System

Abstract

A system is provided.SOLUTION: A system comprising: means for a terminal to acquire position information, health care information, payment information, search information, and weather information of a user from a plurality of sensors and applications; means for a server to receive the acquired data and accumulate the data for each user; means for the server to automatically generate a life log of the user based on the accumulated data; and means for the server to generate a life-improving suggestion based on the life log of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] It is difficult to look back on one's daily life and identify specific improvements that can improve one's quality of life. Furthermore, many people find it tedious to keep a diary or record their daily life, making it difficult to keep up with it. It is especially difficult for the elderly and those with memory impairments to track and reflect on their own actions. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the present invention provides the following means.

[0006] The device has the means to acquire the user's location information, healthcare information, payment information, search information, and weather information from multiple sensors and applications, and to format this data into JSON format and send it to the server.

[0007] The server analyzes the received data, accumulates the data for each user, and has means for automatically generating a life log for the user based on the data.

[0008] Furthermore, the server provides an environment where users can add or edit their life logs, and the system stores the edited life logs again and uses AI to generate lifestyle improvement suggestions, allowing users to easily look back on their lives and identify areas for improvement.

[0009] A "terminal" is a device used by a user, and includes a smartphone, a tablet, a wearable device, and the like.

[0010] A "sensor" is a device that detects physical environmental information (such as position, movement, or heart rate) and converts it into digital data.

[0011] An "application" is a software program that runs on a device, including healthcare apps, payment apps, browsers, etc.

[0012] "Location information" refers to geographical location data of a user obtained using technology such as GPS.

[0013] "Health care information" is information related to the user's health condition, including the number of steps taken, heart rate, calories burned, and the like.

[0014] "Payment information" refers to data related to payments made by users, including the place of purchase, amount, date and time, etc.

[0015] "Search information" refers to data related to the user's search history and keywords used on the Internet.

[0016] "Weather information" is data relating to the current weather and weather forecast, including temperature, humidity, precipitation, and the like.

[0017] The "JSON format" is a type of data exchange format, an abbreviation for JavaScript Object Notation, and is a format used to structure, store, and transfer data.

[0018] A "server" is a computer system that receives, analyzes, and stores data and provides information to users.

[0019] A "life log" is a collection of data that records a user's daily life, including a history of activities and behaviors.

[0020] "AI" stands for artificial intelligence, a technology used to analyze data and generate lifestyle improvement suggestions.

[0021] "Lifestyle improvement suggestions" refer to specific advice or suggestions to improve the quality of a user's life.

[0022] The above are definitions of important terms included in the scope of the present patent claims. [Brief explanation of the drawings]

[0023] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0024] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0025] First, the terms used in the following description will be explained.

[0026] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0027] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0028] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0029] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0030] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0034] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0035] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0036] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0037] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0038] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0041] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0042] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0043] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0044] The present invention is a system that records the user's daily life and suggests lifestyle improvements based on the data. This system is composed of a terminal, a server, and user interactions.

[0045] Overall system overview

[0046] 1. Data collection

[0047] The device acquires the user's location information, health information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health app, payment app, browser, etc.). This data is collected periodically and formatted in JSON format.

[0048] 2. Data transmission

[0049] The device compiles the collected data into JSON format and sends it to the server along with the user's identification information (user ID). The server receives this information and analyzes it.

[0050] 3. Data accumulation

[0051] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and suggest lifestyle improvements.

[0052] 4. Generating a life log

[0053] The server analyzes the accumulated data and automatically generates a life log for the user, which is a history of the user's daily activities and behavior and is provided to the user via their device.

[0054] 5. Additions and corrections by users

[0055] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[0056] 6. Generating lifestyle improvement proposals

[0057] The server uses AI to generate lifestyle improvement suggestions based on the user's accumulated data and life log. These suggestions include health habit suggestions, exercise advice, and suggestions for improving dietary habits. The generated suggestions are notified to the user via their device.

[0058] Explanation of program processing

[0059] Terminal handling

[0060] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. All of this data is formatted into JSON and sent to the server.

[0061] Server Processing

[0062] The server receives JSON-formatted data sent from the device and accumulates the data for each user ID. The accumulated data is analyzed as appropriate, and a life log is automatically generated. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and updated life log, and notifies the device.

[0063] User Action

[0064] Users can review their life logs displayed on their devices and reflect on their lives. They can make additions or corrections as needed to make the life logs more detailed and accurate. Users can also refer to suggestions for lifestyle improvements from the server and review their health habits and improve the quality of their lives.

[0065] Specific examples

[0066] For example, if a user goes jogging in the park at 8:00 in the morning, the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and health app and sends them to the server. The server analyzes this information and automatically records it in the user's life log as "Jogging in the park at 8:00." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. Then, using AI, it generates lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining your health," and notifies the user.

[0067] This system allows users to effortlessly reflect on their daily lives and obtain hints for improving their lifestyle habits. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably reflect on their own behavior and helps improve the quality of their lives.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] The device uses a GPS sensor to obtain the user's current location. It also collects health information such as the number of steps taken and heart rate from a health app, purchase history and amount spent information from a payment app, and obtains the user's search information from the browser's search history, as well as current weather information from a weather app or API.

[0071] Step 2:

[0072] The device formats the location, health, payment, search, and weather information into a single JSON object, including the user ID, ready to be sent to the server later.

[0073] Step 3:

[0074] The device creates a POST request to send a JSON object to the server and sends it to the specified server URL. If the transmission is successful, the device notifies the user of this information.

[0075] Step 4:

[0076] The server receives the POST request sent from the device. The received data is analyzed and stored in a database for each user ID. The stored data will be used to generate future life logs and propose lifestyle improvements.

[0077] Step 5:

[0078] The server periodically generates a user's life log based on the accumulated data. The life log includes a history of the user's daily activities and behavior. The generated life log is then sent to the device.

[0079] Step 6:

[0080] The user checks the life log displayed on the device. The life log displays a detailed record of the user's daily activities. The user can add or edit the life log as needed.

[0081] Step 7:

[0082] After the user adds or modifies the lifelog, the device sends the information back to the server as a JSON object. The server receives the modified lifelog and updates the database.

[0083] Step 8:

[0084] The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and the revised life log. The generated suggestions include specific health habits and lifestyle advice.

[0085] Step 9:

[0086] The server formats the generated lifestyle improvement proposals in JSON format and sends them to the device, which receives them and notifies the user.

[0087] Step 10:

[0088] Users can check the lifestyle improvement suggestions displayed on their devices and take actions to improve the quality of their daily lives. Users can refer to the suggestions and review their health and lifestyle habits.

[0089] These are the specific processing steps of the program, which allow the user to reflect on their daily life and receive specific suggestions for improving the quality of their life.

[0090] Example 1

[0091] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0092] Conventional systems that record daily life and suggest lifestyle improvements often require time-consuming data collection, storage, and analysis, or are insufficient. Furthermore, users often have to spend time checking and editing their own life logs, which results in poor accuracy in lifestyle improvement suggestions. This makes the introduction and use of such systems particularly difficult for elderly users and those with memory impairments.

[0093] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0094] In this invention, the server

[0095] A means for the terminal to acquire user location information, health status information, transaction information, search history, and weather information from a plurality of sensors and software;

[0096] a server receiving the acquired data and storing the data for each user;

[0097] A means for the server to automatically generate a life record of the user based on the accumulated data;

[0098] A server generates lifestyle improvement suggestions based on the user's lifestyle records;

[0099] A means for the terminal to format the acquired data into a JSON format and transmit the formatted data to a server;

[0100] A means for a server to analyze the JSON format data and generate a life record of the user;

[0101] A means for the server to analyze the accumulated data and life records using AI and generate improvement suggestions;

[0102] This includes:

[0103] Users can effortlessly record their daily lives, easily add to and edit their life logs, and even receive highly accurate lifestyle improvement suggestions based on the accumulated data.

[0104] A "terminal" is an information processing device equipped with multiple sensors and software for collecting data on the user's daily life.

[0105] A "sensor" is a device that measures physical environmental information, and in this system includes GPS sensors, health status sensors, weather sensors, etc.

[0106] "Software" refers to a program that is installed on a device and performs a specific function, such as a healthcare app, a payment app, or a browser.

[0107] "Location Information" means data that indicates a user's geographic location and is collected by a GPS sensor.

[0108] "Health status information" is data related to the user's health, and includes information such as the number of steps taken, heart rate, and calorie consumption.

[0109] "Transaction information" is data related to a user's purchasing activities, including purchase history obtained from a payment app.

[0110] "Search history" is the history of searches a user has performed on the Internet, and is data obtained from a browser.

[0111] "Weather information" refers to data related to the weather, obtained from weather apps and weather sensors.

[0112] A "life log" is data that records the history of a user's daily activities and behavior, and is automatically generated by a server.

[0113] "Lifestyle improvement suggestions" are suggestions for improving the quality of life that are generated based on the user's life log and accumulated data.

[0114] The "JSON format" is a format used to structurally represent data and communicate between servers and terminals.

[0115] "AI" refers to artificial intelligence, a technology that analyzes accumulated data and generates lifestyle improvement suggestions.

[0116] This invention relates to a system that records a user's daily life and makes suggestions for improving their lifestyle based on the data. This system is composed of a terminal, a server, and user interactions.

[0117] System configuration

[0118] 1. Terminal configuration and operation

[0119] The device collects various data about the user using multiple built-in sensors (e.g., GPS sensor, health condition sensor) and installed software (e.g., healthcare app, payment app, browser). Specifically, the device collects the following data:

[0120] Location information using a GPS sensor

[0121] Health status information such as steps taken, heart rate, and calorie consumption via the Health app

[0122] Transaction information (purchase history) from payment apps

[0123] Browser search history

[0124] Weather information from weather apps and weather sensors

[0125] This collected data is obtained at regular intervals and formatted into JSON format.

[0126] 2. Data transmission

[0127] The device periodically converts the collected data into JSON format and sends it to the server along with the user ID. This transmission is performed every 15 minutes, and the HTTPS protocol is used to maintain data integrity.

[0128] 3. Server Configuration and Operation

[0129] The server receives and analyzes the JSON format data sent from the device. The received data is stored in a database for each user ID, and each record also includes a timestamp for the data.

[0130] The server periodically analyzes the accumulated data and automatically generates a record of the user's daily life (life log). The life log records the user's daily activities and behavior. The server then uses AI to generate lifestyle improvement suggestions based on the accumulated data and the latest life log, and notifies the device.

[0131] 4. User Operation

[0132] Users can check the lifelog displayed on their device and reflect on their daily lives. They can add or edit the lifelog as needed, which improves its accuracy. Data added or edited by the user is sent back to the server, and the lifelog is updated.

[0133] Specific examples

[0134] For example, if a user goes jogging in the park at 8:00 a.m., the device obtains location information from the GPS sensor and jogging data (distance, time, heart rate) from the health app, then compiles this into a JSON file and sends it to the server. The server analyzes the received data and automatically records "Jogging in the park at 8:00" in the user's life log. If the user checks this life log and adds "That was a great run!", this information is also sent to the server and the life log is updated. The server then uses AI to generate lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and notifies the user via the device.

[0135] Prompt Sentence Examples

[0136] "If the user has the habit of jogging every morning, explain how jogging three times a week can help them stay healthy."

[0137] In this way, users can effortlessly review their daily lives, receive highly accurate suggestions for lifestyle improvements, and improve their quality of life. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably review their own actions, helping to improve their quality of life.

[0138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0139] Step 1: Collect data

[0140] Terminal handling

[0141] The device collects user data using various sensors and software: location information from the GPS sensor, step count and heart rate from health apps, purchase history from payment apps, search history from the browser, and weather information from weather apps.

[0142] Input: Data obtained from GPS sensor, health app, payment app, browser, and weather app

[0143] Data processing: Acquire raw data from each sensor and app and format it into JSON format.

[0144] Output: JSON format data

[0145] How it works: Every 15 minutes, the device retrieves new data from each sensor and app, consolidates it, and generates a JSON file.

[0146] Step 2: Sending data

[0147] Terminal handling

[0148] The data collected by the device is formatted in JSON and sent to the server along with the user ID.

[0149] Input: Formatted JSON data and user ID

[0150] Data processing: Encoding to maintain data integrity

[0151] Output: HTTPS request to the server

[0152] Specific operation: Every 15 minutes, the device makes an HTTPS request to the server and sends data in JSON format along with the user ID.

[0153] Step 3: Accumulate data

[0154] Server Processing

[0155] The server analyzes the received JSON format data and stores it in a database for each user ID.

[0156] Input: JSON format data sent from the terminal

[0157] Data processing: Parse the JSON data, extract each data item, and store it in the database.

[0158] Output: Data stored in the database

[0159] Specific operation: The server first stores the received data in temporary memory and then writes it to the database sequentially.

[0160] Step 4: Generating a Lifelog

[0161] Server Processing

[0162] The server periodically analyzes the accumulated data and automatically generates a life log for the user.

[0163] Input: Data stored for each user

[0164] Data processing: Perform time series analysis of the data and compile it into a history of the user's daily behavior.

[0165] Output: Life log

[0166] Specific operation: The server runs a job every day at midnight, analyzes data from the past 24 hours, generates a "life log," and stores it in a database.

[0167] Step 5: User additions and modifications

[0168] User Action

[0169] Users can check their lifelog and add or edit it as needed.

[0170] Input: Lifelog displayed on the device

[0171] Data processing: Form input processing to support user additions and corrections

[0172] Output: Modified lifelog

[0173] Specific operation: When a user opens the app on their device, displays their life log, and adds "I ate bread for breakfast," the information is sent to the server in JSON format and the life log database is updated.

[0174] Step 6: Generate life improvement proposals

[0175] Server Processing

[0176] The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and life logs, and these suggestions are sent to the user via their device.

[0177] Input: User's accumulated data and life log

[0178] Data processing: Generate lifestyle improvement suggestions through analysis and pattern recognition using AI models

[0179] Output: Lifestyle improvement suggestions

[0180] Specific operation: The server runs the AI ​​model at 1 a.m. every day, analyzes the data, generates suggestions such as "It is recommended to jog three times a week," and notifies the user via the device.

[0181] (Application example 1)

[0182] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0183] In modern society, users are expected to improve their daily lifestyle habits and maintain their health. However, manually recording and analyzing their daily life data to find improvement measures is a very time-consuming process. For this reason, there is a need for a system that automatically collects, stores, and analyzes users' daily life data to provide lifestyle improvement suggestions. Furthermore, to improve the accuracy of lifestyle improvement suggestions, it is necessary to use generative AI models to perform more advanced analysis based on diverse data.

[0184] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0185] In this invention, the server includes: means for the terminal to acquire user location information, healthcare information, payment information, search information, and weather information from multiple sensors and applications; means for the server to receive the acquired data and accumulate the data for each user; means for the server to automatically generate a user's life log based on the accumulated data; means for the server to generate lifestyle improvement suggestions based on the user's life log; and means for generating prompt sentences and requesting analysis by a generative AI model to improve the accuracy of the lifestyle improvement suggestions. This allows users to easily collect and accumulate data about their daily lives and perform advanced analysis using AI, enabling them to receive highly accurate lifestyle improvement suggestions.

[0186] A "terminal" is an electronic device used to collect data from a user's daily life, and is equipped with multiple sensors and applications.

[0187] A "sensor" is a device that detects a physical phenomenon (e.g., position, movement, temperature, etc.) and converts it into digital data.

[0188] An "application" is a software program that runs on a terminal to provide a specific function or service.

[0189] "Location Information" means geographic location data of a user obtained using a GPS sensor.

[0190] "Healthcare information" refers to data related to health status and physical activity, including, for example, the number of steps taken and heart rate.

[0191] "Payment information" is data related to the purchase and payment history of a user.

[0192] "Search Information" is data about search queries performed by users on the Internet and their history.

[0193] "Weather information" is data about the weather conditions at the user's location.

[0194] A "server" is a computer system that receives, stores, and analyzes data sent from a terminal.

[0195] "Data storage" is the process of organizing collected data and storing it for later analysis and reuse.

[0196] A "life log" is digital data that records the history of a user's daily actions and activities.

[0197] "Lifestyle improvement suggestions" are specific advice and recommendations for improving lifestyle habits based on the user's life log.

[0198] A "prompt" is an instruction entered into a generative AI model to make it perform a specific task.

[0199] A "generative AI model" is an artificial intelligence algorithm used to analyze data using machine learning to generate insights and recommendations.

[0200] The present invention is a system that records the user's daily life and suggests lifestyle improvements based on the data. This system is composed of a terminal, a server, and user interactions.

[0201] 1. Data collection

[0202] The device acquires the user's location information, health information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health app, payment app, browser, etc.). The collected data is periodically formatted into JSON format.

[0203] 2. Data transmission

[0204] The data collected by the device is compiled in JSON format and sent to the server along with the user's identification information (user ID). The server receives and analyzes this data.

[0205] 3. Data accumulation

[0206] The server stores the received data in a database for each user ID. The stored data will be used to generate a life log and suggest lifestyle improvements.

[0207] 4. Generating a life log

[0208] The server analyzes the accumulated data and automatically generates a life log for the user, which records the user's daily activities and behavioral history and is provided to the user via their device.

[0209] 5. Additions and corrections by users

[0210] The user can check the lifelog displayed on the device and add or modify it as needed. The added or modified lifelog is then sent back to the server and updated.

[0211] 6. Generating lifestyle improvement proposals

[0212] The server uses a generative AI model to generate lifestyle improvement suggestions based on the user's accumulated data and life log. These suggestions include health habit suggestions, exercise advice, and suggestions for improving dietary habits. The generated suggestions are notified to the user via their device.

[0213] 7. Improved accuracy with generative AI models

[0214] The server then generates a prompt and requests the generative AI model to analyze it. This prompt includes the user's life log and collected data. The generative AI model provides analysis results that improve the accuracy of lifestyle improvement suggestions.

[0215] Hardware / Software used

[0216] Hardware: Smartphone

[0217] Software: Python, HTTP API (communication with server), generative AI model

[0218] Data processing / calculation: Data collection, formatting into JSON format, advanced analysis using AI

[0219] Specific examples

[0220] For example, if a user goes jogging in the morning, the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and healthcare app and sends them to the server. The server analyzes this information and automatically records it in the user's life log as "Jogging in the park at 8:00." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. The generative AI model is then used to generate lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and notifies the user.

[0221] Prompt Sentence Examples

[0222] "Analyze the following data to generate suggestions to improve the user's life:

[0223] GPS data: 35.6895, 139.6917, "jogging"

[0224] Health data: Steps: 3000, Heart rate: 120

[0225] Payment Data: Purchase: None

[0226] Search data: None

[0227] Weather data: Sunny, Temperature: 15

[0228] Please offer some advice on how to improve your life."

[0229] This system allows users to effortlessly reflect on their daily lives and receive specific advice on how to improve their lifestyle habits.

[0230] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0231] Step 1:

[0232] The device collects the user's location, health, payment, search, and weather information from multiple sensors and applications. Data obtained from sensors and applications includes location information from the GPS sensor, step count and heart rate records from the health app, purchase history from the payment app, browser search history, and weather information from the weather app. This data is temporarily stored on the device.

[0233] input:

[0234] Data from multiple sensors and applications

[0235] output:

[0236] Temporarily stored data on the device

[0237] Step 2:

[0238] The data collected by the device is periodically formatted into JSON format. The collected location information, health information, payment information, search information, weather information, etc. are compiled into a single JSON object, along with the user ID.

[0239] input:

[0240] Temporarily saved data

[0241] output:

[0242] Integration data in JSON format

[0243] Step 3:

[0244] The device sends formatted JSON data to the server using an HTTP POST request to send the data to the server's API endpoint. The server receives this request and prepares to parse the data.

[0245] input:

[0246] Integration data in JSON format

[0247] output:

[0248] Data sent to the server

[0249] Step 4:

[0250] The server receives the data sent from the device and stores it in a database for each user, allowing data associated with each user to be permanently stored and used for later analysis.

[0251] input:

[0252] Data sent to the server

[0253] output:

[0254] Accumulated data in the database

[0255] Step 5:

[0256] The server analyzes the accumulated data and automatically generates a life log for the user. It compares past data with newly added data to generate a life log that summarizes the user's daily activities and health status in chronological order. The generated life log is then saved back into the database.

[0257] input:

[0258] Accumulated data in the database

[0259] output:

[0260] Automatically generated lifelog

[0261] Step 6:

[0262] The server sends the generated lifelog to the device and provides it to the user. The user can check their own lifelog on the device and add or modify it as necessary.

[0263] input:

[0264] Automatically generated lifelog

[0265] output:

[0266] Life log presentation data

[0267] Step 7:

[0268] After the user adds or modifies the lifelog, the device sends the modified lifelog back to the server, which then updates the database with the modified lifelog.

[0269] input:

[0270] Modified Lifelog

[0271] output:

[0272] Updated database

[0273] Step 8:

[0274] The server generates lifestyle improvement proposals using a generative AI model based on the updated life log and accumulated data. The server generates prompt statements and requests the generative AI model to analyze them. Based on the analysis results of the generative AI model, highly accurate lifestyle improvement proposals are created.

[0275] input:

[0276] Updated lifelog and accumulated data

[0277] output:

[0278] Generated lifestyle improvement proposals

[0279] Step 9:

[0280] The server sends the generated lifestyle improvement suggestions to the terminal, and the user receives the lifestyle improvement suggestions via the terminal and makes lifestyle improvements based on them.

[0281] input:

[0282] Generated lifestyle improvement proposals

[0283] output:

[0284] User notification data

[0285] Prompt Sentence Examples

[0286] "Analyze the following data to generate suggestions to improve the user's life:

[0287] GPS data: 35.6895, 139.6917, "jogging"

[0288] Health data: Steps: 3000, Heart rate: 120

[0289] Payment Data: Purchase: None

[0290] Search data: None

[0291] Weather data: Sunny, Temperature: 15

[0292] Please offer some advice on how to improve your life."

[0293] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0294] This invention combines an emotion engine with a system that records a user's daily life and makes suggestions for lifestyle improvements based on that data. This system is composed of a terminal, a server, and an engine that handles user interaction and emotion recognition.

[0295] Overall system overview

[0296] 1. Data collection

[0297] The device acquires the user's location information, health care information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health care app, payment app, browser, etc.). In addition, the device's built-in emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[0298] 2. Data transmission

[0299] The device collects location information, health information, payment information, search information, weather information, and emotion data, and then compiles them into JSON format and sends them along with the user ID to the server. The server receives this information and analyzes it.

[0300] 3. Data accumulation

[0301] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[0302] 4. Generating a life log

[0303] The server analyzes the accumulated data and automatically generates a life log for the user, which includes the user's daily activities, behavioral history, and emotional state. The generated life log is provided to the user via their device.

[0304] 5. Additions and corrections by users

[0305] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[0306] 6. Generating lifestyle improvement proposals

[0307] The server uses AI to generate lifestyle improvement suggestions based on the user's accumulated data and life log. Taking into account the user's emotional data in particular, the server generates personalized suggestions based on their emotional state. The generated suggestions are then sent to the user via their device.

[0308] Explanation of program processing

[0309] Terminal handling

[0310] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. Furthermore, an emotion engine analyzes the user's facial expressions and voice tone to generate emotion data. All of this data is formatted in JSON format and sent to the server.

[0311] Server Processing

[0312] The server receives JSON-formatted data sent from the device and stores it in a database for each user ID. The stored data is analyzed as appropriate, and a life log is automatically generated. The generated life log records the user's emotional state along with their activity history. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI to generate lifestyle improvement suggestions based on the stored data and updated life log, and notifies the device. The suggestions take emotional data into consideration and include advice that fits the user's psychological state.

[0313] User Action

[0314] Users can check the life log displayed on their device and review their daily activity records. They can add or edit the life log as needed to make the record more detailed and accurate. Users can refer to the lifestyle improvement suggestions from the server and review their health and lifestyle habits. In particular, suggestions based on emotional data provide specific advice that is tailored to the user's psychological state.

[0315] Specific examples

[0316] For example, if a user goes jogging in the park at 8:00 a.m., the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and health app, and then uses the emotion engine to recognize the user's emotion of "comfortable" from their facial expressions and voice. This data is sent to the server, which analyzes it and automatically records it in the user's life log as "8:00 Jogging in the park, comfortable." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. Then, using AI, the device generates lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and provides specific exercise advice based on the user's comfortable jogging experience.

[0317] This system allows users to effortlessly reflect on their daily lives and receive suggestions for lifestyle improvements that reflect their emotional state. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably reflect on their own actions and emotions, helping to improve the quality of their lives.

[0318] The processing flow will be explained below.

[0319] Step 1:

[0320] The device uses the GPS sensor to obtain the user's current location, collects health information such as the number of steps taken and heart rate from the health app, and obtains purchase history and payment amount information from the payment app.

[0321] Step 2:

[0322] The device retrieves the user's search keywords and visited websites from the browser's search history, and also retrieves the current day's weather information from weather apps and APIs.

[0323] Step 3:

[0324] The device's emotion engine captures the user's facial expressions with a camera and records their voice with a microphone, and analyzes them to generate emotion data (e.g., happiness, anger, sadness, etc.).

[0325] Step 4:

[0326] The device formats the collected location, health, payment, search, weather, and emotion data into a single JSON object, which also includes the user ID.

[0327] Step 5:

[0328] The device creates a POST request to send the formatted JSON object to the server, sends it to the specified server URL, and notifies the user of the status if the transmission is successful.

[0329] Step 6:

[0330] The server receives the POST request sent from the device and analyzes the data. The received data is stored in a database for each user ID. This stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[0331] Step 7:

[0332] The server periodically generates a user's life log based on the accumulated data. The life log includes the user's daily activities, behavioral history, and emotional state. The generated life log is formatted in JSON format and sent to the device.

[0333] Step 8:

[0334] The user checks the life log displayed on the device. The life log displays a detailed account of the user's daily activities, behaviors, and emotional state. The user can add or edit the life log as needed.

[0335] Step 9:

[0336] The device reformats the lifelog that the user has added or modified into JSON format and sends it to the server. The server receives the modified lifelog and updates the database.

[0337] Step 10:

[0338] The server generates lifestyle improvement suggestions based on the accumulated data and the revised life log, using AI to take into account the user's emotional data and generate specific suggestions based on their emotions.

[0339] Step 11:

[0340] The server formats the generated lifestyle improvement proposals in JSON format and sends them to the device, which receives them and notifies the user.

[0341] Step 12:

[0342] Users can check the lifestyle improvement suggestions displayed on the device and improve their daily habits and behaviors based on them. For example, they receive specific advice such as how to maintain health by continuing to jog or how to reduce stress.

[0343] As a concrete example, consider the case where a user goes jogging in the park at 8:00 in the morning. The device obtains location information and jogging-related data (distance, time, heart rate) from the GPS sensor and health care app, and the emotion engine recognizes the emotion of "comfortable" from the user's facial expressions and voice. This data is sent to the server, analyzed, and automatically recorded in the life log as "8:00 Jogging in the park, comfortable." If the user checks this life log and adds "I had a great run!", the server updates and stores this information. Then, using AI, it generates lifestyle improvement suggestions such as "Jogging three times a week is effective for maintaining health" and provides specific exercise advice.

[0344] The above is a specific embodiment of the present invention. This system allows users to easily record their actions and emotions and receive specific suggestions for improving their quality of life. In particular, by using an emotion engine, it is possible to provide advice that fits the user's psychological state.

[0345] Example 2

[0346] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0347] Conventional lifelog systems have the problem of not being able to fully reflect a user's daily activities and emotional state. Furthermore, their lifestyle improvement suggestions do not take into account the user's emotional state, resulting in low user satisfaction and implementation rates. Furthermore, the process of collecting and analyzing data is cumbersome, often causing users to feel overwhelmed.

[0348] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0349] In this invention, the server includes: a terminal that acquires a user's location information, health information, purchase information, search information, and weather information from multiple sensors and software; a terminal that analyzes a user's facial expressions and voice tone and generates emotion data; a terminal that formats the acquired data into JSON format and transmits it to the server; a server that receives the acquired data and accumulates the data for each user; a server that automatically generates a user's life log based on the accumulated data; and a server that generates lifestyle improvement suggestions using a generative AI model based on the user's life log. This makes it possible to collect and analyze a user's comprehensive activity and emotion data and provide lifestyle improvement suggestions based on the user's individual emotional state.

[0350] A "terminal" is an electronic device equipped with multiple sensors and software for collecting a user's location information, health information, purchase information, search information, weather information, and emotional data.

[0351] A "server" is a computer system that receives, stores, and analyzes data sent from a terminal.

[0352] A "sensor" is an electronic device that collects environmental or biometric information, such as a user's location or physiological data.

[0353] "Software" refers to application programs installed on the terminal that collect and format data.

[0354] "User location information" is data about the user's current location obtained using a GPS sensor.

[0355] "Health information" is data indicating the physiological state of the user, such as the number of steps taken and heart rate.

[0356] "Purchase information" is data related to the purchase history and transactions made by the user.

[0357] "Search information" refers to data related to the keywords and history of searches a user has performed on the Internet.

[0358] "Weather information" refers to weather forecasts and temperature information obtained based on the user's location.

[0359] "Emotion data" is data that indicates an emotional state generated by the terminal's emotion engine by analyzing the user's facial expressions and vocal tone.

[0360] The "JSON format" is a lightweight, text-based data exchange format for structuring and representing data.

[0361] A "user ID" is an identification code assigned to each user to uniquely identify them.

[0362] A "life log" is data that records a user's daily activity history and emotional state.

[0363] A "generative AI model" is an artificial intelligence algorithm that generates lifestyle improvement suggestions based on collected data.

[0364] "Lifestyle Improvement Suggestions" provides advice to improve the user's lifestyle habits based on the user's life log and emotional data.

[0365] The present invention is a system for providing suggestions to improve a user's life. This system records the user's daily life and makes suggestions to improve their life based on that data. The system is mainly composed of a terminal, a server, and an engine that handles user interaction and emotion recognition.

[0366] Specific configuration

[0367] Terminal

[0368] The device collects data using various sensors and applications, including GPS sensors, health management software, payment applications, web browsers, and emotion engines. For example, consider a device that implements the following measures:

[0369] Location information: Uses a GPS sensor to obtain real-time user location information.

[0370] Health information: We collect health data such as your steps and heart rate from health management software (e.g., Apple Health, Google Fit).

[0371] Purchase information: Obtain purchase history from a payment application (e.g., a general-purpose payment system).

[0372] Search information: Obtain search history from web browsers (e.g., general-purpose browsers).

[0373] Emotion data: The emotion engine analyzes the user's facial expressions and vocal tone to generate emotion data.

[0374] All collected data is formatted in JSON and sent to the server.

[0375] server

[0376] The server receives the JSON format data sent from the device and accumulates the data for each user. Specifically, the data is saved for each user ID using a database (e.g., a general-purpose database management system). The accumulated data is analyzed, and the user's life log is automatically generated.

[0377] The generated life log includes the user's emotional state along with their activity history. For example, the following life log may be generated:

[0378] 8:00 Jogging in the park, comfortable

[0379] 12:00 Buy coffee at the cafe

[0380] The server then uses a generative AI model (e.g., a general-purpose generative AI model) to generate lifestyle improvement suggestions based on the generated life log. The suggestions take into account the user's emotional data and include specific advice that matches the user's psychological state. For example, a suggestion such as "Jogging three times a week is effective for maintaining health" may be generated.

[0381] User

[0382] The user can check the lifelog displayed on the device and make additions or corrections as necessary. The corrected lifelog is reformatted into JSON format and sent to the server. The server receives this information and updates the database. For example, if a user adds "That was a great run!" to the lifelog, this information is sent to the server and re-stored.

[0383] This allows users to effortlessly reflect on their daily lives and receive suggestions for lifestyle improvements that reflect their emotional state.It also helps elderly people and those with memory impairments to easily and enjoyably reflect on their actions and emotions, helping to improve the quality of their lives.

[0384] Examples of specific examples and prompts

[0385] For example, when a user goes jogging in the park at 8:00 in the morning, the device collects location information, health data (step count 5000, heart rate 70 BPM), and emotional data (comfortable), and sends them to the server in JSON format. The server analyzes this data and automatically records "8:00 Jogging in the park, comfortable" in the life log.

[0386] If the user checks this life log and adds, "That was a great run!", the server updates this information and uses AI to generate lifestyle improvement suggestions such as, "Jogging three times a week is effective for maintaining health." An example of such a prompt would be something specific like, "I want to increase the amount of exercise I do to stay healthy. What advice do you have?"

[0387] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0388] Step 1:

[0389] Data collection

[0390] Device operation: The device uses multiple sensors and software to obtain the user's location, health, purchase, search, and weather information. Specifically, the device obtains the user's current location (e.g., latitude 35.6895, longitude 139.6917) using a GPS sensor, and obtains the number of steps (e.g., 5,000 steps) and heart rate (e.g., 70 BPM) from health management software. It also obtains purchase history from the payment application and search history (e.g., weather forecast search) from the browser. It uses an emotion engine to analyze the user's facial expressions and voice tone and generate emotion data (e.g., "comfortable").

[0391] Input: User location information, health information, purchase information, search information, weather information, emotional data

[0392] Output: Formatted JSON data

[0393] Step 2:

[0394] Organizing and sending data

[0395] What the device does: It formats all the data collected by the device into JSON format. For example, it generates the following JSON object:

[0396] json

[0397] {

[0398] "userID": "12345",

[0399] "location": {"lat": 35.6895, "long": 139.6917},

[0400] "healthData": {"steps": 5000, "heartRate": 70},

[0401] "transactions": [{"time": "12:00", "item": "coffee"}],

[0402] "searchHistory": ["Weather Forecast"],

[0403] "emotion": "comfortable"

[0404] }

[0405] Input: Data obtained from various sensors and software

[0406] Output: JSON data to send to the server

[0407] Step 3:

[0408] Receiving and storing data

[0409] Server operation: The server receives the JSON format data sent from the device. It analyzes the received data and saves it in the database based on the user ID. For example, add the following record to the database:

[0410] json

[0411] {

[0412] "userID": "12345",

[0413] "location": {"lat": 35.6895, "long": 139.6917},

[0414] "healthData": {"steps": 5000, "heartRate": 70},

[0415] "transactions": [{"time": "12:00", "item": "coffee"}],

[0416] "searchHistory": ["Weather Forecast"],

[0417] "emotion": "comfortable"

[0418] }

[0419] Input: JSON data sent from the terminal

[0420] Output: User data stored in the database

[0421] Step 4:

[0422] Generating a life log

[0423] Server operation: The server automatically generates a user's life log based on the accumulated data. It aggregates the analyzed data and generates a content that describes the user's daily activity history and emotional state. For example, a life log such as "8:00 Jogging in the park, comfortable" may be generated.

[0424] Input: User data stored in the database

[0425] Output: Automatically generated lifelog

[0426] Step 5:

[0427] Checking, adding, and correcting life logs

[0428] User action: The user checks the life log displayed on the device and adds or corrects it as necessary. For example, to the entry "8:00 Jogging in the park, comfortable," the user adds "It was a great run!"

[0429] Input: Lifelog displayed on the device

[0430] Output: Added and corrected lifelog

[0431] Step 6:

[0432] Updating and re-accumulating life logs

[0433] Operation of the device and server: The added and corrected lifelog is reformatted into JSON format and sent to the server. The server receives it and updates the database.

[0434] Input: Added / modified lifelog

[0435] Output: Updated database

[0436] Step 7:

[0437] Generating lifestyle improvement proposals

[0438] Server operation: The server generates lifestyle improvement suggestions using a generative AI model based on accumulated data and the latest life log. In particular, it takes into account the user's emotional data and generates specific advice that fits the user's psychological state (e.g., "Jogging three times a week is effective for maintaining health").

[0439] Input: Updated lifelog and accumulated data

[0440] Output: Generated lifestyle improvement suggestions

[0441] Step 8:

[0442] Notification of lifestyle improvement proposals

[0443] Operation of the device and server: The generated lifestyle improvement suggestions are sent to the device, where the user can check them and apply them to their daily lives.

[0444] Input: Generated lifestyle improvement proposals

[0445] Output: Proposal posted to terminal

[0446] (Application example 2)

[0447] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0448] In modern life, users are seeking ways to reflect on and improve their lifestyles, but specific and personalized lifestyle improvement suggestions that take emotional data into account are lacking. In particular, it is difficult for users to obtain detailed suggestions about what kind of diet they should eat.

[0449] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0450] In this invention, the server includes: means for a terminal to acquire user location information, health care information, payment information, search information, and weather information from multiple sensors and applications; means for the server to receive the acquired data and accumulate data for each user; means for the server to automatically generate a life log for the user based on the accumulated data; means for the server to generate lifestyle improvement suggestions based on the user's life log; and means for the server to analyze the user's dietary content and diet-related emotional data and make individual dietary suggestions. This enables users to receive more specific and personalized dietary suggestions by making lifestyle improvements that take the emotional data into consideration.

[0451] A "terminal" is a device equipped with multiple sensors and applications that acquires user information and sends it to a server.

[0452] A "sensor" is a device that detects a user's location information, physical information, etc. and outputs it as digital data.

[0453] An "application" is a software program that runs on a terminal and obtains the user's healthcare information, payment information, search information, weather information, and the like.

[0454] "Location information" refers to data on a user's current location and movement history obtained through a GPS sensor or other means.

[0455] "Healthcare information" is data related to the user's health condition, including the number of steps taken and heart rate.

[0456] "Payment information" is data related to monetary transactions made by a user.

[0457] "Search information" is data relating to the search behavior of users on the Internet.

[0458] "Weather information" is data about the weather in the area where the user is located.

[0459] The "server" is a computer system that receives and stores data sent from the terminals, analyzes it, and generates lifestyle improvement proposals.

[0460] A "life log" is a history of a user's daily activities and behavior that is automatically generated based on data accumulated by a server.

[0461] "Lifestyle improvement suggestions" are advice for improving the user's lifestyle, generated by the server based on the user's life log and emotional data.

[0462] "Emotion data" is data generated by analyzing emotions from the user's facial expressions and voice.

[0463] "Meal details" is data related to meals taken by the user.

[0464] "Emotion data related to meals" is data that records the emotions felt by the user while eating.

[0465] "Dietary suggestions" are dietary advice provided individually by the server based on an analysis of the user's dietary content and emotional data related to the diet.

[0466] The present invention combines an emotion engine with a system that records a user's daily life and makes suggestions for improving their lifestyle based on that data. Specific embodiments of the present invention are described below.

[0467] System Overview

[0468] 1. Data collection

[0469] The device acquires the user's location, health care, payment, search, and weather information from multiple sensors and applications (e.g., GPS sensor, health care app, payment app, browser, etc.). The device's built-in emotion engine also analyzes the user's voice and facial expressions to generate emotion data. Furthermore, data on the user's diet and emotion related to the diet is also collected.

[0470] 2. Data transmission

[0471] The device collects location information, health information, payment information, search information, weather information, emotional data, meal contents, and emotional data related to meals, and compiles them into JSON format and sends them to the server along with the user ID. The server receives this information and analyzes it.

[0472] 3. Data accumulation

[0473] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[0474] 4. Generating a life log

[0475] The server analyzes the accumulated data and automatically generates a life log for the user. The life log includes the user's daily activities and behavior history, emotional state, and diet history. The generated life log is provided to the user via the device.

[0476] 5. Additions and corrections by users

[0477] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[0478] 6. Generating lifestyle improvement and dietary suggestions

[0479] The server uses AI to generate lifestyle improvement and meal suggestions based on the user's accumulated data and life log. Taking into account the user's emotional data in particular, the server generates personalized suggestions based on their emotional state. The generated suggestions are then sent to the user via their device.

[0480] Explanation of program processing

[0481] Terminal handling

[0482] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. The emotion engine analyzes the user's facial expressions and tone of voice to generate emotion data. Food content and emotion-related data are also collected, and all of this data is formatted into JSON and sent to the server.

[0483] Server Processing

[0484] The server receives JSON-formatted data sent from the device and stores it in a database for each user ID. The stored data is analyzed as appropriate, and a life log is automatically generated. The generated life log records the user's activity history as well as their emotional state and dietary history. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI (e.g., TensorFlow or PyTorch) based on the stored data and updated life log to generate lifestyle improvement suggestions and dietary suggestions, and notifies the device. The suggestions take emotional data into consideration and include advice that fits the user's psychological state.

[0485] User Action

[0486] Users can check the life log displayed on their device and review their daily activity records. They can add or edit the life log as needed to make the record more detailed and accurate. Users can refer to lifestyle improvement and dietary suggestions from the server and review their health habits and eating habits. In particular, suggestions based on emotional data provide specific advice that is tailored to the user's psychological state.

[0487] Specific examples

[0488] For example, if a user eats yogurt for breakfast at 8:00 a.m. and thinks it's "delicious," the device collects the meal details and emotional data (emotions about how delicious it is). This data is sent to a server, which analyzes it and automatically records the user's life log as "8:00 Breakfast Yogurt Delicious." Based on this information, the server generates a specific meal suggestion, such as "We recommend you eat the same yogurt for breakfast next time," and notifies the user.

[0489] Examples of prompt statements

[0490] text

[0491] Use user ID 123's food and sentiment data from the past week to generate personalized suggestions for their next meal. The user is experiencing multiple periods of high stress. The suggestions should include healthy meals appropriate for these times and ingredients that are good for reducing stress.

[0492] The above is an embodiment of the present invention.

[0493] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0494] Step 1:

[0495] The device collects user data from multiple sensors and applications.

[0496] Input: Location information from the GPS sensor, step count and heart rate from the health app, purchase history from the payment app, search information from the browser history, and user voice, facial expressions, meal contents, and meal-related emotional data from the emotion engine.

[0497] Output: A JSON-formatted dataset of location, health, payment, search, weather, sentiment, and diet data.

[0498] Specific operation: The device acquires various information from sensors and applications in real time, and generates emotion data using the emotion engine. This data is then formatted and compiled in JSON format.

[0499] Step 2:

[0500] The terminal transmits the collected data to the server.

[0501] Input: A dataset in JSON format.

[0502] Output: The data sent to the server.

[0503] Specific operation: The terminal sends an HTTP request to the server via the Internet and transfers data in JSON format.

[0504] Step 3:

[0505] The server analyzes the received data and stores it in a database.

[0506] Input: JSON formatted data sent to the server.

[0507] Output: User data stored in a database.

[0508] Specific operation: The server parses the received JSON data and stores it in a database for each user ID. The data is stored appropriately using a database management system (e.g., MySQL or PostgreSQL).

[0509] Step 4:

[0510] The server generates a life log of the user based on the accumulated data.

[0511] Input: User data stored in a database.

[0512] Output: The generated lifelog.

[0513] What it does: The server runs scripts to retrieve user data from a database, aggregate and format the data, and generate a life log, which includes detailed logs by date and activity.

[0514] Step 5:

[0515] The user checks the life log and makes additions or corrections as necessary.

[0516] Input: The generated lifelog.

[0517] Output: Lifelog modified and added by the user.

[0518] Specific operation: The user views the life log through the application on the device and makes additions or modifications as necessary. The added or modified life log is sent back to the server and updated.

[0519] Step 6:

[0520] The server generates and provides lifestyle improvement suggestions and meal suggestions based on the updated life log.

[0521] Input: Revised and added life log, emotional data, and dietary data.

[0522] Output: Generated lifestyle improvement suggestions and dietary suggestions.

[0523] Specific operation: The server uses an AI model (e.g., TensorFlow or PyTorch) to analyze the accumulated data and life logs, and generates lifestyle improvement and dietary suggestions. The suggestions are then notified to the user via their device.

[0524] Examples:

[0525] A user eats yogurt at 8:00 AM and feels it is "delicious." The device collects data along with the user's emotion. This data is sent to the server, and the life log records "8:00 Breakfast Yogurt Delicious." Based on this information, the server makes a suggestion: "We recommend eating yogurt for breakfast next time."

[0526] Examples of prompt statements

[0527] text

[0528] Use user ID 123's food and sentiment data from the past week to generate personalized suggestions for their next meal. The user is experiencing multiple periods of high stress. The suggestions should include healthy meals appropriate for these times and ingredients that are good for reducing stress.

[0529] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0530] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0531] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0532] [Second embodiment]

[0533] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0534] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0535] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0536] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0537] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0538] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0539] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0540] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0541] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0542] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0543] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0544] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0545] The present invention is a system that records the user's daily life and suggests lifestyle improvements based on the data. This system is composed of a terminal, a server, and user interactions.

[0546] Overall system overview

[0547] 1. Data collection

[0548] The device acquires the user's location information, health information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health app, payment app, browser, etc.). This data is collected periodically and formatted in JSON format.

[0549] 2. Data transmission

[0550] The device compiles the collected data into JSON format and sends it to the server along with the user's identification information (user ID). The server receives this information and analyzes it.

[0551] 3. Data accumulation

[0552] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and suggest lifestyle improvements.

[0553] 4. Generating a life log

[0554] The server analyzes the accumulated data and automatically generates a life log for the user, which is a history of the user's daily activities and behavior and is provided to the user via their device.

[0555] 5. Additions and corrections by users

[0556] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[0557] 6. Generating lifestyle improvement proposals

[0558] The server uses AI to generate lifestyle improvement suggestions based on the user's accumulated data and life log. These suggestions include health habit suggestions, exercise advice, and suggestions for improving dietary habits. The generated suggestions are notified to the user via their device.

[0559] Explanation of program processing

[0560] Terminal handling

[0561] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. All of this data is formatted into JSON and sent to the server.

[0562] Server Processing

[0563] The server receives JSON-formatted data sent from the device and accumulates the data for each user ID. The accumulated data is analyzed as appropriate, and a life log is automatically generated. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and updated life log, and notifies the device.

[0564] User Action

[0565] Users can review their life logs displayed on their devices and reflect on their lives. They can make additions or corrections as needed to make the life logs more detailed and accurate. Users can also refer to suggestions for lifestyle improvements from the server and review their health habits and improve the quality of their lives.

[0566] Specific examples

[0567] For example, if a user goes jogging in the park at 8:00 in the morning, the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and health app and sends them to the server. The server analyzes this information and automatically records it in the user's life log as "Jogging in the park at 8:00." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. Then, using AI, it generates lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining your health," and notifies the user.

[0568] This system allows users to effortlessly reflect on their daily lives and obtain hints for improving their lifestyle habits. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably reflect on their own behavior and helps improve the quality of their lives.

[0569] The processing flow will be explained below.

[0570] Step 1:

[0571] The device uses a GPS sensor to obtain the user's current location. It also collects health information such as the number of steps taken and heart rate from a health app, purchase history and amount spent information from a payment app, and obtains the user's search information from the browser's search history, as well as current weather information from a weather app or API.

[0572] Step 2:

[0573] The device formats the location, health, payment, search, and weather information into a single JSON object, including the user ID, ready to be sent to the server later.

[0574] Step 3:

[0575] The device creates a POST request to send a JSON object to the server and sends it to the specified server URL. If the transmission is successful, the device notifies the user of this information.

[0576] Step 4:

[0577] The server receives the POST request sent from the device. The received data is analyzed and stored in a database for each user ID. The stored data will be used to generate future life logs and propose lifestyle improvements.

[0578] Step 5:

[0579] The server periodically generates a user's life log based on the accumulated data. The life log includes a history of the user's daily activities and behavior. The generated life log is then sent to the device.

[0580] Step 6:

[0581] The user checks the life log displayed on the device. The life log displays a detailed record of the user's daily activities. The user can add or edit the life log as needed.

[0582] Step 7:

[0583] After the user adds or modifies the lifelog, the device sends the information back to the server as a JSON object. The server receives the modified lifelog and updates the database.

[0584] Step 8:

[0585] The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and the revised life log. The generated suggestions include specific health habits and lifestyle advice.

[0586] Step 9:

[0587] The server formats the generated lifestyle improvement proposals in JSON format and sends them to the device, which receives them and notifies the user.

[0588] Step 10:

[0589] Users can check the lifestyle improvement suggestions displayed on their devices and take actions to improve the quality of their daily lives. Users can refer to the suggestions and review their health and lifestyle habits.

[0590] These are the specific processing steps of the program, which allow the user to reflect on their daily life and receive specific suggestions for improving the quality of their life.

[0591] Example 1

[0592] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0593] Conventional systems that record daily life and suggest lifestyle improvements often require time-consuming data collection, storage, and analysis, or are insufficient. Furthermore, users often have to spend time checking and editing their own life logs, which results in poor accuracy in lifestyle improvement suggestions. This makes the introduction and use of such systems particularly difficult for elderly users and those with memory impairments.

[0594] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0595] In this invention, the server

[0596] A means for the terminal to acquire user location information, health status information, transaction information, search history, and weather information from a plurality of sensors and software;

[0597] a server receiving the acquired data and storing the data for each user;

[0598] A means for the server to automatically generate a life record of the user based on the accumulated data;

[0599] A server generates lifestyle improvement suggestions based on the user's lifestyle records;

[0600] A means for the terminal to format the acquired data into a JSON format and transmit the formatted data to a server;

[0601] A means for a server to analyze the JSON format data and generate a life record of the user;

[0602] A means for the server to analyze the accumulated data and life records using AI and generate improvement suggestions;

[0603] This includes:

[0604] Users can effortlessly record their daily lives, easily add to and edit their life logs, and even receive highly accurate lifestyle improvement suggestions based on the accumulated data.

[0605] A "terminal" is an information processing device equipped with multiple sensors and software for collecting data on the user's daily life.

[0606] A "sensor" is a device that measures physical environmental information, and in this system includes GPS sensors, health status sensors, weather sensors, etc.

[0607] "Software" refers to a program that is installed on a device and performs a specific function, such as a healthcare app, a payment app, or a browser.

[0608] "Location Information" means data that indicates a user's geographic location and is collected by a GPS sensor.

[0609] "Health status information" is data related to the user's health, and includes information such as the number of steps taken, heart rate, and calorie consumption.

[0610] "Transaction information" is data related to a user's purchasing activities, including purchase history obtained from a payment app.

[0611] "Search history" is the history of searches a user has performed on the Internet, and is data obtained from a browser.

[0612] "Weather information" refers to data related to the weather, obtained from weather apps and weather sensors.

[0613] A "life log" is data that records the history of a user's daily activities and behavior, and is automatically generated by a server.

[0614] "Lifestyle improvement suggestions" are suggestions for improving the quality of life that are generated based on the user's life log and accumulated data.

[0615] The "JSON format" is a format used to structurally represent data and communicate between servers and terminals.

[0616] "AI" refers to artificial intelligence, a technology that analyzes accumulated data and generates lifestyle improvement suggestions.

[0617] This invention relates to a system that records a user's daily life and makes suggestions for improving their lifestyle based on the data. This system is composed of a terminal, a server, and user interactions.

[0618] System configuration

[0619] 1. Terminal configuration and operation

[0620] The device collects various data about the user using multiple built-in sensors (e.g., GPS sensor, health condition sensor) and installed software (e.g., healthcare app, payment app, browser). Specifically, the device collects the following data:

[0621] Location information using a GPS sensor

[0622] Health status information such as steps taken, heart rate, and calorie consumption via the Health app

[0623] Transaction information (purchase history) from payment apps

[0624] Browser search history

[0625] Weather information from weather apps and weather sensors

[0626] This collected data is obtained at regular intervals and formatted into JSON format.

[0627] 2. Data transmission

[0628] The device periodically converts the collected data into JSON format and sends it to the server along with the user ID. This transmission is performed every 15 minutes, and the HTTPS protocol is used to maintain data integrity.

[0629] 3. Server Configuration and Operation

[0630] The server receives and analyzes the JSON format data sent from the device. The received data is stored in a database for each user ID, and each record also includes a timestamp for the data.

[0631] The server periodically analyzes the accumulated data and automatically generates a record of the user's daily life (life log). The life log records the user's daily activities and behavior. The server then uses AI to generate lifestyle improvement suggestions based on the accumulated data and the latest life log, and notifies the device.

[0632] 4. User Operation

[0633] Users can check the lifelog displayed on their device and reflect on their daily lives. They can add or edit the lifelog as needed, which improves its accuracy. Data added or edited by the user is sent back to the server, and the lifelog is updated.

[0634] Specific examples

[0635] For example, if a user goes jogging in the park at 8:00 a.m., the device obtains location information from the GPS sensor and jogging data (distance, time, heart rate) from the health app, then compiles this into a JSON file and sends it to the server. The server analyzes the received data and automatically records "Jogging in the park at 8:00" in the user's life log. If the user checks this life log and adds "That was a great run!", this information is also sent to the server and the life log is updated. The server then uses AI to generate lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and notifies the user via the device.

[0636] Prompt Sentence Examples

[0637] "If the user has the habit of jogging every morning, explain how jogging three times a week can help them stay healthy."

[0638] In this way, users can effortlessly review their daily lives, receive highly accurate suggestions for lifestyle improvements, and improve their quality of life. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably review their own actions, helping to improve their quality of life.

[0639] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0640] Step 1: Collect data

[0641] Terminal handling

[0642] The device collects user data using various sensors and software: location information from the GPS sensor, step count and heart rate from health apps, purchase history from payment apps, search history from the browser, and weather information from weather apps.

[0643] Input: Data obtained from GPS sensor, health app, payment app, browser, and weather app

[0644] Data processing: Acquire raw data from each sensor and app and format it into JSON format.

[0645] Output: JSON format data

[0646] How it works: Every 15 minutes, the device retrieves new data from each sensor and app, consolidates it, and generates a JSON file.

[0647] Step 2: Sending data

[0648] Terminal handling

[0649] The data collected by the device is formatted in JSON and sent to the server along with the user ID.

[0650] Input: Formatted JSON data and user ID

[0651] Data processing: Encoding to maintain data integrity

[0652] Output: HTTPS request to the server

[0653] Specific operation: Every 15 minutes, the device makes an HTTPS request to the server and sends data in JSON format along with the user ID.

[0654] Step 3: Accumulate data

[0655] Server Processing

[0656] The server analyzes the received JSON format data and stores it in a database for each user ID.

[0657] Input: JSON format data sent from the terminal

[0658] Data processing: Parse the JSON data, extract each data item, and store it in the database.

[0659] Output: Data stored in the database

[0660] Specific operation: The server first stores the received data in temporary memory and then writes it to the database sequentially.

[0661] Step 4: Generating a Lifelog

[0662] Server Processing

[0663] The server periodically analyzes the accumulated data and automatically generates a life log for the user.

[0664] Input: Data stored for each user

[0665] Data processing: Perform time series analysis of the data and compile it into a history of the user's daily behavior.

[0666] Output: Life log

[0667] Specific operation: The server runs a job every day at midnight, analyzes data from the past 24 hours, generates a "life log," and stores it in a database.

[0668] Step 5: User additions and modifications

[0669] User Action

[0670] Users can check their lifelog and add or edit it as needed.

[0671] Input: Lifelog displayed on the device

[0672] Data processing: Form input processing to support user additions and corrections

[0673] Output: Modified lifelog

[0674] Specific operation: When a user opens the app on their device, displays their life log, and adds "I ate bread for breakfast," the information is sent to the server in JSON format and the life log database is updated.

[0675] Step 6: Generate life improvement proposals

[0676] Server Processing

[0677] The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and life logs, and these suggestions are sent to the user via their device.

[0678] Input: User's accumulated data and life log

[0679] Data processing: Generate lifestyle improvement suggestions through analysis and pattern recognition using AI models

[0680] Output: Lifestyle improvement suggestions

[0681] Specific operation: The server runs the AI ​​model at 1 a.m. every day, analyzes the data, generates suggestions such as "It is recommended to jog three times a week," and notifies the user via the device.

[0682] (Application example 1)

[0683] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0684] In modern society, users are expected to improve their daily lifestyle habits and maintain their health. However, manually recording and analyzing their daily life data to find improvement measures is a very time-consuming process. For this reason, there is a need for a system that automatically collects, stores, and analyzes users' daily life data to provide lifestyle improvement suggestions. Furthermore, to improve the accuracy of lifestyle improvement suggestions, it is necessary to use generative AI models to perform more advanced analysis based on diverse data.

[0685] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0686] In this invention, the server includes: means for the terminal to acquire user location information, healthcare information, payment information, search information, and weather information from multiple sensors and applications; means for the server to receive the acquired data and accumulate the data for each user; means for the server to automatically generate a user's life log based on the accumulated data; means for the server to generate lifestyle improvement suggestions based on the user's life log; and means for generating prompt sentences and requesting analysis by a generative AI model to improve the accuracy of the lifestyle improvement suggestions. This allows users to easily collect and accumulate data about their daily lives and perform advanced analysis using AI, enabling them to receive highly accurate lifestyle improvement suggestions.

[0687] A "terminal" is an electronic device used to collect data from a user's daily life, and is equipped with multiple sensors and applications.

[0688] A "sensor" is a device that detects a physical phenomenon (e.g., position, movement, temperature, etc.) and converts it into digital data.

[0689] An "application" is a software program that runs on a terminal to provide a specific function or service.

[0690] "Location Information" means geographic location data of a user obtained using a GPS sensor.

[0691] "Healthcare information" refers to data related to health status and physical activity, including, for example, the number of steps taken and heart rate.

[0692] "Payment information" is data related to the purchase and payment history of a user.

[0693] "Search Information" is data about search queries performed by users on the Internet and their history.

[0694] "Weather information" is data about the weather conditions at the user's location.

[0695] A "server" is a computer system that receives, stores, and analyzes data sent from a terminal.

[0696] "Data storage" is the process of organizing collected data and storing it for later analysis and reuse.

[0697] A "life log" is digital data that records the history of a user's daily actions and activities.

[0698] "Lifestyle improvement suggestions" are specific advice and recommendations for improving lifestyle habits based on the user's life log.

[0699] A "prompt" is an instruction entered into a generative AI model to make it perform a specific task.

[0700] A "generative AI model" is an artificial intelligence algorithm used to analyze data using machine learning to generate insights and recommendations.

[0701] The present invention is a system that records the user's daily life and suggests lifestyle improvements based on the data. This system is composed of a terminal, a server, and user interactions.

[0702] 1. Data collection

[0703] The device acquires the user's location information, health information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health app, payment app, browser, etc.). The collected data is periodically formatted into JSON format.

[0704] 2. Data transmission

[0705] The data collected by the device is compiled in JSON format and sent to the server along with the user's identification information (user ID). The server receives and analyzes this data.

[0706] 3. Data accumulation

[0707] The server stores the received data in a database for each user ID. The stored data will be used to generate a life log and suggest lifestyle improvements.

[0708] 4. Generating a life log

[0709] The server analyzes the accumulated data and automatically generates a life log for the user, which records the user's daily activities and behavioral history and is provided to the user via their device.

[0710] 5. Additions and corrections by users

[0711] The user can check the lifelog displayed on the device and add or modify it as needed. The added or modified lifelog is then sent back to the server and updated.

[0712] 6. Generating lifestyle improvement proposals

[0713] The server uses a generative AI model to generate lifestyle improvement suggestions based on the user's accumulated data and life log. These suggestions include health habit suggestions, exercise advice, and suggestions for improving dietary habits. The generated suggestions are notified to the user via their device.

[0714] 7. Improved accuracy with generative AI models

[0715] The server then generates a prompt and requests the generative AI model to analyze it. This prompt includes the user's life log and collected data. The generative AI model provides analysis results that improve the accuracy of lifestyle improvement suggestions.

[0716] Hardware / Software used

[0717] Hardware: Smartphone

[0718] Software: Python, HTTP API (communication with server), generative AI model

[0719] Data processing / calculation: Data collection, formatting into JSON format, advanced analysis using AI

[0720] Specific examples

[0721] For example, if a user goes jogging in the morning, the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and healthcare app and sends them to the server. The server analyzes this information and automatically records it in the user's life log as "Jogging in the park at 8:00." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. The generative AI model is then used to generate lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and notifies the user.

[0722] Prompt Sentence Examples

[0723] "Analyze the following data to generate suggestions to improve the user's life:

[0724] GPS data: 35.6895, 139.6917, "jogging"

[0725] Health data: Steps: 3000, Heart rate: 120

[0726] Payment Data: Purchase: None

[0727] Search data: None

[0728] Weather data: Sunny, Temperature: 15

[0729] Please offer some advice on how to improve your life."

[0730] This system allows users to effortlessly reflect on their daily lives and receive specific advice on how to improve their lifestyle habits.

[0731] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0732] Step 1:

[0733] The device collects the user's location, health, payment, search, and weather information from multiple sensors and applications. Data obtained from sensors and applications includes location information from the GPS sensor, step count and heart rate records from the health app, purchase history from the payment app, browser search history, and weather information from the weather app. This data is temporarily stored on the device.

[0734] input:

[0735] Data from multiple sensors and applications

[0736] output:

[0737] Temporarily stored data on the device

[0738] Step 2:

[0739] The data collected by the device is periodically formatted into JSON format. The collected location information, health information, payment information, search information, weather information, etc. are compiled into a single JSON object, along with the user ID.

[0740] input:

[0741] Temporarily saved data

[0742] output:

[0743] Integration data in JSON format

[0744] Step 3:

[0745] The device sends formatted JSON data to the server using an HTTP POST request to send the data to the server's API endpoint. The server receives this request and prepares to parse the data.

[0746] input:

[0747] Integration data in JSON format

[0748] output:

[0749] Data sent to the server

[0750] Step 4:

[0751] The server receives the data sent from the device and stores it in a database for each user, allowing data associated with each user to be permanently stored and used for later analysis.

[0752] input:

[0753] Data sent to the server

[0754] output:

[0755] Accumulated data in the database

[0756] Step 5:

[0757] The server analyzes the accumulated data and automatically generates a life log for the user. It compares past data with newly added data to generate a life log that summarizes the user's daily activities and health status in chronological order. The generated life log is then saved back into the database.

[0758] input:

[0759] Accumulated data in the database

[0760] output:

[0761] Automatically generated lifelog

[0762] Step 6:

[0763] The server sends the generated lifelog to the device and provides it to the user. The user can check their own lifelog on the device and add or modify it as necessary.

[0764] input:

[0765] Automatically generated lifelog

[0766] output:

[0767] Life log presentation data

[0768] Step 7:

[0769] After the user adds or modifies the lifelog, the device sends the modified lifelog back to the server, which then updates the database with the modified lifelog.

[0770] input:

[0771] Modified Lifelog

[0772] output:

[0773] Updated database

[0774] Step 8:

[0775] The server generates lifestyle improvement proposals using a generative AI model based on the updated life log and accumulated data. The server generates prompt statements and requests the generative AI model to analyze them. Based on the analysis results of the generative AI model, highly accurate lifestyle improvement proposals are created.

[0776] input:

[0777] Updated lifelog and accumulated data

[0778] output:

[0779] Generated lifestyle improvement proposals

[0780] Step 9:

[0781] The server sends the generated lifestyle improvement suggestions to the terminal, and the user receives the lifestyle improvement suggestions via the terminal and makes lifestyle improvements based on them.

[0782] input:

[0783] Generated lifestyle improvement proposals

[0784] output:

[0785] User notification data

[0786] Prompt Sentence Examples

[0787] "Analyze the following data to generate suggestions to improve the user's life:

[0788] GPS data: 35.6895, 139.6917, "jogging"

[0789] Health data: Steps: 3000, Heart rate: 120

[0790] Payment Data: Purchase: None

[0791] Search data: None

[0792] Weather data: Sunny, Temperature: 15

[0793] Please offer some advice on how to improve your life."

[0794] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0795] This invention combines an emotion engine with a system that records a user's daily life and makes suggestions for lifestyle improvements based on that data. This system is composed of a terminal, a server, and an engine that handles user interaction and emotion recognition.

[0796] Overall system overview

[0797] 1. Data collection

[0798] The device acquires the user's location information, health care information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health care app, payment app, browser, etc.). In addition, the device's built-in emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[0799] 2. Data transmission

[0800] The device collects location information, health information, payment information, search information, weather information, and emotion data, and then compiles them into JSON format and sends them along with the user ID to the server. The server receives this information and analyzes it.

[0801] 3. Data accumulation

[0802] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[0803] 4. Generating a life log

[0804] The server analyzes the accumulated data and automatically generates a life log for the user, which includes the user's daily activities, behavioral history, and emotional state. The generated life log is provided to the user via their device.

[0805] 5. Additions and corrections by users

[0806] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[0807] 6. Generating lifestyle improvement proposals

[0808] The server uses AI to generate lifestyle improvement suggestions based on the user's accumulated data and life log. Taking into account the user's emotional data in particular, the server generates personalized suggestions based on their emotional state. The generated suggestions are then sent to the user via their device.

[0809] Explanation of program processing

[0810] Terminal handling

[0811] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. Furthermore, an emotion engine analyzes the user's facial expressions and voice tone to generate emotion data. All of this data is formatted in JSON format and sent to the server.

[0812] Server Processing

[0813] The server receives JSON-formatted data sent from the device and stores it in a database for each user ID. The stored data is analyzed as appropriate, and a life log is automatically generated. The generated life log records the user's emotional state along with their activity history. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI to generate lifestyle improvement suggestions based on the stored data and updated life log, and notifies the device. The suggestions take emotional data into consideration and include advice that fits the user's psychological state.

[0814] User Action

[0815] Users can check the life log displayed on their device and review their daily activity records. They can add or edit the life log as needed to make the record more detailed and accurate. Users can refer to the lifestyle improvement suggestions from the server and review their health and lifestyle habits. In particular, suggestions based on emotional data provide specific advice that is tailored to the user's psychological state.

[0816] Specific examples

[0817] For example, if a user goes jogging in the park at 8:00 a.m., the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and health app, and then uses the emotion engine to recognize the user's emotion of "comfortable" from their facial expressions and voice. This data is sent to the server, which analyzes it and automatically records it in the user's life log as "8:00 Jogging in the park, comfortable." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. Then, using AI, the device generates lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and provides specific exercise advice based on the user's comfortable jogging experience.

[0818] This system allows users to effortlessly reflect on their daily lives and receive suggestions for lifestyle improvements that reflect their emotional state. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably reflect on their own actions and emotions, helping to improve the quality of their lives.

[0819] The processing flow will be explained below.

[0820] Step 1:

[0821] The device uses the GPS sensor to obtain the user's current location, collects health information such as the number of steps taken and heart rate from the health app, and obtains purchase history and payment amount information from the payment app.

[0822] Step 2:

[0823] The device retrieves the user's search keywords and visited websites from the browser's search history, and also retrieves the current day's weather information from weather apps and APIs.

[0824] Step 3:

[0825] The device's emotion engine captures the user's facial expressions with a camera and records their voice with a microphone, and analyzes them to generate emotion data (e.g., happiness, anger, sadness, etc.).

[0826] Step 4:

[0827] The device formats the collected location, health, payment, search, weather, and emotion data into a single JSON object, which also includes the user ID.

[0828] Step 5:

[0829] The device creates a POST request to send the formatted JSON object to the server, sends it to the specified server URL, and notifies the user of the status if the transmission is successful.

[0830] Step 6:

[0831] The server receives the POST request sent from the device and analyzes the data. The received data is stored in a database for each user ID. This stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[0832] Step 7:

[0833] The server periodically generates a user's life log based on the accumulated data. The life log includes the user's daily activities, behavioral history, and emotional state. The generated life log is formatted in JSON format and sent to the device.

[0834] Step 8:

[0835] The user checks the life log displayed on the device. The life log displays a detailed account of the user's daily activities, behaviors, and emotional state. The user can add or edit the life log as needed.

[0836] Step 9:

[0837] The device reformats the lifelog that the user has added or modified into JSON format and sends it to the server. The server receives the modified lifelog and updates the database.

[0838] Step 10:

[0839] The server generates lifestyle improvement suggestions based on the accumulated data and the revised life log, using AI to take into account the user's emotional data and generate specific suggestions based on their emotions.

[0840] Step 11:

[0841] The server formats the generated lifestyle improvement proposals in JSON format and sends them to the device, which receives them and notifies the user.

[0842] Step 12:

[0843] Users can check the lifestyle improvement suggestions displayed on the device and improve their daily habits and behaviors based on them. For example, they receive specific advice such as how to maintain health by continuing to jog or how to reduce stress.

[0844] As a concrete example, consider the case where a user goes jogging in the park at 8:00 in the morning. The device obtains location information and jogging-related data (distance, time, heart rate) from the GPS sensor and health care app, and the emotion engine recognizes the emotion of "comfortable" from the user's facial expressions and voice. This data is sent to the server, analyzed, and automatically recorded in the life log as "8:00 Jogging in the park, comfortable." If the user checks this life log and adds "I had a great run!", the server updates and stores this information. Then, using AI, it generates lifestyle improvement suggestions such as "Jogging three times a week is effective for maintaining health" and provides specific exercise advice.

[0845] The above is a specific embodiment of the present invention. This system allows users to easily record their actions and emotions and receive specific suggestions for improving their quality of life. In particular, by using an emotion engine, it is possible to provide advice that fits the user's psychological state.

[0846] Example 2

[0847] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0848] Conventional lifelog systems have the problem of not being able to fully reflect a user's daily activities and emotional state. Furthermore, their lifestyle improvement suggestions do not take into account the user's emotional state, resulting in low user satisfaction and implementation rates. Furthermore, the process of collecting and analyzing data is cumbersome, often causing users to feel overwhelmed.

[0849] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0850] In this invention, the server includes: a terminal that acquires a user's location information, health information, purchase information, search information, and weather information from multiple sensors and software; a terminal that analyzes a user's facial expressions and voice tone and generates emotion data; a terminal that formats the acquired data into JSON format and transmits it to the server; a server that receives the acquired data and accumulates the data for each user; a server that automatically generates a user's life log based on the accumulated data; and a server that generates lifestyle improvement suggestions using a generative AI model based on the user's life log. This makes it possible to collect and analyze a user's comprehensive activity and emotion data and provide lifestyle improvement suggestions based on the user's individual emotional state.

[0851] A "terminal" is an electronic device equipped with multiple sensors and software for collecting a user's location information, health information, purchase information, search information, weather information, and emotional data.

[0852] A "server" is a computer system that receives, stores, and analyzes data sent from a terminal.

[0853] A "sensor" is an electronic device that collects environmental or biometric information, such as a user's location or physiological data.

[0854] "Software" refers to application programs installed on the terminal that collect and format data.

[0855] "User location information" is data about the user's current location obtained using a GPS sensor.

[0856] "Health information" is data indicating the physiological state of the user, such as the number of steps taken and heart rate.

[0857] "Purchase information" is data related to the purchase history and transactions made by the user.

[0858] "Search information" refers to data related to the keywords and history of searches a user has performed on the Internet.

[0859] "Weather information" refers to weather forecasts and temperature information obtained based on the user's location.

[0860] "Emotion data" is data that indicates an emotional state generated by the terminal's emotion engine by analyzing the user's facial expressions and vocal tone.

[0861] The "JSON format" is a lightweight, text-based data exchange format for structuring and representing data.

[0862] A "user ID" is an identification code assigned to each user to uniquely identify them.

[0863] A "life log" is data that records a user's daily activity history and emotional state.

[0864] A "generative AI model" is an artificial intelligence algorithm that generates lifestyle improvement suggestions based on collected data.

[0865] "Lifestyle Improvement Suggestions" provides advice to improve the user's lifestyle habits based on the user's life log and emotional data.

[0866] The present invention is a system for providing suggestions to improve a user's life. This system records the user's daily life and makes suggestions to improve their life based on that data. The system is mainly composed of a terminal, a server, and an engine that handles user interaction and emotion recognition.

[0867] Specific configuration

[0868] Terminal

[0869] The device collects data using various sensors and applications, including GPS sensors, health management software, payment applications, web browsers, and emotion engines. For example, consider a device that implements the following measures:

[0870] Location information: Uses a GPS sensor to obtain real-time user location information.

[0871] Health information: We collect health data such as your steps and heart rate from health management software (e.g., Apple Health, Google Fit).

[0872] Purchase information: Obtain purchase history from a payment application (e.g., a general-purpose payment system).

[0873] Search information: Obtain search history from web browsers (e.g., general-purpose browsers).

[0874] Emotion data: The emotion engine analyzes the user's facial expressions and vocal tone to generate emotion data.

[0875] All collected data is formatted in JSON and sent to the server.

[0876] server

[0877] The server receives the JSON format data sent from the device and accumulates the data for each user. Specifically, the data is saved for each user ID using a database (e.g., a general-purpose database management system). The accumulated data is analyzed, and the user's life log is automatically generated.

[0878] The generated life log includes the user's emotional state along with their activity history. For example, the following life log may be generated:

[0879] 8:00 Jogging in the park, comfortable

[0880] 12:00 Buy coffee at the cafe

[0881] The server then uses a generative AI model (e.g., a general-purpose generative AI model) to generate lifestyle improvement suggestions based on the generated life log. The suggestions take into account the user's emotional data and include specific advice that matches the user's psychological state. For example, a suggestion such as "Jogging three times a week is effective for maintaining health" may be generated.

[0882] User

[0883] The user can check the lifelog displayed on the device and make additions or corrections as necessary. The corrected lifelog is reformatted into JSON format and sent to the server. The server receives this information and updates the database. For example, if a user adds "That was a great run!" to the lifelog, this information is sent to the server and re-stored.

[0884] This allows users to effortlessly reflect on their daily lives and receive suggestions for lifestyle improvements that reflect their emotional state.It also helps elderly people and those with memory impairments to easily and enjoyably reflect on their actions and emotions, helping to improve the quality of their lives.

[0885] Examples of specific examples and prompts

[0886] For example, when a user goes jogging in the park at 8:00 in the morning, the device collects location information, health data (step count 5000, heart rate 70 BPM), and emotional data (comfortable), and sends them to the server in JSON format. The server analyzes this data and automatically records "8:00 Jogging in the park, comfortable" in the life log.

[0887] If the user checks this life log and adds, "That was a great run!", the server updates this information and uses AI to generate lifestyle improvement suggestions such as, "Jogging three times a week is effective for maintaining health." An example of such a prompt would be something specific like, "I want to increase the amount of exercise I do to stay healthy. What advice do you have?"

[0888] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0889] Step 1:

[0890] Data collection

[0891] Device operation: The device uses multiple sensors and software to obtain the user's location, health, purchase, search, and weather information. Specifically, the device obtains the user's current location (e.g., latitude 35.6895, longitude 139.6917) using a GPS sensor, and obtains the number of steps (e.g., 5,000 steps) and heart rate (e.g., 70 BPM) from health management software. It also obtains purchase history from the payment application and search history (e.g., weather forecast search) from the browser. It uses an emotion engine to analyze the user's facial expressions and voice tone and generate emotion data (e.g., "comfortable").

[0892] Input: User location information, health information, purchase information, search information, weather information, emotional data

[0893] Output: Formatted JSON data

[0894] Step 2:

[0895] Organizing and sending data

[0896] What the device does: It formats all the data collected by the device into JSON format. For example, it generates the following JSON object:

[0897] json

[0898] {

[0899] "userID": "12345",

[0900] "location": {"lat": 35.6895, "long": 139.6917},

[0901] "healthData": {"steps": 5000, "heartRate": 70},

[0902] "transactions": [{"time": "12:00", "item": "coffee"}],

[0903] "searchHistory": ["Weather Forecast"],

[0904] "emotion": "comfortable"

[0905] }

[0906] Input: Data obtained from various sensors and software

[0907] Output: JSON data to send to the server

[0908] Step 3:

[0909] Receiving and storing data

[0910] Server operation: The server receives the JSON format data sent from the device. It analyzes the received data and saves it in the database based on the user ID. For example, add the following record to the database:

[0911] json

[0912] {

[0913] "userID": "12345",

[0914] "location": {"lat": 35.6895, "long": 139.6917},

[0915] "healthData": {"steps": 5000, "heartRate": 70},

[0916] "transactions": [{"time": "12:00", "item": "coffee"}],

[0917] "searchHistory": ["Weather Forecast"],

[0918] "emotion": "comfortable"

[0919] }

[0920] Input: JSON data sent from the terminal

[0921] Output: User data stored in the database

[0922] Step 4:

[0923] Generating a life log

[0924] Server operation: The server automatically generates a user's life log based on the accumulated data. It aggregates the analyzed data and generates a content that describes the user's daily activity history and emotional state. For example, a life log such as "8:00 Jogging in the park, comfortable" may be generated.

[0925] Input: User data stored in the database

[0926] Output: Automatically generated lifelog

[0927] Step 5:

[0928] Checking, adding, and correcting life logs

[0929] User action: The user checks the life log displayed on the device and adds or corrects it as necessary. For example, to the entry "8:00 Jogging in the park, comfortable," the user adds "It was a great run!"

[0930] Input: Lifelog displayed on the device

[0931] Output: Added and corrected lifelog

[0932] Step 6:

[0933] Updating and re-accumulating life logs

[0934] Operation of the device and server: The added and corrected lifelog is reformatted into JSON format and sent to the server. The server receives it and updates the database.

[0935] Input: Added / modified lifelog

[0936] Output: Updated database

[0937] Step 7:

[0938] Generating lifestyle improvement proposals

[0939] Server operation: The server generates lifestyle improvement suggestions using a generative AI model based on accumulated data and the latest life log. In particular, it takes into account the user's emotional data and generates specific advice that fits the user's psychological state (e.g., "Jogging three times a week is effective for maintaining health").

[0940] Input: Updated lifelog and accumulated data

[0941] Output: Generated lifestyle improvement suggestions

[0942] Step 8:

[0943] Notification of lifestyle improvement proposals

[0944] Operation of the device and server: The generated lifestyle improvement suggestions are sent to the device, where the user can check them and apply them to their daily lives.

[0945] Input: Generated lifestyle improvement proposals

[0946] Output: Proposal posted to terminal

[0947] (Application example 2)

[0948] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0949] In modern life, users are seeking ways to reflect on and improve their lifestyles, but specific and personalized lifestyle improvement suggestions that take emotional data into account are lacking. In particular, it is difficult for users to obtain detailed suggestions about what kind of diet they should eat.

[0950] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0951] In this invention, the server includes: means for a terminal to acquire user location information, health care information, payment information, search information, and weather information from multiple sensors and applications; means for the server to receive the acquired data and accumulate data for each user; means for the server to automatically generate a life log for the user based on the accumulated data; means for the server to generate lifestyle improvement suggestions based on the user's life log; and means for the server to analyze the user's dietary content and diet-related emotional data and make individual dietary suggestions. This enables users to receive more specific and personalized dietary suggestions by making lifestyle improvements that take the emotional data into consideration.

[0952] A "terminal" is a device equipped with multiple sensors and applications that acquires user information and sends it to a server.

[0953] A "sensor" is a device that detects a user's location information, physical information, etc. and outputs it as digital data.

[0954] An "application" is a software program that runs on a terminal and obtains the user's healthcare information, payment information, search information, weather information, and the like.

[0955] "Location information" refers to data on a user's current location and movement history obtained through a GPS sensor or other means.

[0956] "Healthcare information" is data related to the user's health condition, including the number of steps taken and heart rate.

[0957] "Payment information" is data related to monetary transactions made by a user.

[0958] "Search information" is data relating to the search behavior of users on the Internet.

[0959] "Weather information" is data about the weather in the area where the user is located.

[0960] The "server" is a computer system that receives and stores data sent from the terminals, analyzes it, and generates lifestyle improvement proposals.

[0961] A "life log" is a history of a user's daily activities and behavior that is automatically generated based on data accumulated by a server.

[0962] "Lifestyle improvement suggestions" are advice for improving the user's lifestyle, generated by the server based on the user's life log and emotional data.

[0963] "Emotion data" is data generated by analyzing emotions from the user's facial expressions and voice.

[0964] "Meal details" is data related to meals taken by the user.

[0965] "Emotion data related to meals" is data that records the emotions felt by the user while eating.

[0966] "Dietary suggestions" are dietary advice provided individually by the server based on an analysis of the user's dietary content and emotional data related to the diet.

[0967] The present invention combines an emotion engine with a system that records a user's daily life and makes suggestions for improving their lifestyle based on that data. Specific embodiments of the present invention are described below.

[0968] System Overview

[0969] 1. Data collection

[0970] The device acquires the user's location, health care, payment, search, and weather information from multiple sensors and applications (e.g., GPS sensor, health care app, payment app, browser, etc.). The device's built-in emotion engine also analyzes the user's voice and facial expressions to generate emotion data. Furthermore, data on the user's diet and emotion related to the diet is also collected.

[0971] 2. Data transmission

[0972] The device collects location information, health information, payment information, search information, weather information, emotional data, meal contents, and emotional data related to meals, and compiles them into JSON format and sends them to the server along with the user ID. The server receives this information and analyzes it.

[0973] 3. Data accumulation

[0974] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[0975] 4. Generating a life log

[0976] The server analyzes the accumulated data and automatically generates a life log for the user. The life log includes the user's daily activities and behavior history, emotional state, and diet history. The generated life log is provided to the user via the device.

[0977] 5. Additions and corrections by users

[0978] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[0979] 6. Generating lifestyle improvement and dietary suggestions

[0980] The server uses AI to generate lifestyle improvement and meal suggestions based on the user's accumulated data and life log. Taking into account the user's emotional data in particular, the server generates personalized suggestions based on their emotional state. The generated suggestions are then sent to the user via their device.

[0981] Explanation of program processing

[0982] Terminal handling

[0983] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. The emotion engine analyzes the user's facial expressions and tone of voice to generate emotion data. Food content and emotion-related data are also collected, and all of this data is formatted into JSON and sent to the server.

[0984] Server Processing

[0985] The server receives JSON-formatted data sent from the device and stores it in a database for each user ID. The stored data is analyzed as appropriate, and a life log is automatically generated. The generated life log records the user's activity history as well as their emotional state and dietary history. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI (e.g., TensorFlow or PyTorch) based on the stored data and updated life log to generate lifestyle improvement suggestions and dietary suggestions, and notifies the device. The suggestions take emotional data into consideration and include advice that fits the user's psychological state.

[0986] User Action

[0987] Users can check the life log displayed on their device and review their daily activity records. They can add or edit the life log as needed to make the record more detailed and accurate. Users can refer to lifestyle improvement and dietary suggestions from the server and review their health habits and eating habits. In particular, suggestions based on emotional data provide specific advice that is tailored to the user's psychological state.

[0988] Specific examples

[0989] For example, if a user eats yogurt for breakfast at 8:00 a.m. and thinks it's "delicious," the device collects the meal details and emotional data (emotions about how delicious it is). This data is sent to a server, which analyzes it and automatically records the user's life log as "8:00 Breakfast Yogurt Delicious." Based on this information, the server generates a specific meal suggestion, such as "We recommend you eat the same yogurt for breakfast next time," and notifies the user.

[0990] Examples of prompt statements

[0991] text

[0992] Use user ID 123's food and sentiment data from the past week to generate personalized suggestions for their next meal. The user is experiencing multiple periods of high stress. The suggestions should include healthy meals appropriate for these times and ingredients that are good for reducing stress.

[0993] The above is an embodiment of the present invention.

[0994] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0995] Step 1:

[0996] The device collects user data from multiple sensors and applications.

[0997] Input: Location information from the GPS sensor, step count and heart rate from the health app, purchase history from the payment app, search information from the browser history, and user voice, facial expressions, meal contents, and meal-related emotional data from the emotion engine.

[0998] Output: A JSON-formatted dataset of location, health, payment, search, weather, sentiment, and diet data.

[0999] Specific operation: The device acquires various information from sensors and applications in real time, and generates emotion data using the emotion engine. This data is then formatted and compiled in JSON format.

[1000] Step 2:

[1001] The terminal transmits the collected data to the server.

[1002] Input: A dataset in JSON format.

[1003] Output: The data sent to the server.

[1004] Specific operation: The terminal sends an HTTP request to the server via the Internet and transfers data in JSON format.

[1005] Step 3:

[1006] The server analyzes the received data and stores it in a database.

[1007] Input: JSON formatted data sent to the server.

[1008] Output: User data stored in a database.

[1009] Specific operation: The server parses the received JSON data and stores it in a database for each user ID. The data is stored appropriately using a database management system (e.g., MySQL or PostgreSQL).

[1010] Step 4:

[1011] The server generates a life log of the user based on the accumulated data.

[1012] Input: User data stored in a database.

[1013] Output: The generated lifelog.

[1014] What it does: The server runs scripts to retrieve user data from a database, aggregate and format the data, and generate a life log, which includes detailed logs by date and activity.

[1015] Step 5:

[1016] The user checks the life log and makes additions or corrections as necessary.

[1017] Input: The generated lifelog.

[1018] Output: Lifelog modified and added by the user.

[1019] Specific operation: The user views the life log through the application on the device and makes additions or modifications as necessary. The added or modified life log is sent back to the server and updated.

[1020] Step 6:

[1021] The server generates and provides lifestyle improvement suggestions and meal suggestions based on the updated life log.

[1022] Input: Revised and added life log, emotional data, and dietary data.

[1023] Output: Generated lifestyle improvement suggestions and dietary suggestions.

[1024] Specific operation: The server uses an AI model (e.g., TensorFlow or PyTorch) to analyze the accumulated data and life logs, and generates lifestyle improvement and dietary suggestions. The suggestions are then notified to the user via their device.

[1025] Examples:

[1026] A user eats yogurt at 8:00 AM and feels it is "delicious." The device collects data along with the user's emotion. This data is sent to the server, and the life log records "8:00 Breakfast Yogurt Delicious." Based on this information, the server makes a suggestion: "We recommend eating yogurt for breakfast next time."

[1027] Examples of prompt statements

[1028] text

[1029] Use user ID 123's food and sentiment data from the past week to generate personalized suggestions for their next meal. The user is experiencing multiple periods of high stress. The suggestions should include healthy meals appropriate for these times and ingredients that are good for reducing stress.

[1030] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1031] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1032] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1033] [Third embodiment]

[1034] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1035] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1036] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1037] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1038] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1039] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1040] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1041] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1042] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1043] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1044] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1045] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1046] The present invention is a system that records the user's daily life and suggests lifestyle improvements based on the data. This system is composed of a terminal, a server, and user interactions.

[1047] Overall system overview

[1048] 1. Data collection

[1049] The device acquires the user's location information, health information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health app, payment app, browser, etc.). This data is collected periodically and formatted in JSON format.

[1050] 2. Data transmission

[1051] The device compiles the collected data into JSON format and sends it to the server along with the user's identification information (user ID). The server receives this information and analyzes it.

[1052] 3. Data accumulation

[1053] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and suggest lifestyle improvements.

[1054] 4. Generating a life log

[1055] The server analyzes the accumulated data and automatically generates a life log for the user, which is a history of the user's daily activities and behavior and is provided to the user via their device.

[1056] 5. Additions and corrections by users

[1057] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[1058] 6. Generating lifestyle improvement proposals

[1059] The server uses AI to generate lifestyle improvement suggestions based on the user's accumulated data and life log. These suggestions include health habit suggestions, exercise advice, and suggestions for improving dietary habits. The generated suggestions are notified to the user via their device.

[1060] Explanation of program processing

[1061] Terminal handling

[1062] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. All of this data is formatted into JSON and sent to the server.

[1063] Server Processing

[1064] The server receives JSON-formatted data sent from the device and accumulates the data for each user ID. The accumulated data is analyzed as appropriate, and a life log is automatically generated. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and updated life log, and notifies the device.

[1065] User Action

[1066] Users can review their life logs displayed on their devices and reflect on their lives. They can make additions or corrections as needed to make the life logs more detailed and accurate. Users can also refer to suggestions for lifestyle improvements from the server and review their health habits and improve the quality of their lives.

[1067] Specific examples

[1068] For example, if a user goes jogging in the park at 8:00 in the morning, the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and health app and sends them to the server. The server analyzes this information and automatically records it in the user's life log as "Jogging in the park at 8:00." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. Then, using AI, it generates lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining your health," and notifies the user.

[1069] This system allows users to effortlessly reflect on their daily lives and obtain hints for improving their lifestyle habits. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably reflect on their own behavior and helps improve the quality of their lives.

[1070] The processing flow will be explained below.

[1071] Step 1:

[1072] The device uses a GPS sensor to obtain the user's current location. It also collects health information such as the number of steps taken and heart rate from a health app, purchase history and amount spent information from a payment app, and obtains the user's search information from the browser's search history, as well as current weather information from a weather app or API.

[1073] Step 2:

[1074] The device formats the location, health, payment, search, and weather information into a single JSON object, including the user ID, ready to be sent to the server later.

[1075] Step 3:

[1076] The device creates a POST request to send a JSON object to the server and sends it to the specified server URL. If the transmission is successful, the device notifies the user of this information.

[1077] Step 4:

[1078] The server receives the POST request sent from the device. The received data is analyzed and stored in a database for each user ID. The stored data will be used to generate future life logs and propose lifestyle improvements.

[1079] Step 5:

[1080] The server periodically generates a user's life log based on the accumulated data. The life log includes a history of the user's daily activities and behavior. The generated life log is then sent to the device.

[1081] Step 6:

[1082] The user checks the life log displayed on the device. The life log displays a detailed record of the user's daily activities. The user can add or edit the life log as needed.

[1083] Step 7:

[1084] After the user adds or modifies the lifelog, the device sends the information back to the server as a JSON object. The server receives the modified lifelog and updates the database.

[1085] Step 8:

[1086] The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and the revised life log. The generated suggestions include specific health habits and lifestyle advice.

[1087] Step 9:

[1088] The server formats the generated lifestyle improvement proposals in JSON format and sends them to the device, which receives them and notifies the user.

[1089] Step 10:

[1090] Users can check the lifestyle improvement suggestions displayed on their devices and take actions to improve the quality of their daily lives. Users can refer to the suggestions and review their health and lifestyle habits.

[1091] These are the specific processing steps of the program, which allow the user to reflect on their daily life and receive specific suggestions for improving the quality of their life.

[1092] Example 1

[1093] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1094] Conventional systems that record daily life and suggest lifestyle improvements often require time-consuming data collection, storage, and analysis, or are insufficient. Furthermore, users often have to spend time checking and editing their own life logs, which results in poor accuracy in lifestyle improvement suggestions. This makes the introduction and use of such systems particularly difficult for elderly users and those with memory impairments.

[1095] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1096] In this invention, the server

[1097] A means for the terminal to acquire user location information, health status information, transaction information, search history, and weather information from a plurality of sensors and software;

[1098] a server receiving the acquired data and storing the data for each user;

[1099] A means for the server to automatically generate a life record of the user based on the accumulated data;

[1100] A server generates lifestyle improvement suggestions based on the user's lifestyle records;

[1101] A means for the terminal to format the acquired data into a JSON format and transmit the formatted data to a server;

[1102] A means for a server to analyze the JSON format data and generate a life record of the user;

[1103] A means for the server to analyze the accumulated data and life records using AI and generate improvement suggestions;

[1104] This includes:

[1105] Users can effortlessly record their daily lives, easily add to and edit their life logs, and even receive highly accurate lifestyle improvement suggestions based on the accumulated data.

[1106] A "terminal" is an information processing device equipped with multiple sensors and software for collecting data on the user's daily life.

[1107] A "sensor" is a device that measures physical environmental information, and in this system includes GPS sensors, health status sensors, weather sensors, etc.

[1108] "Software" refers to a program that is installed on a device and performs a specific function, such as a healthcare app, a payment app, or a browser.

[1109] "Location Information" means data that indicates a user's geographic location and is collected by a GPS sensor.

[1110] "Health status information" is data related to the user's health, and includes information such as the number of steps taken, heart rate, and calorie consumption.

[1111] "Transaction information" is data related to a user's purchasing activities, including purchase history obtained from a payment app.

[1112] "Search history" is the history of searches a user has performed on the Internet, and is data obtained from a browser.

[1113] "Weather information" refers to data related to the weather, obtained from weather apps and weather sensors.

[1114] A "life log" is data that records the history of a user's daily activities and behavior, and is automatically generated by a server.

[1115] "Lifestyle improvement suggestions" are suggestions for improving the quality of life that are generated based on the user's life log and accumulated data.

[1116] The "JSON format" is a format used to structurally represent data and communicate between servers and terminals.

[1117] "AI" refers to artificial intelligence, a technology that analyzes accumulated data and generates lifestyle improvement suggestions.

[1118] This invention relates to a system that records a user's daily life and makes suggestions for improving their lifestyle based on the data. This system is composed of a terminal, a server, and user interactions.

[1119] System configuration

[1120] 1. Terminal configuration and operation

[1121] The device collects various data about the user using multiple built-in sensors (e.g., GPS sensor, health condition sensor) and installed software (e.g., healthcare app, payment app, browser). Specifically, the device collects the following data:

[1122] Location information using a GPS sensor

[1123] Health status information such as steps taken, heart rate, and calorie consumption via the Health app

[1124] Transaction information (purchase history) from payment apps

[1125] Browser search history

[1126] Weather information from weather apps and weather sensors

[1127] This collected data is obtained at regular intervals and formatted into JSON format.

[1128] 2. Data transmission

[1129] The device periodically converts the collected data into JSON format and sends it to the server along with the user ID. This transmission is performed every 15 minutes, and the HTTPS protocol is used to maintain data integrity.

[1130] 3. Server Configuration and Operation

[1131] The server receives and analyzes the JSON format data sent from the device. The received data is stored in a database for each user ID, and each record also includes a timestamp for the data.

[1132] The server periodically analyzes the accumulated data and automatically generates a record of the user's daily life (life log). The life log records the user's daily activities and behavior. The server then uses AI to generate lifestyle improvement suggestions based on the accumulated data and the latest life log, and notifies the device.

[1133] 4. User Operation

[1134] Users can check the lifelog displayed on their device and reflect on their daily lives. They can add or edit the lifelog as needed, which improves its accuracy. Data added or edited by the user is sent back to the server, and the lifelog is updated.

[1135] Specific examples

[1136] For example, if a user goes jogging in the park at 8:00 a.m., the device obtains location information from the GPS sensor and jogging data (distance, time, heart rate) from the health app, then compiles this into a JSON file and sends it to the server. The server analyzes the received data and automatically records "Jogging in the park at 8:00" in the user's life log. If the user checks this life log and adds "That was a great run!", this information is also sent to the server and the life log is updated. The server then uses AI to generate lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and notifies the user via the device.

[1137] Prompt Sentence Examples

[1138] "If the user has the habit of jogging every morning, explain how jogging three times a week can help them stay healthy."

[1139] In this way, users can effortlessly review their daily lives, receive highly accurate suggestions for lifestyle improvements, and improve their quality of life. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably review their own actions, helping to improve their quality of life.

[1140] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1141] Step 1: Collect data

[1142] Terminal handling

[1143] The device collects user data using various sensors and software: location information from the GPS sensor, step count and heart rate from health apps, purchase history from payment apps, search history from the browser, and weather information from weather apps.

[1144] Input: Data obtained from GPS sensor, health app, payment app, browser, and weather app

[1145] Data processing: Acquire raw data from each sensor and app and format it into JSON format.

[1146] Output: JSON format data

[1147] How it works: Every 15 minutes, the device retrieves new data from each sensor and app, consolidates it, and generates a JSON file.

[1148] Step 2: Sending data

[1149] Terminal handling

[1150] The data collected by the device is formatted in JSON and sent to the server along with the user ID.

[1151] Input: Formatted JSON data and user ID

[1152] Data processing: Encoding to maintain data integrity

[1153] Output: HTTPS request to the server

[1154] Specific operation: Every 15 minutes, the device makes an HTTPS request to the server and sends data in JSON format along with the user ID.

[1155] Step 3: Accumulate data

[1156] Server Processing

[1157] The server analyzes the received JSON format data and stores it in a database for each user ID.

[1158] Input: JSON format data sent from the terminal

[1159] Data processing: Parse the JSON data, extract each data item, and store it in the database.

[1160] Output: Data stored in the database

[1161] Specific operation: The server first stores the received data in temporary memory and then writes it to the database sequentially.

[1162] Step 4: Generating a Lifelog

[1163] Server Processing

[1164] The server periodically analyzes the accumulated data and automatically generates a life log for the user.

[1165] Input: Data stored for each user

[1166] Data processing: Perform time series analysis of the data and compile it into a history of the user's daily behavior.

[1167] Output: Life log

[1168] Specific operation: The server runs a job every day at midnight, analyzes data from the past 24 hours, generates a "life log," and stores it in a database.

[1169] Step 5: User additions and modifications

[1170] User Action

[1171] Users can check their lifelog and add or edit it as needed.

[1172] Input: Lifelog displayed on the device

[1173] Data processing: Form input processing to support user additions and corrections

[1174] Output: Modified lifelog

[1175] Specific operation: When a user opens the app on their device, displays their life log, and adds "I ate bread for breakfast," the information is sent to the server in JSON format and the life log database is updated.

[1176] Step 6: Generate life improvement proposals

[1177] Server Processing

[1178] The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and life logs, and these suggestions are sent to the user via their device.

[1179] Input: User's accumulated data and life log

[1180] Data processing: Generate lifestyle improvement suggestions through analysis and pattern recognition using AI models

[1181] Output: Lifestyle improvement suggestions

[1182] Specific operation: The server runs the AI ​​model at 1 a.m. every day, analyzes the data, generates suggestions such as "It is recommended to jog three times a week," and notifies the user via the device.

[1183] (Application example 1)

[1184] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1185] In modern society, users are expected to improve their daily lifestyle habits and maintain their health. However, manually recording and analyzing their daily life data to find improvement measures is a very time-consuming process. For this reason, there is a need for a system that automatically collects, stores, and analyzes users' daily life data to provide lifestyle improvement suggestions. Furthermore, to improve the accuracy of lifestyle improvement suggestions, it is necessary to use generative AI models to perform more advanced analysis based on diverse data.

[1186] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1187] In this invention, the server includes: means for the terminal to acquire user location information, healthcare information, payment information, search information, and weather information from multiple sensors and applications; means for the server to receive the acquired data and accumulate the data for each user; means for the server to automatically generate a user's life log based on the accumulated data; means for the server to generate lifestyle improvement suggestions based on the user's life log; and means for generating prompt sentences and requesting analysis by a generative AI model to improve the accuracy of the lifestyle improvement suggestions. This allows users to easily collect and accumulate data about their daily lives and perform advanced analysis using AI, enabling them to receive highly accurate lifestyle improvement suggestions.

[1188] A "terminal" is an electronic device used to collect data from a user's daily life, and is equipped with multiple sensors and applications.

[1189] A "sensor" is a device that detects a physical phenomenon (e.g., position, movement, temperature, etc.) and converts it into digital data.

[1190] An "application" is a software program that runs on a terminal to provide a specific function or service.

[1191] "Location Information" means geographic location data of a user obtained using a GPS sensor.

[1192] "Healthcare information" refers to data related to health status and physical activity, including, for example, the number of steps taken and heart rate.

[1193] "Payment information" is data related to the purchase and payment history of a user.

[1194] "Search Information" is data about search queries performed by users on the Internet and their history.

[1195] "Weather information" is data about the weather conditions at the user's location.

[1196] A "server" is a computer system that receives, stores, and analyzes data sent from a terminal.

[1197] "Data storage" is the process of organizing collected data and storing it for later analysis and reuse.

[1198] A "life log" is digital data that records the history of a user's daily actions and activities.

[1199] "Lifestyle improvement suggestions" are specific advice and recommendations for improving lifestyle habits based on the user's life log.

[1200] A "prompt" is an instruction entered into a generative AI model to make it perform a specific task.

[1201] A "generative AI model" is an artificial intelligence algorithm used to analyze data using machine learning to generate insights and recommendations.

[1202] The present invention is a system that records the user's daily life and suggests lifestyle improvements based on the data. This system is composed of a terminal, a server, and user interactions.

[1203] 1. Data collection

[1204] The device acquires the user's location information, health information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health app, payment app, browser, etc.). The collected data is periodically formatted into JSON format.

[1205] 2. Data transmission

[1206] The data collected by the device is compiled in JSON format and sent to the server along with the user's identification information (user ID). The server receives and analyzes this data.

[1207] 3. Data accumulation

[1208] The server stores the received data in a database for each user ID. The stored data will be used to generate a life log and suggest lifestyle improvements.

[1209] 4. Generating a life log

[1210] The server analyzes the accumulated data and automatically generates a life log for the user, which records the user's daily activities and behavioral history and is provided to the user via their device.

[1211] 5. Additions and corrections by users

[1212] The user can check the lifelog displayed on the device and add or modify it as needed. The added or modified lifelog is then sent back to the server and updated.

[1213] 6. Generating lifestyle improvement proposals

[1214] The server uses a generative AI model to generate lifestyle improvement suggestions based on the user's accumulated data and life log. These suggestions include health habit suggestions, exercise advice, and suggestions for improving dietary habits. The generated suggestions are notified to the user via their device.

[1215] 7. Improved accuracy with generative AI models

[1216] The server then generates a prompt and requests the generative AI model to analyze it. This prompt includes the user's life log and collected data. The generative AI model provides analysis results that improve the accuracy of lifestyle improvement suggestions.

[1217] Hardware / Software used

[1218] Hardware: Smartphone

[1219] Software: Python, HTTP API (communication with server), generative AI model

[1220] Data processing / calculation: Data collection, formatting into JSON format, advanced analysis using AI

[1221] Specific examples

[1222] For example, if a user goes jogging in the morning, the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and healthcare app and sends them to the server. The server analyzes this information and automatically records it in the user's life log as "Jogging in the park at 8:00." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. The generative AI model is then used to generate lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and notifies the user.

[1223] Prompt Sentence Examples

[1224] "Analyze the following data to generate suggestions to improve the user's life:

[1225] GPS data: 35.6895, 139.6917, "jogging"

[1226] Health data: Steps: 3000, Heart rate: 120

[1227] Payment Data: Purchase: None

[1228] Search data: None

[1229] Weather data: Sunny, Temperature: 15

[1230] Please offer some advice on how to improve your life."

[1231] This system allows users to effortlessly reflect on their daily lives and receive specific advice on how to improve their lifestyle habits.

[1232] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1233] Step 1:

[1234] The device collects the user's location, health, payment, search, and weather information from multiple sensors and applications. Data obtained from sensors and applications includes location information from the GPS sensor, step count and heart rate records from the health app, purchase history from the payment app, browser search history, and weather information from the weather app. This data is temporarily stored on the device.

[1235] input:

[1236] Data from multiple sensors and applications

[1237] output:

[1238] Temporarily stored data on the device

[1239] Step 2:

[1240] The data collected by the device is periodically formatted into JSON format. The collected location information, health information, payment information, search information, weather information, etc. are compiled into a single JSON object, along with the user ID.

[1241] input:

[1242] Temporarily saved data

[1243] output:

[1244] Integration data in JSON format

[1245] Step 3:

[1246] The device sends formatted JSON data to the server using an HTTP POST request to send the data to the server's API endpoint. The server receives this request and prepares to parse the data.

[1247] input:

[1248] Integration data in JSON format

[1249] output:

[1250] Data sent to the server

[1251] Step 4:

[1252] The server receives the data sent from the device and stores it in a database for each user, allowing data associated with each user to be permanently stored and used for later analysis.

[1253] input:

[1254] Data sent to the server

[1255] output:

[1256] Accumulated data in the database

[1257] Step 5:

[1258] The server analyzes the accumulated data and automatically generates a life log for the user. It compares past data with newly added data to generate a life log that summarizes the user's daily activities and health status in chronological order. The generated life log is then saved back into the database.

[1259] input:

[1260] Accumulated data in the database

[1261] output:

[1262] Automatically generated lifelog

[1263] Step 6:

[1264] The server sends the generated lifelog to the device and provides it to the user. The user can check their own lifelog on the device and add or modify it as necessary.

[1265] input:

[1266] Automatically generated lifelog

[1267] output:

[1268] Life log presentation data

[1269] Step 7:

[1270] After the user adds or modifies the lifelog, the device sends the modified lifelog back to the server, which then updates the database with the modified lifelog.

[1271] input:

[1272] Modified Lifelog

[1273] output:

[1274] Updated database

[1275] Step 8:

[1276] The server generates lifestyle improvement proposals using a generative AI model based on the updated life log and accumulated data. The server generates prompt statements and requests the generative AI model to analyze them. Based on the analysis results of the generative AI model, highly accurate lifestyle improvement proposals are created.

[1277] input:

[1278] Updated lifelog and accumulated data

[1279] output:

[1280] Generated lifestyle improvement proposals

[1281] Step 9:

[1282] The server sends the generated lifestyle improvement suggestions to the terminal, and the user receives the lifestyle improvement suggestions via the terminal and makes lifestyle improvements based on them.

[1283] input:

[1284] Generated lifestyle improvement proposals

[1285] output:

[1286] User notification data

[1287] Prompt Sentence Examples

[1288] "Analyze the following data to generate suggestions to improve the user's life:

[1289] GPS data: 35.6895, 139.6917, "jogging"

[1290] Health data: Steps: 3000, Heart rate: 120

[1291] Payment Data: Purchase: None

[1292] Search data: None

[1293] Weather data: Sunny, Temperature: 15

[1294] Please offer some advice on how to improve your life."

[1295] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1296] This invention combines an emotion engine with a system that records a user's daily life and makes suggestions for lifestyle improvements based on that data. This system is composed of a terminal, a server, and an engine that handles user interaction and emotion recognition.

[1297] Overall system overview

[1298] 1. Data collection

[1299] The device acquires the user's location information, health care information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health care app, payment app, browser, etc.). In addition, the device's built-in emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[1300] 2. Data transmission

[1301] The device collects location information, health information, payment information, search information, weather information, and emotion data, and then compiles them into JSON format and sends them along with the user ID to the server. The server receives this information and analyzes it.

[1302] 3. Data accumulation

[1303] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[1304] 4. Generating a life log

[1305] The server analyzes the accumulated data and automatically generates a life log for the user, which includes the user's daily activities, behavioral history, and emotional state. The generated life log is provided to the user via their device.

[1306] 5. Additions and corrections by users

[1307] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[1308] 6. Generating lifestyle improvement proposals

[1309] The server uses AI to generate lifestyle improvement suggestions based on the user's accumulated data and life log. Taking into account the user's emotional data in particular, the server generates personalized suggestions based on their emotional state. The generated suggestions are then sent to the user via their device.

[1310] Explanation of program processing

[1311] Terminal handling

[1312] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. Furthermore, an emotion engine analyzes the user's facial expressions and voice tone to generate emotion data. All of this data is formatted in JSON format and sent to the server.

[1313] Server Processing

[1314] The server receives JSON-formatted data sent from the device and stores it in a database for each user ID. The stored data is analyzed as appropriate, and a life log is automatically generated. The generated life log records the user's emotional state along with their activity history. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI to generate lifestyle improvement suggestions based on the stored data and updated life log, and notifies the device. The suggestions take emotional data into consideration and include advice that fits the user's psychological state.

[1315] User Action

[1316] Users can check the life log displayed on their device and review their daily activity records. They can add or edit the life log as needed to make the record more detailed and accurate. Users can refer to the lifestyle improvement suggestions from the server and review their health and lifestyle habits. In particular, suggestions based on emotional data provide specific advice that is tailored to the user's psychological state.

[1317] Specific examples

[1318] For example, if a user goes jogging in the park at 8:00 a.m., the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and health app, and then uses the emotion engine to recognize the user's emotion of "comfortable" from their facial expressions and voice. This data is sent to the server, which analyzes it and automatically records it in the user's life log as "8:00 Jogging in the park, comfortable." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. Then, using AI, the device generates lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and provides specific exercise advice based on the user's comfortable jogging experience.

[1319] This system allows users to effortlessly reflect on their daily lives and receive suggestions for lifestyle improvements that reflect their emotional state. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably reflect on their own actions and emotions, helping to improve the quality of their lives.

[1320] The processing flow will be explained below.

[1321] Step 1:

[1322] The device uses the GPS sensor to obtain the user's current location, collects health information such as the number of steps taken and heart rate from the health app, and obtains purchase history and payment amount information from the payment app.

[1323] Step 2:

[1324] The device retrieves the user's search keywords and visited websites from the browser's search history, and also retrieves the current day's weather information from weather apps and APIs.

[1325] Step 3:

[1326] The device's emotion engine captures the user's facial expressions with a camera and records their voice with a microphone, and analyzes them to generate emotion data (e.g., happiness, anger, sadness, etc.).

[1327] Step 4:

[1328] The device formats the collected location, health, payment, search, weather, and emotion data into a single JSON object, which also includes the user ID.

[1329] Step 5:

[1330] The device creates a POST request to send the formatted JSON object to the server, sends it to the specified server URL, and notifies the user of the status if the transmission is successful.

[1331] Step 6:

[1332] The server receives the POST request sent from the device and analyzes the data. The received data is stored in a database for each user ID. This stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[1333] Step 7:

[1334] The server periodically generates a user's life log based on the accumulated data. The life log includes the user's daily activities, behavioral history, and emotional state. The generated life log is formatted in JSON format and sent to the device.

[1335] Step 8:

[1336] The user checks the life log displayed on the device. The life log displays a detailed account of the user's daily activities, behaviors, and emotional state. The user can add or edit the life log as needed.

[1337] Step 9:

[1338] The device reformats the lifelog that the user has added or modified into JSON format and sends it to the server. The server receives the modified lifelog and updates the database.

[1339] Step 10:

[1340] The server generates lifestyle improvement suggestions based on the accumulated data and the revised life log, using AI to take into account the user's emotional data and generate specific suggestions based on their emotions.

[1341] Step 11:

[1342] The server formats the generated lifestyle improvement proposals in JSON format and sends them to the device, which receives them and notifies the user.

[1343] Step 12:

[1344] Users can check the lifestyle improvement suggestions displayed on the device and improve their daily habits and behaviors based on them. For example, they receive specific advice such as how to maintain health by continuing to jog or how to reduce stress.

[1345] As a concrete example, consider the case where a user goes jogging in the park at 8:00 in the morning. The device obtains location information and jogging-related data (distance, time, heart rate) from the GPS sensor and health care app, and the emotion engine recognizes the emotion of "comfortable" from the user's facial expressions and voice. This data is sent to the server, analyzed, and automatically recorded in the life log as "8:00 Jogging in the park, comfortable." If the user checks this life log and adds "I had a great run!", the server updates and stores this information. Then, using AI, it generates lifestyle improvement suggestions such as "Jogging three times a week is effective for maintaining health" and provides specific exercise advice.

[1346] The above is a specific embodiment of the present invention. This system allows users to easily record their actions and emotions and receive specific suggestions for improving their quality of life. In particular, by using an emotion engine, it is possible to provide advice that fits the user's psychological state.

[1347] Example 2

[1348] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1349] Conventional lifelog systems have the problem of not being able to fully reflect a user's daily activities and emotional state. Furthermore, their lifestyle improvement suggestions do not take into account the user's emotional state, resulting in low user satisfaction and implementation rates. Furthermore, the process of collecting and analyzing data is cumbersome, often causing users to feel overwhelmed.

[1350] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1351] In this invention, the server includes: a terminal that acquires a user's location information, health information, purchase information, search information, and weather information from multiple sensors and software; a terminal that analyzes a user's facial expressions and voice tone and generates emotion data; a terminal that formats the acquired data into JSON format and transmits it to the server; a server that receives the acquired data and accumulates the data for each user; a server that automatically generates a user's life log based on the accumulated data; and a server that generates lifestyle improvement suggestions using a generative AI model based on the user's life log. This makes it possible to collect and analyze a user's comprehensive activity and emotion data and provide lifestyle improvement suggestions based on the user's individual emotional state.

[1352] A "terminal" is an electronic device equipped with multiple sensors and software for collecting a user's location information, health information, purchase information, search information, weather information, and emotional data.

[1353] A "server" is a computer system that receives, stores, and analyzes data sent from a terminal.

[1354] A "sensor" is an electronic device that collects environmental or biometric information, such as a user's location or physiological data.

[1355] "Software" refers to application programs installed on the terminal that collect and format data.

[1356] "User location information" is data about the user's current location obtained using a GPS sensor.

[1357] "Health information" is data indicating the physiological state of the user, such as the number of steps taken and heart rate.

[1358] "Purchase information" is data related to the purchase history and transactions made by the user.

[1359] "Search information" refers to data related to the keywords and history of searches a user has performed on the Internet.

[1360] "Weather information" refers to weather forecasts and temperature information obtained based on the user's location.

[1361] "Emotion data" is data that indicates an emotional state generated by the terminal's emotion engine by analyzing the user's facial expressions and vocal tone.

[1362] The "JSON format" is a lightweight, text-based data exchange format for structuring and representing data.

[1363] A "user ID" is an identification code assigned to each user to uniquely identify them.

[1364] A "life log" is data that records a user's daily activity history and emotional state.

[1365] A "generative AI model" is an artificial intelligence algorithm that generates lifestyle improvement suggestions based on collected data.

[1366] "Lifestyle Improvement Suggestions" provides advice to improve the user's lifestyle habits based on the user's life log and emotional data.

[1367] The present invention is a system for providing suggestions to improve a user's life. This system records the user's daily life and makes suggestions to improve their life based on that data. The system is mainly composed of a terminal, a server, and an engine that handles user interaction and emotion recognition.

[1368] Specific configuration

[1369] Terminal

[1370] The device collects data using various sensors and applications, including GPS sensors, health management software, payment applications, web browsers, and emotion engines. For example, consider a device that implements the following measures:

[1371] Location information: Uses a GPS sensor to obtain real-time user location information.

[1372] Health information: We collect health data such as your steps and heart rate from health management software (e.g., Apple Health, Google Fit).

[1373] Purchase information: Obtain purchase history from a payment application (e.g., a general-purpose payment system).

[1374] Search information: Obtain search history from web browsers (e.g., general-purpose browsers).

[1375] Emotion data: The emotion engine analyzes the user's facial expressions and vocal tone to generate emotion data.

[1376] All collected data is formatted in JSON and sent to the server.

[1377] server

[1378] The server receives the JSON format data sent from the device and accumulates the data for each user. Specifically, the data is saved for each user ID using a database (e.g., a general-purpose database management system). The accumulated data is analyzed, and the user's life log is automatically generated.

[1379] The generated life log includes the user's emotional state along with their activity history. For example, the following life log may be generated:

[1380] 8:00 Jogging in the park, comfortable

[1381] 12:00 Buy coffee at the cafe

[1382] The server then uses a generative AI model (e.g., a general-purpose generative AI model) to generate lifestyle improvement suggestions based on the generated life log. The suggestions take into account the user's emotional data and include specific advice that matches the user's psychological state. For example, a suggestion such as "Jogging three times a week is effective for maintaining health" may be generated.

[1383] User

[1384] The user can check the lifelog displayed on the device and make additions or corrections as necessary. The corrected lifelog is reformatted into JSON format and sent to the server. The server receives this information and updates the database. For example, if a user adds "That was a great run!" to the lifelog, this information is sent to the server and re-stored.

[1385] This allows users to effortlessly reflect on their daily lives and receive suggestions for lifestyle improvements that reflect their emotional state.It also helps elderly people and those with memory impairments to easily and enjoyably reflect on their actions and emotions, helping to improve the quality of their lives.

[1386] Examples of specific examples and prompts

[1387] For example, when a user goes jogging in the park at 8:00 in the morning, the device collects location information, health data (step count 5000, heart rate 70 BPM), and emotional data (comfortable), and sends them to the server in JSON format. The server analyzes this data and automatically records "8:00 Jogging in the park, comfortable" in the life log.

[1388] If the user checks this life log and adds, "That was a great run!", the server updates this information and uses AI to generate lifestyle improvement suggestions such as, "Jogging three times a week is effective for maintaining health." An example of such a prompt would be something specific like, "I want to increase the amount of exercise I do to stay healthy. What advice do you have?"

[1389] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1390] Step 1:

[1391] Data collection

[1392] Device operation: The device uses multiple sensors and software to obtain the user's location, health, purchase, search, and weather information. Specifically, the device obtains the user's current location (e.g., latitude 35.6895, longitude 139.6917) using a GPS sensor, and obtains the number of steps (e.g., 5,000 steps) and heart rate (e.g., 70 BPM) from health management software. It also obtains purchase history from the payment application and search history (e.g., weather forecast search) from the browser. It uses an emotion engine to analyze the user's facial expressions and voice tone and generate emotion data (e.g., "comfortable").

[1393] Input: User location information, health information, purchase information, search information, weather information, emotional data

[1394] Output: Formatted JSON data

[1395] Step 2:

[1396] Organizing and sending data

[1397] What the device does: It formats all the data collected by the device into JSON format. For example, it generates the following JSON object:

[1398] json

[1399] {

[1400] "userID": "12345",

[1401] "location": {"lat": 35.6895, "long": 139.6917},

[1402] "healthData": {"steps": 5000, "heartRate": 70},

[1403] "transactions": [{"time": "12:00", "item": "coffee"}],

[1404] "searchHistory": ["Weather Forecast"],

[1405] "emotion": "comfortable"

[1406] }

[1407] Input: Data obtained from various sensors and software

[1408] Output: JSON data to send to the server

[1409] Step 3:

[1410] Receiving and storing data

[1411] Server operation: The server receives the JSON format data sent from the device. It analyzes the received data and saves it in the database based on the user ID. For example, add the following record to the database:

[1412] json

[1413] {

[1414] "userID": "12345",

[1415] "location": {"lat": 35.6895, "long": 139.6917},

[1416] "healthData": {"steps": 5000, "heartRate": 70},

[1417] "transactions": [{"time": "12:00", "item": "coffee"}],

[1418] "searchHistory": ["Weather Forecast"],

[1419] "emotion": "comfortable"

[1420] }

[1421] Input: JSON data sent from the terminal

[1422] Output: User data stored in the database

[1423] Step 4:

[1424] Generating a life log

[1425] Server operation: The server automatically generates a user's life log based on the accumulated data. It aggregates the analyzed data and generates a content that describes the user's daily activity history and emotional state. For example, a life log such as "8:00 Jogging in the park, comfortable" may be generated.

[1426] Input: User data stored in the database

[1427] Output: Automatically generated lifelog

[1428] Step 5:

[1429] Checking, adding, and correcting life logs

[1430] User action: The user checks the life log displayed on the device and adds or corrects it as necessary. For example, to the entry "8:00 Jogging in the park, comfortable," the user adds "It was a great run!"

[1431] Input: Lifelog displayed on the device

[1432] Output: Added and corrected lifelog

[1433] Step 6:

[1434] Updating and re-accumulating life logs

[1435] Operation of the device and server: The added and corrected lifelog is reformatted into JSON format and sent to the server. The server receives it and updates the database.

[1436] Input: Added / modified lifelog

[1437] Output: Updated database

[1438] Step 7:

[1439] Generating lifestyle improvement proposals

[1440] Server operation: The server generates lifestyle improvement suggestions using a generative AI model based on accumulated data and the latest life log. In particular, it takes into account the user's emotional data and generates specific advice that fits the user's psychological state (e.g., "Jogging three times a week is effective for maintaining health").

[1441] Input: Updated lifelog and accumulated data

[1442] Output: Generated lifestyle improvement suggestions

[1443] Step 8:

[1444] Notification of lifestyle improvement proposals

[1445] Operation of the device and server: The generated lifestyle improvement suggestions are sent to the device, where the user can check them and apply them to their daily lives.

[1446] Input: Generated lifestyle improvement proposals

[1447] Output: Proposal posted to terminal

[1448] (Application example 2)

[1449] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1450] In modern life, users are seeking ways to reflect on and improve their lifestyles, but specific and personalized lifestyle improvement suggestions that take emotional data into account are lacking. In particular, it is difficult for users to obtain detailed suggestions about what kind of diet they should eat.

[1451] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1452] In this invention, the server includes: means for a terminal to acquire user location information, health care information, payment information, search information, and weather information from multiple sensors and applications; means for the server to receive the acquired data and accumulate data for each user; means for the server to automatically generate a life log for the user based on the accumulated data; means for the server to generate lifestyle improvement suggestions based on the user's life log; and means for the server to analyze the user's dietary content and diet-related emotional data and make individual dietary suggestions. This enables users to receive more specific and personalized dietary suggestions by making lifestyle improvements that take the emotional data into consideration.

[1453] A "terminal" is a device equipped with multiple sensors and applications that acquires user information and sends it to a server.

[1454] A "sensor" is a device that detects a user's location information, physical information, etc. and outputs it as digital data.

[1455] An "application" is a software program that runs on a terminal and obtains the user's healthcare information, payment information, search information, weather information, and the like.

[1456] "Location information" refers to data on a user's current location and movement history obtained through a GPS sensor or other means.

[1457] "Healthcare information" is data related to the user's health condition, including the number of steps taken and heart rate.

[1458] "Payment information" is data related to monetary transactions made by a user.

[1459] "Search information" is data relating to the search behavior of users on the Internet.

[1460] "Weather information" is data about the weather in the area where the user is located.

[1461] The "server" is a computer system that receives and stores data sent from the terminals, analyzes it, and generates lifestyle improvement proposals.

[1462] A "life log" is a history of a user's daily activities and behavior that is automatically generated based on data accumulated by a server.

[1463] "Lifestyle improvement suggestions" are advice for improving the user's lifestyle, generated by the server based on the user's life log and emotional data.

[1464] "Emotion data" is data generated by analyzing emotions from the user's facial expressions and voice.

[1465] "Meal details" is data related to meals taken by the user.

[1466] "Emotion data related to meals" is data that records the emotions felt by the user while eating.

[1467] "Dietary suggestions" are dietary advice provided individually by the server based on an analysis of the user's dietary content and emotional data related to the diet.

[1468] The present invention combines an emotion engine with a system that records a user's daily life and makes suggestions for improving their lifestyle based on that data. Specific embodiments of the present invention are described below.

[1469] System Overview

[1470] 1. Data collection

[1471] The device acquires the user's location, health care, payment, search, and weather information from multiple sensors and applications (e.g., GPS sensor, health care app, payment app, browser, etc.). The device's built-in emotion engine also analyzes the user's voice and facial expressions to generate emotion data. Furthermore, data on the user's diet and emotion related to the diet is also collected.

[1472] 2. Data transmission

[1473] The device collects location information, health information, payment information, search information, weather information, emotional data, meal contents, and emotional data related to meals, and compiles them into JSON format and sends them to the server along with the user ID. The server receives this information and analyzes it.

[1474] 3. Data accumulation

[1475] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[1476] 4. Generating a life log

[1477] The server analyzes the accumulated data and automatically generates a life log for the user. The life log includes the user's daily activities and behavior history, emotional state, and diet history. The generated life log is provided to the user via the device.

[1478] 5. Additions and corrections by users

[1479] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[1480] 6. Generating lifestyle improvement and dietary suggestions

[1481] The server uses AI to generate lifestyle improvement and meal suggestions based on the user's accumulated data and life log. Taking into account the user's emotional data in particular, the server generates personalized suggestions based on their emotional state. The generated suggestions are then sent to the user via their device.

[1482] Explanation of program processing

[1483] Terminal handling

[1484] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. The emotion engine analyzes the user's facial expressions and tone of voice to generate emotion data. Food content and emotion-related data are also collected, and all of this data is formatted into JSON and sent to the server.

[1485] Server Processing

[1486] The server receives JSON-formatted data sent from the device and stores it in a database for each user ID. The stored data is analyzed as appropriate, and a life log is automatically generated. The generated life log records the user's activity history as well as their emotional state and dietary history. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI (e.g., TensorFlow or PyTorch) based on the stored data and updated life log to generate lifestyle improvement suggestions and dietary suggestions, and notifies the device. The suggestions take emotional data into consideration and include advice that fits the user's psychological state.

[1487] User Action

[1488] Users can check the life log displayed on their device and review their daily activity records. They can add or edit the life log as needed to make the record more detailed and accurate. Users can refer to lifestyle improvement and dietary suggestions from the server and review their health habits and eating habits. In particular, suggestions based on emotional data provide specific advice that is tailored to the user's psychological state.

[1489] Specific examples

[1490] For example, if a user eats yogurt for breakfast at 8:00 a.m. and thinks it's "delicious," the device collects the meal details and emotional data (emotions about how delicious it is). This data is sent to a server, which analyzes it and automatically records the user's life log as "8:00 Breakfast Yogurt Delicious." Based on this information, the server generates a specific meal suggestion, such as "We recommend you eat the same yogurt for breakfast next time," and notifies the user.

[1491] Examples of prompt statements

[1492] text

[1493] Use user ID 123's food and sentiment data from the past week to generate personalized suggestions for their next meal. The user is experiencing multiple periods of high stress. The suggestions should include healthy meals appropriate for these times and ingredients that are good for reducing stress.

[1494] The above is an embodiment of the present invention.

[1495] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1496] Step 1:

[1497] The device collects user data from multiple sensors and applications.

[1498] Input: Location information from the GPS sensor, step count and heart rate from the health app, purchase history from the payment app, search information from the browser history, and user voice, facial expressions, meal contents, and meal-related emotional data from the emotion engine.

[1499] Output: A JSON-formatted dataset of location, health, payment, search, weather, sentiment, and diet data.

[1500] Specific operation: The device acquires various information from sensors and applications in real time, and generates emotion data using the emotion engine. This data is then formatted and compiled in JSON format.

[1501] Step 2:

[1502] The terminal transmits the collected data to the server.

[1503] Input: A dataset in JSON format.

[1504] Output: The data sent to the server.

[1505] Specific operation: The terminal sends an HTTP request to the server via the Internet and transfers data in JSON format.

[1506] Step 3:

[1507] The server analyzes the received data and stores it in a database.

[1508] Input: JSON formatted data sent to the server.

[1509] Output: User data stored in a database.

[1510] Specific operation: The server parses the received JSON data and stores it in a database for each user ID. The data is stored appropriately using a database management system (e.g., MySQL or PostgreSQL).

[1511] Step 4:

[1512] The server generates a life log of the user based on the accumulated data.

[1513] Input: User data stored in a database.

[1514] Output: The generated lifelog.

[1515] What it does: The server runs scripts to retrieve user data from a database, aggregate and format the data, and generate a life log, which includes detailed logs by date and activity.

[1516] Step 5:

[1517] The user checks the life log and makes additions or corrections as necessary.

[1518] Input: The generated lifelog.

[1519] Output: Lifelog modified and added by the user.

[1520] Specific operation: The user views the life log through the application on the device and makes additions or modifications as necessary. The added or modified life log is sent back to the server and updated.

[1521] Step 6:

[1522] The server generates and provides lifestyle improvement suggestions and meal suggestions based on the updated life log.

[1523] Input: Revised and added life log, emotional data, and dietary data.

[1524] Output: Generated lifestyle improvement suggestions and dietary suggestions.

[1525] Specific operation: The server uses an AI model (e.g., TensorFlow or PyTorch) to analyze the accumulated data and life logs, and generates lifestyle improvement and dietary suggestions. The suggestions are then notified to the user via their device.

[1526] Examples:

[1527] A user eats yogurt at 8:00 AM and feels it is "delicious." The device collects data along with the user's emotion. This data is sent to the server, and the life log records "8:00 Breakfast Yogurt Delicious." Based on this information, the server makes a suggestion: "We recommend eating yogurt for breakfast next time."

[1528] Examples of prompt statements

[1529] text

[1530] Use user ID 123's food and sentiment data from the past week to generate personalized suggestions for their next meal. The user is experiencing multiple periods of high stress. The suggestions should include healthy meals appropriate for these times and ingredients that are good for reducing stress.

[1531] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1532] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1533] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1534] [Fourth embodiment]

[1535] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1536] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1537] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1538] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1539] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1540] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1541] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1542] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1543] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1544] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1545] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1546] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1547] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1548] The present invention is a system that records the user's daily life and suggests lifestyle improvements based on the data. This system is composed of a terminal, a server, and user interactions.

[1549] Overall system overview

[1550] 1. Data collection

[1551] The device acquires the user's location information, health information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health app, payment app, browser, etc.). This data is collected periodically and formatted in JSON format.

[1552] 2. Data transmission

[1553] The device compiles the collected data into JSON format and sends it to the server along with the user's identification information (user ID). The server receives this information and analyzes it.

[1554] 3. Data accumulation

[1555] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and suggest lifestyle improvements.

[1556] 4. Generating a life log

[1557] The server analyzes the accumulated data and automatically generates a life log for the user, which is a history of the user's daily activities and behavior and is provided to the user via their device.

[1558] 5. Additions and corrections by users

[1559] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[1560] 6. Generating lifestyle improvement proposals

[1561] The server uses AI to generate lifestyle improvement suggestions based on the user's accumulated data and life log. These suggestions include health habit suggestions, exercise advice, and suggestions for improving dietary habits. The generated suggestions are notified to the user via their device.

[1562] Explanation of program processing

[1563] Terminal handling

[1564] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. All of this data is formatted into JSON and sent to the server.

[1565] Server Processing

[1566] The server receives JSON-formatted data sent from the device and accumulates the data for each user ID. The accumulated data is analyzed as appropriate, and a life log is automatically generated. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and updated life log, and notifies the device.

[1567] User Action

[1568] Users can review their life logs displayed on their devices and reflect on their lives. They can make additions or corrections as needed to make the life logs more detailed and accurate. Users can also refer to suggestions for lifestyle improvements from the server and review their health habits and improve the quality of their lives.

[1569] Specific examples

[1570] For example, if a user goes jogging in the park at 8:00 in the morning, the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and health app and sends them to the server. The server analyzes this information and automatically records it in the user's life log as "Jogging in the park at 8:00." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. Then, using AI, it generates lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining your health," and notifies the user.

[1571] This system allows users to effortlessly reflect on their daily lives and obtain hints for improving their lifestyle habits. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably reflect on their own behavior and helps improve the quality of their lives.

[1572] The processing flow will be explained below.

[1573] Step 1:

[1574] The device uses a GPS sensor to obtain the user's current location. It also collects health information such as the number of steps taken and heart rate from a health app, purchase history and amount spent information from a payment app, and obtains the user's search information from the browser's search history, as well as current weather information from a weather app or API.

[1575] Step 2:

[1576] The device formats the location, health, payment, search, and weather information into a single JSON object, including the user ID, ready to be sent to the server later.

[1577] Step 3:

[1578] The device creates a POST request to send a JSON object to the server and sends it to the specified server URL. If the transmission is successful, the device notifies the user of this information.

[1579] Step 4:

[1580] The server receives the POST request sent from the device. The received data is analyzed and stored in a database for each user ID. The stored data will be used to generate future life logs and propose lifestyle improvements.

[1581] Step 5:

[1582] The server periodically generates a user's life log based on the accumulated data. The life log includes a history of the user's daily activities and behavior. The generated life log is then sent to the device.

[1583] Step 6:

[1584] The user checks the life log displayed on the device. The life log displays a detailed record of the user's daily activities. The user can add or edit the life log as needed.

[1585] Step 7:

[1586] After the user adds or modifies the lifelog, the device sends the information back to the server as a JSON object. The server receives the modified lifelog and updates the database.

[1587] Step 8:

[1588] The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and the revised life log. The generated suggestions include specific health habits and lifestyle advice.

[1589] Step 9:

[1590] The server formats the generated lifestyle improvement proposals in JSON format and sends them to the device, which receives them and notifies the user.

[1591] Step 10:

[1592] Users can check the lifestyle improvement suggestions displayed on their devices and take actions to improve the quality of their daily lives. Users can refer to the suggestions and review their health and lifestyle habits.

[1593] These are the specific processing steps of the program, which allow the user to reflect on their daily life and receive specific suggestions for improving the quality of their life.

[1594] Example 1

[1595] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1596] Conventional systems that record daily life and suggest lifestyle improvements often require time-consuming data collection, storage, and analysis, or are insufficient. Furthermore, users often have to spend time checking and editing their own life logs, which results in poor accuracy in lifestyle improvement suggestions. This makes the introduction and use of such systems particularly difficult for elderly users and those with memory impairments.

[1597] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1598] In this invention, the server

[1599] A means for the terminal to acquire user location information, health status information, transaction information, search history, and weather information from a plurality of sensors and software;

[1600] a server receiving the acquired data and storing the data for each user;

[1601] A means for the server to automatically generate a life record of the user based on the accumulated data;

[1602] A server generates lifestyle improvement suggestions based on the user's lifestyle records;

[1603] A means for the terminal to format the acquired data into a JSON format and transmit the formatted data to a server;

[1604] A means for a server to analyze the JSON format data and generate a life record of the user;

[1605] A means for the server to analyze the accumulated data and life records using AI and generate improvement suggestions;

[1606] This includes:

[1607] Users can effortlessly record their daily lives, easily add to and edit their life logs, and even receive highly accurate lifestyle improvement suggestions based on the accumulated data.

[1608] A "terminal" is an information processing device equipped with multiple sensors and software for collecting data on the user's daily life.

[1609] A "sensor" is a device that measures physical environmental information, and in this system includes GPS sensors, health status sensors, weather sensors, etc.

[1610] "Software" refers to a program that is installed on a device and performs a specific function, such as a healthcare app, a payment app, or a browser.

[1611] "Location Information" means data that indicates a user's geographic location and is collected by a GPS sensor.

[1612] "Health status information" is data related to the user's health, and includes information such as the number of steps taken, heart rate, and calorie consumption.

[1613] "Transaction information" is data related to a user's purchasing activities, including purchase history obtained from a payment app.

[1614] "Search history" is the history of searches a user has performed on the Internet, and is data obtained from a browser.

[1615] "Weather information" refers to data related to the weather, obtained from weather apps and weather sensors.

[1616] A "life log" is data that records the history of a user's daily activities and behavior, and is automatically generated by a server.

[1617] "Lifestyle improvement suggestions" are suggestions for improving the quality of life that are generated based on the user's life log and accumulated data.

[1618] The "JSON format" is a format used to structurally represent data and communicate between servers and terminals.

[1619] "AI" refers to artificial intelligence, a technology that analyzes accumulated data and generates lifestyle improvement suggestions.

[1620] This invention relates to a system that records a user's daily life and makes suggestions for improving their lifestyle based on the data. This system is composed of a terminal, a server, and user interactions.

[1621] System configuration

[1622] 1. Terminal configuration and operation

[1623] The device collects various data about the user using multiple built-in sensors (e.g., GPS sensor, health condition sensor) and installed software (e.g., healthcare app, payment app, browser). Specifically, the device collects the following data:

[1624] Location information using a GPS sensor

[1625] Health status information such as steps taken, heart rate, and calorie consumption via the Health app

[1626] Transaction information (purchase history) from payment apps

[1627] Browser search history

[1628] Weather information from weather apps and weather sensors

[1629] This collected data is obtained at regular intervals and formatted into JSON format.

[1630] 2. Data transmission

[1631] The device periodically converts the collected data into JSON format and sends it to the server along with the user ID. This transmission is performed every 15 minutes, and the HTTPS protocol is used to maintain data integrity.

[1632] 3. Server Configuration and Operation

[1633] The server receives and analyzes the JSON format data sent from the device. The received data is stored in a database for each user ID, and each record also includes a timestamp for the data.

[1634] The server periodically analyzes the accumulated data and automatically generates a record of the user's daily life (life log). The life log records the user's daily activities and behavior. The server then uses AI to generate lifestyle improvement suggestions based on the accumulated data and the latest life log, and notifies the device.

[1635] 4. User Operation

[1636] Users can check the lifelog displayed on their device and reflect on their daily lives. They can add or edit the lifelog as needed, which improves its accuracy. Data added or edited by the user is sent back to the server, and the lifelog is updated.

[1637] Specific examples

[1638] For example, if a user goes jogging in the park at 8:00 a.m., the device obtains location information from the GPS sensor and jogging data (distance, time, heart rate) from the health app, then compiles this into a JSON file and sends it to the server. The server analyzes the received data and automatically records "Jogging in the park at 8:00" in the user's life log. If the user checks this life log and adds "That was a great run!", this information is also sent to the server and the life log is updated. The server then uses AI to generate lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and notifies the user via the device.

[1639] Prompt Sentence Examples

[1640] "If the user has the habit of jogging every morning, explain how jogging three times a week can help them stay healthy."

[1641] In this way, users can effortlessly review their daily lives, receive highly accurate suggestions for lifestyle improvements, and improve their quality of life. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably review their own actions, helping to improve their quality of life.

[1642] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1643] Step 1: Collect data

[1644] Terminal handling

[1645] The device collects user data using various sensors and software: location information from the GPS sensor, step count and heart rate from health apps, purchase history from payment apps, search history from the browser, and weather information from weather apps.

[1646] Input: Data obtained from GPS sensor, health app, payment app, browser, and weather app

[1647] Data processing: Acquire raw data from each sensor and app and format it into JSON format.

[1648] Output: JSON format data

[1649] How it works: Every 15 minutes, the device retrieves new data from each sensor and app, consolidates it, and generates a JSON file.

[1650] Step 2: Sending data

[1651] Terminal handling

[1652] The data collected by the device is formatted in JSON and sent to the server along with the user ID.

[1653] Input: Formatted JSON data and user ID

[1654] Data processing: Encoding to maintain data integrity

[1655] Output: HTTPS request to the server

[1656] Specific operation: Every 15 minutes, the device makes an HTTPS request to the server and sends data in JSON format along with the user ID.

[1657] Step 3: Accumulate data

[1658] Server Processing

[1659] The server analyzes the received JSON format data and stores it in a database for each user ID.

[1660] Input: JSON format data sent from the terminal

[1661] Data processing: Parse the JSON data, extract each data item, and store it in the database.

[1662] Output: Data stored in the database

[1663] Specific operation: The server first stores the received data in temporary memory and then writes it to the database sequentially.

[1664] Step 4: Generating a Lifelog

[1665] Server Processing

[1666] The server periodically analyzes the accumulated data and automatically generates a life log for the user.

[1667] Input: Data stored for each user

[1668] Data processing: Perform time series analysis of the data and compile it into a history of the user's daily behavior.

[1669] Output: Life log

[1670] Specific operation: The server runs a job every day at midnight, analyzes data from the past 24 hours, generates a "life log," and stores it in a database.

[1671] Step 5: User additions and modifications

[1672] User Action

[1673] Users can check their lifelog and add or edit it as needed.

[1674] Input: Lifelog displayed on the device

[1675] Data processing: Form input processing to support user additions and corrections

[1676] Output: Modified lifelog

[1677] Specific operation: When a user opens the app on their device, displays their life log, and adds "I ate bread for breakfast," the information is sent to the server in JSON format and the life log database is updated.

[1678] Step 6: Generate life improvement proposals

[1679] Server Processing

[1680] The server uses AI to generate lifestyle improvement suggestions based on the accumulated data and life logs, and these suggestions are sent to the user via their device.

[1681] Input: User's accumulated data and life log

[1682] Data processing: Generate lifestyle improvement suggestions through analysis and pattern recognition using AI models

[1683] Output: Lifestyle improvement suggestions

[1684] Specific operation: The server runs the AI ​​model at 1 a.m. every day, analyzes the data, generates suggestions such as "It is recommended to jog three times a week," and notifies the user via the device.

[1685] (Application example 1)

[1686] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1687] In modern society, users are expected to improve their daily lifestyle habits and maintain their health. However, manually recording and analyzing their daily life data to find improvement measures is a very time-consuming process. For this reason, there is a need for a system that automatically collects, stores, and analyzes users' daily life data to provide lifestyle improvement suggestions. Furthermore, to improve the accuracy of lifestyle improvement suggestions, it is necessary to use generative AI models to perform more advanced analysis based on diverse data.

[1688] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1689] In this invention, the server includes: means for the terminal to acquire user location information, healthcare information, payment information, search information, and weather information from multiple sensors and applications; means for the server to receive the acquired data and accumulate the data for each user; means for the server to automatically generate a user's life log based on the accumulated data; means for the server to generate lifestyle improvement suggestions based on the user's life log; and means for generating prompt sentences and requesting analysis by a generative AI model to improve the accuracy of the lifestyle improvement suggestions. This allows users to easily collect and accumulate data about their daily lives and perform advanced analysis using AI, enabling them to receive highly accurate lifestyle improvement suggestions.

[1690] A "terminal" is an electronic device used to collect data from a user's daily life, and is equipped with multiple sensors and applications.

[1691] A "sensor" is a device that detects a physical phenomenon (e.g., position, movement, temperature, etc.) and converts it into digital data.

[1692] An "application" is a software program that runs on a terminal to provide a specific function or service.

[1693] "Location Information" means geographic location data of a user obtained using a GPS sensor.

[1694] "Healthcare information" refers to data related to health status and physical activity, including, for example, the number of steps taken and heart rate.

[1695] "Payment information" is data related to the purchase and payment history of a user.

[1696] "Search Information" is data about search queries performed by users on the Internet and their history.

[1697] "Weather information" is data about the weather conditions at the user's location.

[1698] A "server" is a computer system that receives, stores, and analyzes data sent from a terminal.

[1699] "Data storage" is the process of organizing collected data and storing it for later analysis and reuse.

[1700] A "life log" is digital data that records the history of a user's daily actions and activities.

[1701] "Lifestyle improvement suggestions" are specific advice and recommendations for improving lifestyle habits based on the user's life log.

[1702] A "prompt" is an instruction entered into a generative AI model to make it perform a specific task.

[1703] A "generative AI model" is an artificial intelligence algorithm used to analyze data using machine learning to generate insights and recommendations.

[1704] The present invention is a system that records the user's daily life and suggests lifestyle improvements based on the data. This system is composed of a terminal, a server, and user interactions.

[1705] 1. Data collection

[1706] The device acquires the user's location information, health information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health app, payment app, browser, etc.). The collected data is periodically formatted into JSON format.

[1707] 2. Data transmission

[1708] The data collected by the device is compiled in JSON format and sent to the server along with the user's identification information (user ID). The server receives and analyzes this data.

[1709] 3. Data accumulation

[1710] The server stores the received data in a database for each user ID. The stored data will be used to generate a life log and suggest lifestyle improvements.

[1711] 4. Generating a life log

[1712] The server analyzes the accumulated data and automatically generates a life log for the user, which records the user's daily activities and behavioral history and is provided to the user via their device.

[1713] 5. Additions and corrections by users

[1714] The user can check the lifelog displayed on the device and add or modify it as needed. The added or modified lifelog is then sent back to the server and updated.

[1715] 6. Generating lifestyle improvement proposals

[1716] The server uses a generative AI model to generate lifestyle improvement suggestions based on the user's accumulated data and life log. These suggestions include health habit suggestions, exercise advice, and suggestions for improving dietary habits. The generated suggestions are notified to the user via their device.

[1717] 7. Improved accuracy with generative AI models

[1718] The server then generates a prompt and requests the generative AI model to analyze it. This prompt includes the user's life log and collected data. The generative AI model provides analysis results that improve the accuracy of lifestyle improvement suggestions.

[1719] Hardware / Software used

[1720] Hardware: Smartphone

[1721] Software: Python, HTTP API (communication with server), generative AI model

[1722] Data processing / calculation: Data collection, formatting into JSON format, advanced analysis using AI

[1723] Specific examples

[1724] For example, if a user goes jogging in the morning, the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and healthcare app and sends them to the server. The server analyzes this information and automatically records it in the user's life log as "Jogging in the park at 8:00." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. The generative AI model is then used to generate lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and notifies the user.

[1725] Prompt Sentence Examples

[1726] "Analyze the following data to generate suggestions to improve the user's life:

[1727] GPS data: 35.6895, 139.6917, "jogging"

[1728] Health data: Steps: 3000, Heart rate: 120

[1729] Payment Data: Purchase: None

[1730] Search data: None

[1731] Weather data: Sunny, Temperature: 15

[1732] Please offer some advice on how to improve your life."

[1733] This system allows users to effortlessly reflect on their daily lives and receive specific advice on how to improve their lifestyle habits.

[1734] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1735] Step 1:

[1736] The device collects the user's location, health, payment, search, and weather information from multiple sensors and applications. Data obtained from sensors and applications includes location information from the GPS sensor, step count and heart rate records from the health app, purchase history from the payment app, browser search history, and weather information from the weather app. This data is temporarily stored on the device.

[1737] input:

[1738] Data from multiple sensors and applications

[1739] output:

[1740] Temporarily stored data on the device

[1741] Step 2:

[1742] The data collected by the device is periodically formatted into JSON format. The collected location information, health information, payment information, search information, weather information, etc. are compiled into a single JSON object, along with the user ID.

[1743] input:

[1744] Temporarily saved data

[1745] output:

[1746] Integration data in JSON format

[1747] Step 3:

[1748] The device sends formatted JSON data to the server using an HTTP POST request to send the data to the server's API endpoint. The server receives this request and prepares to parse the data.

[1749] input:

[1750] Integration data in JSON format

[1751] output:

[1752] Data sent to the server

[1753] Step 4:

[1754] The server receives the data sent from the device and stores it in a database for each user, allowing data associated with each user to be permanently stored and used for later analysis.

[1755] input:

[1756] Data sent to the server

[1757] output:

[1758] Accumulated data in the database

[1759] Step 5:

[1760] The server analyzes the accumulated data and automatically generates a life log for the user. It compares past data with newly added data to generate a life log that summarizes the user's daily activities and health status in chronological order. The generated life log is then saved back into the database.

[1761] input:

[1762] Accumulated data in the database

[1763] output:

[1764] Automatically generated lifelog

[1765] Step 6:

[1766] The server sends the generated lifelog to the device and provides it to the user. The user can check their own lifelog on the device and add or modify it as necessary.

[1767] input:

[1768] Automatically generated lifelog

[1769] output:

[1770] Life log presentation data

[1771] Step 7:

[1772] After the user adds or modifies the lifelog, the device sends the modified lifelog back to the server, which then updates the database with the modified lifelog.

[1773] input:

[1774] Modified Lifelog

[1775] output:

[1776] Updated database

[1777] Step 8:

[1778] The server generates lifestyle improvement proposals using a generative AI model based on the updated life log and accumulated data. The server generates prompt statements and requests the generative AI model to analyze them. Based on the analysis results of the generative AI model, highly accurate lifestyle improvement proposals are created.

[1779] input:

[1780] Updated lifelog and accumulated data

[1781] output:

[1782] Generated lifestyle improvement proposals

[1783] Step 9:

[1784] The server sends the generated lifestyle improvement suggestions to the terminal, and the user receives the lifestyle improvement suggestions via the terminal and makes lifestyle improvements based on them.

[1785] input:

[1786] Generated lifestyle improvement proposals

[1787] output:

[1788] User notification data

[1789] Prompt Sentence Examples

[1790] "Analyze the following data to generate suggestions to improve the user's life:

[1791] GPS data: 35.6895, 139.6917, "jogging"

[1792] Health data: Steps: 3000, Heart rate: 120

[1793] Payment Data: Purchase: None

[1794] Search data: None

[1795] Weather data: Sunny, Temperature: 15

[1796] Please offer some advice on how to improve your life."

[1797] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1798] This invention combines an emotion engine with a system that records a user's daily life and makes suggestions for lifestyle improvements based on that data. This system is composed of a terminal, a server, and an engine that handles user interaction and emotion recognition.

[1799] Overall system overview

[1800] 1. Data collection

[1801] The device acquires the user's location information, health care information, payment information, search information, and weather information from multiple sensors and applications (e.g., GPS sensor, health care app, payment app, browser, etc.). In addition, the device's built-in emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[1802] 2. Data transmission

[1803] The device collects location information, health information, payment information, search information, weather information, and emotion data, and then compiles them into JSON format and sends them along with the user ID to the server. The server receives this information and analyzes it.

[1804] 3. Data accumulation

[1805] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[1806] 4. Generating a life log

[1807] The server analyzes the accumulated data and automatically generates a life log for the user, which includes the user's daily activities, behavioral history, and emotional state. The generated life log is provided to the user via their device.

[1808] 5. Additions and corrections by users

[1809] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[1810] 6. Generating lifestyle improvement proposals

[1811] The server uses AI to generate lifestyle improvement suggestions based on the user's accumulated data and life log. Taking into account the user's emotional data in particular, the server generates personalized suggestions based on their emotional state. The generated suggestions are then sent to the user via their device.

[1812] Explanation of program processing

[1813] Terminal handling

[1814] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. Furthermore, an emotion engine analyzes the user's facial expressions and voice tone to generate emotion data. All of this data is formatted in JSON format and sent to the server.

[1815] Server Processing

[1816] The server receives JSON-formatted data sent from the device and stores it in a database for each user ID. The stored data is analyzed as appropriate, and a life log is automatically generated. The generated life log records the user's emotional state along with their activity history. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI to generate lifestyle improvement suggestions based on the stored data and updated life log, and notifies the device. The suggestions take emotional data into consideration and include advice that fits the user's psychological state.

[1817] User Action

[1818] Users can check the life log displayed on their device and review their daily activity records. They can add or edit the life log as needed to make the record more detailed and accurate. Users can refer to the lifestyle improvement suggestions from the server and review their health and lifestyle habits. In particular, suggestions based on emotional data provide specific advice that is tailored to the user's psychological state.

[1819] Specific examples

[1820] For example, if a user goes jogging in the park at 8:00 a.m., the device obtains location information and jogging data (distance, time, heart rate) from the GPS sensor and health app, and then uses the emotion engine to recognize the user's emotion of "comfortable" from their facial expressions and voice. This data is sent to the server, which analyzes it and automatically records it in the user's life log as "8:00 Jogging in the park, comfortable." If the user checks this life log and adds, "That was a great run!", the server updates and stores this information. Then, using AI, the device generates lifestyle improvement suggestions, such as "Jogging three times a week is effective for maintaining health," and provides specific exercise advice based on the user's comfortable jogging experience.

[1821] This system allows users to effortlessly reflect on their daily lives and receive suggestions for lifestyle improvements that reflect their emotional state. This is particularly useful for elderly people and those with memory impairments, as it allows them to easily and enjoyably reflect on their own actions and emotions, helping to improve the quality of their lives.

[1822] The processing flow will be explained below.

[1823] Step 1:

[1824] The device uses the GPS sensor to obtain the user's current location, collects health information such as the number of steps taken and heart rate from the health app, and obtains purchase history and payment amount information from the payment app.

[1825] Step 2:

[1826] The device retrieves the user's search keywords and visited websites from the browser's search history, and also retrieves the current day's weather information from weather apps and APIs.

[1827] Step 3:

[1828] The device's emotion engine captures the user's facial expressions with a camera and records their voice with a microphone, and analyzes them to generate emotion data (e.g., happiness, anger, sadness, etc.).

[1829] Step 4:

[1830] The device formats the collected location, health, payment, search, weather, and emotion data into a single JSON object, which also includes the user ID.

[1831] Step 5:

[1832] The device creates a POST request to send the formatted JSON object to the server, sends it to the specified server URL, and notifies the user of the status if the transmission is successful.

[1833] Step 6:

[1834] The server receives the POST request sent from the device and analyzes the data. The received data is stored in a database for each user ID. This stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[1835] Step 7:

[1836] The server periodically generates a user's life log based on the accumulated data. The life log includes the user's daily activities, behavioral history, and emotional state. The generated life log is formatted in JSON format and sent to the device.

[1837] Step 8:

[1838] The user checks the life log displayed on the device. The life log displays a detailed account of the user's daily activities, behaviors, and emotional state. The user can add or edit the life log as needed.

[1839] Step 9:

[1840] The device reformats the lifelog that the user has added or modified into JSON format and sends it to the server. The server receives the modified lifelog and updates the database.

[1841] Step 10:

[1842] The server generates lifestyle improvement suggestions based on the accumulated data and the revised life log, using AI to take into account the user's emotional data and generate specific suggestions based on their emotions.

[1843] Step 11:

[1844] The server formats the generated lifestyle improvement proposals in JSON format and sends them to the device, which receives them and notifies the user.

[1845] Step 12:

[1846] Users can check the lifestyle improvement suggestions displayed on the device and improve their daily habits and behaviors based on them. For example, they receive specific advice such as how to maintain health by continuing to jog or how to reduce stress.

[1847] As a concrete example, consider the case where a user goes jogging in the park at 8:00 in the morning. The device obtains location information and jogging-related data (distance, time, heart rate) from the GPS sensor and health care app, and the emotion engine recognizes the emotion of "comfortable" from the user's facial expressions and voice. This data is sent to the server, analyzed, and automatically recorded in the life log as "8:00 Jogging in the park, comfortable." If the user checks this life log and adds "I had a great run!", the server updates and stores this information. Then, using AI, it generates lifestyle improvement suggestions such as "Jogging three times a week is effective for maintaining health" and provides specific exercise advice.

[1848] The above is a specific embodiment of the present invention. This system allows users to easily record their actions and emotions and receive specific suggestions for improving their quality of life. In particular, by using an emotion engine, it is possible to provide advice that fits the user's psychological state.

[1849] Example 2

[1850] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1851] Conventional lifelog systems have the problem of not being able to fully reflect a user's daily activities and emotional state. Furthermore, their lifestyle improvement suggestions do not take into account the user's emotional state, resulting in low user satisfaction and implementation rates. Furthermore, the process of collecting and analyzing data is cumbersome, often causing users to feel overwhelmed.

[1852] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1853] In this invention, the server includes: a terminal that acquires a user's location information, health information, purchase information, search information, and weather information from multiple sensors and software; a terminal that analyzes a user's facial expressions and voice tone and generates emotion data; a terminal that formats the acquired data into JSON format and transmits it to the server; a server that receives the acquired data and accumulates the data for each user; a server that automatically generates a user's life log based on the accumulated data; and a server that generates lifestyle improvement suggestions using a generative AI model based on the user's life log. This makes it possible to collect and analyze a user's comprehensive activity and emotion data and provide lifestyle improvement suggestions based on the user's individual emotional state.

[1854] A "terminal" is an electronic device equipped with multiple sensors and software for collecting a user's location information, health information, purchase information, search information, weather information, and emotional data.

[1855] A "server" is a computer system that receives, stores, and analyzes data sent from a terminal.

[1856] A "sensor" is an electronic device that collects environmental or biometric information, such as a user's location or physiological data.

[1857] "Software" refers to application programs installed on the terminal that collect and format data.

[1858] "User location information" is data about the user's current location obtained using a GPS sensor.

[1859] "Health information" is data indicating the physiological state of the user, such as the number of steps taken and heart rate.

[1860] "Purchase information" is data related to the purchase history and transactions made by the user.

[1861] "Search information" refers to data related to the keywords and history of searches a user has performed on the Internet.

[1862] "Weather information" refers to weather forecasts and temperature information obtained based on the user's location.

[1863] "Emotion data" is data that indicates an emotional state generated by the terminal's emotion engine by analyzing the user's facial expressions and vocal tone.

[1864] The "JSON format" is a lightweight, text-based data exchange format for structuring and representing data.

[1865] A "user ID" is an identification code assigned to each user to uniquely identify them.

[1866] A "life log" is data that records a user's daily activity history and emotional state.

[1867] A "generative AI model" is an artificial intelligence algorithm that generates lifestyle improvement suggestions based on collected data.

[1868] "Lifestyle Improvement Suggestions" provides advice to improve the user's lifestyle habits based on the user's life log and emotional data.

[1869] The present invention is a system for providing suggestions to improve a user's life. This system records the user's daily life and makes suggestions to improve their life based on that data. The system is mainly composed of a terminal, a server, and an engine that handles user interaction and emotion recognition.

[1870] Specific configuration

[1871] Terminal

[1872] The device collects data using various sensors and applications, including GPS sensors, health management software, payment applications, web browsers, and emotion engines. For example, consider a device that implements the following measures:

[1873] Location information: Uses a GPS sensor to obtain real-time user location information.

[1874] Health information: We collect health data such as your steps and heart rate from health management software (e.g., Apple Health, Google Fit).

[1875] Purchase information: Obtain purchase history from a payment application (e.g., a general-purpose payment system).

[1876] Search information: Obtain search history from web browsers (e.g., general-purpose browsers).

[1877] Emotion data: The emotion engine analyzes the user's facial expressions and vocal tone to generate emotion data.

[1878] All collected data is formatted in JSON and sent to the server.

[1879] server

[1880] The server receives the JSON format data sent from the device and accumulates the data for each user. Specifically, the data is saved for each user ID using a database (e.g., a general-purpose database management system). The accumulated data is analyzed, and the user's life log is automatically generated.

[1881] The generated life log includes the user's emotional state along with their activity history. For example, the following life log may be generated:

[1882] 8:00 Jogging in the park, comfortable

[1883] 12:00 Buy coffee at the cafe

[1884] The server then uses a generative AI model (e.g., a general-purpose generative AI model) to generate lifestyle improvement suggestions based on the generated life log. The suggestions take into account the user's emotional data and include specific advice that matches the user's psychological state. For example, a suggestion such as "Jogging three times a week is effective for maintaining health" may be generated.

[1885] User

[1886] The user can check the lifelog displayed on the device and make additions or corrections as necessary. The corrected lifelog is reformatted into JSON format and sent to the server. The server receives this information and updates the database. For example, if a user adds "That was a great run!" to the lifelog, this information is sent to the server and re-stored.

[1887] This allows users to effortlessly reflect on their daily lives and receive suggestions for lifestyle improvements that reflect their emotional state.It also helps elderly people and those with memory impairments to easily and enjoyably reflect on their actions and emotions, helping to improve the quality of their lives.

[1888] Examples of specific examples and prompts

[1889] For example, when a user goes jogging in the park at 8:00 in the morning, the device collects location information, health data (step count 5000, heart rate 70 BPM), and emotional data (comfortable), and sends them to the server in JSON format. The server analyzes this data and automatically records "8:00 Jogging in the park, comfortable" in the life log.

[1890] If the user checks this life log and adds, "That was a great run!", the server updates this information and uses AI to generate lifestyle improvement suggestions such as, "Jogging three times a week is effective for maintaining health." An example of such a prompt would be something specific like, "I want to increase the amount of exercise I do to stay healthy. What advice do you have?"

[1891] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1892] Step 1:

[1893] Data collection

[1894] Device operation: The device uses multiple sensors and software to obtain the user's location, health, purchase, search, and weather information. Specifically, the device obtains the user's current location (e.g., latitude 35.6895, longitude 139.6917) using a GPS sensor, and obtains the number of steps (e.g., 5,000 steps) and heart rate (e.g., 70 BPM) from health management software. It also obtains purchase history from the payment application and search history (e.g., weather forecast search) from the browser. It uses an emotion engine to analyze the user's facial expressions and voice tone and generate emotion data (e.g., "comfortable").

[1895] Input: User location information, health information, purchase information, search information, weather information, emotional data

[1896] Output: Formatted JSON data

[1897] Step 2:

[1898] Organizing and sending data

[1899] What the device does: It formats all the data collected by the device into JSON format. For example, it generates the following JSON object:

[1900] json

[1901] {

[1902] "userID": "12345",

[1903] "location": {"lat": 35.6895, "long": 139.6917},

[1904] "healthData": {"steps": 5000, "heartRate": 70},

[1905] "transactions": [{"time": "12:00", "item": "coffee"}],

[1906] "searchHistory": ["Weather Forecast"],

[1907] "emotion": "comfortable"

[1908] }

[1909] Input: Data obtained from various sensors and software

[1910] Output: JSON data to send to the server

[1911] Step 3:

[1912] Receiving and storing data

[1913] Server operation: The server receives the JSON format data sent from the device. It analyzes the received data and saves it in the database based on the user ID. For example, add the following record to the database:

[1914] json

[1915] {

[1916] "userID": "12345",

[1917] "location": {"lat": 35.6895, "long": 139.6917},

[1918] "healthData": {"steps": 5000, "heartRate": 70},

[1919] "transactions": [{"time": "12:00", "item": "coffee"}],

[1920] "searchHistory": ["Weather Forecast"],

[1921] "emotion": "comfortable"

[1922] }

[1923] Input: JSON data sent from the terminal

[1924] Output: User data stored in the database

[1925] Step 4:

[1926] Generating a life log

[1927] Server operation: The server automatically generates a user's life log based on the accumulated data. It aggregates the analyzed data and generates a content that describes the user's daily activity history and emotional state. For example, a life log such as "8:00 Jogging in the park, comfortable" may be generated.

[1928] Input: User data stored in the database

[1929] Output: Automatically generated lifelog

[1930] Step 5:

[1931] Checking, adding, and correcting life logs

[1932] User action: The user checks the life log displayed on the device and adds or corrects it as necessary. For example, to the entry "8:00 Jogging in the park, comfortable," the user adds "It was a great run!"

[1933] Input: Lifelog displayed on the device

[1934] Output: Added and corrected lifelog

[1935] Step 6:

[1936] Updating and re-accumulating life logs

[1937] Operation of the device and server: The added and corrected lifelog is reformatted into JSON format and sent to the server. The server receives it and updates the database.

[1938] Input: Added / modified lifelog

[1939] Output: Updated database

[1940] Step 7:

[1941] Generating lifestyle improvement proposals

[1942] Server operation: The server generates lifestyle improvement suggestions using a generative AI model based on accumulated data and the latest life log. In particular, it takes into account the user's emotional data and generates specific advice that fits the user's psychological state (e.g., "Jogging three times a week is effective for maintaining health").

[1943] Input: Updated lifelog and accumulated data

[1944] Output: Generated lifestyle improvement suggestions

[1945] Step 8:

[1946] Notification of lifestyle improvement proposals

[1947] Operation of the device and server: The generated lifestyle improvement suggestions are sent to the device, where the user can check them and apply them to their daily lives.

[1948] Input: Generated lifestyle improvement proposals

[1949] Output: Proposal posted to terminal

[1950] (Application example 2)

[1951] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1952] In modern life, users are seeking ways to reflect on and improve their lifestyles, but specific and personalized lifestyle improvement suggestions that take emotional data into account are lacking. In particular, it is difficult for users to obtain detailed suggestions about what kind of diet they should eat.

[1953] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1954] In this invention, the server includes: means for a terminal to acquire user location information, health care information, payment information, search information, and weather information from multiple sensors and applications; means for the server to receive the acquired data and accumulate data for each user; means for the server to automatically generate a life log for the user based on the accumulated data; means for the server to generate lifestyle improvement suggestions based on the user's life log; and means for the server to analyze the user's dietary content and diet-related emotional data and make individual dietary suggestions. This enables users to receive more specific and personalized dietary suggestions by making lifestyle improvements that take the emotional data into consideration.

[1955] A "terminal" is a device equipped with multiple sensors and applications that acquires user information and sends it to a server.

[1956] A "sensor" is a device that detects a user's location information, physical information, etc. and outputs it as digital data.

[1957] An "application" is a software program that runs on a terminal and obtains the user's healthcare information, payment information, search information, weather information, and the like.

[1958] "Location information" refers to data on a user's current location and movement history obtained through a GPS sensor or other means.

[1959] "Healthcare information" is data related to the user's health condition, including the number of steps taken and heart rate.

[1960] "Payment information" is data related to monetary transactions made by a user.

[1961] "Search information" is data relating to the search behavior of users on the Internet.

[1962] "Weather information" is data about the weather in the area where the user is located.

[1963] The "server" is a computer system that receives and stores data sent from the terminals, analyzes it, and generates lifestyle improvement proposals.

[1964] A "life log" is a history of a user's daily activities and behavior that is automatically generated based on data accumulated by a server.

[1965] "Lifestyle improvement suggestions" are advice for improving the user's lifestyle, generated by the server based on the user's life log and emotional data.

[1966] "Emotion data" is data generated by analyzing emotions from the user's facial expressions and voice.

[1967] "Meal details" is data related to meals taken by the user.

[1968] "Emotion data related to meals" is data that records the emotions felt by the user while eating.

[1969] "Dietary suggestions" are dietary advice provided individually by the server based on an analysis of the user's dietary content and emotional data related to the diet.

[1970] The present invention combines an emotion engine with a system that records a user's daily life and makes suggestions for improving their lifestyle based on that data. Specific embodiments of the present invention are described below.

[1971] System Overview

[1972] 1. Data collection

[1973] The device acquires the user's location, health care, payment, search, and weather information from multiple sensors and applications (e.g., GPS sensor, health care app, payment app, browser, etc.). The device's built-in emotion engine also analyzes the user's voice and facial expressions to generate emotion data. Furthermore, data on the user's diet and emotion related to the diet is also collected.

[1974] 2. Data transmission

[1975] The device collects location information, health information, payment information, search information, weather information, emotional data, meal contents, and emotional data related to meals, and compiles them into JSON format and sends them to the server along with the user ID. The server receives this information and analyzes it.

[1976] 3. Data accumulation

[1977] The server stores the received data in a database for each user ID. The stored data will be used to generate future life logs and make lifestyle improvement suggestions.

[1978] 4. Generating a life log

[1979] The server analyzes the accumulated data and automatically generates a life log for the user. The life log includes the user's daily activities and behavior history, emotional state, and diet history. The generated life log is provided to the user via the device.

[1980] 5. Additions and corrections by users

[1981] Users can check the lifelog displayed on their device and add or modify it as needed, making the lifelog more detailed and accurate. The added or modified lifelog is then sent back to the server and updated.

[1982] 6. Generating lifestyle improvement and dietary suggestions

[1983] The server uses AI to generate lifestyle improvement and meal suggestions based on the user's accumulated data and life log. Taking into account the user's emotional data in particular, the server generates personalized suggestions based on their emotional state. The generated suggestions are then sent to the user via their device.

[1984] Explanation of program processing

[1985] Terminal handling

[1986] The device collects data from various sensors and applications. For example, it obtains location information from the GPS sensor, step counts and heart rate from health apps, purchase history from payment apps, and search information from browser history. The emotion engine analyzes the user's facial expressions and tone of voice to generate emotion data. Food content and emotion-related data are also collected, and all of this data is formatted into JSON and sent to the server.

[1987] Server Processing

[1988] The server receives JSON-formatted data sent from the device and stores it in a database for each user ID. The stored data is analyzed as appropriate, and a life log is automatically generated. The generated life log records the user's activity history as well as their emotional state and dietary history. When the user checks the life log and makes additions or corrections, this information is also sent to the server, and the life log is updated. The server uses AI (e.g., TensorFlow or PyTorch) based on the stored data and updated life log to generate lifestyle improvement suggestions and dietary suggestions, and notifies the device. The suggestions take emotional data into consideration and include advice that fits the user's psychological state.

[1989] User Action

[1990] Users can check the life log displayed on their device and review their daily activity records. They can add or edit the life log as needed to make the record more detailed and accurate. Users can refer to lifestyle improvement and dietary suggestions from the server and review their health habits and eating habits. In particular, suggestions based on emotional data provide specific advice that is tailored to the user's psychological state.

[1991] Specific examples

[1992] For example, if a user eats yogurt for breakfast at 8:00 a.m. and thinks it's "delicious," the device collects the meal details and emotional data (emotions about how delicious it is). This data is sent to a server, which analyzes it and automatically records the user's life log as "8:00 Breakfast Yogurt Delicious." Based on this information, the server generates a specific meal suggestion, such as "We recommend you eat the same yogurt for breakfast next time," and notifies the user.

[1993] Examples of prompt statements

[1994] text

[1995] Use user ID 123's food and sentiment data from the past week to generate personalized suggestions for their next meal. The user is experiencing multiple periods of high stress. The suggestions should include healthy meals appropriate for these times and ingredients that are good for reducing stress.

[1996] The above is an embodiment of the present invention.

[1997] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1998] Step 1:

[1999] The device collects user data from multiple sensors and applications.

[2000] Input: Location information from the GPS sensor, step count and heart rate from the health app, purchase history from the payment app, search information from the browser history, and user voice, facial expressions, meal contents, and meal-related emotional data from the emotion engine.

[2001] Output: A JSON-formatted dataset of location, health, payment, search, weather, sentiment, and diet data.

[2002] Specific operation: The device acquires various information from sensors and applications in real time, and generates emotion data using the emotion engine. This data is then formatted and compiled in JSON format.

[2003] Step 2:

[2004] The terminal transmits the collected data to the server.

[2005] Input: A dataset in JSON format.

[2006] Output: The data sent to the server.

[2007] Specific operation: The terminal sends an HTTP request to the server via the Internet and transfers data in JSON format.

[2008] Step 3:

[2009] The server analyzes the received data and stores it in a database.

[2010] Input: JSON formatted data sent to the server.

[2011] Output: User data stored in a database.

[2012] Specific operation: The server parses the received JSON data and stores it in a database for each user ID. The data is stored appropriately using a database management system (e.g., MySQL or PostgreSQL).

[2013] Step 4:

[2014] The server generates a life log of the user based on the accumulated data.

[2015] Input: User data stored in a database.

[2016] Output: The generated lifelog.

[2017] What it does: The server runs scripts to retrieve user data from a database, aggregate and format the data, and generate a life log, which includes detailed logs by date and activity.

[2018] Step 5:

[2019] The user checks the life log and makes additions or corrections as necessary.

[2020] Input: The generated lifelog.

[2021] Output: Lifelog modified and added by the user.

[2022] Specific operation: The user views the life log through the application on the device and makes additions or modifications as necessary. The added or modified life log is sent back to the server and updated.

[2023] Step 6:

[2024] The server generates and provides lifestyle improvement suggestions and meal suggestions based on the updated life log.

[2025] Input: Revised and added life log, emotional data, and dietary data.

[2026] Output: Generated lifestyle improvement suggestions and dietary suggestions.

[2027] Specific operation: The server uses an AI model (e.g., TensorFlow or PyTorch) to analyze the accumulated data and life logs, and generates lifestyle improvement and dietary suggestions. The suggestions are then notified to the user via their device.

[2028] Examples:

[2029] A user eats yogurt at 8:00 AM and feels it is "delicious." The device collects data along with the user's emotion. This data is sent to the server, and the life log records "8:00 Breakfast Yogurt Delicious." Based on this information, the server makes a suggestion: "We recommend eating yogurt for breakfast next time."

[2030] Examples of prompt statements

[2031] text

[2032] Use user ID 123's food and sentiment data from the past week to generate personalized suggestions for their next meal. The user is experiencing multiple periods of high stress. The suggestions should include healthy meals appropriate for these times and ingredients that are good for reducing stress.

[2033] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2034] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2035] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2036] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2037] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2038] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2039] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2040] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2041] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2042] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2043] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2044] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2045] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2046] 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.

[2047] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2048] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2049] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for...

Claims

1. A means for the device to acquire user location information, health care information, payment information, search information, and weather information from multiple sensors and applications; a server receiving the acquired data and storing the data for each user; A means for the server to automatically generate a life log of the user based on the accumulated data; A means for the server to generate lifestyle improvement suggestions based on the user's life log; A system including:

2. A means for the terminal to format the acquired data into a JSON format and transmit the formatted data to a server; A means for a server to analyze the JSON format data and generate a life log of the user; The system of claim 1 , comprising:

3. A means by which the server allows the user to add or modify the user's life log; A server stores the corrected life log again and updates lifestyle improvement suggestions using AI; The system of claim 1 , comprising: This is the draft of the patent claims, which identify and clearly define the technical scope and innovative aspects of the system.

Images