find duplication and inconsistencies in its content.

[0317] "Automatically optimizing schedules based on priority" refers to a function that creates the most efficient schedule according to the importance and priority of each appointment.

[0318] "Means of acquiring weather information and considering factors that affect the schedule" refers to a function that uses weather data to make adjustments in order to minimize the impact of weather on the schedule.

[0319] "A means of automatically contacting the operating organization and adjusting the schedule" refers to a function that automatically contacts the relevant organizations and institutions and adjusts the schedule when changes to the schedule are necessary.

[0320] "Means of notifying users and collecting feedback" refers to functions that send push notifications and alerts to users and collect their opinions and responses.

[0321] "Means of providing information in accordance with the situation in the physical environment using physical machines for human life support" refers to functions that provide information based on the real environment using robots and assistant devices to support people's lives.

[0322] One embodiment of this invention is an integrated system for streamlining household schedule management and supporting children's daily activities. The server collects schedule information entered by users using data communication means. This includes household schedule information collected via a dedicated application on a smartphone or tablet. Furthermore, it obtains calendar information from external services and schedule information from educational institutions via APIs.

[0323] The server analyzes the collected schedule information to detect duplicates and inconsistencies. Using machine learning algorithms, it optimizes the schedule based on past data and user feedback. This process ensures effective schedule adjustments according to priority and importance.

[0324] Furthermore, the server acquires weather information and makes suggestions considering the impact of weather on the schedule. For example, in the case of outdoor activities, if bad weather is predicted, it can suggest a backup date and automatically contact the organizing body via API to adjust the schedule.

[0325] The device sends push notifications to the user, containing schedule updates and changes, lists of necessary preparations, and alerts about weather-related changes. Users can provide feedback, which will be used to optimize future services.

[0326] The server has the function of providing information tailored to the physical living environment, for example, using a robot designed to support human life. This robot presents appropriate information to the user in real time via voice and display.

[0327] As a concrete example, if a child's school trip is postponed due to rain, the system will suggest alternative dates and send a push notification to the parent's device. An example of a prompt message would be, "Your child's school trip this weekend has been postponed due to rain. Please suggest possible alternative dates."

[0328] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0329] Step 1:

[0330] The server collects schedule information from users using data communication methods. Schedules entered by users via a dedicated application on smartphones or tablets are sent to the server. This input information is received by the server as JSON data.

[0331] Step 2:

[0332] The server uses external APIs to retrieve additional appointment information from external calendar services and educational institutions. This information retrieved through the APIs is stored in an integrated data store, ensuring consistency between internal and external data.

[0333] Step 3:

[0334] The server analyzes the collected schedule information and detects duplicates and inconsistencies. For each entered schedule, it applies an algorithm that matches it using a specific identifier to detect duplicate items and conflicts. The output is formatted so that the analysis results can be used to improve scheduling.

[0335] Step 4:

[0336] The server uses machine learning algorithms to optimize the schedule. It adjusts the schedule according to priority, taking into account historical data and feedback. The resulting optimization becomes the basis data for the next calculation step.

[0337] Step 5:

[0338] The server retrieves weather information from external sources and evaluates factors that may affect the schedule. It analyzes the weather data and incorporates it as a variable to consider rescheduling activities if there is a possibility of impact on outdoor activities.

[0339] Step 6:

[0340] The server automatically contacts the operating organization as needed to adjust the schedule. Using the API, it proposes new dates based on weather and internal requirements. This confirms the adjustment of the plan and generates detailed contact information.

[0341] Step 7:

[0342] The device sends push notifications to the user regarding schedule changes and important information. The generated notification information is delivered to the device, allowing the user to stay informed of necessary information in real time.

[0343] Step 8:

[0344] The user reviews the notification and sends feedback to the server. The feedback information is then stored again in the database on the server and referenced for future schedule optimizations.

[0345] 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.

[0346] This invention provides a schedule management system that takes user emotions into account. By combining it with an emotion engine, it can meet more sophisticated user needs than conventional systems.

[0347] First, the user enters their schedule information via a dedicated application on their device. In the background of this input screen, an emotion engine analyzes data obtained from the user interface, evaluating the user's emotions in real time. For example, it determines whether the user is stressed or relaxed based on factors such as input speed, input content, and even idle time.

[0348] The server continuously collects schedule information using external calendar services and educational institution APIs, while simultaneously receiving user sentiment data sent from the device, and integrates all the data. This not only detects schedule overlaps and inconsistencies, but also enables prioritization that reflects the user's current sentiment state.

[0349] Furthermore, the server uses an AI agent to automatically optimize the schedule based on the collected data. In this process, it also takes into account the user's emotional data recognized by the emotion engine, and takes care not to overschedule the user during times when they are likely to feel stressed. Notifications are also adjusted based on the user's emotional state. For example, when the user is relaxed, new notifications are sent in a gentle tone, while when the user is stressed, the system avoids sending many notifications in a short period of time.

[0350] For example, if a user receives multiple notifications during a busy day, the emotion engine will detect that their stress levels are high and adjust the server to omit non-urgent notifications and deliver them all together later.

[0351] The emotion engine analyzes the user's emotions during feedback, and the AI ​​agent uses this data to improve future schedule optimization processes. This gives the system the ability to continuously improve the user experience and provide personalized schedule management.

[0352] Thus, by incorporating an emotion engine, this invention enables advanced schedule management that responds to the user's actual emotions, providing a richer learning and activity environment.

[0353] The following describes the processing flow.

[0354] Step 1:

[0355] Users enter new appointments using a dedicated application on their device. During this process, an emotion engine operates in the background, analyzing input speed, tone, and writing style to evaluate the user's emotional state in real time. The evaluation results are generated on the device as parameters such as stress, satisfaction, and anxiety.

[0356] Step 2:

[0357] The terminal sends the entered schedule information and sentiment data to the server. The server simultaneously collects schedule information from multiple external services and integrates and stores it in a database. The information is sorted by priority and time, and sentiment data is also recorded in association with it.

[0358] Step 3:

[0359] The server analyzes the schedule information collected using an AI agent to check for duplicates or inconsistencies. If detected, the AI ​​agent prioritizes events based on sentiment data to minimize user stress. It also refers to weather information and considers alternatives if outdoor events are expected to be affected.

[0360] Step 4:

[0361] The server configures notifications based on the optimization schedule created. Here, it utilizes parameters detected by the emotion engine to determine the optimal timing for receiving notifications. For example, if a user is stressed, the frequency of notifications is reduced and they are all sent at once.

[0362] Step 5:

[0363] The device delivers optimized schedules and tailored notifications to the user. Users can use the device's feedback interface to provide information about their actual experience and feelings. This feedback includes a wide range of factors, such as the appropriateness of notifications and satisfaction with the schedule.

[0364] Step 6:

[0365] The server incorporates user feedback and sentiment data into the AI ​​agent, which is then used to optimize future schedules. This allows the system to continuously learn and improve, enabling it to provide a more personalized user experience.

[0366] (Example 2)

[0367] 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".

[0368] Conventional schedule management systems have difficulty considering the emotional state of users, and do not adequately respond to users' stress levels or relaxation states. As a result, they cannot present schedules that are optimal for users' lives and work, which hinders the improvement of the user experience.

[0369] 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.

[0370] In this invention, the server includes means for collecting user schedule information using data communication means, means for analyzing the schedule information and emotional information to detect overlaps and inconsistencies, and means for automatically optimizing the schedule based on emotional information and priority. This enables flexible schedule management tailored to the user's emotional state.

[0371] "Data communication means" refers to communication technology used to send and receive user schedule information to and from a server, and involves data transmission via the internet or local network.

[0372] "Emotional information" refers to data that indicates the user's psychological and emotional state, and includes information obtained from factors such as input speed and idle time.

[0373] "Automatic schedule optimization" refers to the process of efficiently and appropriately organizing a user's schedule, taking into account priorities and emotional information.

[0374] "Weather information" refers to data that indicates weather conditions that may affect the execution of planned activities, and is obtained from weather forecasts and other sources.

[0375] "Operating organization" refers to an external organization or service provider involved in the user's schedule, and is the entity responsible for changing or adjusting the schedule.

[0376] "Notifications" refer to messages that inform users of schedules and related important information, and are provided by voice, text, or other means.

[0377] A "machine learning algorithm" is a mathematical method for efficiently performing analysis and prediction using past data and feedback.

[0378] "External systems" refer to external computer systems or services that interact with the system to retrieve or synchronize the user's schedule information.

[0379] To implement this invention, the user first inputs their schedule information using a dedicated application on their device. An emotion engine operates on the device, analyzing the user's emotional information from the speed and content of keyboard input, as well as the idle time. The hardware used is a general-purpose computer or smartphone, and the software includes an emotion engine module for performing emotion analysis.

[0380] The server collects user sentiment information sent from terminals via data communication methods and retrieves schedule information through interfaces with external calendar services and educational systems. The collected data is stored in a database, where it is processed to detect schedule overlaps and inconsistencies. The server is equipped with an AI agent that uses machine learning algorithms to optimize schedules based on past data and feedback.

[0381] Specifically, if the server detects that a user is under high stress during a busy period, it will refrain from sending non-urgent notifications and adjust its distribution to deliver them in bulk at an appropriate time. Furthermore, in its automatic schedule optimization, it selects times when users are less likely to experience stress and schedules appointments accordingly.

[0382] An example of a prompt message would be, "Please suggest the optimal notification schedule when the user is in a high-stress state." This instruction would be sent to the AI ​​model to generate an appropriate scheduling pattern.

[0383] This system allows users to enjoy personalized schedule management tailored to their individual emotional state, enabling them to live a less stressful and more efficient life.

[0384] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0385] Step 1:

[0386] The user enters their schedule information into a dedicated application on their device.

[0387] Specific operation: The user enters the title, date, time, and location of the appointment into text boxes on the application screen and clicks the submit button.

[0388] Input and Output: In this process, the input is text data entered by the user, and the output is schedule information stored in a temporary database on the terminal.

[0389] Step 2:

[0390] The device analyzes emotional data based on factors such as input speed and idle time.

[0391] Specific operation: The device uses an emotion engine to measure keyboard input speed and the amount of time the user spends looking at the screen. Based on this, it infers the user's emotional state.

[0392] Input and Output: The input consists of keyboard usage and elapsed time. Based on this, the data is analyzed, and the output is data indicating the user's emotional state.

[0393] Step 3:

[0394] The device sends the analyzed emotion data and schedule information to the server.

[0395] Specific operation: The device uploads data to the server via the internet.

[0396] Input and Output: The input is a set of emotion data and schedule information, and the output is a confirmation message indicating whether the data was successfully delivered to the server.

[0397] Step 4:

[0398] The server stores the received data and collects information about additional planned data from external systems.

[0399] Specific operation: The server stores sentiment data and schedule information in the database and calls an external API to retrieve further schedule information.

[0400] Input and Output: Input consists of data submitted by users and schedule information from external systems, while output is an integrated schedule information database.

[0401] Step 5:

[0402] The server automatically optimizes the schedule based on the collected data.

[0403] Specific operation: The server's AI agent applies machine learning algorithms and reorganizes the schedule, taking sentiment data into consideration.

[0404] Input and Output: Input consists of integrated database information and historical feedback, while output consists of optimized scheduling information.

[0405] Step 6:

[0406] The server adjusts notifications to the user based on their emotional state.

[0407] Specific operation: When the server suspects that the user is in a high-stress state, it performs a process to change the timing and content of notifications.

[0408] Input and Output: The input is the user's current emotional state data, and the output is a personalized notification message based on a schedule.

[0409] By using a generative AI model at each step, flexible and efficient scheduling is achieved.

[0410] (Application Example 2)

[0411] 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 as the "terminal".

[0412] Traditional schedule management systems automatically optimize schedules without considering user emotions, often failing to address situations that cause stress or mental strain. Therefore, there is a need to improve the convenience of schedule management and make adjustments based on the user's emotional state.

[0413] 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.

[0414] In this invention, the server includes means for collecting schedule information using data communication means, means for analyzing the schedule information to detect duplication and inconsistencies, means for automatically optimizing the schedule based on priority, means for acquiring weather information and considering factors that affect the schedule, means for automatically contacting the operating organization and adjusting the schedule, means for notifying the user and collecting feedback, and means for performing schedule optimization and notification adjustment using an emotion engine that analyzes the user's emotional state. This makes it possible to adjust the schedule based on the stress level and emotional state felt by the user.

[0415] A "data communication means" is an interface for sending and receiving data over a network.

[0416] "Schedule information" refers to data related to the schedule entered by the user.

[0417] "Analysis" is the act of extracting useful information from obtained data.

[0418] "Detecting duplication and inconsistencies" means checking for multiple appointments at the same time or for any conflicting information.

[0419] "Automatically optimizing the schedule based on priority" means rationally organizing the schedule based on the importance and urgency of each item.

[0420] "Acquiring weather information and considering factors that may affect the plan" means collecting weather-related data and making decisions based on how it will affect the plan.

[0421] "Automatically contacting the operating organization and adjusting the schedule" means contacting the appropriate organization and making changes to the schedule.

[0422] "Notifying users and collecting feedback" refers to methods for informing users and obtaining their responses.

[0423] An "emotion engine" is an algorithm or program used to analyze a user's emotional state.

[0424] "Optimizing schedules and adjusting notifications" means streamlining schedules and setting appropriate notification frequencies and content.

[0425] The system for implementing this invention provides a schedule management application that takes user emotions into consideration. The server forms the core of this system, optimizing the user's schedule using various means and making adjustments according to their emotions.

[0426] The server collects schedule information entered from the user's terminal via data communication. This schedule information includes appointments entered directly by the user and information obtained through integration with external calendar systems. APIs are used for integration with external systems.

[0427] This data is analyzed on the server to detect duplicates and inconsistencies. Prioritized, automated optimization mechanisms streamline the schedule, ensuring efficient management of users' appointments.

[0428] Furthermore, the server acquires weather information and considers factors that may affect the schedule. This minimizes the impact of external factors such as weather on the schedule. It also automates communication with relevant organizations and adjusts the schedule as needed.

[0429] The emotion engine analyzes the user's emotional state and uses that data to optimize schedules and adjust notifications. This analysis utilizes data obtained from the interface, such as the user's input speed and idle time, to evaluate their stress and relaxation levels.

[0430] The server aggregates this data and delivers notifications to the user in the most optimal way. By collecting feedback and incorporating it into machine learning algorithms, the system is continuously improved, enabling a higher level of personalization.

[0431] For example, on busy workdays, the emotion engine can detect stress and reduce the user's burden by delivering only important notifications at the appropriate time. An example of a prompt for the generating AI model would be, "Please propose a method to optimize the schedule based on the user's emotional state and deliver important notifications at the appropriate time."

[0432] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0433] Step 1:

[0434] The terminal receives and collects schedule information entered by the user. This schedule information includes details such as date, time, location, and content. This information is transmitted to the server via data communication.

[0435] Step 2:

[0436] The server analyzes the received schedule information and detects duplicates and inconsistencies. The input for the analysis is the schedule information sent from the terminal, and the output includes the results of the judgment regarding the presence or absence of duplicates and inconsistencies. At this time, text analysis technology is used to verify the consistency of the data.

[0437] Step 3:

[0438] The server automatically optimizes the schedule based on priority. The input is the analysis results and the user's priority settings, and the output is the optimized schedule. It utilizes machine learning algorithms to achieve task arrangement according to importance.

[0439] Step 4:

[0440] The server acquires weather information and considers factors that may affect the schedule. The input is weather data obtained from an external API, and the server adjusts the schedule based on this data. The output is the affected schedule information.

[0441] Step 5:

[0442] The server automatically contacts the operating organization to coordinate the schedule. The input is the schedule coordinated within the server, and the output is a confirmation notification that the communication has been completed. The server uses a communication protocol to ensure appropriate communication is carried out.

[0443] Step 6:

[0444] The server uses an emotion engine to analyze the user's emotional state. Input consists of user usage data obtained from the terminal and external schedule information, and it outputs stress levels and relaxation levels. An emotion recognition algorithm is applied to this analysis.

[0445] Step 7:

[0446] The server adjusts notifications based on sentiment data. The input is analyzed sentiment data and a prioritized schedule, and the output is the adjusted notification plan. The frequency and timing of notifications are optimized according to sentiment.

[0447] Step 8:

[0448] Users receive notifications from the server and review their contents. The server collects feedback from these notifications and uses it to improve future services. Based on this feedback, the goal is to further optimize the notification strategy.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] [Third Embodiment]

[0453] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0454] 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.

[0455] 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).

[0456] 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.

[0457] 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.

[0458] 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).

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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".

[0465] This invention provides a schedule management system that reduces the burden on users and smoothly supports children's activities. Specifically, it is a system that collects schedule information from various sources using data communication means, analyzes it, and performs an optimization process.

[0466] Users can input information about their household schedules and children's extracurricular activities using a dedicated application on their device. This information is sent to a server where it is integrated. The server also collects schedule information from external calendar services and educational institutions via APIs and aggregates this information in one place.

[0467] The server analyzes the collected data to detect duplicate appointments and inconsistencies. An AI agent then optimizes the schedule based on historical data, taking appointment priorities into consideration. Furthermore, it includes a function to acquire weather forecast data and suggest adjustments to mitigate potential impacts on outdoor activities.

[0468] For example, when a user registers the date of their child's sports day, the server checks the weather forecast and, if it detects a possibility of bad weather on the day, automatically suggests alternative dates and notifies the organizing body. If communication with the organizing body is possible, it then uses an API to propose a rescheduled date and automatically submits the application.

[0469] Regarding notifications, the device will send push notifications to the user with the most relevant information related to their schedule. This includes event details, packing lists, and weather-related changes. Users can also provide feedback through the app, and this information is collected on the server and used to optimize future events.

[0470] By combining these functions, the system can reduce the management burden on users and improve the accuracy of schedules, thereby efficiently creating an environment that supports children's learning and experiences.

[0471] The following describes the processing flow.

[0472] Step 1:

[0473] The server periodically collects data from external calendar services and educational institutions using APIs. It also obtains new schedule information via email and notifications.

[0474] Step 2:

[0475] The terminal provides an interface for users to input information about household schedules and children's extracurricular activities. Users input this information through this interface, and the terminal transmits it to the server.

[0476] Step 3:

[0477] The server integrates all collected schedule information and stores it in a database. Next, it analyzes this information to detect events occurring at the same time or conflicting schedules.

[0478] Step 4:

[0479] The server prioritizes and automatically optimizes schedules based on schedule data analyzed using an AI agent. This includes calculating the optimal placement to maximize the efficiency of children's learning and activities.

[0480] Step 5:

[0481] The server uses a weather forecast API to retrieve weather data for the near future, assesses its impact on planned activities, especially those involving outdoor activities, and develops adjustment plans.

[0482] Step 6:

[0483] The server automatically contacts the operating organization according to pre-configured conditions and initiates transfer or cancellation procedures if necessary. It responds quickly using APIs and email.

[0484] Step 7:

[0485] The device notifies the user of an optimized schedule and provides important information such as what to bring and important points via push notifications. The user can then make the necessary preparations based on this information.

[0486] Step 8:

[0487] Users provide feedback on the provided schedule through a terminal app, and this information is sent to the server. The server collects user feedback and uses it to optimize the AI ​​agent for future improvements.

[0488] (Example 1)

[0489] 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."

[0490] In modern households, managing children's diverse activities and events is a significant burden for parents. In particular, overlapping schedules, schedule changes due to weather, and coordination with external organizations are time-consuming and require efficient management. Furthermore, comprehensively managing all this information and creating an efficient schedule is difficult.

[0491] 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.

[0492] In this invention, the server includes means for aggregating schedule information using digital communication technology, means for analyzing the schedule information and identifying duplicates and inconsistencies, and means for automatically optimizing the schedule based on priority. This reduces the management burden on users and enables the setting of an optimal schedule.

[0493] "Digital communication technology" refers to technologies that transmit information electrically or electronically, and is a means of enabling the collection and transmission of scheduled information.

[0494] "Means for aggregating schedule information" refers to methods and technologies for organizing, integrating, and centrally managing schedule-related information obtained from multiple sources.

[0495] "Methods for analyzing schedule information and identifying overlaps and inconsistencies" refers to technologies that analyze aggregated schedule information to detect cases where the same or different schedules overlap.

[0496] "A method for automatically optimizing schedules based on priority" refers to a technology that evaluates the importance and urgency of each appointment and generates an efficient schedule based on that information.

[0497] "Means of acquiring weather data and considering factors that affect activities" refers to methods of collecting weather information and using that information to provide information on the impact on plans and alternative options.

[0498] "A means of automatically contacting the operating organization and adjusting the schedule" refers to technology that communicates with the organization and, if necessary, automatically proposes or confirms schedule changes.

[0499] "Means of notifying users of information and collecting feedback" refers to methods of notifying users of the latest information and changes through their devices and collecting the feedback received.

[0500] "A means by which users input information using a terminal" refers to an interface that allows users to directly input schedules and other related information via a device.

[0501] "A method of using AI models to propose optimizations based on past information" refers to a method that utilizes artificial intelligence technology to analyze data accumulated in the past and generate proposals to optimize future schedules.

[0502] This invention is a schedule management system designed to streamline family management. The system is primarily implemented through the exchange of information via a server, terminals, and users.

[0503] The server utilizes digital communication technology to aggregate schedule information from diverse sources. For example, it not only collects household schedule information entered by users on their devices, but also retrieves information from external systems such as calendars and event management services via APIs. The server analyzes the aggregated information and automatically detects schedule overlaps and inconsistencies.

[0504] Next, the server optimizes the schedule based on priority. It utilizes an AI model to compare with past data and propose the optimal schedule. Specifically, it evaluates the priority and importance of extracurricular activities and family events, and adjusts the schedule accordingly.

[0505] Furthermore, the server acquires weather data and takes into account weather factors that may affect the schedule. For example, if the date of an outdoor activity needs to be changed due to weather, it can automatically propose alternative dates and automatically contact the organizing body.

[0506] The device notifies the user of the latest information and sends push notifications as needed. Users can easily check appointment details and provide feedback using the device. This feedback is collected on the server and used to optimize future schedules.

[0507] For example, if a user enters the date of their child's sports day via their device, the server will compare it with the weather forecast and proactively suggest alternative dates in case of rain, then contact the organizing body. An example of a prompt might be, "Please show me how to automatically notify me of an alternative date if it rains on my child's sports day."

[0508] With the above configuration, the present invention can reduce the management burden on users and achieve effective schedule management.

[0509] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0510] Step 1:

[0511] Users use a dedicated application on their device to input information about family schedules and their children's extracurricular activities. Specific inputs include the event name, date and time, location, and necessary items. The entered information is sent directly from the device to the server. The server records this information in a database, preparing it for subsequent processing.

[0512] Step 2:

[0513] The server collects additional schedule information through external calendar services and educational institution APIs. It sends API requests and retrieves information in a defined format. The data obtained from the APIs is transformed, organized, and integrated into existing databases. This ensures that accurate information is aggregated in real time.

[0514] Step 3:

[0515] The server analyzes the aggregated schedule information. This analysis checks for duplicate or inconsistent schedules and identifies them if found. Specifically, if there are different schedules at the same time, the server compiles them into a list and prepares to notify the user. The analysis results are stored in an internal log.

[0516] Step 4:

[0517] The server optimizes the schedule by considering priority. Based on the input information and aggregated data, the AI ​​agent refers to past data and proposes the most efficient schedule while evaluating the priority of each appointment. The AI ​​model enables rapid schedule creation. This proposal is stored within the system and used for subsequent notifications.

[0518] Step 5:

[0519] The server retrieves weather data using a weather forecast API. This retrieves information such as the forecasted weather, temperature, and probability of precipitation. The retrieved data is used to determine whether adjustments are necessary, especially for outdoor activities. A weather-based adjustment plan is generated, and the schedule is readjusted as needed.

[0520] Step 6:

[0521] The server will automatically contact the operating organization if necessary to have them consider the proposed adjustments. This contact will be made via API or email, automating the confirmation of transfer dates and other details. The response from the operating organization will be fed back into the next step.

[0522] Step 7:

[0523] The device receives organized information from the server and notifies the user via push notification. The notification includes details such as the latest event status, changes, and important notes. Users can also submit feedback, which the device sends back to the server to be used for optimizing future schedules.

[0524] (Application Example 1)

[0525] 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."

[0526] In modern society, managing household schedules and coordinating children's activity schedules requires considerable time and effort, and is particularly burdensome for working parents. Furthermore, information sharing to quickly respond to schedule changes due to weather or external factors is often inefficient. Under these circumstances, there is a need for efficient schedule management and smooth support for children's activities.

[0527] 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.

[0528] In this invention, the server includes means for collecting schedule information using data communication means, means for analyzing the schedule information to detect duplication and inconsistencies, means for automatically optimizing the schedule based on priority, means for acquiring weather information and considering factors that affect the schedule, means for automatically contacting the operating organization and adjusting the schedule, means for notifying the user and collecting feedback, and means for providing information according to the situation in the physical environment using physical machines for supporting human life. This reduces the burden on the user and enables efficient schedule management that smoothly supports children's activities.

[0529] "Data communication methods" is a general term for communication technologies and protocols used to collect scheduled information from external sources.

[0530] "Means for analyzing schedule information to detect duplication and inconsistencies" refers to a function that analyzes collected schedule data to find duplication and inconsistencies in its content.

[0531] "Automatically optimizing schedules based on priority" refers to a function that creates the most efficient schedule according to the importance and priority of each appointment.

[0532] "Means of acquiring weather information and considering factors that affect the schedule" refers to a function that uses weather data to make adjustments in order to minimize the impact of weather on the schedule.

[0533] "A means of automatically contacting the operating organization and adjusting the schedule" refers to a function that automatically contacts the relevant organizations and institutions and adjusts the schedule when changes to the schedule are necessary.

[0534] "Means of notifying users and collecting feedback" refers to functions that send push notifications and alerts to users and collect their opinions and responses.

[0535] "Means of providing information in accordance with the situation in the physical environment using physical machines for human life support" refers to functions that provide information based on the real environment using robots and assistant devices to support people's lives.

[0536] One embodiment of this invention is an integrated system for streamlining household schedule management and supporting children's daily activities. The server collects schedule information entered by users using data communication means. This includes household schedule information collected via a dedicated application on a smartphone or tablet. Furthermore, it obtains calendar information from external services and schedule information from educational institutions via APIs.

[0537] The server analyzes the collected schedule information to detect duplicates and inconsistencies. Using machine learning algorithms, it optimizes the schedule based on past data and user feedback. This process ensures effective schedule adjustments according to priority and importance.

[0538] Furthermore, the server acquires weather information and makes suggestions considering the impact of weather on the schedule. For example, in the case of outdoor activities, if bad weather is predicted, it can suggest a backup date and automatically contact the organizing body via API to adjust the schedule.

[0539] The device sends push notifications to the user, containing schedule updates and changes, lists of necessary preparations, and alerts about weather-related changes. Users can provide feedback, which will be used to optimize future services.

[0540] The server has the function of providing information tailored to the physical living environment, for example, using a robot designed to support human life. This robot presents appropriate information to the user in real time via voice and display.

[0541] As a concrete example, if a child's school trip is postponed due to rain, the system will suggest alternative dates and send a push notification to the parent's device. An example of a prompt message would be, "Your child's school trip this weekend has been postponed due to rain. Please suggest possible alternative dates."

[0542] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0543] Step 1:

[0544] The server collects schedule information from users using data communication methods. Schedules entered by users via a dedicated application on smartphones or tablets are sent to the server. This input information is received by the server as JSON data.

[0545] Step 2:

[0546] The server uses external APIs to retrieve additional appointment information from external calendar services and educational institutions. This information retrieved through the APIs is stored in an integrated data store, ensuring consistency between internal and external data.

[0547] Step 3:

[0548] The server analyzes the collected schedule information and detects duplicates and inconsistencies. For each entered schedule, it applies an algorithm that matches it using a specific identifier to detect duplicate items and conflicts. The output is formatted so that the analysis results can be used to improve scheduling.

[0549] Step 4:

[0550] The server uses machine learning algorithms to optimize the schedule. It adjusts the schedule according to priority, taking into account historical data and feedback. The resulting optimization becomes the basis data for the next calculation step.

[0551] Step 5:

[0552] The server retrieves weather information from external sources and evaluates factors that may affect the schedule. It analyzes the weather data and incorporates it as a variable to consider rescheduling activities if there is a possibility of impact on outdoor activities.

[0553] Step 6:

[0554] The server automatically contacts the operating organization as needed to adjust the schedule. Using the API, it proposes new dates based on weather and internal requirements. This confirms the adjustment of the plan and generates detailed contact information.

[0555] Step 7:

[0556] The device sends push notifications to the user regarding schedule changes and important information. The generated notification information is delivered to the device, allowing the user to stay informed of necessary information in real time.

[0557] Step 8:

[0558] The user reviews the notification and sends feedback to the server. The feedback information is then stored again in the database on the server and referenced for future schedule optimizations.

[0559] 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.

[0560] This invention provides a schedule management system that takes user emotions into account. By combining it with an emotion engine, it can meet more sophisticated user needs than conventional systems.

[0561] First, the user enters their schedule information via a dedicated application on their device. In the background of this input screen, an emotion engine analyzes data obtained from the user interface, evaluating the user's emotions in real time. For example, it determines whether the user is stressed or relaxed based on factors such as input speed, input content, and even idle time.

[0562] The server continuously collects schedule information using external calendar services and educational institution APIs, while simultaneously receiving user sentiment data sent from the device, and integrates all the data. This not only detects schedule overlaps and inconsistencies, but also enables prioritization that reflects the user's current sentiment state.

[0563] Furthermore, the server uses an AI agent to automatically optimize the schedule based on the collected data. In this process, it also takes into account the user's emotional data recognized by the emotion engine, and takes care not to overschedule the user during times when they are likely to feel stressed. Notifications are also adjusted based on the user's emotional state. For example, when the user is relaxed, new notifications are sent in a gentle tone, while when the user is stressed, the system avoids sending many notifications in a short period of time.

[0564] For example, if a user receives multiple notifications during a busy day, the emotion engine will detect that their stress levels are high and adjust the server to omit non-urgent notifications and deliver them all together later.

[0565] The emotion engine analyzes the user's emotions during feedback, and the AI ​​agent uses this data to improve future schedule optimization processes. This gives the system the ability to continuously improve the user experience and provide personalized schedule management.

[0566] Thus, by incorporating an emotion engine, this invention enables advanced schedule management that responds to the user's actual emotions, providing a richer learning and activity environment.

[0567] The following describes the processing flow.

[0568] Step 1:

[0569] Users enter new appointments using a dedicated application on their device. During this process, an emotion engine operates in the background, analyzing input speed, tone, and writing style to evaluate the user's emotional state in real time. The evaluation results are generated on the device as parameters such as stress, satisfaction, and anxiety.

[0570] Step 2:

[0571] The terminal sends the entered schedule information and sentiment data to the server. The server simultaneously collects schedule information from multiple external services and integrates and stores it in a database. The information is sorted by priority and time, and sentiment data is also recorded in association with it.

[0572] Step 3:

[0573] The server analyzes the schedule information collected using an AI agent to check for duplicates or inconsistencies. If detected, the AI ​​agent prioritizes events based on sentiment data to minimize user stress. It also refers to weather information and considers alternatives if outdoor events are expected to be affected.

[0574] Step 4:

[0575] The server configures notifications based on the optimization schedule created. Here, it utilizes parameters detected by the emotion engine to determine the optimal timing for receiving notifications. For example, if a user is stressed, the frequency of notifications is reduced and they are all sent at once.

[0576] Step 5:

[0577] The device delivers optimized schedules and tailored notifications to the user. Users can use the device's feedback interface to provide information about their actual experience and feelings. This feedback includes a wide range of factors, such as the appropriateness of notifications and satisfaction with the schedule.

[0578] Step 6:

[0579] The server incorporates user feedback and sentiment data into the AI ​​agent, which is then used to optimize future schedules. This allows the system to continuously learn and improve, enabling it to provide a more personalized user experience.

[0580] (Example 2)

[0581] 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."

[0582] Conventional schedule management systems have difficulty considering the emotional state of users, and do not adequately respond to users' stress levels or relaxation states. As a result, they cannot present schedules that are optimal for users' lives and work, which hinders the improvement of the user experience.

[0583] 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.

[0584] In this invention, the server includes means for collecting user schedule information using data communication means, means for analyzing the schedule information and emotional information to detect overlaps and inconsistencies, and means for automatically optimizing the schedule based on emotional information and priority. This enables flexible schedule management tailored to the user's emotional state.

[0585] "Data communication means" refers to communication technology used to send and receive user schedule information to and from a server, and involves data transmission via the internet or local network.

[0586] "Emotional information" refers to data that indicates the user's psychological and emotional state, and includes information obtained from factors such as input speed and idle time.

[0587] "Automatic schedule optimization" refers to the process of efficiently and appropriately organizing a user's schedule, taking into account priorities and emotional information.

[0588] "Weather information" refers to data that indicates weather conditions that may affect the execution of planned activities, and is obtained from weather forecasts and other sources.

[0589] "Operating organization" refers to an external organization or service provider involved in the user's schedule, and is the entity responsible for changing or adjusting the schedule.

[0590] "Notifications" refer to messages that inform users of schedules and related important information, and are provided by voice, text, or other means.

[0591] A "machine learning algorithm" is a mathematical method for efficiently performing analysis and prediction using past data and feedback.

[0592] "External systems" refer to external computer systems or services that interact with the system to retrieve or synchronize the user's schedule information.

[0593] To implement this invention, the user first inputs their schedule information using a dedicated application on their device. An emotion engine operates on the device, analyzing the user's emotional information from the speed and content of keyboard input, as well as the idle time. The hardware used is a general-purpose computer or smartphone, and the software includes an emotion engine module for performing emotion analysis.

[0594] The server collects user sentiment information sent from terminals via data communication methods and retrieves schedule information through interfaces with external calendar services and educational systems. The collected data is stored in a database, where it is processed to detect schedule overlaps and inconsistencies. The server is equipped with an AI agent that uses machine learning algorithms to optimize schedules based on past data and feedback.

[0595] Specifically, if the server detects that a user is under high stress during a busy period, it will refrain from sending non-urgent notifications and adjust its distribution to deliver them in bulk at an appropriate time. Furthermore, in its automatic schedule optimization, it selects times when users are less likely to experience stress and schedules appointments accordingly.

[0596] An example of a prompt message would be, "Please suggest the optimal notification schedule when the user is in a high-stress state." This instruction would be sent to the AI ​​model to generate an appropriate scheduling pattern.

[0597] This system allows users to enjoy personalized schedule management tailored to their individual emotional state, enabling them to live a less stressful and more efficient life.

[0598] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0599] Step 1:

[0600] The user enters their schedule information into a dedicated application on their device.

[0601] Specific operation: The user enters the title, date, time, and location of the appointment into text boxes on the application screen and clicks the submit button.

[0602] Input and Output: In this process, the input is text data entered by the user, and the output is schedule information stored in a temporary database on the terminal.

[0603] Step 2:

[0604] The device analyzes emotional data based on factors such as input speed and idle time.

[0605] Specific operation: The device uses an emotion engine to measure keyboard input speed and the amount of time the user spends looking at the screen. Based on this, it infers the user's emotional state.

[0606] Input and Output: The input consists of keyboard usage and elapsed time. Based on this, the data is analyzed, and the output is data indicating the user's emotional state.

[0607] Step 3:

[0608] The device sends the analyzed emotion data and schedule information to the server.

[0609] Specific operation: The device uploads data to the server via the internet.

[0610] Input and Output: The input is a set of emotion data and schedule information, and the output is a confirmation message indicating whether the data was successfully delivered to the server.

[0611] Step 4:

[0612] The server stores the received data and collects information about additional planned data from external systems.

[0613] Specific operation: The server stores sentiment data and schedule information in the database and calls an external API to retrieve further schedule information.

[0614] Input and Output: Input consists of data submitted by users and schedule information from external systems, while output is an integrated schedule information database.

[0615] Step 5:

[0616] The server automatically optimizes the schedule based on the collected data.

[0617] Specific operation: The server's AI agent applies machine learning algorithms and reorganizes the schedule, taking sentiment data into consideration.

[0618] Input and Output: Input consists of integrated database information and historical feedback, while output consists of optimized scheduling information.

[0619] Step 6:

[0620] The server adjusts notifications to the user based on their emotional state.

[0621] Specific operation: When the server suspects that the user is in a high-stress state, it performs a process to change the timing and content of notifications.

[0622] Input and Output: The input is the user's current emotional state data, and the output is a personalized notification message based on a schedule.

[0623] By using a generative AI model at each step, flexible and efficient scheduling is achieved.

[0624] (Application Example 2)

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

[0626] Traditional schedule management systems automatically optimize schedules without considering user emotions, often failing to address situations that cause stress or mental strain. Therefore, there is a need to improve the convenience of schedule management and make adjustments based on the user's emotional state.

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

[0628] In this invention, the server includes means for collecting schedule information using data communication means, means for analyzing the schedule information to detect duplication and inconsistencies, means for automatically optimizing the schedule based on priority, means for acquiring weather information and considering factors that affect the schedule, means for automatically contacting the operating organization and adjusting the schedule, means for notifying the user and collecting feedback, and means for performing schedule optimization and notification adjustment using an emotion engine that analyzes the user's emotional state. This makes it possible to adjust the schedule based on the stress level and emotional state felt by the user.

[0629] A "data communication means" is an interface for sending and receiving data over a network.

[0630] "Schedule information" refers to data related to the schedule entered by the user.

[0631] "Analysis" is the act of extracting useful information from obtained data.

[0632] "Detecting duplication and inconsistencies" means checking for multiple appointments at the same time or for any conflicting information.

[0633] "Automatically optimizing the schedule based on priority" means rationally organizing the schedule based on the importance and urgency of each item.

[0634] "Acquiring weather information and considering factors that may affect the plan" means collecting weather-related data and making decisions based on how it will affect the plan.

[0635] "Automatically contacting the operating organization and adjusting the schedule" means contacting the appropriate organization and making changes to the schedule.

[0636] "Notifying users and collecting feedback" refers to methods for informing users and obtaining their responses.

[0637] An "emotion engine" is an algorithm or program used to analyze a user's emotional state.

[0638] "Optimizing schedules and adjusting notifications" means streamlining schedules and setting appropriate notification frequencies and content.

[0639] The system for implementing this invention provides a schedule management application that takes user emotions into consideration. The server forms the core of this system, optimizing the user's schedule using various means and making adjustments according to their emotions.

[0640] The server collects schedule information entered from the user's terminal via data communication. This schedule information includes appointments entered directly by the user and information obtained through integration with external calendar systems. APIs are used for integration with external systems.

[0641] This data is analyzed on the server to detect duplicates and inconsistencies. Prioritized, automated optimization mechanisms streamline the schedule, ensuring efficient management of users' appointments.

[0642] Furthermore, the server acquires weather information and considers factors that may affect the schedule. This minimizes the impact of external factors such as weather on the schedule. It also automates communication with relevant organizations and adjusts the schedule as needed.

[0643] The emotion engine analyzes the user's emotional state and uses that data to optimize schedules and adjust notifications. This analysis utilizes data obtained from the interface, such as the user's input speed and idle time, to evaluate their stress and relaxation levels.

[0644] The server aggregates this data and delivers notifications to the user in the most optimal way. By collecting feedback and incorporating it into machine learning algorithms, the system is continuously improved, enabling a higher level of personalization.

[0645] For example, on busy workdays, the emotion engine can detect stress and reduce the user's burden by delivering only important notifications at the appropriate time. An example of a prompt for the generating AI model would be, "Please propose a method to optimize the schedule based on the user's emotional state and deliver important notifications at the appropriate time."

[0646] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0647] Step 1:

[0648] The terminal receives and collects schedule information entered by the user. This schedule information includes details such as date, time, location, and content. This information is transmitted to the server via data communication.

[0649] Step 2:

[0650] The server analyzes the received schedule information and detects duplicates and inconsistencies. The input for the analysis is the schedule information sent from the terminal, and the output includes the results of the judgment regarding the presence or absence of duplicates and inconsistencies. At this time, text analysis technology is used to verify the consistency of the data.

[0651] Step 3:

[0652] The server automatically optimizes the schedule based on priority. The input is the analysis results and the user's priority settings, and the output is the optimized schedule. It utilizes machine learning algorithms to achieve task arrangement according to importance.

[0653] Step 4:

[0654] The server acquires weather information and considers factors that may affect the schedule. The input is weather data obtained from an external API, and the server adjusts the schedule based on this data. The output is the affected schedule information.

[0655] Step 5:

[0656] The server automatically contacts the operating organization to coordinate the schedule. The input is the schedule coordinated within the server, and the output is a confirmation notification that the communication has been completed. The server uses a communication protocol to ensure appropriate communication is carried out.

[0657] Step 6:

[0658] The server uses an emotion engine to analyze the user's emotional state. Input consists of user usage data obtained from the terminal and external schedule information, and it outputs stress levels and relaxation levels. An emotion recognition algorithm is applied to this analysis.

[0659] Step 7:

[0660] The server adjusts notifications based on sentiment data. The input is analyzed sentiment data and a prioritized schedule, and the output is the adjusted notification plan. The frequency and timing of notifications are optimized according to sentiment.

[0661] Step 8:

[0662] Users receive notifications from the server and review their contents. The server collects feedback from these notifications and uses it to improve future services. Based on this feedback, the goal is to further optimize the notification strategy.

[0663] 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.

[0664] 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.

[0665] 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.

[0666] [Fourth Embodiment]

[0667] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0668] 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.

[0669] 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).

[0670] 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.

[0671] 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.

[0672] 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).

[0673] 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.

[0674] 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.

[0675] 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.

[0676] 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.

[0677] 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.

[0678] 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.

[0679] 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".

[0680] This invention provides a schedule management system that reduces the burden on users and smoothly supports children's activities. Specifically, it is a system that collects schedule information from various sources using data communication means, analyzes it, and performs an optimization process.

[0681] Users can input information about their household schedules and children's extracurricular activities using a dedicated application on their device. This information is sent to a server where it is integrated. The server also collects schedule information from external calendar services and educational institutions via APIs and aggregates this information in one place.

[0682] The server analyzes the collected data to detect duplicate appointments and inconsistencies. An AI agent then optimizes the schedule based on historical data, taking appointment priorities into consideration. Furthermore, it includes a function to acquire weather forecast data and suggest adjustments to mitigate potential impacts on outdoor activities.

[0683] For example, when a user registers the date of their child's sports day, the server checks the weather forecast and, if it detects a possibility of bad weather on the day, automatically suggests alternative dates and notifies the organizing body. If communication with the organizing body is possible, it then uses an API to propose a rescheduled date and automatically submits the application.

[0684] Regarding notifications, the device will send push notifications to the user with the most relevant information related to their schedule. This includes event details, packing lists, and weather-related changes. Users can also provide feedback through the app, and this information is collected on the server and used to optimize future events.

[0685] By combining these functions, the system can reduce the management burden on users and improve the accuracy of schedules, thereby efficiently creating an environment that supports children's learning and experiences.

[0686] The following describes the processing flow.

[0687] Step 1:

[0688] The server periodically collects data from external calendar services and educational institutions using APIs. It also obtains new schedule information via email and notifications.

[0689] Step 2:

[0690] The terminal provides an interface for users to input information about household schedules and children's extracurricular activities. Users input this information through this interface, and the terminal transmits it to the server.

[0691] Step 3:

[0692] The server integrates all collected schedule information and stores it in a database. Next, it analyzes this information to detect events occurring at the same time or conflicting schedules.

[0693] Step 4:

[0694] The server prioritizes and automatically optimizes schedules based on schedule data analyzed using an AI agent. This includes calculating the optimal placement to maximize the efficiency of children's learning and activities.

[0695] Step 5:

[0696] The server uses a weather forecast API to retrieve weather data for the near future, assesses its impact on planned activities, especially those involving outdoor activities, and develops adjustment plans.

[0697] Step 6:

[0698] The server automatically contacts the operating organization according to pre-configured conditions and initiates transfer or cancellation procedures if necessary. It responds quickly using APIs and email.

[0699] Step 7:

[0700] The device notifies the user of an optimized schedule and provides important information such as what to bring and important points via push notifications. The user can then make the necessary preparations based on this information.

[0701] Step 8:

[0702] Users provide feedback on the provided schedule through a terminal app, and this information is sent to the server. The server collects user feedback and uses it to optimize the AI ​​agent for future improvements.

[0703] (Example 1)

[0704] 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".

[0705] In modern households, managing children's diverse activities and events is a significant burden for parents. In particular, overlapping schedules, schedule changes due to weather, and coordination with external organizations are time-consuming and require efficient management. Furthermore, comprehensively managing all this information and creating an efficient schedule is difficult.

[0706] 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.

[0707] In this invention, the server includes means for aggregating schedule information using digital communication technology, means for analyzing the schedule information and identifying duplicates and inconsistencies, and means for automatically optimizing the schedule based on priority. This reduces the management burden on users and enables the setting of an optimal schedule.

[0708] "Digital communication technology" refers to technologies that transmit information electrically or electronically, and is a means of enabling the collection and transmission of scheduled information.

[0709] "Means for aggregating schedule information" refers to methods and technologies for organizing, integrating, and centrally managing schedule-related information obtained from multiple sources.

[0710] "Methods for analyzing schedule information and identifying overlaps and inconsistencies" refers to technologies that analyze aggregated schedule information to detect cases where the same or different schedules overlap.

[0711] "A method for automatically optimizing schedules based on priority" refers to a technology that evaluates the importance and urgency of each appointment and generates an efficient schedule based on that information.

[0712] "Means of acquiring weather data and considering factors that affect activities" refers to methods of collecting weather information and using that information to provide information on the impact on plans and alternative options.

[0713] "A means of automatically contacting the operating organization and adjusting the schedule" refers to technology that communicates with the organization and, if necessary, automatically proposes or confirms schedule changes.

[0714] "Means of notifying users of information and collecting feedback" refers to methods of notifying users of the latest information and changes through their devices and collecting the feedback received.

[0715] "A means by which users input information using a terminal" refers to an interface that allows users to directly input schedules and other related information via a device.

[0716] "A method of using AI models to propose optimizations based on past information" refers to a method that utilizes artificial intelligence technology to analyze data accumulated in the past and generate proposals to optimize future schedules.

[0717] This invention is a schedule management system designed to streamline family management. The system is primarily implemented through the exchange of information via a server, terminals, and users.

[0718] The server utilizes digital communication technology to aggregate schedule information from diverse sources. For example, it not only collects household schedule information entered by users on their devices, but also retrieves information from external systems such as calendars and event management services via APIs. The server analyzes the aggregated information and automatically detects schedule overlaps and inconsistencies.

[0719] Next, the server optimizes the schedule based on priority. It utilizes an AI model to compare with past data and propose the optimal schedule. Specifically, it evaluates the priority and importance of extracurricular activities and family events, and adjusts the schedule accordingly.

[0720] Furthermore, the server acquires weather data and takes into account weather factors that may affect the schedule. For example, if the date of an outdoor activity needs to be changed due to weather, it can automatically propose alternative dates and automatically contact the organizing body.

[0721] The device notifies the user of the latest information and sends push notifications as needed. Users can easily check appointment details and provide feedback using the device. This feedback is collected on the server and used to optimize future schedules.

[0722] For example, if a user enters the date of their child's sports day via their device, the server will compare it with the weather forecast and proactively suggest alternative dates in case of rain, then contact the organizing body. An example of a prompt might be, "Please show me how to automatically notify me of an alternative date if it rains on my child's sports day."

[0723] With the above configuration, the present invention can reduce the management burden on users and achieve effective schedule management.

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

[0725] Step 1:

[0726] Users use a dedicated application on their device to input information about family schedules and their children's extracurricular activities. Specific inputs include the event name, date and time, location, and necessary items. The entered information is sent directly from the device to the server. The server records this information in a database, preparing it for subsequent processing.

[0727] Step 2:

[0728] The server collects additional schedule information through external calendar services and educational institution APIs. It sends API requests and retrieves information in a defined format. The data obtained from the APIs is transformed, organized, and integrated into existing databases. This ensures that accurate information is aggregated in real time.

[0729] Step 3:

[0730] The server analyzes the aggregated schedule information. This analysis checks for duplicate or inconsistent schedules and identifies them if found. Specifically, if there are different schedules at the same time, the server compiles them into a list and prepares to notify the user. The analysis results are stored in an internal log.

[0731] Step 4:

[0732] The server optimizes the schedule by considering priority. Based on the input information and aggregated data, the AI ​​agent refers to past data and proposes the most efficient schedule while evaluating the priority of each appointment. The AI ​​model enables rapid schedule creation. This proposal is stored within the system and used for subsequent notifications.

[0733] Step 5:

[0734] The server retrieves weather data using a weather forecast API. This retrieves information such as the forecasted weather, temperature, and probability of precipitation. The retrieved data is used to determine whether adjustments are necessary, especially for outdoor activities. A weather-based adjustment plan is generated, and the schedule is readjusted as needed.

[0735] Step 6:

[0736] The server will automatically contact the operating organization if necessary to have them consider the proposed adjustments. This contact will be made via API or email, automating the confirmation of transfer dates and other details. The response from the operating organization will be fed back into the next step.

[0737] Step 7:

[0738] The device receives organized information from the server and notifies the user via push notification. The notification includes details such as the latest event status, changes, and important notes. Users can also submit feedback, which the device sends back to the server to be used for optimizing future schedules.

[0739] (Application Example 1)

[0740] 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".

[0741] In modern society, managing household schedules and coordinating children's activity schedules requires considerable time and effort, and is particularly burdensome for working parents. Furthermore, information sharing to quickly respond to schedule changes due to weather or external factors is often inefficient. Under these circumstances, there is a need for efficient schedule management and smooth support for children's activities.

[0742] 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.

[0743] In this invention, the server includes means for collecting schedule information using data communication means, means for analyzing the schedule information to detect duplication and inconsistencies, means for automatically optimizing the schedule based on priority, means for acquiring weather information and considering factors that affect the schedule, means for automatically contacting the operating organization and adjusting the schedule, means for notifying the user and collecting feedback, and means for providing information according to the situation in the physical environment using physical machines for supporting human life. This reduces the burden on the user and enables efficient schedule management that smoothly supports children's activities.

[0744] "Data communication methods" is a general term for communication technologies and protocols used to collect scheduled information from external sources.

[0745] "Means for analyzing schedule information to detect duplication and inconsistencies" refers to a function that analyzes collected schedule data to find duplication and inconsistencies in its content.

[0746] "Automatically optimizing schedules based on priority" refers to a function that creates the most efficient schedule according to the importance and priority of each appointment.

[0747] "Means of acquiring weather information and considering factors that affect the schedule" refers to a function that uses weather data to make adjustments in order to minimize the impact of weather on the schedule.

[0748] "A means of automatically contacting the operating organization and adjusting the schedule" refers to a function that automatically contacts the relevant organizations and institutions and adjusts the schedule when changes to the schedule are necessary.

[0749] "Means of notifying users and collecting feedback" refers to functions that send push notifications and alerts to users and collect their opinions and responses.

[0750] "Means of providing information in accordance with the situation in the physical environment using physical machines for human life support" refers to functions that provide information based on the real environment using robots and assistant devices to support people's lives.

[0751] One embodiment of this invention is an integrated system for streamlining household schedule management and supporting children's daily activities. The server collects schedule information entered by users using data communication means. This includes household schedule information collected via a dedicated application on a smartphone or tablet. Furthermore, it obtains calendar information from external services and schedule information from educational institutions via APIs.

[0752] The server analyzes the collected schedule information to detect duplicates and inconsistencies. Using machine learning algorithms, it optimizes the schedule based on past data and user feedback. This process ensures effective schedule adjustments according to priority and importance.

[0753] Furthermore, the server acquires weather information and makes suggestions considering the impact of weather on the schedule. For example, in the case of outdoor activities, if bad weather is predicted, it can suggest a backup date and automatically contact the organizing body via API to adjust the schedule.

[0754] The device sends push notifications to the user, containing schedule updates and changes, lists of necessary preparations, and alerts about weather-related changes. Users can provide feedback, which will be used to optimize future services.

[0755] The server has the function of providing information tailored to the physical living environment, for example, using a robot designed to support human life. This robot presents appropriate information to the user in real time via voice and display.

[0756] As a concrete example, if a child's school trip is postponed due to rain, the system will suggest alternative dates and send a push notification to the parent's device. An example of a prompt message would be, "Your child's school trip this weekend has been postponed due to rain. Please suggest possible alternative dates."

[0757] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0758] Step 1:

[0759] The server collects schedule information from users using data communication methods. Schedules entered by users via a dedicated application on smartphones or tablets are sent to the server. This input information is received by the server as JSON data.

[0760] Step 2:

[0761] The server uses external APIs to retrieve additional appointment information from external calendar services and educational institutions. This information retrieved through the APIs is stored in an integrated data store, ensuring consistency between internal and external data.

[0762] Step 3:

[0763] The server analyzes the collected schedule information and detects duplicates and inconsistencies. For each entered schedule, it applies an algorithm that matches it using a specific identifier to detect duplicate items and conflicts. The output is formatted so that the analysis results can be used to improve scheduling.

[0764] Step 4:

[0765] The server uses machine learning algorithms to optimize the schedule. It adjusts the schedule according to priority, taking into account historical data and feedback. The resulting optimization becomes the basis data for the next calculation step.

[0766] Step 5:

[0767] The server retrieves weather information from external sources and evaluates factors that may affect the schedule. It analyzes the weather data and incorporates it as a variable to consider rescheduling activities if there is a possibility of impact on outdoor activities.

[0768] Step 6:

[0769] The server automatically contacts the operating organization as needed to adjust the schedule. Using the API, it proposes new dates based on weather and internal requirements. This confirms the adjustment of the plan and generates detailed contact information.

[0770] Step 7:

[0771] The device sends push notifications to the user regarding schedule changes and important information. The generated notification information is delivered to the device, allowing the user to stay informed of necessary information in real time.

[0772] Step 8:

[0773] The user reviews the notification and sends feedback to the server. The feedback information is then stored again in the database on the server and referenced for future schedule optimizations.

[0774] 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.

[0775] This invention provides a schedule management system that takes user emotions into account. By combining it with an emotion engine, it can meet more sophisticated user needs than conventional systems.

[0776] First, the user enters their schedule information via a dedicated application on their device. In the background of this input screen, an emotion engine analyzes data obtained from the user interface, evaluating the user's emotions in real time. For example, it determines whether the user is stressed or relaxed based on factors such as input speed, input content, and even idle time.

[0777] The server continuously collects schedule information using external calendar services and educational institution APIs, while simultaneously receiving user sentiment data sent from the device, and integrates all the data. This not only detects schedule overlaps and inconsistencies, but also enables prioritization that reflects the user's current sentiment state.

[0778] Furthermore, the server uses an AI agent to automatically optimize the schedule based on the collected data. In this process, it also takes into account the user's emotional data recognized by the emotion engine, and takes care not to overschedule the user during times when they are likely to feel stressed. Notifications are also adjusted based on the user's emotional state. For example, when the user is relaxed, new notifications are sent in a gentle tone, while when the user is stressed, the system avoids sending many notifications in a short period of time.

[0779] For example, if a user receives multiple notifications during a busy day, the emotion engine will detect that their stress levels are high and adjust the server to omit non-urgent notifications and deliver them all together later.

[0780] The emotion engine analyzes the user's emotions during feedback, and the AI ​​agent uses this data to improve future schedule optimization processes. This gives the system the ability to continuously improve the user experience and provide personalized schedule management.

[0781] Thus, by incorporating an emotion engine, this invention enables advanced schedule management that responds to the user's actual emotions, providing a richer learning and activity environment.

[0782] The following describes the processing flow.

[0783] Step 1:

[0784] Users enter new appointments using a dedicated application on their device. During this process, an emotion engine operates in the background, analyzing input speed, tone, and writing style to evaluate the user's emotional state in real time. The evaluation results are generated on the device as parameters such as stress, satisfaction, and anxiety.

[0785] Step 2:

[0786] The terminal sends the entered schedule information and sentiment data to the server. The server simultaneously collects schedule information from multiple external services and integrates and stores it in a database. The information is sorted by priority and time, and sentiment data is also recorded in association with it.

[0787] Step 3:

[0788] The server analyzes the schedule information collected using an AI agent to check for duplicates or inconsistencies. If detected, the AI ​​agent prioritizes events based on sentiment data to minimize user stress. It also refers to weather information and considers alternatives if outdoor events are expected to be affected.

[0789] Step 4:

[0790] The server configures notifications based on the optimization schedule created. Here, it utilizes parameters detected by the emotion engine to determine the optimal timing for receiving notifications. For example, if a user is stressed, the frequency of notifications is reduced and they are all sent at once.

[0791] Step 5:

[0792] The device delivers optimized schedules and tailored notifications to the user. Users can use the device's feedback interface to provide information about their actual experience and feelings. This feedback includes a wide range of factors, such as the appropriateness of notifications and satisfaction with the schedule.

[0793] Step 6:

[0794] The server incorporates user feedback and sentiment data into the AI ​​agent, which is then used to optimize future schedules. This allows the system to continuously learn and improve, enabling it to provide a more personalized user experience.

[0795] (Example 2)

[0796] 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".

[0797] Conventional schedule management systems have difficulty considering the emotional state of users, and do not adequately respond to users' stress levels or relaxation states. As a result, they cannot present schedules that are optimal for users' lives and work, which hinders the improvement of the user experience.

[0798] 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.

[0799] In this invention, the server includes means for collecting user schedule information using data communication means, means for analyzing the schedule information and emotional information to detect overlaps and inconsistencies, and means for automatically optimizing the schedule based on emotional information and priority. This enables flexible schedule management tailored to the user's emotional state.

[0800] "Data communication means" refers to communication technology used to send and receive user schedule information to and from a server, and involves data transmission via the internet or local network.

[0801] "Emotional information" refers to data that indicates the user's psychological and emotional state, and includes information obtained from factors such as input speed and idle time.

[0802] "Automatic schedule optimization" refers to the process of efficiently and appropriately organizing a user's schedule, taking into account priorities and emotional information.

[0803] "Weather information" refers to data that indicates weather conditions that may affect the execution of planned activities, and is obtained from weather forecasts and other sources.

[0804] "Operating organization" refers to an external organization or service provider involved in the user's schedule, and is the entity responsible for changing or adjusting the schedule.

[0805] "Notifications" refer to messages that inform users of schedules and related important information, and are provided by voice, text, or other means.

[0806] A "machine learning algorithm" is a mathematical method for efficiently performing analysis and prediction using past data and feedback.

[0807] "External systems" refer to external computer systems or services that interact with the system to retrieve or synchronize the user's schedule information.

[0808] To implement this invention, the user first inputs their schedule information using a dedicated application on their device. An emotion engine operates on the device, analyzing the user's emotional information from the speed and content of keyboard input, as well as the idle time. The hardware used is a general-purpose computer or smartphone, and the software includes an emotion engine module for performing emotion analysis.

[0809] The server collects user sentiment information sent from terminals via data communication methods and retrieves schedule information through interfaces with external calendar services and educational systems. The collected data is stored in a database, where it is processed to detect schedule overlaps and inconsistencies. The server is equipped with an AI agent that uses machine learning algorithms to optimize schedules based on past data and feedback.

[0810] Specifically, if the server detects that a user is under high stress during a busy period, it will refrain from sending non-urgent notifications and adjust its distribution to deliver them in bulk at an appropriate time. Furthermore, in its automatic schedule optimization, it selects times when users are less likely to experience stress and schedules appointments accordingly.

[0811] An example of a prompt message would be, "Please suggest the optimal notification schedule when the user is in a high-stress state." This instruction would be sent to the AI ​​model to generate an appropriate scheduling pattern.

[0812] This system allows users to enjoy personalized schedule management tailored to their individual emotional state, enabling them to live a less stressful and more efficient life.

[0813] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0814] Step 1:

[0815] The user enters their schedule information into a dedicated application on their device.

[0816] Specific operation: The user enters the title, date, time, and location of the appointment into text boxes on the application screen and clicks the submit button.

[0817] Input and Output: In this process, the input is text data entered by the user, and the output is schedule information stored in a temporary database on the terminal.

[0818] Step 2:

[0819] The device analyzes emotional data based on factors such as input speed and idle time.

[0820] Specific operation: The device uses an emotion engine to measure keyboard input speed and the amount of time the user spends looking at the screen. Based on this, it infers the user's emotional state.

[0821] Input and Output: The input consists of keyboard usage and elapsed time. Based on this, the data is analyzed, and the output is data indicating the user's emotional state.

[0822] Step 3:

[0823] The device sends the analyzed emotion data and schedule information to the server.

[0824] Specific operation: The device uploads data to the server via the internet.

[0825] Input and Output: The input is a set of emotion data and schedule information, and the output is a confirmation message indicating whether the data was successfully delivered to the server.

[0826] Step 4:

[0827] The server stores the received data and collects information about additional planned data from external systems.

[0828] Specific operation: The server stores sentiment data and schedule information in the database and calls an external API to retrieve further schedule information.

[0829] Input and Output: Input consists of data submitted by users and schedule information from external systems, while output is an integrated schedule information database.

[0830] Step 5:

[0831] The server automatically optimizes the schedule based on the collected data.

[0832] Specific operation: The server's AI agent applies machine learning algorithms and reorganizes the schedule, taking sentiment data into consideration.

[0833] Input and Output: Input consists of integrated database information and historical feedback, while output consists of optimized scheduling information.

[0834] Step 6:

[0835] The server adjusts notifications to the user based on their emotional state.

[0836] Specific operation: When the server suspects that the user is in a high-stress state, it performs a process to change the timing and content of notifications.

[0837] Input and Output: The input is the user's current emotional state data, and the output is a personalized notification message based on a schedule.

[0838] By using a generative AI model at each step, flexible and efficient scheduling is achieved.

[0839] (Application Example 2)

[0840] 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".

[0841] Traditional schedule management systems automatically optimize schedules without considering user emotions, often failing to address situations that cause stress or mental strain. Therefore, there is a need to improve the convenience of schedule management and make adjustments based on the user's emotional state.

[0842] 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.

[0843] In this invention, the server includes means for collecting schedule information using data communication means, means for analyzing the schedule information to detect duplication and inconsistencies, means for automatically optimizing the schedule based on priority, means for acquiring weather information and considering factors that affect the schedule, means for automatically contacting the operating organization and adjusting the schedule, means for notifying the user and collecting feedback, and means for performing schedule optimization and notification adjustment using an emotion engine that analyzes the user's emotional state. This makes it possible to adjust the schedule based on the stress level and emotional state felt by the user.

[0844] A "data communication means" is an interface for sending and receiving data over a network.

[0845] "Schedule information" refers to data related to the schedule entered by the user.

[0846] "Analysis" is the act of extracting useful information from obtained data.

[0847] "Detecting duplication and inconsistencies" means checking for multiple appointments at the same time or for any conflicting information.

[0848] "Automatically optimizing the schedule based on priority" means rationally organizing the schedule based on the importance and urgency of each item.

[0849] "Acquiring weather information and considering factors that may affect the plan" means collecting weather-related data and making decisions based on how it will affect the plan.

[0850] "Automatically contacting the operating organization and adjusting the schedule" means contacting the appropriate organization and making changes to the schedule.

[0851] "Notifying users and collecting feedback" refers to methods for informing users and obtaining their responses.

[0852] An "emotion engine" is an algorithm or program used to analyze a user's emotional state.

[0853] "Optimizing schedules and adjusting notifications" means streamlining schedules and setting appropriate notification frequencies and content.

[0854] The system for implementing this invention provides a schedule management application that takes user emotions into consideration. The server forms the core of this system, optimizing the user's schedule using various means and making adjustments according to their emotions.

[0855] The server collects schedule information entered from the user's terminal via data communication. This schedule information includes appointments entered directly by the user and information obtained through integration with external calendar systems. APIs are used for integration with external systems.

[0856] This data is analyzed on the server to detect duplicates and inconsistencies. Prioritized, automated optimization mechanisms streamline the schedule, ensuring efficient management of users' appointments.

[0857] Furthermore, the server acquires weather information and considers factors that may affect the schedule. This minimizes the impact of external factors such as weather on the schedule. It also automates communication with relevant organizations and adjusts the schedule as needed.

[0858] The emotion engine analyzes the user's emotional state and uses that data to optimize schedules and adjust notifications. This analysis utilizes data obtained from the interface, such as the user's input speed and idle time, to evaluate their stress and relaxation levels.

[0859] The server aggregates this data and delivers notifications to the user in the most optimal way. By collecting feedback and incorporating it into machine learning algorithms, the system is continuously improved, enabling a higher level of personalization.

[0860] For example, on busy workdays, the emotion engine can detect stress and reduce the user's burden by delivering only important notifications at the appropriate time. An example of a prompt for the generating AI model would be, "Please propose a method to optimize the schedule based on the user's emotional state and deliver important notifications at the appropriate time."

[0861] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0862] Step 1:

[0863] The terminal receives and collects schedule information entered by the user. This schedule information includes details such as date, time, location, and content. This information is transmitted to the server via data communication.

[0864] Step 2:

[0865] The server analyzes the received schedule information and detects duplicates and inconsistencies. The input for the analysis is the schedule information sent from the terminal, and the output includes the results of the judgment regarding the presence or absence of duplicates and inconsistencies. At this time, text analysis technology is used to verify the consistency of the data.

[0866] Step 3:

[0867] The server automatically optimizes the schedule based on priority. The input is the analysis results and the user's priority settings, and the output is the optimized schedule. It utilizes machine learning algorithms to achieve task arrangement according to importance.

[0868] Step 4:

[0869] The server acquires weather information and considers factors that may affect the schedule. The input is weather data obtained from an external API, and the server adjusts the schedule based on this data. The output is the affected schedule information.

[0870] Step 5:

[0871] The server automatically contacts the operating organization to coordinate the schedule. The input is the schedule coordinated within the server, and the output is a confirmation notification that the communication has been completed. The server uses a communication protocol to ensure appropriate communication is carried out.

[0872] Step 6:

[0873] The server uses an emotion engine to analyze the user's emotional state. Input consists of user usage data obtained from the terminal and external schedule information, and it outputs stress levels and relaxation levels. An emotion recognition algorithm is applied to this analysis.

[0874] Step 7:

[0875] The server adjusts notifications based on sentiment data. The input is analyzed sentiment data and a prioritized schedule, and the output is the adjusted notification plan. The frequency and timing of notifications are optimized according to sentiment.

[0876] Step 8:

[0877] Users receive notifications from the server and review their contents. The server collects feedback from these notifications and uses it to improve future services. Based on this feedback, the goal is to further optimize the notification strategy.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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."

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] The following is further disclosed regarding the embodiments described above.

[0900] (Claim 1)

[0901] A means for collecting schedule information using data communication means,

[0902] A means for analyzing the aforementioned schedule information to detect duplication and inconsistencies,

[0903] A means to automatically optimize the schedule based on priority,

[0904] Means for obtaining weather information and considering factors that may affect the schedule,

[0905] A means of automatically contacting the operating organization and coordinating the schedule,

[0906] A means of notifying users and collecting feedback,

[0907] A system that includes this.

[0908] (Claim 2)

[0909] The system according to claim 1, further comprising means of using a machine learning algorithm to take into account past data and feedback in optimizing the schedule.

[0910] (Claim 3)

[0911] The system according to claim 1, wherein the collection of the aforementioned schedule information includes an interface for linking with an external system using an API.

[0912] "Example 1"

[0913] (Claim 1)

[0914] A means of aggregating schedule information using digital communication technology,

[0915] A means for analyzing the aforementioned planned information and identifying duplications and inconsistencies,

[0916] A method to automatically optimize the schedule based on priority,

[0917] A means of acquiring weather data and considering factors that affect activities,

[0918] A method for automatically contacting the operating organization and coordinating the schedule,

[0919] A means of notifying users of information and collecting feedback,

[0920] A means by which users input information using a terminal,

[0921] A method for using AI models to propose optimizations based on past information,

[0922] A system that includes this.

[0923] (Claim 2)

[0924] The system according to claim 1, further comprising means of using a machine learning algorithm to consider past data and feedback in optimizing the aforementioned schedule.

[0925] (Claim 3)

[0926] The system according to claim 1, wherein the aggregation of the aforementioned schedule information includes a connection with an external system using a business interface.

[0927] "Application Example 1"

[0928] (Claim 1)

[0929] A means for collecting schedule information using data communication means,

[0930] A means for analyzing the aforementioned schedule information to detect duplication and inconsistencies,

[0931] A means to automatically optimize the schedule based on priority,

[0932] Means for obtaining weather information and considering factors that may affect the schedule,

[0933] A means of automatically contacting the operating organization and coordinating the schedule,

[0934] A means of notifying users and collecting feedback,

[0935] A means of providing information tailored to the situation in the physical environment using physical machines for supporting human life,

[0936] A system that includes this.

[0937] (Claim 2)

[0938] The system according to claim 1, further comprising means of using a machine learning algorithm to take into account past data and feedback in optimizing the schedule.

[0939] (Claim 3)

[0940] The system according to claim 1, wherein the collection of the aforementioned schedule information includes an interface for linking with an external system using an API.

[0941] "Example 2 of combining an emotion engine"

[0942] (Claim 1)

[0943] A means for collecting user schedule information using data communication means,

[0944] A means for analyzing the aforementioned planned information and emotional information to detect overlaps and contradictions,

[0945] A means to automatically optimize schedules based on emotional information and priorities,

[0946] Means for obtaining weather information and considering factors that may affect the schedule,

[0947] A means of automatically contacting the operating organization and coordinating the schedule,

[0948] A means of adjusting notifications and collecting feedback based on the user's emotional state,

[0949] A system that includes this.

[0950] (Claim 2)

[0951] The system according to claim 1, further comprising means of using a machine learning algorithm to take into account past data and feedback in optimizing the schedule.

[0952] (Claim 3)

[0953] The system according to claim 1, comprising an interface for linking with an external system in collecting the aforementioned scheduled information.

[0954] "Application example 2 when combining with an emotional engine"

[0955] (Claim 1)

[0956] A means for collecting schedule information using data communication means,

[0957] A means for analyzing the aforementioned schedule information to detect duplication and inconsistencies,

[0958] A means to automatically optimize the schedule based on priority,

[0959] Means for obtaining weather information and considering factors that may affect the schedule,

[0960] A means of automatically contacting the operating organization and coordinating the schedule,

[0961] A means of notifying users and collecting feedback,

[0962] A means of optimizing schedules and adjusting notifications using an emotion engine that analyzes the user's emotional state,

[0963] A system that includes this.

[0964] (Claim 2)

[0965] The system according to claim 1, further comprising means of using a machine learning algorithm to take into account past data and feedback in optimizing the schedule.

[0966] (Claim 3)

[0967] The system according to claim 1, wherein the collection of the aforementioned schedule information includes an interface for linking with an external system using an API. [Explanation of symbols]

[0968] 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 for collecting schedule information using data communication means, A means for analyzing the aforementioned schedule information to detect duplication and inconsistencies, A means to automatically optimize the schedule based on priority, Means for obtaining weather information and considering factors that may affect the schedule, A means of automatically contacting the operating organization and coordinating the schedule, A means of notifying users and collecting feedback, A system that includes this.

2. The system according to claim 1, further comprising means of using a machine learning algorithm to take into account past data and feedback in optimizing the schedule.

3. The system according to claim 1, wherein the collection of the aforementioned schedule information includes an interface for linking with an external system using an API.

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