system

Abstract

We provide the system. [Solution] Means for acquiring visual data and schedule information stored in a mobile communication device, Means for transmitting the aforementioned visual data and schedule information to a data processing device, The data processing device includes means for generating text based on received visual data and schedule information, Means for transmitting the aforementioned text to the mobile communication device, In the aforementioned mobile communication device, the means for displaying the text, 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 persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In an information society, although a diary is useful as a means for individual users to record their daily activities, manual recording is time-consuming and laborious, so there is a problem that it is difficult to use continuously. In addition, since there is a lack of means to effectively manage past activities and purchase histories, there is also a problem that the efficiency of daily life as a whole is not improved.

Means for Solving the Problems

[0005] The present invention provides a means for acquiring visual data and schedule information stored in a mobile communication device (hereinafter referred to as a terminal) and transmitting it to a data processing device (hereinafter referred to as a server). The server includes means for generating text based on the received visual data and schedule information, and for transmitting the generated text back to the terminal for display. It also has a function to suggest repurchases by referencing the purchase history of products based on the visual data and schedule information. Furthermore, it includes means for identifying people or places by analyzing the visual data and adding special notes.

[0006] A "mobile communication device" is a computer device that a user can carry and use, and that is capable of collecting, storing, and transmitting data.

[0007] "Visual data" refers to image and video files stored in digital format, and includes information captured using a camera function.

[0008] "Schedule information" refers to data about a user's activities or events on a specific date and time, and is information recorded in applications such as calendars.

[0009] A "data processing device" is a computing system that can analyze received data and perform various processing operations based on the analysis results.

[0010] "Means for generating text" refers to a function that creates text expressed in natural language based on the results of data analysis.

[0011] "Purchase history" refers to data that records details of products that a user has acquired or purchased in the past.

[0012] A "means of suggesting repurchase" refers to a function that encourages users to purchase equivalent or similar products again, based on products they have previously purchased.

[0013] "Means for reinforcing special notes" refers to a function that adds additional information to the content of a standardly generated diary based on the results of visual data analysis. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, when an emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying out the Invention

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention utilizes a mobile communication device (terminal) and a data processing device (server) to achieve automatic diary generation. The operation of this system is described in detail below.

[0036] The device is used to record the user's daily activities. It retrieves visual data and schedule information from the image library and calendar app. This data becomes the material for a diary automatically generated based on the user's activity records over a certain period.

[0037] The collected data is transmitted to the server via the network using a secure protocol. The server executes advanced data analysis algorithms, performing object recognition from images, text analysis, and integrating schedule and location information. This analysis provides a comprehensive understanding of the day's activities, and natural language processing is used to generate diary-style entries.

[0038] For example, if a user takes an image on a particular day that includes a restaurant, the server analyzes the image to identify details such as, "On this day, I enjoyed a meal with a friend at a specific restaurant." Furthermore, it cross-references this with the user's schedule information to supplement the time and location details.

[0039] Furthermore, the server manages users' purchase history and can recommend repurchases of items relevant to their journal entries. This significantly improves the convenience of users' daily lives.

[0040] The generated diary is sent back to the device and displayed to the user through the device's application. The user can view the diary's contents, edit it as needed, and share it with others. This entire process allows for detailed recording of daily events without the need for manual input.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The device retrieves visual data stored on the user's device and extracts image files from the photo library for a specified period. It also collects associated metadata (such as the date and time of capture and location information).

[0044] Step 2:

[0045] The device accesses the user's calendar application to retrieve event information for a specified period. It collects event titles, dates and times, and participant information to use as data to understand the context of the activities.

[0046] Step 3:

[0047] The device uses GPS data to obtain the user's daily movement history. This allows for accurate recording of the places and times the user has visited.

[0048] Step 4:

[0049] The device encrypts the collected visual data, schedule information, and GPS data, and sends it to the server as a data package. A secure communication protocol is used to prevent information leakage.

[0050] Step 5:

[0051] The server decodes the received data and performs image analysis from the visual data. It extracts information about people, places, and objects from the image to grasp the general outline of the activity. It performs sentiment analysis to evaluate the atmosphere of the image.

[0052] Step 6:

[0053] The server cross-references scheduled information with GPS data and organizes user activity chronologically. It verifies the consistency between scheduled events and actual activities and analyzes the reasons for any discrepancies.

[0054] Step 7:

[0055] The server generates text based on the analysis results, creating a diary-style document. It expresses the user's daily activities in natural language, supplementing any special notes.

[0056] Step 8:

[0057] The server analyzes the user's purchase history and suggests repurchasing items related to their activities in their journal. It also provides the user with information about items they have previously purchased.

[0058] Step 9:

[0059] The server sends the generated diary and repurchase suggestions to the device, and the device displays this content in the application. The user reviews the diary content and edits or shares it with others as needed.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] Manually recording daily events and activities is a time-consuming and laborious task for users. Furthermore, the resulting records are often incomplete and lack usefulness when viewed later. Additionally, there is a lack of systems for integrating and effectively utilizing related information such as purchase history and schedules.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for generating text in natural language based on visual information and scheduled information, means for generating text using a generative AI model, and means for identifying objects or locations in the analysis of visual information and reinforcing special notes. This enables the user to automatically record daily events in detail and manage those records efficiently.

[0065] A "mobile communication device" is a device equipped with communication functions that can be used while on the move, such as a mobile phone, smartphone, or tablet.

[0066] "Visual information" refers to visual data such as photographs, images, and videos, and is information acquired to record the user's daily activities.

[0067] "Schedule information" refers to information about a user's planned activities and appointments, based on calendar applications or schedules.

[0068] An "information processing device" is a device that receives data, analyzes and processes it, and converts it into useful information, and includes computer systems such as servers.

[0069] "Natural language" refers to the language that humans use on a daily basis, and also refers to human-readable text formats generated by computer programs.

[0070] A "generative AI model" is a computational model that uses artificial intelligence to generate text and data, and is particularly characterized by its advanced natural language processing capabilities.

[0071] "Target identification" refers to the process of identifying objects and locations contained in visual information using image analysis techniques and extracting their characteristics.

[0072] "Reinforcing special notes" means highlighting important information and facts based on the information obtained through analysis, thereby improving the accuracy and usefulness of the record.

[0073] This invention is a system for efficiently recording and managing a user's daily activities by linking a mobile communication device and an information processing device. The embodiments for carrying out the invention are described in detail below.

[0074] A device is a mobile communication device such as a smartphone or tablet, and it plays a role in recording the user's daily activities. The device retrieves visual information such as photos and videos from its image library and collects schedule information from its calendar app. It can also obtain location information using GPS functionality.

[0075] The collected visual and schedule information is sent to the server via the network using security protocols such as HTTPS. The server, acting as an information processing device, processes the received data and performs advanced analysis. Libraries such as OpenCV are used for image analysis, and NLP tools such as spaCy and BERT are used for natural language processing. Furthermore, the server utilizes generative AI models to generate text in natural language based on the received visual and schedule information.

[0076] This system uses a generative AI model to automatically create diary-style entries, such as "On this day, I enjoyed a meal with a friend at a specific restaurant," based on visual and scheduled information. An example of a prompt used in this process is, "Based on the user's activity results, please summarize the day's events in detail in a diary," which is input to the generative AI model.

[0077] The server can also manage the user's purchase history and suggest repurchases of related products. The generated diary entries are sent back to the terminal and displayed to the user through a dedicated application. Users can view, edit, and share the provided diary entries with others.

[0078] This invention allows users to obtain a diary that accurately summarizes visual and scheduled information without requiring much effort, thereby improving the convenience of daily life.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] Users record their daily activities using the device. Specifically, the device acquires visual information using its camera and sensors. It also retrieves schedule information from its calendar app and records location information using its GPS function. As a result, image data, schedules, and location information are input into the device. This input data becomes the basic information necessary for subsequent processing.

[0082] Step 2:

[0083] The terminal encrypts the collected visual and schedule information using the HTTPS protocol and sends it to the server over the network. Specifically, the terminal periodically aggregates the accumulated data and forms a transmission batch. The output of this step is an encrypted data packet, which is then input to the server.

[0084] Step 3:

[0085] The server decrypts the encrypted data received from the terminal and begins data analysis. Here, the server uses the OpenCV library to analyze visual information and recognize objects and scenes. It uses NLP tools (spaCy and BERT) to analyze text information and understand the contents of schedules and diaries. The output of this step is the analyzed text data and image tag information.

[0086] Step 4:

[0087] The server uses a generative AI model to generate a diary in natural language from the analysis results. Specifically, it takes the prompt "Based on the user's activity results, please summarize the day's events in detail in a diary" as input to the model, and outputs a detailed natural language text. The output here is a text that summarizes the user's activities for the day.

[0088] Step 5:

[0089] The server sends the generated diary entries to the terminal. The terminal displays the received entries to the user using a dedicated application. Specifically, when the terminal receives new diary data, it notifies the user and provides an interface for viewing the content. The output of this step is the diary screen that the user can view.

[0090] Step 6:

[0091] Users can view the diary generated via their device and edit or share it with others as needed. Specifically, users can view the displayed diary and use editing tools to modify its content, or use the share button to send it to friends. The output is the final or shared diary content.

[0092] (Application Example 1)

[0093] 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."

[0094] In today's busy lives, it's difficult to meticulously record daily events and reflect on memories. Furthermore, to efficiently preserve personal life records, a system is needed that integrates various types of information and automates the process. In such systems, the challenge lies in improving the comprehensiveness, accuracy, and convenience of the recorded information.

[0095] 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.

[0096] In this invention, the server includes means for acquiring information stored in a mobile communication device, means for transmitting the information to a data processing device, means for generating text based on the received information, and means for collecting additional activity information using an environmental recording device. This makes it possible to record an individual's daily life with high accuracy and comprehensively, and to automatically generate detailed records as needed.

[0097] A "mobile communication device" is a terminal device with communication capabilities that can be carried and used by a user.

[0098] "Information" refers to all data related to the user's daily activities, including visual data, schedule information, and environmental data.

[0099] A "data processing device" is a computer system used to analyze received data and perform processing such as converting it into text.

[0100] An "environmental recording device" is a device equipped with instruments and sensors to record surrounding conditions and user behavior, and to acquire additional information.

[0101] "Inference" is the process of deriving a logical conclusion based on collected data.

[0102] "Purchase history" refers to a series of data related to purchases a user has made in the past, and is information used to analyze behavioral patterns based on that data.

[0103] "Identification target" refers to a specific person or object being analyzed, or their attributes.

[0104] "Space" refers to the physical area that constitutes the place or environment in which a user engages in activities.

[0105] "Important matters" refer to events or occurrences in daily life that are particularly worthy of being recorded or recognized.

[0106] To realize this invention, a system comprising a mobile communication device carried by the user, an environmental recording device, and a data processing server on the cloud is required. Specific embodiments are described in detail below.

[0107] First, the device collects the user's visual data and schedule information. Cameras and sensors built into the device record the user's actions and environmental conditions. This information is transmitted from the mobile communication device to a server in the cloud using a secure protocol.

[0108] After receiving the data, the server uses a service such as "Google Cloud Vision API" to perform image recognition, identifying specific objects and locations from the acquired images. In parallel, it uses a natural language processing model, such as "OpenAI's GPT model," to generate diary-style text based on the user's schedule and environment information.

[0109] By integrating the collected data and recognition results, a detailed activity log is generated, and the server creates a diary in a format customized to the user's preferences. For example, if the user enjoys a walk in the park, the server will write a sentence such as, "On a warm spring day, I spent time strolling leisurely in the park."

[0110] The generated diary is then sent back to the mobile communication device, and the user is notified on the terminal. The user can review the content and, if necessary, make edits or share it with others.

[0111] For example, you can input a prompt like, "Generate a text based on events that happened this morning. Inquiry details: weather, events at the park, time spent with family," into an AI model to obtain a detailed diary entry.

[0112] This entire process makes it an excellent system that allows users to automatically review and record their activities, even in the midst of a busy daily life.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The device uses cameras and sensors to collect image and audio data related to the user's daily activities. At this point, the input is visual and audio information obtained from the user's environment, and the output is this information being stored as data on the device.

[0116] Step 2:

[0117] The device transmits the collected information to the server via a secure protocol. The input is image and audio data from the device, and the output is the receipt of this data in an encrypted form to the server.

[0118] Step 3:

[0119] The server analyzes the received data and performs image analysis. Using image recognition technologies such as the Google Cloud Vision API, it identifies objects and locations from the data. The input is the received image data, and the output is the analyzed information about objects and locations.

[0120] Step 4:

[0121] The server further uses natural language processing (NLP) techniques to synthesize the received schedule information and the entire dataset into text. It is possible to utilize OpenAI's GPT model. The input consists of analyzed object / location information and schedule information, while the output is a diary-style text written in natural language.

[0122] Step 5:

[0123] The server sends the generated diary entries back to the terminal. The input is the generated text, and the output is the format in which it is displayed on the terminal.

[0124] Step 6:

[0125] Users can view their diary entries on their devices and manually edit or share them with others as needed. The input is the generated diary content, and the output is the edited or shared information.

[0126] 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.

[0127] The present invention relates to an embodiment of a system that integrates an emotion engine that recognizes a user's emotions and utilizes them as part of diary generation. This system is mainly composed of a mobile communication device (hereinafter referred to as a terminal) and a data processing device (hereinafter referred to as a server).

[0128] The device collects visual data and schedule information related to the user's daily activities. This data includes photos taken by the user and information about events they have attended, and serves as material for emotion recognition. In particular, visual data is a crucial element of emotion analysis, and the device infers the user's emotions from facial expressions and situations in images.

[0129] The collected data is transmitted to the server via a secure communication method. The server uses an emotion engine to recognize the user's emotions from the visual data. This emotion engine combines multiple algorithms; for example, it recognizes smiles and surprised expressions through image analysis and identifies emotions such as "I had a very enjoyable time today."

[0130] Next, the server generates diary entries that incorporate emotions. For example, if a user visited a tourist spot on a holiday and took many photos of themselves smiling, the entries might include phrases like, "I enjoyed my holiday and had a lot of fun." This process also includes analyzing purchase history, making it possible to suggest products that are relevant to the user's emotions.

[0131] The generated diary entries are sent to the device, where the user can view and edit them. In particular, emotionally charged entries are highlighted, serving as an element to attract the user's attention. Activity suggestions are also provided based on emotions, expanding the user's daily choices. Thus, this emotion-driven diary system provides a means of recording individual experiences in a more concrete and emotional way.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] The device retrieves visual data stored on the user's device. It references the image library and extracts images and videos taken within a specified period. It also retrieves metadata such as the date and time of capture and location information.

[0135] Step 2:

[0136] The device retrieves event information from the user's calendar app. It collects event information registered within a specified period and prepares detailed activity data based on the event name, date and time, location, and participant information.

[0137] Step 3:

[0138] The device uses GPS data to track the user's movement history, recording the routes traveled and the places visited. This provides data that offers context to the actual activity.

[0139] Step 4:

[0140] The device sends the acquired visual data, schedule information, and GPS data to the server as a single data package. The packaged data is encrypted before transmission to ensure security.

[0141] Step 5:

[0142] The server receives a data package and applies an emotion engine to the visual data within it. It performs image analysis to infer the user's emotions from facial expressions and context in the image, and then adds emotion tags.

[0143] Step 6:

[0144] The server analyzes schedule information and GPS data, referencing emotions and activity locations to generate chronological diary entries. It incorporates entries that reflect the user's emotional state, creating a unique diary format.

[0145] Step 7:

[0146] The server references purchase history data to identify products related to emotions and activities and suggests repurchases. This includes product recommendations tailored to the analyzed emotional state.

[0147] Step 8:

[0148] The generated diary and suggested content are sent to the user's device. The user can review the received diary and view special notes that are highlighted according to their emotions.

[0149] Step 9:

[0150] It provides interactive options that allow users to edit their diaries and share them with others, enabling them to customize the content of their diaries to their individual preferences.

[0151] (Example 2)

[0152] 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 will be referred to as the "terminal."

[0153] There is a lack of systems that concretely record users' daily experiences from an emotional perspective and generate diaries based on that data. Consequently, there is a challenge in that records and activity suggestions tailored to individual emotions are rarely provided efficiently and automatically.

[0154] 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.

[0155] In this invention, the server includes means for analyzing emotions based on received image data, means for generating text using the analyzed emotion information, and means for generating user activity suggestions. This makes it possible to generate a personalized diary that reflects the user's daily emotions.

[0156] "Communication device" refers to a mobile device that has the function of collecting data from the user's daily life.

[0157] "Image data" refers to visual information collected by communication devices as part of a user's activity.

[0158] "Scheduled information" refers to information about the user's planned activities and events.

[0159] An "information processing device" refers to a device that performs analysis and generates text based on received data.

[0160] "Methods for analyzing emotions" refer to technologies and algorithms used to identify a user's emotional state from image data.

[0161] "Analyzed emotional information" refers to information about the user's emotional state obtained through data analysis.

[0162] "Methods for generating text" refers to the process of automatically creating text in natural language based on analysis results.

[0163] "Means of highlighting special notes" refers to techniques that visually make important emotional information stand out in generated text.

[0164] "Means for generating activity suggestions" refers to a process for presenting appropriate activities and options based on the user's emotional state.

[0165] "A method of suggesting repurchases by referencing transaction history" refers to a system that encourages users to make new purchases by referring to past purchase information.

[0166] "Means for identifying individuals or places and supplementing special notes" refers to the process of identifying specific people or places from image data and adding relevant information based on that identification.

[0167] This invention is a system for utilizing a user's daily emotional data as an activity record, and consists of a communication device and an information processing device. Examples of the communication device include smartphones and tablet devices. The communication device has the function of acquiring image data and schedule information collected by the user in their daily life. Once this data is collected, the device securely transmits it to the information processing device.

[0168] The information processing device, after receiving the data,

[0169] We perform sentiment analysis. Specifically, we use transmitted image data and a sentiment analysis model to identify the user's emotional state. Image recognition algorithms (e.g., OpenCV and TENSORFLOW®) are applied as technologies for this analysis. Based on the analyzed sentiment information, a generative AI model is used to generate diary entries in natural language. This model uses technologies such as GPT and, by inputting prompts tailored to the user's emotions, expresses the user's experience in detail and with rich emotion.

[0170] For example, suppose a user visits a park on a holiday and takes many photos of themselves having fun with friends. The device collects these photos and sends them to an information processing device. The server performs sentiment analysis and determines that many of the photos show "smiles." Based on this, a generative AI model is used to generate a diary entry with content such as, "I spent my holiday at the park with friends and had a great time." This diary is sent to the device and can be viewed and edited by the user.

[0171] An example of a prompt message would be, "Based on the sentiment analysis results and activity details of the photos taken by the user, generate the most appropriate expression for a diary entry."

[0172] Furthermore, the generated text is designed to include activity suggestions that take the user's emotions into consideration. This expands the user's options in daily life and makes it easier for them to take emotionally-driven actions.

[0173] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0174] Step 1:

[0175] The device acquires image data and schedule information from the user's daily life. The acquired image data includes photos and videos taken by the user. It collects information from the user's camera roll and scheduling app as input and generates formatted data as output. This data is the dataset that forms the basis for sentiment analysis and diary generation. Specifically, apps on the device collect information from sensors and the camera and temporarily store it in local storage.

[0176] Step 2:

[0177] The terminal transmits the acquired image data and schedule information to the information processing device. The data formatted in Step 1 is used as input, and the data is securely delivered to the information processing device as output. Specifically, the data is encrypted end-to-end using a network communication protocol (e.g., HTTPS) before transmission.

[0178] Step 3:

[0179] The server performs emotion analysis based on received image data. The input is image data received from the terminal, and the output is emotion information. Specifically, the data processing involves using an image recognition algorithm to detect facial expressions such as smiles and surprise and identify emotions. In terms of operation, it uses an image analysis library (e.g., OpenCV, TensorFlow) to analyze faces and facial expressions and generate data that quantifies emotions.

[0180] Step 4:

[0181] The server generates text based on the results of sentiment analysis. It uses sentiment information obtained in step 3 as input and generates natural language text as output. For specific data calculations, a generative AI model (e.g., GPT) is used, providing the most appropriate prompt sentences as input to generate text. The specific operation involves parameterizing the sentiment information and inputting it into the generative AI model to obtain a diary with richly expressive emotions.

[0182] Step 5:

[0183] The server sends the generated text to the terminal. It uses the text created in step 4 as input and delivers the text in a format that can be displayed on the terminal as output. Specifically, it formats the diary entries as text messages and sends them to the terminal via the network.

[0184] Step 6:

[0185] The terminal displays received text to the user. The input is diary entries sent from the server, and the output is displayed on the screen in a format viewable by the user. Specifically, a dedicated application retrieves the diary text and displays it visually through the user interface. At this time, important points are highlighted, and related activity suggestions are also provided.

[0186] (Application Example 2)

[0187] 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 device 14 will be referred to as the "terminal."

[0188] The challenge is to provide a system that enhances the user experience by recording users' daily lives in a more emotionally rich way and automating action and purchase suggestions based on individual emotions.

[0189] 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.

[0190] In this invention, the server includes means for acquiring image information and schedule information stored in a mobile communication device, means for generating text based on emotion data extracted from the image information, and means for recommending actions based on the emotion data. This makes it possible to specifically record the user's daily life based on emotions and to suggest actions that meet individual needs.

[0191] A "mobile communication device" is an electronic device that a user carries with them to collect and transmit information. This device has the function of acquiring data such as images and schedules, and transmitting it to a data processing device as needed.

[0192] "Image information" refers to photographic and video data acquired by mobile communication devices, which visually records the user's activities and surrounding environment.

[0193] "Schedule information" refers to data on schedules and event information managed by the user, including plans for the user's daily activities.

[0194] A "data processing device" is a computer system that has the function of analyzing data received from a mobile communication device and processing and transforming the information.

[0195] "Emotional data" refers to data that indicates a user's emotional state, analyzed from image information and audio, and expresses emotions such as joy and surprise using numerical values ​​and categories.

[0196] "Means for generating text" refers to a process that automatically creates documents based on acquired data, and in particular, has the function of generating content that reflects emotional data.

[0197] "Behavioral recommendations" refer to suggesting the next course of action or options to the user based on analyzed data. These recommendations are customized based on the user's emotions and behavioral history.

[0198] This system aims to recognize the user's emotions and generate a diary based on those emotions. To implement this, the following programs and hardware are required:

[0199] The server receives image information and schedule information acquired from mobile communication devices (terminals). Smartphones and tablets equipped with high-resolution cameras are used for this purpose. These terminals have the function of sending photos taken by the user on a daily basis and their own schedule data to the server in real time.

[0200] The received information is processed on the server for emotion recognition. The software used here includes OpenCV, an image analysis library, and TensorFlow, a machine learning framework for building emotion inference models. This allows the server to analyze the image information and extract emotion data such as the user's smile or surprise.

[0201] After sentiment data is extracted, a generative AI model (e.g., the GPT model) for natural language processing is used to create sentiment-based diary entries. The generated entries are then sent back to the device and presented to the user visually. The user can review these entries and edit them as needed.

[0202] As a concrete example, suppose a user visits a tourist spot on a holiday and takes several photos of themselves smiling. In this case, the server recognizes the emotion of "enjoyment" from these photos and automatically generates a diary entry such as, "I thoroughly enjoyed my holiday and felt a lot of fun."

[0203] An example of a prompt for a generative AI model would be: "Generate a diary from the following data. Photo emotion: Mostly smiles. Activity: Travel, Situation: Sightseeing." This prompt allows the AI ​​to generate text that reflects the user's intentions and emotions.

[0204] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0205] Step 1:

[0206] The device uses a high-resolution camera to collect image and schedule information to record the user's daily life. This information includes photos taken by the user and event information based on their schedule. The device packages this data into packets and sends them to the server using a secure communication method.

[0207] Step 2:

[0208] The server analyzes image and schedule information received from the terminal. Here, the OpenCV image analysis library is used to detect the content of the photograph, paying particular attention to the user's facial expressions. The input is photographic data from the terminal, and the output is data indicating emotions such as smiles and surprise. This generates emotion data extracted from the photograph.

[0209] Step 3:

[0210] The server utilizes an emotion inference model to determine the user's overall emotional state based on extracted emotion data. This process uses TensorFlow to analyze the emotion data and estimate the user's emotions on that particular day. The output is a numerical and categorized representation of the user's emotions.

[0211] Step 4:

[0212] The server uses a generative AI model (e.g., a GPT model) to generate diary entries based on the obtained sentiment data. The input consists of quantified sentiment data and categorized activity descriptions, while the output is a diary entry in natural-sounding text format. This entry incorporates information about emotions and activities.

[0213] Step 5:

[0214] The server sends the generated text to the terminal. This text is customized to include expressions that match the user's emotions and is displayed on the terminal in a format that the user can view. The user can update their diary based on the provided text and edit it as needed.

[0215] 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.

[0216] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0217] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0218] [Second Embodiment]

[0219] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0220] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0221] 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).

[0222] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0223] 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.

[0224] 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).

[0225] 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.

[0226] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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".

[0231] This invention utilizes a mobile communication device (terminal) and a data processing device (server) to achieve automatic diary generation. The operation of this system is described in detail below.

[0232] The device is used to record the user's daily activities. It retrieves visual data and schedule information from the image library and calendar app. This data becomes the material for a diary automatically generated based on the user's activity records over a certain period.

[0233] The collected data is transmitted to the server via the network using a secure protocol. The server executes advanced data analysis algorithms, performing object recognition from images, text analysis, and integrating schedule and location information. This analysis provides a comprehensive understanding of the day's activities, and natural language processing is used to generate diary-style entries.

[0234] For example, if a user takes an image on a particular day that includes a restaurant, the server analyzes the image to identify details such as, "On this day, I enjoyed a meal with a friend at a specific restaurant." Furthermore, it cross-references this with the user's schedule information to supplement the time and location details.

[0235] Furthermore, the server manages users' purchase history and can recommend repurchases of items relevant to their journal entries. This significantly improves the convenience of users' daily lives.

[0236] The generated diary is sent back to the device and displayed to the user through the device's application. The user can view the diary's contents, edit it as needed, and share it with others. This entire process allows for detailed recording of daily events without the need for manual input.

[0237] The following describes the processing flow.

[0238] Step 1:

[0239] The device retrieves visual data stored on the user's device and extracts image files from the photo library for a specified period. It also collects associated metadata (such as the date and time of capture and location information).

[0240] Step 2:

[0241] The device accesses the user's calendar application to retrieve event information for a specified period. It collects event titles, dates and times, and participant information to use as data to understand the context of the activities.

[0242] Step 3:

[0243] The device uses GPS data to obtain the user's daily movement history. This allows for accurate recording of the places and times the user has visited.

[0244] Step 4:

[0245] The device encrypts the collected visual data, schedule information, and GPS data, and sends it to the server as a data package. A secure communication protocol is used to prevent information leakage.

[0246] Step 5:

[0247] The server decodes the received data and performs image analysis from the visual data. It extracts information about people, places, and objects from the image to grasp the general outline of the activity. It performs sentiment analysis to evaluate the atmosphere of the image.

[0248] Step 6:

[0249] The server cross-references scheduled information with GPS data and organizes user activity chronologically. It verifies the consistency between scheduled events and actual activities and analyzes the reasons for any discrepancies.

[0250] Step 7:

[0251] The server generates text based on the analysis results, creating a diary-style document. It expresses the user's daily activities in natural language, supplementing any special notes.

[0252] Step 8:

[0253] The server analyzes the user's purchase history and suggests repurchasing items related to their activities in their journal. It also provides the user with information about items they have previously purchased.

[0254] Step 9:

[0255] The server sends the generated diary and repurchase suggestions to the device, and the device displays this content in the application. The user reviews the diary content and edits or shares it with others as needed.

[0256] (Example 1)

[0257] 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."

[0258] Manually recording daily events and activities is a time-consuming and laborious task for users. Furthermore, the resulting records are often incomplete and lack usefulness when viewed later. Additionally, there is a lack of systems for integrating and effectively utilizing related information such as purchase history and schedules.

[0259] 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.

[0260] In this invention, the server includes means for generating text in natural language based on visual information and scheduled information, means for generating text using a generative AI model, and means for identifying objects or locations in the analysis of visual information and reinforcing special notes. This enables the user to automatically record daily events in detail and manage those records efficiently.

[0261] A "mobile communication device" is a device equipped with communication functions that can be used while on the move, such as a mobile phone, smartphone, or tablet.

[0262] "Visual information" refers to visual data such as photographs, images, and videos, and is information acquired to record the user's daily activities.

[0263] "Schedule information" refers to information about a user's planned activities and appointments, based on calendar applications or schedules.

[0264] An "information processing device" is a device that receives data, analyzes and processes it, and converts it into useful information, and includes computer systems such as servers.

[0265] "Natural language" refers to the language that humans use on a daily basis, and also refers to human-readable text formats generated by computer programs.

[0266] A "generative AI model" is a computational model that uses artificial intelligence to generate text and data, and is particularly characterized by its advanced natural language processing capabilities.

[0267] "Target identification" refers to the process of identifying objects and locations contained in visual information using image analysis techniques and extracting their characteristics.

[0268] "Reinforcing special notes" means highlighting important information and facts based on the information obtained through analysis, thereby improving the accuracy and usefulness of the record.

[0269] This invention is a system for efficiently recording and managing a user's daily activities by linking a mobile communication device and an information processing device. The embodiments for carrying out the invention are described in detail below.

[0270] A device is a mobile communication device such as a smartphone or tablet, and it plays a role in recording the user's daily activities. The device retrieves visual information such as photos and videos from its image library and collects schedule information from its calendar app. It can also obtain location information using GPS functionality.

[0271] The collected visual and schedule information is sent to the server via the network using security protocols such as HTTPS. The server, acting as an information processing device, processes the received data and performs advanced analysis. Libraries such as OpenCV are used for image analysis, and NLP tools such as spaCy and BERT are used for natural language processing. Furthermore, the server utilizes generative AI models to generate text in natural language based on the received visual and schedule information.

[0272] This system uses a generative AI model to automatically create diary-style entries, such as "On this day, I enjoyed a meal with a friend at a specific restaurant," based on visual and scheduled information. An example of a prompt used in this process is, "Based on the user's activity results, please summarize the day's events in detail in a diary," which is input to the generative AI model.

[0273] The server can also manage the user's purchase history and suggest repurchases of related products. The generated diary entries are sent back to the terminal and displayed to the user through a dedicated application. Users can view, edit, and share the provided diary entries with others.

[0274] This invention allows users to obtain a diary that accurately summarizes visual and scheduled information without requiring much effort, thereby improving the convenience of daily life.

[0275] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0276] Step 1:

[0277] Users record their daily activities using the device. Specifically, the device acquires visual information using its camera and sensors. It also retrieves schedule information from its calendar app and records location information using its GPS function. As a result, image data, schedules, and location information are input into the device. This input data becomes the basic information necessary for subsequent processing.

[0278] Step 2:

[0279] The terminal encrypts the collected visual information and schedule information using the HTTPS protocol and sends it to the server via the network. As a specific operation, the terminal periodically aggregates the accumulated data to form a transmission batch. The output of this step is an encrypted data packet, which is input to the server.

[0280] Step 3:

[0281] The server decrypts the encrypted data received from the terminal and starts data analysis. Here, the server performs image analysis on the visual information using the OpenCV library to recognize objects and scenes. It analyzes the character information using NLP tools (spaCy and BERT) to understand the content of the schedule and diary. The output of this step is the analyzed text data and image tag information.

[0282] Step 4:

[0283] The server uses a generative AI model to generate a diary in natural language from the analysis results. Specifically, it gives the model the prompt sentence "Please summarize the events of the day in detail in the diary based on the user's activity results." as input and outputs a detailed natural language text. The output here is text summarizing the user's daily activities.

[0284] Step 5:

[0285] The server sends the generated diary text to the terminal. The terminal displays the received text to the user using a dedicated application. As a specific operation, when the terminal receives new diary data, it notifies the user and provides an interface for viewing the content. The output of this step is a diary screen that the user can view.

[0286] Step 6:

[0287] Users can view the diary generated via their device and edit or share it with others as needed. Specifically, users can view the displayed diary and use editing tools to modify its content, or use the share button to send it to friends. The output is the final or shared diary content.

[0288] (Application Example 1)

[0289] 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."

[0290] In today's busy lives, it's difficult to meticulously record daily events and reflect on memories. Furthermore, to efficiently preserve personal life records, a system is needed that integrates various types of information and automates the process. In such systems, the challenge lies in improving the comprehensiveness, accuracy, and convenience of the recorded information.

[0291] 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.

[0292] In this invention, the server includes means for acquiring information stored in a mobile communication device, means for transmitting the information to a data processing device, means for generating text based on the received information, and means for collecting additional activity information using an environmental recording device. This makes it possible to record an individual's daily life with high accuracy and comprehensively, and to automatically generate detailed records as needed.

[0293] A "mobile communication device" is a terminal device with communication capabilities that can be carried and used by a user.

[0294] "Information" refers to all data related to the user's daily activities, including visual data, schedule information, and environmental data.

[0295] A "data processing device" is a computer system used to analyze received data and perform processing such as converting it into text.

[0296] An "environmental recording device" is a device equipped with instruments and sensors to record surrounding conditions and user behavior, and to acquire additional information.

[0297] "Inference" is the process of deriving a logical conclusion based on collected data.

[0298] "Purchase history" refers to a series of data related to purchases a user has made in the past, and is information used to analyze behavioral patterns based on that data.

[0299] "Identification target" refers to a specific person or object being analyzed, or their attributes.

[0300] "Space" refers to the physical area that constitutes the place or environment in which a user engages in activities.

[0301] "Important matters" refer to events or occurrences in daily life that are particularly worthy of being recorded or recognized.

[0302] To realize this invention, a system comprising a mobile communication device carried by the user, an environmental recording device, and a data processing server on the cloud is required. Specific embodiments are described in detail below.

[0303] First, the device collects the user's visual data and schedule information. Cameras and sensors built into the device record the user's actions and environmental conditions. This information is transmitted from the mobile communication device to a server in the cloud using a secure protocol.

[0304] After receiving the data, the server uses a service such as the "Google Cloud Vision API" to perform image recognition and identify specific objects or locations from the acquired images. In parallel, it uses a natural language processing model, such as the "OpenAI GPT model", to generate a diary-style text based on the user's schedule information and environmental information.

[0305] By integrating the collected data and recognition results, a detailed activity record is generated, and the server creates a diary in a customized format according to the user's preferences. For example, if the user is enjoying a walk in the park, it formulates an expression like "Spent a leisurely walking time in the park on a warm spring day".

[0306] The generated diary is sent back to the mobile communication device and notified to the user on the terminal. The user can check the content and, if necessary, make additional edits or share it with others.

[0307] As a specific example, by inputting a prompt text such as "Please generate a text based on the events that occurred this morning. Query content: weather, events in the park, time with family." into the generation AI model, a detailed diary entry can be obtained.

[0308] This series of processes provides an excellent system that enables users to automatically review and record their activities even in busy daily life.

[0309] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0310] Step 1:

[0311] The terminal uses a camera and sensors to collect image data and audio data related to the user's daily activities. The input at this point is visual and audio information obtained from the user's environment, and the output is that this information is stored as data in the terminal.

[0312] Step 2:

[0313] The device transmits the collected information to the server via a secure protocol. The input is image and audio data from the device, and the output is the receipt of this data in an encrypted form to the server.

[0314] Step 3:

[0315] The server analyzes the received data and performs image analysis. Using image recognition technologies such as the Google Cloud Vision API, it identifies objects and locations from the data. The input is the received image data, and the output is the analyzed information about objects and locations.

[0316] Step 4:

[0317] The server further uses natural language processing (NLP) techniques to synthesize the received schedule information and the entire dataset into text. It is possible to utilize OpenAI's GPT model. The input consists of analyzed object / location information and schedule information, while the output is a diary-style text written in natural language.

[0318] Step 5:

[0319] The server sends the generated diary entries back to the terminal. The input is the generated text, and the output is the format in which it is displayed on the terminal.

[0320] Step 6:

[0321] Users can view their diary entries on their devices and manually edit or share them with others as needed. The input is the generated diary content, and the output is the edited or shared information.

[0322] 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.

[0323] The present invention relates to an embodiment of a system that integrates an emotion engine that recognizes a user's emotions and utilizes them as part of diary generation. This system is mainly composed of a mobile communication device (hereinafter referred to as a terminal) and a data processing device (hereinafter referred to as a server).

[0324] The device collects visual data and schedule information related to the user's daily activities. This data includes photos taken by the user and information about events they have attended, and serves as material for emotion recognition. In particular, visual data is a crucial element of emotion analysis, and the device infers the user's emotions from facial expressions and situations in images.

[0325] The collected data is transmitted to the server via a secure communication method. The server uses an emotion engine to recognize the user's emotions from the visual data. This emotion engine combines multiple algorithms; for example, it recognizes smiles and surprised expressions through image analysis and identifies emotions such as "I had a very enjoyable time today."

[0326] Next, the server generates diary entries that incorporate emotions. For example, if a user visited a tourist spot on a holiday and took many photos of themselves smiling, the entries might include phrases like, "I enjoyed my holiday and had a lot of fun." This process also includes analyzing purchase history, making it possible to suggest products that are relevant to the user's emotions.

[0327] The generated diary entries are sent to the device, where the user can view and edit them. In particular, emotionally charged entries are highlighted, serving as an element to attract the user's attention. Activity suggestions are also provided based on emotions, expanding the user's daily choices. Thus, this emotion-driven diary system provides a means of recording individual experiences in a more concrete and emotional way.

[0328] The following describes the processing flow.

[0329] Step 1:

[0330] The device retrieves visual data stored on the user's device. It references the image library and extracts images and videos taken within a specified period. It also retrieves metadata such as the date and time of capture and location information.

[0331] Step 2:

[0332] The device retrieves event information from the user's calendar app. It collects event information registered within a specified period and prepares detailed activity data based on the event name, date and time, location, and participant information.

[0333] Step 3:

[0334] The device uses GPS data to track the user's movement history, recording the routes traveled and the places visited. This provides data that offers context to the actual activity.

[0335] Step 4:

[0336] The device sends the acquired visual data, schedule information, and GPS data to the server as a single data package. The packaged data is encrypted before transmission to ensure security.

[0337] Step 5:

[0338] The server receives a data package and applies an emotion engine to the visual data within it. It performs image analysis to infer the user's emotions from facial expressions and context in the image, and then adds emotion tags.

[0339] Step 6:

[0340] The server analyzes schedule information and GPS data, referencing emotions and activity locations to generate chronological diary entries. It incorporates entries that reflect the user's emotional state, creating a unique diary format.

[0341] Step 7:

[0342] The server references purchase history data to identify products related to emotions and activities and suggests repurchases. This includes product recommendations tailored to the analyzed emotional state.

[0343] Step 8:

[0344] The generated diary and suggested content are sent to the user's device. The user can review the received diary and view special notes that are highlighted according to their emotions.

[0345] Step 9:

[0346] It provides interactive options that allow users to edit their diaries and share them with others, enabling them to customize the content of their diaries to their individual preferences.

[0347] (Example 2)

[0348] 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".

[0349] There is a lack of systems that concretely record users' daily experiences from an emotional perspective and generate diaries based on that data. Consequently, there is a challenge in that records and activity suggestions tailored to individual emotions are rarely provided efficiently and automatically.

[0350] 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.

[0351] In this invention, the server includes means for analyzing emotions based on received image data, means for generating text using the analyzed emotion information, and means for generating user activity suggestions. This makes it possible to generate a personalized diary that reflects the user's daily emotions.

[0352] "Communication device" refers to a mobile device that has the function of collecting data from the user's daily life.

[0353] "Image data" refers to visual information collected by communication devices as part of a user's activity.

[0354] "Scheduled information" refers to information about the user's planned activities and events.

[0355] An "information processing device" refers to a device that performs analysis and generates text based on received data.

[0356] "Methods for analyzing emotions" refer to technologies and algorithms used to identify a user's emotional state from image data.

[0357] "Analyzed emotional information" refers to information about the user's emotional state obtained through data analysis.

[0358] "Methods for generating text" refers to the process of automatically creating text in natural language based on analysis results.

[0359] "Means of highlighting special notes" refers to techniques that visually make important emotional information stand out in generated text.

[0360] "Means for generating activity suggestions" refers to a process for presenting appropriate activities and options based on the user's emotional state.

[0361] "A method of suggesting repurchases by referencing transaction history" refers to a system that encourages users to make new purchases by referring to past purchase information.

[0362] "Means for identifying individuals or places and supplementing special notes" refers to the process of identifying specific people or places from image data and adding relevant information based on that identification.

[0363] This invention is a system for utilizing a user's daily emotional data as an activity record, and consists of a communication device and an information processing device. Examples of the communication device include smartphones and tablet devices. The communication device has the function of acquiring image data and schedule information collected by the user in their daily life. Once this data is collected, the device securely transmits it to the information processing device.

[0364] The information processing device, after receiving the data,

[0365] We will perform sentiment analysis. Specifically, we will use the transmitted image data and utilize a sentiment analysis model to identify the user's emotional state. Image recognition algorithms (e.g., OpenCV or TensorFlow) will be applied as the technology used for this analysis. Based on the analyzed sentiment information, a generative AI model will be used to generate diary entries in natural language. This model will use technologies such as GPT and, by inputting prompts tailored to the user's emotions, will express the user's experience in detail and with rich emotion.

[0366] For example, suppose a user visits a park on a holiday and takes many photos of themselves having fun with friends. The device collects these photos and sends them to an information processing device. The server performs sentiment analysis and determines that many of the photos show "smiles." Based on this, a generative AI model is used to generate a diary entry with content such as, "I spent my holiday at the park with friends and had a great time." This diary is sent to the device and can be viewed and edited by the user.

[0367] An example of a prompt message would be, "Based on the sentiment analysis results and activity details of the photos taken by the user, generate the most appropriate expression for a diary entry."

[0368] Furthermore, the generated text is designed to include activity suggestions that take the user's emotions into consideration. This expands the user's options in daily life and makes it easier for them to take emotionally-driven actions.

[0369] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0370] Step 1:

[0371] The device acquires image data and schedule information from the user's daily life. The acquired image data includes photos and videos taken by the user. It collects information from the user's camera roll and scheduling app as input and generates formatted data as output. This data is the dataset that forms the basis for sentiment analysis and diary generation. Specifically, apps on the device collect information from sensors and the camera and temporarily store it in local storage.

[0372] Step 2:

[0373] The terminal transmits the acquired image data and schedule information to the information processing device. The data formatted in Step 1 is used as input, and the data is securely delivered to the information processing device as output. Specifically, the data is encrypted end-to-end using a network communication protocol (e.g., HTTPS) before transmission.

[0374] Step 3:

[0375] The server performs emotion analysis based on received image data. The input is image data received from the terminal, and the output is emotion information. Specifically, the data processing involves using an image recognition algorithm to detect facial expressions such as smiles and surprise and identify emotions. In terms of operation, it uses an image analysis library (e.g., OpenCV, TensorFlow) to analyze faces and facial expressions and generate data that quantifies emotions.

[0376] Step 4:

[0377] The server generates text based on the results of sentiment analysis. It uses sentiment information obtained in step 3 as input and generates natural language text as output. For specific data calculations, a generative AI model (e.g., GPT) is used, providing the most appropriate prompt sentences as input to generate text. The specific operation involves parameterizing the sentiment information and inputting it into the generative AI model to obtain a diary with richly expressive emotions.

[0378] Step 5:

[0379] The server sends the generated text to the terminal. It uses the text created in step 4 as input and delivers the text in a format that can be displayed on the terminal as output. Specifically, it formats the diary entries as text messages and sends them to the terminal via the network.

[0380] Step 6:

[0381] The terminal displays received text to the user. The input is diary entries sent from the server, and the output is displayed on the screen in a format viewable by the user. Specifically, a dedicated application retrieves the diary text and displays it visually through the user interface. At this time, important points are highlighted, and related activity suggestions are also provided.

[0382] (Application Example 2)

[0383] 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."

[0384] The challenge is to provide a system that enhances the user experience by recording users' daily lives in a more emotionally rich way and automating action and purchase suggestions based on individual emotions.

[0385] 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.

[0386] In this invention, the server includes means for acquiring image information and schedule information stored in a mobile communication device, means for generating text based on emotion data extracted from the image information, and means for recommending actions based on the emotion data. This makes it possible to specifically record the user's daily life based on emotions and to suggest actions that meet individual needs.

[0387] A "mobile communication device" is an electronic device that a user carries with them to collect and transmit information. This device has the function of acquiring data such as images and schedules, and transmitting it to a data processing device as needed.

[0388] "Image information" refers to photographic and video data acquired by mobile communication devices, which visually records the user's activities and surrounding environment.

[0389] "Schedule information" refers to data on schedules and event information managed by the user, including plans for the user's daily activities.

[0390] A "data processing device" is a computer system that has the function of analyzing data received from a mobile communication device and processing and transforming the information.

[0391] "Emotional data" refers to data that indicates a user's emotional state, analyzed from image information and audio, and expresses emotions such as joy and surprise using numerical values ​​and categories.

[0392] "Means for generating text" refers to a process that automatically creates documents based on acquired data, and in particular, has the function of generating content that reflects emotional data.

[0393] "Behavioral recommendations" refer to suggesting the next course of action or options to the user based on analyzed data. These recommendations are customized based on the user's emotions and behavioral history.

[0394] This system aims to recognize the user's emotions and generate a diary based on those emotions. To implement this, the following programs and hardware are required:

[0395] The server receives image information and schedule information acquired from mobile communication devices (terminals). Smartphones and tablets equipped with high-resolution cameras are used for this purpose. These terminals have the function of sending photos taken by the user on a daily basis and their own schedule data to the server in real time.

[0396] The received information is processed on the server for emotion recognition. The software used here includes OpenCV, an image analysis library, and TensorFlow, a machine learning framework for building emotion inference models. This allows the server to analyze the image information and extract emotion data such as the user's smile or surprise.

[0397] After sentiment data is extracted, a generative AI model (e.g., the GPT model) for natural language processing is used to create sentiment-based diary entries. The generated entries are then sent back to the device and presented to the user visually. The user can review these entries and edit them as needed.

[0398] As a concrete example, suppose a user visits a tourist spot on a holiday and takes several photos of themselves smiling. In this case, the server recognizes the emotion of "enjoyment" from these photos and automatically generates a diary entry such as, "I thoroughly enjoyed my holiday and felt a lot of fun."

[0399] An example of a prompt for a generative AI model would be: "Generate a diary from the following data. Photo emotion: Mostly smiles. Activity: Travel, Situation: Sightseeing." This prompt allows the AI ​​to generate text that reflects the user's intentions and emotions.

[0400] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0401] Step 1:

[0402] The device uses a high-resolution camera to collect image and schedule information to record the user's daily life. This information includes photos taken by the user and event information based on their schedule. The device packages this data into packets and sends them to the server using a secure communication method.

[0403] Step 2:

[0404] The server analyzes image and schedule information received from the terminal. Here, the OpenCV image analysis library is used to detect the content of the photograph, paying particular attention to the user's facial expressions. The input is photographic data from the terminal, and the output is data indicating emotions such as smiles and surprise. This generates emotion data extracted from the photograph.

[0405] Step 3:

[0406] The server utilizes an emotion inference model to determine the user's overall emotional state based on extracted emotion data. This process uses TensorFlow to analyze the emotion data and estimate the user's emotions on that particular day. The output is a numerical and categorized representation of the user's emotions.

[0407] Step 4:

[0408] The server uses a generative AI model (e.g., a GPT model) to generate diary entries based on the obtained sentiment data. The input consists of quantified sentiment data and categorized activity descriptions, while the output is a diary entry in natural-sounding text format. This entry incorporates information about emotions and activities.

[0409] Step 5:

[0410] The server sends the generated text to the terminal. This text is customized to include expressions that match the user's emotions and is displayed on the terminal in a format that the user can view. The user can update their diary based on the provided text and edit it as needed.

[0411] 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.

[0412] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0413] 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.

[0414] [Third Embodiment]

[0415] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0416] 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.

[0417] 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).

[0418] 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.

[0419] 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.

[0420] 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).

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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".

[0427] This invention utilizes a mobile communication device (terminal) and a data processing device (server) to achieve automatic diary generation. The operation of this system is described in detail below.

[0428] The device is used to record the user's daily activities. It retrieves visual data and schedule information from the image library and calendar app. This data becomes the material for a diary automatically generated based on the user's activity records over a certain period.

[0429] The collected data is transmitted to the server via the network using a secure protocol. The server executes advanced data analysis algorithms, performing object recognition from images, text analysis, and integrating schedule and location information. This analysis provides a comprehensive understanding of the day's activities, and natural language processing is used to generate diary-style entries.

[0430] For example, if a user takes an image on a particular day that includes a restaurant, the server analyzes the image to identify details such as, "On this day, I enjoyed a meal with a friend at a specific restaurant." Furthermore, it cross-references this with the user's schedule information to supplement the time and location details.

[0431] Furthermore, the server manages users' purchase history and can recommend repurchases of items relevant to their journal entries. This significantly improves the convenience of users' daily lives.

[0432] The generated diary is sent back to the device and displayed to the user through the device's application. The user can view the diary's contents, edit it as needed, and share it with others. This entire process allows for detailed recording of daily events without the need for manual input.

[0433] The following describes the processing flow.

[0434] Step 1:

[0435] The device retrieves visual data stored on the user's device and extracts image files from the photo library for a specified period. It also collects associated metadata (such as the date and time of capture and location information).

[0436] Step 2:

[0437] The device accesses the user's calendar application to retrieve event information for a specified period. It collects event titles, dates and times, and participant information to use as data to understand the context of the activities.

[0438] Step 3:

[0439] The device uses GPS data to obtain the user's daily movement history. This allows for accurate recording of the places and times the user has visited.

[0440] Step 4:

[0441] The device encrypts the collected visual data, schedule information, and GPS data, and sends it to the server as a data package. A secure communication protocol is used to prevent information leakage.

[0442] Step 5:

[0443] The server decodes the received data and performs image analysis from the visual data. It extracts information about people, places, and objects from the image to grasp the general outline of the activity. It performs sentiment analysis to evaluate the atmosphere of the image.

[0444] Step 6:

[0445] The server cross-references scheduled information with GPS data and organizes user activity chronologically. It verifies the consistency between scheduled events and actual activities and analyzes the reasons for any discrepancies.

[0446] Step 7:

[0447] The server generates text based on the analysis results, creating a diary-style document. It expresses the user's daily activities in natural language, supplementing any special notes.

[0448] Step 8:

[0449] The server analyzes the user's purchase history and suggests repurchasing items related to their activities in their journal. It also provides the user with information about items they have previously purchased.

[0450] Step 9:

[0451] The server sends the generated diary and repurchase suggestions to the device, and the device displays this content in the application. The user reviews the diary content and edits or shares it with others as needed.

[0452] (Example 1)

[0453] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0454] Manually recording daily events and activities is a time-consuming and laborious task for users. Furthermore, the resulting records are often incomplete and lack usefulness when viewed later. Additionally, there is a lack of systems for integrating and effectively utilizing related information such as purchase history and schedules.

[0455] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0456] In this invention, the server includes means for generating text in natural language based on visual information and scheduled information, means for generating text using a generative AI model, and means for identifying objects or locations in the analysis of visual information and reinforcing special notes. This enables the user to automatically record daily events in detail and manage those records efficiently.

[0457] A "mobile communication device" is a device equipped with communication functions that can be used while on the move, such as a mobile phone, smartphone, or tablet.

[0458] "Visual information" refers to visual data such as photographs, images, and videos, and is information acquired to record the user's daily activities.

[0459] "Schedule information" refers to information about a user's planned activities and appointments, based on calendar applications or schedules.

[0460] An "information processing device" is a device that receives data, analyzes and processes it, and converts it into useful information, and includes computer systems such as servers.

[0461] "Natural language" refers to the language that humans use on a daily basis, and also refers to human-readable text formats generated by computer programs.

[0462] A "generative AI model" is a computational model that uses artificial intelligence to generate text and data, and is particularly characterized by its advanced natural language processing capabilities.

[0463] "Target identification" refers to the process of identifying objects and locations contained in visual information using image analysis techniques and extracting their characteristics.

[0464] "Reinforcing special notes" means highlighting important information and facts based on the information obtained through analysis, thereby improving the accuracy and usefulness of the record.

[0465] This invention is a system for efficiently recording and managing a user's daily activities by linking a mobile communication device and an information processing device. The embodiments for carrying out the invention are described in detail below.

[0466] A device is a mobile communication device such as a smartphone or tablet, and it plays a role in recording the user's daily activities. The device retrieves visual information such as photos and videos from its image library and collects schedule information from its calendar app. It can also obtain location information using GPS functionality.

[0467] The collected visual and schedule information is sent to the server via the network using security protocols such as HTTPS. The server, acting as an information processing device, processes the received data and performs advanced analysis. Libraries such as OpenCV are used for image analysis, and NLP tools such as spaCy and BERT are used for natural language processing. Furthermore, the server utilizes generative AI models to generate text in natural language based on the received visual and schedule information.

[0468] This system uses a generative AI model to automatically create diary-style entries, such as "On this day, I enjoyed a meal with a friend at a specific restaurant," based on visual and scheduled information. An example of a prompt used in this process is, "Based on the user's activity results, please summarize the day's events in detail in a diary," which is input to the generative AI model.

[0469] The server can also manage the user's purchase history and suggest repurchases of related products. The generated diary entries are sent back to the terminal and displayed to the user through a dedicated application. Users can view, edit, and share the provided diary entries with others.

[0470] This invention allows users to obtain a diary that accurately summarizes visual and scheduled information without requiring much effort, thereby improving the convenience of daily life.

[0471] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0472] Step 1:

[0473] Users record their daily activities using the device. Specifically, the device acquires visual information using its camera and sensors. It also retrieves schedule information from its calendar app and records location information using its GPS function. As a result, image data, schedules, and location information are input into the device. This input data becomes the basic information necessary for subsequent processing.

[0474] Step 2:

[0475] The terminal encrypts the collected visual and schedule information using the HTTPS protocol and sends it to the server over the network. Specifically, the terminal periodically aggregates the accumulated data and forms a transmission batch. The output of this step is an encrypted data packet, which is then input to the server.

[0476] Step 3:

[0477] The server decrypts the encrypted data received from the terminal and begins data analysis. Here, the server uses the OpenCV library to analyze visual information and recognize objects and scenes. It uses NLP tools (spaCy and BERT) to analyze text information and understand the contents of schedules and diaries. The output of this step is the analyzed text data and image tag information.

[0478] Step 4:

[0479] The server uses a generative AI model to generate a diary in natural language from the analysis results. Specifically, it takes the prompt "Based on the user's activity results, please summarize the day's events in detail in a diary" as input to the model, and outputs a detailed natural language text. The output here is a text that summarizes the user's activities for the day.

[0480] Step 5:

[0481] The server sends the generated diary entries to the terminal. The terminal displays the received entries to the user using a dedicated application. Specifically, when the terminal receives new diary data, it notifies the user and provides an interface for viewing the content. The output of this step is the diary screen that the user can view.

[0482] Step 6:

[0483] Users can view the diary generated via their device and edit or share it with others as needed. Specifically, users can view the displayed diary and use editing tools to modify its content, or use the share button to send it to friends. The output is the final or shared diary content.

[0484] (Application Example 1)

[0485] 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."

[0486] In today's busy lives, it's difficult to meticulously record daily events and reflect on memories. Furthermore, to efficiently preserve personal life records, a system is needed that integrates various types of information and automates the process. In such systems, the challenge lies in improving the comprehensiveness, accuracy, and convenience of the recorded information.

[0487] 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.

[0488] In this invention, the server includes means for acquiring information stored in a mobile communication device, means for transmitting the information to a data processing device, means for generating text based on the received information, and means for collecting additional activity information using an environmental recording device. This makes it possible to record an individual's daily life with high accuracy and comprehensively, and to automatically generate detailed records as needed.

[0489] A "mobile communication device" is a terminal device with communication capabilities that can be carried and used by a user.

[0490] "Information" refers to all data related to the user's daily activities, including visual data, schedule information, and environmental data.

[0491] A "data processing device" is a computer system used to analyze received data and perform processing such as converting it into text.

[0492] An "environmental recording device" is a device equipped with instruments and sensors to record surrounding conditions and user behavior, and to acquire additional information.

[0493] "Inference" is the process of deriving a logical conclusion based on collected data.

[0494] "Purchase history" refers to a series of data related to purchases a user has made in the past, and is information used to analyze behavioral patterns based on that data.

[0495] "Identification target" refers to a specific person or object being analyzed, or their attributes.

[0496] "Space" refers to the physical area that constitutes the place or environment in which a user engages in activities.

[0497] "Important matters" refer to events or occurrences in daily life that are particularly worthy of being recorded or recognized.

[0498] To realize this invention, a system comprising a mobile communication device carried by the user, an environmental recording device, and a data processing server on the cloud is required. Specific embodiments are described in detail below.

[0499] First, the device collects the user's visual data and schedule information. Cameras and sensors built into the device record the user's actions and environmental conditions. This information is transmitted from the mobile communication device to a server in the cloud using a secure protocol.

[0500] After receiving the data, the server uses a service like "Google Cloud Vision API" to perform image recognition, identifying specific objects and locations from the acquired images. In parallel, it uses a natural language processing model, such as "OpenAI's GPT model," to generate diary-style text based on the user's schedule and environment information.

[0501] By integrating the collected data and recognition results, a detailed activity log is generated, and the server creates a diary in a format customized to the user's preferences. For example, if the user enjoys a walk in the park, the server will write a sentence such as, "On a warm spring day, I spent time strolling leisurely in the park."

[0502] The generated diary is then sent back to the mobile communication device, and the user is notified on the terminal. The user can review the content and, if necessary, make edits or share it with others.

[0503] For example, you can input a prompt like, "Generate a text based on events that happened this morning. Inquiry details: weather, events at the park, time spent with family," into an AI model to obtain a detailed diary entry.

[0504] This entire process makes it an excellent system that allows users to automatically review and record their activities, even in the midst of a busy daily life.

[0505] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0506] Step 1:

[0507] The device uses cameras and sensors to collect image and audio data related to the user's daily activities. At this point, the input is visual and audio information obtained from the user's environment, and the output is this information being stored as data on the device.

[0508] Step 2:

[0509] The device transmits the collected information to the server via a secure protocol. The input is image and audio data from the device, and the output is the receipt of this data in an encrypted form to the server.

[0510] Step 3:

[0511] The server analyzes the received data and performs image analysis. Using image recognition technologies such as the Google Cloud Vision API, it identifies objects and locations from the data. The input is the received image data, and the output is the analyzed information about objects and locations.

[0512] Step 4:

[0513] The server further uses natural language processing (NLP) techniques to synthesize the received schedule information and the entire dataset into text. It is possible to utilize OpenAI's GPT model. The input consists of analyzed object / location information and schedule information, while the output is a diary-style text written in natural language.

[0514] Step 5:

[0515] The server sends the generated diary entries back to the terminal. The input is the generated text, and the output is the format in which it is displayed on the terminal.

[0516] Step 6:

[0517] Users can view their diary entries on their devices and manually edit or share them with others as needed. The input is the generated diary content, and the output is the edited or shared information.

[0518] 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.

[0519] The present invention relates to an embodiment of a system that integrates an emotion engine that recognizes a user's emotions and utilizes them as part of diary generation. This system is mainly composed of a mobile communication device (hereinafter referred to as a terminal) and a data processing device (hereinafter referred to as a server).

[0520] The device collects visual data and schedule information related to the user's daily activities. This data includes photos taken by the user and information about events they have attended, and serves as material for emotion recognition. In particular, visual data is a crucial element of emotion analysis, and the device infers the user's emotions from facial expressions and situations in images.

[0521] The collected data is transmitted to the server via a secure communication method. The server uses an emotion engine to recognize the user's emotions from the visual data. This emotion engine combines multiple algorithms; for example, it recognizes smiles and surprised expressions through image analysis and identifies emotions such as "I had a very enjoyable time today."

[0522] Next, the server generates diary entries that incorporate emotions. For example, if a user visited a tourist spot on a holiday and took many photos of themselves smiling, the entries might include phrases like, "I enjoyed my holiday and had a lot of fun." This process also includes analyzing purchase history, making it possible to suggest products that are relevant to the user's emotions.

[0523] The generated diary entries are sent to the device, where the user can view and edit them. In particular, emotionally charged entries are highlighted, serving as an element to attract the user's attention. Activity suggestions are also provided based on emotions, expanding the user's daily choices. Thus, this emotion-driven diary system provides a means of recording individual experiences in a more concrete and emotional way.

[0524] The following describes the processing flow.

[0525] Step 1:

[0526] The device retrieves visual data stored on the user's device. It references the image library and extracts images and videos taken within a specified period. It also retrieves metadata such as the date and time of capture and location information.

[0527] Step 2:

[0528] The device retrieves event information from the user's calendar app. It collects event information registered within a specified period and prepares detailed activity data based on the event name, date and time, location, and participant information.

[0529] Step 3:

[0530] The device uses GPS data to track the user's movement history, recording the routes traveled and the places visited. This provides data that offers context to the actual activity.

[0531] Step 4:

[0532] The device sends the acquired visual data, schedule information, and GPS data to the server as a single data package. The packaged data is encrypted before transmission to ensure security.

[0533] Step 5:

[0534] The server receives a data package and applies an emotion engine to the visual data within it. It performs image analysis to infer the user's emotions from facial expressions and context in the image, and then adds emotion tags.

[0535] Step 6:

[0536] The server analyzes schedule information and GPS data, referencing emotions and activity locations to generate chronological diary entries. It incorporates entries that reflect the user's emotional state, creating a unique diary format.

[0537] Step 7:

[0538] The server references purchase history data to identify products related to emotions and activities and suggests repurchases. This includes product recommendations tailored to the analyzed emotional state.

[0539] Step 8:

[0540] The generated diary and suggested content are sent to the user's device. The user can review the received diary and view special notes that are highlighted according to their emotions.

[0541] Step 9:

[0542] It provides interactive options that allow users to edit their diaries and share them with others, enabling them to customize the content of their diaries to their individual preferences.

[0543] (Example 2)

[0544] 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."

[0545] There is a lack of systems that concretely record users' daily experiences from an emotional perspective and generate diaries based on that data. Consequently, there is a challenge in that records and activity suggestions tailored to individual emotions are rarely provided efficiently and automatically.

[0546] 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.

[0547] In this invention, the server includes means for analyzing emotions based on received image data, means for generating text using the analyzed emotion information, and means for generating user activity suggestions. This makes it possible to generate a personalized diary that reflects the user's daily emotions.

[0548] "Communication device" refers to a mobile device that has the function of collecting data from the user's daily life.

[0549] "Image data" refers to visual information collected by communication devices as part of a user's activity.

[0550] "Scheduled information" refers to information about the user's planned activities and events.

[0551] An "information processing device" refers to a device that performs analysis and generates text based on received data.

[0552] "Methods for analyzing emotions" refer to technologies and algorithms used to identify a user's emotional state from image data.

[0553] "Analyzed emotional information" refers to information about the user's emotional state obtained through data analysis.

[0554] "Methods for generating text" refers to the process of automatically creating text in natural language based on analysis results.

[0555] "Means of highlighting special notes" refers to techniques that visually make important emotional information stand out in generated text.

[0556] "Means for generating activity suggestions" refers to a process for presenting appropriate activities and options based on the user's emotional state.

[0557] "A method of suggesting repurchases by referencing transaction history" refers to a system that encourages users to make new purchases by referring to past purchase information.

[0558] "Means for identifying individuals or places and supplementing special notes" refers to the process of identifying specific people or places from image data and adding relevant information based on that identification.

[0559] This invention is a system for utilizing a user's daily emotional data as an activity record, and consists of a communication device and an information processing device. Examples of the communication device include smartphones and tablet devices. The communication device has the function of acquiring image data and schedule information collected by the user in their daily life. Once this data is collected, the device securely transmits it to the information processing device.

[0560] The information processing device, after receiving the data,

[0561] We will perform sentiment analysis. Specifically, we will use the transmitted image data and utilize a sentiment analysis model to identify the user's emotional state. Image recognition algorithms (e.g., OpenCV or TensorFlow) will be applied as the technology used for this analysis. Based on the analyzed sentiment information, a generative AI model will be used to generate diary entries in natural language. This model will use technologies such as GPT and, by inputting prompts tailored to the user's emotions, will express the user's experience in detail and with rich emotion.

[0562] For example, suppose a user visits a park on a holiday and takes many photos of themselves having fun with friends. The device collects these photos and sends them to an information processing device. The server performs sentiment analysis and determines that many of the photos show "smiles." Based on this, a generative AI model is used to generate a diary entry with content such as, "I spent my holiday at the park with friends and had a great time." This diary is sent to the device and can be viewed and edited by the user.

[0563] An example of a prompt message would be, "Based on the sentiment analysis results and activity details of the photos taken by the user, generate the most appropriate expression for a diary entry."

[0564] Furthermore, the generated text is designed to include activity suggestions that take the user's emotions into consideration. This expands the user's options in daily life and makes it easier for them to take emotionally-driven actions.

[0565] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0566] Step 1:

[0567] The device acquires image data and schedule information from the user's daily life. The acquired image data includes photos and videos taken by the user. It collects information from the user's camera roll and scheduling app as input and generates formatted data as output. This data is the dataset that forms the basis for sentiment analysis and diary generation. Specifically, apps on the device collect information from sensors and the camera and temporarily store it in local storage.

[0568] Step 2:

[0569] The terminal transmits the acquired image data and schedule information to the information processing device. The data formatted in Step 1 is used as input, and the data is securely delivered to the information processing device as output. Specifically, the data is encrypted end-to-end using a network communication protocol (e.g., HTTPS) before transmission.

[0570] Step 3:

[0571] The server performs emotion analysis based on received image data. The input is image data received from the terminal, and the output is emotion information. Specifically, the data processing involves using an image recognition algorithm to detect facial expressions such as smiles and surprise and identify emotions. In terms of operation, it uses an image analysis library (e.g., OpenCV, TensorFlow) to analyze faces and facial expressions and generate data that quantifies emotions.

[0572] Step 4:

[0573] The server generates text based on the results of sentiment analysis. It uses sentiment information obtained in step 3 as input and generates natural language text as output. For specific data calculations, a generative AI model (e.g., GPT) is used, providing the most appropriate prompt sentences as input to generate text. The specific operation involves parameterizing the sentiment information and inputting it into the generative AI model to obtain a diary with richly expressive emotions.

[0574] Step 5:

[0575] The server sends the generated text to the terminal. It uses the text created in step 4 as input and delivers the text in a format that can be displayed on the terminal as output. Specifically, it formats the diary entries as text messages and sends them to the terminal via the network.

[0576] Step 6:

[0577] The terminal displays received text to the user. The input is diary entries sent from the server, and the output is displayed on the screen in a format viewable by the user. Specifically, a dedicated application retrieves the diary text and displays it visually through the user interface. At this time, important points are highlighted, and related activity suggestions are also provided.

[0578] (Application Example 2)

[0579] 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."

[0580] The challenge is to provide a system that enhances the user experience by recording users' daily lives in a more emotionally rich way and automating action and purchase suggestions based on individual emotions.

[0581] 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.

[0582] In this invention, the server includes means for acquiring image information and schedule information stored in a mobile communication device, means for generating text based on emotion data extracted from the image information, and means for recommending actions based on the emotion data. This makes it possible to specifically record the user's daily life based on emotions and to suggest actions that meet individual needs.

[0583] A "mobile communication device" is an electronic device that a user carries with them to collect and transmit information. This device has the function of acquiring data such as images and schedules, and transmitting it to a data processing device as needed.

[0584] "Image information" refers to photographic and video data acquired by mobile communication devices, which visually records the user's activities and surrounding environment.

[0585] "Schedule information" refers to data on schedules and event information managed by the user, including plans for the user's daily activities.

[0586] A "data processing device" is a computer system that has the function of analyzing data received from a mobile communication device and processing and transforming the information.

[0587] "Emotional data" refers to data that indicates a user's emotional state, analyzed from image information and audio, and expresses emotions such as joy and surprise using numerical values ​​and categories.

[0588] "Means for generating text" refers to a process that automatically creates documents based on acquired data, and in particular, has the function of generating content that reflects emotional data.

[0589] "Behavioral recommendations" refer to suggesting the next course of action or options to the user based on analyzed data. These recommendations are customized based on the user's emotions and behavioral history.

[0590] This system aims to recognize the user's emotions and generate a diary based on those emotions. To implement this, the following programs and hardware are required:

[0591] The server receives image information and schedule information acquired from mobile communication devices (terminals). Smartphones and tablets equipped with high-resolution cameras are used for this purpose. These terminals have the function of sending photos taken by the user on a daily basis and their own schedule data to the server in real time.

[0592] The received information is processed on the server for emotion recognition. The software used here includes OpenCV, an image analysis library, and TensorFlow, a machine learning framework for building emotion inference models. This allows the server to analyze the image information and extract emotion data such as the user's smile or surprise.

[0593] After sentiment data is extracted, a generative AI model (e.g., the GPT model) for natural language processing is used to create sentiment-based diary entries. The generated entries are then sent back to the device and presented to the user visually. The user can review these entries and edit them as needed.

[0594] As a concrete example, suppose a user visits a tourist spot on a holiday and takes several photos of themselves smiling. In this case, the server recognizes the emotion of "enjoyment" from these photos and automatically generates a diary entry such as, "I thoroughly enjoyed my holiday and felt a lot of fun."

[0595] An example of a prompt for a generative AI model would be: "Generate a diary from the following data. Photo emotion: Mostly smiles. Activity: Travel, Situation: Sightseeing." This prompt allows the AI ​​to generate text that reflects the user's intentions and emotions.

[0596] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0597] Step 1:

[0598] The device uses a high-resolution camera to collect image and schedule information to record the user's daily life. This information includes photos taken by the user and event information based on their schedule. The device packages this data into packets and sends them to the server using a secure communication method.

[0599] Step 2:

[0600] The server analyzes image and schedule information received from the terminal. Here, the OpenCV image analysis library is used to detect the content of the photograph, paying particular attention to the user's facial expressions. The input is photographic data from the terminal, and the output is data indicating emotions such as smiles and surprise. This generates emotion data extracted from the photograph.

[0601] Step 3:

[0602] The server utilizes an emotion inference model to determine the user's overall emotional state based on extracted emotion data. This process uses TensorFlow to analyze the emotion data and estimate the user's emotions on that particular day. The output is a numerical and categorized representation of the user's emotions.

[0603] Step 4:

[0604] The server uses a generative AI model (e.g., a GPT model) to generate diary entries based on the obtained sentiment data. The input consists of quantified sentiment data and categorized activity descriptions, while the output is a diary entry in natural-sounding text format. This entry incorporates information about emotions and activities.

[0605] Step 5:

[0606] The server sends the generated text to the terminal. This text is customized to include expressions that match the user's emotions and is displayed on the terminal in a format that the user can view. The user can update their diary based on the provided text and edit it as needed.

[0607] 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.

[0608] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0609] 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.

[0610] [Fourth Embodiment]

[0611] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0612] 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.

[0613] 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).

[0614] 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.

[0615] 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.

[0616] 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).

[0617] 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.

[0618] 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.

[0619] 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.

[0620] 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.

[0621] 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.

[0622] 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.

[0623] 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".

[0624] This invention utilizes a mobile communication device (terminal) and a data processing device (server) to achieve automatic diary generation. The operation of this system is described in detail below.

[0625] The device is used to record the user's daily activities. It retrieves visual data and schedule information from the image library and calendar app. This data becomes the material for a diary automatically generated based on the user's activity records over a certain period.

[0626] The collected data is transmitted to the server via the network using a secure protocol. The server executes advanced data analysis algorithms, performing object recognition from images, text analysis, and integrating schedule and location information. This analysis provides a comprehensive understanding of the day's activities, and natural language processing is used to generate diary-style entries.

[0627] For example, if a user takes an image on a particular day that includes a restaurant, the server analyzes the image to identify details such as, "On this day, I enjoyed a meal with a friend at a specific restaurant." Furthermore, it cross-references this with the user's schedule information to supplement the time and location details.

[0628] Furthermore, the server manages users' purchase history and can recommend repurchases of items relevant to their journal entries. This significantly improves the convenience of users' daily lives.

[0629] The generated diary is sent back to the device and displayed to the user through the device's application. The user can view the diary's contents, edit it as needed, and share it with others. This entire process allows for detailed recording of daily events without the need for manual input.

[0630] The following describes the processing flow.

[0631] Step 1:

[0632] The device retrieves visual data stored on the user's device and extracts image files from the photo library for a specified period. It also collects associated metadata (such as the date and time of capture and location information).

[0633] Step 2:

[0634] The device accesses the user's calendar application to retrieve event information for a specified period. It collects event titles, dates and times, and participant information to use as data to understand the context of the activities.

[0635] Step 3:

[0636] The device uses GPS data to obtain the user's daily movement history. This allows for accurate recording of the places and times the user has visited.

[0637] Step 4:

[0638] The device encrypts the collected visual data, schedule information, and GPS data, and sends it to the server as a data package. A secure communication protocol is used to prevent information leakage.

[0639] Step 5:

[0640] The server decodes the received data and performs image analysis from the visual data. It extracts information about people, places, and objects from the image to grasp the general outline of the activity. It performs sentiment analysis to evaluate the atmosphere of the image.

[0641] Step 6:

[0642] The server cross-references scheduled information with GPS data and organizes user activity chronologically. It verifies the consistency between scheduled events and actual activities and analyzes the reasons for any discrepancies.

[0643] Step 7:

[0644] The server generates text based on the analysis results, creating a diary-style document. It expresses the user's daily activities in natural language, supplementing any special notes.

[0645] Step 8:

[0646] The server analyzes the user's purchase history and suggests repurchasing items related to their activities in their journal. It also provides the user with information about items they have previously purchased.

[0647] Step 9:

[0648] The server sends the generated diary and repurchase suggestions to the device, and the device displays this content in the application. The user reviews the diary content and edits or shares it with others as needed.

[0649] (Example 1)

[0650] 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".

[0651] Manually recording daily events and activities is a time-consuming and laborious task for users. Furthermore, the resulting records are often incomplete and lack usefulness when viewed later. Additionally, there is a lack of systems for integrating and effectively utilizing related information such as purchase history and schedules.

[0652] 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.

[0653] In this invention, the server includes means for generating text in natural language based on visual information and scheduled information, means for generating text using a generative AI model, and means for identifying objects or locations in the analysis of visual information and reinforcing special notes. This enables the user to automatically record daily events in detail and manage those records efficiently.

[0654] A "mobile communication device" is a device equipped with communication functions that can be used while on the move, such as a mobile phone, smartphone, or tablet.

[0655] "Visual information" refers to visual data such as photographs, images, and videos, and is information acquired to record the user's daily activities.

[0656] "Schedule information" refers to information about a user's planned activities and appointments, based on calendar applications or schedules.

[0657] An "information processing device" is a device that receives data, analyzes and processes it, and converts it into useful information, and includes computer systems such as servers.

[0658] "Natural language" refers to the language that humans use on a daily basis, and also refers to human-readable text formats generated by computer programs.

[0659] A "generative AI model" is a computational model that uses artificial intelligence to generate text and data, and is particularly characterized by its advanced natural language processing capabilities.

[0660] "Target identification" refers to the process of identifying objects and locations contained in visual information using image analysis techniques and extracting their characteristics.

[0661] "Reinforcing special notes" means highlighting important information and facts based on the information obtained through analysis, thereby improving the accuracy and usefulness of the record.

[0662] This invention is a system for efficiently recording and managing a user's daily activities by linking a mobile communication device and an information processing device. The embodiments for carrying out the invention are described in detail below.

[0663] A device is a mobile communication device such as a smartphone or tablet, and it plays a role in recording the user's daily activities. The device retrieves visual information such as photos and videos from its image library and collects schedule information from its calendar app. It can also obtain location information using GPS functionality.

[0664] The collected visual and schedule information is sent to the server via the network using security protocols such as HTTPS. The server, acting as an information processing device, processes the received data and performs advanced analysis. Libraries such as OpenCV are used for image analysis, and NLP tools such as spaCy and BERT are used for natural language processing. Furthermore, the server utilizes generative AI models to generate text in natural language based on the received visual and schedule information.

[0665] This system uses a generative AI model to automatically create diary-style entries, such as "On this day, I enjoyed a meal with a friend at a specific restaurant," based on visual and scheduled information. An example of a prompt used in this process is, "Based on the user's activity results, please summarize the day's events in detail in a diary," which is input to the generative AI model.

[0666] The server can also manage the user's purchase history and suggest repurchases of related products. The generated diary entries are sent back to the terminal and displayed to the user through a dedicated application. Users can view, edit, and share the provided diary entries with others.

[0667] This invention allows users to obtain a diary that accurately summarizes visual and scheduled information without requiring much effort, thereby improving the convenience of daily life.

[0668] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0669] Step 1:

[0670] Users record their daily activities using the device. Specifically, the device acquires visual information using its camera and sensors. It also retrieves schedule information from its calendar app and records location information using its GPS function. As a result, image data, schedules, and location information are input into the device. This input data becomes the basic information necessary for subsequent processing.

[0671] Step 2:

[0672] The terminal encrypts the collected visual and schedule information using the HTTPS protocol and sends it to the server over the network. Specifically, the terminal periodically aggregates the accumulated data and forms a transmission batch. The output of this step is an encrypted data packet, which is then input to the server.

[0673] Step 3:

[0674] The server decrypts the encrypted data received from the terminal and begins data analysis. Here, the server uses the OpenCV library to analyze visual information and recognize objects and scenes. It uses NLP tools (spaCy and BERT) to analyze text information and understand the contents of schedules and diaries. The output of this step is the analyzed text data and image tag information.

[0675] Step 4:

[0676] The server uses a generative AI model to generate a diary in natural language from the analysis results. Specifically, it takes the prompt "Based on the user's activity results, please summarize the day's events in detail in a diary" as input to the model, and outputs a detailed natural language text. The output here is a text that summarizes the user's activities for the day.

[0677] Step 5:

[0678] The server sends the generated diary entries to the terminal. The terminal displays the received entries to the user using a dedicated application. Specifically, when the terminal receives new diary data, it notifies the user and provides an interface for viewing the content. The output of this step is the diary screen that the user can view.

[0679] Step 6:

[0680] Users can view the diary generated via their device and edit or share it with others as needed. Specifically, users can view the displayed diary and use editing tools to modify its content, or use the share button to send it to friends. The output is the final or shared diary content.

[0681] (Application Example 1)

[0682] 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".

[0683] In today's busy lives, it's difficult to meticulously record daily events and reflect on memories. Furthermore, to efficiently preserve personal life records, a system is needed that integrates various types of information and automates the process. In such systems, the challenge lies in improving the comprehensiveness, accuracy, and convenience of the recorded information.

[0684] 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.

[0685] In this invention, the server includes means for acquiring information stored in a mobile communication device, means for transmitting the information to a data processing device, means for generating text based on the received information, and means for collecting additional activity information using an environmental recording device. This makes it possible to record an individual's daily life with high accuracy and comprehensively, and to automatically generate detailed records as needed.

[0686] A "mobile communication device" is a terminal device with communication capabilities that can be carried and used by a user.

[0687] "Information" refers to all data related to the user's daily activities, including visual data, schedule information, and environmental data.

[0688] A "data processing device" is a computer system used to analyze received data and perform processing such as converting it into text.

[0689] An "environmental recording device" is a device equipped with instruments and sensors to record surrounding conditions and user behavior, and to acquire additional information.

[0690] "Inference" is the process of deriving a logical conclusion based on collected data.

[0691] "Purchase history" refers to a series of data related to purchases a user has made in the past, and is information used to analyze behavioral patterns based on that data.

[0692] "Identification target" refers to a specific person or object being analyzed, or their attributes.

[0693] "Space" refers to the physical area that constitutes the place or environment in which a user engages in activities.

[0694] "Important matters" refer to events or occurrences in daily life that are particularly worthy of being recorded or recognized.

[0695] To realize this invention, a system comprising a mobile communication device carried by the user, an environmental recording device, and a data processing server on the cloud is required. Specific embodiments are described in detail below.

[0696] First, the device collects the user's visual data and schedule information. Cameras and sensors built into the device record the user's actions and environmental conditions. This information is transmitted from the mobile communication device to a server in the cloud using a secure protocol.

[0697] After receiving the data, the server uses a service like "Google Cloud Vision API" to perform image recognition, identifying specific objects and locations from the acquired images. In parallel, it uses a natural language processing model, such as "OpenAI's GPT model," to generate diary-style text based on the user's schedule and environment information.

[0698] By integrating the collected data and recognition results, a detailed activity log is generated, and the server creates a diary in a format customized to the user's preferences. For example, if the user enjoys a walk in the park, the server will write a sentence such as, "On a warm spring day, I spent time strolling leisurely in the park."

[0699] The generated diary is then sent back to the mobile communication device, and the user is notified on the terminal. The user can review the content and, if necessary, make edits or share it with others.

[0700] For example, you can input a prompt like, "Generate a text based on events that happened this morning. Inquiry details: weather, events at the park, time spent with family," into an AI model to obtain a detailed diary entry.

[0701] This entire process makes it an excellent system that allows users to automatically review and record their activities, even in the midst of a busy daily life.

[0702] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0703] Step 1:

[0704] The device uses cameras and sensors to collect image and audio data related to the user's daily activities. At this point, the input is visual and audio information obtained from the user's environment, and the output is this information being stored as data on the device.

[0705] Step 2:

[0706] The device transmits the collected information to the server via a secure protocol. The input is image and audio data from the device, and the output is the receipt of this data in an encrypted form to the server.

[0707] Step 3:

[0708] The server analyzes the received data and performs image analysis. Using image recognition technologies such as the Google Cloud Vision API, it identifies objects and locations from the data. The input is the received image data, and the output is the analyzed information about objects and locations.

[0709] Step 4:

[0710] The server further uses natural language processing (NLP) techniques to synthesize the received schedule information and the entire dataset into text. It is possible to utilize OpenAI's GPT model. The input consists of analyzed object / location information and schedule information, while the output is a diary-style text written in natural language.

[0711] Step 5:

[0712] The server sends the generated diary entries back to the terminal. The input is the generated text, and the output is the format in which it is displayed on the terminal.

[0713] Step 6:

[0714] Users can view their diary entries on their devices and manually edit or share them with others as needed. The input is the generated diary content, and the output is the edited or shared information.

[0715] 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.

[0716] The present invention relates to an embodiment of a system that integrates an emotion engine that recognizes a user's emotions and utilizes them as part of diary generation. This system is mainly composed of a mobile communication device (hereinafter referred to as a terminal) and a data processing device (hereinafter referred to as a server).

[0717] The device collects visual data and schedule information related to the user's daily activities. This data includes photos taken by the user and information about events they have attended, and serves as material for emotion recognition. In particular, visual data is a crucial element of emotion analysis, and the device infers the user's emotions from facial expressions and situations in images.

[0718] The collected data is transmitted to the server via a secure communication method. The server uses an emotion engine to recognize the user's emotions from the visual data. This emotion engine combines multiple algorithms; for example, it recognizes smiles and surprised expressions through image analysis and identifies emotions such as "I had a very enjoyable time today."

[0719] Next, the server generates diary entries that incorporate emotions. For example, if a user visited a tourist spot on a holiday and took many photos of themselves smiling, the entries might include phrases like, "I enjoyed my holiday and had a lot of fun." This process also includes analyzing purchase history, making it possible to suggest products that are relevant to the user's emotions.

[0720] The generated diary entries are sent to the device, where the user can view and edit them. In particular, emotionally charged entries are highlighted, serving as an element to attract the user's attention. Activity suggestions are also provided based on emotions, expanding the user's daily choices. Thus, this emotion-driven diary system provides a means of recording individual experiences in a more concrete and emotional way.

[0721] The following describes the processing flow.

[0722] Step 1:

[0723] The device retrieves visual data stored on the user's device. It references the image library and extracts images and videos taken within a specified period. It also retrieves metadata such as the date and time of capture and location information.

[0724] Step 2:

[0725] The device retrieves event information from the user's calendar app. It collects event information registered within a specified period and prepares detailed activity data based on the event name, date and time, location, and participant information.

[0726] Step 3:

[0727] The device uses GPS data to track the user's movement history, recording the routes traveled and the places visited. This provides data that offers context to the actual activity.

[0728] Step 4:

[0729] The device sends the acquired visual data, schedule information, and GPS data to the server as a single data package. The packaged data is encrypted before transmission to ensure security.

[0730] Step 5:

[0731] The server receives a data package and applies an emotion engine to the visual data within it. It performs image analysis to infer the user's emotions from facial expressions and context in the image, and then adds emotion tags.

[0732] Step 6:

[0733] The server analyzes schedule information and GPS data, referencing emotions and activity locations to generate chronological diary entries. It incorporates entries that reflect the user's emotional state, creating a unique diary format.

[0734] Step 7:

[0735] The server references purchase history data to identify products related to emotions and activities and suggests repurchases. This includes product recommendations tailored to the analyzed emotional state.

[0736] Step 8:

[0737] The generated diary and suggested content are sent to the user's device. The user can review the received diary and view special notes that are highlighted according to their emotions.

[0738] Step 9:

[0739] It provides interactive options that allow users to edit their diaries and share them with others, enabling them to customize the content of their diaries to their individual preferences.

[0740] (Example 2)

[0741] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0742] There is a lack of systems that concretely record users' daily experiences from an emotional perspective and generate diaries based on that data. Consequently, there is a challenge in that records and activity suggestions tailored to individual emotions are rarely provided efficiently and automatically.

[0743] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0744] In this invention, the server includes means for analyzing emotions based on received image data, means for generating text using the analyzed emotion information, and means for generating user activity suggestions. This makes it possible to generate a personalized diary that reflects the user's daily emotions.

[0745] "Communication device" refers to a mobile device that has the function of collecting data from the user's daily life.

[0746] "Image data" refers to visual information collected by communication devices as part of a user's activity.

[0747] "Scheduled information" refers to information about the user's planned activities and events.

[0748] An "information processing device" refers to a device that performs analysis and generates text based on received data.

[0749] "Methods for analyzing emotions" refer to technologies and algorithms used to identify a user's emotional state from image data.

[0750] "Analyzed emotional information" refers to information about the user's emotional state obtained through data analysis.

[0751] "Methods for generating text" refers to the process of automatically creating text in natural language based on analysis results.

[0752] "Means of highlighting special notes" refers to techniques that visually make important emotional information stand out in generated text.

[0753] "Means for generating activity suggestions" refers to a process for presenting appropriate activities and options based on the user's emotional state.

[0754] "A method of suggesting repurchases by referencing transaction history" refers to a system that encourages users to make new purchases by referring to past purchase information.

[0755] "Means for identifying individuals or places and supplementing special notes" refers to the process of identifying specific people or places from image data and adding relevant information based on that identification.

[0756] This invention is a system for utilizing a user's daily emotional data as an activity record, and consists of a communication device and an information processing device. Examples of the communication device include smartphones and tablet devices. The communication device has the function of acquiring image data and schedule information collected by the user in their daily life. Once this data is collected, the device securely transmits it to the information processing device.

[0757] The information processing device, after receiving the data,

[0758] We will perform sentiment analysis. Specifically, we will use the transmitted image data and utilize a sentiment analysis model to identify the user's emotional state. Image recognition algorithms (e.g., OpenCV or TensorFlow) will be applied as the technology used for this analysis. Based on the analyzed sentiment information, a generative AI model will be used to generate diary entries in natural language. This model will use technologies such as GPT and, by inputting prompts tailored to the user's emotions, will express the user's experience in detail and with rich emotion.

[0759] For example, suppose a user visits a park on a holiday and takes many photos of themselves having fun with friends. The device collects these photos and sends them to an information processing device. The server performs sentiment analysis and determines that many of the photos show "smiles." Based on this, a generative AI model is used to generate a diary entry with content such as, "I spent my holiday at the park with friends and had a great time." This diary is sent to the device and can be viewed and edited by the user.

[0760] An example of a prompt message would be, "Based on the sentiment analysis results and activity details of the photos taken by the user, generate the most appropriate expression for a diary entry."

[0761] Furthermore, the generated text is designed to include activity suggestions that take the user's emotions into consideration. This expands the user's options in daily life and makes it easier for them to take emotionally-driven actions.

[0762] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0763] Step 1:

[0764] The device acquires image data and schedule information from the user's daily life. The acquired image data includes photos and videos taken by the user. It collects information from the user's camera roll and scheduling app as input and generates formatted data as output. This data is the dataset that forms the basis for sentiment analysis and diary generation. Specifically, apps on the device collect information from sensors and the camera and temporarily store it in local storage.

[0765] Step 2:

[0766] The terminal transmits the acquired image data and schedule information to the information processing device. The data formatted in Step 1 is used as input, and the data is securely delivered to the information processing device as output. Specifically, the data is encrypted end-to-end using a network communication protocol (e.g., HTTPS) before transmission.

[0767] Step 3:

[0768] The server performs emotion analysis based on received image data. The input is image data received from the terminal, and the output is emotion information. Specifically, the data processing involves using an image recognition algorithm to detect facial expressions such as smiles and surprise and identify emotions. In terms of operation, it uses an image analysis library (e.g., OpenCV, TensorFlow) to analyze faces and facial expressions and generate data that quantifies emotions.

[0769] Step 4:

[0770] The server generates text based on the results of sentiment analysis. It uses sentiment information obtained in step 3 as input and generates natural language text as output. For specific data calculations, a generative AI model (e.g., GPT) is used, providing the most appropriate prompt sentences as input to generate text. The specific operation involves parameterizing the sentiment information and inputting it into the generative AI model to obtain a diary with richly expressive emotions.

[0771] Step 5:

[0772] The server sends the generated text to the terminal. It uses the text created in step 4 as input and delivers the text in a format that can be displayed on the terminal as output. Specifically, it formats the diary entries as text messages and sends them to the terminal via the network.

[0773] Step 6:

[0774] The terminal displays received text to the user. The input is diary entries sent from the server, and the output is displayed on the screen in a format viewable by the user. Specifically, a dedicated application retrieves the diary text and displays it visually through the user interface. At this time, important points are highlighted, and related activity suggestions are also provided.

[0775] (Application Example 2)

[0776] 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".

[0777] The challenge is to provide a system that enhances the user experience by recording users' daily lives in a more emotionally rich way and automating action and purchase suggestions based on individual emotions.

[0778] 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.

[0779] In this invention, the server includes means for acquiring image information and schedule information stored in a mobile communication device, means for generating text based on emotion data extracted from the image information, and means for recommending actions based on the emotion data. This makes it possible to specifically record the user's daily life based on emotions and to suggest actions that meet individual needs.

[0780] A "mobile communication device" is an electronic device that a user carries with them to collect and transmit information. This device has the function of acquiring data such as images and schedules, and transmitting it to a data processing device as needed.

[0781] "Image information" refers to photographic and video data acquired by mobile communication devices, which visually records the user's activities and surrounding environment.

[0782] "Schedule information" refers to data on schedules and event information managed by the user, including plans for the user's daily activities.

[0783] A "data processing device" is a computer system that has the function of analyzing data received from a mobile communication device and processing and transforming the information.

[0784] "Emotional data" refers to data that indicates a user's emotional state, analyzed from image information and audio, and expresses emotions such as joy and surprise using numerical values ​​and categories.

[0785] "Means for generating text" refers to a process that automatically creates documents based on acquired data, and in particular, has the function of generating content that reflects emotional data.

[0786] "Behavioral recommendations" refer to suggesting the next course of action or options to the user based on analyzed data. These recommendations are customized based on the user's emotions and behavioral history.

[0787] This system aims to recognize the user's emotions and generate a diary based on those emotions. To implement this, the following programs and hardware are required:

[0788] The server receives image information and schedule information acquired from mobile communication devices (terminals). Smartphones and tablets equipped with high-resolution cameras are used for this purpose. These terminals have the function of sending photos taken by the user on a daily basis and their own schedule data to the server in real time.

[0789] The received information is processed on the server for emotion recognition. The software used here includes OpenCV, an image analysis library, and TensorFlow, a machine learning framework for building emotion inference models. This allows the server to analyze the image information and extract emotion data such as the user's smile or surprise.

[0790] After sentiment data is extracted, a generative AI model (e.g., the GPT model) for natural language processing is used to create sentiment-based diary entries. The generated entries are then sent back to the device and presented to the user visually. The user can review these entries and edit them as needed.

[0791] As a concrete example, suppose a user visits a tourist spot on a holiday and takes several photos of themselves smiling. In this case, the server recognizes the emotion of "enjoyment" from these photos and automatically generates a diary entry such as, "I thoroughly enjoyed my holiday and felt a lot of fun."

[0792] An example of a prompt for a generative AI model would be: "Generate a diary from the following data. Photo emotion: Mostly smiles. Activity: Travel, Situation: Sightseeing." This prompt allows the AI ​​to generate text that reflects the user's intentions and emotions.

[0793] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0794] Step 1:

[0795] The device uses a high-resolution camera to collect image and schedule information to record the user's daily life. This information includes photos taken by the user and event information based on their schedule. The device packages this data into packets and sends them to the server using a secure communication method.

[0796] Step 2:

[0797] The server analyzes image and schedule information received from the terminal. Here, the OpenCV image analysis library is used to detect the content of the photograph, paying particular attention to the user's facial expressions. The input is photographic data from the terminal, and the output is data indicating emotions such as smiles and surprise. This generates emotion data extracted from the photograph.

[0798] Step 3:

[0799] The server utilizes an emotion inference model to determine the user's overall emotional state based on extracted emotion data. This process uses TensorFlow to analyze the emotion data and estimate the user's emotions on that particular day. The output is a numerical and categorized representation of the user's emotions.

[0800] Step 4:

[0801] The server uses a generative AI model (e.g., a GPT model) to generate diary entries based on the obtained sentiment data. The input consists of quantified sentiment data and categorized activity descriptions, while the output is a diary entry in natural-sounding text format. This entry incorporates information about emotions and activities.

[0802] Step 5:

[0803] The server sends the generated text to the terminal. This text is customized to include expressions that match the user's emotions and is displayed on the terminal in a format that the user can view. The user can update their diary based on the provided text and edit it as needed.

[0804] 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.

[0805] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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."

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] The following is further disclosed regarding the embodiments described above.

[0826] (Claim 1)

[0827] Means for acquiring visual data and schedule information stored in a mobile communication device,

[0828] Means for transmitting the aforementioned visual data and schedule information to a data processing device,

[0829] The data processing device includes means for generating text based on received visual data and schedule information,

[0830] Means for transmitting the aforementioned text to the mobile communication device,

[0831] In the aforementioned mobile communication device, the means for displaying the text,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, comprising means for referencing the purchase history of a product and making a repurchase suggestion based on the aforementioned visual data and scheduled information.

[0835] (Claim 3)

[0836] The system according to claim 1, further comprising means for identifying a person or place and reinforcing special notes in the analysis of the aforementioned visual data.

[0837] "Example 1"

[0838] (Claim 1)

[0839] Means for acquiring visual information and schedule information stored in a mobile communication device,

[0840] Means for transmitting the aforementioned visual information and schedule information to an information processing device,

[0841] The aforementioned information processing device includes means for generating text in natural language based on received visual information and schedule information,

[0842] A means of generating text using a generative AI model,

[0843] Means for transmitting the aforementioned text to the mobile communication device,

[0844] In the aforementioned mobile communication device, the means for displaying the text,

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, comprising means for referencing the product's purchase history and making a repurchase suggestion based on the aforementioned visual information and scheduled information.

[0848] (Claim 3)

[0849] The system according to claim 1, further comprising means for identifying an object or location and reinforcing special notes in the analysis of the aforementioned visual information.

[0850] "Application Example 1"

[0851] (Claim 1)

[0852] Means for acquiring information stored in a mobile communication device,

[0853] Means for transmitting the aforementioned information to a data processing device,

[0854] The data processing device includes means for generating text based on received information,

[0855] Means for transmitting the aforementioned text to the mobile communication device,

[0856] In the aforementioned mobile communication device, the means for displaying the text,

[0857] Means for collecting additional activity information using environmental recording devices,

[0858] A means for integrating information acquired from the environmental recording device with the aforementioned information and performing inference,

[0859] A means of outputting events linked to memory based on the generated text,

[0860] A system that includes this.

[0861] (Claim 2)

[0862] The system according to claim 1, comprising means for recommending repurchase based on the aforementioned information and environmental information, with reference to purchase behavior history.

[0863] (Claim 3)

[0864] The system according to claim 1, comprising means for identifying an object or space and reinforcing important information in the analysis of the aforementioned information.

[0865] "Example 2 of combining an emotion engine"

[0866] (Claim 1)

[0867] Means for acquiring image data and schedule information stored in a communication device,

[0868] Means for transmitting the aforementioned image data and schedule information to an information processing device,

[0869] The aforementioned information processing device includes means for analyzing emotions based on received image data,

[0870] A means for generating text using the analyzed emotional information,

[0871] Means for transmitting the aforementioned document to the communication device,

[0872] The communication device includes means for displaying the text,

[0873] Means for highlighting special notes in the aforementioned text,

[0874] A means of generating user activity suggestions,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The system according to claim 1, comprising means for referencing transaction history and making a repurchase suggestion based on the aforementioned image data and scheduled information.

[0878] (Claim 3)

[0879] The system according to claim 1, further comprising means for identifying individuals or locations and reinforcing special notes in the analysis of the aforementioned image data.

[0880] "Application example 2 when combining with an emotional engine"

[0881] (Claim 1)

[0882] Means for acquiring image information and schedule information stored in a mobile communication device,

[0883] Means for transmitting the aforementioned image information and schedule information to a data processing device,

[0884] The data processing device includes means for generating text based on received image information and schedule information,

[0885] Means for transmitting the aforementioned text to the mobile communication device,

[0886] In the aforementioned mobile communication device, the means for displaying the text,

[0887] A means for generating text based on emotion data extracted from the aforementioned image information,

[0888] A means for recommending actions based on the aforementioned emotional data,

[0889] A system that includes this.

[0890] (Claim 2)

[0891] The system according to claim 1, comprising means for referencing the product's purchase history and recommending repurchase based on the aforementioned image information and schedule information.

[0892] (Claim 3)

[0893] The system according to claim 1, further comprising means for identifying a person or location and reinforcing special notes in the analysis of the aforementioned image information. [Explanation of symbols]

[0894] 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. Means for acquiring visual data and schedule information stored in a mobile communication device, Means for transmitting the aforementioned visual data and schedule information to a data processing device, The data processing device includes means for generating text based on received visual data and schedule information, Means for transmitting the aforementioned text to the mobile communication device, In the aforementioned mobile communication device, the means for displaying the text, A system that includes this.

2. The system according to claim 1, further comprising means for referencing the purchase history of a product and making a repurchase suggestion based on the aforementioned visual data and scheduled information.

3. The system according to claim 1, further comprising means for identifying a person or place and reinforcing special notes in the analysis of the aforementioned visual data.

Images