system

Abstract

We provide the system. [Solution] A means of inputting information for entering the schedules of all family members, Information transmission means that receives the schedule entered by the information input means and saves it to a cloud database, An analysis means for analyzing schedules in the aforementioned cloud database and detecting and reporting duplicates and inconsistencies, A proposal generation means that generates improvement suggestions based on the detected problems, A notification means for notifying a home terminal of the generated proposal, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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] There is a problem that the schedule management of all family members is complicated, and especially when the parents' work, children's school events, hobbies, etc. overlap, it is very difficult to make adjustments for each. Furthermore, planning activities and events that all family members can enjoy also takes time, and as a result, the plans are often neglected. Also, it is difficult to continuously record important memories in the growth process of children, and as a result, precious memories are often lost.

Means for Solving the Problems

[0005] This invention provides an information input means for centrally managing the schedules of all family members, and an information transmission means for saving the entered schedules to a cloud database. It then constructs a system that analyzes the saved schedules, detects duplicates and inconsistencies, generates improvement suggestions based on these findings, and notifies a home terminal. Furthermore, it includes a function to collect family interest data and external event information, and generate and present recommended activities. In addition, it provides a means for automatically saving media photographed by family members to the cloud, analyzing and tagging it to generate a digital album that can be viewed on a home terminal.

[0006] An "information input means" is a device that provides an interface that allows users to input the schedules of their parents and children.

[0007] An "information transmission means" is a device for sending and storing entered schedules and data in a cloud-based database.

[0008] "Analysis means" refers to a device that has the function of analyzing schedule data in a cloud database and detecting duplicates and inconsistencies.

[0009] The "proposal generation means" is a device that automatically generates improvement measures to solve the detected scheduling problems.

[0010] A "notification device" is a device that has the function of sending the generated improvement suggestions to a home terminal and notifying the user.

[0011] A "data collection method" is a device used to collect information about a family's past interests, preferences, and events.

[0012] A "recommendation generation device" is a device that recommends activities suitable for the user based on collected data.

[0013] A "presentation device" is a device that presents recommended activities to a home terminal and provides the user with choices.

[0014] The "media storage means" is a device for automatically storing photos and videos taken by family members in the cloud.

[0015] The "tagging means" is a device having a function of automatically attaching tags based on events or dates and times to the stored media.

[0016] The "album generation means" is a device for constructing a digital album based on the analyzed media.

[0017] The "browsing means" is a device that displays the generated digital album on a home terminal so that the user can freely browse it.

Brief Description of the Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10]Shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It 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 the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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 a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] 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.

[0023] 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.

[0024] 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).

[0025] 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."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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".

[0039] This invention provides a system for centrally managing the schedules of all family members and for streamlining the recording of family activities and memories. This system consists of a server operating on the cloud and terminals used by each household.

[0040] The server collects schedule information submitted by users into a cloud database and manages it efficiently. During this process, the server uses its information analysis function to detect duplicate or inconsistent schedules and notifies users with suggestions for improvement. This system allows users to optimize their schedules without any extra effort.

[0041] The device provides a means of inputting information through a user interface, making it easy for parents and children to enter their schedules. Furthermore, by receiving notifications sent from the server, the device can promptly check for important events and schedule changes.

[0042] Furthermore, the server collects and maintains a database of the family's past interests and events. Based on this, the server suggests activities tailored to each user. For example, it might recommend outdoor activities or cultural experiences that the family can enjoy, taking into account holiday weather and local events. These suggestions are displayed on the device, and the user has the ability to select them.

[0043] Regarding the recording of memories, the device automatically uploads family photos and videos to the cloud, where the server analyzes and tags them. This allows the server to generate a series of digital albums, organizing family growth and special events. These albums are viewable on the device and are designed to be accessible to all family members.

[0044] For example, when a user enters the date of their child's school performance on their device, that information is sent to the server and compared with the parent's work schedule. If there is a conflict, the server notifies the parent's device with a suggested adjustment. At the same time, it suggests nearby weekend events as family activities. Users can effectively manage their family schedule and record memories by checking this information on their device.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user uses their device to open the schedule input screen and enters appointments such as parents' work, children's school events, and extracurricular activities. The device temporarily saves this information.

[0048] Step 2:

[0049] The terminal sends the entered schedule information to a server in the cloud. Here, data privacy is ensured through security protocols.

[0050] Step 3:

[0051] The server saves the received schedule information to a cloud database. After saving, it runs an algorithm to detect duplicates and inconsistencies.

[0052] Step 4:

[0053] If the server detects scheduling conflicts or inconsistencies, it generates optimal improvement suggestions and determines which appointments should be changed.

[0054] Step 5:

[0055] The server generates improvement suggestions and notifies the terminal. The terminal displays this notification on its user interface, allowing the user to confirm the revised schedule.

[0056] Step 6:

[0057] If the user accepts the suggestion or makes further modifications, they will resend the changes to the server from their device.

[0058] Step 7:

[0059] The server analyzes the family's past data and external event information to suggest activities the family can enjoy. This includes weather data and local event information.

[0060] Step 8:

[0061] The terminal receives the server's suggestions and presents them to the user via the user interface. The user can then select the activity they wish to participate in.

[0062] Step 9:

[0063] The device sends user feedback and activity participation choices to the server, which then stores the results in a database.

[0064] Step 10:

[0065] Photos and videos taken by users during everyday events are automatically uploaded to the cloud by their device.

[0066] Step 11:

[0067] The server analyzes media uploaded to the cloud and tags it based on date and event. Furthermore, it generates digital albums.

[0068] Step 12:

[0069] The device receives the generated digital album and displays it in a user-friendly format. Through this album, users can easily reminisce about their memories.

[0070] (Example 1)

[0071] 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."

[0072] In modern households, effectively managing everyone's schedules and planning fulfilling family activities is crucial. However, centrally managing everyone's schedules is not easy, often resulting in schedule overlaps and inconsistencies. Furthermore, methods for organizing and preserving family memories are not common, leading to challenges such as the loss of records and difficulty in accessing them.

[0073] 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.

[0074] In this invention, the server includes means for storing information, means for analyzing information, and means for generating improvement suggestions. This enables centralized management and optimization of the schedules of all family members. Furthermore, by providing activity suggestions, it is possible to recommend effective activities based on the family's past interests and external information, and it is possible to provide a system that organizes, saves, and easily accesses memories.

[0075] A "terminal device" is a device used by users to input information and receive notifications.

[0076] A "server device" is a central computer that stores and analyzes data received from terminal devices.

[0077] An "analysis device" is a device that analyzes accumulated data and has the function of detecting schedule overlaps and inconsistencies.

[0078] A "proposal device" is a device that has the function of generating revised or improved suggestions for the user based on the analysis results.

[0079] A "notification device" is a system for transmitting generated proposals and revisions to the user's terminal device.

[0080] A "data collection device" is a device that has the function of acquiring and storing past activity history and external event information.

[0081] A "recommended device" is a device that has the function of suggesting family-oriented activities and events based on collected data.

[0082] A "display device" is a device that visualizes proposed activities and generated albums for the user.

[0083] A "storage device" is a storage system for automatically storing images and videos.

[0084] A "classification device" is a device that analyzes stored media and classifies it based on specific events or themes.

[0085] A "generation device" is a device that has the function of creating a digital album based on the analyzed media.

[0086] A "viewing device" is a device that allows users to access and view the generated digital album.

[0087] This invention is a system for effectively managing family schedules and memories. The system primarily consists of terminal devices and a server device.

[0088] The server uses high-performance computer equipment to store and analyze information. Specifically, it uses cloud services and database technologies to store and analyze a wide range of data. This includes using programming languages ​​such as Python to analyze and classify the data. The server also utilizes open APIs to retrieve external event information and provide recommendations.

[0089] The device functions as a means for users to input information and receive notifications. This includes widely used mobile devices such as smartphones and tablets. The user interface is developed as an application using React Native, allowing for intuitive operation. The device also features an interface for automatically capturing images and videos and uploading them to a server. Specifically, the device uploads media to cloud storage such as Amazon S3.

[0090] Users input their daily schedules into their devices. For example, by entering the date of their child's school performance, that information is sent to the server. The server analyzes this data and compares it with the parent's schedule to check for any overlaps. If there are overlaps, the server generates a suggested adjustment and notifies the parent. Similarly, based on past data, the server retrieves information on nearby activities and suggests events that the whole family can enjoy.

[0091] An example prompt might be, "Check if there are any conflicts in today's schedule and suggest nearby events that the family can enjoy." Using this prompt, the server will perform appropriate analysis and make suggestions.

[0092] This system allows users to efficiently manage their family's schedules and plan enriching family experiences.

[0093] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0094] Step 1:

[0095] The user enters schedule information into the terminal. This information includes date, time, location, and event details. The user interface is designed to allow intuitive input of information in a calendar format. Immediately after input, the information is converted to JSON format and ready to be sent to the server.

[0096] Step 2:

[0097] The terminal sends the entered schedule information to the server. The data is transferred to the cloud server in JSON format via the HTTP protocol. This process allows the server to receive data that can be parsed in the next step.

[0098] Step 3:

[0099] The server analyzes the received schedule information. While storing the information in a database, it uses an information analysis algorithm to detect duplicates and inconsistencies. A Python script then runs to identify related schedules. Based on this analysis, data integrity is verified.

[0100] Step 4:

[0101] Based on the analysis results, the server generates improvement suggestions for problematic schedules. For example, if there are scheduling overlaps, it considers alternative time options and creates adjustment plans. The suggestions are recorded in the database and ready for notification.

[0102] Step 5:

[0103] The server notifies the user's device of the generated suggestions. Specific suggestions are delivered to the user via email or in-app notifications. Notifications are delivered quickly, ensuring the user is ready to take immediate action.

[0104] Step 6:

[0105] The server analyzes past interests and external event information to suggest activities that fit the user. Using newly collected local event information from open APIs, it generates suggestions based on an AI model. These suggestions are prioritized based on the user's interests and schedule.

[0106] Step 7:

[0107] The user reviews the suggested activities on their device and selects the appropriate one. The selected activity information is sent to the server and automatically added to the schedule. This selection process is designed with usability in mind and can be completed quickly.

[0108] Step 8:

[0109] The device automatically uploads family photos and videos to the cloud. It sorts media stored on the device in the background and transfers it to a storage server. Cloud storage like Amazon S3 is used, creating a user-friendly environment.

[0110] Step 9:

[0111] The server analyzes uploaded media and generates albums. Machine learning algorithms are used to classify and tag photos and videos. This creates digital albums organized by time and event, improving the user's digital experience.

[0112] Step 10:

[0113] Users can view digital albums generated on their devices. An interactive and user-friendly interface is provided, making it easy for the whole family to reminisce about past memories. Albums are updated in real time and are accessible at any time.

[0114] (Application Example 1)

[0115] 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."

[0116] In today's busy families, there is a need to efficiently manage the schedules of all family members and optimize activities by utilizing local information. Another challenge is organizing everyday memories as digital data, making them easily accessible to all family members. This will help avoid conflicts in individual schedules and facilitate smooth family activities. Furthermore, it is necessary to use the acquired information to build a richer daily life.

[0117] 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.

[0118] In this invention, the server includes information acquisition means for inputting the schedules of multiple users, information storage means for storing the schedules acquired by the information acquisition means, and information optimization means for acquiring external information based on regional information and optimizing the schedule. This enables efficient centralized management of the entire family's schedule and allows for optimal activity suggestions utilizing external information.

[0119] "Information acquisition means" refers to a function within the system that provides an interface for users to input their schedules and accepts those schedules.

[0120] "Information storage means" refers to a function for securely saving acquired schedules on the cloud or locally.

[0121] A "duplicate detection method" is a function that analyzes saved schedules and checks for duplicates or inconsistencies.

[0122] A "means for generating improvement measures" is a function for creating solutions based on overlaps and contradictions in the schedule.

[0123] A "notification method" is a function that transmits generated improvement measures and important information to the user's device.

[0124] "Information optimization means" refers to functions that optimize schedules based on local and external information.

[0125] A "recommendation generation method" is a function that analyzes activity data and external information to recommend the most suitable activities for the user.

[0126] "Presentation means" refers to a function for displaying generated activity recommendations and information on the user interface.

[0127] A "digital data storage method" is a function that automatically saves captured photos and videos in digital format.

[0128] "Information processing means" refers to a function that analyzes stored digital data and adds specific event information.

[0129] An "album presentation method" is a function that displays the generated digital album to the user and makes it viewable.

[0130] The "activity suggestion method" is a function that recommends activities from a digital album generated based on the user's selection.

[0131] This invention provides a system for efficiently managing family schedules and supporting the optimization of activities using local information. This system includes a server and user devices and operates in a cloud environment. Specific embodiments are described below.

[0132] The server is equipped with information acquisition means for receiving each user's schedule data. This means receives schedule data entered from the user's device via the cloud and securely stores it using information storage means. The stored data is analyzed by duplicate detection means to automatically detect inconsistencies and schedule conflicts. Furthermore, based on these detection results, improvement measure generation means generates recommendations to resolve the conflicts and communicates them to the user via notification means.

[0133] Furthermore, information optimization methods incorporate external data such as local and weather information to optimize each family's schedule. This optimization makes it easier for users to plan meaningful activities. For example, it can suggest outdoor activities based on weekend weather information.

[0134] User devices are equipped with recommendation generation capabilities, enabling them to suggest activities and local events tailored to each individual. These suggestions are displayed on the user interface through the suggestion system, allowing users to easily incorporate them into their schedules.

[0135] In addition, the captured visual data is automatically saved to the cloud by a digital data storage device. Subsequently, an information processing device analyzes the data and tags it in relation to the event. The generated digital album is displayed on the user's device via an album display device, providing a system that allows users to easily enjoy family memories.

[0136] For example, if a user enters a prompt such as, "Please recommend some outdoor activities for this weekend," the system will provide optimal suggestions considering weather and event information. This functionality is automatically implemented by inputting prompt text using a generative AI model.

[0137] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0138] Step 1:

[0139] The user enters appointment information on their device.

[0140] The entered schedule data is sent to the server via an information retrieval device. The server receives this data and securely stores it in the cloud using an information storage device.

[0141] Step 2:

[0142] The server analyzes the stored schedule data.

[0143] A duplicate detection mechanism is used to check for conflicts with other appointments entered at the same time. If duplicates or inconsistencies are found, the information is sent to the improvement plan generation mechanism.

[0144] Step 3:

[0145] The improvement solution generation mechanism generates recommended solutions for resolving contradictions.

[0146] Specifically, a schedule adjustment proposal is created, taking priorities into consideration. This proposal is then sent to the user's device via a notification system. The output provides the adjusted schedule proposal.

[0147] Step 4:

[0148] The user device receives the notification and displays it in the user interface.

[0149] The user will review this and manually adjust the schedule if necessary.

[0150] Step 5:

[0151] Information optimization tools acquire local weather information and event information.

[0152] Based on this external information, the server re-evaluates the user's original schedule and generates suggestions for optimal activities.

[0153] Step 6:

[0154] The recommendation generation system generates activity recommendations tailored to each individual user.

[0155] The server generates recommendations based on past user behavior data and interests, and displays them on the user interface using a presentation tool.

[0156] Step 7:

[0157] Visual data captured by the user is automatically saved.

[0158] Digital data storage devices store data in the cloud, and it is analyzed through information processing devices. Tagged data is then generated as a digital album.

[0159] Step 8:

[0160] The album presentation method displays this album on the user's device.

[0161] Users can browse this album and reminisce about their memories. Additionally, the activity suggestion feature provides recommended activity ideas based on the user's choices.

[0162] Step 9:

[0163] When a user inputs a prompt into the generated AI model, the system provides the most appropriate information suggestions in response.

[0164] The system processes data based on user requests and generates the necessary output information. For example, in response to a prompt such as "What are some recommended indoor events nearby?", the system returns the corresponding event information.

[0165] 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.

[0166] This invention proposes a system that not only improves schedule management for the entire family but also provides a more personalized experience to the user by combining it with emotion recognition technology.

[0167] This system operates through family terminals and a server running on the cloud. The terminals have information input capabilities, allowing parents and children to enter their daily schedules. The entered schedules are transmitted from the terminals to the server via an information transmission device and stored in a cloud database.

[0168] The server is equipped with analytical tools to analyze stored schedule data and detect duplicates and inconsistencies. Based on the analysis results, it generates schedule improvement suggestions and sends these suggestions to the terminal via a notification system. This cycle allows users to optimize their schedule management.

[0169] Furthermore, by combining it with an emotion engine, the system achieves a new level of personalization. The device analyzes the user's voice and facial expressions, and the emotion engine recognizes their emotions. This emotion data is sent to and stored on a server. Based on this data, the server utilizes a suggestion update mechanism to generate suggestions tailored to the user's current emotional state. For example, if the system detects that the user is feeling stressed, it can suggest relaxing activities or schedule adjustments.

[0170] It also features emotional integration, which combines past interest and emotional data of the family, further personalizing the suggestions. This allows the system to consider the user's past preferences and present the most suitable activities.

[0171] For example, if the emotion engine determines that a child is feeling stressed in their new school environment, the server will suggest a parent-child event that can help the child relax. This suggestion will be displayed on the device, and the user can choose to participate.

[0172] The system also integrates a memory recording function, automatically uploading photos and videos taken by users to the cloud via media storage. The server analyzes this data and tags it in relation to events, creating a digital album. Users can view this album through their device, recording family growth and special moments. In this way, a new system incorporating emotional elements enables a richer and more seamless family life.

[0173] The following describes the processing flow.

[0174] Step 1:

[0175] The user opens the schedule input screen on their device and enters a new appointment or event. The device temporarily saves this information to its memory.

[0176] Step 2:

[0177] The terminal sends the entered schedule information to a server in the cloud. During this process, data security is ensured based on security protocols.

[0178] Step 3:

[0179] The server saves the received schedule information to a cloud database. The saved information is then analyzed to detect duplicates and inconsistencies.

[0180] Step 4:

[0181] The server generates schedule improvement suggestions based on the analysis results. In particular, it creates suggestions to resolve simultaneous events and time constraints.

[0182] Step 5:

[0183] The server generates improvement suggestions and sends them to the home terminal using a notification system. The terminal displays these suggestions in its user interface, and the user reviews the content.

[0184] Step 6:

[0185] The user accepts the proposal and enters approval or modification instructions via their device. The modifications are then resent from the device to the server.

[0186] Step 7:

[0187] To recognize the user's emotions, the device uses built-in sensors and cameras to acquire voice and facial expression data. This data is then input into the emotion engine.

[0188] Step 8:

[0189] The emotion engine analyzes the user's emotions in real time and sends that data to the server. The server stores this data and updates activity and schedule suggestions to match the user's current emotional state.

[0190] Step 9:

[0191] The server presents suggestions to the terminal based on emotional data. These suggestions include relaxation activities and appropriate events tailored to the user's emotional state.

[0192] Step 10:

[0193] The device receives feedback from the user and sends it to the server. The server uses this feedback to improve the accuracy of future suggestions.

[0194] Step 11:

[0195] Photos and videos taken by users on a daily basis are automatically uploaded to the cloud by their devices. The server then performs media analysis and tagging on these videos and associates them with events.

[0196] Step 12:

[0197] The server generates a digital album based on the analyzed media data and sends it to the user's device. The user can then view this album and enjoy their memories.

[0198] (Example 2)

[0199] 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".

[0200] There is a need to comprehensively improve the scheduling of the entire family, eliminate overlaps and contradictions in daily schedules, and provide a personalized user experience for each member by offering suggestions based on individual emotions and past interests. Furthermore, a system is needed to efficiently save and manage family memories and allow for easy recollection. These challenges remain unresolved in many existing systems.

[0201] 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.

[0202] In this invention, the server includes information transmission means, data analysis means, and emotion recognition means. This enables the detection of overlaps and inconsistencies in each member's schedule and the provision of optimized suggestions. Furthermore, emotion recognition technology allows for personalized suggestions tailored to the user's emotions, and by automatically saving and tagging family memories, it is possible to generate a digital record collection that can be easily viewed.

[0203] An "information input means" is a mechanism that provides an interface for all family members to input their schedules.

[0204] "Information transmission means" refers to a communication means for receiving entered schedules and saving them to network data storage.

[0205] "Data analysis means" refers to processing means for analyzing schedules within network data storage and detecting and reporting duplicates and inconsistencies.

[0206] The "proposal generation method" is an algorithm for generating schedule improvement suggestions based on the detected problems.

[0207] A "notification mechanism" is a system for notifying the user's terminal of the generated proposal.

[0208] "Emotion recognition means" refers to technology that analyzes a user's voice and facial expressions to recognize emotional data.

[0209] A "proposal update method" is a method for updating schedule proposals based on sentiment data.

[0210] A "data collection method" is a system for collecting data on a family's past interests and external activities.

[0211] A "recommendation generation method" is a process for generating suitable activities based on collected information.

[0212] A "presentation means" is a device for displaying recommended activities on the user's terminal.

[0213] "Emotional integration methods" are techniques for integrating emotional data with past interest data to personalize suggestions.

[0214] "Media storage means" refers to technology for automatically saving images and videos to network storage media.

[0215] "Tagging" refers to a technology that analyzes stored media and labels it as a specific event.

[0216] An "album generation method" is a method for generating a digital record collection based on analyzed media.

[0217] "Viewing method" refers to an interface that allows users to view the generated digital record collection on their terminals.

[0218] This invention is a system that manages the schedules of all family members and provides personalized suggestions based on their emotions, and is primarily implemented using a user's device and a server operating in the cloud. The device is equipped with means for inputting information to enter the family's schedule, including a touchscreen and voice input functionality. For example, if the user says, "Let's have a picnic in the park on Saturday," the device converts the voice data into text and sends it to the server.

[0219] The server stores the received schedule data in cloud data storage and uses data analysis tools to detect overlaps and inconsistencies in appointments. To do this, the server utilizes natural language processing technology to analyze the input data. Once the analysis is complete, improvement suggestions are sent to the user's terminal via a notification system. These improvement suggestions are displayed on the terminal as notifications such as, "How about changing your library appointment to 12:00?"

[0220] Furthermore, the device uses a microphone and camera to capture the user's voice and facial expressions, analyzes the data through emotion recognition, and sends the emotion data to a server. This data is analyzed in real time by the server, and a suggestion update mechanism generates more appropriate suggestions based on the user's emotions. For example, if the system detects that the user is feeling stressed, it might suggest, "Try taking a relaxation yoga class this weekend."

[0221] The server personalizes these suggestions and activities using the user's past interest and emotional data. In particular, it uses emotional integration techniques to generate more detailed and personalized suggestions that take into account the user's past experiences and preferences. Based on this process, prompts such as "How can I suggest relaxing activities when the user is feeling stressed?" are used.

[0222] The device further utilizes media storage means to automatically save images and videos taken by the user on the network, and to tag them and generate digital archives. A server-based tagging system analyzes the captured content and labels each event. As a result, users can view digital albums associated with specific events and easily reminisce about past memories.

[0223] This series of processes allows users to efficiently manage their daily schedules, receive emotionally resonant suggestions, and record family memories. This enables the whole family to enjoy a richer, more personalized life.

[0224] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0225] Step 1:

[0226] Users enter their schedules using a terminal. They can input their daily plans via a touch interface or voice input. This input is converted to text and sent to the server via the information input device. For example, if a user voice-inputs "Picnic at the park at 10am on Saturday," the terminal converts the voice data into text data and sends it to the server.

[0227] Step 2:

[0228] The server stores the received text data in network data storage. Data transmitted via the information transmission means is then analyzed by the data analysis means to detect duplicates and inconsistencies. Natural language processing algorithms are used to analyze the data and identify overlapping appointments on the same date and time. For example, if it is determined that "there are two events starting at 10:00," the nature of the overlap is clarified.

[0229] Step 3:

[0230] The server generates improvement suggestions based on the detected duplicates and inconsistencies. The suggestion generation mechanism operates and calculates the optimal solution through an algorithm. For example, a suggestion such as "change the library visit time to 12:00" is generated. This suggestion is sent from the server to the terminal via a notification mechanism, and the user can review the suggested improvement.

[0231] Step 4:

[0232] The device collects user emotional data using emotion recognition technology. Using the camera and microphone, it analyzes the user's facial expressions and voice tone, and sends this data to a server. The emotional data is further analyzed on the server to determine the user's emotional state. For example, it might obtain emotional data indicating that "the user is nervous."

[0233] Step 5:

[0234] The server updates its suggestions based on sentiment data. Using a suggestion update mechanism, it creates personalized suggestions through a generative AI model. For example, if a user is feeling stressed, a suggestion such as "We recommend a relaxing yoga class for the weekend" might be generated.

[0235] Step 6:

[0236] The server integrates the family's past interest and emotional data to further personalize suggestions. Emotional integration recommends activities based on past activities and current emotions. Users can view these recommended activities on their device and select them as appropriate.

[0237] Step 7:

[0238] The device automatically uploads photos and videos taken by the user to the network. The captured data is stored using media storage methods, and the server analyzes it. The analyzed data is tagged by event, and a digital album is generated. This album can be viewed through the device, allowing family members to reminisce about cherished memories.

[0239] (Application Example 2)

[0240] 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".

[0241] In today's society, family schedules have become increasingly complex, requiring smooth coordination. However, conventional schedule management systems have the problem of failing to consider family members' feelings and past interests, making it difficult to provide optimal suggestions tailored to individual circumstances. Furthermore, there has been a lack of systems for efficiently organizing memories and making them easily accessible at any time.

[0242] 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.

[0243] In this invention, the server includes information input means, analysis means, and emotion analysis means. This enables personalized suggestions that take into account not only the schedules of all family members but also their emotional data. Furthermore, by automatically saving video data and identifying specific events, the creation and viewing of digital memory collections becomes easier.

[0244] An "information input method" is a system for inputting the schedules and related information of all family members through a terminal or device.

[0245] The "information transmission means" refers to a function that sends the entered family schedule information to a server and stores it in a large-scale data management device.

[0246] "Analysis means" refers to a mechanism for analyzing schedule information stored in a large-scale data management system to detect schedule overlaps and inconsistencies.

[0247] The "proposal generation means" is a function that generates improved proposals based on the problems detected by the analysis means.

[0248] A "notification mechanism" is a system for transmitting generated suggestions to a home information display device to inform the user.

[0249] "Emotion analysis means" refers to technology that analyzes the user's voice and facial expression data to recognize their emotions. This makes it possible to generate suggestions that are tailored to the user's emotions.

[0250] "Data collection means" refers to functions for collecting data on a family's past interests and external events.

[0251] A "recommendation generation method" is a function that generates optimal recommended actions for families based on information obtained through data collection methods.

[0252] The "presentation means" is a mechanism that displays recommended actions created by the recommendation generation means on a home information display device so that the user can confirm them.

[0253] "Media storage means" refers to a function that automatically saves video data taken by family members to a large-scale data management device.

[0254] "Identification means" refers to a function that analyzes video data stored in media storage means and tags specific events or occurrences.

[0255] A "collection and generation method" is a system for creating and organizing digital memory collections based on analyzed video data.

[0256] "Viewing method" refers to a function that allows the generated digital collection of memories to be viewed on a home information display device.

[0257] The system for realizing this invention includes a home information display device, a server, a large-scale data management device, a camera, a microphone, and related software. The home information display device functions as an information input means for receiving input from a user and includes an information transmission means for transmitting the input data to the server.

[0258] The server analyzes information stored in a large-scale data management system, detects scheduling overlaps and inconsistencies, and further analyzes the user's voice and facial expression data using emotion analysis tools to recognize their emotions. This allows the server to generate personalized suggestions tailored to the user's emotions. For example, if a user is stressed, the server suggests relaxing activities. Such suggestions are notified to a home information display device, making it easier for the user to understand what actions are appropriate.

[0259] Furthermore, it is equipped with data collection and recommendation generation capabilities, which generate optimal recommended actions based on past interest data and external event information. In addition, it automatically saves and organizes family video data using media storage and identification capabilities to create a digital memory collection that can be viewed on a home information display device. Specifically, photos and videos from summer vacation trips will be automatically organized and made viewable.

[0260] The specific hardware used includes smart displays as home information display devices, cloud-based servers for data analysis, and microphones and cameras for emotion recognition. For software, Google® Cloud Speech-to-Text and Amazon Lex are used for speech recognition, while Microsoft® Azure® Emotion API is used for emotion analysis.

[0261] Example of a prompt:

[0262] "You are a highly hospitable home robot. Support the family's daily schedule management and provide relaxing suggestions based on their emotions. For example, how can you suggest relaxing music when family members are feeling stressed?"

[0263] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0264] Step 1:

[0265] The home information display device (terminal) accepts schedule and task input from the user. The input data is sent to a server using an information transmission method, preparing data for scheduling overlaps and sentiment analysis. Since voice input is also included, Google Cloud Speech-to-Text is used. The output of this step is the user's schedule information and voice data.

[0266] Step 2:

[0267] The server stores the received data in a large-scale data management system. Then, it analyzes the stored data using analytical tools to detect schedule overlaps and inconsistencies. The problems identified as a result of the analysis are then prepared as input data for the next step. The output of this step is the analyzed schedule data.

[0268] Step 3:

[0269] The server uses emotion analysis tools to analyze the user's emotions from voice and facial expression data. Using voice and image data as input, it performs analysis using the Microsoft Azure Emotion API to extract the emotions the user may be experiencing. The output of this step is information about the emotional state.

[0270] Step 4:

[0271] Based on the analyzed schedule data and emotional state information, the server generates emotionally appropriate improvement suggestions and recommended actions using a suggestion generation mechanism. For example, if it is determined that the user is feeling stressed, it will suggest relaxing activities. This process is performed using a generation AI model based on prompt statements. The output of this step is improvement suggestions.

[0272] Step 5:

[0273] The server notifies the home information display device of the generated suggestions via an information transmission means. The terminal displays the received suggestions to the user and provides an opportunity to select the suggested activities or actions. The output of this step is the suggestion information displayed to the user.

[0274] Step 6:

[0275] The terminal automatically saves video data captured by the user to a large-scale data management system using media storage means. The server analyzes the saved data using identification means and tags specific events. This tagged data becomes the input data for the next step. The output of this step is tagged media information.

[0276] Step 7:

[0277] The server uses tagged video data to create a digital memory collection using a collection generation method. The generated digital memory collection can be viewed on a home information display device, allowing users to easily reminisce about family memories. The output of this step is a viewable digital memory collection.

[0278] 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.

[0279] 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">)Generative AIs such as the above can be mentioned. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including instructions is input into the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is input. The data generation model 58 makes inferences on the input inference data according to the instructions indicated by the prompt, and outputs the inference results in data formats such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization, etc.

[0280] In the above embodiment, an example form in which specific processing is performed by the data processing device 12 is given, but the technology of the present disclosure is not limited to this, and specific processing may be performed by the smart device 14.

[0281] [Second Embodiment]

[0282] FIG. 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0283] As shown in FIG. 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.

[0284] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of the "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network), etc.

[0285] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. Also, the microphone 238, the speaker 240, and the camera 42 are connected to the bus 52.

[0286] The microphone 238 receives instructions etc. from the user 20 by receiving the voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into voice data, and outputs the voice data to the processor 46. The speaker 240 outputs voice according to an instruction from the processor 46.

[0287] The camera 42 is a small digital camera equipped with an optical system such as a lens, an aperture, and a shutter, and an imaging device such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and images the surroundings of the user 20 (for example, an imaging range defined by an angle of view corresponding to the visual field width of a general healthy person).

[0288] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0289] FIG. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in FIG. 4, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32.

[0290] 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.

[0291] 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.

[0292] 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.

[0293] 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".

[0294] This invention provides a system for centrally managing the schedules of all family members and for streamlining the recording of family activities and memories. This system consists of a server operating on the cloud and terminals used by each household.

[0295] The server collects schedule information submitted by users into a cloud database and manages it efficiently. During this process, the server uses its information analysis function to detect duplicate or inconsistent schedules and notifies users with suggestions for improvement. This system allows users to optimize their schedules without any extra effort.

[0296] The device provides a means of inputting information through a user interface, making it easy for parents and children to enter their schedules. Furthermore, by receiving notifications sent from the server, the device can promptly check for important events and schedule changes.

[0297] Furthermore, the server collects and maintains a database of the family's past interests and events. Based on this, the server suggests activities tailored to each user. For example, it might recommend outdoor activities or cultural experiences that the family can enjoy, taking into account holiday weather and local events. These suggestions are displayed on the device, and the user has the ability to select them.

[0298] Regarding the recording of memories, the device automatically uploads family photos and videos to the cloud, where the server analyzes and tags them. This allows the server to generate a series of digital albums, organizing family growth and special events. These albums are viewable on the device and are designed to be accessible to all family members.

[0299] For example, when a user enters the date of their child's school performance on their device, that information is sent to the server and compared with the parent's work schedule. If there is a conflict, the server notifies the parent's device with a suggested adjustment. At the same time, it suggests nearby weekend events as family activities. Users can effectively manage their family schedule and record memories by checking this information on their device.

[0300] The following describes the processing flow.

[0301] Step 1:

[0302] The user uses their device to open the schedule input screen and enters appointments such as parents' work, children's school events, and extracurricular activities. The device temporarily saves this information.

[0303] Step 2:

[0304] The terminal transmits the input schedule information to the server on the cloud. Here, the privacy of the data is ensured through a security protocol.

[0305] Step 3:

[0306] The server saves the received schedule information in the cloud database. After saving, an algorithm for detecting duplicates and contradictions is executed.

[0307] Step 4:

[0308] If the server detects a duplicate or contradiction in the schedule, it generates an optimal improvement proposal and determines which schedule should be changed.

[0309] Step 5:

[0310] The server notifies the terminal of the improvement proposal generated. The terminal displays this notification on the user interface and allows the user to confirm the modified schedule.

[0311] Step 6:

[0312] If the user accepts the proposal or makes further modifications, the terminal sends the modified content to the server again.

[0313] Step 7:

[0314] The server analyzes the family's past data and external event information and proposes activities that the family can enjoy. This includes weather data and local event information.

[0315] Step 8:

[0316] The terminal receives the server's proposal and presents it to the user through the user interface. The user can select the activities they want to participate in.

[0317] Step 9:

[0318] The device sends user feedback and activity participation choices to the server, which then stores the results in a database.

[0319] Step 10:

[0320] Photos and videos taken by users during everyday events are automatically uploaded to the cloud by their device.

[0321] Step 11:

[0322] The server analyzes media uploaded to the cloud and tags it based on date and event. Furthermore, it generates digital albums.

[0323] Step 12:

[0324] The device receives the generated digital album and displays it in a user-friendly format. Through this album, users can easily reminisce about their memories.

[0325] (Example 1)

[0326] 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."

[0327] In modern households, effectively managing everyone's schedules and planning fulfilling family activities is crucial. However, centrally managing everyone's schedules is not easy, often resulting in schedule overlaps and inconsistencies. Furthermore, methods for organizing and preserving family memories are not common, leading to challenges such as the loss of records and difficulty in accessing them.

[0328] 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.

[0329] In this invention, the server includes means for storing information, means for analyzing information, and means for generating improvement suggestions. This enables centralized management and optimization of the schedules of all family members. Furthermore, by providing activity suggestions, it is possible to recommend effective activities based on the family's past interests and external information, and it is possible to provide a system that organizes, saves, and easily accesses memories.

[0330] A "terminal device" is a device used by users to input information and receive notifications.

[0331] A "server device" is a central computer that stores and analyzes data received from terminal devices.

[0332] An "analysis device" is a device that analyzes accumulated data and has the function of detecting schedule overlaps and inconsistencies.

[0333] A "proposal device" is a device that has the function of generating revised or improved suggestions for the user based on the analysis results.

[0334] A "notification device" is a system for transmitting generated proposals and revisions to the user's terminal device.

[0335] A "data collection device" is a device that has the function of acquiring and storing past activity history and external event information.

[0336] A "recommended device" is a device that has the function of suggesting family-oriented activities and events based on collected data.

[0337] A "display device" is a device that visualizes proposed activities and generated albums for the user.

[0338] A "storage device" is a storage system for automatically storing images and videos.

[0339] A "classification device" is a device that analyzes stored media and classifies it based on specific events or themes.

[0340] A "generation device" is a device that has the function of creating a digital album based on the analyzed media.

[0341] A "viewing device" is a device that allows users to access and view the generated digital album.

[0342] This invention is a system for effectively managing family schedules and memories. The system primarily consists of terminal devices and a server device.

[0343] The server uses high-performance computer equipment to store and analyze information. Specifically, it uses cloud services and database technologies to store and analyze a wide range of data. This includes using programming languages ​​such as Python to analyze and classify the data. The server also utilizes open APIs to retrieve external event information and provide recommendations.

[0344] The device functions as a means for users to input information and receive notifications. This includes widely used mobile devices such as smartphones and tablets. The user interface is developed as an application using React Native, allowing for intuitive operation. The device also features an interface for automatically capturing images and videos and uploading them to a server. Specifically, the device uploads media to cloud storage such as Amazon S3.

[0345] Users input their daily schedules into their devices. For example, by entering the date of their child's school performance, that information is sent to the server. The server analyzes this data and compares it with the parent's schedule to check for any overlaps. If there are overlaps, the server generates a suggested adjustment and notifies the parent. Similarly, based on past data, the server retrieves information on nearby activities and suggests events that the whole family can enjoy.

[0346] An example prompt might be, "Check if there are any conflicts in today's schedule and suggest nearby events that the family can enjoy." Using this prompt, the server will perform appropriate analysis and make suggestions.

[0347] This system allows users to efficiently manage their family's schedules and plan enriching family experiences.

[0348] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0349] Step 1:

[0350] The user enters schedule information into the terminal. This information includes date, time, location, and event details. The user interface is designed to allow intuitive input of information in a calendar format. Immediately after input, the information is converted to JSON format and ready to be sent to the server.

[0351] Step 2:

[0352] The terminal sends the entered schedule information to the server. The data is transferred to the cloud server in JSON format via the HTTP protocol. This process allows the server to receive data that can be parsed in the next step.

[0353] Step 3:

[0354] The server analyzes the received schedule information. While storing the information in a database, it uses an information analysis algorithm to detect duplicates and inconsistencies. A Python script then runs to identify related schedules. Based on this analysis, data integrity is verified.

[0355] Step 4:

[0356] Based on the analysis results, the server generates improvement suggestions for problematic schedules. For example, if there are scheduling overlaps, it considers alternative time options and creates adjustment plans. The suggestions are recorded in the database and ready for notification.

[0357] Step 5:

[0358] The server notifies the user's device of the generated suggestions. Specific suggestions are delivered to the user via email or in-app notifications. Notifications are delivered quickly, ensuring the user is ready to take immediate action.

[0359] Step 6:

[0360] The server analyzes past interests and external event information to suggest activities that fit the user. Using newly collected local event information from open APIs, it generates suggestions based on an AI model. These suggestions are prioritized based on the user's interests and schedule.

[0361] Step 7:

[0362] The user reviews the suggested activities on their device and selects the appropriate one. The selected activity information is sent to the server and automatically added to the schedule. This selection process is designed with usability in mind and can be completed quickly.

[0363] Step 8:

[0364] The device automatically uploads family photos and videos to the cloud. It sorts media stored on the device in the background and transfers it to a storage server. Cloud storage like Amazon S3 is used, creating a user-friendly environment.

[0365] Step 9:

[0366] The server analyzes uploaded media and generates albums. Machine learning algorithms are used to classify and tag photos and videos. This creates digital albums organized by time and event, improving the user's digital experience.

[0367] Step 10:

[0368] Users can view digital albums generated on their devices. An interactive and user-friendly interface is provided, making it easy for the whole family to reminisce about past memories. Albums are updated in real time and are accessible at any time.

[0369] (Application Example 1)

[0370] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0371] In today's busy families, there is a need to efficiently manage the schedules of all family members and optimize activities by utilizing local information. Another challenge is organizing everyday memories as digital data, making them easily accessible to all family members. This will help avoid conflicts in individual schedules and facilitate smooth family activities. Furthermore, it is necessary to use the acquired information to build a richer daily life.

[0372] 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.

[0373] In this invention, the server includes information acquisition means for inputting the schedules of multiple users, information storage means for storing the schedules acquired by the information acquisition means, and information optimization means for acquiring external information based on regional information and optimizing the schedule. This enables efficient centralized management of the entire family's schedule and allows for optimal activity suggestions utilizing external information.

[0374] "Information acquisition means" refers to a function within the system that provides an interface for users to input their schedules and accepts those schedules.

[0375] "Information storage means" refers to a function for securely saving acquired schedules on the cloud or locally.

[0376] A "duplicate detection method" is a function that analyzes saved schedules and checks for duplicates or inconsistencies.

[0377] A "means for generating improvement measures" is a function for creating solutions based on overlaps and contradictions in the schedule.

[0378] A "notification method" is a function that transmits generated improvement measures and important information to the user's device.

[0379] "Information optimization means" refers to functions that optimize schedules based on local and external information.

[0380] A "recommendation generation method" is a function that analyzes activity data and external information to recommend the most suitable activities for the user.

[0381] "Presentation means" refers to a function for displaying generated activity recommendations and information on the user interface.

[0382] A "digital data storage method" is a function that automatically saves captured photos and videos in digital format.

[0383] "Information processing means" refers to a function that analyzes stored digital data and adds specific event information.

[0384] An "album presentation method" is a function that displays the generated digital album to the user and makes it viewable.

[0385] The "activity suggestion method" is a function that recommends activities from a digital album generated based on the user's selection.

[0386] This invention provides a system for efficiently managing family schedules and supporting the optimization of activities using local information. This system includes a server and user devices and operates in a cloud environment. Specific embodiments are described below.

[0387] The server is equipped with information acquisition means for receiving each user's schedule data. This means receives schedule data entered from the user's device via the cloud and securely stores it using information storage means. The stored data is analyzed by duplicate detection means to automatically detect inconsistencies and schedule conflicts. Furthermore, based on these detection results, improvement measure generation means generates recommendations to resolve the conflicts and communicates them to the user via notification means.

[0388] Furthermore, information optimization methods incorporate external data such as local and weather information to optimize each family's schedule. This optimization makes it easier for users to plan meaningful activities. For example, it can suggest outdoor activities based on weekend weather information.

[0389] User devices are equipped with recommendation generation capabilities, enabling them to suggest activities and local events tailored to each individual. These suggestions are displayed on the user interface through the suggestion system, allowing users to easily incorporate them into their schedules.

[0390] In addition, the captured visual data is automatically saved to the cloud by a digital data storage device. Subsequently, an information processing device analyzes the data and tags it in relation to the event. The generated digital album is displayed on the user's device via an album display device, providing a system that allows users to easily enjoy family memories.

[0391] For example, if a user enters a prompt such as, "Please recommend some outdoor activities for this weekend," the system will provide optimal suggestions considering weather and event information. This functionality is automatically implemented by inputting prompt text using a generative AI model.

[0392] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0393] Step 1:

[0394] The user enters appointment information on their device.

[0395] The entered schedule data is sent to the server via an information retrieval device. The server receives this data and securely stores it in the cloud using an information storage device.

[0396] Step 2:

[0397] The server analyzes the stored schedule data.

[0398] A duplicate detection mechanism is used to check for conflicts with other appointments entered at the same time. If duplicates or inconsistencies are found, the information is sent to the improvement plan generation mechanism.

[0399] Step 3:

[0400] The improvement solution generation mechanism generates recommended solutions for resolving contradictions.

[0401] Specifically, a schedule adjustment proposal is created, taking priorities into consideration. This proposal is then sent to the user's device via a notification system. The output provides the adjusted schedule proposal.

[0402] Step 4:

[0403] The user device receives the notification and displays it in the user interface.

[0404] The user will review this and manually adjust the schedule if necessary.

[0405] Step 5:

[0406] Information optimization tools acquire local weather information and event information.

[0407] Based on this external information, the server re-evaluates the user's original schedule and generates suggestions for optimal activities.

[0408] Step 6:

[0409] The recommendation generation system generates activity recommendations tailored to each individual user.

[0410] The server generates recommendations based on past user behavior data and interests, and displays them on the user interface using a presentation tool.

[0411] Step 7:

[0412] Visual data captured by the user is automatically saved.

[0413] Digital data storage devices store data in the cloud, and it is analyzed through information processing devices. Tagged data is then generated as a digital album.

[0414] Step 8:

[0415] The album presentation method displays this album on the user's device.

[0416] Users can browse this album and reminisce about their memories. Additionally, the activity suggestion feature provides recommended activity ideas based on the user's choices.

[0417] Step 9:

[0418] When a user inputs a prompt into the generated AI model, the system provides the most appropriate information suggestions in response.

[0419] The system processes data based on user requests and generates the necessary output information. For example, in response to a prompt such as "What are some recommended indoor events nearby?", the system returns the corresponding event information.

[0420] 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.

[0421] This invention proposes a system that not only improves schedule management for the entire family but also provides a more personalized experience to the user by combining it with emotion recognition technology.

[0422] This system operates through family terminals and a server running on the cloud. The terminals have information input capabilities, allowing parents and children to enter their daily schedules. The entered schedules are transmitted from the terminals to the server via an information transmission device and stored in a cloud database.

[0423] The server is equipped with analytical tools to analyze stored schedule data and detect duplicates and inconsistencies. Based on the analysis results, it generates schedule improvement suggestions and sends these suggestions to the terminal via a notification system. This cycle allows users to optimize their schedule management.

[0424] Furthermore, by combining it with an emotion engine, the system achieves a new level of personalization. The device analyzes the user's voice and facial expressions, and the emotion engine recognizes their emotions. This emotion data is sent to and stored on a server. Based on this data, the server utilizes a suggestion update mechanism to generate suggestions tailored to the user's current emotional state. For example, if the system detects that the user is feeling stressed, it can suggest relaxing activities or schedule adjustments.

[0425] It also features emotional integration, which combines past interest and emotional data of the family, further personalizing the suggestions. This allows the system to consider the user's past preferences and present the most suitable activities.

[0426] For example, if the emotion engine determines that a child is feeling stressed in their new school environment, the server will suggest a parent-child event that can help the child relax. This suggestion will be displayed on the device, and the user can choose to participate.

[0427] The system also integrates a memory recording function, automatically uploading photos and videos taken by users to the cloud via media storage. The server analyzes this data and tags it in relation to events, creating a digital album. Users can view this album through their device, recording family growth and special moments. In this way, a new system incorporating emotional elements enables a richer and more seamless family life.

[0428] The following describes the processing flow.

[0429] Step 1:

[0430] The user opens the schedule input screen on their device and enters a new appointment or event. The device temporarily saves this information to its memory.

[0431] Step 2:

[0432] The terminal sends the entered schedule information to a server in the cloud. During this process, data security is ensured based on security protocols.

[0433] Step 3:

[0434] The server saves the received schedule information to a cloud database. The saved information is then analyzed to detect duplicates and inconsistencies.

[0435] Step 4:

[0436] The server generates schedule improvement suggestions based on the analysis results. In particular, it creates suggestions to resolve simultaneous events and time constraints.

[0437] Step 5:

[0438] The server generates improvement suggestions and sends them to the home terminal using a notification system. The terminal displays these suggestions in its user interface, and the user reviews the content.

[0439] Step 6:

[0440] The user accepts the proposal and enters approval or modification instructions via their device. The modifications are then resent from the device to the server.

[0441] Step 7:

[0442] To recognize the user's emotions, the device uses built-in sensors and cameras to acquire voice and facial expression data. This data is then input into the emotion engine.

[0443] Step 8:

[0444] The emotion engine analyzes the user's emotions in real time and sends that data to the server. The server stores this data and updates activity and schedule suggestions to match the user's current emotional state.

[0445] Step 9:

[0446] The server presents suggestions to the terminal based on emotional data. These suggestions include relaxation activities and appropriate events tailored to the user's emotional state.

[0447] Step 10:

[0448] The device receives feedback from the user and sends it to the server. The server uses this feedback to improve the accuracy of future suggestions.

[0449] Step 11:

[0450] Photos and videos taken by users on a daily basis are automatically uploaded to the cloud by their devices. The server then performs media analysis and tagging on these videos and associates them with events.

[0451] Step 12:

[0452] The server generates a digital album based on the analyzed media data and sends it to the user's device. The user can then view this album and enjoy their memories.

[0453] (Example 2)

[0454] 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".

[0455] There is a need to comprehensively improve the scheduling of the entire family, eliminate overlaps and contradictions in daily schedules, and provide a personalized user experience for each member by offering suggestions based on individual emotions and past interests. Furthermore, a system is needed to efficiently save and manage family memories and allow for easy recollection. These challenges remain unresolved in many existing systems.

[0456] 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.

[0457] In this invention, the server includes information transmission means, data analysis means, and emotion recognition means. This enables the detection of overlaps and inconsistencies in each member's schedule and the provision of optimized suggestions. Furthermore, emotion recognition technology allows for personalized suggestions tailored to the user's emotions, and by automatically saving and tagging family memories, it is possible to generate a digital record collection that can be easily viewed.

[0458] An "information input means" is a mechanism that provides an interface for all family members to input their schedules.

[0459] "Information transmission means" refers to a communication means for receiving entered schedules and saving them to network data storage.

[0460] "Data analysis means" refers to processing means for analyzing schedules within network data storage and detecting and reporting duplicates and inconsistencies.

[0461] The "proposal generation method" is an algorithm for generating schedule improvement suggestions based on the detected problems.

[0462] A "notification mechanism" is a system for notifying the user's terminal of the generated proposal.

[0463] "Emotion recognition means" refers to technology that analyzes a user's voice and facial expressions to recognize emotional data.

[0464] A "proposal update method" is a method for updating schedule proposals based on sentiment data.

[0465] A "data collection method" is a system for collecting data on a family's past interests and external activities.

[0466] A "recommendation generation method" is a process for generating suitable activities based on collected information.

[0467] A "presentation means" is a device for displaying recommended activities on the user's terminal.

[0468] "Emotional integration methods" are techniques for integrating emotional data with past interest data to personalize suggestions.

[0469] "Media storage means" refers to technology for automatically saving images and videos to network storage media.

[0470] "Tagging" refers to a technology that analyzes stored media and labels it as a specific event.

[0471] An "album generation method" is a method for generating a digital record collection based on analyzed media.

[0472] "Viewing method" refers to an interface that allows users to view the generated digital record collection on their terminals.

[0473] This invention is a system that manages the schedules of all family members and provides personalized suggestions based on their emotions, and is primarily implemented using a user's device and a server operating in the cloud. The device is equipped with means for inputting information to enter the family's schedule, including a touchscreen and voice input functionality. For example, if the user says, "Let's have a picnic in the park on Saturday," the device converts the voice data into text and sends it to the server.

[0474] The server stores the received schedule data in cloud data storage and uses data analysis tools to detect overlaps and inconsistencies in appointments. To do this, the server utilizes natural language processing technology to analyze the input data. Once the analysis is complete, improvement suggestions are sent to the user's terminal via a notification system. These improvement suggestions are displayed on the terminal as notifications such as, "How about changing your library appointment to 12:00?"

[0475] Furthermore, the device uses a microphone and camera to capture the user's voice and facial expressions, analyzes the data through emotion recognition, and sends the emotion data to a server. This data is analyzed in real time by the server, and a suggestion update mechanism generates more appropriate suggestions based on the user's emotions. For example, if the system detects that the user is feeling stressed, it might suggest, "Try taking a relaxation yoga class this weekend."

[0476] The server personalizes these suggestions and activities using the user's past interest and emotional data. In particular, it uses emotional integration techniques to generate more detailed and personalized suggestions that take into account the user's past experiences and preferences. Based on this process, prompts such as "How can I suggest relaxing activities when the user is feeling stressed?" are used.

[0477] The device further utilizes media storage means to automatically save images and videos taken by the user on the network, and to tag them and generate digital archives. A server-based tagging system analyzes the captured content and labels each event. As a result, users can view digital albums associated with specific events and easily reminisce about past memories.

[0478] This series of processes allows users to efficiently manage their daily schedules, receive emotionally resonant suggestions, and record family memories. This enables the whole family to enjoy a richer, more personalized life.

[0479] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0480] Step 1:

[0481] Users enter their schedules using a terminal. They can input their daily plans via a touch interface or voice input. This input is converted to text and sent to the server via the information input device. For example, if a user voice-inputs "Picnic at the park at 10am on Saturday," the terminal converts the voice data into text data and sends it to the server.

[0482] Step 2:

[0483] The server stores the received text data in network data storage. Data transmitted via the information transmission means is then analyzed by the data analysis means to detect duplicates and inconsistencies. Natural language processing algorithms are used to analyze the data and identify overlapping appointments on the same date and time. For example, if it is determined that "there are two events starting at 10:00," the nature of the overlap is clarified.

[0484] Step 3:

[0485] The server generates improvement suggestions based on the detected duplicates and inconsistencies. The suggestion generation mechanism operates and calculates the optimal solution through an algorithm. For example, a suggestion such as "change the library visit time to 12:00" is generated. This suggestion is sent from the server to the terminal via a notification mechanism, and the user can review the suggested improvement.

[0486] Step 4:

[0487] The device collects user emotional data using emotion recognition technology. Using the camera and microphone, it analyzes the user's facial expressions and voice tone, and sends this data to a server. The emotional data is further analyzed on the server to determine the user's emotional state. For example, it might obtain emotional data indicating that "the user is nervous."

[0488] Step 5:

[0489] The server updates its suggestions based on sentiment data. Using a suggestion update mechanism, it creates personalized suggestions through a generative AI model. For example, if a user is feeling stressed, a suggestion such as "We recommend a relaxing yoga class for the weekend" might be generated.

[0490] Step 6:

[0491] The server integrates the family's past interest and emotional data to further personalize suggestions. Emotional integration recommends activities based on past activities and current emotions. Users can view these recommended activities on their device and select them as appropriate.

[0492] Step 7:

[0493] The device automatically uploads photos and videos taken by the user to the network. The captured data is stored using media storage methods, and the server analyzes it. The analyzed data is tagged by event, and a digital album is generated. This album can be viewed through the device, allowing family members to reminisce about cherished memories.

[0494] (Application Example 2)

[0495] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0496] In today's society, family schedules have become increasingly complex, requiring smooth coordination. However, conventional schedule management systems have the problem of failing to consider family members' feelings and past interests, making it difficult to provide optimal suggestions tailored to individual circumstances. Furthermore, there has been a lack of systems for efficiently organizing memories and making them easily accessible at any time.

[0497] 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.

[0498] In this invention, the server includes information input means, analysis means, and emotion analysis means. This enables personalized suggestions that take into account not only the schedules of all family members but also their emotional data. Furthermore, by automatically saving video data and identifying specific events, the creation and viewing of digital memory collections becomes easier.

[0499] An "information input method" is a system for inputting the schedules and related information of all family members through a terminal or device.

[0500] The "information transmission means" refers to a function that sends the entered family schedule information to a server and stores it in a large-scale data management device.

[0501] "Analysis means" refers to a mechanism for analyzing schedule information stored in a large-scale data management system to detect schedule overlaps and inconsistencies.

[0502] The "proposal generation means" is a function that generates improved proposals based on the problems detected by the analysis means.

[0503] A "notification mechanism" is a system for transmitting generated suggestions to a home information display device to inform the user.

[0504] "Emotion analysis means" refers to technology that analyzes the user's voice and facial expression data to recognize their emotions. This makes it possible to generate suggestions that are tailored to the user's emotions.

[0505] "Data collection means" refers to functions for collecting data on a family's past interests and external events.

[0506] A "recommendation generation method" is a function that generates optimal recommended actions for families based on information obtained through data collection methods.

[0507] The "presentation means" is a mechanism that displays recommended actions created by the recommendation generation means on a home information display device so that the user can confirm them.

[0508] "Media storage means" refers to a function that automatically saves video data taken by family members to a large-scale data management device.

[0509] "Identification means" refers to a function that analyzes video data stored in media storage means and tags specific events or occurrences.

[0510] A "collection and generation method" is a system for creating and organizing digital memory collections based on analyzed video data.

[0511] "Viewing method" refers to a function that allows the generated digital collection of memories to be viewed on a home information display device.

[0512] The system for realizing this invention includes a home information display device, a server, a large-scale data management device, a camera, a microphone, and related software. The home information display device functions as an information input means for receiving input from a user and includes an information transmission means for transmitting the input data to the server.

[0513] The server analyzes information stored in a large-scale data management system, detects scheduling overlaps and inconsistencies, and further analyzes the user's voice and facial expression data using emotion analysis tools to recognize their emotions. This allows the server to generate personalized suggestions tailored to the user's emotions. For example, if a user is stressed, the server suggests relaxing activities. Such suggestions are notified to a home information display device, making it easier for the user to understand what actions are appropriate.

[0514] Furthermore, it is equipped with data collection and recommendation generation capabilities, which generate optimal recommended actions based on past interest data and external event information. In addition, it automatically saves and organizes family video data using media storage and identification capabilities to create a digital memory collection that can be viewed on a home information display device. Specifically, photos and videos from summer vacation trips will be automatically organized and made viewable.

[0515] The specific hardware used includes smart displays as home information display devices, cloud-based servers for data analysis, and microphones and cameras for emotion recognition. For software, Google Cloud Speech-to-Text and Amazon Lex are used for speech recognition, while Microsoft Azure's Emotion API is used for emotion analysis.

[0516] Example of a prompt:

[0517] "You are a highly hospitable home robot. Support the family's daily schedule management and provide relaxing suggestions based on their emotions. For example, how can you suggest relaxing music when family members are feeling stressed?"

[0518] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0519] Step 1:

[0520] The home information display device (terminal) accepts schedule and task input from the user. The input data is sent to a server using an information transmission method, preparing data for scheduling overlaps and sentiment analysis. Since voice input is also included, Google Cloud Speech-to-Text is used. The output of this step is the user's schedule information and voice data.

[0521] Step 2:

[0522] The server stores the received data in a large-scale data management system. Then, it analyzes the stored data using analytical tools to detect schedule overlaps and inconsistencies. The problems identified as a result of the analysis are then prepared as input data for the next step. The output of this step is the analyzed schedule data.

[0523] Step 3:

[0524] The server uses emotion analysis tools to analyze the user's emotions from voice and facial expression data. Using voice and image data as input, it performs analysis using the Microsoft Azure Emotion API to extract the emotions the user may be experiencing. The output of this step is information about the emotional state.

[0525] Step 4:

[0526] Based on the analyzed schedule data and emotional state information, the server generates emotionally appropriate improvement suggestions and recommended actions using a suggestion generation mechanism. For example, if it is determined that the user is feeling stressed, it will suggest relaxing activities. This process is performed using a generation AI model based on prompt statements. The output of this step is improvement suggestions.

[0527] Step 5:

[0528] The server notifies the home information display device of the generated suggestions via an information transmission means. The terminal displays the received suggestions to the user and provides an opportunity to select the suggested activities or actions. The output of this step is the suggestion information displayed to the user.

[0529] Step 6:

[0530] The terminal automatically saves video data captured by the user to a large-scale data management system using media storage means. The server analyzes the saved data using identification means and tags specific events. This tagged data becomes the input data for the next step. The output of this step is tagged media information.

[0531] Step 7:

[0532] The server uses tagged video data to create a digital memory collection using a collection generation method. The generated digital memory collection can be viewed on a home information display device, allowing users to easily reminisce about family memories. The output of this step is a viewable digital memory collection.

[0533] 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.

[0534] 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.

[0535] 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.

[0536] [Third Embodiment]

[0537] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0538] 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.

[0539] 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).

[0540] 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.

[0541] 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.

[0542] 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).

[0543] 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.

[0544] 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.

[0545] 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.

[0546] 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.

[0547] 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.

[0548] 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".

[0549] This invention provides a system for centrally managing the schedules of all family members and for streamlining the recording of family activities and memories. This system consists of a server operating on the cloud and terminals used by each household.

[0550] The server collects schedule information submitted by users into a cloud database and manages it efficiently. During this process, the server uses its information analysis function to detect duplicate or inconsistent schedules and notifies users with suggestions for improvement. This system allows users to optimize their schedules without any extra effort.

[0551] The device provides a means of inputting information through a user interface, making it easy for parents and children to enter their schedules. Furthermore, by receiving notifications sent from the server, the device can promptly check for important events and schedule changes.

[0552] Furthermore, the server collects and maintains a database of the family's past interests and events. Based on this, the server suggests activities tailored to each user. For example, it might recommend outdoor activities or cultural experiences that the family can enjoy, taking into account holiday weather and local events. These suggestions are displayed on the device, and the user has the ability to select them.

[0553] Regarding the recording of memories, the device automatically uploads family photos and videos to the cloud, where the server analyzes and tags them. This allows the server to generate a series of digital albums, organizing family growth and special events. These albums are viewable on the device and are designed to be accessible to all family members.

[0554] For example, when a user enters the date of their child's school performance on their device, that information is sent to the server and compared with the parent's work schedule. If there is a conflict, the server notifies the parent's device with a suggested adjustment. At the same time, it suggests nearby weekend events as family activities. Users can effectively manage their family schedule and record memories by checking this information on their device.

[0555] The following describes the processing flow.

[0556] Step 1:

[0557] The user uses their device to open the schedule input screen and enters appointments such as parents' work, children's school events, and extracurricular activities. The device temporarily saves this information.

[0558] Step 2:

[0559] The terminal sends the entered schedule information to a server in the cloud. Here, data privacy is ensured through security protocols.

[0560] Step 3:

[0561] The server saves the received schedule information to a cloud database. After saving, it runs an algorithm to detect duplicates and inconsistencies.

[0562] Step 4:

[0563] If the server detects scheduling conflicts or inconsistencies, it generates optimal improvement suggestions and determines which appointments should be changed.

[0564] Step 5:

[0565] The server generates improvement suggestions and notifies the terminal. The terminal displays this notification on its user interface, allowing the user to confirm the revised schedule.

[0566] Step 6:

[0567] If the user accepts the suggestion or makes further modifications, they will resend the changes to the server from their device.

[0568] Step 7:

[0569] The server analyzes the family's past data and external event information to suggest activities the family can enjoy. This includes weather data and local event information.

[0570] Step 8:

[0571] The terminal receives the server's suggestions and presents them to the user via the user interface. The user can then select the activity they wish to participate in.

[0572] Step 9:

[0573] The device sends user feedback and activity participation choices to the server, which then stores the results in a database.

[0574] Step 10:

[0575] Photos and videos taken by users during everyday events are automatically uploaded to the cloud by their device.

[0576] Step 11:

[0577] The server analyzes media uploaded to the cloud and tags it based on date and event. Furthermore, it generates digital albums.

[0578] Step 12:

[0579] The device receives the generated digital album and displays it in a user-friendly format. Through this album, users can easily reminisce about their memories.

[0580] (Example 1)

[0581] 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."

[0582] In modern households, effectively managing everyone's schedules and planning fulfilling family activities is crucial. However, centrally managing everyone's schedules is not easy, often resulting in schedule overlaps and inconsistencies. Furthermore, methods for organizing and preserving family memories are not common, leading to challenges such as the loss of records and difficulty in accessing them.

[0583] 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.

[0584] In this invention, the server includes means for storing information, means for analyzing information, and means for generating improvement suggestions. This enables centralized management and optimization of the schedules of all family members. Furthermore, by providing activity suggestions, it is possible to recommend effective activities based on the family's past interests and external information, and it is possible to provide a system that organizes, saves, and easily accesses memories.

[0585] A "terminal device" is a device used by users to input information and receive notifications.

[0586] A "server device" is a central computer that stores and analyzes data received from terminal devices.

[0587] An "analysis device" is a device that analyzes accumulated data and has the function of detecting schedule overlaps and inconsistencies.

[0588] A "proposal device" is a device that has the function of generating revised or improved suggestions for the user based on the analysis results.

[0589] A "notification device" is a system for transmitting generated proposals and revisions to the user's terminal device.

[0590] A "data collection device" is a device that has the function of acquiring and storing past activity history and external event information.

[0591] A "recommended device" is a device that has the function of suggesting family-oriented activities and events based on collected data.

[0592] A "display device" is a device that visualizes proposed activities and generated albums for the user.

[0593] A "storage device" is a storage system for automatically storing images and videos.

[0594] A "classification device" is a device that analyzes stored media and classifies it based on specific events or themes.

[0595] A "generation device" is a device that has the function of creating a digital album based on the analyzed media.

[0596] A "viewing device" is a device that allows users to access and view the generated digital album.

[0597] This invention is a system for effectively managing family schedules and memories. The system primarily consists of terminal devices and a server device.

[0598] The server uses high-performance computer equipment to store and analyze information. Specifically, it uses cloud services and database technologies to store and analyze a wide range of data. This includes using programming languages ​​such as Python to analyze and classify the data. The server also utilizes open APIs to retrieve external event information and provide recommendations.

[0599] The device functions as a means for users to input information and receive notifications. This includes widely used mobile devices such as smartphones and tablets. The user interface is developed as an application using React Native, allowing for intuitive operation. The device also features an interface for automatically capturing images and videos and uploading them to a server. Specifically, the device uploads media to cloud storage such as Amazon S3.

[0600] Users input their daily schedules into their devices. For example, by entering the date of their child's school performance, that information is sent to the server. The server analyzes this data and compares it with the parent's schedule to check for any overlaps. If there are overlaps, the server generates a suggested adjustment and notifies the parent. Similarly, based on past data, the server retrieves information on nearby activities and suggests events that the whole family can enjoy.

[0601] An example prompt might be, "Check if there are any conflicts in today's schedule and suggest nearby events that the family can enjoy." Using this prompt, the server will perform appropriate analysis and make suggestions.

[0602] This system allows users to efficiently manage their family's schedules and plan enriching family experiences.

[0603] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0604] Step 1:

[0605] The user enters schedule information into the terminal. This information includes date, time, location, and event details. The user interface is designed to allow intuitive input of information in a calendar format. Immediately after input, the information is converted to JSON format and ready to be sent to the server.

[0606] Step 2:

[0607] The terminal sends the entered schedule information to the server. The data is transferred to the cloud server in JSON format via the HTTP protocol. This process allows the server to receive data that can be parsed in the next step.

[0608] Step 3:

[0609] The server analyzes the received schedule information. While storing the information in a database, it uses an information analysis algorithm to detect duplicates and inconsistencies. A Python script then runs to identify related schedules. Based on this analysis, data integrity is verified.

[0610] Step 4:

[0611] Based on the analysis results, the server generates improvement suggestions for problematic schedules. For example, if there are scheduling overlaps, it considers alternative time options and creates adjustment plans. The suggestions are recorded in the database and ready for notification.

[0612] Step 5:

[0613] The server notifies the user's device of the generated suggestions. Specific suggestions are delivered to the user via email or in-app notifications. Notifications are delivered quickly, ensuring the user is ready to take immediate action.

[0614] Step 6:

[0615] The server analyzes past interests and external event information to suggest activities that fit the user. Using newly collected local event information from open APIs, it generates suggestions based on an AI model. These suggestions are prioritized based on the user's interests and schedule.

[0616] Step 7:

[0617] The user reviews the suggested activities on their device and selects the appropriate one. The selected activity information is sent to the server and automatically added to the schedule. This selection process is designed with usability in mind and can be completed quickly.

[0618] Step 8:

[0619] The device automatically uploads family photos and videos to the cloud. It sorts media stored on the device in the background and transfers it to a storage server. Cloud storage like Amazon S3 is used, creating a user-friendly environment.

[0620] Step 9:

[0621] The server analyzes uploaded media and generates albums. Machine learning algorithms are used to classify and tag photos and videos. This creates digital albums organized by time and event, improving the user's digital experience.

[0622] Step 10:

[0623] Users can view digital albums generated on their devices. An interactive and user-friendly interface is provided, making it easy for the whole family to reminisce about past memories. Albums are updated in real time and are accessible at any time.

[0624] (Application Example 1)

[0625] 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."

[0626] In today's busy families, there is a need to efficiently manage the schedules of all family members and optimize activities by utilizing local information. Another challenge is organizing everyday memories as digital data, making them easily accessible to all family members. This will help avoid conflicts in individual schedules and facilitate smooth family activities. Furthermore, it is necessary to use the acquired information to build a richer daily life.

[0627] 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.

[0628] In this invention, the server includes information acquisition means for inputting the schedules of multiple users, information storage means for storing the schedules acquired by the information acquisition means, and information optimization means for acquiring external information based on regional information and optimizing the schedule. This enables efficient centralized management of the entire family's schedule and allows for optimal activity suggestions utilizing external information.

[0629] "Information acquisition means" refers to a function within the system that provides an interface for users to input their schedules and accepts those schedules.

[0630] "Information storage means" refers to a function for securely saving acquired schedules on the cloud or locally.

[0631] A "duplicate detection method" is a function that analyzes saved schedules and checks for duplicates or inconsistencies.

[0632] A "means for generating improvement measures" is a function for creating solutions based on overlaps and contradictions in the schedule.

[0633] A "notification method" is a function that transmits generated improvement measures and important information to the user's device.

[0634] "Information optimization means" refers to functions that optimize schedules based on local and external information.

[0635] A "recommendation generation method" is a function that analyzes activity data and external information to recommend the most suitable activities for the user.

[0636] "Presentation means" refers to a function for displaying generated activity recommendations and information on the user interface.

[0637] A "digital data storage method" is a function that automatically saves captured photos and videos in digital format.

[0638] "Information processing means" refers to a function that analyzes stored digital data and adds specific event information.

[0639] An "album presentation method" is a function that displays the generated digital album to the user and makes it viewable.

[0640] The "activity suggestion method" is a function that recommends activities from a digital album generated based on the user's selection.

[0641] This invention provides a system for efficiently managing family schedules and supporting the optimization of activities using local information. This system includes a server and user devices and operates in a cloud environment. Specific embodiments are described below.

[0642] The server is equipped with information acquisition means for receiving each user's schedule data. This means receives schedule data entered from the user's device via the cloud and securely stores it using information storage means. The stored data is analyzed by duplicate detection means to automatically detect inconsistencies and schedule conflicts. Furthermore, based on these detection results, improvement measure generation means generates recommendations to resolve the conflicts and communicates them to the user via notification means.

[0643] Furthermore, information optimization methods incorporate external data such as local and weather information to optimize each family's schedule. This optimization makes it easier for users to plan meaningful activities. For example, it can suggest outdoor activities based on weekend weather information.

[0644] User devices are equipped with recommendation generation capabilities, enabling them to suggest activities and local events tailored to each individual. These suggestions are displayed on the user interface through the suggestion system, allowing users to easily incorporate them into their schedules.

[0645] In addition, the captured visual data is automatically saved to the cloud by a digital data storage device. Subsequently, an information processing device analyzes the data and tags it in relation to the event. The generated digital album is displayed on the user's device via an album display device, providing a system that allows users to easily enjoy family memories.

[0646] For example, if a user enters a prompt such as, "Please recommend some outdoor activities for this weekend," the system will provide optimal suggestions considering weather and event information. This functionality is automatically implemented by inputting prompt text using a generative AI model.

[0647] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0648] Step 1:

[0649] The user enters appointment information on their device.

[0650] The entered schedule data is sent to the server via an information retrieval device. The server receives this data and securely stores it in the cloud using an information storage device.

[0651] Step 2:

[0652] The server analyzes the stored schedule data.

[0653] A duplicate detection mechanism is used to check for conflicts with other appointments entered at the same time. If duplicates or inconsistencies are found, the information is sent to the improvement plan generation mechanism.

[0654] Step 3:

[0655] The improvement solution generation mechanism generates recommended solutions for resolving contradictions.

[0656] Specifically, a schedule adjustment proposal is created, taking priorities into consideration. This proposal is then sent to the user's device via a notification system. The output provides the adjusted schedule proposal.

[0657] Step 4:

[0658] The user device receives the notification and displays it in the user interface.

[0659] The user will review this and manually adjust the schedule if necessary.

[0660] Step 5:

[0661] Information optimization tools acquire local weather information and event information.

[0662] Based on this external information, the server re-evaluates the user's original schedule and generates suggestions for optimal activities.

[0663] Step 6:

[0664] The recommendation generation system generates activity recommendations tailored to each individual user.

[0665] The server generates recommendations based on past user behavior data and interests, and displays them on the user interface using a presentation tool.

[0666] Step 7:

[0667] Visual data captured by the user is automatically saved.

[0668] Digital data storage devices store data in the cloud, and it is analyzed through information processing devices. Tagged data is then generated as a digital album.

[0669] Step 8:

[0670] The album presentation method displays this album on the user's device.

[0671] Users can browse this album and reminisce about their memories. Additionally, the activity suggestion feature provides recommended activity ideas based on the user's choices.

[0672] Step 9:

[0673] When a user inputs a prompt into the generated AI model, the system provides the most appropriate information suggestions in response.

[0674] The system processes data based on user requests and generates the necessary output information. For example, in response to a prompt such as "What are some recommended indoor events nearby?", the system returns the corresponding event information.

[0675] 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.

[0676] This invention proposes a system that not only improves schedule management for the entire family but also provides a more personalized experience to the user by combining it with emotion recognition technology.

[0677] This system operates through family terminals and a server running on the cloud. The terminals have information input capabilities, allowing parents and children to enter their daily schedules. The entered schedules are transmitted from the terminals to the server via an information transmission device and stored in a cloud database.

[0678] The server is equipped with analytical tools to analyze stored schedule data and detect duplicates and inconsistencies. Based on the analysis results, it generates schedule improvement suggestions and sends these suggestions to the terminal via a notification system. This cycle allows users to optimize their schedule management.

[0679] Furthermore, by combining it with an emotion engine, the system achieves a new level of personalization. The device analyzes the user's voice and facial expressions, and the emotion engine recognizes their emotions. This emotion data is sent to and stored on a server. Based on this data, the server utilizes a suggestion update mechanism to generate suggestions tailored to the user's current emotional state. For example, if the system detects that the user is feeling stressed, it can suggest relaxing activities or schedule adjustments.

[0680] It also features emotional integration, which combines past interest and emotional data of the family, further personalizing the suggestions. This allows the system to consider the user's past preferences and present the most suitable activities.

[0681] For example, if the emotion engine determines that a child is feeling stressed in their new school environment, the server will suggest a parent-child event that can help the child relax. This suggestion will be displayed on the device, and the user can choose to participate.

[0682] The system also integrates a memory recording function, automatically uploading photos and videos taken by users to the cloud via media storage. The server analyzes this data and tags it in relation to events, creating a digital album. Users can view this album through their device, recording family growth and special moments. In this way, a new system incorporating emotional elements enables a richer and more seamless family life.

[0683] The following describes the processing flow.

[0684] Step 1:

[0685] The user opens the schedule input screen on their device and enters a new appointment or event. The device temporarily saves this information to its memory.

[0686] Step 2:

[0687] The terminal sends the entered schedule information to a server in the cloud. During this process, data security is ensured based on security protocols.

[0688] Step 3:

[0689] The server saves the received schedule information to a cloud database. The saved information is then analyzed to detect duplicates and inconsistencies.

[0690] Step 4:

[0691] The server generates schedule improvement suggestions based on the analysis results. In particular, it creates suggestions to resolve simultaneous events and time constraints.

[0692] Step 5:

[0693] The server generates improvement suggestions and sends them to the home terminal using a notification system. The terminal displays these suggestions in its user interface, and the user reviews the content.

[0694] Step 6:

[0695] The user accepts the proposal and enters approval or modification instructions via their device. The modifications are then resent from the device to the server.

[0696] Step 7:

[0697] To recognize the user's emotions, the device uses built-in sensors and cameras to acquire voice and facial expression data. This data is then input into the emotion engine.

[0698] Step 8:

[0699] The emotion engine analyzes the user's emotions in real time and sends that data to the server. The server stores this data and updates activity and schedule suggestions to match the user's current emotional state.

[0700] Step 9:

[0701] The server presents suggestions to the terminal based on emotional data. These suggestions include relaxation activities and appropriate events tailored to the user's emotional state.

[0702] Step 10:

[0703] The device receives feedback from the user and sends it to the server. The server uses this feedback to improve the accuracy of future suggestions.

[0704] Step 11:

[0705] Photos and videos taken by users on a daily basis are automatically uploaded to the cloud by their devices. The server then performs media analysis and tagging on these videos and associates them with events.

[0706] Step 12:

[0707] The server generates a digital album based on the analyzed media data and sends it to the user's device. The user can then view this album and enjoy their memories.

[0708] (Example 2)

[0709] 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."

[0710] There is a need to comprehensively improve the scheduling of the entire family, eliminate overlaps and contradictions in daily schedules, and provide a personalized user experience for each member by offering suggestions based on individual emotions and past interests. Furthermore, a system is needed to efficiently save and manage family memories and allow for easy recollection. These challenges remain unresolved in many existing systems.

[0711] 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.

[0712] In this invention, the server includes information transmission means, data analysis means, and emotion recognition means. This enables the detection of overlaps and inconsistencies in each member's schedule and the provision of optimized suggestions. Furthermore, emotion recognition technology allows for personalized suggestions tailored to the user's emotions, and by automatically saving and tagging family memories, it is possible to generate a digital record collection that can be easily viewed.

[0713] An "information input means" is a mechanism that provides an interface for all family members to input their schedules.

[0714] "Information transmission means" refers to a communication means for receiving entered schedules and saving them to network data storage.

[0715] "Data analysis means" refers to processing means for analyzing schedules within network data storage and detecting and reporting duplicates and inconsistencies.

[0716] The "proposal generation method" is an algorithm for generating schedule improvement suggestions based on the detected problems.

[0717] A "notification mechanism" is a system for notifying the user's terminal of the generated proposal.

[0718] "Emotion recognition means" refers to technology that analyzes a user's voice and facial expressions to recognize emotional data.

[0719] A "proposal update method" is a method for updating schedule proposals based on sentiment data.

[0720] A "data collection method" is a system for collecting data on a family's past interests and external activities.

[0721] A "recommendation generation method" is a process for generating suitable activities based on collected information.

[0722] A "presentation means" is a device for displaying recommended activities on the user's terminal.

[0723] "Emotional integration methods" are techniques for integrating emotional data with past interest data to personalize suggestions.

[0724] "Media storage means" refers to technology for automatically saving images and videos to network storage media.

[0725] "Tagging" refers to a technology that analyzes stored media and labels it as a specific event.

[0726] An "album generation method" is a method for generating a digital record collection based on analyzed media.

[0727] "Viewing method" refers to an interface that allows users to view the generated digital record collection on their terminals.

[0728] This invention is a system that manages the schedules of all family members and provides personalized suggestions based on their emotions, and is primarily implemented using a user's device and a server operating in the cloud. The device is equipped with means for inputting information to enter the family's schedule, including a touchscreen and voice input functionality. For example, if the user says, "Let's have a picnic in the park on Saturday," the device converts the voice data into text and sends it to the server.

[0729] The server stores the received schedule data in cloud data storage and uses data analysis tools to detect overlaps and inconsistencies in appointments. To do this, the server utilizes natural language processing technology to analyze the input data. Once the analysis is complete, improvement suggestions are sent to the user's terminal via a notification system. These improvement suggestions are displayed on the terminal as notifications such as, "How about changing your library appointment to 12:00?"

[0730] Furthermore, the device uses a microphone and camera to capture the user's voice and facial expressions, analyzes the data through emotion recognition, and sends the emotion data to a server. This data is analyzed in real time by the server, and a suggestion update mechanism generates more appropriate suggestions based on the user's emotions. For example, if the system detects that the user is feeling stressed, it might suggest, "Try taking a relaxation yoga class this weekend."

[0731] The server personalizes these suggestions and activities using the user's past interest and emotional data. In particular, it uses emotional integration techniques to generate more detailed and personalized suggestions that take into account the user's past experiences and preferences. Based on this process, prompts such as "How can I suggest relaxing activities when the user is feeling stressed?" are used.

[0732] The device further utilizes media storage means to automatically save images and videos taken by the user on the network, and to tag them and generate digital archives. A server-based tagging system analyzes the captured content and labels each event. As a result, users can view digital albums associated with specific events and easily reminisce about past memories.

[0733] This series of processes allows users to efficiently manage their daily schedules, receive emotionally resonant suggestions, and record family memories. This enables the whole family to enjoy a richer, more personalized life.

[0734] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0735] Step 1:

[0736] Users enter their schedules using a terminal. They can input their daily plans via a touch interface or voice input. This input is converted to text and sent to the server via the information input device. For example, if a user voice-inputs "Picnic at the park at 10am on Saturday," the terminal converts the voice data into text data and sends it to the server.

[0737] Step 2:

[0738] The server stores the received text data in network data storage. Data transmitted via the information transmission means is then analyzed by the data analysis means to detect duplicates and inconsistencies. Natural language processing algorithms are used to analyze the data and identify overlapping appointments on the same date and time. For example, if it is determined that "there are two events starting at 10:00," the nature of the overlap is clarified.

[0739] Step 3:

[0740] The server generates improvement suggestions based on the detected duplicates and inconsistencies. The suggestion generation mechanism operates and calculates the optimal solution through an algorithm. For example, a suggestion such as "change the library visit time to 12:00" is generated. This suggestion is sent from the server to the terminal via a notification mechanism, and the user can review the suggested improvement.

[0741] Step 4:

[0742] The device collects user emotional data using emotion recognition technology. Using the camera and microphone, it analyzes the user's facial expressions and voice tone, and sends this data to a server. The emotional data is further analyzed on the server to determine the user's emotional state. For example, it might obtain emotional data indicating that "the user is nervous."

[0743] Step 5:

[0744] The server updates its suggestions based on sentiment data. Using a suggestion update mechanism, it creates personalized suggestions through a generative AI model. For example, if a user is feeling stressed, a suggestion such as "We recommend a relaxing yoga class for the weekend" might be generated.

[0745] Step 6:

[0746] The server integrates the family's past interest and emotional data to further personalize suggestions. Emotional integration recommends activities based on past activities and current emotions. Users can view these recommended activities on their device and select them as appropriate.

[0747] Step 7:

[0748] The device automatically uploads photos and videos taken by the user to the network. The captured data is stored using media storage methods, and the server analyzes it. The analyzed data is tagged by event, and a digital album is generated. This album can be viewed through the device, allowing family members to reminisce about cherished memories.

[0749] (Application Example 2)

[0750] 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."

[0751] In today's society, family schedules have become increasingly complex, requiring smooth coordination. However, conventional schedule management systems have the problem of failing to consider family members' feelings and past interests, making it difficult to provide optimal suggestions tailored to individual circumstances. Furthermore, there has been a lack of systems for efficiently organizing memories and making them easily accessible at any time.

[0752] 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.

[0753] In this invention, the server includes information input means, analysis means, and emotion analysis means. This enables personalized suggestions that take into account not only the schedules of all family members but also their emotional data. Furthermore, by automatically saving video data and identifying specific events, the creation and viewing of digital memory collections becomes easier.

[0754] An "information input method" is a system for inputting the schedules and related information of all family members through a terminal or device.

[0755] The "information transmission means" refers to a function that sends the entered family schedule information to a server and stores it in a large-scale data management device.

[0756] "Analysis means" refers to a mechanism for analyzing schedule information stored in a large-scale data management system to detect schedule overlaps and inconsistencies.

[0757] The "proposal generation means" is a function that generates improved proposals based on the problems detected by the analysis means.

[0758] A "notification mechanism" is a system for transmitting generated suggestions to a home information display device to inform the user.

[0759] "Emotion analysis means" refers to technology that analyzes the user's voice and facial expression data to recognize their emotions. This makes it possible to generate suggestions that are tailored to the user's emotions.

[0760] "Data collection means" refers to functions for collecting data on a family's past interests and external events.

[0761] A "recommendation generation method" is a function that generates optimal recommended actions for families based on information obtained through data collection methods.

[0762] The "presentation means" is a mechanism that displays recommended actions created by the recommendation generation means on a home information display device so that the user can confirm them.

[0763] "Media storage means" refers to a function that automatically saves video data taken by family members to a large-scale data management device.

[0764] "Identification means" refers to a function that analyzes video data stored in media storage means and tags specific events or occurrences.

[0765] A "collection and generation method" is a system for creating and organizing digital memory collections based on analyzed video data.

[0766] "Viewing method" refers to a function that allows the generated digital collection of memories to be viewed on a home information display device.

[0767] The system for realizing this invention includes a home information display device, a server, a large-scale data management device, a camera, a microphone, and related software. The home information display device functions as an information input means for receiving input from a user and includes an information transmission means for transmitting the input data to the server.

[0768] The server analyzes information stored in a large-scale data management system, detects scheduling overlaps and inconsistencies, and further analyzes the user's voice and facial expression data using emotion analysis tools to recognize their emotions. This allows the server to generate personalized suggestions tailored to the user's emotions. For example, if a user is stressed, the server suggests relaxing activities. Such suggestions are notified to a home information display device, making it easier for the user to understand what actions are appropriate.

[0769] Furthermore, it is equipped with data collection and recommendation generation capabilities, which generate optimal recommended actions based on past interest data and external event information. In addition, it automatically saves and organizes family video data using media storage and identification capabilities to create a digital memory collection that can be viewed on a home information display device. Specifically, photos and videos from summer vacation trips will be automatically organized and made viewable.

[0770] The specific hardware used includes smart displays as home information display devices, cloud-based servers for data analysis, and microphones and cameras for emotion recognition. For software, Google Cloud Speech-to-Text and Amazon Lex are used for speech recognition, while Microsoft Azure's Emotion API is used for emotion analysis.

[0771] Example of a prompt:

[0772] "You are a highly hospitable home robot. Support the family's daily schedule management and provide relaxing suggestions based on their emotions. For example, how can you suggest relaxing music when family members are feeling stressed?"

[0773] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0774] Step 1:

[0775] The home information display device (terminal) accepts schedule and task input from the user. The input data is sent to a server using an information transmission method, preparing data for scheduling overlaps and sentiment analysis. Since voice input is also included, Google Cloud Speech-to-Text is used. The output of this step is the user's schedule information and voice data.

[0776] Step 2:

[0777] The server stores the received data in a large-scale data management system. Then, it analyzes the stored data using analytical tools to detect schedule overlaps and inconsistencies. The problems identified as a result of the analysis are then prepared as input data for the next step. The output of this step is the analyzed schedule data.

[0778] Step 3:

[0779] The server uses emotion analysis tools to analyze the user's emotions from voice and facial expression data. Using voice and image data as input, it performs analysis using the Microsoft Azure Emotion API to extract the emotions the user may be experiencing. The output of this step is information about the emotional state.

[0780] Step 4:

[0781] Based on the analyzed schedule data and emotional state information, the server generates emotionally appropriate improvement suggestions and recommended actions using a suggestion generation mechanism. For example, if it is determined that the user is feeling stressed, it will suggest relaxing activities. This process is performed using a generation AI model based on prompt statements. The output of this step is improvement suggestions.

[0782] Step 5:

[0783] The server notifies the home information display device of the generated suggestions via an information transmission means. The terminal displays the received suggestions to the user and provides an opportunity to select the suggested activities or actions. The output of this step is the suggestion information displayed to the user.

[0784] Step 6:

[0785] The terminal automatically saves video data captured by the user to a large-scale data management system using media storage means. The server analyzes the saved data using identification means and tags specific events. This tagged data becomes the input data for the next step. The output of this step is tagged media information.

[0786] Step 7:

[0787] The server uses tagged video data to create a digital memory collection using a collection generation method. The generated digital memory collection can be viewed on a home information display device, allowing users to easily reminisce about family memories. The output of this step is a viewable digital memory collection.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] [Fourth Embodiment]

[0792] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0793] 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.

[0794] 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).

[0795] 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.

[0796] 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.

[0797] 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).

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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".

[0805] This invention provides a system for centrally managing the schedules of all family members and for streamlining the recording of family activities and memories. This system consists of a server operating on the cloud and terminals used by each household.

[0806] The server collects schedule information submitted by users into a cloud database and manages it efficiently. During this process, the server uses its information analysis function to detect duplicate or inconsistent schedules and notifies users with suggestions for improvement. This system allows users to optimize their schedules without any extra effort.

[0807] The device provides a means of inputting information through a user interface, making it easy for parents and children to enter their schedules. Furthermore, by receiving notifications sent from the server, the device can promptly check for important events and schedule changes.

[0808] Furthermore, the server collects and maintains a database of the family's past interests and events. Based on this, the server suggests activities tailored to each user. For example, it might recommend outdoor activities or cultural experiences that the family can enjoy, taking into account holiday weather and local events. These suggestions are displayed on the device, and the user has the ability to select them.

[0809] Regarding the recording of memories, the device automatically uploads family photos and videos to the cloud, where the server analyzes and tags them. This allows the server to generate a series of digital albums, organizing family growth and special events. These albums are viewable on the device and are designed to be accessible to all family members.

[0810] For example, when a user enters the date of their child's school performance on their device, that information is sent to the server and compared with the parent's work schedule. If there is a conflict, the server notifies the parent's device with a suggested adjustment. At the same time, it suggests nearby weekend events as family activities. Users can effectively manage their family schedule and record memories by checking this information on their device.

[0811] The following describes the processing flow.

[0812] Step 1:

[0813] The user uses their device to open the schedule input screen and enters appointments such as parents' work, children's school events, and extracurricular activities. The device temporarily saves this information.

[0814] Step 2:

[0815] The terminal sends the entered schedule information to a server in the cloud. Here, data privacy is ensured through security protocols.

[0816] Step 3:

[0817] The server saves the received schedule information to a cloud database. After saving, it runs an algorithm to detect duplicates and inconsistencies.

[0818] Step 4:

[0819] If the server detects scheduling conflicts or inconsistencies, it generates optimal improvement suggestions and determines which appointments should be changed.

[0820] Step 5:

[0821] The server generates improvement suggestions and notifies the terminal. The terminal displays this notification on its user interface, allowing the user to confirm the revised schedule.

[0822] Step 6:

[0823] If the user accepts the suggestion or makes further modifications, they will resend the changes to the server from their device.

[0824] Step 7:

[0825] The server analyzes the family's past data and external event information to suggest activities the family can enjoy. This includes weather data and local event information.

[0826] Step 8:

[0827] The terminal receives the server's suggestions and presents them to the user via the user interface. The user can then select the activity they wish to participate in.

[0828] Step 9:

[0829] The device sends user feedback and activity participation choices to the server, which then stores the results in a database.

[0830] Step 10:

[0831] Photos and videos taken by users during everyday events are automatically uploaded to the cloud by their device.

[0832] Step 11:

[0833] The server analyzes media uploaded to the cloud and tags it based on date and event. Furthermore, it generates digital albums.

[0834] Step 12:

[0835] The device receives the generated digital album and displays it in a user-friendly format. Through this album, users can easily reminisce about their memories.

[0836] (Example 1)

[0837] 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".

[0838] In modern households, effectively managing everyone's schedules and planning fulfilling family activities is crucial. However, centrally managing everyone's schedules is not easy, often resulting in schedule overlaps and inconsistencies. Furthermore, methods for organizing and preserving family memories are not common, leading to challenges such as the loss of records and difficulty in accessing them.

[0839] 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.

[0840] In this invention, the server includes means for storing information, means for analyzing information, and means for generating improvement suggestions. This enables centralized management and optimization of the schedules of all family members. Furthermore, by providing activity suggestions, it is possible to recommend effective activities based on the family's past interests and external information, and it is possible to provide a system that organizes, saves, and easily accesses memories.

[0841] A "terminal device" is a device used by users to input information and receive notifications.

[0842] A "server device" is a central computer that stores and analyzes data received from terminal devices.

[0843] An "analysis device" is a device that analyzes accumulated data and has the function of detecting schedule overlaps and inconsistencies.

[0844] A "proposal device" is a device that has the function of generating revised or improved suggestions for the user based on the analysis results.

[0845] A "notification device" is a system for transmitting generated proposals and revisions to the user's terminal device.

[0846] A "data collection device" is a device that has the function of acquiring and storing past activity history and external event information.

[0847] A "recommended device" is a device that has the function of suggesting family-oriented activities and events based on collected data.

[0848] A "display device" is a device that visualizes proposed activities and generated albums for the user.

[0849] A "storage device" is a storage system for automatically storing images and videos.

[0850] A "classification device" is a device that analyzes stored media and classifies it based on specific events or themes.

[0851] A "generation device" is a device that has the function of creating a digital album based on the analyzed media.

[0852] A "viewing device" is a device that allows users to access and view the generated digital album.

[0853] This invention is a system for effectively managing family schedules and memories. The system primarily consists of terminal devices and a server device.

[0854] The server uses high-performance computer equipment to store and analyze information. Specifically, it uses cloud services and database technologies to store and analyze a wide range of data. This includes using programming languages ​​such as Python to analyze and classify the data. The server also utilizes open APIs to retrieve external event information and provide recommendations.

[0855] The device functions as a means for users to input information and receive notifications. This includes widely used mobile devices such as smartphones and tablets. The user interface is developed as an application using React Native, allowing for intuitive operation. The device also features an interface for automatically capturing images and videos and uploading them to a server. Specifically, the device uploads media to cloud storage such as Amazon S3.

[0856] Users input their daily schedules into their devices. For example, by entering the date of their child's school performance, that information is sent to the server. The server analyzes this data and compares it with the parent's schedule to check for any overlaps. If there are overlaps, the server generates a suggested adjustment and notifies the parent. Similarly, based on past data, the server retrieves information on nearby activities and suggests events that the whole family can enjoy.

[0857] An example prompt might be, "Check if there are any conflicts in today's schedule and suggest nearby events that the family can enjoy." Using this prompt, the server will perform appropriate analysis and make suggestions.

[0858] This system allows users to efficiently manage their family's schedules and plan enriching family experiences.

[0859] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0860] Step 1:

[0861] The user enters schedule information into the terminal. This information includes date, time, location, and event details. The user interface is designed to allow intuitive input of information in a calendar format. Immediately after input, the information is converted to JSON format and ready to be sent to the server.

[0862] Step 2:

[0863] The terminal sends the entered schedule information to the server. The data is transferred to the cloud server in JSON format via the HTTP protocol. This process allows the server to receive data that can be parsed in the next step.

[0864] Step 3:

[0865] The server analyzes the received schedule information. While storing the information in a database, it uses an information analysis algorithm to detect duplicates and inconsistencies. A Python script then runs to identify related schedules. Based on this analysis, data integrity is verified.

[0866] Step 4:

[0867] Based on the analysis results, the server generates improvement suggestions for problematic schedules. For example, if there are scheduling overlaps, it considers alternative time options and creates adjustment plans. The suggestions are recorded in the database and ready for notification.

[0868] Step 5:

[0869] The server notifies the user's device of the generated suggestions. Specific suggestions are delivered to the user via email or in-app notifications. Notifications are delivered quickly, ensuring the user is ready to take immediate action.

[0870] Step 6:

[0871] The server analyzes past interests and external event information to suggest activities that fit the user. Using newly collected local event information from open APIs, it generates suggestions based on an AI model. These suggestions are prioritized based on the user's interests and schedule.

[0872] Step 7:

[0873] The user reviews the suggested activities on their device and selects the appropriate one. The selected activity information is sent to the server and automatically added to the schedule. This selection process is designed with usability in mind and can be completed quickly.

[0874] Step 8:

[0875] The device automatically uploads family photos and videos to the cloud. It sorts media stored on the device in the background and transfers it to a storage server. Cloud storage like Amazon S3 is used, creating a user-friendly environment.

[0876] Step 9:

[0877] The server analyzes uploaded media and generates albums. Machine learning algorithms are used to classify and tag photos and videos. This creates digital albums organized by time and event, improving the user's digital experience.

[0878] Step 10:

[0879] Users can view digital albums generated on their devices. An interactive and user-friendly interface is provided, making it easy for the whole family to reminisce about past memories. Albums are updated in real time and are accessible at any time.

[0880] (Application Example 1)

[0881] 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".

[0882] In today's busy families, there is a need to efficiently manage the schedules of all family members and optimize activities by utilizing local information. Another challenge is organizing everyday memories as digital data, making them easily accessible to all family members. This will help avoid conflicts in individual schedules and facilitate smooth family activities. Furthermore, it is necessary to use the acquired information to build a richer daily life.

[0883] 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.

[0884] In this invention, the server includes information acquisition means for inputting the schedules of multiple users, information storage means for storing the schedules acquired by the information acquisition means, and information optimization means for acquiring external information based on regional information and optimizing the schedule. This enables efficient centralized management of the entire family's schedule and allows for optimal activity suggestions utilizing external information.

[0885] "Information acquisition means" refers to a function within the system that provides an interface for users to input their schedules and accepts those schedules.

[0886] "Information storage means" refers to a function for securely saving acquired schedules on the cloud or locally.

[0887] A "duplicate detection method" is a function that analyzes saved schedules and checks for duplicates or inconsistencies.

[0888] A "means for generating improvement measures" is a function for creating solutions based on overlaps and contradictions in the schedule.

[0889] A "notification method" is a function that transmits generated improvement measures and important information to the user's device.

[0890] "Information optimization means" refers to functions that optimize schedules based on local and external information.

[0891] A "recommendation generation method" is a function that analyzes activity data and external information to recommend the most suitable activities for the user.

[0892] "Presentation means" refers to a function for displaying generated activity recommendations and information on the user interface.

[0893] A "digital data storage method" is a function that automatically saves captured photos and videos in digital format.

[0894] "Information processing means" refers to a function that analyzes stored digital data and adds specific event information.

[0895] An "album presentation method" is a function that displays the generated digital album to the user and makes it viewable.

[0896] The "activity suggestion method" is a function that recommends activities from a digital album generated based on the user's selection.

[0897] This invention provides a system for efficiently managing family schedules and supporting the optimization of activities using local information. This system includes a server and user devices and operates in a cloud environment. Specific embodiments are described below.

[0898] The server is equipped with information acquisition means for receiving each user's schedule data. This means receives schedule data entered from the user's device via the cloud and securely stores it using information storage means. The stored data is analyzed by duplicate detection means to automatically detect inconsistencies and schedule conflicts. Furthermore, based on these detection results, improvement measure generation means generates recommendations to resolve the conflicts and communicates them to the user via notification means.

[0899] Furthermore, information optimization methods incorporate external data such as local and weather information to optimize each family's schedule. This optimization makes it easier for users to plan meaningful activities. For example, it can suggest outdoor activities based on weekend weather information.

[0900] User devices are equipped with recommendation generation capabilities, enabling them to suggest activities and local events tailored to each individual. These suggestions are displayed on the user interface through the suggestion system, allowing users to easily incorporate them into their schedules.

[0901] In addition, the captured visual data is automatically saved to the cloud by a digital data storage device. Subsequently, an information processing device analyzes the data and tags it in relation to the event. The generated digital album is displayed on the user's device via an album display device, providing a system that allows users to easily enjoy family memories.

[0902] For example, if a user enters a prompt such as, "Please recommend some outdoor activities for this weekend," the system will provide optimal suggestions considering weather and event information. This functionality is automatically implemented by inputting prompt text using a generative AI model.

[0903] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0904] Step 1:

[0905] The user enters appointment information on their device.

[0906] The entered schedule data is sent to the server via an information retrieval device. The server receives this data and securely stores it in the cloud using an information storage device.

[0907] Step 2:

[0908] The server analyzes the stored schedule data.

[0909] A duplicate detection mechanism is used to check for conflicts with other appointments entered at the same time. If duplicates or inconsistencies are found, the information is sent to the improvement plan generation mechanism.

[0910] Step 3:

[0911] The improvement solution generation mechanism generates recommended solutions for resolving contradictions.

[0912] Specifically, a schedule adjustment proposal is created, taking priorities into consideration. This proposal is then sent to the user's device via a notification system. The output provides the adjusted schedule proposal.

[0913] Step 4:

[0914] The user device receives the notification and displays it in the user interface.

[0915] The user will review this and manually adjust the schedule if necessary.

[0916] Step 5:

[0917] Information optimization tools acquire local weather information and event information.

[0918] Based on this external information, the server re-evaluates the user's original schedule and generates suggestions for optimal activities.

[0919] Step 6:

[0920] The recommendation generation system generates activity recommendations tailored to each individual user.

[0921] The server generates recommendations based on past user behavior data and interests, and displays them on the user interface using a presentation tool.

[0922] Step 7:

[0923] Visual data captured by the user is automatically saved.

[0924] Digital data storage devices store data in the cloud, and it is analyzed through information processing devices. Tagged data is then generated as a digital album.

[0925] Step 8:

[0926] The album presentation method displays this album on the user's device.

[0927] Users can browse this album and reminisce about their memories. Additionally, the activity suggestion feature provides recommended activity ideas based on the user's choices.

[0928] Step 9:

[0929] When a user inputs a prompt into the generated AI model, the system provides the most appropriate information suggestions in response.

[0930] The system processes data based on user requests and generates the necessary output information. For example, in response to a prompt such as "What are some recommended indoor events nearby?", the system returns the corresponding event information.

[0931] 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.

[0932] This invention proposes a system that not only improves schedule management for the entire family but also provides a more personalized experience to the user by combining it with emotion recognition technology.

[0933] This system operates through family terminals and a server running on the cloud. The terminals have information input capabilities, allowing parents and children to enter their daily schedules. The entered schedules are transmitted from the terminals to the server via an information transmission device and stored in a cloud database.

[0934] The server is equipped with analytical tools to analyze stored schedule data and detect duplicates and inconsistencies. Based on the analysis results, it generates schedule improvement suggestions and sends these suggestions to the terminal via a notification system. This cycle allows users to optimize their schedule management.

[0935] Furthermore, by combining it with an emotion engine, the system achieves a new level of personalization. The device analyzes the user's voice and facial expressions, and the emotion engine recognizes their emotions. This emotion data is sent to and stored on a server. Based on this data, the server utilizes a suggestion update mechanism to generate suggestions tailored to the user's current emotional state. For example, if the system detects that the user is feeling stressed, it can suggest relaxing activities or schedule adjustments.

[0936] It also features emotional integration, which combines past interest and emotional data of the family, further personalizing the suggestions. This allows the system to consider the user's past preferences and present the most suitable activities.

[0937] For example, if the emotion engine determines that a child is feeling stressed in their new school environment, the server will suggest a parent-child event that can help the child relax. This suggestion will be displayed on the device, and the user can choose to participate.

[0938] The system also integrates a memory recording function, automatically uploading photos and videos taken by users to the cloud via media storage. The server analyzes this data and tags it in relation to events, creating a digital album. Users can view this album through their device, recording family growth and special moments. In this way, a new system incorporating emotional elements enables a richer and more seamless family life.

[0939] The following describes the processing flow.

[0940] Step 1:

[0941] The user opens the schedule input screen on their device and enters a new appointment or event. The device temporarily saves this information to its memory.

[0942] Step 2:

[0943] The terminal sends the entered schedule information to a server in the cloud. During this process, data security is ensured based on security protocols.

[0944] Step 3:

[0945] The server saves the received schedule information to a cloud database. The saved information is then analyzed to detect duplicates and inconsistencies.

[0946] Step 4:

[0947] The server generates schedule improvement suggestions based on the analysis results. In particular, it creates suggestions to resolve simultaneous events and time constraints.

[0948] Step 5:

[0949] The server generates improvement suggestions and sends them to the home terminal using a notification system. The terminal displays these suggestions in its user interface, and the user reviews the content.

[0950] Step 6:

[0951] The user accepts the proposal and enters approval or modification instructions via their device. The modifications are then resent from the device to the server.

[0952] Step 7:

[0953] To recognize the user's emotions, the device uses built-in sensors and cameras to acquire voice and facial expression data. This data is then input into the emotion engine.

[0954] Step 8:

[0955] The emotion engine analyzes the user's emotions in real time and sends that data to the server. The server stores this data and updates activity and schedule suggestions to match the user's current emotional state.

[0956] Step 9:

[0957] The server presents suggestions to the terminal based on emotional data. These suggestions include relaxation activities and appropriate events tailored to the user's emotional state.

[0958] Step 10:

[0959] The device receives feedback from the user and sends it to the server. The server uses this feedback to improve the accuracy of future suggestions.

[0960] Step 11:

[0961] Photos and videos taken by users on a daily basis are automatically uploaded to the cloud by their devices. The server then performs media analysis and tagging on these videos and associates them with events.

[0962] Step 12:

[0963] The server generates a digital album based on the analyzed media data and sends it to the user's device. The user can then view this album and enjoy their memories.

[0964] (Example 2)

[0965] 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".

[0966] There is a need to comprehensively improve the scheduling of the entire family, eliminate overlaps and contradictions in daily schedules, and provide a personalized user experience for each member by offering suggestions based on individual emotions and past interests. Furthermore, a system is needed to efficiently save and manage family memories and allow for easy recollection. These challenges remain unresolved in many existing systems.

[0967] 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.

[0968] In this invention, the server includes information transmission means, data analysis means, and emotion recognition means. This enables the detection of overlaps and inconsistencies in each member's schedule and the provision of optimized suggestions. Furthermore, emotion recognition technology allows for personalized suggestions tailored to the user's emotions, and by automatically saving and tagging family memories, it is possible to generate a digital record collection that can be easily viewed.

[0969] An "information input means" is a mechanism that provides an interface for all family members to input their schedules.

[0970] "Information transmission means" refers to a communication means for receiving entered schedules and saving them to network data storage.

[0971] "Data analysis means" refers to processing means for analyzing schedules within network data storage and detecting and reporting duplicates and inconsistencies.

[0972] The "proposal generation method" is an algorithm for generating schedule improvement suggestions based on the detected problems.

[0973] A "notification mechanism" is a system for notifying the user's terminal of the generated proposal.

[0974] "Emotion recognition means" refers to technology that analyzes a user's voice and facial expressions to recognize emotional data.

[0975] A "proposal update method" is a method for updating schedule proposals based on sentiment data.

[0976] A "data collection method" is a system for collecting data on a family's past interests and external activities.

[0977] A "recommendation generation method" is a process for generating suitable activities based on collected information.

[0978] A "presentation means" is a device for displaying recommended activities on the user's terminal.

[0979] "Emotional integration methods" are techniques for integrating emotional data with past interest data to personalize suggestions.

[0980] "Media storage means" refers to technology for automatically saving images and videos to network storage media.

[0981] "Tagging" refers to a technology that analyzes stored media and labels it as a specific event.

[0982] An "album generation method" is a method for generating a digital record collection based on analyzed media.

[0983] "Viewing method" refers to an interface that allows users to view the generated digital record collection on their terminals.

[0984] This invention is a system that manages the schedules of all family members and provides personalized suggestions based on their emotions, and is primarily implemented using a user's device and a server operating in the cloud. The device is equipped with means for inputting information to enter the family's schedule, including a touchscreen and voice input functionality. For example, if the user says, "Let's have a picnic in the park on Saturday," the device converts the voice data into text and sends it to the server.

[0985] The server stores the received schedule data in cloud data storage and uses data analysis tools to detect overlaps and inconsistencies in appointments. To do this, the server utilizes natural language processing technology to analyze the input data. Once the analysis is complete, improvement suggestions are sent to the user's terminal via a notification system. These improvement suggestions are displayed on the terminal as notifications such as, "How about changing your library appointment to 12:00?"

[0986] Furthermore, the device uses a microphone and camera to capture the user's voice and facial expressions, analyzes the data through emotion recognition, and sends the emotion data to a server. This data is analyzed in real time by the server, and a suggestion update mechanism generates more appropriate suggestions based on the user's emotions. For example, if the system detects that the user is feeling stressed, it might suggest, "Try taking a relaxation yoga class this weekend."

[0987] The server personalizes these suggestions and activities using the user's past interest and emotional data. In particular, it uses emotional integration techniques to generate more detailed and personalized suggestions that take into account the user's past experiences and preferences. Based on this process, prompts such as "How can I suggest relaxing activities when the user is feeling stressed?" are used.

[0988] The device further utilizes media storage means to automatically save images and videos taken by the user on the network, and to tag them and generate digital archives. A server-based tagging system analyzes the captured content and labels each event. As a result, users can view digital albums associated with specific events and easily reminisce about past memories.

[0989] This series of processes allows users to efficiently manage their daily schedules, receive emotionally resonant suggestions, and record family memories. This enables the whole family to enjoy a richer, more personalized life.

[0990] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0991] Step 1:

[0992] Users enter their schedules using a terminal. They can input their daily plans via a touch interface or voice input. This input is converted to text and sent to the server via the information input device. For example, if a user voice-inputs "Picnic at the park at 10am on Saturday," the terminal converts the voice data into text data and sends it to the server.

[0993] Step 2:

[0994] The server stores the received text data in network data storage. Data transmitted via the information transmission means is then analyzed by the data analysis means to detect duplicates and inconsistencies. Natural language processing algorithms are used to analyze the data and identify overlapping appointments on the same date and time. For example, if it is determined that "there are two events starting at 10:00," the nature of the overlap is clarified.

[0995] Step 3:

[0996] The server generates improvement suggestions based on the detected duplicates and inconsistencies. The suggestion generation mechanism operates and calculates the optimal solution through an algorithm. For example, a suggestion such as "change the library visit time to 12:00" is generated. This suggestion is sent from the server to the terminal via a notification mechanism, and the user can review the suggested improvement.

[0997] Step 4:

[0998] The device collects user emotional data using emotion recognition technology. Using the camera and microphone, it analyzes the user's facial expressions and voice tone, and sends this data to a server. The emotional data is further analyzed on the server to determine the user's emotional state. For example, it might obtain emotional data indicating that "the user is nervous."

[0999] Step 5:

[1000] The server updates its suggestions based on sentiment data. Using a suggestion update mechanism, it creates personalized suggestions through a generative AI model. For example, if a user is feeling stressed, a suggestion such as "We recommend a relaxing yoga class for the weekend" might be generated.

[1001] Step 6:

[1002] The server integrates the family's past interest and emotional data to further personalize suggestions. Emotional integration recommends activities based on past activities and current emotions. Users can view these recommended activities on their device and select them as appropriate.

[1003] Step 7:

[1004] The device automatically uploads photos and videos taken by the user to the network. The captured data is stored using media storage methods, and the server analyzes it. The analyzed data is tagged by event, and a digital album is generated. This album can be viewed through the device, allowing family members to reminisce about cherished memories.

[1005] (Application Example 2)

[1006] 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".

[1007] In today's society, family schedules have become increasingly complex, requiring smooth coordination. However, conventional schedule management systems have the problem of failing to consider family members' feelings and past interests, making it difficult to provide optimal suggestions tailored to individual circumstances. Furthermore, there has been a lack of systems for efficiently organizing memories and making them easily accessible at any time.

[1008] 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.

[1009] In this invention, the server includes information input means, analysis means, and emotion analysis means. This enables personalized suggestions that take into account not only the schedules of all family members but also their emotional data. Furthermore, by automatically saving video data and identifying specific events, the creation and viewing of digital memory collections becomes easier.

[1010] An "information input method" is a system for inputting the schedules and related information of all family members through a terminal or device.

[1011] The "information transmission means" refers to a function that sends the entered family schedule information to a server and stores it in a large-scale data management device.

[1012] "Analysis means" refers to a mechanism for analyzing schedule information stored in a large-scale data management system to detect schedule overlaps and inconsistencies.

[1013] The "proposal generation means" is a function that generates improved proposals based on the problems detected by the analysis means.

[1014] A "notification mechanism" is a system for transmitting generated suggestions to a home information display device to inform the user.

[1015] "Emotion analysis means" refers to technology that analyzes the user's voice and facial expression data to recognize their emotions. This makes it possible to generate suggestions that are tailored to the user's emotions.

[1016] "Data collection means" refers to functions for collecting data on a family's past interests and external events.

[1017] A "recommendation generation method" is a function that generates optimal recommended actions for families based on information obtained through data collection methods.

[1018] The "presentation means" is a mechanism that displays recommended actions created by the recommendation generation means on a home information display device so that the user can confirm them.

[1019] "Media storage means" refers to a function that automatically saves video data taken by family members to a large-scale data management device.

[1020] "Identification means" refers to a function that analyzes video data stored in media storage means and tags specific events or occurrences.

[1021] A "collection and generation method" is a system for creating and organizing digital memory collections based on analyzed video data.

[1022] "Viewing method" refers to a function that allows the generated digital collection of memories to be viewed on a home information display device.

[1023] The system for realizing this invention includes a home information display device, a server, a large-scale data management device, a camera, a microphone, and related software. The home information display device functions as an information input means for receiving input from a user and includes an information transmission means for transmitting the input data to the server.

[1024] The server analyzes information stored in a large-scale data management system, detects scheduling overlaps and inconsistencies, and further analyzes the user's voice and facial expression data using emotion analysis tools to recognize their emotions. This allows the server to generate personalized suggestions tailored to the user's emotions. For example, if a user is stressed, the server suggests relaxing activities. Such suggestions are notified to a home information display device, making it easier for the user to understand what actions are appropriate.

[1025] Furthermore, it is equipped with data collection and recommendation generation capabilities, which generate optimal recommended actions based on past interest data and external event information. In addition, it automatically saves and organizes family video data using media storage and identification capabilities to create a digital memory collection that can be viewed on a home information display device. Specifically, photos and videos from summer vacation trips will be automatically organized and made viewable.

[1026] The specific hardware used includes smart displays as home information display devices, cloud-based servers for data analysis, and microphones and cameras for emotion recognition. For software, Google Cloud Speech-to-Text and Amazon Lex are used for speech recognition, while Microsoft Azure's Emotion API is used for emotion analysis.

[1027] Example of a prompt:

[1028] "You are a highly hospitable home robot. Support the family's daily schedule management and provide relaxing suggestions based on their emotions. For example, how can you suggest relaxing music when family members are feeling stressed?"

[1029] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1030] Step 1:

[1031] The home information display device (terminal) accepts schedule and task input from the user. The input data is sent to a server using an information transmission method, preparing data for scheduling overlaps and sentiment analysis. Since voice input is also included, Google Cloud Speech-to-Text is used. The output of this step is the user's schedule information and voice data.

[1032] Step 2:

[1033] The server stores the received data in a large-scale data management system. Then, it analyzes the stored data using analytical tools to detect schedule overlaps and inconsistencies. The problems identified as a result of the analysis are then prepared as input data for the next step. The output of this step is the analyzed schedule data.

[1034] Step 3:

[1035] The server uses emotion analysis tools to analyze the user's emotions from voice and facial expression data. Using voice and image data as input, it performs analysis using the Microsoft Azure Emotion API to extract the emotions the user may be experiencing. The output of this step is information about the emotional state.

[1036] Step 4:

[1037] Based on the analyzed schedule data and emotional state information, the server generates emotionally appropriate improvement suggestions and recommended actions using a suggestion generation mechanism. For example, if it is determined that the user is feeling stressed, it will suggest relaxing activities. This process is performed using a generation AI model based on prompt statements. The output of this step is improvement suggestions.

[1038] Step 5:

[1039] The server notifies the home information display device of the generated suggestions via an information transmission means. The terminal displays the received suggestions to the user and provides an opportunity to select the suggested activities or actions. The output of this step is the suggestion information displayed to the user.

[1040] Step 6:

[1041] The terminal automatically saves video data captured by the user to a large-scale data management system using media storage means. The server analyzes the saved data using identification means and tags specific events. This tagged data becomes the input data for the next step. The output of this step is tagged media information.

[1042] Step 7:

[1043] The server uses tagged video data to create a digital memory collection using a collection generation method. The generated digital memory collection can be viewed on a home information display device, allowing users to easily reminisce about family memories. The output of this step is a viewable digital memory collection.

[1044] 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.

[1045] 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.

[1046] 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.

[1047] 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.

[1048] 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.

[1049] 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.

[1050] 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.

[1051] 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.

[1052] 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."

[1053] 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.

[1054] 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.

[1055] 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.

[1056] 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.

[1057] 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.

[1058] 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.

[1059] 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.

[1060] 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.

[1061] 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.

[1062] 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.

[1063] 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.

[1064] 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.

[1065] The following is further disclosed regarding the embodiments described above.

[1066] (Claim 1)

[1067] A means of inputting information for entering the schedules of all family members,

[1068] Information transmission means that receives the schedule entered by the information input means and saves it to a cloud database,

[1069] An analysis means for analyzing schedules in the aforementioned cloud database and detecting and reporting duplicates and inconsistencies,

[1070] A proposal generation means that generates improvement suggestions based on the detected problems,

[1071] A notification means for notifying a home terminal of the generated proposal,

[1072] A system that includes this.

[1073] (Claim 2)

[1074] A data collection method for collecting data on the family's past interests and external event information,

[1075] A recommendation generation means that generates recommended activities based on the information collected by the aforementioned data collection means,

[1076] A presentation means for displaying the aforementioned recommended activities to a home terminal,

[1077] The system according to claim 1, including the following:

[1078] (Claim 3)

[1079] A media storage method for automatically saving photos and videos taken by family members to the cloud,

[1080] A tagging means that analyzes the media stored by the media storage means and tags specific events,

[1081] An album generation method that generates a digital album based on the analyzed media,

[1082] A viewing means for making the aforementioned digital album viewable on a home terminal,

[1083] The system according to claim 1, including the following:

[1084] "Example 1"

[1085] (Claim 1)

[1086] A terminal device for inputting information,

[1087] A server device that receives information input by the terminal device and stores the data,

[1088] An analysis device that analyzes the accumulated data and detects duplication and inconsistencies,

[1089] A proposal device that generates improvement plans based on detected problems,

[1090] A notification device that notifies the terminal device of the generated proposal,

[1091] A system that includes this.

[1092] (Claim 2)

[1093] A data collection device that collects past activity data and external event information,

[1094] A recommendation device that recommends activities based on the information collected by the aforementioned data collection device,

[1095] A display device that shows the recommended activity,

[1096] The system according to claim 1, including the following:

[1097] (Claim 3)

[1098] A storage device for automatically saving captured images and videos,

[1099] A classification device that analyzes images and videos stored by the aforementioned storage device and classifies specific events,

[1100] A generating device that generates an album based on analyzed images and videos,

[1101] A viewing device that makes the generated album viewable on a display device,

[1102] The system according to claim 1, including the following:

[1103] "Application Example 1"

[1104] (Claim 1)

[1105] A means of obtaining information for inputting the schedules of multiple users,

[1106] Information storage means for storing the schedule acquired by the information acquisition means,

[1107] A duplicate detection means analyzes the schedule stored by the aforementioned information storage means and detects duplicates and inconsistencies,

[1108] A means for generating improvement measures based on the detected problems,

[1109] A notification means for notifying information terminals of the generated improvement measures,

[1110] An information optimization method that acquires external information based on local information and optimizes the schedule,

[1111] A system that includes this.

[1112] (Claim 2)

[1113] A recommendation generation means that collects activity data and external information and generates recommendations for the user,

[1114] A presentation means for presenting recommendations generated by the recommendation generation means to the user interface,

[1115] The system according to claim 1, including the following:

[1116] (Claim 3)

[1117] A digital data storage method for automatically saving captured visual data,

[1118] Information processing means for analyzing the digital data stored by the aforementioned digital data storage means and adding event information,

[1119] An album presentation means that generates an album based on the analyzed digital data and makes it viewable on the user's device,

[1120] An activity suggestion means that generates activity recommendations based on a digital album generated according to the user's selection,

[1121] The system according to claim 1, including the following:

[1122] "Example 2 of combining an emotion engine"

[1123] (Claim 1)

[1124] A means of inputting information for entering the schedules of all family members,

[1125] Information transmission means that receives the schedule entered by the information input means and stores it in network data storage,

[1126] A data analysis means for analyzing schedules in the aforementioned network data storage and detecting and reporting duplicates and inconsistencies,

[1127] A proposal generation means that generates improvement suggestions based on the detected problems,

[1128] A notification means for notifying the user terminal of the generated proposal,

[1129] An emotion recognition method that analyzes the user's voice and facial expressions to recognize emotion data,

[1130] A proposal update means that updates the proposal based on the aforementioned sentiment data,

[1131] A system that includes this.

[1132] (Claim 2)

[1133] A data collection method for collecting data on the family's past interests and external activities,

[1134] A recommendation generation means that generates recommended activities based on the information collected by the aforementioned data collection means,

[1135] A presentation means for displaying the aforementioned recommended activity to the user's terminal,

[1136] An emotion integration means that integrates the aforementioned emotion data and the aforementioned past interest data to personalize the proposal,

[1137] The system according to claim 1, including the following:

[1138] (Claim 3)

[1139] A media storage method for automatically saving images and videos taken by family members to a network storage medium,

[1140] A tagging means for analyzing media stored by the media storage means and tagging specific activities,

[1141] An album generation method that generates a digital record collection based on the analyzed media,

[1142] A viewing means that makes the aforementioned digital record collection viewable on a user terminal,

[1143] The system according to claim 1, including the following:

[1144] "Application example 2 when combining with an emotional engine"

[1145] (Claim 1)

[1146] A means of inputting information for entering the schedules of all family members,

[1147] Information transmission means that receives the schedule entered by the information input means and stores it in a large-scale data management device,

[1148] An analysis means for analyzing the schedule within the aforementioned large-scale data management device and detecting and reporting duplicates and inconsistencies,

[1149] A proposal generation means that generates improvement suggestions based on the detected problems,

[1150] A notification means for notifying a home information display device of the generated proposal,

[1151] An emotion analysis means that performs emotion analysis and generates individual suggestions according to the user's emotional state,

[1152] A system that includes this.

[1153] (Claim 2)

[1154] A data collection method for collecting data on the family's past interests and external event information,

[1155] A recommendation generation means that generates recommended actions based on the information collected by the aforementioned data collection means,

[1156] A presentation means for presenting the aforementioned recommended behavior to a home information display device,

[1157] The system according to claim 1, including the following:

[1158] (Claim 3)

[1159] A media storage method for automatically saving video data taken by family members to a large-scale data management device,

[1160] An identification means for analyzing media stored by the media storage means and identifying a specific event,

[1161] A collection generation method for generating a digital collection of memories based on analyzed media,

[1162] A viewing means for making the aforementioned digital collection of memories viewable on a home information display device,

[1163] The system according to claim 1, including the following: [Explanation of Symbols]

[1164] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of inputting information for entering the schedules of all family members, Information transmission means that receives the schedule entered by the information input means and saves it to a cloud database, An analysis means for analyzing schedules in the aforementioned cloud database and detecting and reporting duplicates and inconsistencies, A proposal generation means that generates improvement suggestions based on the detected problems, A notification means for notifying a home terminal of the generated proposal, A system that includes this.

2. A data collection method for collecting data on the family's past interests and external event information, A recommendation generation means that generates recommended activities based on the information collected by the aforementioned data collection means, A presentation means for displaying the aforementioned recommended activities to a home terminal, The system according to claim 1, including the following:

3. A media storage method for automatically saving photos and videos taken by family members to the cloud, A tagging means that analyzes the media stored by the media storage means and tags specific events, An album generation method that generates a digital album based on the analyzed media, A viewing means for making the aforementioned digital album viewable on a home terminal, The system according to claim 1, including the following:

Images