System

Abstract

A system is provided.SOLUTION: This system includes a means for collecting the living information of a user, a means for analyzing the collected living information, a means for generating an optimal holiday plan on the basis of an analysis result, and a means for notifying the user of the generated holiday plan.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] Many people have trouble making plans for their holidays due to their busy daily lives, and as a result end up spending their holidays without feeling fulfilled. This invention aims to solve this problem by automatically providing optimal holiday plans based on the user's lifestyle information, enabling users to spend their holidays in a healthy and fulfilling manner both physically and mentally. [Means for solving the problem]

[0005] The present invention is a system that includes means for collecting a user's lifestyle information, means for analyzing the collected lifestyle information, means for generating an optimal holiday plan based on the analysis results, and means for notifying the user of the generated holiday plan. Specifically, the system automatically collects and analyzes the user's health information, exercise information, and schedule information to present a holiday plan that is best suited to the user's current condition. Furthermore, by collecting user feedback and using it to improve the accuracy of the generated holiday plan, it is possible to provide suggestions that are more suited to each individual user.

[0006] "Lifestyle information" is information related to the user's daily life, and is data including sleep time, heart rate, number of steps, calendar schedule, and the like.

[0007] "Health information" refers to information that indicates the user's physical health condition, and specifically refers to vital data such as sleep time and heart rate.

[0008] "Exercise information" is information related to the user's physical activity, and is data including the number of steps taken, exercise intensity, and the like.

[0009] "Schedule information" is information about the user's schedule, such as data about meetings and appointments extracted from a calendar application or the like.

[0010] The "means of collection" refers to a method or system for acquiring the user's lifestyle information, and has the function of automatically acquiring data from healthcare apps and calendar apps.

[0011] The "analyzing means" refers to a method or system for analyzing collected life information and evaluating the user's condition, and includes a data analysis module.

[0012] The "holiday plan" is a proposal for the user to spend their weekends, holidays, and other holidays in a fulfilling way, and is a plan that recommends exercise, relaxation, time with family, and the like.

[0013] The "notification means" refers to a method or system for notifying the user of the generated holiday plan, and includes a notification function and an interface.

[0014] "Feedback" refers to the user's evaluation and opinions of the holiday plan they have implemented, and is data that will be used to improve the accuracy of future suggestions.

[0015] "Improved accuracy" refers to increasing the accuracy of the system's suggestions based on collected feedback, with the aim of providing plans that are more suited to each user's individual needs. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

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

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

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

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0031] 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.

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

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] System Overview

[0038] The present invention is a system for generating optimal holiday plans based on a user's lifestyle information and notifying the user of the plans. The system includes a user terminal, a server, and a network over which these communicate.

[0039] User device functions

[0040] Data collection

[0041] The user device will connect to various healthcare and calendar apps to collect weekday lifestyle information. Through this connection, the following data will be automatically collected:

[0042] sleep time

[0043] Heart rate

[0044] Step count

[0045] Calendar events

[0046] Data transmission

[0047] The collected data is sent to a server at regular intervals. This communication is secure, protecting user privacy.

[0048] Server Features

[0049] Data reception

[0050] The server receives the data sent from the user terminal and stores it in an internal database.

[0051] Data analysis

[0052] The server analyzes the collected data, which may include the following elements:

[0053] Is your average sleep time sufficient?

[0054] Is there any abnormality in your heart rate?

[0055] Is the amount of exercise enough?

[0056] Overscheduling and balance

[0057] Plan Generation

[0058] Based on the results of the data analysis, the server generates the optimal holiday plan for the user, which may include:

[0059] If you're not feeling well: Watch a movie or relax in a hot spring

[0060] If you are not getting enough exercise: Walking in a nearby park or using sports facilities

[0061] If you don't have much time with your family: Day camping or picnics

[0062] notification

[0063] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time, including specific activities and recommended locations and times.

[0064] User Feedback

[0065] Feedback collection

[0066] After the user implements the proposed plan, the user device collects feedback, for example, by displaying a question such as "Was this plan helpful?"

[0067] Send Feedback

[0068] The feedback provided by the user is sent to the server and stored in a database.

[0069] Improved accuracy

[0070] The server then uses the collected feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions. This cycle allows the server to continually provide plans that better suit the user's needs.

[0071] Specific examples

[0072] Example 1: Lack of exercise

[0073] The user's device collects data on weekdays and sends it to the server indicating that the user is not exercising much. The server receives and analyzes this data and suggests walking in a nearby park on the weekend. The user receives a notification from the device and actually goes for a walk. The user then provides feedback at a later date, which the server uses to improve the accuracy of its next suggestions.

[0074] Example 2: Family time

[0075] The user's device sends information from the user's calendar indicating that they have little time to spend with their family to the server. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback. Based on this feedback, the server adjusts the next suggestion more appropriately.

[0076] The present invention allows users to have a fulfilling holiday by being offered an optimal holiday plan based on their weekday lifestyle information, which helps them maintain a healthy state of mind and body.

[0077] The processing flow will be explained below.

[0078] Step 1:

[0079] The user's device automatically collects information about their weekday lifestyle. Specifically, it connects with a healthcare app to obtain data on sleep time, heart rate, and number of steps taken. It also obtains schedule information from a calendar app.

[0080] Step 2:

[0081] The user device periodically sends the collected data to the server, including the amount of sleep each day, average heart rate, number of steps taken, and schedule details.

[0082] Step 3:

[0083] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the consistency and completeness of the data are verified.

[0084] Step 4:

[0085] The server launches a data analysis module to analyze the received data, which evaluates whether the person is getting enough sleep, has an abnormal heart rate, is exercising enough, or has an overscheduled schedule.

[0086] Step 5:

[0087] The server generates an optimal holiday plan based on the results of the data analysis. Specifically, it suggests relaxing activities for users who are sleep-deprived, recommended exercise activities for users who are not getting enough exercise, and stress-relieving activities for users who have a busy schedule.

[0088] Step 6:

[0089] The server sends the generated holiday plan to the user's device, along with detailed information such as the specific contents of the plan, location, and time.

[0090] Step 7:

[0091] The user's device displays the holiday plan received from the server, and also notifies the user of the proposal using the notification function.

[0092] Step 8:

[0093] The user carries out the proposed plan, and after spending the holiday, the user's device collects feedback.

[0094] Step 9:

[0095] The user terminal sends the collected feedback to the server, including the usefulness and satisfaction of the suggestions.

[0096] Step 10:

[0097] The server analyzes the received feedback and adjusts and improves the holiday plan generation algorithm for future trips. This feedback cycle allows the server to provide a plan that is more suitable for the user.

[0098] Example 1

[0099] 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."

[0100] In modern life, there is a demand for a means to automatically suggest holiday plans that are suited to each individual's health condition and lifestyle. However, existing systems have difficulty effectively collecting and analyzing users' lifestyle information and providing optimal holiday plans for each individual. Furthermore, the accuracy of suggestions is limited due to a lack of functionality to continuously improve the system based on user feedback.

[0101] 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.

[0102] In this invention, the server includes means for periodically transmitting the user's lifestyle information to the server, means for the server to store the transmitted lifestyle information in a database, means for analysing the lifestyle information using a data analysis algorithm and assessing the user's condition, means for generating an optimum holiday plan based on the analysis results, means for transmitting and notifying the user of the generated holiday plan to a user terminal, and means for collecting user feedback and improving the analysis algorithm. This makes it possible to provide specific and accurate holiday plans suited to the user's individual health condition and lifestyle rhythm.

[0103] "User's lifestyle information" is data related to the user's daily life, and includes health information, exercise information, and schedule information.

[0104] The term "fixed cycle" refers to a preset time interval, such as a daily or weekly cycle.

[0105] "Server" refers to a computer system for receiving, storing, and analyzing data sent from a user terminal.

[0106] "Database" refers to an information management system used by a server to store users' life information.

[0107] "Data analysis algorithm" refers to a series of calculation methods used by the server to analyze the user's lifestyle information and evaluate the user's condition.

[0108] A "holiday plan" refers to a plan that suggests activities that are optimal for the user's health condition and lifestyle based on the analysis results.

[0109] A "user terminal" refers to a device used by a user, such as a smartphone or PC, that is capable of communicating with a server.

[0110] "Feedback" refers to the rating and opinion information provided by a user regarding a proposed holiday plan.

[0111] "Improving the analysis algorithm" refers to the process of adjusting the data analysis algorithm based on feedback information collected from users to improve the accuracy of the next proposal.

[0112] The present invention is a system for generating optimal holiday plans based on a user's lifestyle information and notifying the user of the plans. The system includes a user terminal, a server, and a network over which these communicate.

[0113] User device functions

[0114] The user device will automatically collect information about the user's daily life by linking with various healthcare and calendar apps. Specifically, the following data will be collected:

[0115] sleep time

[0116] Heart rate

[0117] Step count

[0118] Calendar events

[0119] The collected data is sent to a server at regular intervals, and this communication is securely carried out using encryption protocols such as SSL / TLS.

[0120] Server Features

[0121] The server receives the data sent from the user terminal and stores it in a database. Then, the server uses a data analysis algorithm to perform data analysis, including the following elements:

[0122] Assessment of average sleep time

[0123] Heart rate abnormality detection

[0124] Assessment of exercise volume

[0125] Schedule balance assessment

[0126] Based on the results of the data analysis, the server generates the optimal holiday plan for the user. The generated plan may include watching a movie or refreshing in a hot spring if you are not feeling well, walking in a nearby park if you are lacking exercise, or going on a day camp if you have little time to spend with family. The generated plan is sent to the user's device and notified to the user at the appropriate time.

[0127] User Notification and Feedback

[0128] The user device notifies the user of the plan sent from the server. The notification includes specific activity details and recommended locations and times. After the user carries out the proposed plan, the user device collects feedback. The feedback includes the usefulness of the plan. The feedback information is sent to the server and stored in a database. The server uses this feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions.

[0129] Specific examples

[0130] Example 1: Lack of exercise

[0131] The user's device collects data on weekdays and sends it to the server. Based on the analysis result that the user's physical activity is low, the server suggests walking in a nearby park on the weekend. The user receives a notification from the device and follows the suggestion. Later, the user provides feedback, which the server uses to improve the accuracy of the next suggestion.

[0132] Example 2: Family time

[0133] The user's device sends calendar information indicating that they have little time to spend with their family to the server. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback. Based on this feedback, the server adjusts the next suggestion more appropriately.

[0134] Example prompts for generative AI models

[0135] "Please create a program for a system that generates and notifies optimal holiday plans based on a user's weekday lifestyle information (e.g., sleep time, heart rate, number of steps, calendar events). This system includes user devices, a server, and the network over which they communicate."

[0136] This system will suggest optimal holiday plans based on the user's health condition and lifestyle, allowing them to spend their holidays more fulfillingly. Furthermore, by continuously improving the system based on feedback, the system will continue to provide highly accurate suggestions over time.

[0137] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0138] Step 1: Data collection

[0139] The user device connects with a healthcare app and a calendar app to collect weekday lifestyle information. Specifically, it obtains data on sleep time, heart rate, and number of steps from the healthcare app, and obtains the user's schedule information from the calendar app. These data are compiled into a data package. The input of this step is data from each app, and the output is the compiled data package.

[0140] Step 2: Send data

[0141] The user terminal transmits the collected data packages to the server at regular intervals (e.g., once a day). This communication is securely performed using encryption protocols such as SSL / TLS. The input is the data package, and the output is the transmission of encrypted data.

[0142] Step 3: Receiving data

[0143] The server receives data packages sent from user terminals. The received data is stored in a database. The input is the encrypted data package, and the output is the data stored in the database.

[0144] Step 4: Data analysis

[0145] The server analyzes the received data using a data analysis algorithm. Specifically, it calculates average sleep time using Python's pandas library and detects abnormal heart rate values ​​using scikit-learn's anomaly detection algorithm. It also evaluates the amount of exercise and schedule balance. The input is lifestyle information stored in the database, and the output is the analysis results.

[0146] Step 5: Generate a plan

[0147] The server generates an optimal holiday plan based on the results of the data analysis. For example, if you are not getting enough exercise, it will suggest walking in a nearby park, or if you don't spend much time with your family, it will suggest day camping. The input is the results of the data analysis, and the output is a specific holiday plan.

[0148] Step 6: Plan Notification

[0149] The server sends the generated holiday plan to the user's device. The user's device notifies the user of the plan at the appropriate time. The notification content includes specific activities and recommended locations and times. The input is the specific holiday plan, and the output is a notification to the user.

[0150] Step 7: Gather feedback

[0151] After the user executes the proposed plan, the user terminal collects feedback. The feedback is in the form of questions about the usefulness of the plan and whether the activity was enjoyable. The input is the user's answer, and the output is the collected feedback data.

[0152] Step 8: Send your feedback

[0153] The user terminal sends the collected feedback data to the server, which stores the data in a database. The input is the feedback data, and the output is the feedback stored in the database.

[0154] Step 9: Improve the analysis algorithm

[0155] The server improves the analysis algorithm based on the collected feedback. For example, if a particular plan is popular, it may be given higher priority. The input is the feedback data, and the output is an improved analysis algorithm.

[0156] These specific processing steps make it possible to continuously provide optimal holiday plans to users.

[0157] (Application example 1)

[0158] 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."

[0159] Conventional self-driving vehicles lack the functionality to utilize the user's health information and schedule to provide optimal driving routes, rest spots, and activities while traveling. As a result, users are unable to receive appropriate suggestions for entertainment and health promotion while traveling, making it difficult to enjoy an efficient and comfortable driving experience. The present invention aims to solve this problem and provide users with optimal suggestions even while traveling.

[0160] 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.

[0161] In this invention, the server includes: means for collecting user lifestyle information; means for analyzing the collected lifestyle information; means for generating an optimal holiday plan based on the analysis results; means for notifying the user of the generated holiday plan; means including an application installed in the self-driving vehicle; means for suggesting optimal driving routes, rest spots, and activities based on the user's lifestyle data; means for notifying the user of the suggestions in real time while driving; and means for collecting feedback provided by the user and improving the accuracy of the suggestions for the next trip. This enables the user to receive optimal suggestions based on their health condition and schedule even while on the move, enabling them to enjoy a comfortable and efficient driving experience.

[0162] "User's lifestyle information" is data related to the user's daily life, including, for example, sleep time, heart rate, number of steps, calendar schedule, and the like.

[0163] The term "means" refers to a method or device for achieving a specific purpose, and in this invention refers to a method or device for realizing functions such as data collection, analysis, notification, and feedback collection.

[0164] "Applications installed in autonomous vehicles" refers to software installed inside vehicles with autonomous driving capabilities that analyzes user data and provides notifications.

[0165] "User's lifestyle data" is a general term for various information generated in the course of a user's daily life, and includes health information, schedule information, and the like.

[0166] The "optimal driving route" refers to the most efficient and convenient driving route for the user, calculated and suggested based on the user's health condition and schedule.

[0167] "Rest Spots" refers to suitable places for users to take a rest while driving, and are suggested based on their health status and schedule.

[0168] "Activity" refers to fitness and entertainment related activities that a user can engage in while driving.

[0169] The "means for notifying the user of the proposed content in real time" refers to a method or device for instantly notifying the user's terminal of the analysis results and the recommended plan while driving.

[0170] "User-provided feedback" refers to the user's reactions to the suggestions, such as evaluations and impressions, and is information that the system uses to improve its next suggestions.

[0171] The present invention provides a system that generates optimal holiday plans based on a user's lifestyle information and notifies the user of the plans. The system includes a user terminal, an application installed in an autonomous vehicle, a cloud server, and a network over which these communicate.

[0172] User device functions

[0173] Data collection

[0174] The user's device connects to various healthcare and calendar apps to collect weekday lifestyle information. This connection automatically collects the following data, for example, using the health information API or Google Calendar API.

[0175] sleep time

[0176] Heart rate

[0177] Step count

[0178] Calendar events

[0179] Data transmission

[0180] The collected data is sent to the server at regular intervals. This communication is secure, using encrypted communication such as SSL / TLS, to protect user privacy.

[0181] Cloud Server Functions

[0182] Data reception

[0183] The server receives the data sent from the user terminal and stores it in an internal database.

[0184] Data analysis

[0185] The server analyzes the collected data, which may include the following elements:

[0186] Is your average sleep time sufficient?

[0187] Is there any abnormality in your heart rate?

[0188] Is the amount of exercise enough?

[0189] Calendar overload or balance

[0190] These analyses are performed using data analysis tools using Python and R. For example, if the average sleep time is less than six hours, the system will suggest watching a movie.

[0191] Plan Generation

[0192] Based on the results of the data analysis, the server generates the optimal holiday plan for the user, which may include:

[0193] If you're not feeling well: Watch a movie or relax in a hot spring

[0194] If you are not getting enough exercise: Walking in a nearby park or using sports facilities

[0195] If you don't have much time with your family: Day camping or picnics

[0196] This plan generation may be powered by a generative AI model, which applies machine learning algorithms to provide a customized plan for each user.

[0197] notification

[0198] The generated plan is sent to the user's device and notifications are sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. Notifications are sent using a dedicated notification API.

[0199] Autonomous vehicle features

[0200] Real-time suggestions

[0201] The application installed in the autonomous vehicle will suggest optimal driving routes, rest spots, and activities based on the user's lifestyle data, including a function to optimize driving routes in conjunction with the GPS module.

[0202] User Feedback

[0203] Feedback collection

[0204] After the user implements the proposed plan, the user device collects feedback, for example, by displaying a question such as "Was this plan helpful?"

[0205] Send Feedback

[0206] The feedback provided by the user is sent to the server and stored in a database.

[0207] Improved accuracy

[0208] The server then uses the collected feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions. This cycle allows the server to continually provide plans that better suit the user's needs.

[0209] Prompt Sentence Examples

[0210] Design a system that collects a user's health data and generates an optimal holiday plan based on that data. The holiday plan includes entertainment (e.g., watching movies), exercise (e.g., walking), and family activities (e.g., day camping). Analyze the plan based on the user's sleep time, heart rate, number of steps, and calendar events. Also include a function to improve the next proposal based on user feedback.

[0211] This invention allows users to have a fulfilling holiday by receiving optimal holiday plans based on their weekday lifestyle information. Furthermore, users can receive suggestions for optimal driving routes and rest spots while on the move, realizing an efficient and comfortable driving experience.

[0212] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0213] Step 1:

[0214] Data collection

[0215] The user's device uses the health information API and Google Calendar API to collect the user's lifestyle information (sleep time, heart rate, number of steps, calendar schedule). For example, the user's average sleep time and heart rate are obtained from the health app API, and the user's schedule information is obtained from the Google Calendar API. This data is collected and saved in the device in JSON format.

[0216] Input: Data from smartphone health information API and Google Calendar API.

[0217] Output: User's lifestyle information data (JSON format).

[0218] Step 2:

[0219] Data transmission

[0220] The user device securely transmits the collected lifestyle information data to the cloud server at regular intervals (e.g., daily or weekly). This communication uses encryption protocols such as SSL / TLS. For example, data such as the user's sleep time and heart rate is transmitted to the server using HTTPS.

[0221] Input: Collected user lifestyle information data.

[0222] Output: Lifestyle information data stored on a cloud server.

[0223] Step 3:

[0224] Data reception

[0225] The server receives the lifestyle information data sent from the user terminal and stores it in a database, for example, using a database management system (DBMS).

[0226] Input: Lifestyle information data sent from the user's device.

[0227] Output: Life information data stored in a database.

[0228] Step 4:

[0229] Data analysis

[0230] The server analyzes the lifestyle information data stored in the database. For example, it processes the data using Python data analysis libraries (Pandas and NumPy) to calculate average sleep time, heart rate, and exercise volume. Based on this, the server evaluates the user's health status and selects activities suitable for future holiday plans. As a specific example, it suggests walking if the user is not getting enough exercise.

[0231] Input: Lifestyle information data stored in a database.

[0232] Output: Analysis results (e.g. lack of exercise, lack of average sleep time).

[0233] Step 5:

[0234] Plan Generation

[0235] The server then uses a generative AI model based on the results of the data analysis to create an optimal holiday plan. For example, if the user is not getting enough exercise, it might suggest walking in a nearby park. This generation process uses machine learning algorithms and takes into account the user's past feedback.

[0236] Input: Analysis results, user feedback.

[0237] Output: Recommended optimal holiday plans.

[0238] Step 6:

[0239] Plan Notification

[0240] The server then sends the generated holiday plan to the user's device and notifies them at the appropriate time. For example, it uses a dedicated notification API to send push notifications to the user. The notifications include specific activities, recommended locations, and times.

[0241] Input: The generated holiday plan.

[0242] Output: Notification content sent to the user's terminal.

[0243] Step 7:

[0244] Real-time suggestions

[0245] While driving, an application installed in the autonomous vehicle will suggest optimal driving routes, rest spots, and activities in real time based on the user's lifestyle data. For example, it will use the GPS function to obtain the current location and display suitable rest spots.

[0246] Input: User's daily life data, current GPS location information.

[0247] Output: Real-time driving routes, rest stops, and activity suggestions.

[0248] Step 8:

[0249] Feedback collection

[0250] After the user implements the proposed plan, the user terminal collects feedback. For example, a question such as "Was this plan helpful?" is displayed on the application and the user's answer is obtained.

[0251] Input: User feedback.

[0252] Output: User feedback data.

[0253] Step 9:

[0254] Send Feedback

[0255] The collected feedback is sent to the server and stored in a database, and this data is also used to improve the accuracy of the next suggestion.

[0256] Input: Feedback data from user terminal.

[0257] Output: Feedback data stored in a database.

[0258] Step 10:

[0259] Improved accuracy

[0260] The server updates its analysis algorithms based on the collected feedback data to improve the accuracy of its next plan proposals, for example by retraining the machine learning model to learn new feedback patterns.

[0261] Input: Feedback data.

[0262] Output: The updated parsing algorithm.

[0263] 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.

[0264] System Overview

[0265] The present invention is a system that generates optimal holiday plans based on a user's lifestyle information and emotional state and notifies the user of the plans. The system includes a user terminal, a server, an emotion engine, and a network over which these communicate.

[0266] User device functions

[0267] Data collection

[0268] The user device automatically collects weekday lifestyle information and emotional state. Specifically, it connects with a healthcare app to obtain the following data:

[0269] sleep time

[0270] Heart rate

[0271] Step count

[0272] Calendar events

[0273] In addition, an emotion engine analyzes the user's emotional state and collects emotional information through text messages, voice input, etc.

[0274] Data transmission

[0275] The collected lifestyle and emotional information is periodically sent to a server, including daily sleep duration, average heart rate, number of steps taken, schedule details, and an indicator of emotional state.

[0276] Server Features

[0277] Data reception

[0278] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the server checks the consistency and integrity of the data.

[0279] Data analysis

[0280] The server launches a data analysis module and an emotion engine to analyze the received lifestyle and emotion information. The analysis evaluates the following factors:

[0281] Is your average sleep time sufficient?

[0282] Is there any abnormality in your heart rate?

[0283] Is the amount of exercise enough?

[0284] Is there an over-schedule?

[0285] The user's emotional state (e.g., stress level, happiness)

[0286] Plan Generation

[0287] Based on the results of the data analysis, the server generates the optimal holiday plan for the user. Based on the analysis results of the emotion engine, the plan is created taking into account the user's emotional state. For example, if the stress level is high, it will suggest relaxing activities, and if the happiness level is low, it will suggest activities that will help you change your mood.

[0288] notification

[0289] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time, including specific activities and recommended locations and times.

[0290] User Feedback

[0291] Feedback collection

[0292] After the user implements the proposed plan, the user device collects feedback and emotional state, such as questions like "Was this plan helpful?" and "Did you feel better after this activity?"

[0293] Send Feedback

[0294] The feedback and emotional state data provided by the user are sent to a server and stored in a database.

[0295] Improved accuracy

[0296] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, increasing the accuracy of future plan suggestions. This cycle allows the server to continuously provide plans that better suit the user's needs.

[0297] Specific examples

[0298] Example 1: Lack of exercise and stress

[0299] The user's device collects data on weekdays and sends it to the server indicating that the user's exercise volume is low and stress levels are high. The server receives and analyzes this data and suggests walking and meditating in a nearby park on the weekend. The user receives a notification from the device and actually walks and meditates. Later, the user provides feedback and emotional state, which the server uses to improve the accuracy of its next suggestions.

[0300] Example 2: Family time and happiness

[0301] The user's device transmits information from the user's calendar and emotional state to the server, indicating that the user spends little time with family and has a low happiness level. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback and their emotional state. Based on this feedback and emotional information, the server adjusts the next suggestion more appropriately.

[0302] The present invention allows users to have a fulfilling holiday by receiving an optimal holiday plan based on their weekday lifestyle information and emotional state, which helps them maintain a healthy state of mind and body.

[0303] The processing flow will be explained below.

[0304] Processing Steps

[0305] Step 1:

[0306] The user's device automatically collects weekday lifestyle and emotional information. Specifically, it connects with a healthcare app to obtain data on sleep time, heart rate, and number of steps. It also obtains schedule information from a calendar app, and the emotion engine analyzes text messages and voice input to evaluate the user's emotional state.

[0307] Step 2:

[0308] The user device periodically transmits the collected data to the server, including average sleep time, average heart rate, number of steps, schedule details, and indicators of emotional state for each day.

[0309] Step 3:

[0310] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the consistency and completeness of the data are verified.

[0311] Step 4:

[0312] The server launches the data analysis module and emotion engine to analyze the received data. The analysis considers the following factors:

[0313] Is your average sleep time sufficient?

[0314] Is there any abnormality in your heart rate?

[0315] Is the amount of exercise enough?

[0316] Isn't the schedule too busy?

[0317] The user's emotional state (e.g., stress level, happiness)

[0318] Step 5:

[0319] The server generates an optimal holiday plan based on the results of data analysis. Specifically, it creates a plan that takes into account the user's emotional state based on the analysis results of the emotion engine. For example, it suggests relaxing activities (watching movies, meditating, visiting hot springs) for a user with a high stress level, and activities that will change your mood (walking, bouldering, meeting up with friends) for a user with a low happiness level.

[0320] Step 6:

[0321] The server sends the generated holiday plan to the user's device, along with detailed information such as the specific contents of the plan, location, and time.

[0322] Step 7:

[0323] The user terminal notifies the user of the holiday plan received from the server. The notification function is also used to notify the user of the proposal and display the detailed plan contents.

[0324] Step 8:

[0325] The user carries out the proposed plan. After the holiday, the user's device collects feedback and emotional state after the plan is implemented. For example, questions such as "Was this plan helpful?" and "How did your mood change after this activity?" are displayed.

[0326] Step 9:

[0327] The user terminal transmits the collected feedback and emotional state data to the server, which stores the collected feedback and data in a database.

[0328] Step 10:

[0329] The server analyzes the received feedback and emotional information, and adjusts and improves the holiday plan generation algorithm and emotional engine for future trips. By continuously performing this analysis and adjustment, the accuracy of providing plans that better suit the user's needs and emotional state increases.

[0330] Specific examples

[0331] Example 1: Lack of exercise and stress

[0332] The user's device collects data from the weekdays and sends it to the server, indicating that the user's exercise volume is low and stress levels are high. The server receives and analyzes this data, and then suggests a walking and meditation session at a nearby park on the weekend. The user receives this notification from their device and actually walks and meditates. Later, the user provides feedback and emotional state, which the server uses to improve the accuracy of the next suggestion.

[0333] Example 2: Family time and happiness

[0334] The user's device transmits to the server, based on the user's calendar information and emotional information, information indicating that they spend little time with their family and their happiness level is low. The server analyzes this information and suggests a day camp that the family can enjoy. The user accepts the suggestion and actually enjoys the day camp. After the suggestion, the user provides feedback and their emotional state. The server then adjusts the next suggestion based on this feedback.

[0335] This allows users to receive suggestions for optimal holiday plans based on their weekday lifestyle information and emotional state, helping them maintain a healthy state of mind and body.

[0336] Example 2

[0337] 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."

[0338] In modern society, there is a demand for systems that comprehensively evaluate users' lifestyles, health, and emotional states, and then provide optimal holiday plans based on these assessments. However, conventional systems have been unable to effectively provide customized plans suited to individual users due to insufficient collection and analysis of users' lifestyle information. In particular, there has been a lack of systems that provide plans that take into account the user's emotional state, and measures are needed to further improve users' emotional satisfaction.

[0339] 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.

[0340] In this invention, the server comprises means for collecting lifestyle information and emotional information of the user, means for transmitting the collected lifestyle information and emotional information to the server, means for analysing the lifestyle information and emotional information received by the server and assessing the user's condition, means for introducing a generative AI model which generates an optimal holiday plan based on the analysis results, and means for notifying the user terminal of the generated holiday plan. This makes it possible to provide a more customised holiday plan that takes into account the user's individual lifestyle rhythm and emotional state.

[0341] "User's lifestyle information" is data related to the user's daily life, including sleep time, heart rate, number of steps, calendar schedule, and the like.

[0342] "Emotional information" refers to the emotional state (such as stress level or happiness) analyzed from a user's text messages or voice input.

[0343] The "server" is a computer system that receives lifestyle information and emotional information sent from the user's device, analyzes it, and generates holiday plans using a generative AI model.

[0344] "Generative AI model" refers to artificial intelligence algorithms or software that generate optimal holiday plans for users based on the data they receive.

[0345] A "user terminal" is a device used to collect information about a user's daily life and emotions and transmit this data to a server, and examples of such devices include smartphones and tablets.

[0346] "Plan generation" refers to the process by which the server creates an optimal holiday plan for the user based on the analysis results.

[0347] "Notification" refers to the act of informing the user of the holiday plan generated by the server, and is done in the form of a push notification or the like.

[0348] "Feedback" refers to information that records the user's thoughts and emotional state regarding the plan they have implemented and is used to improve the accuracy of future plan proposals.

[0349] MODE FOR CARRYING OUT THE INVENTION

[0350] The present invention is a system that generates optimal holiday plans based on a user's lifestyle information and emotional state and notifies the user of the plans. The system includes a user terminal, a server, an emotion engine, and a network over which these communicate.

[0351] User device functions

[0352] Data collection

[0353] The user device collects weekday lifestyle information and emotional state. The specific hardware used is a smartphone, and the device connects with a healthcare app (e.g., Apple Health or Google Fit) installed on the device to acquire the following data:

[0354] User sleep time

[0355] User's heart rate

[0356] User steps

[0357] User's calendar events

[0358] The emotion engine analyzes the user's text messages and voice inputs to gather emotional states (e.g., stress levels and happiness).

[0359] Data transmission

[0360] The collected lifestyle and emotional information is periodically sent to a server. Specifically, the data sent includes each day's sleep duration, average heart rate, number of steps, schedule details, and indicators of emotional state. Data is sent using FTP or HTTP protocols.

[0361] Server Features

[0362] Data reception

[0363] The server receives the data sent from the user terminal and stores it in a database. The database may be MySQL or PostgreSQL, for example. The consistency and completeness of the data is checked upon receipt.

[0364] Data analysis

[0365] The server launches a data analysis module implemented in a programming language such as Python to analyze the received lifestyle and emotion information. The analysis evaluates the following factors:

[0366] Is your average sleep time sufficient?

[0367] Is there any abnormality in your heart rate?

[0368] Is the amount of exercise enough?

[0369] Is there an over-schedule?

[0370] The user's emotional state (e.g., stress level, happiness)

[0371] Additionally, an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) is used to assess the emotional state.

[0372] Plan Generation

[0373] Based on the analysis results, the server generates the optimal holiday plan for the user using a generative AI model (e.g., GPT-4) and generates the plan by sending prompts.

[0374] Example prompt sentence:

[0375] "Please suggest the best holiday plan for users who are lacking exercise and have high stress levels. Include specific activity and location suggestions."

[0376] notification

[0377] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. The notification is sent using a push notification service (e.g., Firebase Cloud Messaging).

[0378] User Feedback

[0379] Feedback collection

[0380] After the user implements the proposed plan, the user terminal collects feedback and emotional state, for example, displaying questions such as "Was this plan helpful?" and "Did you feel better after this activity?"

[0381] Send Feedback

[0382] The collected feedback and emotional state data is sent to a server and stored in a database.

[0383] Improved accuracy

[0384] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, increasing the accuracy of future plan suggestions. This cycle allows the server to continuously provide plans that better suit the user's needs.

[0385] In this manner, the present invention proposes optimal holiday plans based on the user's lifestyle information and emotional state, and supports the user in having a fulfilling holiday.

[0386] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0387] Step 1:

[0388] Data collection from user devices

[0389] The user's device collects information about their weekday lifestyle and emotional state. Specifically, it connects with healthcare apps (e.g., Apple Health or Google Fit) installed on their smartphone to obtain the user's sleep time, heart rate, number of steps, and calendar appointments. The emotion engine also analyzes the user's text messages and voice input to collect their emotional state (stress level and happiness).

[0390] Input: User's life information and emotional state

[0391] Output: Collected data

[0392] Step 2:

[0393] Data transmission by user terminal

[0394] The user device periodically transmits the collected data to the server. Specifically, the transmitted data includes daily sleep duration, average heart rate, number of steps, calendar appointments, and indicators of emotional state. Data transmission is performed using FTP or HTTP protocols.

[0395] Input: Collected lifestyle and emotional information

[0396] Output: Data sent to the server

[0397] Step 3:

[0398] Data reception by the server

[0399] The server receives the data sent from the user terminal and stores it in a database. Upon receiving the data, it checks its consistency and completeness. The database used can be, for example, MySQL or PostgreSQL.

[0400] Input: Data sent from the user's device

[0401] Output: Data stored in the database

[0402] Step 4:

[0403] Data analysis by server

[0404] The server launches a data analysis module using a programming language such as Python to analyze the received lifestyle and emotion information. The analysis evaluates the following elements:

[0405] Is your average sleep time sufficient?

[0406] Is there any abnormality in your heart rate?

[0407] Is the amount of exercise enough?

[0408] Is there an over-schedule?

[0409] The user's emotional state (e.g., stress level, happiness)

[0410] Additionally, an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) is used to assess the emotional state.

[0411] Input: Received lifestyle and emotional information

[0412] Output: Analysis results

[0413] Step 5:

[0414] Server-generated plan

[0415] The server generates an optimal holiday plan based on the analysis results. The plan is generated using a generative AI model (e.g., GPT-4) and is generated by sending prompts.

[0416] Input: Analysis results

[0417] Output: Generated holiday plan

[0418] Example prompt sentence:

[0419] "Please suggest the best holiday plan for users who are lacking exercise and have high stress levels. Include specific activity and location suggestions."

[0420] Step 6:

[0421] Server Notification

[0422] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. The notification is sent using a push notification service (e.g., Firebase Cloud Messaging).

[0423] Input: Generated holiday plan

[0424] Output: Notification to user terminal

[0425] Step 7:

[0426] Collecting user feedback

[0427] After the user implements the proposed plan, the user device collects feedback and emotional state, such as questions like "Was this plan helpful?" and "Did you feel better after this activity?"

[0428] Input: User's performance and emotional state

[0429] Output: Collected feedback data

[0430] Step 8:

[0431] Send Feedback

[0432] The user's feedback and emotional state data are sent to the server. The sending process uses FTP or HTTP protocols, similar to data transmission.

[0433] Input: Collected feedback data

[0434] Output: Feedback data sent to the server

[0435] Step 9:

[0436] Server-based accuracy improvement

[0437] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, improving the accuracy of future plan suggestions. For example, if a particular activity was highly beneficial to the user, the server will adjust its suggestions to suggest more similar activities.

[0438] Input: Feedback and emotional information data

[0439] Output: Improved algorithms and sentiment engine

[0440] By executing these steps in succession, a system is realized that provides users with optimal holiday plans and supports healthy living both physically and mentally.

[0441] (Application example 2)

[0442] 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."

[0443] Conventional systems that propose optimal holiday plans to users based on lifestyle and emotional information have had issues with the accuracy of their proposals and their feasibility in the real world. Specifically, they lack real-time guidance based on the user's current location, and they also lack sufficient feedback to confirm whether the proposed plans are actually beneficial to the user. Therefore, there is a need for a system that provides real-time guidance using the user's location information and smart devices, as well as improving the accuracy of proposals based on feedback.

[0444] The identification process performed by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting user lifestyle information, means for analyzing the collected lifestyle information and emotional state, means for generating an optimal experience plan based on the analysis results, means for notifying the user of the generated experience plan, means for guiding the user to the proposed plan's location based on the user's location information, means for collecting feedback obtained by the user through the experience at the physical store, means for improving the accuracy of the next proposal based on the collected feedback and emotional information, means including emotion analysis software and a database management system, and means for generating prompt sentences and inputting them into the generative AI model. This enables the user to be provided with an optimal experience in real time and guided to the experience location. Furthermore, collecting feedback can improve the accuracy of future proposals.

[0445] "Lifestyle information" refers to data related to the user's daily life, including health status, amount of exercise, schedule, and the like.

[0446] "Emotional state" is an indicator of the user's current psychological state, and includes stress level, happiness level, and the like.

[0447] "Experience Plan" refers to activities or schedules that a user is encouraged to undertake over a specific period of time.

[0448] "Notification means" refers to a method or device for notifying the user of the generated experience plan.

[0449] "Location information" is information that indicates the user's current geographical location.

[0450] "Guidance means" refers to a method or device that provides directions and detailed information to the location where the user will carry out the proposed experience plan.

[0451] "Feedback" refers to the user's evaluation and impressions of the experience plan they implemented.

[0452] "Emotion analysis software" refers to programs and algorithms used to analyze a user's emotional state.

[0453] A "database management system" is a system for storing, managing, and retrieving collected data.

[0454] A "generative AI model" is an artificial intelligence model used to generate a proposed experience plan.

[0455] A "prompt sentence" is an instruction sentence that is input into a generative AI model to obtain a generated result based on the user's situation and wishes.

[0456] As an embodiment of the present invention, an application installed on smart glasses will be specifically described.

[0457] Generating a Program

[0458] The system is realized using smart glasses, emotion analysis software, a database management system, a cloud server, and a generative AI model.

[0459] Hardware and Software

[0460] 1. Smart Glasses:

[0461] Sensors: Heart rate monitor, pedometer, GPS

[0462] Display: For presenting information

[0463] 2. Sentiment Analysis Software:

[0464] Example: Using various SDKs (e.g. Affectiva SDK)

[0465] 3. Database Management System:

[0466] Example: MySQL

[0467] 4. Cloud Server:

[0468] Example: AWS EC2

[0469] 5. Recommended engines:

[0470] Example: AWS SageMaker

[0471] explanation

[0472] 1. Data Collection:

[0473] The server uses the smart glasses' built-in sensors to collect the user's heart rate, steps, and GPS information in real time.

[0474] Emotion analysis software is used to analyze a user's emotional state from their text messages and voice inputs.

[0475] 2. Data transmission:

[0476] The collected data is sent to a cloud server at a fixed interval, where the data is checked for consistency and completeness.

[0477] 3. Data Analysis:

[0478] The data received by the cloud server is stored in a database management system (MySQL).

[0479] The data analysis module on the server evaluates the user's health and emotional state, calculating stress levels and happiness based on heart rate, steps, GPS information, and emotional state.

[0480] 4. Plan Generation:

[0481] A recommendation engine (AWS SageMaker) is used to generate optimal experience plan candidates based on the analysis results.

[0482] For example, if a user's stress level is high, the system recommends tea time at a relaxing cafe.

[0483] 5. Notices and Guidance:

[0484] The generated experience plan is displayed on the smart glasses' display, and the shortest route to the proposed experience location is also provided based on the user's location information.

[0485] Guidance is updated in real time, so the user is provided with appropriate directions based on their current location.

[0486] 6. User Feedback:

[0487] After completing the proposed experience plan, users enter their feedback through the smart glasses. The feedback form includes questions such as, "Did you find this time relaxing?"

[0488] The feedback and additional emotion data are sent to a cloud server and used to improve the accuracy of the next suggestion.

[0489] Specific examples

[0490] A day in smart glasses

[0491] 1. Data Collection and Analysis:

[0492] During the day, the smart glasses collect the user's heart rate, steps, and GPS information, and analyze stress levels through text messages.

[0493] For example, at 3pm, an increased heart rate and increased stress are observed.

[0494] 2. Plan Generation and Notification:

[0495] The cloud server obtains as an analysis result that the user's stress level is high.

[0496] Suggestion: The smart glasses display recommends a relaxing tea time at a quiet nearby cafe.

[0497] The smart glasses also display directions to the selected cafe.

[0498] 3. Practice and feedback:

[0499] After a user has tea time at a cafe, they input feedback through the smart glasses, such as "Was this time relaxing?"

[0500] The feedback and emotion data are sent to a cloud server and used to improve the accuracy of future plan generation.

[0501] Prompt Sentence Examples

[0502] "User data:

[0503] Heart rate average: 80

[0504] Steps: 3000

[0505] Sleep time: 6 hours

[0506] Emotional state: Stress

[0507] User location: Shibuya-ku, Tokyo

[0508] suggestion:

[0509] "Please suggest a place where users can relax."

[0510] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0511] Step 1:

[0512] The smart glasses use built-in sensors to collect the user's heart rate, steps, and GPS information in real time. The inputs are heart rate, steps, and GPS data, and the output is the collected raw data.

[0513] Step 2:

[0514] The collected data is then used to analyze the user's emotional state using emotion analysis software. The input is text messages or voice input, and the output is analyzed emotional data.

[0515] Step 3:

[0516] The device sends the collected lifestyle information and emotional information to a cloud server. The inputs are heart rate, step count, GPS data, and emotional data, and the output is the integrated data sent to the cloud server.

[0517] Step 4:

[0518] The cloud server stores the received data in a database management system (MySQL) and performs the necessary consistency checks. The input is the transmitted integrated data, and the output is the data stored in the database.

[0519] Step 5:

[0520] The cloud server launches the data analysis module and analyzes the stored data. The input is the user's lifestyle and emotional information obtained from the database, and the output is the analysis results. Specifically, the average heart rate, total number of steps, stress level, etc. are calculated.

[0521] Step 6:

[0522] Using a recommendation engine (AWS SageMaker), an optimal experience plan is generated based on the analysis results. The input is the analysis results, and the output is the generated experience plan.

[0523] Step 7:

[0524] The cloud server notifies the smart glasses of the generated experience plan. The input is the experience plan, and the output is the plan displayed on the smart glasses' display.

[0525] Step 8:

[0526] The smart glasses use location information to guide the user to the proposed plan location. The input is the user's current location and the proposed location, and the output is the route displayed on the smart glasses' display.

[0527] Step 9:

[0528] After the user executes the plan, they input feedback through the smart glasses. The input is the user's feedback and additional emotional data, and the output is the collected feedback.

[0529] Step 10:

[0530] The collected feedback is sent to the cloud server again and stored in a database. The input is the user's feedback data, and the output is the feedback stored in the database.

[0531] Step 11:

[0532] The cloud server analyzes the collected feedback and updates the generative AI model to improve the accuracy of future plan generation. The input is the feedback data, and the output is the updated generative AI model.

[0533] 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.

[0534] 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.

[0535] 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.

[0536] [Second embodiment]

[0537] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0538] 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.

[0539] 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).

[0540] 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.

[0541] 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.

[0542] 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).

[0543] 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.

[0544] 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.

[0545] 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.

[0546] 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.

[0547] 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.

[0548] 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."

[0549] System Overview

[0550] The present invention is a system for generating optimal holiday plans based on a user's lifestyle information and notifying the user of the plans. The system includes a user terminal, a server, and a network over which these communicate.

[0551] User device functions

[0552] Data collection

[0553] The user device will connect to various healthcare and calendar apps to collect weekday lifestyle information. Through this connection, the following data will be automatically collected:

[0554] sleep time

[0555] Heart rate

[0556] Step count

[0557] Calendar events

[0558] Data transmission

[0559] The collected data is sent to a server at regular intervals. This communication is secure, protecting user privacy.

[0560] Server Features

[0561] Data reception

[0562] The server receives the data sent from the user terminal and stores it in an internal database.

[0563] Data analysis

[0564] The server analyzes the collected data, which may include the following elements:

[0565] Is your average sleep time sufficient?

[0566] Is there any abnormality in your heart rate?

[0567] Is the amount of exercise enough?

[0568] Overscheduling and balance

[0569] Plan Generation

[0570] Based on the results of the data analysis, the server generates the optimal holiday plan for the user, which may include:

[0571] If you're not feeling well: Watch a movie or relax in a hot spring

[0572] If you are not getting enough exercise: Walking in a nearby park or using sports facilities

[0573] If you don't have much time with your family: Day camping or picnics

[0574] notification

[0575] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time, including specific activities and recommended locations and times.

[0576] User Feedback

[0577] Feedback collection

[0578] After the user implements the proposed plan, the user device collects feedback, for example, by displaying a question such as "Was this plan helpful?"

[0579] Send Feedback

[0580] The feedback provided by the user is sent to the server and stored in a database.

[0581] Improved accuracy

[0582] The server then uses the collected feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions. This cycle allows the server to continually provide plans that better suit the user's needs.

[0583] Specific examples

[0584] Example 1: Lack of exercise

[0585] The user's device collects data on weekdays and sends it to the server indicating that the user is not exercising much. The server receives and analyzes this data and suggests walking in a nearby park on the weekend. The user receives a notification from the device and actually goes for a walk. The user then provides feedback at a later date, which the server uses to improve the accuracy of its next suggestions.

[0586] Example 2: Family time

[0587] The user's device sends information from the user's calendar indicating that they have little time to spend with their family to the server. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback. Based on this feedback, the server adjusts the next suggestion more appropriately.

[0588] The present invention allows users to have a fulfilling holiday by being offered an optimal holiday plan based on their weekday lifestyle information, which helps them maintain a healthy state of mind and body.

[0589] The processing flow will be explained below.

[0590] Step 1:

[0591] The user's device automatically collects information about their weekday lifestyle. Specifically, it connects with a healthcare app to obtain data on sleep time, heart rate, and number of steps taken. It also obtains schedule information from a calendar app.

[0592] Step 2:

[0593] The user device periodically sends the collected data to the server, including the amount of sleep each day, average heart rate, number of steps taken, and schedule details.

[0594] Step 3:

[0595] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the consistency and completeness of the data are verified.

[0596] Step 4:

[0597] The server launches a data analysis module to analyze the received data, which evaluates whether the person is getting enough sleep, has an abnormal heart rate, is exercising enough, or has an overscheduled schedule.

[0598] Step 5:

[0599] The server generates an optimal holiday plan based on the results of the data analysis. Specifically, it suggests relaxing activities for users who are sleep-deprived, recommended exercise activities for users who are not getting enough exercise, and stress-relieving activities for users who have a busy schedule.

[0600] Step 6:

[0601] The server sends the generated holiday plan to the user's device, along with detailed information such as the specific contents of the plan, location, and time.

[0602] Step 7:

[0603] The user's device displays the holiday plan received from the server, and also notifies the user of the proposal using the notification function.

[0604] Step 8:

[0605] The user carries out the proposed plan, and after spending the holiday, the user's device collects feedback.

[0606] Step 9:

[0607] The user terminal sends the collected feedback to the server, including the usefulness and satisfaction of the suggestions.

[0608] Step 10:

[0609] The server analyzes the received feedback and adjusts and improves the holiday plan generation algorithm for future trips. This feedback cycle allows the server to provide a plan that is more suitable for the user.

[0610] Example 1

[0611] 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."

[0612] In modern life, there is a demand for a means to automatically suggest holiday plans that are suited to each individual's health condition and lifestyle. However, existing systems have difficulty effectively collecting and analyzing users' lifestyle information and providing optimal holiday plans for each individual. Furthermore, the accuracy of suggestions is limited due to a lack of functionality to continuously improve the system based on user feedback.

[0613] 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.

[0614] In this invention, the server includes means for periodically transmitting the user's lifestyle information to the server, means for the server to store the transmitted lifestyle information in a database, means for analysing the lifestyle information using a data analysis algorithm and assessing the user's condition, means for generating an optimum holiday plan based on the analysis results, means for transmitting and notifying the user of the generated holiday plan to a user terminal, and means for collecting user feedback and improving the analysis algorithm. This makes it possible to provide specific and accurate holiday plans suited to the user's individual health condition and lifestyle rhythm.

[0615] "User's lifestyle information" is data related to the user's daily life, and includes health information, exercise information, and schedule information.

[0616] The term "fixed cycle" refers to a preset time interval, such as a daily or weekly cycle.

[0617] "Server" refers to a computer system for receiving, storing, and analyzing data sent from a user terminal.

[0618] "Database" refers to an information management system used by a server to store users' life information.

[0619] "Data analysis algorithm" refers to a series of calculation methods used by the server to analyze the user's lifestyle information and evaluate the user's condition.

[0620] A "holiday plan" refers to a plan that suggests activities that are optimal for the user's health condition and lifestyle based on the analysis results.

[0621] A "user terminal" refers to a device used by a user, such as a smartphone or PC, that is capable of communicating with a server.

[0622] "Feedback" refers to the rating and opinion information provided by a user regarding a proposed holiday plan.

[0623] "Improving the analysis algorithm" refers to the process of adjusting the data analysis algorithm based on feedback information collected from users to improve the accuracy of the next proposal.

[0624] The present invention is a system for generating optimal holiday plans based on a user's lifestyle information and notifying the user of the plans. The system includes a user terminal, a server, and a network over which these communicate.

[0625] User device functions

[0626] The user device will automatically collect information about the user's daily life by linking with various healthcare and calendar apps. Specifically, the following data will be collected:

[0627] sleep time

[0628] Heart rate

[0629] Step count

[0630] Calendar events

[0631] The collected data is sent to a server at regular intervals, and this communication is securely carried out using encryption protocols such as SSL / TLS.

[0632] Server Features

[0633] The server receives the data sent from the user terminal and stores it in a database. Then, the server uses a data analysis algorithm to perform data analysis, including the following elements:

[0634] Assessment of average sleep time

[0635] Heart rate abnormality detection

[0636] Assessment of exercise volume

[0637] Schedule balance assessment

[0638] Based on the results of the data analysis, the server generates the optimal holiday plan for the user. The generated plan may include watching a movie or refreshing in a hot spring if you are not feeling well, walking in a nearby park if you are lacking exercise, or going on a day camp if you have little time to spend with family. The generated plan is sent to the user's device and notified to the user at the appropriate time.

[0639] User Notification and Feedback

[0640] The user device notifies the user of the plan sent from the server. The notification includes specific activity details and recommended locations and times. After the user carries out the proposed plan, the user device collects feedback. The feedback includes the usefulness of the plan. The feedback information is sent to the server and stored in a database. The server uses this feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions.

[0641] Specific examples

[0642] Example 1: Lack of exercise

[0643] The user's device collects data on weekdays and sends it to the server. Based on the analysis result that the user's physical activity is low, the server suggests walking in a nearby park on the weekend. The user receives a notification from the device and follows the suggestion. Later, the user provides feedback, which the server uses to improve the accuracy of the next suggestion.

[0644] Example 2: Family time

[0645] The user's device sends calendar information indicating that they have little time to spend with their family to the server. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback. Based on this feedback, the server adjusts the next suggestion more appropriately.

[0646] Example prompts for generative AI models

[0647] "Please create a program for a system that generates and notifies optimal holiday plans based on a user's weekday lifestyle information (e.g., sleep time, heart rate, number of steps, calendar events). This system includes user devices, a server, and the network over which they communicate."

[0648] This system will suggest optimal holiday plans based on the user's health condition and lifestyle, allowing them to spend their holidays more fulfillingly. Furthermore, by continuously improving the system based on feedback, the system will continue to provide highly accurate suggestions over time.

[0649] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0650] Step 1: Data collection

[0651] The user device connects with a healthcare app and a calendar app to collect weekday lifestyle information. Specifically, it obtains data on sleep time, heart rate, and number of steps from the healthcare app, and obtains the user's schedule information from the calendar app. These data are compiled into a data package. The input of this step is data from each app, and the output is the compiled data package.

[0652] Step 2: Send data

[0653] The user terminal transmits the collected data packages to the server at regular intervals (e.g., once a day). This communication is securely performed using encryption protocols such as SSL / TLS. The input is the data package, and the output is the transmission of encrypted data.

[0654] Step 3: Receiving data

[0655] The server receives data packages sent from user terminals. The received data is stored in a database. The input is the encrypted data package, and the output is the data stored in the database.

[0656] Step 4: Data analysis

[0657] The server analyzes the received data using a data analysis algorithm. Specifically, it calculates average sleep time using Python's pandas library and detects abnormal heart rate values ​​using scikit-learn's anomaly detection algorithm. It also evaluates the amount of exercise and schedule balance. The input is lifestyle information stored in the database, and the output is the analysis results.

[0658] Step 5: Generate a plan

[0659] The server generates an optimal holiday plan based on the results of the data analysis. For example, if you are not getting enough exercise, it will suggest walking in a nearby park, or if you don't spend much time with your family, it will suggest day camping. The input is the results of the data analysis, and the output is a specific holiday plan.

[0660] Step 6: Plan Notification

[0661] The server sends the generated holiday plan to the user's device. The user's device notifies the user of the plan at the appropriate time. The notification content includes specific activities and recommended locations and times. The input is the specific holiday plan, and the output is a notification to the user.

[0662] Step 7: Gather feedback

[0663] After the user executes the proposed plan, the user terminal collects feedback. The feedback is in the form of questions about the usefulness of the plan and whether the activity was enjoyable. The input is the user's answer, and the output is the collected feedback data.

[0664] Step 8: Send your feedback

[0665] The user terminal sends the collected feedback data to the server, which stores the data in a database. The input is the feedback data, and the output is the feedback stored in the database.

[0666] Step 9: Improve the analysis algorithm

[0667] The server improves the analysis algorithm based on the collected feedback. For example, if a particular plan is popular, it may be given higher priority. The input is the feedback data, and the output is an improved analysis algorithm.

[0668] These specific processing steps make it possible to continuously provide optimal holiday plans to users.

[0669] (Application example 1)

[0670] 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."

[0671] Conventional self-driving vehicles lack the functionality to utilize the user's health information and schedule to provide optimal driving routes, rest spots, and activities while traveling. As a result, users are unable to receive appropriate suggestions for entertainment and health promotion while traveling, making it difficult to enjoy an efficient and comfortable driving experience. The present invention aims to solve this problem and provide users with optimal suggestions even while traveling.

[0672] 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.

[0673] In this invention, the server includes: means for collecting user lifestyle information; means for analyzing the collected lifestyle information; means for generating an optimal holiday plan based on the analysis results; means for notifying the user of the generated holiday plan; means including an application installed in the self-driving vehicle; means for suggesting optimal driving routes, rest spots, and activities based on the user's lifestyle data; means for notifying the user of the suggestions in real time while driving; and means for collecting feedback provided by the user and improving the accuracy of the suggestions for the next trip. This enables the user to receive optimal suggestions based on their health condition and schedule even while on the move, enabling them to enjoy a comfortable and efficient driving experience.

[0674] "User's lifestyle information" is data related to the user's daily life, including, for example, sleep time, heart rate, number of steps, calendar schedule, and the like.

[0675] The term "means" refers to a method or device for achieving a specific purpose, and in this invention refers to a method or device for realizing functions such as data collection, analysis, notification, and feedback collection.

[0676] "Applications installed in autonomous vehicles" refers to software installed inside vehicles with autonomous driving capabilities that analyzes user data and provides notifications.

[0677] "User's lifestyle data" is a general term for various information generated in the course of a user's daily life, and includes health information, schedule information, and the like.

[0678] The "optimal driving route" refers to the most efficient and convenient driving route for the user, calculated and suggested based on the user's health condition and schedule.

[0679] "Rest Spots" refers to suitable places for users to take a rest while driving, and are suggested based on their health status and schedule.

[0680] "Activity" refers to fitness and entertainment related activities that a user can engage in while driving.

[0681] The "means for notifying the user of the proposed content in real time" refers to a method or device for instantly notifying the user's terminal of the analysis results and the recommended plan while driving.

[0682] "User-provided feedback" refers to the user's reactions to the suggestions, such as evaluations and impressions, and is information that the system uses to improve its next suggestions.

[0683] The present invention provides a system that generates optimal holiday plans based on a user's lifestyle information and notifies the user of the plans. The system includes a user terminal, an application installed in an autonomous vehicle, a cloud server, and a network over which these communicate.

[0684] User device functions

[0685] Data collection

[0686] The user's device connects to various healthcare and calendar apps to collect weekday lifestyle information. This connection automatically collects the following data, for example, using the health information API or Google Calendar API.

[0687] sleep time

[0688] Heart rate

[0689] Step count

[0690] Calendar events

[0691] Data transmission

[0692] The collected data is sent to the server at regular intervals. This communication is secure, using encrypted communication such as SSL / TLS, to protect user privacy.

[0693] Cloud Server Functions

[0694] Data reception

[0695] The server receives the data sent from the user terminal and stores it in an internal database.

[0696] Data analysis

[0697] The server analyzes the collected data, which may include the following elements:

[0698] Is your average sleep time sufficient?

[0699] Is there any abnormality in your heart rate?

[0700] Is the amount of exercise enough?

[0701] Calendar overload or balance

[0702] These analyses are performed using data analysis tools using Python and R. For example, if the average sleep time is less than six hours, the system will suggest watching a movie.

[0703] Plan Generation

[0704] Based on the results of the data analysis, the server generates the optimal holiday plan for the user, which may include:

[0705] If you're not feeling well: Watch a movie or relax in a hot spring

[0706] If you are not getting enough exercise: Walking in a nearby park or using sports facilities

[0707] If you don't have much time with your family: Day camping or picnics

[0708] This plan generation may be powered by a generative AI model, which applies machine learning algorithms to provide a customized plan for each user.

[0709] notification

[0710] The generated plan is sent to the user's device and notifications are sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. Notifications are sent using a dedicated notification API.

[0711] Autonomous vehicle features

[0712] Real-time suggestions

[0713] The application installed in the autonomous vehicle will suggest optimal driving routes, rest spots, and activities based on the user's lifestyle data, including a function to optimize driving routes in conjunction with the GPS module.

[0714] User Feedback

[0715] Feedback collection

[0716] After the user implements the proposed plan, the user device collects feedback, for example, by displaying a question such as "Was this plan helpful?"

[0717] Send Feedback

[0718] The feedback provided by the user is sent to the server and stored in a database.

[0719] Improved accuracy

[0720] The server then uses the collected feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions. This cycle allows the server to continually provide plans that better suit the user's needs.

[0721] Prompt Sentence Examples

[0722] Design a system that collects a user's health data and generates an optimal holiday plan based on that data. The holiday plan includes entertainment (e.g., watching movies), exercise (e.g., walking), and family activities (e.g., day camping). Analyze the plan based on the user's sleep time, heart rate, number of steps, and calendar events. Also include a function to improve the next proposal based on user feedback.

[0723] This invention allows users to have a fulfilling holiday by receiving optimal holiday plans based on their weekday lifestyle information. Furthermore, users can receive suggestions for optimal driving routes and rest spots while on the move, realizing an efficient and comfortable driving experience.

[0724] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0725] Step 1:

[0726] Data collection

[0727] The user's device uses the health information API and Google Calendar API to collect the user's lifestyle information (sleep time, heart rate, number of steps, calendar schedule). For example, the user's average sleep time and heart rate are obtained from the health app API, and the user's schedule information is obtained from the Google Calendar API. This data is collected and saved in the device in JSON format.

[0728] Input: Data from smartphone health information API and Google Calendar API.

[0729] Output: User's lifestyle information data (JSON format).

[0730] Step 2:

[0731] Data transmission

[0732] The user device securely transmits the collected lifestyle information data to the cloud server at regular intervals (e.g., daily or weekly). This communication uses encryption protocols such as SSL / TLS. For example, data such as the user's sleep time and heart rate is transmitted to the server using HTTPS.

[0733] Input: Collected user lifestyle information data.

[0734] Output: Lifestyle information data stored on a cloud server.

[0735] Step 3:

[0736] Data reception

[0737] The server receives the lifestyle information data sent from the user terminal and stores it in a database, for example, using a database management system (DBMS).

[0738] Input: Lifestyle information data sent from the user's device.

[0739] Output: Life information data stored in a database.

[0740] Step 4:

[0741] Data analysis

[0742] The server analyzes the lifestyle information data stored in the database. For example, it processes the data using Python data analysis libraries (Pandas and NumPy) to calculate average sleep time, heart rate, and exercise volume. Based on this, the server evaluates the user's health status and selects activities suitable for future holiday plans. As a specific example, it suggests walking if the user is not getting enough exercise.

[0743] Input: Lifestyle information data stored in a database.

[0744] Output: Analysis results (e.g. lack of exercise, lack of average sleep time).

[0745] Step 5:

[0746] Plan Generation

[0747] The server then uses a generative AI model based on the results of the data analysis to create an optimal holiday plan. For example, if the user is not getting enough exercise, it might suggest walking in a nearby park. This generation process uses machine learning algorithms and takes into account the user's past feedback.

[0748] Input: Analysis results, user feedback.

[0749] Output: Recommended optimal holiday plans.

[0750] Step 6:

[0751] Plan Notification

[0752] The server then sends the generated holiday plan to the user's device and notifies them at the appropriate time. For example, it uses a dedicated notification API to send push notifications to the user. The notifications include specific activities, recommended locations, and times.

[0753] Input: The generated holiday plan.

[0754] Output: Notification content sent to the user's terminal.

[0755] Step 7:

[0756] Real-time suggestions

[0757] While driving, an application installed in the autonomous vehicle will suggest optimal driving routes, rest spots, and activities in real time based on the user's lifestyle data. For example, it will use the GPS function to obtain the current location and display suitable rest spots.

[0758] Input: User's daily life data, current GPS location information.

[0759] Output: Real-time driving routes, rest stops, and activity suggestions.

[0760] Step 8:

[0761] Feedback collection

[0762] After the user implements the proposed plan, the user terminal collects feedback. For example, a question such as "Was this plan helpful?" is displayed on the application and the user's answer is obtained.

[0763] Input: User feedback.

[0764] Output: User feedback data.

[0765] Step 9:

[0766] Send Feedback

[0767] The collected feedback is sent to the server and stored in a database, and this data is also used to improve the accuracy of the next suggestion.

[0768] Input: Feedback data from user terminal.

[0769] Output: Feedback data stored in a database.

[0770] Step 10:

[0771] Improved accuracy

[0772] The server updates its analysis algorithms based on the collected feedback data to improve the accuracy of its next plan proposals, for example by retraining the machine learning model to learn new feedback patterns.

[0773] Input: Feedback data.

[0774] Output: The updated parsing algorithm.

[0775] 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.

[0776] System Overview

[0777] The present invention is a system that generates optimal holiday plans based on a user's lifestyle information and emotional state and notifies the user of the plans. The system includes a user terminal, a server, an emotion engine, and a network over which these communicate.

[0778] User device functions

[0779] Data collection

[0780] The user device automatically collects weekday lifestyle information and emotional state. Specifically, it connects with a healthcare app to obtain the following data:

[0781] sleep time

[0782] Heart rate

[0783] Step count

[0784] Calendar events

[0785] In addition, an emotion engine analyzes the user's emotional state and collects emotional information through text messages, voice input, etc.

[0786] Data transmission

[0787] The collected lifestyle and emotional information is periodically sent to a server, including daily sleep duration, average heart rate, number of steps taken, schedule details, and an indicator of emotional state.

[0788] Server Features

[0789] Data reception

[0790] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the server checks the consistency and integrity of the data.

[0791] Data analysis

[0792] The server launches a data analysis module and an emotion engine to analyze the received lifestyle and emotion information. The analysis evaluates the following factors:

[0793] Is your average sleep time sufficient?

[0794] Is there any abnormality in your heart rate?

[0795] Is the amount of exercise enough?

[0796] Is there an over-schedule?

[0797] The user's emotional state (e.g., stress level, happiness)

[0798] Plan Generation

[0799] Based on the results of the data analysis, the server generates the optimal holiday plan for the user. Based on the analysis results of the emotion engine, the plan is created taking into account the user's emotional state. For example, if the stress level is high, it will suggest relaxing activities, and if the happiness level is low, it will suggest activities that will help you change your mood.

[0800] notification

[0801] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time, including specific activities and recommended locations and times.

[0802] User Feedback

[0803] Feedback collection

[0804] After the user implements the proposed plan, the user device collects feedback and emotional state, such as questions like "Was this plan helpful?" and "Did you feel better after this activity?"

[0805] Send Feedback

[0806] The feedback and emotional state data provided by the user are sent to a server and stored in a database.

[0807] Improved accuracy

[0808] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, increasing the accuracy of future plan suggestions. This cycle allows the server to continuously provide plans that better suit the user's needs.

[0809] Specific examples

[0810] Example 1: Lack of exercise and stress

[0811] The user's device collects data on weekdays and sends it to the server indicating that the user's exercise volume is low and stress levels are high. The server receives and analyzes this data and suggests walking and meditating in a nearby park on the weekend. The user receives a notification from the device and actually walks and meditates. Later, the user provides feedback and emotional state, which the server uses to improve the accuracy of its next suggestions.

[0812] Example 2: Family time and happiness

[0813] The user's device transmits information from the user's calendar and emotional state to the server, indicating that the user spends little time with family and has a low happiness level. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback and their emotional state. Based on this feedback and emotional information, the server adjusts the next suggestion more appropriately.

[0814] The present invention allows users to have a fulfilling holiday by receiving an optimal holiday plan based on their weekday lifestyle information and emotional state, which helps them maintain a healthy state of mind and body.

[0815] The processing flow will be explained below.

[0816] Processing Steps

[0817] Step 1:

[0818] The user's device automatically collects weekday lifestyle and emotional information. Specifically, it connects with a healthcare app to obtain data on sleep time, heart rate, and number of steps. It also obtains schedule information from a calendar app, and the emotion engine analyzes text messages and voice input to evaluate the user's emotional state.

[0819] Step 2:

[0820] The user device periodically transmits the collected data to the server, including average sleep time, average heart rate, number of steps, schedule details, and indicators of emotional state for each day.

[0821] Step 3:

[0822] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the consistency and completeness of the data are verified.

[0823] Step 4:

[0824] The server launches the data analysis module and emotion engine to analyze the received data. The analysis considers the following factors:

[0825] Is your average sleep time sufficient?

[0826] Is there any abnormality in your heart rate?

[0827] Is the amount of exercise enough?

[0828] Isn't the schedule too busy?

[0829] The user's emotional state (e.g., stress level, happiness)

[0830] Step 5:

[0831] The server generates an optimal holiday plan based on the results of data analysis. Specifically, it creates a plan that takes into account the user's emotional state based on the analysis results of the emotion engine. For example, it suggests relaxing activities (watching movies, meditating, visiting hot springs) for a user with a high stress level, and activities that will change your mood (walking, bouldering, meeting up with friends) for a user with a low happiness level.

[0832] Step 6:

[0833] The server sends the generated holiday plan to the user's device, along with detailed information such as the specific contents of the plan, location, and time.

[0834] Step 7:

[0835] The user terminal notifies the user of the holiday plan received from the server. The notification function is also used to notify the user of the proposal and display the detailed plan contents.

[0836] Step 8:

[0837] The user carries out the proposed plan. After the holiday, the user's device collects feedback and emotional state after the plan is implemented. For example, questions such as "Was this plan helpful?" and "How did your mood change after this activity?" are displayed.

[0838] Step 9:

[0839] The user terminal transmits the collected feedback and emotional state data to the server, which stores the collected feedback and data in a database.

[0840] Step 10:

[0841] The server analyzes the received feedback and emotional information, and adjusts and improves the holiday plan generation algorithm and emotional engine for future trips. By continuously performing this analysis and adjustment, the accuracy of providing plans that better suit the user's needs and emotional state increases.

[0842] Specific examples

[0843] Example 1: Lack of exercise and stress

[0844] The user's device collects data from the weekdays and sends it to the server, indicating that the user's exercise volume is low and stress levels are high. The server receives and analyzes this data, and then suggests a walking and meditation session at a nearby park on the weekend. The user receives this notification from their device and actually walks and meditates. Later, the user provides feedback and emotional state, which the server uses to improve the accuracy of the next suggestion.

[0845] Example 2: Family time and happiness

[0846] The user's device transmits to the server, based on the user's calendar information and emotional information, information indicating that they spend little time with their family and their happiness level is low. The server analyzes this information and suggests a day camp that the family can enjoy. The user accepts the suggestion and actually enjoys the day camp. After the suggestion, the user provides feedback and their emotional state. The server then adjusts the next suggestion based on this feedback.

[0847] This allows users to receive suggestions for optimal holiday plans based on their weekday lifestyle information and emotional state, helping them maintain a healthy state of mind and body.

[0848] Example 2

[0849] 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."

[0850] In modern society, there is a demand for systems that comprehensively evaluate users' lifestyles, health, and emotional states, and then provide optimal holiday plans based on these assessments. However, conventional systems have been unable to effectively provide customized plans suited to individual users due to insufficient collection and analysis of users' lifestyle information. In particular, there has been a lack of systems that provide plans that take into account the user's emotional state, and measures are needed to further improve users' emotional satisfaction.

[0851] 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.

[0852] In this invention, the server comprises means for collecting lifestyle information and emotional information of the user, means for transmitting the collected lifestyle information and emotional information to the server, means for analysing the lifestyle information and emotional information received by the server and assessing the user's condition, means for introducing a generative AI model which generates an optimal holiday plan based on the analysis results, and means for notifying the user terminal of the generated holiday plan. This makes it possible to provide a more customised holiday plan that takes into account the user's individual lifestyle rhythm and emotional state.

[0853] "User's lifestyle information" is data related to the user's daily life, including sleep time, heart rate, number of steps, calendar schedule, and the like.

[0854] "Emotional information" refers to the emotional state (such as stress level or happiness) analyzed from a user's text messages or voice input.

[0855] The "server" is a computer system that receives lifestyle information and emotional information sent from the user's device, analyzes it, and generates holiday plans using a generative AI model.

[0856] "Generative AI model" refers to artificial intelligence algorithms or software that generate optimal holiday plans for users based on the data they receive.

[0857] A "user terminal" is a device used to collect information about a user's daily life and emotions and transmit this data to a server, and examples of such devices include smartphones and tablets.

[0858] "Plan generation" refers to the process by which the server creates an optimal holiday plan for the user based on the analysis results.

[0859] "Notification" refers to the act of informing the user of the holiday plan generated by the server, and is done in the form of a push notification or the like.

[0860] "Feedback" refers to information that records the user's thoughts and emotional state regarding the plan they have implemented and is used to improve the accuracy of future plan proposals.

[0861] MODE FOR CARRYING OUT THE INVENTION

[0862] The present invention is a system that generates optimal holiday plans based on a user's lifestyle information and emotional state and notifies the user of the plans. The system includes a user terminal, a server, an emotion engine, and a network over which these communicate.

[0863] User device functions

[0864] Data collection

[0865] The user device collects weekday lifestyle information and emotional state. The specific hardware used is a smartphone, and the device connects with a healthcare app (e.g., Apple Health or Google Fit) installed on the device to acquire the following data:

[0866] User sleep time

[0867] User's heart rate

[0868] User steps

[0869] User's calendar events

[0870] The emotion engine analyzes the user's text messages and voice inputs to gather emotional states (e.g., stress levels and happiness).

[0871] Data transmission

[0872] The collected lifestyle and emotional information is periodically sent to a server. Specifically, the data sent includes each day's sleep duration, average heart rate, number of steps, schedule details, and indicators of emotional state. Data is sent using FTP or HTTP protocols.

[0873] Server Features

[0874] Data reception

[0875] The server receives the data sent from the user terminal and stores it in a database. The database may be MySQL or PostgreSQL, for example. The consistency and completeness of the data is checked upon receipt.

[0876] Data analysis

[0877] The server launches a data analysis module implemented in a programming language such as Python to analyze the received lifestyle and emotion information. The analysis evaluates the following factors:

[0878] Is your average sleep time sufficient?

[0879] Is there any abnormality in your heart rate?

[0880] Is the amount of exercise enough?

[0881] Is there an over-schedule?

[0882] The user's emotional state (e.g., stress level, happiness)

[0883] Additionally, an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) is used to assess the emotional state.

[0884] Plan Generation

[0885] Based on the analysis results, the server generates the optimal holiday plan for the user using a generative AI model (e.g., GPT-4) and generates the plan by sending prompts.

[0886] Example prompt sentence:

[0887] "Please suggest the best holiday plan for users who are lacking exercise and have high stress levels. Include specific activity and location suggestions."

[0888] notification

[0889] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. The notification is sent using a push notification service (e.g., Firebase Cloud Messaging).

[0890] User Feedback

[0891] Feedback collection

[0892] After the user implements the proposed plan, the user terminal collects feedback and emotional state, for example, displaying questions such as "Was this plan helpful?" and "Did you feel better after this activity?"

[0893] Send Feedback

[0894] The collected feedback and emotional state data is sent to a server and stored in a database.

[0895] Improved accuracy

[0896] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, increasing the accuracy of future plan suggestions. This cycle allows the server to continuously provide plans that better suit the user's needs.

[0897] In this manner, the present invention proposes optimal holiday plans based on the user's lifestyle information and emotional state, and supports the user in having a fulfilling holiday.

[0898] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0899] Step 1:

[0900] Data collection from user devices

[0901] The user's device collects information about their weekday lifestyle and emotional state. Specifically, it connects with healthcare apps (e.g., Apple Health or Google Fit) installed on their smartphone to obtain the user's sleep time, heart rate, number of steps, and calendar appointments. The emotion engine also analyzes the user's text messages and voice input to collect their emotional state (stress level and happiness).

[0902] Input: User's life information and emotional state

[0903] Output: Collected data

[0904] Step 2:

[0905] Data transmission by user terminal

[0906] The user device periodically transmits the collected data to the server. Specifically, the transmitted data includes daily sleep duration, average heart rate, number of steps, calendar appointments, and indicators of emotional state. Data transmission is performed using FTP or HTTP protocols.

[0907] Input: Collected lifestyle and emotional information

[0908] Output: Data sent to the server

[0909] Step 3:

[0910] Data reception by the server

[0911] The server receives the data sent from the user terminal and stores it in a database. Upon receiving the data, it checks its consistency and completeness. The database used can be, for example, MySQL or PostgreSQL.

[0912] Input: Data sent from the user's device

[0913] Output: Data stored in the database

[0914] Step 4:

[0915] Data analysis by server

[0916] The server launches a data analysis module using a programming language such as Python to analyze the received lifestyle and emotion information. The analysis evaluates the following elements:

[0917] Is your average sleep time sufficient?

[0918] Is there any abnormality in your heart rate?

[0919] Is the amount of exercise enough?

[0920] Is there an over-schedule?

[0921] The user's emotional state (e.g., stress level, happiness)

[0922] Additionally, an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) is used to assess the emotional state.

[0923] Input: Received lifestyle and emotional information

[0924] Output: Analysis results

[0925] Step 5:

[0926] Server-generated plan

[0927] The server generates an optimal holiday plan based on the analysis results. The plan is generated using a generative AI model (e.g., GPT-4) and is generated by sending prompts.

[0928] Input: Analysis results

[0929] Output: Generated holiday plan

[0930] Example prompt sentence:

[0931] "Please suggest the best holiday plan for users who are lacking exercise and have high stress levels. Include specific activity and location suggestions."

[0932] Step 6:

[0933] Server Notification

[0934] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. The notification is sent using a push notification service (e.g., Firebase Cloud Messaging).

[0935] Input: Generated holiday plan

[0936] Output: Notification to user terminal

[0937] Step 7:

[0938] Collecting user feedback

[0939] After the user implements the proposed plan, the user device collects feedback and emotional state, such as questions like "Was this plan helpful?" and "Did you feel better after this activity?"

[0940] Input: User's performance and emotional state

[0941] Output: Collected feedback data

[0942] Step 8:

[0943] Send Feedback

[0944] The user's feedback and emotional state data are sent to the server. The sending process uses FTP or HTTP protocols, similar to data transmission.

[0945] Input: Collected feedback data

[0946] Output: Feedback data sent to the server

[0947] Step 9:

[0948] Server-based accuracy improvement

[0949] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, improving the accuracy of future plan suggestions. For example, if a particular activity was highly beneficial to the user, the server will adjust its suggestions to suggest more similar activities.

[0950] Input: Feedback and emotional information data

[0951] Output: Improved algorithms and sentiment engine

[0952] By executing these steps in succession, a system is realized that provides users with optimal holiday plans and supports healthy living both physically and mentally.

[0953] (Application example 2)

[0954] 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."

[0955] Conventional systems that propose optimal holiday plans to users based on lifestyle and emotional information have had issues with the accuracy of their proposals and their feasibility in the real world. Specifically, they lack real-time guidance based on the user's current location, and they also lack sufficient feedback to confirm whether the proposed plans are actually beneficial to the user. Therefore, there is a need for a system that provides real-time guidance using the user's location information and smart devices, as well as improving the accuracy of proposals based on feedback.

[0956] The identification process performed by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting user lifestyle information, means for analyzing the collected lifestyle information and emotional state, means for generating an optimal experience plan based on the analysis results, means for notifying the user of the generated experience plan, means for guiding the user to the proposed plan's location based on the user's location information, means for collecting feedback obtained by the user through the experience at the physical store, means for improving the accuracy of the next proposal based on the collected feedback and emotional information, means including emotion analysis software and a database management system, and means for generating prompt sentences and inputting them into the generative AI model. This enables the user to be provided with an optimal experience in real time and guided to the experience location. Furthermore, collecting feedback can improve the accuracy of future proposals.

[0957] "Lifestyle information" refers to data related to the user's daily life, including health status, amount of exercise, schedule, and the like.

[0958] "Emotional state" is an indicator of the user's current psychological state, and includes stress level, happiness level, and the like.

[0959] "Experience Plan" refers to activities or schedules that a user is encouraged to undertake over a specific period of time.

[0960] "Notification means" refers to a method or device for notifying the user of the generated experience plan.

[0961] "Location information" is information that indicates the user's current geographical location.

[0962] "Guidance means" refers to a method or device that provides directions and detailed information to the location where the user will carry out the proposed experience plan.

[0963] "Feedback" refers to the user's evaluation and impressions of the experience plan they implemented.

[0964] "Emotion analysis software" refers to programs and algorithms used to analyze a user's emotional state.

[0965] A "database management system" is a system for storing, managing, and retrieving collected data.

[0966] A "generative AI model" is an artificial intelligence model used to generate a proposed experience plan.

[0967] A "prompt sentence" is an instruction sentence that is input into a generative AI model to obtain a generated result based on the user's situation and wishes.

[0968] As an embodiment of the present invention, an application installed on smart glasses will be specifically described.

[0969] Generating a Program

[0970] The system is realized using smart glasses, emotion analysis software, a database management system, a cloud server, and a generative AI model.

[0971] Hardware and Software

[0972] 1. Smart Glasses:

[0973] Sensors: Heart rate monitor, pedometer, GPS

[0974] Display: For presenting information

[0975] 2. Sentiment Analysis Software:

[0976] Example: Using various SDKs (e.g. Affectiva SDK)

[0977] 3. Database Management System:

[0978] Example: MySQL

[0979] 4. Cloud Server:

[0980] Example: AWS EC2

[0981] 5. Recommended engines:

[0982] Example: AWS SageMaker

[0983] explanation

[0984] 1. Data Collection:

[0985] The server uses the smart glasses' built-in sensors to collect the user's heart rate, steps, and GPS information in real time.

[0986] Emotion analysis software is used to analyze a user's emotional state from their text messages and voice inputs.

[0987] 2. Data transmission:

[0988] The collected data is sent to a cloud server at a fixed interval, where the data is checked for consistency and completeness.

[0989] 3. Data Analysis:

[0990] The data received by the cloud server is stored in a database management system (MySQL).

[0991] The data analysis module on the server evaluates the user's health and emotional state, calculating stress levels and happiness based on heart rate, steps, GPS information, and emotional state.

[0992] 4. Plan Generation:

[0993] A recommendation engine (AWS SageMaker) is used to generate optimal experience plan candidates based on the analysis results.

[0994] For example, if a user's stress level is high, the system recommends tea time at a relaxing cafe.

[0995] 5. Notices and Guidance:

[0996] The generated experience plan is displayed on the smart glasses' display, and the shortest route to the proposed experience location is also provided based on the user's location information.

[0997] Guidance is updated in real time, so the user is provided with appropriate directions based on their current location.

[0998] 6. User Feedback:

[0999] After completing the proposed experience plan, users enter their feedback through the smart glasses. The feedback form includes questions such as, "Did you find this time relaxing?"

[1000] The feedback and additional emotion data are sent to a cloud server and used to improve the accuracy of the next suggestion.

[1001] Specific examples

[1002] A day in smart glasses

[1003] 1. Data Collection and Analysis:

[1004] During the day, the smart glasses collect the user's heart rate, steps, and GPS information, and analyze stress levels through text messages.

[1005] For example, at 3pm, an increased heart rate and increased stress are observed.

[1006] 2. Plan Generation and Notification:

[1007] The cloud server obtains as an analysis result that the user's stress level is high.

[1008] Suggestion: The smart glasses display recommends a relaxing tea time at a quiet nearby cafe.

[1009] The smart glasses also display directions to the selected cafe.

[1010] 3. Practice and feedback:

[1011] After a user has tea time at a cafe, they input feedback through the smart glasses, such as "Was this time relaxing?"

[1012] The feedback and emotion data are sent to a cloud server and used to improve the accuracy of future plan generation.

[1013] Prompt Sentence Examples

[1014] "User data:

[1015] Heart rate average: 80

[1016] Steps: 3000

[1017] Sleep time: 6 hours

[1018] Emotional state: Stress

[1019] User location: Shibuya-ku, Tokyo

[1020] suggestion:

[1021] "Please suggest a place where users can relax."

[1022] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1023] Step 1:

[1024] The smart glasses use built-in sensors to collect the user's heart rate, steps, and GPS information in real time. The inputs are heart rate, steps, and GPS data, and the output is the collected raw data.

[1025] Step 2:

[1026] The collected data is then used to analyze the user's emotional state using emotion analysis software. The input is text messages or voice input, and the output is analyzed emotional data.

[1027] Step 3:

[1028] The device sends the collected lifestyle information and emotional information to a cloud server. The inputs are heart rate, step count, GPS data, and emotional data, and the output is the integrated data sent to the cloud server.

[1029] Step 4:

[1030] The cloud server stores the received data in a database management system (MySQL) and performs the necessary consistency checks. The input is the transmitted integrated data, and the output is the data stored in the database.

[1031] Step 5:

[1032] The cloud server launches the data analysis module and analyzes the stored data. The input is the user's lifestyle and emotional information obtained from the database, and the output is the analysis results. Specifically, the average heart rate, total number of steps, stress level, etc. are calculated.

[1033] Step 6:

[1034] Using a recommendation engine (AWS SageMaker), an optimal experience plan is generated based on the analysis results. The input is the analysis results, and the output is the generated experience plan.

[1035] Step 7:

[1036] The cloud server notifies the smart glasses of the generated experience plan. The input is the experience plan, and the output is the plan displayed on the smart glasses' display.

[1037] Step 8:

[1038] The smart glasses use location information to guide the user to the proposed plan location. The input is the user's current location and the proposed location, and the output is the route displayed on the smart glasses' display.

[1039] Step 9:

[1040] After the user executes the plan, they input feedback through the smart glasses. The input is the user's feedback and additional emotional data, and the output is the collected feedback.

[1041] Step 10:

[1042] The collected feedback is sent to the cloud server again and stored in a database. The input is the user's feedback data, and the output is the feedback stored in the database.

[1043] Step 11:

[1044] The cloud server analyzes the collected feedback and updates the generative AI model to improve the accuracy of future plan generation. The input is the feedback data, and the output is the updated generative AI model.

[1045] 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.

[1046] 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.

[1047] 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.

[1048] [Third embodiment]

[1049] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1050] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1051] 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).

[1052] 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.

[1053] 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.

[1054] 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).

[1055] 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.

[1056] 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.

[1057] 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.

[1058] 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.

[1059] 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.

[1060] 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."

[1061] System Overview

[1062] The present invention is a system for generating optimal holiday plans based on a user's lifestyle information and notifying the user of the plans. The system includes a user terminal, a server, and a network over which these communicate.

[1063] User device functions

[1064] Data collection

[1065] The user device will connect to various healthcare and calendar apps to collect weekday lifestyle information. Through this connection, the following data will be automatically collected:

[1066] sleep time

[1067] Heart rate

[1068] Step count

[1069] Calendar events

[1070] Data transmission

[1071] The collected data is sent to a server at regular intervals. This communication is secure, protecting user privacy.

[1072] Server Features

[1073] Data reception

[1074] The server receives the data sent from the user terminal and stores it in an internal database.

[1075] Data analysis

[1076] The server analyzes the collected data, which may include the following elements:

[1077] Is your average sleep time sufficient?

[1078] Is there any abnormality in your heart rate?

[1079] Is the amount of exercise enough?

[1080] Overscheduling and balance

[1081] Plan Generation

[1082] Based on the results of the data analysis, the server generates the optimal holiday plan for the user, which may include:

[1083] If you're not feeling well: Watch a movie or relax in a hot spring

[1084] If you are not getting enough exercise: Walking in a nearby park or using sports facilities

[1085] If you don't have much time with your family: Day camping or picnics

[1086] notification

[1087] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time, including specific activities and recommended locations and times.

[1088] User Feedback

[1089] Feedback collection

[1090] After the user implements the proposed plan, the user device collects feedback, for example, by displaying a question such as "Was this plan helpful?"

[1091] Send Feedback

[1092] The feedback provided by the user is sent to the server and stored in a database.

[1093] Improved accuracy

[1094] The server then uses the collected feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions. This cycle allows the server to continually provide plans that better suit the user's needs.

[1095] Specific examples

[1096] Example 1: Lack of exercise

[1097] The user's device collects data on weekdays and sends it to the server indicating that the user is not exercising much. The server receives and analyzes this data and suggests walking in a nearby park on the weekend. The user receives a notification from the device and actually goes for a walk. The user then provides feedback at a later date, which the server uses to improve the accuracy of its next suggestions.

[1098] Example 2: Family time

[1099] The user's device sends information from the user's calendar indicating that they have little time to spend with their family to the server. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback. Based on this feedback, the server adjusts the next suggestion more appropriately.

[1100] The present invention allows users to have a fulfilling holiday by being offered an optimal holiday plan based on their weekday lifestyle information, which helps them maintain a healthy state of mind and body.

[1101] The processing flow will be explained below.

[1102] Step 1:

[1103] The user's device automatically collects information about their weekday lifestyle. Specifically, it connects with a healthcare app to obtain data on sleep time, heart rate, and number of steps taken. It also obtains schedule information from a calendar app.

[1104] Step 2:

[1105] The user device periodically sends the collected data to the server, including the amount of sleep each day, average heart rate, number of steps taken, and schedule details.

[1106] Step 3:

[1107] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the consistency and completeness of the data are verified.

[1108] Step 4:

[1109] The server launches a data analysis module to analyze the received data, which evaluates whether the person is getting enough sleep, has an abnormal heart rate, is exercising enough, or has an overscheduled schedule.

[1110] Step 5:

[1111] The server generates an optimal holiday plan based on the results of the data analysis. Specifically, it suggests relaxing activities for users who are sleep-deprived, recommended exercise activities for users who are not getting enough exercise, and stress-relieving activities for users who have a busy schedule.

[1112] Step 6:

[1113] The server sends the generated holiday plan to the user's device, along with detailed information such as the specific contents of the plan, location, and time.

[1114] Step 7:

[1115] The user's device displays the holiday plan received from the server, and also notifies the user of the proposal using the notification function.

[1116] Step 8:

[1117] The user carries out the proposed plan, and after spending the holiday, the user's device collects feedback.

[1118] Step 9:

[1119] The user terminal sends the collected feedback to the server, including the usefulness and satisfaction of the suggestions.

[1120] Step 10:

[1121] The server analyzes the received feedback and adjusts and improves the holiday plan generation algorithm for future trips. This feedback cycle allows the server to provide a plan that is more suitable for the user.

[1122] Example 1

[1123] 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."

[1124] In modern life, there is a demand for a means to automatically suggest holiday plans that are suited to each individual's health condition and lifestyle. However, existing systems have difficulty effectively collecting and analyzing users' lifestyle information and providing optimal holiday plans for each individual. Furthermore, the accuracy of suggestions is limited due to a lack of functionality to continuously improve the system based on user feedback.

[1125] 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.

[1126] In this invention, the server includes means for periodically transmitting the user's lifestyle information to the server, means for the server to store the transmitted lifestyle information in a database, means for analysing the lifestyle information using a data analysis algorithm and assessing the user's condition, means for generating an optimum holiday plan based on the analysis results, means for transmitting and notifying the user of the generated holiday plan to a user terminal, and means for collecting user feedback and improving the analysis algorithm. This makes it possible to provide specific and accurate holiday plans suited to the user's individual health condition and lifestyle rhythm.

[1127] "User's lifestyle information" is data related to the user's daily life, and includes health information, exercise information, and schedule information.

[1128] The term "fixed cycle" refers to a preset time interval, such as a daily or weekly cycle.

[1129] "Server" refers to a computer system for receiving, storing, and analyzing data sent from a user terminal.

[1130] "Database" refers to an information management system used by a server to store users' life information.

[1131] "Data analysis algorithm" refers to a series of calculation methods used by the server to analyze the user's lifestyle information and evaluate the user's condition.

[1132] A "holiday plan" refers to a plan that suggests activities that are optimal for the user's health condition and lifestyle based on the analysis results.

[1133] A "user terminal" refers to a device used by a user, such as a smartphone or PC, that is capable of communicating with a server.

[1134] "Feedback" refers to the rating and opinion information provided by a user regarding a proposed holiday plan.

[1135] "Improving the analysis algorithm" refers to the process of adjusting the data analysis algorithm based on feedback information collected from users to improve the accuracy of the next proposal.

[1136] The present invention is a system for generating optimal holiday plans based on a user's lifestyle information and notifying the user of the plans. The system includes a user terminal, a server, and a network over which these communicate.

[1137] User device functions

[1138] The user device will automatically collect information about the user's daily life by linking with various healthcare and calendar apps. Specifically, the following data will be collected:

[1139] sleep time

[1140] Heart rate

[1141] Step count

[1142] Calendar events

[1143] The collected data is sent to a server at regular intervals, and this communication is securely carried out using encryption protocols such as SSL / TLS.

[1144] Server Features

[1145] The server receives the data sent from the user terminal and stores it in a database. Then, the server uses a data analysis algorithm to perform data analysis, including the following elements:

[1146] Assessment of average sleep time

[1147] Heart rate abnormality detection

[1148] Assessment of exercise volume

[1149] Schedule balance assessment

[1150] Based on the results of the data analysis, the server generates the optimal holiday plan for the user. The generated plan may include watching a movie or refreshing in a hot spring if you are not feeling well, walking in a nearby park if you are lacking exercise, or going on a day camp if you have little time to spend with family. The generated plan is sent to the user's device and notified to the user at the appropriate time.

[1151] User Notification and Feedback

[1152] The user device notifies the user of the plan sent from the server. The notification includes specific activity details and recommended locations and times. After the user carries out the proposed plan, the user device collects feedback. The feedback includes the usefulness of the plan. The feedback information is sent to the server and stored in a database. The server uses this feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions.

[1153] Specific examples

[1154] Example 1: Lack of exercise

[1155] The user's device collects data on weekdays and sends it to the server. Based on the analysis result that the user's physical activity is low, the server suggests walking in a nearby park on the weekend. The user receives a notification from the device and follows the suggestion. Later, the user provides feedback, which the server uses to improve the accuracy of the next suggestion.

[1156] Example 2: Family time

[1157] The user's device sends calendar information indicating that they have little time to spend with their family to the server. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback. Based on this feedback, the server adjusts the next suggestion more appropriately.

[1158] Example prompts for generative AI models

[1159] "Please create a program for a system that generates and notifies optimal holiday plans based on a user's weekday lifestyle information (e.g., sleep time, heart rate, number of steps, calendar events). This system includes user devices, a server, and the network over which they communicate."

[1160] This system will suggest optimal holiday plans based on the user's health condition and lifestyle, allowing them to spend their holidays more fulfillingly. Furthermore, by continuously improving the system based on feedback, the system will continue to provide highly accurate suggestions over time.

[1161] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1162] Step 1: Data collection

[1163] The user device connects with a healthcare app and a calendar app to collect weekday lifestyle information. Specifically, it obtains data on sleep time, heart rate, and number of steps from the healthcare app, and obtains the user's schedule information from the calendar app. These data are compiled into a data package. The input of this step is data from each app, and the output is the compiled data package.

[1164] Step 2: Send data

[1165] The user terminal transmits the collected data packages to the server at regular intervals (e.g., once a day). This communication is securely performed using encryption protocols such as SSL / TLS. The input is the data package, and the output is the transmission of encrypted data.

[1166] Step 3: Receiving data

[1167] The server receives data packages sent from user terminals. The received data is stored in a database. The input is the encrypted data package, and the output is the data stored in the database.

[1168] Step 4: Data analysis

[1169] The server analyzes the received data using a data analysis algorithm. Specifically, it calculates average sleep time using Python's pandas library and detects abnormal heart rate values ​​using scikit-learn's anomaly detection algorithm. It also evaluates the amount of exercise and schedule balance. The input is lifestyle information stored in the database, and the output is the analysis results.

[1170] Step 5: Generate a plan

[1171] The server generates an optimal holiday plan based on the results of the data analysis. For example, if you are not getting enough exercise, it will suggest walking in a nearby park, or if you don't spend much time with your family, it will suggest day camping. The input is the results of the data analysis, and the output is a specific holiday plan.

[1172] Step 6: Plan Notification

[1173] The server sends the generated holiday plan to the user's device. The user's device notifies the user of the plan at the appropriate time. The notification content includes specific activities and recommended locations and times. The input is the specific holiday plan, and the output is a notification to the user.

[1174] Step 7: Gather feedback

[1175] After the user executes the proposed plan, the user terminal collects feedback. The feedback is in the form of questions about the usefulness of the plan and whether the activity was enjoyable. The input is the user's answer, and the output is the collected feedback data.

[1176] Step 8: Send your feedback

[1177] The user terminal sends the collected feedback data to the server, which stores the data in a database. The input is the feedback data, and the output is the feedback stored in the database.

[1178] Step 9: Improve the analysis algorithm

[1179] The server improves the analysis algorithm based on the collected feedback. For example, if a particular plan is popular, it may be given higher priority. The input is the feedback data, and the output is an improved analysis algorithm.

[1180] These specific processing steps make it possible to continuously provide optimal holiday plans to users.

[1181] (Application example 1)

[1182] 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."

[1183] Conventional self-driving vehicles lack the functionality to utilize the user's health information and schedule to provide optimal driving routes, rest spots, and activities while traveling. As a result, users are unable to receive appropriate suggestions for entertainment and health promotion while traveling, making it difficult to enjoy an efficient and comfortable driving experience. The present invention aims to solve this problem and provide users with optimal suggestions even while traveling.

[1184] 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.

[1185] In this invention, the server includes: means for collecting user lifestyle information; means for analyzing the collected lifestyle information; means for generating an optimal holiday plan based on the analysis results; means for notifying the user of the generated holiday plan; means including an application installed in the self-driving vehicle; means for suggesting optimal driving routes, rest spots, and activities based on the user's lifestyle data; means for notifying the user of the suggestions in real time while driving; and means for collecting feedback provided by the user and improving the accuracy of the suggestions for the next trip. This enables the user to receive optimal suggestions based on their health condition and schedule even while on the move, enabling them to enjoy a comfortable and efficient driving experience.

[1186] "User's lifestyle information" is data related to the user's daily life, including, for example, sleep time, heart rate, number of steps, calendar schedule, and the like.

[1187] The term "means" refers to a method or device for achieving a specific purpose, and in this invention refers to a method or device for realizing functions such as data collection, analysis, notification, and feedback collection.

[1188] "Applications installed in autonomous vehicles" refers to software installed inside vehicles with autonomous driving capabilities that analyzes user data and provides notifications.

[1189] "User's lifestyle data" is a general term for various information generated in the course of a user's daily life, and includes health information, schedule information, and the like.

[1190] The "optimal driving route" refers to the most efficient and convenient driving route for the user, calculated and suggested based on the user's health condition and schedule.

[1191] "Rest Spots" refers to suitable places for users to take a rest while driving, and are suggested based on their health status and schedule.

[1192] "Activity" refers to fitness and entertainment related activities that a user can engage in while driving.

[1193] The "means for notifying the user of the proposed content in real time" refers to a method or device for instantly notifying the user's terminal of the analysis results and the recommended plan while driving.

[1194] "User-provided feedback" refers to the user's reactions to the suggestions, such as evaluations and impressions, and is information that the system uses to improve its next suggestions.

[1195] The present invention provides a system that generates optimal holiday plans based on a user's lifestyle information and notifies the user of the plans. The system includes a user terminal, an application installed in an autonomous vehicle, a cloud server, and a network over which these communicate.

[1196] User device functions

[1197] Data collection

[1198] The user's device connects to various healthcare and calendar apps to collect weekday lifestyle information. This connection automatically collects the following data, for example, using the health information API or Google Calendar API.

[1199] sleep time

[1200] Heart rate

[1201] Step count

[1202] Calendar events

[1203] Data transmission

[1204] The collected data is sent to the server at regular intervals. This communication is secure, using encrypted communication such as SSL / TLS, to protect user privacy.

[1205] Cloud Server Functions

[1206] Data reception

[1207] The server receives the data sent from the user terminal and stores it in an internal database.

[1208] Data analysis

[1209] The server analyzes the collected data, which may include the following elements:

[1210] Is your average sleep time sufficient?

[1211] Is there any abnormality in your heart rate?

[1212] Is the amount of exercise enough?

[1213] Calendar overload or balance

[1214] These analyses are performed using data analysis tools using Python and R. For example, if the average sleep time is less than six hours, the system will suggest watching a movie.

[1215] Plan Generation

[1216] Based on the results of the data analysis, the server generates the optimal holiday plan for the user, which may include:

[1217] If you're not feeling well: Watch a movie or relax in a hot spring

[1218] If you are not getting enough exercise: Walking in a nearby park or using sports facilities

[1219] If you don't have much time with your family: Day camping or picnics

[1220] This plan generation may be powered by a generative AI model, which applies machine learning algorithms to provide a customized plan for each user.

[1221] notification

[1222] The generated plan is sent to the user's device and notifications are sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. Notifications are sent using a dedicated notification API.

[1223] Autonomous vehicle features

[1224] Real-time suggestions

[1225] The application installed in the autonomous vehicle will suggest optimal driving routes, rest spots, and activities based on the user's lifestyle data, including a function to optimize driving routes in conjunction with the GPS module.

[1226] User Feedback

[1227] Feedback collection

[1228] After the user implements the proposed plan, the user device collects feedback, for example, by displaying a question such as "Was this plan helpful?"

[1229] Send Feedback

[1230] The feedback provided by the user is sent to the server and stored in a database.

[1231] Improved accuracy

[1232] The server then uses the collected feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions. This cycle allows the server to continually provide plans that better suit the user's needs.

[1233] Prompt Sentence Examples

[1234] Design a system that collects a user's health data and generates an optimal holiday plan based on that data. The holiday plan includes entertainment (e.g., watching movies), exercise (e.g., walking), and family activities (e.g., day camping). Analyze the plan based on the user's sleep time, heart rate, number of steps, and calendar events. Also include a function to improve the next proposal based on user feedback.

[1235] This invention allows users to have a fulfilling holiday by receiving optimal holiday plans based on their weekday lifestyle information. Furthermore, users can receive suggestions for optimal driving routes and rest spots while on the move, realizing an efficient and comfortable driving experience.

[1236] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1237] Step 1:

[1238] Data collection

[1239] The user's device uses the health information API and Google Calendar API to collect the user's lifestyle information (sleep time, heart rate, number of steps, calendar schedule). For example, the user's average sleep time and heart rate are obtained from the health app API, and the user's schedule information is obtained from the Google Calendar API. This data is collected and saved in the device in JSON format.

[1240] Input: Data from smartphone health information API and Google Calendar API.

[1241] Output: User's lifestyle information data (JSON format).

[1242] Step 2:

[1243] Data transmission

[1244] The user device securely transmits the collected lifestyle information data to the cloud server at regular intervals (e.g., daily or weekly). This communication uses encryption protocols such as SSL / TLS. For example, data such as the user's sleep time and heart rate is transmitted to the server using HTTPS.

[1245] Input: Collected user lifestyle information data.

[1246] Output: Lifestyle information data stored on a cloud server.

[1247] Step 3:

[1248] Data reception

[1249] The server receives the lifestyle information data sent from the user terminal and stores it in a database, for example, using a database management system (DBMS).

[1250] Input: Lifestyle information data sent from the user's device.

[1251] Output: Life information data stored in a database.

[1252] Step 4:

[1253] Data analysis

[1254] The server analyzes the lifestyle information data stored in the database. For example, it processes the data using Python data analysis libraries (Pandas and NumPy) to calculate average sleep time, heart rate, and exercise volume. Based on this, the server evaluates the user's health status and selects activities suitable for future holiday plans. As a specific example, it suggests walking if the user is not getting enough exercise.

[1255] Input: Lifestyle information data stored in a database.

[1256] Output: Analysis results (e.g. lack of exercise, lack of average sleep time).

[1257] Step 5:

[1258] Plan Generation

[1259] The server then uses a generative AI model based on the results of the data analysis to create an optimal holiday plan. For example, if the user is not getting enough exercise, it might suggest walking in a nearby park. This generation process uses machine learning algorithms and takes into account the user's past feedback.

[1260] Input: Analysis results, user feedback.

[1261] Output: Recommended optimal holiday plans.

[1262] Step 6:

[1263] Plan Notification

[1264] The server then sends the generated holiday plan to the user's device and notifies them at the appropriate time. For example, it uses a dedicated notification API to send push notifications to the user. The notifications include specific activities, recommended locations, and times.

[1265] Input: The generated holiday plan.

[1266] Output: Notification content sent to the user's terminal.

[1267] Step 7:

[1268] Real-time suggestions

[1269] While driving, an application installed in the autonomous vehicle will suggest optimal driving routes, rest spots, and activities in real time based on the user's lifestyle data. For example, it will use the GPS function to obtain the current location and display suitable rest spots.

[1270] Input: User's daily life data, current GPS location information.

[1271] Output: Real-time driving routes, rest stops, and activity suggestions.

[1272] Step 8:

[1273] Feedback collection

[1274] After the user implements the proposed plan, the user terminal collects feedback. For example, a question such as "Was this plan helpful?" is displayed on the application and the user's answer is obtained.

[1275] Input: User feedback.

[1276] Output: User feedback data.

[1277] Step 9:

[1278] Send Feedback

[1279] The collected feedback is sent to the server and stored in a database, and this data is also used to improve the accuracy of the next suggestion.

[1280] Input: Feedback data from user terminal.

[1281] Output: Feedback data stored in a database.

[1282] Step 10:

[1283] Improved accuracy

[1284] The server updates its analysis algorithms based on the collected feedback data to improve the accuracy of its next plan proposals, for example by retraining the machine learning model to learn new feedback patterns.

[1285] Input: Feedback data.

[1286] Output: The updated parsing algorithm.

[1287] 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.

[1288] System Overview

[1289] The present invention is a system that generates optimal holiday plans based on a user's lifestyle information and emotional state and notifies the user of the plans. The system includes a user terminal, a server, an emotion engine, and a network over which these communicate.

[1290] User device functions

[1291] Data collection

[1292] The user device automatically collects weekday lifestyle information and emotional state. Specifically, it connects with a healthcare app to obtain the following data:

[1293] sleep time

[1294] Heart rate

[1295] Step count

[1296] Calendar events

[1297] In addition, an emotion engine analyzes the user's emotional state and collects emotional information through text messages, voice input, etc.

[1298] Data transmission

[1299] The collected lifestyle and emotional information is periodically sent to a server, including daily sleep duration, average heart rate, number of steps taken, schedule details, and an indicator of emotional state.

[1300] Server Features

[1301] Data reception

[1302] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the server checks the consistency and integrity of the data.

[1303] Data analysis

[1304] The server launches a data analysis module and an emotion engine to analyze the received lifestyle and emotion information. The analysis evaluates the following factors:

[1305] Is your average sleep time sufficient?

[1306] Is there any abnormality in your heart rate?

[1307] Is the amount of exercise enough?

[1308] Is there an over-schedule?

[1309] The user's emotional state (e.g., stress level, happiness)

[1310] Plan Generation

[1311] Based on the results of the data analysis, the server generates the optimal holiday plan for the user. Based on the analysis results of the emotion engine, the plan is created taking into account the user's emotional state. For example, if the stress level is high, it will suggest relaxing activities, and if the happiness level is low, it will suggest activities that will help you change your mood.

[1312] notification

[1313] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time, including specific activities and recommended locations and times.

[1314] User Feedback

[1315] Feedback collection

[1316] After the user implements the proposed plan, the user device collects feedback and emotional state, such as questions like "Was this plan helpful?" and "Did you feel better after this activity?"

[1317] Send Feedback

[1318] The feedback and emotional state data provided by the user are sent to a server and stored in a database.

[1319] Improved accuracy

[1320] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, increasing the accuracy of future plan suggestions. This cycle allows the server to continuously provide plans that better suit the user's needs.

[1321] Specific examples

[1322] Example 1: Lack of exercise and stress

[1323] The user's device collects data on weekdays and sends it to the server indicating that the user's exercise volume is low and stress levels are high. The server receives and analyzes this data and suggests walking and meditating in a nearby park on the weekend. The user receives a notification from the device and actually walks and meditates. Later, the user provides feedback and emotional state, which the server uses to improve the accuracy of its next suggestions.

[1324] Example 2: Family time and happiness

[1325] The user's device transmits information from the user's calendar and emotional state to the server, indicating that the user spends little time with family and has a low happiness level. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback and their emotional state. Based on this feedback and emotional information, the server adjusts the next suggestion more appropriately.

[1326] The present invention allows users to have a fulfilling holiday by receiving an optimal holiday plan based on their weekday lifestyle information and emotional state, which helps them maintain a healthy state of mind and body.

[1327] The processing flow will be explained below.

[1328] Processing Steps

[1329] Step 1:

[1330] The user's device automatically collects weekday lifestyle and emotional information. Specifically, it connects with a healthcare app to obtain data on sleep time, heart rate, and number of steps. It also obtains schedule information from a calendar app, and the emotion engine analyzes text messages and voice input to evaluate the user's emotional state.

[1331] Step 2:

[1332] The user device periodically transmits the collected data to the server, including average sleep time, average heart rate, number of steps, schedule details, and indicators of emotional state for each day.

[1333] Step 3:

[1334] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the consistency and completeness of the data are verified.

[1335] Step 4:

[1336] The server launches the data analysis module and emotion engine to analyze the received data. The analysis considers the following factors:

[1337] Is your average sleep time sufficient?

[1338] Is there any abnormality in your heart rate?

[1339] Is the amount of exercise enough?

[1340] Isn't the schedule too busy?

[1341] The user's emotional state (e.g., stress level, happiness)

[1342] Step 5:

[1343] The server generates an optimal holiday plan based on the results of data analysis. Specifically, it creates a plan that takes into account the user's emotional state based on the analysis results of the emotion engine. For example, it suggests relaxing activities (watching movies, meditating, visiting hot springs) for a user with a high stress level, and activities that will change your mood (walking, bouldering, meeting up with friends) for a user with a low happiness level.

[1344] Step 6:

[1345] The server sends the generated holiday plan to the user's device, along with detailed information such as the specific contents of the plan, location, and time.

[1346] Step 7:

[1347] The user terminal notifies the user of the holiday plan received from the server. The notification function is also used to notify the user of the proposal and display the detailed plan contents.

[1348] Step 8:

[1349] The user carries out the proposed plan. After the holiday, the user's device collects feedback and emotional state after the plan is implemented. For example, questions such as "Was this plan helpful?" and "How did your mood change after this activity?" are displayed.

[1350] Step 9:

[1351] The user terminal transmits the collected feedback and emotional state data to the server, which stores the collected feedback and data in a database.

[1352] Step 10:

[1353] The server analyzes the received feedback and emotional information, and adjusts and improves the holiday plan generation algorithm and emotional engine for future trips. By continuously performing this analysis and adjustment, the accuracy of providing plans that better suit the user's needs and emotional state increases.

[1354] Specific examples

[1355] Example 1: Lack of exercise and stress

[1356] The user's device collects data from the weekdays and sends it to the server, indicating that the user's exercise volume is low and stress levels are high. The server receives and analyzes this data, and then suggests a walking and meditation session at a nearby park on the weekend. The user receives this notification from their device and actually walks and meditates. Later, the user provides feedback and emotional state, which the server uses to improve the accuracy of the next suggestion.

[1357] Example 2: Family time and happiness

[1358] The user's device transmits to the server, based on the user's calendar information and emotional information, information indicating that they spend little time with their family and their happiness level is low. The server analyzes this information and suggests a day camp that the family can enjoy. The user accepts the suggestion and actually enjoys the day camp. After the suggestion, the user provides feedback and their emotional state. The server then adjusts the next suggestion based on this feedback.

[1359] This allows users to receive suggestions for optimal holiday plans based on their weekday lifestyle information and emotional state, helping them maintain a healthy state of mind and body.

[1360] Example 2

[1361] 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."

[1362] In modern society, there is a demand for systems that comprehensively evaluate users' lifestyles, health, and emotional states, and then provide optimal holiday plans based on these assessments. However, conventional systems have been unable to effectively provide customized plans suited to individual users due to insufficient collection and analysis of users' lifestyle information. In particular, there has been a lack of systems that provide plans that take into account the user's emotional state, and measures are needed to further improve users' emotional satisfaction.

[1363] 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.

[1364] In this invention, the server comprises means for collecting lifestyle information and emotional information of the user, means for transmitting the collected lifestyle information and emotional information to the server, means for analysing the lifestyle information and emotional information received by the server and assessing the user's condition, means for introducing a generative AI model which generates an optimal holiday plan based on the analysis results, and means for notifying the user terminal of the generated holiday plan. This makes it possible to provide a more customised holiday plan that takes into account the user's individual lifestyle rhythm and emotional state.

[1365] "User's lifestyle information" is data related to the user's daily life, including sleep time, heart rate, number of steps, calendar schedule, and the like.

[1366] "Emotional information" refers to the emotional state (such as stress level or happiness) analyzed from a user's text messages or voice input.

[1367] The "server" is a computer system that receives lifestyle information and emotional information sent from the user's device, analyzes it, and generates holiday plans using a generative AI model.

[1368] "Generative AI model" refers to artificial intelligence algorithms or software that generate optimal holiday plans for users based on the data they receive.

[1369] A "user terminal" is a device used to collect information about a user's daily life and emotions and transmit this data to a server, and examples of such devices include smartphones and tablets.

[1370] "Plan generation" refers to the process by which the server creates an optimal holiday plan for the user based on the analysis results.

[1371] "Notification" refers to the act of informing the user of the holiday plan generated by the server, and is done in the form of a push notification or the like.

[1372] "Feedback" refers to information that records the user's thoughts and emotional state regarding the plan they have implemented and is used to improve the accuracy of future plan proposals.

[1373] MODE FOR CARRYING OUT THE INVENTION

[1374] The present invention is a system that generates optimal holiday plans based on a user's lifestyle information and emotional state and notifies the user of the plans. The system includes a user terminal, a server, an emotion engine, and a network over which these communicate.

[1375] User device functions

[1376] Data collection

[1377] The user device collects weekday lifestyle information and emotional state. The specific hardware used is a smartphone, and the device connects with a healthcare app (e.g., Apple Health or Google Fit) installed on the device to acquire the following data:

[1378] User sleep time

[1379] User's heart rate

[1380] User steps

[1381] User's calendar events

[1382] The emotion engine analyzes the user's text messages and voice inputs to gather emotional states (e.g., stress levels and happiness).

[1383] Data transmission

[1384] The collected lifestyle and emotional information is periodically sent to a server. Specifically, the data sent includes each day's sleep duration, average heart rate, number of steps, schedule details, and indicators of emotional state. Data is sent using FTP or HTTP protocols.

[1385] Server Features

[1386] Data reception

[1387] The server receives the data sent from the user terminal and stores it in a database. The database may be MySQL or PostgreSQL, for example. The consistency and completeness of the data is checked upon receipt.

[1388] Data analysis

[1389] The server launches a data analysis module implemented in a programming language such as Python to analyze the received lifestyle and emotion information. The analysis evaluates the following factors:

[1390] Is your average sleep time sufficient?

[1391] Is there any abnormality in your heart rate?

[1392] Is the amount of exercise enough?

[1393] Is there an over-schedule?

[1394] The user's emotional state (e.g., stress level, happiness)

[1395] Additionally, an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) is used to assess the emotional state.

[1396] Plan Generation

[1397] Based on the analysis results, the server generates the optimal holiday plan for the user using a generative AI model (e.g., GPT-4) and generates the plan by sending prompts.

[1398] Example prompt sentence:

[1399] "Please suggest the best holiday plan for users who are lacking exercise and have high stress levels. Include specific activity and location suggestions."

[1400] notification

[1401] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. The notification is sent using a push notification service (e.g., Firebase Cloud Messaging).

[1402] User Feedback

[1403] Feedback collection

[1404] After the user implements the proposed plan, the user terminal collects feedback and emotional state, for example, displaying questions such as "Was this plan helpful?" and "Did you feel better after this activity?"

[1405] Send Feedback

[1406] The collected feedback and emotional state data is sent to a server and stored in a database.

[1407] Improved accuracy

[1408] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, increasing the accuracy of future plan suggestions. This cycle allows the server to continuously provide plans that better suit the user's needs.

[1409] In this manner, the present invention proposes optimal holiday plans based on the user's lifestyle information and emotional state, and supports the user in having a fulfilling holiday.

[1410] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1411] Step 1:

[1412] Data collection from user devices

[1413] The user's device collects information about their weekday lifestyle and emotional state. Specifically, it connects with healthcare apps (e.g., Apple Health or Google Fit) installed on their smartphone to obtain the user's sleep time, heart rate, number of steps, and calendar appointments. The emotion engine also analyzes the user's text messages and voice input to collect their emotional state (stress level and happiness).

[1414] Input: User's life information and emotional state

[1415] Output: Collected data

[1416] Step 2:

[1417] Data transmission by user terminal

[1418] The user device periodically transmits the collected data to the server. Specifically, the transmitted data includes daily sleep duration, average heart rate, number of steps, calendar appointments, and indicators of emotional state. Data transmission is performed using FTP or HTTP protocols.

[1419] Input: Collected lifestyle and emotional information

[1420] Output: Data sent to the server

[1421] Step 3:

[1422] Data reception by the server

[1423] The server receives the data sent from the user terminal and stores it in a database. Upon receiving the data, it checks its consistency and completeness. The database used can be, for example, MySQL or PostgreSQL.

[1424] Input: Data sent from the user's device

[1425] Output: Data stored in the database

[1426] Step 4:

[1427] Data analysis by server

[1428] The server launches a data analysis module using a programming language such as Python to analyze the received lifestyle and emotion information. The analysis evaluates the following elements:

[1429] Is your average sleep time sufficient?

[1430] Is there any abnormality in your heart rate?

[1431] Is the amount of exercise enough?

[1432] Is there an over-schedule?

[1433] The user's emotional state (e.g., stress level, happiness)

[1434] Additionally, an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) is used to assess the emotional state.

[1435] Input: Received lifestyle and emotional information

[1436] Output: Analysis results

[1437] Step 5:

[1438] Server-generated plan

[1439] The server generates an optimal holiday plan based on the analysis results. The plan is generated using a generative AI model (e.g., GPT-4) and is generated by sending prompts.

[1440] Input: Analysis results

[1441] Output: Generated holiday plan

[1442] Example prompt sentence:

[1443] "Please suggest the best holiday plan for users who are lacking exercise and have high stress levels. Include specific activity and location suggestions."

[1444] Step 6:

[1445] Server Notification

[1446] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. The notification is sent using a push notification service (e.g., Firebase Cloud Messaging).

[1447] Input: Generated holiday plan

[1448] Output: Notification to user terminal

[1449] Step 7:

[1450] Collecting user feedback

[1451] After the user implements the proposed plan, the user device collects feedback and emotional state, such as questions like "Was this plan helpful?" and "Did you feel better after this activity?"

[1452] Input: User's performance and emotional state

[1453] Output: Collected feedback data

[1454] Step 8:

[1455] Send Feedback

[1456] The user's feedback and emotional state data are sent to the server. The sending process uses FTP or HTTP protocols, similar to data transmission.

[1457] Input: Collected feedback data

[1458] Output: Feedback data sent to the server

[1459] Step 9:

[1460] Server-based accuracy improvement

[1461] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, improving the accuracy of future plan suggestions. For example, if a particular activity was highly beneficial to the user, the server will adjust its suggestions to suggest more similar activities.

[1462] Input: Feedback and emotional information data

[1463] Output: Improved algorithms and sentiment engine

[1464] By executing these steps in succession, a system is realized that provides users with optimal holiday plans and supports healthy living both physically and mentally.

[1465] (Application example 2)

[1466] 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."

[1467] Conventional systems that propose optimal holiday plans to users based on lifestyle and emotional information have had issues with the accuracy of their proposals and their feasibility in the real world. Specifically, they lack real-time guidance based on the user's current location, and they also lack sufficient feedback to confirm whether the proposed plans are actually beneficial to the user. Therefore, there is a need for a system that provides real-time guidance using the user's location information and smart devices, as well as improving the accuracy of proposals based on feedback.

[1468] The identification process performed by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting user lifestyle information, means for analyzing the collected lifestyle information and emotional state, means for generating an optimal experience plan based on the analysis results, means for notifying the user of the generated experience plan, means for guiding the user to the proposed plan's location based on the user's location information, means for collecting feedback obtained by the user through the experience at the physical store, means for improving the accuracy of the next proposal based on the collected feedback and emotional information, means including emotion analysis software and a database management system, and means for generating prompt sentences and inputting them into the generative AI model. This enables the user to be provided with an optimal experience in real time and guided to the experience location. Furthermore, collecting feedback can improve the accuracy of future proposals.

[1469] "Lifestyle information" refers to data related to the user's daily life, including health status, amount of exercise, schedule, and the like.

[1470] "Emotional state" is an indicator of the user's current psychological state, and includes stress level, happiness level, and the like.

[1471] "Experience Plan" refers to activities or schedules that a user is encouraged to undertake over a specific period of time.

[1472] "Notification means" refers to a method or device for notifying the user of the generated experience plan.

[1473] "Location information" is information that indicates the user's current geographical location.

[1474] "Guidance means" refers to a method or device that provides directions and detailed information to the location where the user will carry out the proposed experience plan.

[1475] "Feedback" refers to the user's evaluation and impressions of the experience plan they implemented.

[1476] "Emotion analysis software" refers to programs and algorithms used to analyze a user's emotional state.

[1477] A "database management system" is a system for storing, managing, and retrieving collected data.

[1478] A "generative AI model" is an artificial intelligence model used to generate a proposed experience plan.

[1479] A "prompt sentence" is an instruction sentence that is input into a generative AI model to obtain a generated result based on the user's situation and wishes.

[1480] As an embodiment of the present invention, an application installed on smart glasses will be specifically described.

[1481] Generating a Program

[1482] The system is realized using smart glasses, emotion analysis software, a database management system, a cloud server, and a generative AI model.

[1483] Hardware and Software

[1484] 1. Smart Glasses:

[1485] Sensors: Heart rate monitor, pedometer, GPS

[1486] Display: For presenting information

[1487] 2. Sentiment Analysis Software:

[1488] Example: Using various SDKs (e.g. Affectiva SDK)

[1489] 3. Database Management System:

[1490] Example: MySQL

[1491] 4. Cloud Server:

[1492] Example: AWS EC2

[1493] 5. Recommended engines:

[1494] Example: AWS SageMaker

[1495] explanation

[1496] 1. Data Collection:

[1497] The server uses the smart glasses' built-in sensors to collect the user's heart rate, steps, and GPS information in real time.

[1498] Emotion analysis software is used to analyze a user's emotional state from their text messages and voice inputs.

[1499] 2. Data transmission:

[1500] The collected data is sent to a cloud server at a fixed interval, where the data is checked for consistency and completeness.

[1501] 3. Data Analysis:

[1502] The data received by the cloud server is stored in a database management system (MySQL).

[1503] The data analysis module on the server evaluates the user's health and emotional state, calculating stress levels and happiness based on heart rate, steps, GPS information, and emotional state.

[1504] 4. Plan Generation:

[1505] A recommendation engine (AWS SageMaker) is used to generate optimal experience plan candidates based on the analysis results.

[1506] For example, if a user's stress level is high, the system recommends tea time at a relaxing cafe.

[1507] 5. Notices and Guidance:

[1508] The generated experience plan is displayed on the smart glasses' display, and the shortest route to the proposed experience location is also provided based on the user's location information.

[1509] Guidance is updated in real time, so the user is provided with appropriate directions based on their current location.

[1510] 6. User Feedback:

[1511] After completing the proposed experience plan, users enter their feedback through the smart glasses. The feedback form includes questions such as, "Did you find this time relaxing?"

[1512] The feedback and additional emotion data are sent to a cloud server and used to improve the accuracy of the next suggestion.

[1513] Specific examples

[1514] A day in smart glasses

[1515] 1. Data Collection and Analysis:

[1516] During the day, the smart glasses collect the user's heart rate, steps, and GPS information, and analyze stress levels through text messages.

[1517] For example, at 3pm, an increased heart rate and increased stress are observed.

[1518] 2. Plan Generation and Notification:

[1519] The cloud server obtains as an analysis result that the user's stress level is high.

[1520] Suggestion: The smart glasses display recommends a relaxing tea time at a quiet nearby cafe.

[1521] The smart glasses also display directions to the selected cafe.

[1522] 3. Practice and feedback:

[1523] After a user has tea time at a cafe, they input feedback through the smart glasses, such as "Was this time relaxing?"

[1524] The feedback and emotion data are sent to a cloud server and used to improve the accuracy of future plan generation.

[1525] Prompt Sentence Examples

[1526] "User data:

[1527] Heart rate average: 80

[1528] Steps: 3000

[1529] Sleep time: 6 hours

[1530] Emotional state: Stress

[1531] User location: Shibuya-ku, Tokyo

[1532] suggestion:

[1533] "Please suggest a place where users can relax."

[1534] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1535] Step 1:

[1536] The smart glasses use built-in sensors to collect the user's heart rate, steps, and GPS information in real time. The inputs are heart rate, steps, and GPS data, and the output is the collected raw data.

[1537] Step 2:

[1538] The collected data is then used to analyze the user's emotional state using emotion analysis software. The input is text messages or voice input, and the output is analyzed emotional data.

[1539] Step 3:

[1540] The device sends the collected lifestyle information and emotional information to a cloud server. The inputs are heart rate, step count, GPS data, and emotional data, and the output is the integrated data sent to the cloud server.

[1541] Step 4:

[1542] The cloud server stores the received data in a database management system (MySQL) and performs the necessary consistency checks. The input is the transmitted integrated data, and the output is the data stored in the database.

[1543] Step 5:

[1544] The cloud server launches the data analysis module and analyzes the stored data. The input is the user's lifestyle and emotional information obtained from the database, and the output is the analysis results. Specifically, the average heart rate, total number of steps, stress level, etc. are calculated.

[1545] Step 6:

[1546] Using a recommendation engine (AWS SageMaker), an optimal experience plan is generated based on the analysis results. The input is the analysis results, and the output is the generated experience plan.

[1547] Step 7:

[1548] The cloud server notifies the smart glasses of the generated experience plan. The input is the experience plan, and the output is the plan displayed on the smart glasses' display.

[1549] Step 8:

[1550] The smart glasses use location information to guide the user to the proposed plan location. The input is the user's current location and the proposed location, and the output is the route displayed on the smart glasses' display.

[1551] Step 9:

[1552] After the user executes the plan, they input feedback through the smart glasses. The input is the user's feedback and additional emotional data, and the output is the collected feedback.

[1553] Step 10:

[1554] The collected feedback is sent to the cloud server again and stored in a database. The input is the user's feedback data, and the output is the feedback stored in the database.

[1555] Step 11:

[1556] The cloud server analyzes the collected feedback and updates the generative AI model to improve the accuracy of future plan generation. The input is the feedback data, and the output is the updated generative AI model.

[1557] 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.

[1558] 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.

[1559] 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.

[1560] [Fourth embodiment]

[1561] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1562] 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.

[1563] 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).

[1564] 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.

[1565] 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.

[1566] 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).

[1567] 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.

[1568] 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.

[1569] 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.

[1570] 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.

[1571] 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.

[1572] 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.

[1573] 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."

[1574] System Overview

[1575] The present invention is a system for generating optimal holiday plans based on a user's lifestyle information and notifying the user of the plans. The system includes a user terminal, a server, and a network over which these communicate.

[1576] User device functions

[1577] Data collection

[1578] The user device will connect to various healthcare and calendar apps to collect weekday lifestyle information. Through this connection, the following data will be automatically collected:

[1579] sleep time

[1580] Heart rate

[1581] Step count

[1582] Calendar events

[1583] Data transmission

[1584] The collected data is sent to a server at regular intervals. This communication is secure, protecting user privacy.

[1585] Server Features

[1586] Data reception

[1587] The server receives the data sent from the user terminal and stores it in an internal database.

[1588] Data analysis

[1589] The server analyzes the collected data, which may include the following elements:

[1590] Is your average sleep time sufficient?

[1591] Is there any abnormality in your heart rate?

[1592] Is the amount of exercise enough?

[1593] Overscheduling and balance

[1594] Plan Generation

[1595] Based on the results of the data analysis, the server generates the optimal holiday plan for the user, which may include:

[1596] If you're not feeling well: Watch a movie or relax in a hot spring

[1597] If you are not getting enough exercise: Walking in a nearby park or using sports facilities

[1598] If you don't have much time with your family: Day camping or picnics

[1599] notification

[1600] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time, including specific activities and recommended locations and times.

[1601] User Feedback

[1602] Feedback collection

[1603] After the user implements the proposed plan, the user device collects feedback, for example, by displaying a question such as "Was this plan helpful?"

[1604] Send Feedback

[1605] The feedback provided by the user is sent to the server and stored in a database.

[1606] Improved accuracy

[1607] The server then uses the collected feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions. This cycle allows the server to continually provide plans that better suit the user's needs.

[1608] Specific examples

[1609] Example 1: Lack of exercise

[1610] The user's device collects data on weekdays and sends it to the server indicating that the user is not exercising much. The server receives and analyzes this data and suggests walking in a nearby park on the weekend. The user receives a notification from the device and actually goes for a walk. The user then provides feedback at a later date, which the server uses to improve the accuracy of its next suggestions.

[1611] Example 2: Family time

[1612] The user's device sends information from the user's calendar indicating that they have little time to spend with their family to the server. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback. Based on this feedback, the server adjusts the next suggestion more appropriately.

[1613] The present invention allows users to have a fulfilling holiday by being offered an optimal holiday plan based on their weekday lifestyle information, which helps them maintain a healthy state of mind and body.

[1614] The processing flow will be explained below.

[1615] Step 1:

[1616] The user's device automatically collects information about their weekday lifestyle. Specifically, it connects with a healthcare app to obtain data on sleep time, heart rate, and number of steps taken. It also obtains schedule information from a calendar app.

[1617] Step 2:

[1618] The user device periodically sends the collected data to the server, including the amount of sleep each day, average heart rate, number of steps taken, and schedule details.

[1619] Step 3:

[1620] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the consistency and completeness of the data are verified.

[1621] Step 4:

[1622] The server launches a data analysis module to analyze the received data, which evaluates whether the person is getting enough sleep, has an abnormal heart rate, is exercising enough, or has an overscheduled schedule.

[1623] Step 5:

[1624] The server generates an optimal holiday plan based on the results of the data analysis. Specifically, it suggests relaxing activities for users who are sleep-deprived, recommended exercise activities for users who are not getting enough exercise, and stress-relieving activities for users who have a busy schedule.

[1625] Step 6:

[1626] The server sends the generated holiday plan to the user's device, along with detailed information such as the specific contents of the plan, location, and time.

[1627] Step 7:

[1628] The user's device displays the holiday plan received from the server, and also notifies the user of the proposal using the notification function.

[1629] Step 8:

[1630] The user carries out the proposed plan, and after spending the holiday, the user's device collects feedback.

[1631] Step 9:

[1632] The user terminal sends the collected feedback to the server, including the usefulness and satisfaction of the suggestions.

[1633] Step 10:

[1634] The server analyzes the received feedback and adjusts and improves the holiday plan generation algorithm for future trips. This feedback cycle allows the server to provide a plan that is more suitable for the user.

[1635] Example 1

[1636] 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."

[1637] In modern life, there is a demand for a means to automatically suggest holiday plans that are suited to each individual's health condition and lifestyle. However, existing systems have difficulty effectively collecting and analyzing users' lifestyle information and providing optimal holiday plans for each individual. Furthermore, the accuracy of suggestions is limited due to a lack of functionality to continuously improve the system based on user feedback.

[1638] 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.

[1639] In this invention, the server includes means for periodically transmitting the user's lifestyle information to the server, means for the server to store the transmitted lifestyle information in a database, means for analysing the lifestyle information using a data analysis algorithm and assessing the user's condition, means for generating an optimum holiday plan based on the analysis results, means for transmitting and notifying the user of the generated holiday plan to a user terminal, and means for collecting user feedback and improving the analysis algorithm. This makes it possible to provide specific and accurate holiday plans suited to the user's individual health condition and lifestyle rhythm.

[1640] "User's lifestyle information" is data related to the user's daily life, and includes health information, exercise information, and schedule information.

[1641] The term "fixed cycle" refers to a preset time interval, such as a daily or weekly cycle.

[1642] "Server" refers to a computer system for receiving, storing, and analyzing data sent from a user terminal.

[1643] "Database" refers to an information management system used by a server to store users' life information.

[1644] "Data analysis algorithm" refers to a series of calculation methods used by the server to analyze the user's lifestyle information and evaluate the user's condition.

[1645] A "holiday plan" refers to a plan that suggests activities that are optimal for the user's health condition and lifestyle based on the analysis results.

[1646] A "user terminal" refers to a device used by a user, such as a smartphone or PC, that is capable of communicating with a server.

[1647] "Feedback" refers to the rating and opinion information provided by a user regarding a proposed holiday plan.

[1648] "Improving the analysis algorithm" refers to the process of adjusting the data analysis algorithm based on feedback information collected from users to improve the accuracy of the next proposal.

[1649] The present invention is a system for generating optimal holiday plans based on a user's lifestyle information and notifying the user of the plans. The system includes a user terminal, a server, and a network over which these communicate.

[1650] User device functions

[1651] The user device will automatically collect information about the user's daily life by linking with various healthcare and calendar apps. Specifically, the following data will be collected:

[1652] sleep time

[1653] Heart rate

[1654] Step count

[1655] Calendar events

[1656] The collected data is sent to a server at regular intervals, and this communication is securely carried out using encryption protocols such as SSL / TLS.

[1657] Server Features

[1658] The server receives the data sent from the user terminal and stores it in a database. Then, the server uses a data analysis algorithm to perform data analysis, including the following elements:

[1659] Assessment of average sleep time

[1660] Heart rate abnormality detection

[1661] Assessment of exercise volume

[1662] Schedule balance assessment

[1663] Based on the results of the data analysis, the server generates the optimal holiday plan for the user. The generated plan may include watching a movie or refreshing in a hot spring if you are not feeling well, walking in a nearby park if you are lacking exercise, or going on a day camp if you have little time to spend with family. The generated plan is sent to the user's device and notified to the user at the appropriate time.

[1664] User Notification and Feedback

[1665] The user device notifies the user of the plan sent from the server. The notification includes specific activity details and recommended locations and times. After the user carries out the proposed plan, the user device collects feedback. The feedback includes the usefulness of the plan. The feedback information is sent to the server and stored in a database. The server uses this feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions.

[1666] Specific examples

[1667] Example 1: Lack of exercise

[1668] The user's device collects data on weekdays and sends it to the server. Based on the analysis result that the user's physical activity is low, the server suggests walking in a nearby park on the weekend. The user receives a notification from the device and follows the suggestion. Later, the user provides feedback, which the server uses to improve the accuracy of the next suggestion.

[1669] Example 2: Family time

[1670] The user's device sends calendar information indicating that they have little time to spend with their family to the server. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback. Based on this feedback, the server adjusts the next suggestion more appropriately.

[1671] Example prompts for generative AI models

[1672] "Please create a program for a system that generates and notifies optimal holiday plans based on a user's weekday lifestyle information (e.g., sleep time, heart rate, number of steps, calendar events). This system includes user devices, a server, and the network over which they communicate."

[1673] This system will suggest optimal holiday plans based on the user's health condition and lifestyle, allowing them to spend their holidays more fulfillingly. Furthermore, by continuously improving the system based on feedback, the system will continue to provide highly accurate suggestions over time.

[1674] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1675] Step 1: Data collection

[1676] The user device connects with a healthcare app and a calendar app to collect weekday lifestyle information. Specifically, it obtains data on sleep time, heart rate, and number of steps from the healthcare app, and obtains the user's schedule information from the calendar app. These data are compiled into a data package. The input of this step is data from each app, and the output is the compiled data package.

[1677] Step 2: Send data

[1678] The user terminal transmits the collected data packages to the server at regular intervals (e.g., once a day). This communication is securely performed using encryption protocols such as SSL / TLS. The input is the data package, and the output is the transmission of encrypted data.

[1679] Step 3: Receiving data

[1680] The server receives data packages sent from user terminals. The received data is stored in a database. The input is the encrypted data package, and the output is the data stored in the database.

[1681] Step 4: Data analysis

[1682] The server analyzes the received data using a data analysis algorithm. Specifically, it calculates average sleep time using Python's pandas library and detects abnormal heart rate values ​​using scikit-learn's anomaly detection algorithm. It also evaluates the amount of exercise and schedule balance. The input is lifestyle information stored in the database, and the output is the analysis results.

[1683] Step 5: Generate a plan

[1684] The server generates an optimal holiday plan based on the results of the data analysis. For example, if you are not getting enough exercise, it will suggest walking in a nearby park, or if you don't spend much time with your family, it will suggest day camping. The input is the results of the data analysis, and the output is a specific holiday plan.

[1685] Step 6: Plan Notification

[1686] The server sends the generated holiday plan to the user's device. The user's device notifies the user of the plan at the appropriate time. The notification content includes specific activities and recommended locations and times. The input is the specific holiday plan, and the output is a notification to the user.

[1687] Step 7: Gather feedback

[1688] After the user executes the proposed plan, the user terminal collects feedback. The feedback is in the form of questions about the usefulness of the plan and whether the activity was enjoyable. The input is the user's answer, and the output is the collected feedback data.

[1689] Step 8: Send your feedback

[1690] The user terminal sends the collected feedback data to the server, which stores the data in a database. The input is the feedback data, and the output is the feedback stored in the database.

[1691] Step 9: Improve the analysis algorithm

[1692] The server improves the analysis algorithm based on the collected feedback. For example, if a particular plan is popular, it may be given higher priority. The input is the feedback data, and the output is an improved analysis algorithm.

[1693] These specific processing steps make it possible to continuously provide optimal holiday plans to users.

[1694] (Application example 1)

[1695] 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."

[1696] Conventional self-driving vehicles lack the functionality to utilize the user's health information and schedule to provide optimal driving routes, rest spots, and activities while traveling. As a result, users are unable to receive appropriate suggestions for entertainment and health promotion while traveling, making it difficult to enjoy an efficient and comfortable driving experience. The present invention aims to solve this problem and provide users with optimal suggestions even while traveling.

[1697] 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.

[1698] In this invention, the server includes: means for collecting user lifestyle information; means for analyzing the collected lifestyle information; means for generating an optimal holiday plan based on the analysis results; means for notifying the user of the generated holiday plan; means including an application installed in the self-driving vehicle; means for suggesting optimal driving routes, rest spots, and activities based on the user's lifestyle data; means for notifying the user of the suggestions in real time while driving; and means for collecting feedback provided by the user and improving the accuracy of the suggestions for the next trip. This enables the user to receive optimal suggestions based on their health condition and schedule even while on the move, enabling them to enjoy a comfortable and efficient driving experience.

[1699] "User's lifestyle information" is data related to the user's daily life, including, for example, sleep time, heart rate, number of steps, calendar schedule, and the like.

[1700] The term "means" refers to a method or device for achieving a specific purpose, and in this invention refers to a method or device for realizing functions such as data collection, analysis, notification, and feedback collection.

[1701] "Applications installed in autonomous vehicles" refers to software installed inside vehicles with autonomous driving capabilities that analyzes user data and provides notifications.

[1702] "User's lifestyle data" is a general term for various information generated in the course of a user's daily life, and includes health information, schedule information, and the like.

[1703] The "optimal driving route" refers to the most efficient and convenient driving route for the user, calculated and suggested based on the user's health condition and schedule.

[1704] "Rest Spots" refers to suitable places for users to take a rest while driving, and are suggested based on their health status and schedule.

[1705] "Activity" refers to fitness and entertainment related activities that a user can engage in while driving.

[1706] The "means for notifying the user of the proposed content in real time" refers to a method or device for instantly notifying the user's terminal of the analysis results and the recommended plan while driving.

[1707] "User-provided feedback" refers to the user's reactions to the suggestions, such as evaluations and impressions, and is information that the system uses to improve its next suggestions.

[1708] The present invention provides a system that generates optimal holiday plans based on a user's lifestyle information and notifies the user of the plans. The system includes a user terminal, an application installed in an autonomous vehicle, a cloud server, and a network over which these communicate.

[1709] User device functions

[1710] Data collection

[1711] The user's device connects to various healthcare and calendar apps to collect weekday lifestyle information. This connection automatically collects the following data, for example, using the health information API or Google Calendar API.

[1712] sleep time

[1713] Heart rate

[1714] Step count

[1715] Calendar events

[1716] Data transmission

[1717] The collected data is sent to the server at regular intervals. This communication is secure, using encrypted communication such as SSL / TLS, to protect user privacy.

[1718] Cloud Server Functions

[1719] Data reception

[1720] The server receives the data sent from the user terminal and stores it in an internal database.

[1721] Data analysis

[1722] The server analyzes the collected data, which may include the following elements:

[1723] Is your average sleep time sufficient?

[1724] Is there any abnormality in your heart rate?

[1725] Is the amount of exercise enough?

[1726] Calendar overload or balance

[1727] These analyses are performed using data analysis tools using Python and R. For example, if the average sleep time is less than six hours, the system will suggest watching a movie.

[1728] Plan Generation

[1729] Based on the results of the data analysis, the server generates the optimal holiday plan for the user, which may include:

[1730] If you're not feeling well: Watch a movie or relax in a hot spring

[1731] If you are not getting enough exercise: Walking in a nearby park or using sports facilities

[1732] If you don't have much time with your family: Day camping or picnics

[1733] This plan generation may be powered by a generative AI model, which applies machine learning algorithms to provide a customized plan for each user.

[1734] notification

[1735] The generated plan is sent to the user's device and notifications are sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. Notifications are sent using a dedicated notification API.

[1736] Autonomous vehicle features

[1737] Real-time suggestions

[1738] The application installed in the autonomous vehicle will suggest optimal driving routes, rest spots, and activities based on the user's lifestyle data, including a function to optimize driving routes in conjunction with the GPS module.

[1739] User Feedback

[1740] Feedback collection

[1741] After the user implements the proposed plan, the user device collects feedback, for example, by displaying a question such as "Was this plan helpful?"

[1742] Send Feedback

[1743] The feedback provided by the user is sent to the server and stored in a database.

[1744] Improved accuracy

[1745] The server then uses the collected feedback to improve its analysis algorithm and increase the accuracy of future plan suggestions. This cycle allows the server to continually provide plans that better suit the user's needs.

[1746] Prompt Sentence Examples

[1747] Design a system that collects a user's health data and generates an optimal holiday plan based on that data. The holiday plan includes entertainment (e.g., watching movies), exercise (e.g., walking), and family activities (e.g., day camping). Analyze the plan based on the user's sleep time, heart rate, number of steps, and calendar events. Also include a function to improve the next proposal based on user feedback.

[1748] This invention allows users to have a fulfilling holiday by receiving optimal holiday plans based on their weekday lifestyle information. Furthermore, users can receive suggestions for optimal driving routes and rest spots while on the move, realizing an efficient and comfortable driving experience.

[1749] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1750] Step 1:

[1751] Data collection

[1752] The user's device uses the health information API and Google Calendar API to collect the user's lifestyle information (sleep time, heart rate, number of steps, calendar schedule). For example, the user's average sleep time and heart rate are obtained from the health app API, and the user's schedule information is obtained from the Google Calendar API. This data is collected and saved in the device in JSON format.

[1753] Input: Data from smartphone health information API and Google Calendar API.

[1754] Output: User's lifestyle information data (JSON format).

[1755] Step 2:

[1756] Data transmission

[1757] The user device securely transmits the collected lifestyle information data to the cloud server at regular intervals (e.g., daily or weekly). This communication uses encryption protocols such as SSL / TLS. For example, data such as the user's sleep time and heart rate is transmitted to the server using HTTPS.

[1758] Input: Collected user lifestyle information data.

[1759] Output: Lifestyle information data stored on a cloud server.

[1760] Step 3:

[1761] Data reception

[1762] The server receives the lifestyle information data sent from the user terminal and stores it in a database, for example, using a database management system (DBMS).

[1763] Input: Lifestyle information data sent from the user's device.

[1764] Output: Life information data stored in a database.

[1765] Step 4:

[1766] Data analysis

[1767] The server analyzes the lifestyle information data stored in the database. For example, it processes the data using Python data analysis libraries (Pandas and NumPy) to calculate average sleep time, heart rate, and exercise volume. Based on this, the server evaluates the user's health status and selects activities suitable for future holiday plans. As a specific example, it suggests walking if the user is not getting enough exercise.

[1768] Input: Lifestyle information data stored in a database.

[1769] Output: Analysis results (e.g. lack of exercise, lack of average sleep time).

[1770] Step 5:

[1771] Plan Generation

[1772] The server then uses a generative AI model based on the results of the data analysis to create an optimal holiday plan. For example, if the user is not getting enough exercise, it might suggest walking in a nearby park. This generation process uses machine learning algorithms and takes into account the user's past feedback.

[1773] Input: Analysis results, user feedback.

[1774] Output: Recommended optimal holiday plans.

[1775] Step 6:

[1776] Plan Notification

[1777] The server then sends the generated holiday plan to the user's device and notifies them at the appropriate time. For example, it uses a dedicated notification API to send push notifications to the user. The notifications include specific activities, recommended locations, and times.

[1778] Input: The generated holiday plan.

[1779] Output: Notification content sent to the user's terminal.

[1780] Step 7:

[1781] Real-time suggestions

[1782] While driving, an application installed in the autonomous vehicle will suggest optimal driving routes, rest spots, and activities in real time based on the user's lifestyle data. For example, it will use the GPS function to obtain the current location and display suitable rest spots.

[1783] Input: User's daily life data, current GPS location information.

[1784] Output: Real-time driving routes, rest stops, and activity suggestions.

[1785] Step 8:

[1786] Feedback collection

[1787] After the user implements the proposed plan, the user terminal collects feedback. For example, a question such as "Was this plan helpful?" is displayed on the application and the user's answer is obtained.

[1788] Input: User feedback.

[1789] Output: User feedback data.

[1790] Step 9:

[1791] Send Feedback

[1792] The collected feedback is sent to the server and stored in a database, and this data is also used to improve the accuracy of the next suggestion.

[1793] Input: Feedback data from user terminal.

[1794] Output: Feedback data stored in a database.

[1795] Step 10:

[1796] Improved accuracy

[1797] The server updates its analysis algorithms based on the collected feedback data to improve the accuracy of its next plan proposals, for example by retraining the machine learning model to learn new feedback patterns.

[1798] Input: Feedback data.

[1799] Output: The updated parsing algorithm.

[1800] 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.

[1801] System Overview

[1802] The present invention is a system that generates optimal holiday plans based on a user's lifestyle information and emotional state and notifies the user of the plans. The system includes a user terminal, a server, an emotion engine, and a network over which these communicate.

[1803] User device functions

[1804] Data collection

[1805] The user device automatically collects weekday lifestyle information and emotional state. Specifically, it connects with a healthcare app to obtain the following data:

[1806] sleep time

[1807] Heart rate

[1808] Step count

[1809] Calendar events

[1810] In addition, an emotion engine analyzes the user's emotional state and collects emotional information through text messages, voice input, etc.

[1811] Data transmission

[1812] The collected lifestyle and emotional information is periodically sent to a server, including daily sleep duration, average heart rate, number of steps taken, schedule details, and an indicator of emotional state.

[1813] Server Features

[1814] Data reception

[1815] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the server checks the consistency and integrity of the data.

[1816] Data analysis

[1817] The server launches a data analysis module and an emotion engine to analyze the received lifestyle and emotion information. The analysis evaluates the following factors:

[1818] Is your average sleep time sufficient?

[1819] Is there any abnormality in your heart rate?

[1820] Is the amount of exercise enough?

[1821] Is there an over-schedule?

[1822] The user's emotional state (e.g., stress level, happiness)

[1823] Plan Generation

[1824] Based on the results of the data analysis, the server generates the optimal holiday plan for the user. Based on the analysis results of the emotion engine, the plan is created taking into account the user's emotional state. For example, if the stress level is high, it will suggest relaxing activities, and if the happiness level is low, it will suggest activities that will help you change your mood.

[1825] notification

[1826] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time, including specific activities and recommended locations and times.

[1827] User Feedback

[1828] Feedback collection

[1829] After the user implements the proposed plan, the user device collects feedback and emotional state, such as questions like "Was this plan helpful?" and "Did you feel better after this activity?"

[1830] Send Feedback

[1831] The feedback and emotional state data provided by the user are sent to a server and stored in a database.

[1832] Improved accuracy

[1833] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, increasing the accuracy of future plan suggestions. This cycle allows the server to continuously provide plans that better suit the user's needs.

[1834] Specific examples

[1835] Example 1: Lack of exercise and stress

[1836] The user's device collects data on weekdays and sends it to the server indicating that the user's exercise volume is low and stress levels are high. The server receives and analyzes this data and suggests walking and meditating in a nearby park on the weekend. The user receives a notification from the device and actually walks and meditates. Later, the user provides feedback and emotional state, which the server uses to improve the accuracy of its next suggestions.

[1837] Example 2: Family time and happiness

[1838] The user's device transmits information from the user's calendar and emotional state to the server, indicating that the user spends little time with family and has a low happiness level. The server analyzes this information and suggests a fun day camp for the family. The user accepts the suggestion and provides feedback and their emotional state. Based on this feedback and emotional information, the server adjusts the next suggestion more appropriately.

[1839] The present invention allows users to have a fulfilling holiday by receiving an optimal holiday plan based on their weekday lifestyle information and emotional state, which helps them maintain a healthy state of mind and body.

[1840] The processing flow will be explained below.

[1841] Processing Steps

[1842] Step 1:

[1843] The user's device automatically collects weekday lifestyle and emotional information. Specifically, it connects with a healthcare app to obtain data on sleep time, heart rate, and number of steps. It also obtains schedule information from a calendar app, and the emotion engine analyzes text messages and voice input to evaluate the user's emotional state.

[1844] Step 2:

[1845] The user device periodically transmits the collected data to the server, including average sleep time, average heart rate, number of steps, schedule details, and indicators of emotional state for each day.

[1846] Step 3:

[1847] The server receives the data sent from the user terminal and stores it in a database. During the receiving process, the consistency and completeness of the data are verified.

[1848] Step 4:

[1849] The server launches the data analysis module and emotion engine to analyze the received data. The analysis considers the following factors:

[1850] Is your average sleep time sufficient?

[1851] Is there any abnormality in your heart rate?

[1852] Is the amount of exercise enough?

[1853] Isn't the schedule too busy?

[1854] The user's emotional state (e.g., stress level, happiness)

[1855] Step 5:

[1856] The server generates an optimal holiday plan based on the results of data analysis. Specifically, it creates a plan that takes into account the user's emotional state based on the analysis results of the emotion engine. For example, it suggests relaxing activities (watching movies, meditating, visiting hot springs) for a user with a high stress level, and activities that will change your mood (walking, bouldering, meeting up with friends) for a user with a low happiness level.

[1857] Step 6:

[1858] The server sends the generated holiday plan to the user's device, along with detailed information such as the specific contents of the plan, location, and time.

[1859] Step 7:

[1860] The user terminal notifies the user of the holiday plan received from the server. The notification function is also used to notify the user of the proposal and display the detailed plan contents.

[1861] Step 8:

[1862] The user carries out the proposed plan. After the holiday, the user's device collects feedback and emotional state after the plan is implemented. For example, questions such as "Was this plan helpful?" and "How did your mood change after this activity?" are displayed.

[1863] Step 9:

[1864] The user terminal transmits the collected feedback and emotional state data to the server, which stores the collected feedback and data in a database.

[1865] Step 10:

[1866] The server analyzes the received feedback and emotional information, and adjusts and improves the holiday plan generation algorithm and emotional engine for future trips. By continuously performing this analysis and adjustment, the accuracy of providing plans that better suit the user's needs and emotional state increases.

[1867] Specific examples

[1868] Example 1: Lack of exercise and stress

[1869] The user's device collects data from the weekdays and sends it to the server, indicating that the user's exercise volume is low and stress levels are high. The server receives and analyzes this data, and then suggests a walking and meditation session at a nearby park on the weekend. The user receives this notification from their device and actually walks and meditates. Later, the user provides feedback and emotional state, which the server uses to improve the accuracy of the next suggestion.

[1870] Example 2: Family time and happiness

[1871] The user's device transmits to the server, based on the user's calendar information and emotional information, information indicating that they spend little time with their family and their happiness level is low. The server analyzes this information and suggests a day camp that the family can enjoy. The user accepts the suggestion and actually enjoys the day camp. After the suggestion, the user provides feedback and their emotional state. The server then adjusts the next suggestion based on this feedback.

[1872] This allows users to receive suggestions for optimal holiday plans based on their weekday lifestyle information and emotional state, helping them maintain a healthy state of mind and body.

[1873] Example 2

[1874] 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."

[1875] In modern society, there is a demand for systems that comprehensively evaluate users' lifestyles, health, and emotional states, and then provide optimal holiday plans based on these assessments. However, conventional systems have been unable to effectively provide customized plans suited to individual users due to insufficient collection and analysis of users' lifestyle information. In particular, there has been a lack of systems that provide plans that take into account the user's emotional state, and measures are needed to further improve users' emotional satisfaction.

[1876] 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.

[1877] In this invention, the server comprises means for collecting lifestyle information and emotional information of the user, means for transmitting the collected lifestyle information and emotional information to the server, means for analysing the lifestyle information and emotional information received by the server and assessing the user's condition, means for introducing a generative AI model which generates an optimal holiday plan based on the analysis results, and means for notifying the user terminal of the generated holiday plan. This makes it possible to provide a more customised holiday plan that takes into account the user's individual lifestyle rhythm and emotional state.

[1878] "User's lifestyle information" is data related to the user's daily life, including sleep time, heart rate, number of steps, calendar schedule, and the like.

[1879] "Emotional information" refers to the emotional state (such as stress level or happiness) analyzed from a user's text messages or voice input.

[1880] The "server" is a computer system that receives lifestyle information and emotional information sent from the user's device, analyzes it, and generates holiday plans using a generative AI model.

[1881] "Generative AI model" refers to artificial intelligence algorithms or software that generate optimal holiday plans for users based on the data they receive.

[1882] A "user terminal" is a device used to collect information about a user's daily life and emotions and transmit this data to a server, and examples of such devices include smartphones and tablets.

[1883] "Plan generation" refers to the process by which the server creates an optimal holiday plan for the user based on the analysis results.

[1884] "Notification" refers to the act of informing the user of the holiday plan generated by the server, and is done in the form of a push notification or the like.

[1885] "Feedback" refers to information that records the user's thoughts and emotional state regarding the plan they have implemented and is used to improve the accuracy of future plan proposals.

[1886] MODE FOR CARRYING OUT THE INVENTION

[1887] The present invention is a system that generates optimal holiday plans based on a user's lifestyle information and emotional state and notifies the user of the plans. The system includes a user terminal, a server, an emotion engine, and a network over which these communicate.

[1888] User device functions

[1889] Data collection

[1890] The user device collects weekday lifestyle information and emotional state. The specific hardware used is a smartphone, and the device connects with a healthcare app (e.g., Apple Health or Google Fit) installed on the device to acquire the following data:

[1891] User sleep time

[1892] User's heart rate

[1893] User steps

[1894] User's calendar events

[1895] The emotion engine analyzes the user's text messages and voice inputs to gather emotional states (e.g., stress levels and happiness).

[1896] Data transmission

[1897] The collected lifestyle and emotional information is periodically sent to a server. Specifically, the data sent includes each day's sleep duration, average heart rate, number of steps, schedule details, and indicators of emotional state. Data is sent using FTP or HTTP protocols.

[1898] Server Features

[1899] Data reception

[1900] The server receives the data sent from the user terminal and stores it in a database. The database may be MySQL or PostgreSQL, for example. The consistency and completeness of the data is checked upon receipt.

[1901] Data analysis

[1902] The server launches a data analysis module implemented in a programming language such as Python to analyze the received lifestyle and emotion information. The analysis evaluates the following factors:

[1903] Is your average sleep time sufficient?

[1904] Is there any abnormality in your heart rate?

[1905] Is the amount of exercise enough?

[1906] Is there an over-schedule?

[1907] The user's emotional state (e.g., stress level, happiness)

[1908] Additionally, an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) is used to assess the emotional state.

[1909] Plan Generation

[1910] Based on the analysis results, the server generates the optimal holiday plan for the user using a generative AI model (e.g., GPT-4) and generates the plan by sending prompts.

[1911] Example prompt sentence:

[1912] "Please suggest the best holiday plan for users who are lacking exercise and have high stress levels. Include specific activity and location suggestions."

[1913] notification

[1914] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. The notification is sent using a push notification service (e.g., Firebase Cloud Messaging).

[1915] User Feedback

[1916] Feedback collection

[1917] After the user implements the proposed plan, the user terminal collects feedback and emotional state, for example, displaying questions such as "Was this plan helpful?" and "Did you feel better after this activity?"

[1918] Send Feedback

[1919] The collected feedback and emotional state data is sent to a server and stored in a database.

[1920] Improved accuracy

[1921] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, increasing the accuracy of future plan suggestions. This cycle allows the server to continuously provide plans that better suit the user's needs.

[1922] In this manner, the present invention proposes optimal holiday plans based on the user's lifestyle information and emotional state, and supports the user in having a fulfilling holiday.

[1923] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1924] Step 1:

[1925] Data collection from user devices

[1926] The user's device collects information about their weekday lifestyle and emotional state. Specifically, it connects with healthcare apps (e.g., Apple Health or Google Fit) installed on their smartphone to obtain the user's sleep time, heart rate, number of steps, and calendar appointments. The emotion engine also analyzes the user's text messages and voice input to collect their emotional state (stress level and happiness).

[1927] Input: User's life information and emotional state

[1928] Output: Collected data

[1929] Step 2:

[1930] Data transmission by user terminal

[1931] The user device periodically transmits the collected data to the server. Specifically, the transmitted data includes daily sleep duration, average heart rate, number of steps, calendar appointments, and indicators of emotional state. Data transmission is performed using FTP or HTTP protocols.

[1932] Input: Collected lifestyle and emotional information

[1933] Output: Data sent to the server

[1934] Step 3:

[1935] Data reception by the server

[1936] The server receives the data sent from the user terminal and stores it in a database. Upon receiving the data, it checks its consistency and completeness. The database used can be, for example, MySQL or PostgreSQL.

[1937] Input: Data sent from the user's device

[1938] Output: Data stored in the database

[1939] Step 4:

[1940] Data analysis by server

[1941] The server launches a data analysis module using a programming language such as Python to analyze the received lifestyle and emotion information. The analysis evaluates the following elements:

[1942] Is your average sleep time sufficient?

[1943] Is there any abnormality in your heart rate?

[1944] Is the amount of exercise enough?

[1945] Is there an over-schedule?

[1946] The user's emotional state (e.g., stress level, happiness)

[1947] Additionally, an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) is used to assess the emotional state.

[1948] Input: Received lifestyle and emotional information

[1949] Output: Analysis results

[1950] Step 5:

[1951] Server-generated plan

[1952] The server generates an optimal holiday plan based on the analysis results. The plan is generated using a generative AI model (e.g., GPT-4) and is generated by sending prompts.

[1953] Input: Analysis results

[1954] Output: Generated holiday plan

[1955] Example prompt sentence:

[1956] "Please suggest the best holiday plan for users who are lacking exercise and have high stress levels. Include specific activity and location suggestions."

[1957] Step 6:

[1958] Server Notification

[1959] The generated plan is sent to the user's device and a notification is sent to the user at the appropriate time. The notification content includes specific activities, recommended locations, and times. The notification is sent using a push notification service (e.g., Firebase Cloud Messaging).

[1960] Input: Generated holiday plan

[1961] Output: Notification to user terminal

[1962] Step 7:

[1963] Collecting user feedback

[1964] After the user implements the proposed plan, the user device collects feedback and emotional state, such as questions like "Was this plan helpful?" and "Did you feel better after this activity?"

[1965] Input: User's performance and emotional state

[1966] Output: Collected feedback data

[1967] Step 8:

[1968] Send Feedback

[1969] The user's feedback and emotional state data are sent to the server. The sending process uses FTP or HTTP protocols, similar to data transmission.

[1970] Input: Collected feedback data

[1971] Output: Feedback data sent to the server

[1972] Step 9:

[1973] Server-based accuracy improvement

[1974] The server improves its analysis algorithm and emotion engine based on the collected feedback and emotion information, improving the accuracy of future plan suggestions. For example, if a particular activity was highly beneficial to the user, the server will adjust its suggestions to suggest more similar activities.

[1975] Input: Feedback and emotional information data

[1976] Output: Improved algorithms and sentiment engine

[1977] By executing these steps in succession, a system is realized that provides users with optimal holiday plans and supports healthy living both physically and mentally.

[1978] (Application example 2)

[1979] 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."

[1980] Conventional systems that propose optimal holiday plans to users based on lifestyle and emotional information have had issues with the accuracy of their proposals and their feasibility in the real world. Specifically, they lack real-time guidance based on the user's current location, and they also lack sufficient feedback to confirm whether the proposed plans are actually beneficial to the user. Therefore, there is a need for a system that provides real-time guidance using the user's location information and smart devices, as well as improving the accuracy of proposals based on feedback.

[1981] The identification process performed by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting user lifestyle information, means for analyzing the collected lifestyle information and emotional state, means for generating an optimal experience plan based on the analysis results, means for notifying the user of the generated experience plan, means for guiding the user to the proposed plan's location based on the user's location information, means for collecting feedback obtained by the user through the experience at the physical store, means for improving the accuracy of the next proposal based on the collected feedback and emotional information, means including emotion analysis software and a database management system, and means for generating prompt sentences and inputting them into the generative AI model. This enables the user to be provided with an optimal experience in real time and guided to the experience location. Furthermore, collecting feedback can improve the accuracy of future proposals.

[1982] "Lifestyle information" refers to data related to the user's daily life, including health status, amount of exercise, schedule, and the like.

[1983] "Emotional state" is an indicator of the user's current psychological state, and includes stress level, happiness level, and the like.

[1984] "Experience Plan" refers to activities or schedules that a user is encouraged to undertake over a specific period of time.

[1985] "Notification means" refers to a method or device for notifying the user of the generated experience plan.

[1986] "Location information" is information that indicates the user's current geographical location.

[1987] "Guidance means" refers to a method or device that provides directions and detailed information to the location where the user will carry out the proposed experience plan.

[1988] "Feedback" refers to the user's evaluation and impressions of the experience plan they implemented.

[1989] "Emotion analysis software" refers to programs and algorithms used to analyze a user's emotional state.

[1990] A "database management system" is a system for storing, managing, and retrieving collected data.

[1991] A "generative AI model" is an artificial intelligence model used to generate a proposed experience plan.

[1992] A "prompt sentence" is an instruction sentence that is input into a generative AI model to obtain a generated result based on the user's situation and wishes.

[1993] As an embodiment of the present invention, an application installed on smart glasses will be specifically described.

[1994] Generating a Program

[1995] The system is realized using smart glasses, emotion analysis software, a database management system, a cloud server, and a generative AI model.

[1996] Hardware and Software

[1997] 1. Smart Glasses:

[1998] Sensors: Heart rate monitor, pedometer, GPS

[1999] Display: For presenting information

[2000] 2. Sentiment Analysis Software:

[2001] Example: Using various SDKs (e.g. Affectiva SDK)

[2002] 3. Database Management System:

[2003] Example: MySQL

[2004] 4. Cloud Server:

[2005] Example: AWS EC2

[2006] 5. Recommended engines:

[2007] Example: AWS SageMaker

[2008] explanation

[2009] 1. Data Collection:

[2010] The server uses the smart glasses' built-in sensors to collect the user's heart rate, steps, and GPS information in real time.

[2011] Emotion analysis software is used to analyze a user's emotional state from their text messages and voice inputs.

[2012] 2. Data transmission:

[2013] The collected data is sent to a cloud server at a fixed interval, where the data is checked for consistency and completeness.

[2014] 3. Data Analysis:

[2015] The data received by the cloud server is stored in a database management system (MySQL).

[2016] The data analysis module on the server evaluates the user's health and emotional state, calculating stress levels and happiness based on heart rate, steps, GPS information, and emotional state.

[2017] 4. Plan Generation:

[2018] A recommendation engine (AWS SageMaker) is used to generate optimal experience plan candidates based on the analysis results.

[2019] For example, if a user's stress level is high, the system recommends tea time at a relaxing cafe.

[2020] 5. Notices and Guidance:

[2021] The generated experience plan is displayed on the smart glasses' display, and the shortest route to the proposed experience location is also provided based on the user's location information.

[2022] Guidance is updated in real time, so the user is provided with appropriate directions based on their current location.

[2023] 6. User Feedback:

[2024] After completing the proposed experience plan, users enter their feedback through the smart glasses. The feedback form includes questions such as, "Did you find this time relaxing?"

[2025] The feedback and additional emotion data are sent to a cloud server and used to improve the accuracy of the next suggestion.

[2026] Specific examples

[2027] A day in smart glasses

[2028] 1. Data Collection and Analysis:

[2029] During the day, the smart glasses collect the user's heart rate, steps, and GPS information, and analyze stress levels through text messages.

[2030] For example, at 3pm, an increased heart rate and increased stress are observed.

[2031] 2. Plan Generation and Notification:

[2032] The cloud server obtains as an analysis result that the user's stress level is high.

[2033] Suggestion: The smart glasses display recommends a relaxing tea time at a quiet nearby cafe.

[2034] The smart glasses also display directions to the selected cafe.

[2035] 3. Practice and feedback:

[2036] After a user has tea time at a cafe, they input feedback through the smart glasses, such as "Was this time relaxing?"

[2037] The feedback and emotion data are sent to a cloud server and used to improve the accuracy of future plan generation.

[2038] Prompt Sentence Examples

[2039] "User data:

[2040] Heart rate average: 80

[2041] Steps: 3000

[2042] Sleep time: 6 hours

[2043] Emotional state: Stress

[2044] User location: Shibuya-ku, Tokyo

[2045] suggestion:

[2046] "Please suggest a place where users can relax."

[2047] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2048] Step 1:

[2049] The smart glasses use built-in sensors to collect the user's heart rate, steps, and GPS information in real time. The inputs are heart rate, steps, and GPS data, and the output is the collected raw data.

[2050] Step 2:

[2051] The collected data is then used to analyze the user's emotional state using emotion analysis software. The input is text messages or voice input, and the output is analyzed emotional data.

[2052] Step 3:

[2053] The device sends the collected lifestyle information and emotional information to a cloud server. The inputs are heart rate, step count, GPS data, and emotional data, and the output is the integrated data sent to the cloud server.

[2054] Step 4:

[2055] The cloud server stores the received data in a database management system (MySQL) and performs the necessary consistency checks. The input is the transmitted integrated data, and the output is the data stored in the database.

[2056] Step 5:

[2057] The cloud server launches the data analysis module and analyzes the stored data. The input is the user's lifestyle and emotional information obtained from the database, and the output is the analysis results. Specifically, the average heart rate, total number of steps, stress level, etc. are calculated.

[2058] Step 6:

[2059] Using a recommendation engine (AWS SageMaker), an optimal experience plan is generated based on the analysis results. The input is the analysis results, and the output is the generated experience plan.

[2060] Step 7:

[2061] The cloud server notifies the smart glasses of the generated experience plan. The input is the experience plan, and the output is the plan displayed on the smart glasses' display.

[2062] Step 8:

[2063] The smart glasses use location information to guide the user to the proposed plan location. The input is the user's current location and the proposed location, and the output is the route displayed on the smart glasses' display.

[2064] Step 9:

[2065] After the user executes the plan, they input feedback through the smart glasses. The input is the user's feedback and additional emotional data, and the output is the collected feedback.

[2066] Step 10:

[2067] The collected feedback is sent to the cloud server again and stored in a database. The input is the user's feedback data, and the output is the feedback stored in the database.

[2068] Step 11:

[2069] The cloud server analyzes the collected feedback and updates the generative AI model to improve the accuracy of future plan generation. The input is the feedback data, and the output is the updated generative AI model.

[2070] 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.

[2071] 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.

[2072] 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.

[2073] 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.

[2074] FIG. 9 illustrates 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 behaviors 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.

[2075] 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.

[2076] 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).

[2077] 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.

[2078] 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."

[2079] 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.

[2080] 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).

[2081] 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.

[2082] 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.

[2083] 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.

[2084] 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.

[2085] 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.

[2086] 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 example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2087] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2088] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2089] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2090] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2091] The following is further disclosed regarding the above embodiment.

[2092] (Claim 1)

[2093] A means for collecting user lifestyle information;

[2094] A means of analyzing the collected lifestyle information;

[2095] A means for generating an optimal holiday plan based on the analysis results;

[2096] The system includes means for notifying the user of the generated holiday plan.

[2097] (Claim 2)

[2098] 10. The system of claim 1, further comprising means for collecting health, exercise, and schedule information of the user.

[2099] (Claim 3)

[2100] 10. The system of claim 1, further comprising means for collecting and utilizing user feedback to improve the holiday plans generated.

[2101] "Example 1"

[2102] (Claim 1)

[2103] A means for collecting user lifestyle information;

[2104] means for periodically transmitting the collected life information to a server;

[2105] A means for the server to store the transmitted life information in a database;

[2106] A means for analyzing life information using a data analysis algorithm and evaluating a user's condition;

[2107] A means for generating an optimal holiday plan based on the analysis results;

[2108] means for transmitting the generated holiday plan to a user terminal and notifying the user;

[2109] a means of collecting user feedback and improving the analysis algorithm;

[2110] A system including...

[2111] (Claim 2)

[2112] 10. The system of claim 1, further comprising means for collecting health, exercise, and schedule information of the user.

[2113] (Claim 3)

[2114] 10. The system of claim 1, further comprising means for utilizing the collected feedback to refine the generated holiday plans.

[2115] "Application Example 1"

[2116] (Claim 1)

[2117] A means for collecting user lifestyle information;

[2118] A means of analyzing the collected lifestyle information;

[2119] A means for generating an optimal holiday plan based on the analysis results;

[2120] means for notifying a user of the generated holiday plan;

[2121] a means including an application installed on the autonomous vehicle;

[2122] A means for suggesting optimal driving routes, rest spots, and activities based on the user's lifestyle data;

[2123] a means for notifying the user of the suggestions in real time while driving;

[2124] A means to collect user-provided feedback to improve the accuracy of next suggestions;

[2125] A system including:

[2126] (Claim 2)

[2127] 10. The system of claim 1, further comprising means for collecting health, exercise, and schedule information of the user.

[2128] (Claim 3)

[2129] 10. The system of claim 1, further comprising means for collecting and utilizing user feedback to improve the holiday plans generated.

[2130] "Example 2: Combining Emotion Engines"

[2131] (Claim 1)

[2132] A means for collecting user's life information and emotion information;

[2133] means for transmitting the collected life information and emotion information to a server;

[2134] A means for analyzing the lifestyle information and emotion information received by the server and evaluating the state of the user;

[2135] A means to introduce a generative AI model that generates optimal holiday plans based on the analysis results; and

[2136] The system includes a means for notifying a user terminal of the generated holiday plan.

[2137] (Claim 2)

[2138] 10. The system of claim 1, further comprising means for collecting health information, athletic information, and emotional state information of the user.

[2139] (Claim 3)

[2140] 10. The system of claim 1, further comprising means for collecting and utilizing user feedback and emotional state data to refine the generated holiday plans.

[2141] "Application example 2 when combining emotion engines"

[2142] (Claim 1)

[2143] A means for collecting user lifestyle information;

[2144] a means for analyzing the collected life information and emotional state;

[2145] A means for generating an optimal experience plan based on the analysis results;

[2146] a means for notifying a user of the generated experience plan;

[2147] A means for providing guidance to the location of the proposed plan based on the user's location information;

[2148] A means to collect feedback from users through their in-store experiences;

[2149] A means to improve the accuracy of the next suggestion based on the collected feedback and sentiment information;

[2150] means including sentiment analysis software and a database management system;

[2151] A system including means for generating prompt sentences and inputting them to a generative AI model.

[2152] (Claim 2)

[2153] 10. The system of claim 1, further comprising means for collecting health information, exercise information, schedule information, and emotion information of the user.

[2154] (Claim 3)

[2155] 10. The system of claim 1, further comprising means for providing notifications and guidance to a user using the smart glasses. [Explanation of symbols]

[2156] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for collecting user lifestyle information; A means of analyzing the collected lifestyle information; A means for generating an optimal holiday plan based on the analysis results; The system includes means for notifying the user of the generated holiday plan.

2. The system of claim 1 further comprising means for collecting user health, exercise, and schedule information.

3. 10. The system of claim 1, further comprising means for collecting and utilizing user feedback to improve the holiday plans generated.

Images