System

Abstract

A system is provided.SOLUTION: A system includes means for acquiring schedule information of a user, means for acquiring position information of the user, means for evaluating a loss risk on the basis of the acquired schedule information and position information, means for selecting an optimum insurance plan on the basis of an evaluation result, and means for automatically applying the selected insurance plan to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] This section describes the "problem that the invention aims to solve" and "means for solving the problem" in the patent specification for the "insurance system."

[0005] Users may face a higher risk of losing important items in their daily lives or at work. This risk is particularly pronounced in situations that deviate from their usual behavioral patterns, such as unexpected business trips or travel. However, users tend to forget to always take out appropriate insurance, and manually setting the insurance coverage is a hassle. In such situations, it is necessary to provide a convenient and flexible insurance service that allows users to prepare for the risk of loss with peace of mind. [Means for solving the problem]

[0006] In order to solve the above problems, the present invention provides the following means.

[0007] Provided is a system including means for acquiring a user's schedule information, means for acquiring the user's location information, means for evaluating the risk of loss based on the acquired schedule information and location information, means for selecting an optimal insurance plan based on the evaluation results, and means for automatically applying the selected insurance plan to the user. The system also includes means for consulting and setting the user's insurance settings in advance and means for adjusting the contents of the insurance plan based on the user's setting information, as well as means for sending notifications to the user in real time when the risk of loss increases and means for providing the user with appropriate suggestions and support. This system allows users to use optimal insurance without any hassle and prepare for the risk of loss.

[0008] Understood. Below are definitions of important terms included in the claims.

[0009] "User" means an individual or legal entity that uses the system and receives insurance services against the risk of loss.

[0010] "Schedule information" refers to information about appointments and events recorded in a calendar application or schedule that a user uses on a daily basis.

[0011] "Location information" refers to GPS data that indicates a user's current location and movement history.

[0012] "Risk of loss" refers to the user's assessment of the likelihood of losing an important item.

[0013] A "generative model" is a computational model used to analyze acquired data and evaluate user behavior patterns and loss risk.

[0014] "Insurance Plan" means a specific insurance contract or service provided in response to a risk of loss, the content and scope of which are predetermined.

[0015] "Notification" means a warning or suggestion message sent by the system to the user, which may be sent in the form of a push notification, email, or other similar message.

[0016] "Setting information" refers to information about the insurance coverage conditions and scope that the user has set in advance within the system. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] MODE FOR CARRYING OUT THE INVENTION

[0039] A specific embodiment of the present invention will be described. The present invention includes a system that provides insurance services to allow users to appropriately manage the risk of loss. The system evaluates the risk of loss based on the user's schedule information and location information, and automatically selects and applies the optimal insurance plan.

[0040] System Overview

[0041] The system consists of user devices, a central processing server, and a cloud-based database for storing and processing user data.

[0042] 1. The user grants the app permission to access their calendar and GPS information, allowing the app to obtain the user's schedule and location information.

[0043] 2. The device (user's smartphone or tablet) periodically collects calendar and location information and sends this data to a central processing server.

[0044] 3. Based on the received schedule information and location information, the server analyzes the user's behavioral patterns using a generative model and evaluates the risk of loss.

[0045] 4. The server selects the most suitable insurance plan based on the evaluation results and automatically applies it to the user.

[0046] 5. Provide an interface that allows users to consult and set insurance settings in advance, and adjust the insurance content based on the user's responses.

[0047] Program processing

[0048] The operation of the system is explained in natural language below.

[0049] Obtaining user schedule and location information

[0050] 1. The user initiates the system by granting the app permission to access the calendar and location services.

[0051] 2. The device acquires the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history) and periodically sends them to the server.

[0052] Loss risk assessment

[0053] 3. The server uses a generative model to analyze the user's behavioral patterns based on the received schedule information and location information.

[0054] 4. The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[0055] Insurance plan selection and application

[0056] 5. The server selects the most suitable insurance plan based on the assessed risk score.

[0057] 6. The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[0058] Insurance adjustment

[0059] 7. The user reviews their insurance details within the app and adjusts their coverage and settings as needed. Adjusted settings are sent to the server in real time.

[0060] Real-time assistance and suggestions

[0061] 8. The server uses the generative model to notify the user when the risk of loss increases or when certain conditions are met, and provides appropriate suggestions and support.

[0062] Specific examples

[0063] Example 1: If you have many regular business trips

[0064] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[0065] 2. The device sends calendar information and GPS data to the server.

[0066] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling."

[0067] 4. The server automatically adds "Travel Insurance" and notifies the user.

[0068] 5. The user reviews their insurance and adjusts coverage as needed.

[0069] Example 2: When there are many sudden actions

[0070] 1. The user suddenly goes on a weekend trip.

[0071] 2. The device sends real-time GPS data to the server.

[0072] 3. The server uses the generative model to determine that there is a high risk of loss during travel.

[0073] 4. The server temporarily applies "travel insurance" and notifies the user.

[0074] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0075] In this way, users can easily access the most suitable insurance and prepare for the risk of loss.

[0076] The processing flow will be explained below.

[0077] Understood. Below is a step-by-step explanation of the specific flow of the programming process for the "Anytime Insurance" system.

[0078] Program processing

[0079] Obtaining user schedule and location information

[0080] Step 1:

[0081] The user grants the app permission to access the calendar app and location services.

[0082] Specific behavior: On the initial setup screen for the app, select the options to allow access to your calendar and use your GPS location.

[0083] Step 2:

[0084] The device periodically collects calendar information and GPS data and sends it to the app.

[0085] Specific behavior: The app periodically retrieves the user's calendar information (e.g., scheduled dates and times, locations) and GPS data (e.g., current location, movement history) in the background.

[0086] Specific operation: The acquired data is stored in local storage and sent to the cloud server at regular intervals.

[0087] Loss risk assessment

[0088] Step 3:

[0089] The server receives the calendar information and GPS data sent from the device and stores them in a database.

[0090] Specific actions: Accurately store received data in a database and format the data for analysis.

[0091] Step 4:

[0092] The server uses a generative model to analyze the user's behavioral patterns based on the stored schedule information and location information, and assesses the risk of loss.

[0093] How it works: The generative model runs on the server and uses calendar information and GPS data as input to identify user behavior patterns and calculate a loss risk score.

[0094] Insurance plan selection and application

[0095] Step 5:

[0096] The server selects the most suitable insurance plan based on the assessed risk score.

[0097] Specific Action: Select the appropriate plan from a pre-configured list of insurance plans based on risk score.

[0098] Step 6:

[0099] The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[0100] What it does: Automatically applies the insurance to the user's account and notifies the user via push notification or email.

[0101] Insurance adjustment

[0102] Step 7:

[0103] Users can review their insurance details within the app and adjust coverage and settings as needed.

[0104] Specific actions: Access the app's insurance settings screen, review the displayed insurance details, and make any necessary adjustments (e.g., change the insurance amount, set the coverage).

[0105] Step 8:

[0106] The device sends the user's settings to the server and updates them.

[0107] Specific operation: The adjusted setting information is sent to the server in real time, and the user's insurance information is updated on the server side.

[0108] Real-time assistance and suggestions

[0109] Step 9:

[0110] The server uses the generative model to send notifications to the user when there is an increased risk of loss or when certain conditions are met.

[0111] What it does: It monitors GPS data and behavioral patterns in real time, and triggers a push notification if the generative model detects an increased risk.

[0112] Step 10:

[0113] Users receive real-time notifications and can view and respond within the app.

[0114] What to do: Tap the notification in the app for more details and to take additional insurance adjustments or actions as needed.

[0115] In this way, users can easily use appropriate loss insurance and prepare for the risk of loss.

[0116] Example 1

[0117] 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."

[0118] The current insurance system requires users to select and change their insurance plans, which makes it difficult to achieve optimal risk management. Furthermore, many users find it difficult to properly assess their risk of loss, resulting in insufficient insurance coverage. Furthermore, in situations where the risk of loss fluctuates in real time, appropriate insurance proposals and support are often not provided.

[0119] 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.

[0120] In this invention, the server includes a means for analyzing a user's behavioral pattern, a means for calculating a risk score, and a means for selecting and applying an appropriate insurance plan, thereby making it possible to evaluate the risk of loss in real time based on the user's behavioral data and automatically apply the most appropriate insurance plan.

[0121] "Means for obtaining user schedule information" refers to a function for obtaining data regarding scheduled dates, times, and locations from the calendar app or schedule management app used by the user.

[0122] "Means of obtaining user location information" refers to a function that uses the user's location information service or GPS function to obtain the user's current location and movement history.

[0123] The "means for transmitting acquired schedule information and location information to a server" is a function that transmits schedule information and location information periodically collected by a user's terminal to a central processing server via data communication.

[0124] "Means for analyzing user behavior patterns using generative AI models" refers to a function that uses machine learning algorithms and artificial intelligence based on collected data to analyze and reveal user behavior patterns.

[0125] "Means for assessing the risk of loss based on behavioral patterns and calculating a risk score" refers to a function that assesses the risk of loss using statistical analysis and risk models based on user behavioral data and calculates that risk as a numerical score.

[0126] "Means for selecting the most suitable insurance plan based on risk score" is a function for selecting the most suitable insurance plan from a database based on the calculated risk score and applying it to the user.

[0127] "Means for automatically applying the selected insurance plan to the user" is a function for automatically applying the selected insurance plan to the user's account and notifying the user of the application results.

[0128] "Means for users to consult and set up their insurance settings in advance" refers to interfaces and functions that allow users to consult about insurance details in advance and set up insurance according to their individual needs.

[0129] "Means for adjusting the contents of the insurance plan based on the user's setting information" is a function for automatically adjusting the contents of the insurance plan based on the information set in advance by the user and applying it to the user.

[0130] "Means for sending a notification to the user in real time when the risk of loss increases" is a function for sending a notification to the user in real time when the risk of loss exceeds a certain threshold.

[0131] "Means for providing appropriate suggestions and support to users" refers to a function for providing appropriate suggestions and support to users to reduce the risk of loss.

[0132] MODE FOR CARRYING OUT THE INVENTION

[0133] A specific embodiment of the present invention will be described in detail. This invention is a system that provides insurance services to enable users to appropriately manage the risk of loss. The system aims to evaluate the risk of loss based on the user's schedule information and location information, and automatically select and apply the optimal insurance plan.

[0134] System configuration

[0135] The system consists of the following major components:

[0136] 1. User's Device

[0137] Devices users carry around with them, such as smartphones and tablets

[0138] Includes a calendar app and location services

[0139] The app collects the user's calendar information and GPS data and sends it to a server

[0140] 2. Central Processing Server

[0141] A server with high-performance computing power

[0142] Analyze user behavior patterns using generative AI models to assess risk of loss

[0143] Select the best insurance plan and automatically apply it to the user

[0144] 3. Cloud-based databases

[0145] A database for storing and processing user schedule information, location information, and insurance setting information

[0146] High security and scalability

[0147] Program processing

[0148] The operation of the system is explained in natural language below.

[0149] Obtaining user schedule and location information

[0150] 1. The user grants the app permission to access the Calendar app and Location Services.

[0151] 2. The device obtains the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history).

[0152] 3. The device periodically sends the acquired data to the server.

[0153] Loss risk assessment

[0154] 4. The server analyzes the user's behavioral patterns using a generative AI model based on the received schedule and location information.

[0155] 5. The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[0156] Insurance plan selection and application

[0157] 6. The server selects the most suitable insurance plan based on the assessed risk score.

[0158] 7. The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[0159] Insurance adjustment

[0160] 8. The user reviews their insurance within the app and adjusts their coverage and settings as needed.

[0161] 9. The server receives the adjusted settings and updates the insurance plan.

[0162] Real-time assistance and suggestions

[0163] 10. The server uses generative AI models to notify users when there is an increased risk of loss or when certain conditions are met, and provide appropriate suggestions and support.

[0164] Specific examples

[0165] Example 1: If you have many regular business trips

[0166] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[0167] 2. The device sends calendar information and GPS data to the server.

[0168] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling."

[0169] 4. The server automatically adds "Travel Insurance" and notifies the user.

[0170] 5. The user reviews their insurance and adjusts coverage as needed.

[0171] Example 2: When there are many sudden actions

[0172] 1. The user suddenly goes on a weekend trip.

[0173] 2. The device sends real-time GPS data to the server.

[0174] 3. The server uses the generative model to determine that there is a high risk of loss during travel.

[0175] 4. The server temporarily applies "travel insurance" and notifies the user.

[0176] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0177] In this way, users can easily access the most suitable insurance and prepare for the risk of loss.

[0178] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0179] Step 1:

[0180] The user grants the app permission to access the Calendar app and Location Services.

[0181] Specific operation: The user sets the app's permissions from the smartphone settings screen and allows access to calendar information and location information.

[0182] Input: User sets permissions.

[0183] Output: The permission information that has been set.

[0184] Step 2:

[0185] The device obtains the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history).

[0186] Specific operation: Uses the smartphone's antenna and Wi-Fi to obtain real-time location information and loads schedule information through the calendar API.

[0187] Input: Calendar and location with permissions set.

[0188] Output: Retrieved calendar information and GPS data.

[0189] Step 3:

[0190] The data acquired by the terminal is periodically sent to the server.

[0191] Specific operation: At regular intervals (for example, every minute), a background process on the device is started, which encrypts the acquired data packets and sends them to the server using the HTTPS protocol.

[0192] Input: Captured calendar information and GPS data.

[0193] Output: Data packet sent to the server.

[0194] Step 4:

[0195] The server uses a generative AI model to analyze the user's behavioral patterns based on the received schedule information and location information.

[0196] Specific operation: The server calls a generative AI model such as a cloud AI service and performs analysis using the user's data stream as input.

[0197] Input: Schedule and location information sent to the server.

[0198] Output: Analyzed behavioral patterns.

[0199] Step 5:

[0200] The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[0201] What it does: It uses pattern recognition technology to evaluate certain behavioral trends and outliers, then uses statistical models to calculate a risk score.

[0202] Input: Analyzed behavioral patterns.

[0203] Output: The calculated risk score.

[0204] Step 6:

[0205] The server selects the most suitable insurance plan based on the assessed risk score.

[0206] Specific operation: Search and select the insurance plan that best suits the risk profile from the database in the server. For example, use SQL to retrieve the insurance plan that corresponds to the risk score.

[0207] Input: Risk score.

[0208] Output: The selected insurance plan.

[0209] Step 7:

[0210] The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[0211] What it does: Sends a notification to the user's app via a REST API, displaying details of the insurance plan applied.

[0212] Input: Selected insurance plan.

[0213] Output: Notification to user terminal.

[0214] Step 8:

[0215] Users can review their insurance details within the app and adjust coverage and settings as needed.

[0216] What it does: The app UI displays insurance information and allows users to change settings using a form, with changes sent to the server in real time.

[0217] Input: Insurance plan details.

[0218] Output: Adjusted insurance settings.

[0219] Step 9:

[0220] The server receives the adjusted settings and updates the insurance plan.

[0221] Specific operation: Analyzes the received data and updates the insurance configuration database on the server. For example, it updates the configuration data using a NoSQL database (such as MongoDB).

[0222] Input: Adjusted insurance settings.

[0223] Output: Updated insurance plan.

[0224] Step 10:

[0225] The server uses a generative AI model to notify users when there is an increased risk of loss or when certain conditions are met, and provide appropriate suggestions and support.

[0226] Specific operation: Monitors real-time data and issues push notifications when conditions are met. Notifications are sent to users' devices using cloud messaging services, etc.

[0227] Input: Real-time loss risk assessment.

[0228] Output: Push notification and suggestion.

[0229] (Application example 1)

[0230] 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."

[0231] When managing the risk of loss for customers and employees in physical stores, conventional methods have made it difficult to perform detailed risk assessments and apply optimal insurance plans. Furthermore, automatic application of insurance based on real-time risk fluctuations and user behavior has not been sufficiently implemented. This has led to the issue of not being able to provide appropriate support in situations where the risk of loss is high.

[0232] 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.

[0233] In this invention, the server includes: means for acquiring a user's schedule information; means for acquiring the user's location information; means for assessing the risk of loss based on the acquired schedule information and location information; means for selecting an optimal insurance plan based on the assessment results; means for automatically applying the selected insurance plan to the user; means for periodically updating the user's location information and reassessing the risk of loss; means for applying and updating the insurance plan based on the reassessment results; means for consulting and setting the user's insurance settings in advance; means for adjusting the contents of the insurance plan based on the user's setting information; means for notifying the user of the insurance application results; means for sending a notification to the user in real time when the risk of loss increases; means for providing appropriate suggestions and support to the user; and means for providing an interface for manual adjustment based on the reassessment results. This enables the risk of loss for customers and employees in physical stores to be managed through detailed assessments and the application of optimal insurance plans. It can also respond to risk fluctuations in real time and automatically apply insurance and support based on user behavior.

[0234] "Means for obtaining user schedule information" refers to a function for obtaining information entered by the user into a calendar app or schedule management application.

[0235] "Means of obtaining user location information" refers to a function for obtaining location information from a user's device, such as a smartphone or tablet, through GPS or location information services.

[0236] "Means for assessing the risk of loss based on acquired schedule information and location information" is a function for calculating the possibility of loss and assessing the risk based on the user's calendar information and location information.

[0237] The "means for selecting the most suitable insurance plan based on the evaluation results" is a function for selecting the most suitable insurance plan for the user based on the evaluation of the risk of loss.

[0238] The "means for automatically applying the selected insurance plan to the user" is a function that enables the system to automatically apply the selected insurance plan to the user.

[0239] "Means for periodically updating the user's location information and reassessing the risk of loss" is a function for periodically obtaining the user's current location and reassessing the risk based on that information.

[0240] "Means to apply and update insurance plans based on reassessment results" refers to the functionality for reviewing and updating existing insurance plans based on new risk assessment results.

[0241] "Means for consulting and setting up the user's insurance settings in advance" is a function that allows the user to consult with the user in advance about the details and settings of the insurance and set up the insurance settings that the user desires.

[0242] "Means for adjusting the contents of the insurance plan based on the user's setting information" refers to a function for changing and adjusting the contents of the insurance plan based on the information set in advance by the user.

[0243] "Means for notifying users of insurance coverage results" is a function for informing users that the selected insurance plan has been applied.

[0244] "Means for sending notifications to users in real time when the risk of loss increases" is a function for immediately sending warnings and notifications to users when the risk of loss increases.

[0245] "Means of making appropriate suggestions and support to users" refers to a function that provides specific advice and support to avoid risks when it is determined that there is a high risk of loss.

[0246] "Means for providing an interface that allows manual adjustments based on the results of reassessment" refers to a function for providing an interface that allows a user to manually adjust insurance coverage based on the updated results of risk assessment.

[0247] An embodiment of the present invention will now be described in detail. This system evaluates the risk of loss based on the user's schedule information and location information, and selects and applies an appropriate insurance plan. A detailed description of the system is provided below.

[0248] System configuration

[0249] The system mainly consists of a user terminal, a central processing server, and a cloud-based database. Users are expected to use smartphones and tablets.

[0250] Hardware and software used

[0251] Hardware: Smartphones, tablets

[0252] Software: Python 3.9, geopy library, requests library

[0253] Data processing and calculation

[0254] Obtaining user schedule and location information

[0255] The system is activated when a user grants the app permission to access the calendar app and location services. The user's device obtains calendar information (scheduled dates and times, locations) and GPS data (current location, movement history), and periodically sends this data to a central processing server.

[0256] Example prompt: "Do you consent to collecting your calendar and location information?"

[0257] Loss risk assessment

[0258] The server uses the generated AI model to analyze the user's behavioral patterns based on the acquired schedule and location information. During this process, the server calculates the distance between the user's current location and the scheduled location, and calculates a risk score based on the result. For example, if the current location is very close to the scheduled location, the risk score will be high.

[0259] Selecting an insurance plan

[0260] The server selects the most suitable insurance plan based on the assessed risk score, which is then automatically applied to the user's account.

[0261] Insurance coverage based on risk scores

[0262] The server periodically updates the user's location and reassess the risk of loss based on that information. Based on the risk assessment, the insurance plan in place is adjusted and, if necessary, a new insurance plan is installed.

[0263] Specific examples

[0264] Example 1: If you have many regular business trips

[0265] 1. A user enters "Business Trip" into their calendar and enters "City A" as the destination.

[0266] 2. The user's device sends calendar information and GPS data to the server.

[0267] 3. Based on this information, the server generates an AI model that assesses that "the risk of loss increases when traveling."

[0268] 4. The server automatically adds "Travel Insurance" and notifies the user.

[0269] 5. The user reviews their insurance and adjusts coverage as needed.

[0270] Example 2: When there are many sudden actions

[0271] 1. The user suddenly goes on a weekend trip.

[0272] 2. The user's device sends real-time GPS data to the server.

[0273] 3. The server uses the generated AI model to determine that there is a high risk of loss during travel.

[0274] 4. The server temporarily applies "travel insurance" and notifies the user.

[0275] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0276] In this way, users can easily use the most suitable insurance and prepare for the risk of loss. Real-time risk assessment and automatic insurance application will more effectively protect users' safety.

[0277] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0278] Step 1:

[0279] The system starts when the user grants the app permission to access the calendar app and location services.

[0280] Input: User permission information

[0281] What happens: The user confirms the permissions based on the prompt and presses the accept button.

[0282] Output: The app gets access to the user's schedule and location.

[0283] Step 2:

[0284] The device acquires the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history), and periodically transmits this data to a central processing server.

[0285] Input: Calendar information, GPS data

[0286] How it works: Your device periodically retrieves data from the Calendar app and Location Services and sends it to the server.

[0287] Output: Calendar information and GPS data are sent to the server.

[0288] Step 3:

[0289] The server uses a generative AI model to analyze the user's behavioral patterns based on the received schedule and location information.

[0290] Input: Calendar information, GPS data

[0291] How it works: The server inputs schedule and location information into a generative AI model that analyzes behavioral patterns.

[0292] Output: User behavior pattern data

[0293] Step 4:

[0294] The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[0295] Input: User behavior pattern data

[0296] How it works: The server calculates a risk score based on the analysis results, taking into account factors such as the distance between locations and the length of time spent there.

[0297] Output: Risk score

[0298] Step 5:

[0299] The server selects the most appropriate insurance plan based on the evaluation results and automatically applies it to the user.

[0300] Input: Risk Score

[0301] How it works: The server selects the most appropriate plan from pre-set insurance plans (low, medium, high) based on the risk score and automatically applies it.

[0302] Output: Insurance plan information applied

[0303] Step 6:

[0304] The server periodically updates the user's location and reassess the risk of loss.

[0305] Input: Latest GPS data

[0306] How it works: The server periodically retrieves the latest location information and performs risk assessment again.

[0307] Output: Updated risk score

[0308] Step 7:

[0309] The server applies and updates the insurance plan based on the reassessment results.

[0310] Input: Updated Risk Score

[0311] How it works: The server updates the insurance plan as needed based on the new risk score.

[0312] Output: Updated insurance plan information

[0313] Step 8:

[0314] Users can check their insurance coverage results within the app and adjust their insurance coverage as needed.

[0315] Input: Insurance plan information

[0316] How it works: A user opens the app, sees their insurance plan, and makes adjustments through the interface.

[0317] Output: Adjusted insurance plan settings

[0318] 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.

[0319] MODE FOR CARRYING OUT THE INVENTION

[0320] A specific embodiment of the present invention will be described. The present invention includes a system that allows users to appropriately manage their risk of loss and provides insurance plans according to that risk, and by combining it with an emotion engine, it further improves accuracy and provides insurance services according to the user's emotional state.

[0321] System Overview

[0322] The system consists of a user device, a central processing server, and a cloud-based database for storing and processing user data. It also incorporates an emotion engine to identify the user's emotional state and use that information to assess loss risk and select insurance plans.

[0323] 1. The user grants the app permission to access the calendar app, GPS information, and emotion recognition, allowing the app to obtain the user's schedule information, location information, and emotional state.

[0324] 2. The device periodically collects calendar information, GPS data, and emotional state data and transmits this data to a central processing server.

[0325] 3. Based on the received data, the server uses a generative model to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[0326] 4. The server selects the optimal insurance plan based on the evaluation results and automatically applies the customized plan to the user, taking into account their emotional state.

[0327] 5. Provide an interface that allows users to consult and set insurance settings in advance, and adjust the insurance content based on the user's settings information.

[0328] Program processing

[0329] The operation of the system is explained in natural language below.

[0330] Obtaining user schedule information, location information, and emotional state

[0331] 1. The user initiates the system by granting the app permission to access the calendar app, location services, and emotion recognition features.

[0332] 2. The device periodically collects calendar information (scheduled date and time, location), GPS data (current location, movement history), and emotional state data using the camera and microphone, and sends this data to the server.

[0333] Assessment of loss risk and emotional state

[0334] 3. The server receives the calendar information, GPS data, and emotional state data sent from the device and stores them in a database.

[0335] 4. The server uses a generative model to analyze the user's behavioral patterns and emotional state based on the stored schedule information, location information, and emotional state data, and evaluates the risk of loss.

[0336] Insurance plan selection and application

[0337] 5. The server selects the best insurance plan based on the assessed risk score and emotional state.

[0338] 6. The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[0339] Insurance adjustment

[0340] 7. The user checks the insurance details within the app and adjusts the coverage and settings to take into account their emotional state as needed. The adjusted settings are sent to the server in real time.

[0341] Real-time assistance and suggestions

[0342] 8. When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions or support.

[0343] Specific examples

[0344] Example 1: If you have many regular business trips

[0345] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[0346] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[0347] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling." If the user's emotional state indicates stress, the server sets a higher risk score.

[0348] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[0349] 5. The user reviews their insurance and adjusts coverage as needed.

[0350] Example 2: When there are many sudden actions

[0351] 1. The user suddenly goes on a weekend trip.

[0352] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[0353] 3. The server uses the generative model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[0354] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[0355] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0356] In this way, users can easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[0357] The processing flow will be explained below.

[0358] Understood. Below is a step-by-step explanation of the specific flow of the programming process for the "Anytime Insurance" system.

[0359] Program processing

[0360] Obtaining user schedule information, location information, and emotional state

[0361] Step 1:

[0362] The user grants the app permission to access the calendar app, location services, and emotion recognition features.

[0363] What it does: On the initial setup screen for the app, select the options to allow access to your calendar, GPS location, and emotion recognition features on your camera and microphone.

[0364] Step 2:

[0365] The device periodically collects calendar information, GPS data, and emotional state data and stores it within the app.

[0366] What it does: The app periodically runs in the background and collects the user's calendar information (e.g., scheduled dates and times, locations), GPS data (e.g., current location, movement history), and emotion recognition data (e.g., facial expressions captured by the camera, voice tones collected by the microphone).

[0367] Step 3:

[0368] The device transmits the collected calendar information, GPS data, and emotional state data to a server.

[0369] Specific operation: Generates packets containing various acquired data and sends them securely to the server using the HTTPS protocol.

[0370] Assessment of loss risk and emotional state

[0371] Step 4:

[0372] The server receives the calendar information, GPS data, and emotional state data sent from the terminal and stores them in a database.

[0373] What it does: Stores the received data in a database for analysis and links it to the registered user profile.

[0374] Step 5:

[0375] The server uses a generative model based on the stored schedule information, location information, and emotional state data to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[0376] How it works: The generative model inputs schedule data, location data, and emotion recognition data to identify the user's behavioral patterns, analyze the correlation with their emotional state, and calculate a loss risk score.

[0377] Specific Actions: If emotional state indicates stress or agitation, increase risk score.

[0378] Insurance plan selection and application

[0379] Step 6:

[0380] The server selects the most suitable insurance plan based on the assessed risk score and emotional state.

[0381] What it does: From a list of pre-defined insurance plans, select the plan that best matches your risk score and emotional state, and then configure its details.

[0382] Step 7:

[0383] The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[0384] Specific operation: The insurance plan details (e.g., insurance period, coverage, compensation amount) are reflected in the user's account and the user is notified via push notification or email.

[0385] Insurance adjustment

[0386] Step 8:

[0387] Users can review their insurance details within the app and adjust coverage and settings as needed, taking their emotional state into account.

[0388] What it does: Displays insurance details in the in-app insurance settings screen, allowing the user to review the options presented and adjust insurance coverage and compensation.

[0389] Step 9:

[0390] The device sends the user's settings to the server and updates them.

[0391] Specific operation: The updated settings are sent to the server using the HTTPS protocol, and the user's insurance information is updated on the server side in real time.

[0392] Real-time assistance and suggestions

[0393] Step 10:

[0394] The server uses a generative model to send notifications that take into account the user's emotional state when there is an increased risk of loss or when certain conditions are met.

[0395] What it does: It monitors GPS data, behavioral patterns, and emotional state in real time, and sends push notifications when the generative model detects increased risk.

[0396] Step 11:

[0397] Users receive real-time notifications and can view and respond within the app.

[0398] Action: Tap the app notification to learn more and take additional action or adjust your behavior as needed.

[0399] Specific examples

[0400] Example 1: If you have many regular business trips

[0401] 1. A user enters "Business Trip" into their calendar and enters "City A" as the destination.

[0402] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[0403] 3. Based on this information, the server generates a generative model that evaluates that the risk of loss increases when traveling. If the user's emotional state indicates stress, the server increases the risk score.

[0404] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[0405] 5. The user reviews the insurance and adjusts the coverage as needed.

[0406] Example 2: When there are many sudden actions

[0407] 1. The user suddenly goes on a weekend trip.

[0408] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[0409] 3. The server uses the generative model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[0410] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[0411] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0412] In this way, users can easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[0413] Example 2

[0414] 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."

[0415] Conventional insurance services have difficulty in properly assessing the degree of risk of loss for users. Furthermore, because insurance plans are applied uniformly without considering the user's emotional state, it is not possible to provide optimal insurance products for users. Therefore, there is a need for a highly accurate insurance service that takes into account the user's behavioral patterns and emotional state.

[0416] 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.

[0417] In this invention, the server includes means for acquiring user schedule information, means for acquiring user location information, means for acquiring the user's emotional state, means for assessing the risk of loss based on the acquired schedule information, location information, and emotional state data, means for selecting an optimal insurance plan based on the assessment result and the emotional state, and means for automatically applying the selected insurance plan to the user. This makes it possible to provide a more accurate assessment of the risk of loss and an insurance plan based on the user's behavioral patterns and emotional state.

[0418] "Schedule information" refers to information about appointments and events that a user has entered into a calendar or app.

[0419] "Location information" refers to GPS data that indicates the user's current location and movement history.

[0420] "Emotional state" is data that captures the user's emotions through a camera or microphone.

[0421] "Loss risk" is the likelihood of losing an item or information, assessed based on the user's behavioral patterns and emotional state.

[0422] "Insurance Plan" means a customized insurance product offered based on the results of a User's risk assessment.

[0423] "Means for acquiring" refers to a method or device for collecting a user's schedule information, location information, or emotional state.

[0424] The "means for evaluating" refers to a method or device for analyzing collected data and evaluating the risk of loss.

[0425] A "means for selecting" is a method or device for selecting the most suitable insurance plan based on the evaluation results and emotional state.

[0426] The "applying means" is a method or device for automatically providing the selected insurance plan to the user.

[0427] A "means for sending notifications" is a method or device for sending information to a user in real time.

[0428] "Means for providing appropriate suggestions and support" are methods and devices for providing optimal actions and support to users.

[0429] MODE FOR CARRYING OUT THE INVENTION

[0430] A specific embodiment of this invention will be described. The present invention is a system that allows users to appropriately manage their loss risk and provides insurance plans tailored to that risk. The system's accuracy is further enhanced by incorporating an emotion engine. Its unique feature is that it provides insurance services tailored to the user's emotional state. This system is comprised of a user's terminal, a central processing server, and a cloud-based database.

[0431] System configuration

[0432] 1. The user grants the app permission to access the calendar app, location services, and emotion recognition, allowing the app to obtain the user's schedule information, location information, and emotional state.

[0433] 2. The device periodically collects calendar information (scheduled dates and times, locations), GPS data (current location, movement history), and emotional state data using the camera and microphone, and sends this data to a central processing server using emotion recognition technologies such as the Face API in Microsoft's Azure Cognitive Services.

[0434] 3. The server uses a generative model based on the received data to analyze the user's behavioral patterns and emotional state and assess the risk of loss. The generative AI model uses Google Cloud's AI Platform.

[0435] 4. The server selects the optimal insurance plan based on the evaluation results and the user's emotional state, and automatically applies the selected insurance plan to the user. For example, if a user travels frequently and is feeling stressed, the server applies "business trip insurance."

[0436] 5. The interface for users to consult and set insurance preferences in advance is always available, and the insurance contents are adjusted based on the user's preferences. The adjusted preferences are sent to the server in real time.

[0437] 6. When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions or support.

[0438] Specific examples

[0439] Example 1: If you have many regular business trips

[0440] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[0441] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[0442] 3. Based on this information, the server uses the generative AI model to evaluate that "the risk of loss increases when traveling." If the user's emotional state indicates stress, the server sets a higher risk score.

[0443] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[0444] 5. The user reviews their insurance and adjusts coverage as needed.

[0445] Example 2: When there are many sudden actions

[0446] 1. The user suddenly goes on a weekend trip.

[0447] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[0448] 3. The server uses the generated AI model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[0449] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[0450] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0451] Prompt Sentence Examples

[0452] An example of a prompt sentence would be:

[0453] "A user has entered a business trip into their calendar. The destination is City A, and the user's emotional state is high. Describe a process for applying travel insurance based on this information and sending notifications that take the user's emotional state into account."

[0454] "A user has an impromptu trip over the weekend. Their current emotional state is excitement. Based on this information, explain the process for applying travel insurance and sending alerts tailored to their emotional state."

[0455] In this way, a system is constructed that allows users to easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[0456] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0457] Program processing flow

[0458] Step 1:

[0459] The user grants permission to access the Calendar app, location services, and emotion recognition features.

[0460] Input: The user grants the app permission to access the calendar app, location services, and emotion recognition features.

[0461] Specific behavior: The user turns on the required permissions in the settings screen.

[0462] Output: Authorization is given for the system to retrieve these data.

[0463] Step 2:

[0464] The device periodically collects calendar information, GPS data, and emotional state data and sends them to a server.

[0465] Input: User's calendar information, current location, movement history, emotional state via camera and microphone.

[0466] How it works: The device periodically reads calendar information and GPS data, and uses the camera and microphone to recognize emotions, for example, using the Face API from Microsoft's Azure Cognitive Services.

[0467] Output: Collected calendar information, GPS data, and emotional state data are sent to a server.

[0468] Step 3:

[0469] The server receives the calendar information, GPS data, and emotional state data sent from the device and stores them in a database.

[0470] Input: Calendar information, GPS data, and emotional state data sent from the device.

[0471] Specific operation: The server stores the received data in a secure cloud database.

[0472] Output: A database of behavioral patterns and emotional states for each user.

[0473] Step 4:

[0474] The server uses a generative AI model based on the stored data to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[0475] Input: Calendar information, GPS data, and emotional state data stored in a database.

[0476] How it works: The server runs a generative model using Google Cloud's AI Platform to analyze this data, extracting features from behavioral patterns and assessing stress levels based on emotional states.

[0477] Output: Generates an assessment of the risk of loss based on the user's behavioral patterns and emotional state.

[0478] Step 5:

[0479] The server selects the most suitable insurance plan based on the evaluation results and emotional state and automatically applies it to the user.

[0480] Input: Loss risk assessment results, emotional state assessment results.

[0481] Specific operation: The server selects an insurance plan based on the risk assessment score and emotional state. In this process, for example, "business trip insurance" or "travel insurance" is selected.

[0482] Output: Selected insurance plan is applied and user is notified.

[0483] Step 6:

[0484] Users can view notifications within the app, review their insurance coverage, and adjust coverage as needed.

[0485] Input: Applied insurance plan, notification message.

[0486] What happens: The user receives a notification, views details in the app, and adjusts the coverage and content of their insurance plan as needed.

[0487] Output: The customized insurance information is reflected in the system.

[0488] Step 7:

[0489] When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions and support.

[0490] Input: Real-time risk of loss, user emotional state.

[0491] How it works: The server continuously monitors data and generates notifications and alerts based on the analysis results of the generative AI model.

[0492] Output: Real-time notifications and suggestions to the user.

[0493] (Application example 2)

[0494] 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."

[0495] In modern society, users are at increased risk of losing their belongings, and this risk often fluctuates depending on the user's emotional state and behavioral patterns. However, traditional insurance systems have struggled to propose optimal insurance plans that take into account individual emotional states and behavioral patterns. Furthermore, they lacked the means to flexibly respond to users' changing risks in real time, making it difficult for users to receive appropriate protection.

[0496] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0497] In this invention, the server includes means for acquiring user schedule information, means for acquiring user location information, means for acquiring the user's emotional state, means for assessing the risk of loss based on the acquired schedule information, location information, and emotional state, means for selecting an optimal insurance plan based on the assessment results, means for automatically applying the selected insurance plan to the user, means for sending a warning notice when the risk of loss increases, and means for suggesting appropriate security measures to the user. This makes it possible to provide more accurate risk assessments and insurance plans based on the individual emotional state and behavioral patterns of the user.

[0498] "User schedule information" refers to information about appointments and events managed by the electronic device used by the user.

[0499] "User location information" refers to information about a user's current location and movement history obtained through GPS or other positioning systems.

[0500] "User's emotional state" is information that indicates the user's emotional and psychological state, which is analyzed using sensors such as a camera and a microphone.

[0501] A "means for assessing risk of loss" is a system or algorithm that analyzes and assesses the likelihood of an item being lost based on the acquired schedule information, location information, and emotional state.

[0502] The "means for selecting the optimal insurance plan" refers to a system or algorithm that determines the appropriate insurance plan for the user based on the results of an assessment of the risk of loss.

[0503] An "automated user insurance plan application" is a system or process that provides a selected insurance plan to a user without manual intervention.

[0504] "Warning notification mechanism" means a system or protocol that sends real-time warnings or alerts to a user's device in response to an increased risk.

[0505] A "means for suggesting security measures" is a system or algorithm that provides users with specific preventative measures or suggested actions to reduce the risk of loss or theft.

[0506] MODE FOR CARRYING OUT THE INVENTION

[0507] This invention is a system that uses a user's emotional state and location information to assess the risk of loss and provide an appropriate insurance plan. Specific embodiments for realizing this system are described below.

[0508] System Configuration

[0509] 1. User's device

[0510] These are mobile devices used by users, such as smartphones and tablets.

[0511] It is equipped with a camera and microphone to capture the user's emotional state.

[0512] It has a GPS function and can obtain the user's location information.

[0513] Use a calendar application to manage your schedule.

[0514] 2. Central Processing Server

[0515] It is equipped with an emotion engine, a data analysis module, and a generative AI model.

[0516] As emotion engines, we use, for example, Affectiva and Microsoft Azure Cognitive Services.

[0517] As a data analysis module, we use cloud-based data storage and analysis infrastructure (e.g., Amazon AWS and Google Cloud Platform).

[0518] Hugging Face Transformers and Google TensorFlow are used as generative AI models.

[0519] 3. Cloud Storage

[0520] Stores and manages user schedule information, location information, and emotional state data.

[0521] The data is sent to the server in real time and the analysis results are returned.

[0522] System Operation

[0523] 1. Data Collection

[0524] A user enters an event into a calendar application and grants access to GPS and emotion recognition features.

[0525] The device periodically collects calendar information, GPS data, and emotional state data from the camera and microphone and sends it to a central processing server.

[0526] 2. Data Analysis

[0527] The server stores the received calendar information, location information, and emotional state data in cloud storage.

[0528] The server uses an emotion engine to analyze the emotional state data and identify the user's psychological state.

[0529] The server uses the generated AI model to analyze user behavior patterns and assess the risk of loss.

[0530] 3. Insurance plan selection and application

[0531] The server selects the most suitable insurance plan based on the assessed risk score and emotional state.

[0532] The selected insurance plan will be automatically applied to the user and a notification will be sent via the app.

[0533] Specific examples

[0534] Example 1: When walking alone at night

[0535] 1. If a user goes out alone at night, enter that information into the calendar.

[0536] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[0537] 3. The server uses an emotion engine to detect when a user is alone at night and exhibits an anxious emotional state.

[0538] 4. The server-generated AI model assesses that there is a high risk of loss due to "going out alone at night."

[0539] 5. The server selects the best insurance plan and notifies the user that they are at high risk.

[0540] 6. The user checks the notification in the app and adjusts their insurance as needed.

[0541] Example prompts for generative AI models

[0542] When the user's emotional state is "unstable" and their location is in a "high crime area," the risk assessment score is set high and a warning is sent to the user saying, "Going out alone late at night is risky. Please choose a safe route."

[0543] As described above, users can receive security assistance based on their emotional state and take safety into consideration.

[0544] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0545] Program processing steps

[0546] Step 1:

[0547] A user enters an event into a calendar app and grants access to GPS and emotion recognition, allowing the device to obtain the user's schedule information, location, and emotional state.

[0548] Input: User's calendar information, GPS information, emotion recognition permission information

[0549] Output: Permission to access user schedule, location, and emotion recognition data

[0550] Step 2:

[0551] The device periodically collects calendar information, GPS data, and emotional state data captured from the camera and microphone, and transmits this data to a central processing server.

[0552] Input: Calendar information, GPS data, emotional state data

[0553] Output: Send collected data to the server

[0554] Step 3:

[0555] The server stores the received calendar information, location information, and emotional state data in cloud storage for later analysis.

[0556] Input: Calendar information, GPS data, and emotional state data sent from the device

[0557] Output: User data stored in cloud storage

[0558] Step 4:

[0559] The server analyzes the emotional state data using an emotion engine to identify the user's psychological state, for example, using Affectiva or Microsoft Azure Cognitive Services to convert the emotion data into an emotion score.

[0560] Input: Emotional state data stored in cloud storage

[0561] Output: Emotion score (analysis result of psychological state)

[0562] Step 5:

[0563] The server analyzes the stored behavioral pattern data using a generative AI model, such as Hugging Face Transformers or Google TensorFlow, to assess the risk of loss based on the user's behavioral patterns and current emotional state.

[0564] Input: Calendar information, location information, sentiment score

[0565] Output: Loss risk assessment score

[0566] Step 6:

[0567] The server selects the optimal insurance plan based on the assessed risk score and emotional state, thereby determining the best insurance plan for the user.

[0568] Input: Loss risk assessment score, sentiment score

[0569] Output: Selected optimal insurance plan

[0570] Step 7:

[0571] The server automatically applies the selected insurance plan to the user and sends a notification through the app, ensuring the user receives the appropriate insurance cover in real time.

[0572] Input: Selected optimal insurance plan

[0573] Output: Insurance plan coverage notification

[0574] Step 8:

[0575] If the risk of loss increases, the server will send a warning notification to the user and suggest appropriate security measures, allowing the user to take defensive measures against the risk in real time.

[0576] Input: Loss Risk Assessment Score

[0577] Output: Warning notice and security suggestion

[0578] Through this series of processing steps, users can receive the optimal insurance plan and real-time security assistance based on various information, including their emotional state.

[0579] 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.

[0580] 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.

[0581] 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.

[0582] [Second embodiment]

[0583] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0584] 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.

[0585] 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).

[0586] 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.

[0587] 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.

[0588] 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).

[0589] 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.

[0590] 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.

[0591] 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.

[0592] 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.

[0593] 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.

[0594] 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."

[0595] MODE FOR CARRYING OUT THE INVENTION

[0596] A specific embodiment of the present invention will be described. The present invention includes a system that provides insurance services to allow users to appropriately manage the risk of loss. The system evaluates the risk of loss based on the user's schedule information and location information, and automatically selects and applies the optimal insurance plan.

[0597] System Overview

[0598] The system consists of user devices, a central processing server, and a cloud-based database for storing and processing user data.

[0599] 1. The user grants the app permission to access their calendar and GPS information, allowing the app to obtain the user's schedule and location information.

[0600] 2. The device (user's smartphone or tablet) periodically collects calendar and location information and sends this data to a central processing server.

[0601] 3. Based on the received schedule information and location information, the server analyzes the user's behavioral patterns using a generative model and evaluates the risk of loss.

[0602] 4. The server selects the most suitable insurance plan based on the evaluation results and automatically applies it to the user.

[0603] 5. Provide an interface that allows users to consult and set insurance settings in advance, and adjust the insurance content based on the user's responses.

[0604] Program processing

[0605] The operation of the system is explained in natural language below.

[0606] Obtaining user schedule and location information

[0607] 1. The user initiates the system by granting the app permission to access the calendar and location services.

[0608] 2. The device acquires the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history) and periodically sends them to the server.

[0609] Loss risk assessment

[0610] 3. The server uses a generative model to analyze the user's behavioral patterns based on the received schedule information and location information.

[0611] 4. The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[0612] Insurance plan selection and application

[0613] 5. The server selects the most suitable insurance plan based on the assessed risk score.

[0614] 6. The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[0615] Insurance adjustment

[0616] 7. The user reviews their insurance details within the app and adjusts their coverage and settings as needed. Adjusted settings are sent to the server in real time.

[0617] Real-time assistance and suggestions

[0618] 8. The server uses the generative model to notify the user when the risk of loss increases or when certain conditions are met, and provides appropriate suggestions and support.

[0619] Specific examples

[0620] Example 1: If you have many regular business trips

[0621] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[0622] 2. The device sends calendar information and GPS data to the server.

[0623] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling."

[0624] 4. The server automatically adds "Travel Insurance" and notifies the user.

[0625] 5. The user reviews their insurance and adjusts coverage as needed.

[0626] Example 2: When there are many sudden actions

[0627] 1. The user suddenly goes on a weekend trip.

[0628] 2. The device sends real-time GPS data to the server.

[0629] 3. The server uses the generative model to determine that there is a high risk of loss during travel.

[0630] 4. The server temporarily applies "travel insurance" and notifies the user.

[0631] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0632] In this way, users can easily access the most suitable insurance and prepare for the risk of loss.

[0633] The processing flow will be explained below.

[0634] Understood. Below is a step-by-step explanation of the specific flow of the programming process for the "Anytime Insurance" system.

[0635] Program processing

[0636] Obtaining user schedule and location information

[0637] Step 1:

[0638] The user grants the app permission to access the calendar app and location services.

[0639] Specific behavior: On the initial setup screen for the app, select the options to allow access to your calendar and use your GPS location.

[0640] Step 2:

[0641] The device periodically collects calendar information and GPS data and sends it to the app.

[0642] Specific behavior: The app periodically retrieves the user's calendar information (e.g., scheduled dates and times, locations) and GPS data (e.g., current location, movement history) in the background.

[0643] Specific operation: The acquired data is stored in local storage and sent to the cloud server at regular intervals.

[0644] Loss risk assessment

[0645] Step 3:

[0646] The server receives the calendar information and GPS data sent from the device and stores them in a database.

[0647] Specific actions: Accurately store received data in a database and format the data for analysis.

[0648] Step 4:

[0649] The server uses a generative model to analyze the user's behavioral patterns based on the stored schedule information and location information, and assesses the risk of loss.

[0650] How it works: The generative model runs on the server and uses calendar information and GPS data as input to identify user behavior patterns and calculate a loss risk score.

[0651] Insurance plan selection and application

[0652] Step 5:

[0653] The server selects the most suitable insurance plan based on the assessed risk score.

[0654] Specific Action: Select the appropriate plan from a pre-configured list of insurance plans based on risk score.

[0655] Step 6:

[0656] The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[0657] What it does: Automatically applies the insurance to the user's account and notifies the user via push notification or email.

[0658] Insurance adjustment

[0659] Step 7:

[0660] Users can review their insurance details within the app and adjust coverage and settings as needed.

[0661] Specific actions: Access the app's insurance settings screen, review the displayed insurance details, and make any necessary adjustments (e.g., change the insurance amount, set the coverage).

[0662] Step 8:

[0663] The device sends the user's settings to the server and updates them.

[0664] Specific operation: The adjusted setting information is sent to the server in real time, and the user's insurance information is updated on the server side.

[0665] Real-time assistance and suggestions

[0666] Step 9:

[0667] The server uses the generative model to send notifications to the user when there is an increased risk of loss or when certain conditions are met.

[0668] What it does: It monitors GPS data and behavioral patterns in real time, and triggers a push notification if the generative model detects an increased risk.

[0669] Step 10:

[0670] Users receive real-time notifications and can view and respond within the app.

[0671] What to do: Tap the notification in the app for more details and to take additional insurance adjustments or actions as needed.

[0672] In this way, users can easily use appropriate loss insurance and prepare for the risk of loss.

[0673] Example 1

[0674] 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."

[0675] The current insurance system requires users to select and change their insurance plans, which makes it difficult to achieve optimal risk management. Furthermore, many users find it difficult to properly assess their risk of loss, resulting in insufficient insurance coverage. Furthermore, in situations where the risk of loss fluctuates in real time, appropriate insurance proposals and support are often not provided.

[0676] 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.

[0677] In this invention, the server includes a means for analyzing a user's behavioral pattern, a means for calculating a risk score, and a means for selecting and applying an appropriate insurance plan, thereby making it possible to evaluate the risk of loss in real time based on the user's behavioral data and automatically apply the most appropriate insurance plan.

[0678] "Means for obtaining user schedule information" refers to a function for obtaining data regarding scheduled dates, times, and locations from the calendar app or schedule management app used by the user.

[0679] "Means of obtaining user location information" refers to a function that uses the user's location information service or GPS function to obtain the user's current location and movement history.

[0680] The "means for transmitting acquired schedule information and location information to a server" is a function that transmits schedule information and location information periodically collected by a user's terminal to a central processing server via data communication.

[0681] "Means for analyzing user behavior patterns using generative AI models" refers to a function that uses machine learning algorithms and artificial intelligence based on collected data to analyze and reveal user behavior patterns.

[0682] "Means for assessing the risk of loss based on behavioral patterns and calculating a risk score" refers to a function that assesses the risk of loss using statistical analysis and risk models based on user behavioral data and calculates that risk as a numerical score.

[0683] "Means for selecting the most suitable insurance plan based on risk score" is a function for selecting the most suitable insurance plan from a database based on the calculated risk score and applying it to the user.

[0684] "Means for automatically applying the selected insurance plan to the user" is a function for automatically applying the selected insurance plan to the user's account and notifying the user of the application results.

[0685] "Means for users to consult and set up their insurance settings in advance" refers to interfaces and functions that allow users to consult about insurance details in advance and set up insurance according to their individual needs.

[0686] "Means for adjusting the contents of the insurance plan based on the user's setting information" is a function for automatically adjusting the contents of the insurance plan based on the information set in advance by the user and applying it to the user.

[0687] "Means for sending a notification to the user in real time when the risk of loss increases" is a function for sending a notification to the user in real time when the risk of loss exceeds a certain threshold.

[0688] "Means for providing appropriate suggestions and support to users" refers to a function for providing appropriate suggestions and support to users to reduce the risk of loss.

[0689] MODE FOR CARRYING OUT THE INVENTION

[0690] A specific embodiment of the present invention will be described in detail. This invention is a system that provides insurance services to enable users to appropriately manage the risk of loss. The system aims to evaluate the risk of loss based on the user's schedule information and location information, and automatically select and apply the optimal insurance plan.

[0691] System configuration

[0692] The system consists of the following major components:

[0693] 1. User's Device

[0694] Devices users carry around with them, such as smartphones and tablets

[0695] Includes a calendar app and location services

[0696] The app collects the user's calendar information and GPS data and sends it to a server

[0697] 2. Central Processing Server

[0698] A server with high-performance computing power

[0699] Analyze user behavior patterns using generative AI models to assess risk of loss

[0700] Select the best insurance plan and automatically apply it to the user

[0701] 3. Cloud-based databases

[0702] A database for storing and processing user schedule information, location information, and insurance setting information

[0703] High security and scalability

[0704] Program processing

[0705] The operation of the system is explained in natural language below.

[0706] Obtaining user schedule and location information

[0707] 1. The user grants the app permission to access the Calendar app and Location Services.

[0708] 2. The device obtains the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history).

[0709] 3. The device periodically sends the acquired data to the server.

[0710] Loss risk assessment

[0711] 4. The server analyzes the user's behavioral patterns using a generative AI model based on the received schedule and location information.

[0712] 5. The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[0713] Insurance plan selection and application

[0714] 6. The server selects the most suitable insurance plan based on the assessed risk score.

[0715] 7. The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[0716] Insurance adjustment

[0717] 8. The user reviews their insurance within the app and adjusts their coverage and settings as needed.

[0718] 9. The server receives the adjusted settings and updates the insurance plan.

[0719] Real-time assistance and suggestions

[0720] 10. The server uses generative AI models to notify users when there is an increased risk of loss or when certain conditions are met, and provide appropriate suggestions and support.

[0721] Specific examples

[0722] Example 1: If you have many regular business trips

[0723] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[0724] 2. The device sends calendar information and GPS data to the server.

[0725] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling."

[0726] 4. The server automatically adds "Travel Insurance" and notifies the user.

[0727] 5. The user reviews their insurance and adjusts coverage as needed.

[0728] Example 2: When there are many sudden actions

[0729] 1. The user suddenly goes on a weekend trip.

[0730] 2. The device sends real-time GPS data to the server.

[0731] 3. The server uses the generative model to determine that there is a high risk of loss during travel.

[0732] 4. The server temporarily applies "travel insurance" and notifies the user.

[0733] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0734] In this way, users can easily access the most suitable insurance and prepare for the risk of loss.

[0735] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0736] Step 1:

[0737] The user grants the app permission to access the Calendar app and Location Services.

[0738] Specific operation: The user sets the app's permissions from the smartphone settings screen and allows access to calendar information and location information.

[0739] Input: User sets permissions.

[0740] Output: The permission information that has been set.

[0741] Step 2:

[0742] The device obtains the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history).

[0743] Specific operation: Uses the smartphone's antenna and Wi-Fi to obtain real-time location information and loads schedule information through the calendar API.

[0744] Input: Calendar and location with permissions set.

[0745] Output: Retrieved calendar information and GPS data.

[0746] Step 3:

[0747] The data acquired by the terminal is periodically sent to the server.

[0748] Specific operation: At regular intervals (for example, every minute), a background process on the device is started, which encrypts the acquired data packets and sends them to the server using the HTTPS protocol.

[0749] Input: Captured calendar information and GPS data.

[0750] Output: Data packet sent to the server.

[0751] Step 4:

[0752] The server uses a generative AI model to analyze the user's behavioral patterns based on the received schedule information and location information.

[0753] Specific operation: The server calls a generative AI model such as a cloud AI service and performs analysis using the user's data stream as input.

[0754] Input: Schedule and location information sent to the server.

[0755] Output: Analyzed behavioral patterns.

[0756] Step 5:

[0757] The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[0758] What it does: It uses pattern recognition technology to evaluate certain behavioral trends and outliers, then uses statistical models to calculate a risk score.

[0759] Input: Analyzed behavioral patterns.

[0760] Output: The calculated risk score.

[0761] Step 6:

[0762] The server selects the most suitable insurance plan based on the assessed risk score.

[0763] Specific operation: Search and select the insurance plan that best suits the risk profile from the database in the server. For example, use SQL to retrieve the insurance plan that corresponds to the risk score.

[0764] Input: Risk score.

[0765] Output: The selected insurance plan.

[0766] Step 7:

[0767] The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[0768] What it does: Sends a notification to the user's app via a REST API, displaying details of the insurance plan applied.

[0769] Input: Selected insurance plan.

[0770] Output: Notification to user terminal.

[0771] Step 8:

[0772] Users can review their insurance details within the app and adjust coverage and settings as needed.

[0773] What it does: The app UI displays insurance information and allows users to change settings using a form, with changes sent to the server in real time.

[0774] Input: Insurance plan details.

[0775] Output: Adjusted insurance settings.

[0776] Step 9:

[0777] The server receives the adjusted settings and updates the insurance plan.

[0778] Specific operation: Analyzes the received data and updates the insurance configuration database on the server. For example, it updates the configuration data using a NoSQL database (such as MongoDB).

[0779] Input: Adjusted insurance settings.

[0780] Output: Updated insurance plan.

[0781] Step 10:

[0782] The server uses a generative AI model to notify users when there is an increased risk of loss or when certain conditions are met, and provide appropriate suggestions and support.

[0783] Specific operation: Monitors real-time data and issues push notifications when conditions are met. Notifications are sent to users' devices using cloud messaging services, etc.

[0784] Input: Real-time loss risk assessment.

[0785] Output: Push notification and suggestion.

[0786] (Application example 1)

[0787] 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."

[0788] When managing the risk of loss for customers and employees in physical stores, conventional methods have made it difficult to perform detailed risk assessments and apply optimal insurance plans. Furthermore, automatic application of insurance based on real-time risk fluctuations and user behavior has not been sufficiently implemented. This has led to the issue of not being able to provide appropriate support in situations where the risk of loss is high.

[0789] 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.

[0790] In this invention, the server includes: means for acquiring a user's schedule information; means for acquiring the user's location information; means for assessing the risk of loss based on the acquired schedule information and location information; means for selecting an optimal insurance plan based on the assessment results; means for automatically applying the selected insurance plan to the user; means for periodically updating the user's location information and reassessing the risk of loss; means for applying and updating the insurance plan based on the reassessment results; means for consulting and setting the user's insurance settings in advance; means for adjusting the contents of the insurance plan based on the user's setting information; means for notifying the user of the insurance application results; means for sending a notification to the user in real time when the risk of loss increases; means for providing appropriate suggestions and support to the user; and means for providing an interface for manual adjustment based on the reassessment results. This enables the risk of loss for customers and employees in physical stores to be managed through detailed assessments and the application of optimal insurance plans. It can also respond to risk fluctuations in real time and automatically apply insurance and support based on user behavior.

[0791] "Means for obtaining user schedule information" refers to a function for obtaining information entered by the user into a calendar app or schedule management application.

[0792] "Means of obtaining user location information" refers to a function for obtaining location information from a user's device, such as a smartphone or tablet, through GPS or location information services.

[0793] "Means for assessing the risk of loss based on acquired schedule information and location information" is a function for calculating the possibility of loss and assessing the risk based on the user's calendar information and location information.

[0794] The "means for selecting the most suitable insurance plan based on the evaluation results" is a function for selecting the most suitable insurance plan for the user based on the evaluation of the risk of loss.

[0795] The "means for automatically applying the selected insurance plan to the user" is a function that enables the system to automatically apply the selected insurance plan to the user.

[0796] "Means for periodically updating the user's location information and reassessing the risk of loss" is a function for periodically obtaining the user's current location and reassessing the risk based on that information.

[0797] "Means to apply and update insurance plans based on reassessment results" refers to the functionality for reviewing and updating existing insurance plans based on new risk assessment results.

[0798] "Means for consulting and setting up the user's insurance settings in advance" is a function that allows the user to consult with the user in advance about the details and settings of the insurance and set up the insurance settings that the user desires.

[0799] "Means for adjusting the contents of the insurance plan based on the user's setting information" refers to a function for changing and adjusting the contents of the insurance plan based on the information set in advance by the user.

[0800] "Means for notifying users of insurance coverage results" is a function for informing users that the selected insurance plan has been applied.

[0801] "Means for sending notifications to users in real time when the risk of loss increases" is a function for immediately sending warnings and notifications to users when the risk of loss increases.

[0802] "Means of making appropriate suggestions and support to users" refers to a function that provides specific advice and support to avoid risks when it is determined that there is a high risk of loss.

[0803] "Means for providing an interface that allows manual adjustments based on the results of reassessment" refers to a function for providing an interface that allows a user to manually adjust insurance coverage based on the updated results of risk assessment.

[0804] An embodiment of the present invention will now be described in detail. This system evaluates the risk of loss based on the user's schedule information and location information, and selects and applies an appropriate insurance plan. A detailed description of the system is provided below.

[0805] System configuration

[0806] The system mainly consists of a user terminal, a central processing server, and a cloud-based database. Users are expected to use smartphones and tablets.

[0807] Hardware and software used

[0808] Hardware: Smartphones, tablets

[0809] Software: Python 3.9, geopy library, requests library

[0810] Data processing and calculation

[0811] Obtaining user schedule and location information

[0812] The system is activated when a user grants the app permission to access the calendar app and location services. The user's device obtains calendar information (scheduled dates and times, locations) and GPS data (current location, movement history), and periodically sends this data to a central processing server.

[0813] Example prompt: "Do you consent to collecting your calendar and location information?"

[0814] Loss risk assessment

[0815] The server uses the generated AI model to analyze the user's behavioral patterns based on the acquired schedule and location information. During this process, the server calculates the distance between the user's current location and the scheduled location, and calculates a risk score based on the result. For example, if the current location is very close to the scheduled location, the risk score will be high.

[0816] Selecting an insurance plan

[0817] The server selects the most suitable insurance plan based on the assessed risk score, which is then automatically applied to the user's account.

[0818] Insurance coverage based on risk scores

[0819] The server periodically updates the user's location and reassess the risk of loss based on that information. Based on the risk assessment, the insurance plan in place is adjusted and, if necessary, a new insurance plan is installed.

[0820] Specific examples

[0821] Example 1: If you have many regular business trips

[0822] 1. A user enters "Business Trip" into their calendar and enters "City A" as the destination.

[0823] 2. The user's device sends calendar information and GPS data to the server.

[0824] 3. Based on this information, the server generates an AI model that assesses that "the risk of loss increases when traveling."

[0825] 4. The server automatically adds "Travel Insurance" and notifies the user.

[0826] 5. The user reviews their insurance and adjusts coverage as needed.

[0827] Example 2: When there are many sudden actions

[0828] 1. The user suddenly goes on a weekend trip.

[0829] 2. The user's device sends real-time GPS data to the server.

[0830] 3. The server uses the generated AI model to determine that there is a high risk of loss during travel.

[0831] 4. The server temporarily applies "travel insurance" and notifies the user.

[0832] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0833] In this way, users can easily use the most suitable insurance and prepare for the risk of loss. Real-time risk assessment and automatic insurance application will more effectively protect users' safety.

[0834] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0835] Step 1:

[0836] The system starts when the user grants the app permission to access the calendar app and location services.

[0837] Input: User permission information

[0838] What happens: The user confirms the permissions based on the prompt and presses the accept button.

[0839] Output: The app gets access to the user's schedule and location.

[0840] Step 2:

[0841] The device acquires the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history), and periodically transmits this data to a central processing server.

[0842] Input: Calendar information, GPS data

[0843] How it works: Your device periodically retrieves data from the Calendar app and Location Services and sends it to the server.

[0844] Output: Calendar information and GPS data are sent to the server.

[0845] Step 3:

[0846] The server uses a generative AI model to analyze the user's behavioral patterns based on the received schedule and location information.

[0847] Input: Calendar information, GPS data

[0848] How it works: The server inputs schedule and location information into a generative AI model that analyzes behavioral patterns.

[0849] Output: User behavior pattern data

[0850] Step 4:

[0851] The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[0852] Input: User behavior pattern data

[0853] How it works: The server calculates a risk score based on the analysis results, taking into account factors such as the distance between locations and the length of time spent there.

[0854] Output: Risk score

[0855] Step 5:

[0856] The server selects the most appropriate insurance plan based on the evaluation results and automatically applies it to the user.

[0857] Input: Risk Score

[0858] How it works: The server selects the most appropriate plan from pre-set insurance plans (low, medium, high) based on the risk score and automatically applies it.

[0859] Output: Insurance plan information applied

[0860] Step 6:

[0861] The server periodically updates the user's location and reassess the risk of loss.

[0862] Input: Latest GPS data

[0863] How it works: The server periodically retrieves the latest location information and performs risk assessment again.

[0864] Output: Updated risk score

[0865] Step 7:

[0866] The server applies and updates the insurance plan based on the reassessment results.

[0867] Input: Updated Risk Score

[0868] How it works: The server updates the insurance plan as needed based on the new risk score.

[0869] Output: Updated insurance plan information

[0870] Step 8:

[0871] Users can check their insurance coverage results within the app and adjust their insurance coverage as needed.

[0872] Input: Insurance plan information

[0873] How it works: A user opens the app, sees their insurance plan, and makes adjustments through the interface.

[0874] Output: Adjusted insurance plan settings

[0875] 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.

[0876] MODE FOR CARRYING OUT THE INVENTION

[0877] A specific embodiment of the present invention will be described. The present invention includes a system that allows users to appropriately manage their risk of loss and provides insurance plans according to that risk, and by combining it with an emotion engine, it further improves accuracy and provides insurance services according to the user's emotional state.

[0878] System Overview

[0879] The system consists of a user device, a central processing server, and a cloud-based database for storing and processing user data. It also incorporates an emotion engine to identify the user's emotional state and use that information to assess loss risk and select insurance plans.

[0880] 1. The user grants the app permission to access the calendar app, GPS information, and emotion recognition, allowing the app to obtain the user's schedule information, location information, and emotional state.

[0881] 2. The device periodically collects calendar information, GPS data, and emotional state data and transmits this data to a central processing server.

[0882] 3. Based on the received data, the server uses a generative model to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[0883] 4. The server selects the optimal insurance plan based on the evaluation results and automatically applies the customized plan to the user, taking into account their emotional state.

[0884] 5. Provide an interface that allows users to consult and set insurance settings in advance, and adjust the insurance content based on the user's settings information.

[0885] Program processing

[0886] The operation of the system is explained in natural language below.

[0887] Obtaining user schedule information, location information, and emotional state

[0888] 1. The user initiates the system by granting the app permission to access the calendar app, location services, and emotion recognition features.

[0889] 2. The device periodically collects calendar information (scheduled date and time, location), GPS data (current location, movement history), and emotional state data using the camera and microphone, and sends this data to the server.

[0890] Assessment of loss risk and emotional state

[0891] 3. The server receives the calendar information, GPS data, and emotional state data sent from the device and stores them in a database.

[0892] 4. The server uses a generative model to analyze the user's behavioral patterns and emotional state based on the stored schedule information, location information, and emotional state data, and evaluates the risk of loss.

[0893] Insurance plan selection and application

[0894] 5. The server selects the best insurance plan based on the assessed risk score and emotional state.

[0895] 6. The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[0896] Insurance adjustment

[0897] 7. The user checks the insurance details within the app and adjusts the coverage and settings to take into account their emotional state as needed. The adjusted settings are sent to the server in real time.

[0898] Real-time assistance and suggestions

[0899] 8. When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions or support.

[0900] Specific examples

[0901] Example 1: If you have many regular business trips

[0902] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[0903] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[0904] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling." If the user's emotional state indicates stress, the server sets a higher risk score.

[0905] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[0906] 5. The user reviews their insurance and adjusts coverage as needed.

[0907] Example 2: When there are many sudden actions

[0908] 1. The user suddenly goes on a weekend trip.

[0909] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[0910] 3. The server uses the generative model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[0911] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[0912] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0913] In this way, users can easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[0914] The processing flow will be explained below.

[0915] Understood. Below is a step-by-step explanation of the specific flow of the programming process for the "Anytime Insurance" system.

[0916] Program processing

[0917] Obtaining user schedule information, location information, and emotional state

[0918] Step 1:

[0919] The user grants the app permission to access the calendar app, location services, and emotion recognition features.

[0920] What it does: On the initial setup screen for the app, select the options to allow access to your calendar, GPS location, and emotion recognition features on your camera and microphone.

[0921] Step 2:

[0922] The device periodically collects calendar information, GPS data, and emotional state data and stores it within the app.

[0923] What it does: The app periodically runs in the background and collects the user's calendar information (e.g., scheduled dates and times, locations), GPS data (e.g., current location, movement history), and emotion recognition data (e.g., facial expressions captured by the camera, voice tones collected by the microphone).

[0924] Step 3:

[0925] The device transmits the collected calendar information, GPS data, and emotional state data to a server.

[0926] Specific operation: Generates packets containing various acquired data and sends them securely to the server using the HTTPS protocol.

[0927] Assessment of loss risk and emotional state

[0928] Step 4:

[0929] The server receives the calendar information, GPS data, and emotional state data sent from the terminal and stores them in a database.

[0930] What it does: Stores the received data in a database for analysis and links it to the registered user profile.

[0931] Step 5:

[0932] The server uses a generative model based on the stored schedule information, location information, and emotional state data to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[0933] How it works: The generative model inputs schedule data, location data, and emotion recognition data to identify the user's behavioral patterns, analyze the correlation with their emotional state, and calculate a loss risk score.

[0934] Specific Actions: If emotional state indicates stress or agitation, increase risk score.

[0935] Insurance plan selection and application

[0936] Step 6:

[0937] The server selects the most suitable insurance plan based on the assessed risk score and emotional state.

[0938] What it does: From a list of pre-defined insurance plans, select the plan that best matches your risk score and emotional state, and then configure its details.

[0939] Step 7:

[0940] The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[0941] Specific operation: The insurance plan details (e.g., insurance period, coverage, compensation amount) are reflected in the user's account and the user is notified via push notification or email.

[0942] Insurance adjustment

[0943] Step 8:

[0944] Users can review their insurance details within the app and adjust coverage and settings as needed, taking their emotional state into account.

[0945] What it does: Displays insurance details in the in-app insurance settings screen, allowing the user to review the options presented and adjust insurance coverage and compensation.

[0946] Step 9:

[0947] The device sends the user's settings to the server and updates them.

[0948] Specific operation: The updated settings are sent to the server using the HTTPS protocol, and the user's insurance information is updated on the server side in real time.

[0949] Real-time assistance and suggestions

[0950] Step 10:

[0951] The server uses a generative model to send notifications that take into account the user's emotional state when there is an increased risk of loss or when certain conditions are met.

[0952] What it does: It monitors GPS data, behavioral patterns, and emotional state in real time, and sends push notifications when the generative model detects increased risk.

[0953] Step 11:

[0954] Users receive real-time notifications and can view and respond within the app.

[0955] Action: Tap the app notification to learn more and take additional action or adjust your behavior as needed.

[0956] Specific examples

[0957] Example 1: If you have many regular business trips

[0958] 1. A user enters "Business Trip" into their calendar and enters "City A" as the destination.

[0959] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[0960] 3. Based on this information, the server generates a generative model that evaluates that the risk of loss increases when traveling. If the user's emotional state indicates stress, the server increases the risk score.

[0961] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[0962] 5. The user reviews the insurance and adjusts the coverage as needed.

[0963] Example 2: When there are many sudden actions

[0964] 1. The user suddenly goes on a weekend trip.

[0965] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[0966] 3. The server uses the generative model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[0967] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[0968] 5. The user reviews the notification in the app and customizes the insurance as needed.

[0969] In this way, users can easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[0970] Example 2

[0971] 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."

[0972] Conventional insurance services have difficulty in properly assessing the degree of risk of loss for users. Furthermore, because insurance plans are applied uniformly without considering the user's emotional state, it is not possible to provide optimal insurance products for users. Therefore, there is a need for a highly accurate insurance service that takes into account the user's behavioral patterns and emotional state.

[0973] 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.

[0974] In this invention, the server includes means for acquiring user schedule information, means for acquiring user location information, means for acquiring the user's emotional state, means for assessing the risk of loss based on the acquired schedule information, location information, and emotional state data, means for selecting an optimal insurance plan based on the assessment result and the emotional state, and means for automatically applying the selected insurance plan to the user. This makes it possible to provide a more accurate assessment of the risk of loss and an insurance plan based on the user's behavioral patterns and emotional state.

[0975] "Schedule information" refers to information about appointments and events that a user has entered into a calendar or app.

[0976] "Location information" refers to GPS data that indicates the user's current location and movement history.

[0977] "Emotional state" is data that captures the user's emotions through a camera or microphone.

[0978] "Loss risk" is the likelihood of losing an item or information, assessed based on the user's behavioral patterns and emotional state.

[0979] "Insurance Plan" means a customized insurance product offered based on the results of a User's risk assessment.

[0980] "Means for acquiring" refers to a method or device for collecting a user's schedule information, location information, or emotional state.

[0981] The "means for evaluating" refers to a method or device for analyzing collected data and evaluating the risk of loss.

[0982] A "means for selecting" is a method or device for selecting the most suitable insurance plan based on the evaluation results and emotional state.

[0983] The "applying means" is a method or device for automatically providing the selected insurance plan to the user.

[0984] A "means for sending notifications" is a method or device for sending information to a user in real time.

[0985] "Means for providing appropriate suggestions and support" are methods and devices for providing optimal actions and support to users.

[0986] MODE FOR CARRYING OUT THE INVENTION

[0987] A specific embodiment of this invention will be described. The present invention is a system that allows users to appropriately manage their loss risk and provides insurance plans tailored to that risk. The system's accuracy is further enhanced by incorporating an emotion engine. Its unique feature is that it provides insurance services tailored to the user's emotional state. This system is comprised of a user's terminal, a central processing server, and a cloud-based database.

[0988] System configuration

[0989] 1. The user grants the app permission to access the calendar app, location services, and emotion recognition, allowing the app to obtain the user's schedule information, location information, and emotional state.

[0990] 2. The device periodically collects calendar information (scheduled dates and times, locations), GPS data (current location, movement history), and emotional state data using the camera and microphone, and sends this data to a central processing server using emotion recognition technologies such as the Face API in Microsoft's Azure Cognitive Services.

[0991] 3. The server uses a generative model based on the received data to analyze the user's behavioral patterns and emotional state and assess the risk of loss. The generative AI model uses Google Cloud's AI Platform.

[0992] 4. The server selects the optimal insurance plan based on the evaluation results and the user's emotional state, and automatically applies the selected insurance plan to the user. For example, if a user travels frequently and is feeling stressed, the server applies "business trip insurance."

[0993] 5. The interface for users to consult and set insurance preferences in advance is always available, and the insurance contents are adjusted based on the user's preferences. The adjusted preferences are sent to the server in real time.

[0994] 6. When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions or support.

[0995] Specific examples

[0996] Example 1: If you have many regular business trips

[0997] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[0998] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[0999] 3. Based on this information, the server uses the generative AI model to evaluate that "the risk of loss increases when traveling." If the user's emotional state indicates stress, the server sets a higher risk score.

[1000] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[1001] 5. The user reviews their insurance and adjusts coverage as needed.

[1002] Example 2: When there are many sudden actions

[1003] 1. The user suddenly goes on a weekend trip.

[1004] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[1005] 3. The server uses the generated AI model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[1006] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[1007] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1008] Prompt Sentence Examples

[1009] An example of a prompt sentence would be:

[1010] "A user has entered a business trip into their calendar. The destination is City A, and the user's emotional state is high. Describe a process for applying travel insurance based on this information and sending notifications that take the user's emotional state into account."

[1011] "A user has an impromptu trip over the weekend. Their current emotional state is excitement. Based on this information, explain the process for applying travel insurance and sending alerts tailored to their emotional state."

[1012] In this way, a system is constructed that allows users to easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[1013] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1014] Program processing flow

[1015] Step 1:

[1016] The user grants permission to access the Calendar app, location services, and emotion recognition features.

[1017] Input: The user grants the app permission to access the calendar app, location services, and emotion recognition features.

[1018] Specific behavior: The user turns on the required permissions in the settings screen.

[1019] Output: Authorization is given for the system to retrieve these data.

[1020] Step 2:

[1021] The device periodically collects calendar information, GPS data, and emotional state data and sends them to a server.

[1022] Input: User's calendar information, current location, movement history, emotional state via camera and microphone.

[1023] How it works: The device periodically reads calendar information and GPS data, and uses the camera and microphone to recognize emotions, for example, using the Face API from Microsoft's Azure Cognitive Services.

[1024] Output: Collected calendar information, GPS data, and emotional state data are sent to a server.

[1025] Step 3:

[1026] The server receives the calendar information, GPS data, and emotional state data sent from the device and stores them in a database.

[1027] Input: Calendar information, GPS data, and emotional state data sent from the device.

[1028] Specific operation: The server stores the received data in a secure cloud database.

[1029] Output: A database of behavioral patterns and emotional states for each user.

[1030] Step 4:

[1031] The server uses a generative AI model based on the stored data to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[1032] Input: Calendar information, GPS data, and emotional state data stored in a database.

[1033] How it works: The server runs a generative model using Google Cloud's AI Platform to analyze this data, extracting features from behavioral patterns and assessing stress levels based on emotional states.

[1034] Output: Generates an assessment of the risk of loss based on the user's behavioral patterns and emotional state.

[1035] Step 5:

[1036] The server selects the most suitable insurance plan based on the evaluation results and emotional state and automatically applies it to the user.

[1037] Input: Loss risk assessment results, emotional state assessment results.

[1038] Specific operation: The server selects an insurance plan based on the risk assessment score and emotional state. In this process, for example, "business trip insurance" or "travel insurance" is selected.

[1039] Output: Selected insurance plan is applied and user is notified.

[1040] Step 6:

[1041] Users can view notifications within the app, review their insurance coverage, and adjust coverage as needed.

[1042] Input: Applied insurance plan, notification message.

[1043] What happens: The user receives a notification, views details in the app, and adjusts the coverage and content of their insurance plan as needed.

[1044] Output: The customized insurance information is reflected in the system.

[1045] Step 7:

[1046] When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions and support.

[1047] Input: Real-time risk of loss, user emotional state.

[1048] How it works: The server continuously monitors data and generates notifications and alerts based on the analysis results of the generative AI model.

[1049] Output: Real-time notifications and suggestions to the user.

[1050] (Application example 2)

[1051] 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."

[1052] In modern society, users are at increased risk of losing their belongings, and this risk often fluctuates depending on the user's emotional state and behavioral patterns. However, traditional insurance systems have struggled to propose optimal insurance plans that take into account individual emotional states and behavioral patterns. Furthermore, they lacked the means to flexibly respond to users' changing risks in real time, making it difficult for users to receive appropriate protection.

[1053] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1054] In this invention, the server includes means for acquiring user schedule information, means for acquiring user location information, means for acquiring the user's emotional state, means for assessing the risk of loss based on the acquired schedule information, location information, and emotional state, means for selecting an optimal insurance plan based on the assessment results, means for automatically applying the selected insurance plan to the user, means for sending a warning notice when the risk of loss increases, and means for suggesting appropriate security measures to the user. This makes it possible to provide more accurate risk assessments and insurance plans based on the individual emotional state and behavioral patterns of the user.

[1055] "User schedule information" refers to information about appointments and events managed by the electronic device used by the user.

[1056] "User location information" refers to information about a user's current location and movement history obtained through GPS or other positioning systems.

[1057] "User's emotional state" is information that indicates the user's emotional and psychological state, which is analyzed using sensors such as a camera and a microphone.

[1058] A "means for assessing risk of loss" is a system or algorithm that analyzes and assesses the likelihood of an item being lost based on the acquired schedule information, location information, and emotional state.

[1059] The "means for selecting the optimal insurance plan" refers to a system or algorithm that determines the appropriate insurance plan for the user based on the results of an assessment of the risk of loss.

[1060] An "automated user insurance plan application" is a system or process that provides a selected insurance plan to a user without manual intervention.

[1061] "Warning notification mechanism" means a system or protocol that sends real-time warnings or alerts to a user's device in response to an increased risk.

[1062] A "means for suggesting security measures" is a system or algorithm that provides users with specific preventative measures or suggested actions to reduce the risk of loss or theft.

[1063] MODE FOR CARRYING OUT THE INVENTION

[1064] This invention is a system that uses a user's emotional state and location information to assess the risk of loss and provide an appropriate insurance plan. Specific embodiments for realizing this system are described below.

[1065] System Configuration

[1066] 1. User's device

[1067] These are mobile devices used by users, such as smartphones and tablets.

[1068] It is equipped with a camera and microphone to capture the user's emotional state.

[1069] It has a GPS function and can obtain the user's location information.

[1070] Use a calendar application to manage your schedule.

[1071] 2. Central Processing Server

[1072] It is equipped with an emotion engine, a data analysis module, and a generative AI model.

[1073] As emotion engines, we use, for example, Affectiva and Microsoft Azure Cognitive Services.

[1074] As a data analysis module, we use cloud-based data storage and analysis infrastructure (e.g., Amazon AWS and Google Cloud Platform).

[1075] Hugging Face Transformers and Google TensorFlow are used as generative AI models.

[1076] 3. Cloud Storage

[1077] Stores and manages user schedule information, location information, and emotional state data.

[1078] The data is sent to the server in real time and the analysis results are returned.

[1079] System Operation

[1080] 1. Data Collection

[1081] A user enters an event into a calendar application and grants access to GPS and emotion recognition features.

[1082] The device periodically collects calendar information, GPS data, and emotional state data from the camera and microphone and sends it to a central processing server.

[1083] 2. Data Analysis

[1084] The server stores the received calendar information, location information, and emotional state data in cloud storage.

[1085] The server uses an emotion engine to analyze the emotional state data and identify the user's psychological state.

[1086] The server uses the generated AI model to analyze user behavior patterns and assess the risk of loss.

[1087] 3. Insurance plan selection and application

[1088] The server selects the most suitable insurance plan based on the assessed risk score and emotional state.

[1089] The selected insurance plan will be automatically applied to the user and a notification will be sent via the app.

[1090] Specific examples

[1091] Example 1: When walking alone at night

[1092] 1. If a user goes out alone at night, enter that information into the calendar.

[1093] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[1094] 3. The server uses an emotion engine to detect when a user is alone at night and exhibits an anxious emotional state.

[1095] 4. The server-generated AI model assesses that there is a high risk of loss due to "going out alone at night."

[1096] 5. The server selects the best insurance plan and notifies the user that they are at high risk.

[1097] 6. The user checks the notification in the app and adjusts their insurance as needed.

[1098] Example prompts for generative AI models

[1099] When the user's emotional state is "unstable" and their location is in a "high crime area," the risk assessment score is set high and a warning is sent to the user saying, "Going out alone late at night is risky. Please choose a safe route."

[1100] As described above, users can receive security assistance based on their emotional state and take safety into consideration.

[1101] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1102] Program processing steps

[1103] Step 1:

[1104] A user enters an event into a calendar app and grants access to GPS and emotion recognition, allowing the device to obtain the user's schedule information, location, and emotional state.

[1105] Input: User's calendar information, GPS information, emotion recognition permission information

[1106] Output: Permission to access user schedule, location, and emotion recognition data

[1107] Step 2:

[1108] The device periodically collects calendar information, GPS data, and emotional state data captured from the camera and microphone, and transmits this data to a central processing server.

[1109] Input: Calendar information, GPS data, emotional state data

[1110] Output: Send collected data to the server

[1111] Step 3:

[1112] The server stores the received calendar information, location information, and emotional state data in cloud storage for later analysis.

[1113] Input: Calendar information, GPS data, and emotional state data sent from the device

[1114] Output: User data stored in cloud storage

[1115] Step 4:

[1116] The server analyzes the emotional state data using an emotion engine to identify the user's psychological state, for example, using Affectiva or Microsoft Azure Cognitive Services to convert the emotion data into an emotion score.

[1117] Input: Emotional state data stored in cloud storage

[1118] Output: Emotion score (analysis result of psychological state)

[1119] Step 5:

[1120] The server analyzes the stored behavioral pattern data using a generative AI model, such as Hugging Face Transformers or Google TensorFlow, to assess the risk of loss based on the user's behavioral patterns and current emotional state.

[1121] Input: Calendar information, location information, sentiment score

[1122] Output: Loss risk assessment score

[1123] Step 6:

[1124] The server selects the optimal insurance plan based on the assessed risk score and emotional state, thereby determining the best insurance plan for the user.

[1125] Input: Loss risk assessment score, sentiment score

[1126] Output: Selected optimal insurance plan

[1127] Step 7:

[1128] The server automatically applies the selected insurance plan to the user and sends a notification through the app, ensuring the user receives the appropriate insurance cover in real time.

[1129] Input: Selected optimal insurance plan

[1130] Output: Insurance plan coverage notification

[1131] Step 8:

[1132] If the risk of loss increases, the server will send a warning notification to the user and suggest appropriate security measures, allowing the user to take defensive measures against the risk in real time.

[1133] Input: Loss Risk Assessment Score

[1134] Output: Warning notice and security suggestion

[1135] Through this series of processing steps, users can receive the optimal insurance plan and real-time security assistance based on various information, including their emotional state.

[1136] 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.

[1137] 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.

[1138] 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.

[1139] [Third embodiment]

[1140] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1141] 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.

[1142] 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).

[1143] 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.

[1144] 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.

[1145] 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).

[1146] 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.

[1147] 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.

[1148] 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.

[1149] 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.

[1150] 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.

[1151] 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."

[1152] MODE FOR CARRYING OUT THE INVENTION

[1153] A specific embodiment of the present invention will be described. The present invention includes a system that provides insurance services to allow users to appropriately manage the risk of loss. The system evaluates the risk of loss based on the user's schedule information and location information, and automatically selects and applies the optimal insurance plan.

[1154] System Overview

[1155] The system consists of user devices, a central processing server, and a cloud-based database for storing and processing user data.

[1156] 1. The user grants the app permission to access their calendar and GPS information, allowing the app to obtain the user's schedule and location information.

[1157] 2. The device (user's smartphone or tablet) periodically collects calendar and location information and sends this data to a central processing server.

[1158] 3. Based on the received schedule information and location information, the server analyzes the user's behavioral patterns using a generative model and evaluates the risk of loss.

[1159] 4. The server selects the most suitable insurance plan based on the evaluation results and automatically applies it to the user.

[1160] 5. Provide an interface that allows users to consult and set insurance settings in advance, and adjust the insurance content based on the user's responses.

[1161] Program processing

[1162] The operation of the system is explained in natural language below.

[1163] Obtaining user schedule and location information

[1164] 1. The user initiates the system by granting the app permission to access the calendar and location services.

[1165] 2. The device acquires the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history) and periodically sends them to the server.

[1166] Loss risk assessment

[1167] 3. The server uses a generative model to analyze the user's behavioral patterns based on the received schedule information and location information.

[1168] 4. The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[1169] Insurance plan selection and application

[1170] 5. The server selects the most suitable insurance plan based on the assessed risk score.

[1171] 6. The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[1172] Insurance adjustment

[1173] 7. The user reviews their insurance details within the app and adjusts their coverage and settings as needed. Adjusted settings are sent to the server in real time.

[1174] Real-time assistance and suggestions

[1175] 8. The server uses the generative model to notify the user when the risk of loss increases or when certain conditions are met, and provides appropriate suggestions and support.

[1176] Specific examples

[1177] Example 1: If you have many regular business trips

[1178] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[1179] 2. The device sends calendar information and GPS data to the server.

[1180] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling."

[1181] 4. The server automatically adds "Travel Insurance" and notifies the user.

[1182] 5. The user reviews their insurance and adjusts coverage as needed.

[1183] Example 2: When there are many sudden actions

[1184] 1. The user suddenly goes on a weekend trip.

[1185] 2. The device sends real-time GPS data to the server.

[1186] 3. The server uses the generative model to determine that there is a high risk of loss during travel.

[1187] 4. The server temporarily applies "travel insurance" and notifies the user.

[1188] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1189] In this way, users can easily access the most suitable insurance and prepare for the risk of loss.

[1190] The processing flow will be explained below.

[1191] Understood. Below is a step-by-step explanation of the specific flow of the programming process for the "Anytime Insurance" system.

[1192] Program processing

[1193] Obtaining user schedule and location information

[1194] Step 1:

[1195] The user grants the app permission to access the calendar app and location services.

[1196] Specific behavior: On the initial setup screen for the app, select the options to allow access to your calendar and use your GPS location.

[1197] Step 2:

[1198] The device periodically collects calendar information and GPS data and sends it to the app.

[1199] Specific behavior: The app periodically retrieves the user's calendar information (e.g., scheduled dates and times, locations) and GPS data (e.g., current location, movement history) in the background.

[1200] Specific operation: The acquired data is stored in local storage and sent to the cloud server at regular intervals.

[1201] Loss risk assessment

[1202] Step 3:

[1203] The server receives the calendar information and GPS data sent from the device and stores them in a database.

[1204] Specific actions: Accurately store received data in a database and format the data for analysis.

[1205] Step 4:

[1206] The server uses a generative model to analyze the user's behavioral patterns based on the stored schedule information and location information, and assesses the risk of loss.

[1207] How it works: The generative model runs on the server and uses calendar information and GPS data as input to identify user behavior patterns and calculate a loss risk score.

[1208] Insurance plan selection and application

[1209] Step 5:

[1210] The server selects the most suitable insurance plan based on the assessed risk score.

[1211] Specific Action: Select the appropriate plan from a pre-configured list of insurance plans based on risk score.

[1212] Step 6:

[1213] The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[1214] What it does: Automatically applies the insurance to the user's account and notifies the user via push notification or email.

[1215] Insurance adjustment

[1216] Step 7:

[1217] Users can review their insurance details within the app and adjust coverage and settings as needed.

[1218] Specific actions: Access the app's insurance settings screen, review the displayed insurance details, and make any necessary adjustments (e.g., change the insurance amount, set the coverage).

[1219] Step 8:

[1220] The device sends the user's settings to the server and updates them.

[1221] Specific operation: The adjusted setting information is sent to the server in real time, and the user's insurance information is updated on the server side.

[1222] Real-time assistance and suggestions

[1223] Step 9:

[1224] The server uses the generative model to send notifications to the user when there is an increased risk of loss or when certain conditions are met.

[1225] What it does: It monitors GPS data and behavioral patterns in real time, and triggers a push notification if the generative model detects an increased risk.

[1226] Step 10:

[1227] Users receive real-time notifications and can view and respond within the app.

[1228] What to do: Tap the notification in the app for more details and to take additional insurance adjustments or actions as needed.

[1229] In this way, users can easily use appropriate loss insurance and prepare for the risk of loss.

[1230] Example 1

[1231] 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."

[1232] The current insurance system requires users to select and change their insurance plans, which makes it difficult to achieve optimal risk management. Furthermore, many users find it difficult to properly assess their risk of loss, resulting in insufficient insurance coverage. Furthermore, in situations where the risk of loss fluctuates in real time, appropriate insurance proposals and support are often not provided.

[1233] 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.

[1234] In this invention, the server includes a means for analyzing a user's behavioral pattern, a means for calculating a risk score, and a means for selecting and applying an appropriate insurance plan, thereby making it possible to evaluate the risk of loss in real time based on the user's behavioral data and automatically apply the most appropriate insurance plan.

[1235] "Means for obtaining user schedule information" refers to a function for obtaining data regarding scheduled dates, times, and locations from the calendar app or schedule management app used by the user.

[1236] "Means of obtaining user location information" refers to a function that uses the user's location information service or GPS function to obtain the user's current location and movement history.

[1237] The "means for transmitting acquired schedule information and location information to a server" is a function that transmits schedule information and location information periodically collected by a user's terminal to a central processing server via data communication.

[1238] "Means for analyzing user behavior patterns using generative AI models" refers to a function that uses machine learning algorithms and artificial intelligence based on collected data to analyze and reveal user behavior patterns.

[1239] "Means for assessing the risk of loss based on behavioral patterns and calculating a risk score" refers to a function that assesses the risk of loss using statistical analysis and risk models based on user behavioral data and calculates that risk as a numerical score.

[1240] "Means for selecting the most suitable insurance plan based on risk score" is a function for selecting the most suitable insurance plan from a database based on the calculated risk score and applying it to the user.

[1241] "Means for automatically applying the selected insurance plan to the user" is a function for automatically applying the selected insurance plan to the user's account and notifying the user of the application results.

[1242] "Means for users to consult and set up their insurance settings in advance" refers to interfaces and functions that allow users to consult about insurance details in advance and set up insurance according to their individual needs.

[1243] "Means for adjusting the contents of the insurance plan based on the user's setting information" is a function for automatically adjusting the contents of the insurance plan based on the information set in advance by the user and applying it to the user.

[1244] "Means for sending a notification to the user in real time when the risk of loss increases" is a function for sending a notification to the user in real time when the risk of loss exceeds a certain threshold.

[1245] "Means for providing appropriate suggestions and support to users" refers to a function for providing appropriate suggestions and support to users to reduce the risk of loss.

[1246] MODE FOR CARRYING OUT THE INVENTION

[1247] A specific embodiment of the present invention will be described in detail. This invention is a system that provides insurance services to enable users to appropriately manage the risk of loss. The system aims to evaluate the risk of loss based on the user's schedule information and location information, and automatically select and apply the optimal insurance plan.

[1248] System configuration

[1249] The system consists of the following major components:

[1250] 1. User's Device

[1251] Devices users carry around with them, such as smartphones and tablets

[1252] Includes a calendar app and location services

[1253] The app collects the user's calendar information and GPS data and sends it to a server

[1254] 2. Central Processing Server

[1255] A server with high-performance computing power

[1256] Analyze user behavior patterns using generative AI models to assess risk of loss

[1257] Select the best insurance plan and automatically apply it to the user

[1258] 3. Cloud-based databases

[1259] A database for storing and processing user schedule information, location information, and insurance setting information

[1260] High security and scalability

[1261] Program processing

[1262] The operation of the system is explained in natural language below.

[1263] Obtaining user schedule and location information

[1264] 1. The user grants the app permission to access the Calendar app and Location Services.

[1265] 2. The device obtains the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history).

[1266] 3. The device periodically sends the acquired data to the server.

[1267] Loss risk assessment

[1268] 4. The server analyzes the user's behavioral patterns using a generative AI model based on the received schedule and location information.

[1269] 5. The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[1270] Insurance plan selection and application

[1271] 6. The server selects the most suitable insurance plan based on the assessed risk score.

[1272] 7. The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[1273] Insurance adjustment

[1274] 8. The user reviews their insurance within the app and adjusts their coverage and settings as needed.

[1275] 9. The server receives the adjusted settings and updates the insurance plan.

[1276] Real-time assistance and suggestions

[1277] 10. The server uses generative AI models to notify users when there is an increased risk of loss or when certain conditions are met, and provide appropriate suggestions and support.

[1278] Specific examples

[1279] Example 1: If you have many regular business trips

[1280] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[1281] 2. The device sends calendar information and GPS data to the server.

[1282] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling."

[1283] 4. The server automatically adds "Travel Insurance" and notifies the user.

[1284] 5. The user reviews their insurance and adjusts coverage as needed.

[1285] Example 2: When there are many sudden actions

[1286] 1. The user suddenly goes on a weekend trip.

[1287] 2. The device sends real-time GPS data to the server.

[1288] 3. The server uses the generative model to determine that there is a high risk of loss during travel.

[1289] 4. The server temporarily applies "travel insurance" and notifies the user.

[1290] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1291] In this way, users can easily access the most suitable insurance and prepare for the risk of loss.

[1292] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1293] Step 1:

[1294] The user grants the app permission to access the Calendar app and Location Services.

[1295] Specific operation: The user sets the app's permissions from the smartphone settings screen and allows access to calendar information and location information.

[1296] Input: User sets permissions.

[1297] Output: The permission information that has been set.

[1298] Step 2:

[1299] The device obtains the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history).

[1300] Specific operation: Uses the smartphone's antenna and Wi-Fi to obtain real-time location information and loads schedule information through the calendar API.

[1301] Input: Calendar and location with permissions set.

[1302] Output: Retrieved calendar information and GPS data.

[1303] Step 3:

[1304] The data acquired by the terminal is periodically sent to the server.

[1305] Specific operation: At regular intervals (for example, every minute), a background process on the device is started, which encrypts the acquired data packets and sends them to the server using the HTTPS protocol.

[1306] Input: Captured calendar information and GPS data.

[1307] Output: Data packet sent to the server.

[1308] Step 4:

[1309] The server uses a generative AI model to analyze the user's behavioral patterns based on the received schedule information and location information.

[1310] Specific operation: The server calls a generative AI model such as a cloud AI service and performs analysis using the user's data stream as input.

[1311] Input: Schedule and location information sent to the server.

[1312] Output: Analyzed behavioral patterns.

[1313] Step 5:

[1314] The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[1315] What it does: It uses pattern recognition technology to evaluate certain behavioral trends and outliers, then uses statistical models to calculate a risk score.

[1316] Input: Analyzed behavioral patterns.

[1317] Output: The calculated risk score.

[1318] Step 6:

[1319] The server selects the most suitable insurance plan based on the assessed risk score.

[1320] Specific operation: Search and select the insurance plan that best suits the risk profile from the database in the server. For example, use SQL to retrieve the insurance plan that corresponds to the risk score.

[1321] Input: Risk score.

[1322] Output: The selected insurance plan.

[1323] Step 7:

[1324] The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[1325] What it does: Sends a notification to the user's app via a REST API, displaying details of the insurance plan applied.

[1326] Input: Selected insurance plan.

[1327] Output: Notification to user terminal.

[1328] Step 8:

[1329] Users can review their insurance details within the app and adjust coverage and settings as needed.

[1330] What it does: The app UI displays insurance information and allows users to change settings using a form, with changes sent to the server in real time.

[1331] Input: Insurance plan details.

[1332] Output: Adjusted insurance settings.

[1333] Step 9:

[1334] The server receives the adjusted settings and updates the insurance plan.

[1335] Specific operation: Analyzes the received data and updates the insurance configuration database on the server. For example, it updates the configuration data using a NoSQL database (such as MongoDB).

[1336] Input: Adjusted insurance settings.

[1337] Output: Updated insurance plan.

[1338] Step 10:

[1339] The server uses a generative AI model to notify users when there is an increased risk of loss or when certain conditions are met, and provide appropriate suggestions and support.

[1340] Specific operation: Monitors real-time data and issues push notifications when conditions are met. Notifications are sent to users' devices using cloud messaging services, etc.

[1341] Input: Real-time loss risk assessment.

[1342] Output: Push notification and suggestion.

[1343] (Application example 1)

[1344] 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."

[1345] When managing the risk of loss for customers and employees in physical stores, conventional methods have made it difficult to perform detailed risk assessments and apply optimal insurance plans. Furthermore, automatic application of insurance based on real-time risk fluctuations and user behavior has not been sufficiently implemented. This has led to the issue of not being able to provide appropriate support in situations where the risk of loss is high.

[1346] 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.

[1347] In this invention, the server includes: means for acquiring a user's schedule information; means for acquiring the user's location information; means for assessing the risk of loss based on the acquired schedule information and location information; means for selecting an optimal insurance plan based on the assessment results; means for automatically applying the selected insurance plan to the user; means for periodically updating the user's location information and reassessing the risk of loss; means for applying and updating the insurance plan based on the reassessment results; means for consulting and setting the user's insurance settings in advance; means for adjusting the contents of the insurance plan based on the user's setting information; means for notifying the user of the insurance application results; means for sending a notification to the user in real time when the risk of loss increases; means for providing appropriate suggestions and support to the user; and means for providing an interface for manual adjustment based on the reassessment results. This enables the risk of loss for customers and employees in physical stores to be managed through detailed assessments and the application of optimal insurance plans. It can also respond to risk fluctuations in real time and automatically apply insurance and support based on user behavior.

[1348] "Means for obtaining user schedule information" refers to a function for obtaining information entered by the user into a calendar app or schedule management application.

[1349] "Means of obtaining user location information" refers to a function for obtaining location information from a user's device, such as a smartphone or tablet, through GPS or location information services.

[1350] "Means for assessing the risk of loss based on acquired schedule information and location information" is a function for calculating the possibility of loss and assessing the risk based on the user's calendar information and location information.

[1351] The "means for selecting the most suitable insurance plan based on the evaluation results" is a function for selecting the most suitable insurance plan for the user based on the evaluation of the risk of loss.

[1352] The "means for automatically applying the selected insurance plan to the user" is a function that enables the system to automatically apply the selected insurance plan to the user.

[1353] "Means for periodically updating the user's location information and reassessing the risk of loss" is a function for periodically obtaining the user's current location and reassessing the risk based on that information.

[1354] "Means to apply and update insurance plans based on reassessment results" refers to the functionality for reviewing and updating existing insurance plans based on new risk assessment results.

[1355] "Means for consulting and setting up the user's insurance settings in advance" is a function that allows the user to consult with the user in advance about the details and settings of the insurance and set up the insurance settings that the user desires.

[1356] "Means for adjusting the contents of the insurance plan based on the user's setting information" refers to a function for changing and adjusting the contents of the insurance plan based on the information set in advance by the user.

[1357] "Means for notifying users of insurance coverage results" is a function for informing users that the selected insurance plan has been applied.

[1358] "Means for sending notifications to users in real time when the risk of loss increases" is a function for immediately sending warnings and notifications to users when the risk of loss increases.

[1359] "Means of making appropriate suggestions and support to users" refers to a function that provides specific advice and support to avoid risks when it is determined that there is a high risk of loss.

[1360] "Means for providing an interface that allows manual adjustments based on the results of reassessment" refers to a function for providing an interface that allows a user to manually adjust insurance coverage based on the updated results of risk assessment.

[1361] An embodiment of the present invention will now be described in detail. This system evaluates the risk of loss based on the user's schedule information and location information, and selects and applies an appropriate insurance plan. A detailed description of the system is provided below.

[1362] System configuration

[1363] The system mainly consists of a user terminal, a central processing server, and a cloud-based database. Users are expected to use smartphones and tablets.

[1364] Hardware and software used

[1365] Hardware: Smartphones, tablets

[1366] Software: Python 3.9, geopy library, requests library

[1367] Data processing and calculation

[1368] Obtaining user schedule and location information

[1369] The system is activated when a user grants the app permission to access the calendar app and location services. The user's device obtains calendar information (scheduled dates and times, locations) and GPS data (current location, movement history), and periodically sends this data to a central processing server.

[1370] Example prompt: "Do you consent to collecting your calendar and location information?"

[1371] Loss risk assessment

[1372] The server uses the generated AI model to analyze the user's behavioral patterns based on the acquired schedule and location information. During this process, the server calculates the distance between the user's current location and the scheduled location, and calculates a risk score based on the result. For example, if the current location is very close to the scheduled location, the risk score will be high.

[1373] Selecting an insurance plan

[1374] The server selects the most suitable insurance plan based on the assessed risk score, which is then automatically applied to the user's account.

[1375] Insurance coverage based on risk scores

[1376] The server periodically updates the user's location and reassess the risk of loss based on that information. Based on the risk assessment, the insurance plan in place is adjusted and, if necessary, a new insurance plan is installed.

[1377] Specific examples

[1378] Example 1: If you have many regular business trips

[1379] 1. A user enters "Business Trip" into their calendar and enters "City A" as the destination.

[1380] 2. The user's device sends calendar information and GPS data to the server.

[1381] 3. Based on this information, the server generates an AI model that assesses that "the risk of loss increases when traveling."

[1382] 4. The server automatically adds "Travel Insurance" and notifies the user.

[1383] 5. The user reviews their insurance and adjusts coverage as needed.

[1384] Example 2: When there are many sudden actions

[1385] 1. The user suddenly goes on a weekend trip.

[1386] 2. The user's device sends real-time GPS data to the server.

[1387] 3. The server uses the generated AI model to determine that there is a high risk of loss during travel.

[1388] 4. The server temporarily applies "travel insurance" and notifies the user.

[1389] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1390] In this way, users can easily use the most suitable insurance and prepare for the risk of loss. Real-time risk assessment and automatic insurance application will more effectively protect users' safety.

[1391] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1392] Step 1:

[1393] The system starts when the user grants the app permission to access the calendar app and location services.

[1394] Input: User permission information

[1395] What happens: The user confirms the permissions based on the prompt and presses the accept button.

[1396] Output: The app gets access to the user's schedule and location.

[1397] Step 2:

[1398] The device acquires the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history), and periodically transmits this data to a central processing server.

[1399] Input: Calendar information, GPS data

[1400] How it works: Your device periodically retrieves data from the Calendar app and Location Services and sends it to the server.

[1401] Output: Calendar information and GPS data are sent to the server.

[1402] Step 3:

[1403] The server uses a generative AI model to analyze the user's behavioral patterns based on the received schedule and location information.

[1404] Input: Calendar information, GPS data

[1405] How it works: The server inputs schedule and location information into a generative AI model that analyzes behavioral patterns.

[1406] Output: User behavior pattern data

[1407] Step 4:

[1408] The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[1409] Input: User behavior pattern data

[1410] How it works: The server calculates a risk score based on the analysis results, taking into account factors such as the distance between locations and the length of time spent there.

[1411] Output: Risk score

[1412] Step 5:

[1413] The server selects the most appropriate insurance plan based on the evaluation results and automatically applies it to the user.

[1414] Input: Risk Score

[1415] How it works: The server selects the most appropriate plan from pre-set insurance plans (low, medium, high) based on the risk score and automatically applies it.

[1416] Output: Insurance plan information applied

[1417] Step 6:

[1418] The server periodically updates the user's location and reassess the risk of loss.

[1419] Input: Latest GPS data

[1420] How it works: The server periodically retrieves the latest location information and performs risk assessment again.

[1421] Output: Updated risk score

[1422] Step 7:

[1423] The server applies and updates the insurance plan based on the reassessment results.

[1424] Input: Updated Risk Score

[1425] How it works: The server updates the insurance plan as needed based on the new risk score.

[1426] Output: Updated insurance plan information

[1427] Step 8:

[1428] Users can check their insurance coverage results within the app and adjust their insurance coverage as needed.

[1429] Input: Insurance plan information

[1430] How it works: A user opens the app, sees their insurance plan, and makes adjustments through the interface.

[1431] Output: Adjusted insurance plan settings

[1432] 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.

[1433] MODE FOR CARRYING OUT THE INVENTION

[1434] A specific embodiment of the present invention will be described. The present invention includes a system that allows users to appropriately manage their risk of loss and provides insurance plans according to that risk, and by combining it with an emotion engine, it further improves accuracy and provides insurance services according to the user's emotional state.

[1435] System Overview

[1436] The system consists of a user device, a central processing server, and a cloud-based database for storing and processing user data. It also incorporates an emotion engine to identify the user's emotional state and use that information to assess loss risk and select insurance plans.

[1437] 1. The user grants the app permission to access the calendar app, GPS information, and emotion recognition, allowing the app to obtain the user's schedule information, location information, and emotional state.

[1438] 2. The device periodically collects calendar information, GPS data, and emotional state data and transmits this data to a central processing server.

[1439] 3. Based on the received data, the server uses a generative model to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[1440] 4. The server selects the optimal insurance plan based on the evaluation results and automatically applies the customized plan to the user, taking into account their emotional state.

[1441] 5. Provide an interface that allows users to consult and set insurance settings in advance, and adjust the insurance content based on the user's settings information.

[1442] Program processing

[1443] The operation of the system is explained in natural language below.

[1444] Obtaining user schedule information, location information, and emotional state

[1445] 1. The user initiates the system by granting the app permission to access the calendar app, location services, and emotion recognition features.

[1446] 2. The device periodically collects calendar information (scheduled date and time, location), GPS data (current location, movement history), and emotional state data using the camera and microphone, and sends this data to the server.

[1447] Assessment of loss risk and emotional state

[1448] 3. The server receives the calendar information, GPS data, and emotional state data sent from the device and stores them in a database.

[1449] 4. The server uses a generative model to analyze the user's behavioral patterns and emotional state based on the stored schedule information, location information, and emotional state data, and evaluates the risk of loss.

[1450] Insurance plan selection and application

[1451] 5. The server selects the best insurance plan based on the assessed risk score and emotional state.

[1452] 6. The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[1453] Insurance adjustment

[1454] 7. The user checks the insurance details within the app and adjusts the coverage and settings to take into account their emotional state as needed. The adjusted settings are sent to the server in real time.

[1455] Real-time assistance and suggestions

[1456] 8. When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions or support.

[1457] Specific examples

[1458] Example 1: If you have many regular business trips

[1459] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[1460] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[1461] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling." If the user's emotional state indicates stress, the server sets a higher risk score.

[1462] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[1463] 5. The user reviews their insurance and adjusts coverage as needed.

[1464] Example 2: When there are many sudden actions

[1465] 1. The user suddenly goes on a weekend trip.

[1466] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[1467] 3. The server uses the generative model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[1468] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[1469] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1470] In this way, users can easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[1471] The processing flow will be explained below.

[1472] Understood. Below is a step-by-step explanation of the specific flow of the programming process for the "Anytime Insurance" system.

[1473] Program processing

[1474] Obtaining user schedule information, location information, and emotional state

[1475] Step 1:

[1476] The user grants the app permission to access the calendar app, location services, and emotion recognition features.

[1477] What it does: On the initial setup screen for the app, select the options to allow access to your calendar, GPS location, and emotion recognition features on your camera and microphone.

[1478] Step 2:

[1479] The device periodically collects calendar information, GPS data, and emotional state data and stores it within the app.

[1480] What it does: The app periodically runs in the background and collects the user's calendar information (e.g., scheduled dates and times, locations), GPS data (e.g., current location, movement history), and emotion recognition data (e.g., facial expressions captured by the camera, voice tones collected by the microphone).

[1481] Step 3:

[1482] The device transmits the collected calendar information, GPS data, and emotional state data to a server.

[1483] Specific operation: Generates packets containing various acquired data and sends them securely to the server using the HTTPS protocol.

[1484] Assessment of loss risk and emotional state

[1485] Step 4:

[1486] The server receives the calendar information, GPS data, and emotional state data sent from the terminal and stores them in a database.

[1487] What it does: Stores the received data in a database for analysis and links it to the registered user profile.

[1488] Step 5:

[1489] The server uses a generative model based on the stored schedule information, location information, and emotional state data to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[1490] How it works: The generative model inputs schedule data, location data, and emotion recognition data to identify the user's behavioral patterns, analyze the correlation with their emotional state, and calculate a loss risk score.

[1491] Specific Actions: If emotional state indicates stress or agitation, increase risk score.

[1492] Insurance plan selection and application

[1493] Step 6:

[1494] The server selects the most suitable insurance plan based on the assessed risk score and emotional state.

[1495] What it does: From a list of pre-defined insurance plans, select the plan that best matches your risk score and emotional state, and then configure its details.

[1496] Step 7:

[1497] The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[1498] Specific operation: The insurance plan details (e.g., insurance period, coverage, compensation amount) are reflected in the user's account and the user is notified via push notification or email.

[1499] Insurance adjustment

[1500] Step 8:

[1501] Users can review their insurance details within the app and adjust coverage and settings as needed, taking their emotional state into account.

[1502] What it does: Displays insurance details in the in-app insurance settings screen, allowing the user to review the options presented and adjust insurance coverage and compensation.

[1503] Step 9:

[1504] The device sends the user's settings to the server and updates them.

[1505] Specific operation: The updated settings are sent to the server using the HTTPS protocol, and the user's insurance information is updated on the server side in real time.

[1506] Real-time assistance and suggestions

[1507] Step 10:

[1508] The server uses a generative model to send notifications that take into account the user's emotional state when there is an increased risk of loss or when certain conditions are met.

[1509] What it does: It monitors GPS data, behavioral patterns, and emotional state in real time, and sends push notifications when the generative model detects increased risk.

[1510] Step 11:

[1511] Users receive real-time notifications and can view and respond within the app.

[1512] Action: Tap the app notification to learn more and take additional action or adjust your behavior as needed.

[1513] Specific examples

[1514] Example 1: If you have many regular business trips

[1515] 1. A user enters "Business Trip" into their calendar and enters "City A" as the destination.

[1516] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[1517] 3. Based on this information, the server generates a generative model that evaluates that the risk of loss increases when traveling. If the user's emotional state indicates stress, the server increases the risk score.

[1518] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[1519] 5. The user reviews the insurance and adjusts the coverage as needed.

[1520] Example 2: When there are many sudden actions

[1521] 1. The user suddenly goes on a weekend trip.

[1522] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[1523] 3. The server uses the generative model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[1524] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[1525] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1526] In this way, users can easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[1527] Example 2

[1528] 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."

[1529] Conventional insurance services have difficulty in properly assessing the degree of risk of loss for users. Furthermore, because insurance plans are applied uniformly without considering the user's emotional state, it is not possible to provide optimal insurance products for users. Therefore, there is a need for a highly accurate insurance service that takes into account the user's behavioral patterns and emotional state.

[1530] 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.

[1531] In this invention, the server includes means for acquiring user schedule information, means for acquiring user location information, means for acquiring the user's emotional state, means for assessing the risk of loss based on the acquired schedule information, location information, and emotional state data, means for selecting an optimal insurance plan based on the assessment result and the emotional state, and means for automatically applying the selected insurance plan to the user. This makes it possible to provide a more accurate assessment of the risk of loss and an insurance plan based on the user's behavioral patterns and emotional state.

[1532] "Schedule information" refers to information about appointments and events that a user has entered into a calendar or app.

[1533] "Location information" refers to GPS data that indicates the user's current location and movement history.

[1534] "Emotional state" is data that captures the user's emotions through a camera or microphone.

[1535] "Loss risk" is the likelihood of losing an item or information, assessed based on the user's behavioral patterns and emotional state.

[1536] "Insurance Plan" means a customized insurance product offered based on the results of a User's risk assessment.

[1537] "Means for acquiring" refers to a method or device for collecting a user's schedule information, location information, or emotional state.

[1538] The "means for evaluating" refers to a method or device for analyzing collected data and evaluating the risk of loss.

[1539] A "means for selecting" is a method or device for selecting the most suitable insurance plan based on the evaluation results and emotional state.

[1540] The "applying means" is a method or device for automatically providing the selected insurance plan to the user.

[1541] A "means for sending notifications" is a method or device for sending information to a user in real time.

[1542] "Means for providing appropriate suggestions and support" are methods and devices for providing optimal actions and support to users.

[1543] MODE FOR CARRYING OUT THE INVENTION

[1544] A specific embodiment of this invention will be described. The present invention is a system that allows users to appropriately manage their loss risk and provides insurance plans tailored to that risk. The system's accuracy is further enhanced by incorporating an emotion engine. Its unique feature is that it provides insurance services tailored to the user's emotional state. This system is comprised of a user's terminal, a central processing server, and a cloud-based database.

[1545] System configuration

[1546] 1. The user grants the app permission to access the calendar app, location services, and emotion recognition, allowing the app to obtain the user's schedule information, location information, and emotional state.

[1547] 2. The device periodically collects calendar information (scheduled dates and times, locations), GPS data (current location, movement history), and emotional state data using the camera and microphone, and sends this data to a central processing server using emotion recognition technologies such as the Face API in Microsoft's Azure Cognitive Services.

[1548] 3. The server uses a generative model based on the received data to analyze the user's behavioral patterns and emotional state and assess the risk of loss. The generative AI model uses Google Cloud's AI Platform.

[1549] 4. The server selects the optimal insurance plan based on the evaluation results and the user's emotional state, and automatically applies the selected insurance plan to the user. For example, if a user travels frequently and is feeling stressed, the server applies "business trip insurance."

[1550] 5. The interface for users to consult and set insurance preferences in advance is always available, and the insurance contents are adjusted based on the user's preferences. The adjusted preferences are sent to the server in real time.

[1551] 6. When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions or support.

[1552] Specific examples

[1553] Example 1: If you have many regular business trips

[1554] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[1555] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[1556] 3. Based on this information, the server uses the generative AI model to evaluate that "the risk of loss increases when traveling." If the user's emotional state indicates stress, the server sets a higher risk score.

[1557] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[1558] 5. The user reviews their insurance and adjusts coverage as needed.

[1559] Example 2: When there are many sudden actions

[1560] 1. The user suddenly goes on a weekend trip.

[1561] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[1562] 3. The server uses the generated AI model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[1563] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[1564] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1565] Prompt Sentence Examples

[1566] An example of a prompt sentence would be:

[1567] "A user has entered a business trip into their calendar. The destination is City A, and the user's emotional state is high. Describe a process for applying travel insurance based on this information and sending notifications that take the user's emotional state into account."

[1568] "A user has an impromptu trip over the weekend. Their current emotional state is excitement. Based on this information, explain the process for applying travel insurance and sending alerts tailored to their emotional state."

[1569] In this way, a system is constructed that allows users to easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[1570] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1571] Program processing flow

[1572] Step 1:

[1573] The user grants permission to access the Calendar app, location services, and emotion recognition features.

[1574] Input: The user grants the app permission to access the calendar app, location services, and emotion recognition features.

[1575] Specific behavior: The user turns on the required permissions in the settings screen.

[1576] Output: Authorization is given for the system to retrieve these data.

[1577] Step 2:

[1578] The device periodically collects calendar information, GPS data, and emotional state data and sends them to a server.

[1579] Input: User's calendar information, current location, movement history, emotional state via camera and microphone.

[1580] How it works: The device periodically reads calendar information and GPS data, and uses the camera and microphone to recognize emotions, for example, using the Face API from Microsoft's Azure Cognitive Services.

[1581] Output: Collected calendar information, GPS data, and emotional state data are sent to a server.

[1582] Step 3:

[1583] The server receives the calendar information, GPS data, and emotional state data sent from the device and stores them in a database.

[1584] Input: Calendar information, GPS data, and emotional state data sent from the device.

[1585] Specific operation: The server stores the received data in a secure cloud database.

[1586] Output: A database of behavioral patterns and emotional states for each user.

[1587] Step 4:

[1588] The server uses a generative AI model based on the stored data to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[1589] Input: Calendar information, GPS data, and emotional state data stored in a database.

[1590] How it works: The server runs a generative model using Google Cloud's AI Platform to analyze this data, extracting features from behavioral patterns and assessing stress levels based on emotional states.

[1591] Output: Generates an assessment of the risk of loss based on the user's behavioral patterns and emotional state.

[1592] Step 5:

[1593] The server selects the most suitable insurance plan based on the evaluation results and emotional state and automatically applies it to the user.

[1594] Input: Loss risk assessment results, emotional state assessment results.

[1595] Specific operation: The server selects an insurance plan based on the risk assessment score and emotional state. In this process, for example, "business trip insurance" or "travel insurance" is selected.

[1596] Output: Selected insurance plan is applied and user is notified.

[1597] Step 6:

[1598] Users can view notifications within the app, review their insurance coverage, and adjust coverage as needed.

[1599] Input: Applied insurance plan, notification message.

[1600] What happens: The user receives a notification, views details in the app, and adjusts the coverage and content of their insurance plan as needed.

[1601] Output: The customized insurance information is reflected in the system.

[1602] Step 7:

[1603] When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions and support.

[1604] Input: Real-time risk of loss, user emotional state.

[1605] How it works: The server continuously monitors data and generates notifications and alerts based on the analysis results of the generative AI model.

[1606] Output: Real-time notifications and suggestions to the user.

[1607] (Application example 2)

[1608] 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."

[1609] In modern society, users are at increased risk of losing their belongings, and this risk often fluctuates depending on the user's emotional state and behavioral patterns. However, traditional insurance systems have struggled to propose optimal insurance plans that take into account individual emotional states and behavioral patterns. Furthermore, they lacked the means to flexibly respond to users' changing risks in real time, making it difficult for users to receive appropriate protection.

[1610] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1611] In this invention, the server includes means for acquiring user schedule information, means for acquiring user location information, means for acquiring the user's emotional state, means for assessing the risk of loss based on the acquired schedule information, location information, and emotional state, means for selecting an optimal insurance plan based on the assessment results, means for automatically applying the selected insurance plan to the user, means for sending a warning notice when the risk of loss increases, and means for suggesting appropriate security measures to the user. This makes it possible to provide more accurate risk assessments and insurance plans based on the individual emotional state and behavioral patterns of the user.

[1612] "User schedule information" refers to information about appointments and events managed by the electronic device used by the user.

[1613] "User location information" refers to information about a user's current location and movement history obtained through GPS or other positioning systems.

[1614] "User's emotional state" is information that indicates the user's emotional and psychological state, which is analyzed using sensors such as a camera and a microphone.

[1615] A "means for assessing risk of loss" is a system or algorithm that analyzes and assesses the likelihood of an item being lost based on the acquired schedule information, location information, and emotional state.

[1616] The "means for selecting the optimal insurance plan" refers to a system or algorithm that determines the appropriate insurance plan for the user based on the results of an assessment of the risk of loss.

[1617] An "automated user insurance plan application" is a system or process that provides a selected insurance plan to a user without manual intervention.

[1618] "Warning notification mechanism" means a system or protocol that sends real-time warnings or alerts to a user's device in response to an increased risk.

[1619] A "means for suggesting security measures" is a system or algorithm that provides users with specific preventative measures or suggested actions to reduce the risk of loss or theft.

[1620] MODE FOR CARRYING OUT THE INVENTION

[1621] This invention is a system that uses a user's emotional state and location information to assess the risk of loss and provide an appropriate insurance plan. Specific embodiments for realizing this system are described below.

[1622] System Configuration

[1623] 1. User's device

[1624] These are mobile devices used by users, such as smartphones and tablets.

[1625] It is equipped with a camera and microphone to capture the user's emotional state.

[1626] It has a GPS function and can obtain the user's location information.

[1627] Use a calendar application to manage your schedule.

[1628] 2. Central Processing Server

[1629] It is equipped with an emotion engine, a data analysis module, and a generative AI model.

[1630] As emotion engines, we use, for example, Affectiva and Microsoft Azure Cognitive Services.

[1631] As a data analysis module, we use cloud-based data storage and analysis infrastructure (e.g., Amazon AWS and Google Cloud Platform).

[1632] Hugging Face Transformers and Google TensorFlow are used as generative AI models.

[1633] 3. Cloud Storage

[1634] Stores and manages user schedule information, location information, and emotional state data.

[1635] The data is sent to the server in real time and the analysis results are returned.

[1636] System Operation

[1637] 1. Data Collection

[1638] A user enters an event into a calendar application and grants access to GPS and emotion recognition features.

[1639] The device periodically collects calendar information, GPS data, and emotional state data from the camera and microphone and sends it to a central processing server.

[1640] 2. Data Analysis

[1641] The server stores the received calendar information, location information, and emotional state data in cloud storage.

[1642] The server uses an emotion engine to analyze the emotional state data and identify the user's psychological state.

[1643] The server uses the generated AI model to analyze user behavior patterns and assess the risk of loss.

[1644] 3. Insurance plan selection and application

[1645] The server selects the most suitable insurance plan based on the assessed risk score and emotional state.

[1646] The selected insurance plan will be automatically applied to the user and a notification will be sent via the app.

[1647] Specific examples

[1648] Example 1: When walking alone at night

[1649] 1. If a user goes out alone at night, enter that information into the calendar.

[1650] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[1651] 3. The server uses an emotion engine to detect when a user is alone at night and exhibits an anxious emotional state.

[1652] 4. The server-generated AI model assesses that there is a high risk of loss due to "going out alone at night."

[1653] 5. The server selects the best insurance plan and notifies the user that they are at high risk.

[1654] 6. The user checks the notification in the app and adjusts their insurance as needed.

[1655] Example prompts for generative AI models

[1656] When the user's emotional state is "unstable" and their location is in a "high crime area," the risk assessment score is set high and a warning is sent to the user saying, "Going out alone late at night is risky. Please choose a safe route."

[1657] As described above, users can receive security assistance based on their emotional state and take safety into consideration.

[1658] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1659] Program processing steps

[1660] Step 1:

[1661] A user enters an event into a calendar app and grants access to GPS and emotion recognition, allowing the device to obtain the user's schedule information, location, and emotional state.

[1662] Input: User's calendar information, GPS information, emotion recognition permission information

[1663] Output: Permission to access user schedule, location, and emotion recognition data

[1664] Step 2:

[1665] The device periodically collects calendar information, GPS data, and emotional state data captured from the camera and microphone, and transmits this data to a central processing server.

[1666] Input: Calendar information, GPS data, emotional state data

[1667] Output: Send collected data to the server

[1668] Step 3:

[1669] The server stores the received calendar information, location information, and emotional state data in cloud storage for later analysis.

[1670] Input: Calendar information, GPS data, and emotional state data sent from the device

[1671] Output: User data stored in cloud storage

[1672] Step 4:

[1673] The server analyzes the emotional state data using an emotion engine to identify the user's psychological state, for example, using Affectiva or Microsoft Azure Cognitive Services to convert the emotion data into an emotion score.

[1674] Input: Emotional state data stored in cloud storage

[1675] Output: Emotion score (analysis result of psychological state)

[1676] Step 5:

[1677] The server analyzes the stored behavioral pattern data using a generative AI model, such as Hugging Face Transformers or Google TensorFlow, to assess the risk of loss based on the user's behavioral patterns and current emotional state.

[1678] Input: Calendar information, location information, sentiment score

[1679] Output: Loss risk assessment score

[1680] Step 6:

[1681] The server selects the optimal insurance plan based on the assessed risk score and emotional state, thereby determining the best insurance plan for the user.

[1682] Input: Loss risk assessment score, sentiment score

[1683] Output: Selected optimal insurance plan

[1684] Step 7:

[1685] The server automatically applies the selected insurance plan to the user and sends a notification through the app, ensuring the user receives the appropriate insurance cover in real time.

[1686] Input: Selected optimal insurance plan

[1687] Output: Insurance plan coverage notification

[1688] Step 8:

[1689] If the risk of loss increases, the server will send a warning notification to the user and suggest appropriate security measures, allowing the user to take defensive measures against the risk in real time.

[1690] Input: Loss Risk Assessment Score

[1691] Output: Warning notice and security suggestion

[1692] Through this series of processing steps, users can receive the optimal insurance plan and real-time security assistance based on various information, including their emotional state.

[1693] 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.

[1694] 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.

[1695] 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.

[1696] [Fourth embodiment]

[1697] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1698] 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.

[1699] 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).

[1700] 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.

[1701] 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.

[1702] 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).

[1703] 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.

[1704] 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.

[1705] 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.

[1706] 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.

[1707] 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.

[1708] 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.

[1709] 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."

[1710] MODE FOR CARRYING OUT THE INVENTION

[1711] A specific embodiment of the present invention will be described. The present invention includes a system that provides insurance services to allow users to appropriately manage the risk of loss. The system evaluates the risk of loss based on the user's schedule information and location information, and automatically selects and applies the optimal insurance plan.

[1712] System Overview

[1713] The system consists of user devices, a central processing server, and a cloud-based database for storing and processing user data.

[1714] 1. The user grants the app permission to access their calendar and GPS information, allowing the app to obtain the user's schedule and location information.

[1715] 2. The device (user's smartphone or tablet) periodically collects calendar and location information and sends this data to a central processing server.

[1716] 3. Based on the received schedule information and location information, the server analyzes the user's behavioral patterns using a generative model and evaluates the risk of loss.

[1717] 4. The server selects the most suitable insurance plan based on the evaluation results and automatically applies it to the user.

[1718] 5. Provide an interface that allows users to consult and set insurance settings in advance, and adjust the insurance content based on the user's responses.

[1719] Program processing

[1720] The operation of the system is explained in natural language below.

[1721] Obtaining user schedule and location information

[1722] 1. The user initiates the system by granting the app permission to access the calendar and location services.

[1723] 2. The device acquires the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history) and periodically sends them to the server.

[1724] Loss risk assessment

[1725] 3. The server uses a generative model to analyze the user's behavioral patterns based on the received schedule information and location information.

[1726] 4. The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[1727] Insurance plan selection and application

[1728] 5. The server selects the most suitable insurance plan based on the assessed risk score.

[1729] 6. The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[1730] Insurance adjustment

[1731] 7. The user reviews their insurance details within the app and adjusts their coverage and settings as needed. Adjusted settings are sent to the server in real time.

[1732] Real-time assistance and suggestions

[1733] 8. The server uses the generative model to notify the user when the risk of loss increases or when certain conditions are met, and provides appropriate suggestions and support.

[1734] Specific examples

[1735] Example 1: If you have many regular business trips

[1736] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[1737] 2. The device sends calendar information and GPS data to the server.

[1738] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling."

[1739] 4. The server automatically adds "Travel Insurance" and notifies the user.

[1740] 5. The user reviews their insurance and adjusts coverage as needed.

[1741] Example 2: When there are many sudden actions

[1742] 1. The user suddenly goes on a weekend trip.

[1743] 2. The device sends real-time GPS data to the server.

[1744] 3. The server uses the generative model to determine that there is a high risk of loss during travel.

[1745] 4. The server temporarily applies "travel insurance" and notifies the user.

[1746] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1747] In this way, users can easily access the most suitable insurance and prepare for the risk of loss.

[1748] The processing flow will be explained below.

[1749] Understood. Below is a step-by-step explanation of the specific flow of the programming process for the "Anytime Insurance" system.

[1750] Program processing

[1751] Obtaining user schedule and location information

[1752] Step 1:

[1753] The user grants the app permission to access the calendar app and location services.

[1754] Specific behavior: On the initial setup screen for the app, select the options to allow access to your calendar and use your GPS location.

[1755] Step 2:

[1756] The device periodically collects calendar information and GPS data and sends it to the app.

[1757] Specific behavior: The app periodically retrieves the user's calendar information (e.g., scheduled dates and times, locations) and GPS data (e.g., current location, movement history) in the background.

[1758] Specific operation: The acquired data is stored in local storage and sent to the cloud server at regular intervals.

[1759] Loss risk assessment

[1760] Step 3:

[1761] The server receives the calendar information and GPS data sent from the device and stores them in a database.

[1762] Specific actions: Accurately store received data in a database and format the data for analysis.

[1763] Step 4:

[1764] The server uses a generative model to analyze the user's behavioral patterns based on the stored schedule information and location information, and assesses the risk of loss.

[1765] How it works: The generative model runs on the server and uses calendar information and GPS data as input to identify user behavior patterns and calculate a loss risk score.

[1766] Insurance plan selection and application

[1767] Step 5:

[1768] The server selects the most suitable insurance plan based on the assessed risk score.

[1769] Specific Action: Select the appropriate plan from a pre-configured list of insurance plans based on risk score.

[1770] Step 6:

[1771] The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[1772] What it does: Automatically applies the insurance to the user's account and notifies the user via push notification or email.

[1773] Insurance adjustment

[1774] Step 7:

[1775] Users can review their insurance details within the app and adjust coverage and settings as needed.

[1776] Specific actions: Access the app's insurance settings screen, review the displayed insurance details, and make any necessary adjustments (e.g., change the insurance amount, set the coverage).

[1777] Step 8:

[1778] The device sends the user's settings to the server and updates them.

[1779] Specific operation: The adjusted setting information is sent to the server in real time, and the user's insurance information is updated on the server side.

[1780] Real-time assistance and suggestions

[1781] Step 9:

[1782] The server uses the generative model to send notifications to the user when there is an increased risk of loss or when certain conditions are met.

[1783] What it does: It monitors GPS data and behavioral patterns in real time, and triggers a push notification if the generative model detects an increased risk.

[1784] Step 10:

[1785] Users receive real-time notifications and can view and respond within the app.

[1786] What to do: Tap the notification in the app for more details and to take additional insurance adjustments or actions as needed.

[1787] In this way, users can easily use appropriate loss insurance and prepare for the risk of loss.

[1788] Example 1

[1789] 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."

[1790] The current insurance system requires users to select and change their insurance plans, which makes it difficult to achieve optimal risk management. Furthermore, many users find it difficult to properly assess their risk of loss, resulting in insufficient insurance coverage. Furthermore, in situations where the risk of loss fluctuates in real time, appropriate insurance proposals and support are often not provided.

[1791] 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.

[1792] In this invention, the server includes a means for analyzing a user's behavioral pattern, a means for calculating a risk score, and a means for selecting and applying an appropriate insurance plan, thereby making it possible to evaluate the risk of loss in real time based on the user's behavioral data and automatically apply the most appropriate insurance plan.

[1793] "Means for obtaining user schedule information" refers to a function for obtaining data regarding scheduled dates, times, and locations from the calendar app or schedule management app used by the user.

[1794] "Means of obtaining user location information" refers to a function that uses the user's location information service or GPS function to obtain the user's current location and movement history.

[1795] The "means for transmitting acquired schedule information and location information to a server" is a function that transmits schedule information and location information periodically collected by a user's terminal to a central processing server via data communication.

[1796] "Means for analyzing user behavior patterns using generative AI models" refers to a function that uses machine learning algorithms and artificial intelligence based on collected data to analyze and reveal user behavior patterns.

[1797] "Means for assessing the risk of loss based on behavioral patterns and calculating a risk score" refers to a function that assesses the risk of loss using statistical analysis and risk models based on user behavioral data and calculates that risk as a numerical score.

[1798] "Means for selecting the most suitable insurance plan based on risk score" is a function for selecting the most suitable insurance plan from a database based on the calculated risk score and applying it to the user.

[1799] "Means for automatically applying the selected insurance plan to the user" is a function for automatically applying the selected insurance plan to the user's account and notifying the user of the application results.

[1800] "Means for users to consult and set up their insurance settings in advance" refers to interfaces and functions that allow users to consult about insurance details in advance and set up insurance according to their individual needs.

[1801] "Means for adjusting the contents of the insurance plan based on the user's setting information" is a function for automatically adjusting the contents of the insurance plan based on the information set in advance by the user and applying it to the user.

[1802] "Means for sending a notification to the user in real time when the risk of loss increases" is a function for sending a notification to the user in real time when the risk of loss exceeds a certain threshold.

[1803] "Means for providing appropriate suggestions and support to users" refers to a function for providing appropriate suggestions and support to users to reduce the risk of loss.

[1804] MODE FOR CARRYING OUT THE INVENTION

[1805] A specific embodiment of the present invention will be described in detail. This invention is a system that provides insurance services to enable users to appropriately manage the risk of loss. The system aims to evaluate the risk of loss based on the user's schedule information and location information, and automatically select and apply the optimal insurance plan.

[1806] System configuration

[1807] The system consists of the following major components:

[1808] 1. User's Device

[1809] Devices users carry around with them, such as smartphones and tablets

[1810] Includes a calendar app and location services

[1811] The app collects the user's calendar information and GPS data and sends it to a server

[1812] 2. Central Processing Server

[1813] A server with high-performance computing power

[1814] Analyze user behavior patterns using generative AI models to assess risk of loss

[1815] Select the best insurance plan and automatically apply it to the user

[1816] 3. Cloud-based databases

[1817] A database for storing and processing user schedule information, location information, and insurance setting information

[1818] High security and scalability

[1819] Program processing

[1820] The operation of the system is explained in natural language below.

[1821] Obtaining user schedule and location information

[1822] 1. The user grants the app permission to access the Calendar app and Location Services.

[1823] 2. The device obtains the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history).

[1824] 3. The device periodically sends the acquired data to the server.

[1825] Loss risk assessment

[1826] 4. The server analyzes the user's behavioral patterns using a generative AI model based on the received schedule and location information.

[1827] 5. The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[1828] Insurance plan selection and application

[1829] 6. The server selects the most suitable insurance plan based on the assessed risk score.

[1830] 7. The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[1831] Insurance adjustment

[1832] 8. The user reviews their insurance within the app and adjusts their coverage and settings as needed.

[1833] 9. The server receives the adjusted settings and updates the insurance plan.

[1834] Real-time assistance and suggestions

[1835] 10. The server uses generative AI models to notify users when there is an increased risk of loss or when certain conditions are met, and provide appropriate suggestions and support.

[1836] Specific examples

[1837] Example 1: If you have many regular business trips

[1838] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[1839] 2. The device sends calendar information and GPS data to the server.

[1840] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling."

[1841] 4. The server automatically adds "Travel Insurance" and notifies the user.

[1842] 5. The user reviews their insurance and adjusts coverage as needed.

[1843] Example 2: When there are many sudden actions

[1844] 1. The user suddenly goes on a weekend trip.

[1845] 2. The device sends real-time GPS data to the server.

[1846] 3. The server uses the generative model to determine that there is a high risk of loss during travel.

[1847] 4. The server temporarily applies "travel insurance" and notifies the user.

[1848] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1849] In this way, users can easily access the most suitable insurance and prepare for the risk of loss.

[1850] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1851] Step 1:

[1852] The user grants the app permission to access the Calendar app and Location Services.

[1853] Specific operation: The user sets the app's permissions from the smartphone settings screen and allows access to calendar information and location information.

[1854] Input: User sets permissions.

[1855] Output: The permission information that has been set.

[1856] Step 2:

[1857] The device obtains the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history).

[1858] Specific operation: Uses the smartphone's antenna and Wi-Fi to obtain real-time location information and loads schedule information through the calendar API.

[1859] Input: Calendar and location with permissions set.

[1860] Output: Retrieved calendar information and GPS data.

[1861] Step 3:

[1862] The data acquired by the terminal is periodically sent to the server.

[1863] Specific operation: At regular intervals (for example, every minute), a background process on the device is started, which encrypts the acquired data packets and sends them to the server using the HTTPS protocol.

[1864] Input: Captured calendar information and GPS data.

[1865] Output: Data packet sent to the server.

[1866] Step 4:

[1867] The server uses a generative AI model to analyze the user's behavioral patterns based on the received schedule information and location information.

[1868] Specific operation: The server calls a generative AI model such as a cloud AI service and performs analysis using the user's data stream as input.

[1869] Input: Schedule and location information sent to the server.

[1870] Output: Analyzed behavioral patterns.

[1871] Step 5:

[1872] The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[1873] What it does: It uses pattern recognition technology to evaluate certain behavioral trends and outliers, then uses statistical models to calculate a risk score.

[1874] Input: Analyzed behavioral patterns.

[1875] Output: The calculated risk score.

[1876] Step 6:

[1877] The server selects the most suitable insurance plan based on the assessed risk score.

[1878] Specific operation: Search and select the insurance plan that best suits the risk profile from the database in the server. For example, use SQL to retrieve the insurance plan that corresponds to the risk score.

[1879] Input: Risk score.

[1880] Output: The selected insurance plan.

[1881] Step 7:

[1882] The server automatically applies the selected insurance plan to the user and notifies the user through the app.

[1883] What it does: Sends a notification to the user's app via a REST API, displaying details of the insurance plan applied.

[1884] Input: Selected insurance plan.

[1885] Output: Notification to user terminal.

[1886] Step 8:

[1887] Users can review their insurance details within the app and adjust coverage and settings as needed.

[1888] What it does: The app UI displays insurance information and allows users to change settings using a form, with changes sent to the server in real time.

[1889] Input: Insurance plan details.

[1890] Output: Adjusted insurance settings.

[1891] Step 9:

[1892] The server receives the adjusted settings and updates the insurance plan.

[1893] Specific operation: Analyzes the received data and updates the insurance configuration database on the server. For example, it updates the configuration data using a NoSQL database (such as MongoDB).

[1894] Input: Adjusted insurance settings.

[1895] Output: Updated insurance plan.

[1896] Step 10:

[1897] The server uses a generative AI model to notify users when there is an increased risk of loss or when certain conditions are met, and provide appropriate suggestions and support.

[1898] Specific operation: Monitors real-time data and issues push notifications when conditions are met. Notifications are sent to users' devices using cloud messaging services, etc.

[1899] Input: Real-time loss risk assessment.

[1900] Output: Push notification and suggestion.

[1901] (Application example 1)

[1902] 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."

[1903] When managing the risk of loss for customers and employees in physical stores, conventional methods have made it difficult to perform detailed risk assessments and apply optimal insurance plans. Furthermore, automatic application of insurance based on real-time risk fluctuations and user behavior has not been sufficiently implemented. This has led to the issue of not being able to provide appropriate support in situations where the risk of loss is high.

[1904] 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.

[1905] In this invention, the server includes: means for acquiring a user's schedule information; means for acquiring the user's location information; means for assessing the risk of loss based on the acquired schedule information and location information; means for selecting an optimal insurance plan based on the assessment results; means for automatically applying the selected insurance plan to the user; means for periodically updating the user's location information and reassessing the risk of loss; means for applying and updating the insurance plan based on the reassessment results; means for consulting and setting the user's insurance settings in advance; means for adjusting the contents of the insurance plan based on the user's setting information; means for notifying the user of the insurance application results; means for sending a notification to the user in real time when the risk of loss increases; means for providing appropriate suggestions and support to the user; and means for providing an interface for manual adjustment based on the reassessment results. This enables the risk of loss for customers and employees in physical stores to be managed through detailed assessments and the application of optimal insurance plans. It can also respond to risk fluctuations in real time and automatically apply insurance and support based on user behavior.

[1906] "Means for obtaining user schedule information" refers to a function for obtaining information entered by the user into a calendar app or schedule management application.

[1907] "Means of obtaining user location information" refers to a function for obtaining location information from a user's device, such as a smartphone or tablet, through GPS or location information services.

[1908] "Means for assessing the risk of loss based on acquired schedule information and location information" is a function for calculating the possibility of loss and assessing the risk based on the user's calendar information and location information.

[1909] The "means for selecting the most suitable insurance plan based on the evaluation results" is a function for selecting the most suitable insurance plan for the user based on the evaluation of the risk of loss.

[1910] The "means for automatically applying the selected insurance plan to the user" is a function that enables the system to automatically apply the selected insurance plan to the user.

[1911] "Means for periodically updating the user's location information and reassessing the risk of loss" is a function for periodically obtaining the user's current location and reassessing the risk based on that information.

[1912] "Means to apply and update insurance plans based on reassessment results" refers to the functionality for reviewing and updating existing insurance plans based on new risk assessment results.

[1913] "Means for consulting and setting up the user's insurance settings in advance" is a function that allows the user to consult with the user in advance about the details and settings of the insurance and set up the insurance settings that the user desires.

[1914] "Means for adjusting the contents of the insurance plan based on the user's setting information" refers to a function for changing and adjusting the contents of the insurance plan based on the information set in advance by the user.

[1915] "Means for notifying users of insurance coverage results" is a function for informing users that the selected insurance plan has been applied.

[1916] "Means for sending notifications to users in real time when the risk of loss increases" is a function for immediately sending warnings and notifications to users when the risk of loss increases.

[1917] "Means of making appropriate suggestions and support to users" refers to a function that provides specific advice and support to avoid risks when it is determined that there is a high risk of loss.

[1918] "Means for providing an interface that allows manual adjustments based on the results of reassessment" refers to a function for providing an interface that allows a user to manually adjust insurance coverage based on the updated results of risk assessment.

[1919] An embodiment of the present invention will now be described in detail. This system evaluates the risk of loss based on the user's schedule information and location information, and selects and applies an appropriate insurance plan. A detailed description of the system is provided below.

[1920] System configuration

[1921] The system mainly consists of a user terminal, a central processing server, and a cloud-based database. Users are expected to use smartphones and tablets.

[1922] Hardware and software used

[1923] Hardware: Smartphones, tablets

[1924] Software: Python 3.9, geopy library, requests library

[1925] Data processing and calculation

[1926] Obtaining user schedule and location information

[1927] The system is activated when a user grants the app permission to access the calendar app and location services. The user's device obtains calendar information (scheduled dates and times, locations) and GPS data (current location, movement history), and periodically sends this data to a central processing server.

[1928] Example prompt: "Do you consent to collecting your calendar and location information?"

[1929] Loss risk assessment

[1930] The server uses the generated AI model to analyze the user's behavioral patterns based on the acquired schedule and location information. During this process, the server calculates the distance between the user's current location and the scheduled location, and calculates a risk score based on the result. For example, if the current location is very close to the scheduled location, the risk score will be high.

[1931] Selecting an insurance plan

[1932] The server selects the most suitable insurance plan based on the assessed risk score, which is then automatically applied to the user's account.

[1933] Insurance coverage based on risk scores

[1934] The server periodically updates the user's location and reassess the risk of loss based on that information. Based on the risk assessment, the insurance plan in place is adjusted and, if necessary, a new insurance plan is installed.

[1935] Specific examples

[1936] Example 1: If you have many regular business trips

[1937] 1. A user enters "Business Trip" into their calendar and enters "City A" as the destination.

[1938] 2. The user's device sends calendar information and GPS data to the server.

[1939] 3. Based on this information, the server generates an AI model that assesses that "the risk of loss increases when traveling."

[1940] 4. The server automatically adds "Travel Insurance" and notifies the user.

[1941] 5. The user reviews their insurance and adjusts coverage as needed.

[1942] Example 2: When there are many sudden actions

[1943] 1. The user suddenly goes on a weekend trip.

[1944] 2. The user's device sends real-time GPS data to the server.

[1945] 3. The server uses the generated AI model to determine that there is a high risk of loss during travel.

[1946] 4. The server temporarily applies "travel insurance" and notifies the user.

[1947] 5. The user reviews the notification in the app and customizes the insurance as needed.

[1948] In this way, users can easily use the most suitable insurance and prepare for the risk of loss. Real-time risk assessment and automatic insurance application will more effectively protect users' safety.

[1949] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1950] Step 1:

[1951] The system starts when the user grants the app permission to access the calendar app and location services.

[1952] Input: User permission information

[1953] What happens: The user confirms the permissions based on the prompt and presses the accept button.

[1954] Output: The app gets access to the user's schedule and location.

[1955] Step 2:

[1956] The device acquires the user's calendar information (scheduled date and time, location) and GPS data (current location, movement history), and periodically transmits this data to a central processing server.

[1957] Input: Calendar information, GPS data

[1958] How it works: Your device periodically retrieves data from the Calendar app and Location Services and sends it to the server.

[1959] Output: Calendar information and GPS data are sent to the server.

[1960] Step 3:

[1961] The server uses a generative AI model to analyze the user's behavioral patterns based on the received schedule and location information.

[1962] Input: Calendar information, GPS data

[1963] How it works: The server inputs schedule and location information into a generative AI model that analyzes behavioral patterns.

[1964] Output: User behavior pattern data

[1965] Step 4:

[1966] The server evaluates the risk of loss based on the behavioral patterns and calculates a risk score.

[1967] Input: User behavior pattern data

[1968] How it works: The server calculates a risk score based on the analysis results, taking into account factors such as the distance between locations and the length of time spent there.

[1969] Output: Risk score

[1970] Step 5:

[1971] The server selects the most appropriate insurance plan based on the evaluation results and automatically applies it to the user.

[1972] Input: Risk Score

[1973] How it works: The server selects the most appropriate plan from pre-set insurance plans (low, medium, high) based on the risk score and automatically applies it.

[1974] Output: Insurance plan information applied

[1975] Step 6:

[1976] The server periodically updates the user's location and reassess the risk of loss.

[1977] Input: Latest GPS data

[1978] How it works: The server periodically retrieves the latest location information and performs risk assessment again.

[1979] Output: Updated risk score

[1980] Step 7:

[1981] The server applies and updates the insurance plan based on the reassessment results.

[1982] Input: Updated Risk Score

[1983] How it works: The server updates the insurance plan as needed based on the new risk score.

[1984] Output: Updated insurance plan information

[1985] Step 8:

[1986] Users can check their insurance coverage results within the app and adjust their insurance coverage as needed.

[1987] Input: Insurance plan information

[1988] How it works: A user opens the app, sees their insurance plan, and makes adjustments through the interface.

[1989] Output: Adjusted insurance plan settings

[1990] 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.

[1991] MODE FOR CARRYING OUT THE INVENTION

[1992] A specific embodiment of the present invention will be described. The present invention includes a system that allows users to appropriately manage their risk of loss and provides insurance plans according to that risk, and by combining it with an emotion engine, it further improves accuracy and provides insurance services according to the user's emotional state.

[1993] System Overview

[1994] The system consists of a user device, a central processing server, and a cloud-based database for storing and processing user data. It also incorporates an emotion engine to identify the user's emotional state and use that information to assess loss risk and select insurance plans.

[1995] 1. The user grants the app permission to access the calendar app, GPS information, and emotion recognition, allowing the app to obtain the user's schedule information, location information, and emotional state.

[1996] 2. The device periodically collects calendar information, GPS data, and emotional state data and transmits this data to a central processing server.

[1997] 3. Based on the received data, the server uses a generative model to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[1998] 4. The server selects the optimal insurance plan based on the evaluation results and automatically applies the customized plan to the user, taking into account their emotional state.

[1999] 5. Provide an interface that allows users to consult and set insurance settings in advance, and adjust the insurance content based on the user's settings information.

[2000] Program processing

[2001] The operation of the system is explained in natural language below.

[2002] Obtaining user schedule information, location information, and emotional state

[2003] 1. The user initiates the system by granting the app permission to access the calendar app, location services, and emotion recognition features.

[2004] 2. The device periodically collects calendar information (scheduled date and time, location), GPS data (current location, movement history), and emotional state data using the camera and microphone, and sends this data to the server.

[2005] Assessment of loss risk and emotional state

[2006] 3. The server receives the calendar information, GPS data, and emotional state data sent from the device and stores them in a database.

[2007] 4. The server uses a generative model to analyze the user's behavioral patterns and emotional state based on the stored schedule information, location information, and emotional state data, and evaluates the risk of loss.

[2008] Insurance plan selection and application

[2009] 5. The server selects the best insurance plan based on the assessed risk score and emotional state.

[2010] 6. The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[2011] Insurance adjustment

[2012] 7. The user checks the insurance details within the app and adjusts the coverage and settings to take into account their emotional state as needed. The adjusted settings are sent to the server in real time.

[2013] Real-time assistance and suggestions

[2014] 8. When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions or support.

[2015] Specific examples

[2016] Example 1: If you have many regular business trips

[2017] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[2018] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[2019] 3. Based on this information, the server uses a generative model to evaluate that "the risk of loss increases when traveling." If the user's emotional state indicates stress, the server sets a higher risk score.

[2020] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[2021] 5. The user reviews their insurance and adjusts coverage as needed.

[2022] Example 2: When there are many sudden actions

[2023] 1. The user suddenly goes on a weekend trip.

[2024] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[2025] 3. The server uses the generative model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[2026] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[2027] 5. The user reviews the notification in the app and customizes the insurance as needed.

[2028] In this way, users can easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[2029] The processing flow will be explained below.

[2030] Understood. Below is a step-by-step explanation of the specific flow of the programming process for the "Anytime Insurance" system.

[2031] Program processing

[2032] Obtaining user schedule information, location information, and emotional state

[2033] Step 1:

[2034] The user grants the app permission to access the calendar app, location services, and emotion recognition features.

[2035] What it does: On the initial setup screen for the app, select the options to allow access to your calendar, GPS location, and emotion recognition features on your camera and microphone.

[2036] Step 2:

[2037] The device periodically collects calendar information, GPS data, and emotional state data and stores it within the app.

[2038] What it does: The app periodically runs in the background and collects the user's calendar information (e.g., scheduled dates and times, locations), GPS data (e.g., current location, movement history), and emotion recognition data (e.g., facial expressions captured by the camera, voice tones collected by the microphone).

[2039] Step 3:

[2040] The device transmits the collected calendar information, GPS data, and emotional state data to a server.

[2041] Specific operation: Generates packets containing various acquired data and sends them securely to the server using the HTTPS protocol.

[2042] Assessment of loss risk and emotional state

[2043] Step 4:

[2044] The server receives the calendar information, GPS data, and emotional state data sent from the terminal and stores them in a database.

[2045] What it does: Stores the received data in a database for analysis and links it to the registered user profile.

[2046] Step 5:

[2047] The server uses a generative model based on the stored schedule information, location information, and emotional state data to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[2048] How it works: The generative model inputs schedule data, location data, and emotion recognition data to identify the user's behavioral patterns, analyze the correlation with their emotional state, and calculate a loss risk score.

[2049] Specific Actions: If emotional state indicates stress or agitation, increase risk score.

[2050] Insurance plan selection and application

[2051] Step 6:

[2052] The server selects the most suitable insurance plan based on the assessed risk score and emotional state.

[2053] What it does: From a list of pre-defined insurance plans, select the plan that best matches your risk score and emotional state, and then configure its details.

[2054] Step 7:

[2055] The server automatically applies the selected insurance plan to the user and sends a notification through the app.

[2056] Specific operation: The insurance plan details (e.g., insurance period, coverage, compensation amount) are reflected in the user's account and the user is notified via push notification or email.

[2057] Insurance adjustment

[2058] Step 8:

[2059] Users can review their insurance details within the app and adjust coverage and settings as needed, taking their emotional state into account.

[2060] What it does: Displays insurance details in the in-app insurance settings screen, allowing the user to review the options presented and adjust insurance coverage and compensation.

[2061] Step 9:

[2062] The device sends the user's settings to the server and updates them.

[2063] Specific operation: The updated settings are sent to the server using the HTTPS protocol, and the user's insurance information is updated on the server side in real time.

[2064] Real-time assistance and suggestions

[2065] Step 10:

[2066] The server uses a generative model to send notifications that take into account the user's emotional state when there is an increased risk of loss or when certain conditions are met.

[2067] What it does: It monitors GPS data, behavioral patterns, and emotional state in real time, and sends push notifications when the generative model detects increased risk.

[2068] Step 11:

[2069] Users receive real-time notifications and can view and respond within the app.

[2070] Action: Tap the app notification to learn more and take additional action or adjust your behavior as needed.

[2071] Specific examples

[2072] Example 1: If you have many regular business trips

[2073] 1. A user enters "Business Trip" into their calendar and enters "City A" as the destination.

[2074] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[2075] 3. Based on this information, the server generates a generative model that evaluates that the risk of loss increases when traveling. If the user's emotional state indicates stress, the server increases the risk score.

[2076] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[2077] 5. The user reviews the insurance and adjusts the coverage as needed.

[2078] Example 2: When there are many sudden actions

[2079] 1. The user suddenly goes on a weekend trip.

[2080] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[2081] 3. The server uses the generative model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[2082] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[2083] 5. The user reviews the notification in the app and customizes the insurance as needed.

[2084] In this way, users can easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[2085] Example 2

[2086] 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."

[2087] Conventional insurance services have difficulty in properly assessing the degree of risk of loss for users. Furthermore, because insurance plans are applied uniformly without considering the user's emotional state, it is not possible to provide optimal insurance products for users. Therefore, there is a need for a highly accurate insurance service that takes into account the user's behavioral patterns and emotional state.

[2088] 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.

[2089] In this invention, the server includes means for acquiring user schedule information, means for acquiring user location information, means for acquiring the user's emotional state, means for assessing the risk of loss based on the acquired schedule information, location information, and emotional state data, means for selecting an optimal insurance plan based on the assessment result and the emotional state, and means for automatically applying the selected insurance plan to the user. This makes it possible to provide a more accurate assessment of the risk of loss and an insurance plan based on the user's behavioral patterns and emotional state.

[2090] "Schedule information" refers to information about appointments and events that a user has entered into a calendar or app.

[2091] "Location information" refers to GPS data that indicates the user's current location and movement history.

[2092] "Emotional state" is data that captures the user's emotions through a camera or microphone.

[2093] "Loss risk" is the likelihood of losing an item or information, assessed based on the user's behavioral patterns and emotional state.

[2094] "Insurance Plan" means a customized insurance product offered based on the results of a User's risk assessment.

[2095] "Means for acquiring" refers to a method or device for collecting a user's schedule information, location information, or emotional state.

[2096] The "means for evaluating" refers to a method or device for analyzing collected data and evaluating the risk of loss.

[2097] A "means for selecting" is a method or device for selecting the most suitable insurance plan based on the evaluation results and emotional state.

[2098] The "applying means" is a method or device for automatically providing the selected insurance plan to the user.

[2099] A "means for sending notifications" is a method or device for sending information to a user in real time.

[2100] "Means for providing appropriate suggestions and support" are methods and devices for providing optimal actions and support to users.

[2101] MODE FOR CARRYING OUT THE INVENTION

[2102] A specific embodiment of this invention will be described. The present invention is a system that allows users to appropriately manage their loss risk and provides insurance plans tailored to that risk. The system's accuracy is further enhanced by incorporating an emotion engine. Its unique feature is that it provides insurance services tailored to the user's emotional state. This system is comprised of a user's terminal, a central processing server, and a cloud-based database.

[2103] System configuration

[2104] 1. The user grants the app permission to access the calendar app, location services, and emotion recognition, allowing the app to obtain the user's schedule information, location information, and emotional state.

[2105] 2. The device periodically collects calendar information (scheduled dates and times, locations), GPS data (current location, movement history), and emotional state data using the camera and microphone, and sends this data to a central processing server using emotion recognition technologies such as the Face API in Microsoft's Azure Cognitive Services.

[2106] 3. The server uses a generative model based on the received data to analyze the user's behavioral patterns and emotional state and assess the risk of loss. The generative AI model uses Google Cloud's AI Platform.

[2107] 4. The server selects the optimal insurance plan based on the evaluation results and the user's emotional state, and automatically applies the selected insurance plan to the user. For example, if a user travels frequently and is feeling stressed, the server applies "business trip insurance."

[2108] 5. The interface for users to consult and set insurance preferences in advance is always available, and the insurance contents are adjusted based on the user's preferences. The adjusted preferences are sent to the server in real time.

[2109] 6. When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions or support.

[2110] Specific examples

[2111] Example 1: If you have many regular business trips

[2112] 1. A user enters "Business Trip" into the calendar and enters "City A" as the destination.

[2113] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[2114] 3. Based on this information, the server uses the generative AI model to evaluate that "the risk of loss increases when traveling." If the user's emotional state indicates stress, the server sets a higher risk score.

[2115] 4. The server applies the "business trip insurance" and sends a notification to the user that takes into account their emotional state.

[2116] 5. The user reviews their insurance and adjusts coverage as needed.

[2117] Example 2: When there are many sudden actions

[2118] 1. The user suddenly goes on a weekend trip.

[2119] 2. The device sends real-time GPS data and emotional state data via microphone to the server.

[2120] 3. The server uses the generated AI model to determine that there is a high risk of loss during travel and detects the user's state of excitement.

[2121] 4. The server temporarily applies "travel insurance" and sends alerts to the user tailored to their emotional state.

[2122] 5. The user reviews the notification in the app and customizes the insurance as needed.

[2123] Prompt Sentence Examples

[2124] An example of a prompt sentence would be:

[2125] "A user has entered a business trip into their calendar. The destination is City A, and the user's emotional state is high. Describe a process for applying travel insurance based on this information and sending notifications that take the user's emotional state into account."

[2126] "A user has an impromptu trip over the weekend. Their current emotional state is excitement. Based on this information, explain the process for applying travel insurance and sending alerts tailored to their emotional state."

[2127] In this way, a system is constructed that allows users to easily use appropriate loss insurance based on information including their emotional state and prepare for the risk of loss.

[2128] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2129] Program processing flow

[2130] Step 1:

[2131] The user grants permission to access the Calendar app, location services, and emotion recognition features.

[2132] Input: The user grants the app permission to access the calendar app, location services, and emotion recognition features.

[2133] Specific behavior: The user turns on the required permissions in the settings screen.

[2134] Output: Authorization is given for the system to retrieve these data.

[2135] Step 2:

[2136] The device periodically collects calendar information, GPS data, and emotional state data and sends them to a server.

[2137] Input: User's calendar information, current location, movement history, emotional state via camera and microphone.

[2138] How it works: The device periodically reads calendar information and GPS data, and uses the camera and microphone to recognize emotions, for example, using the Face API from Microsoft's Azure Cognitive Services.

[2139] Output: Collected calendar information, GPS data, and emotional state data are sent to a server.

[2140] Step 3:

[2141] The server receives the calendar information, GPS data, and emotional state data sent from the device and stores them in a database.

[2142] Input: Calendar information, GPS data, and emotional state data sent from the device.

[2143] Specific operation: The server stores the received data in a secure cloud database.

[2144] Output: A database of behavioral patterns and emotional states for each user.

[2145] Step 4:

[2146] The server uses a generative AI model based on the stored data to analyze the user's behavioral patterns and emotional state and assess the risk of loss.

[2147] Input: Calendar information, GPS data, and emotional state data stored in a database.

[2148] How it works: The server runs a generative model using Google Cloud's AI Platform to analyze this data, extracting features from behavioral patterns and assessing stress levels based on emotional states.

[2149] Output: Generates an assessment of the risk of loss based on the user's behavioral patterns and emotional state.

[2150] Step 5:

[2151] The server selects the most suitable insurance plan based on the evaluation results and emotional state and automatically applies it to the user.

[2152] Input: Loss risk assessment results, emotional state assessment results.

[2153] Specific operation: The server selects an insurance plan based on the risk assessment score and emotional state. In this process, for example, "business trip insurance" or "travel insurance" is selected.

[2154] Output: Selected insurance plan is applied and user is notified.

[2155] Step 6:

[2156] Users can view notifications within the app, review their insurance coverage, and adjust coverage as needed.

[2157] Input: Applied insurance plan, notification message.

[2158] What happens: The user receives a notification, views details in the app, and adjusts the coverage and content of their insurance plan as needed.

[2159] Output: The customized insurance information is reflected in the system.

[2160] Step 7:

[2161] When the risk of loss increases or certain conditions are met, the server uses a generative model to send notifications that take into account the user's emotional state and provide appropriate suggestions and support.

[2162] Input: Real-time risk of loss, user emotional state.

[2163] How it works: The server continuously monitors data and generates notifications and alerts based on the analysis results of the generative AI model.

[2164] Output: Real-time notifications and suggestions to the user.

[2165] (Application example 2)

[2166] 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."

[2167] In modern society, users are at increased risk of losing their belongings, and this risk often fluctuates depending on the user's emotional state and behavioral patterns. However, traditional insurance systems have struggled to propose optimal insurance plans that take into account individual emotional states and behavioral patterns. Furthermore, they lacked the means to flexibly respond to users' changing risks in real time, making it difficult for users to receive appropriate protection.

[2168] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2169] In this invention, the server includes means for acquiring user schedule information, means for acquiring user location information, means for acquiring the user's emotional state, means for assessing the risk of loss based on the acquired schedule information, location information, and emotional state, means for selecting an optimal insurance plan based on the assessment results, means for automatically applying the selected insurance plan to the user, means for sending a warning notice when the risk of loss increases, and means for suggesting appropriate security measures to the user. This makes it possible to provide more accurate risk assessments and insurance plans based on the individual emotional state and behavioral patterns of the user.

[2170] "User schedule information" refers to information about appointments and events managed by the electronic device used by the user.

[2171] "User location information" refers to information about a user's current location and movement history obtained through GPS or other positioning systems.

[2172] "User's emotional state" is information that indicates the user's emotional and psychological state, which is analyzed using sensors such as a camera and a microphone.

[2173] A "means for assessing risk of loss" is a system or algorithm that analyzes and assesses the likelihood of an item being lost based on the acquired schedule information, location information, and emotional state.

[2174] The "means for selecting the optimal insurance plan" refers to a system or algorithm that determines the appropriate insurance plan for the user based on the results of an assessment of the risk of loss.

[2175] An "automated user insurance plan application" is a system or process that provides a selected insurance plan to a user without manual intervention.

[2176] "Warning notification mechanism" means a system or protocol that sends real-time warnings or alerts to a user's device in response to an increased risk.

[2177] A "means for suggesting security measures" is a system or algorithm that provides users with specific preventative measures or suggested actions to reduce the risk of loss or theft.

[2178] MODE FOR CARRYING OUT THE INVENTION

[2179] This invention is a system that uses a user's emotional state and location information to assess the risk of loss and provide an appropriate insurance plan. Specific embodiments for realizing this system are described below.

[2180] System Configuration

[2181] 1. User's device

[2182] These are mobile devices used by users, such as smartphones and tablets.

[2183] It is equipped with a camera and microphone to capture the user's emotional state.

[2184] It has a GPS function and can obtain the user's location information.

[2185] Use a calendar application to manage your schedule.

[2186] 2. Central Processing Server

[2187] It is equipped with an emotion engine, a data analysis module, and a generative AI model.

[2188] As emotion engines, we use, for example, Affectiva and Microsoft Azure Cognitive Services.

[2189] As a data analysis module, we use cloud-based data storage and analysis infrastructure (e.g., Amazon AWS and Google Cloud Platform).

[2190] Hugging Face Transformers and Google TensorFlow are used as generative AI models.

[2191] 3. Cloud Storage

[2192] Stores and manages user schedule information, location information, and emotional state data.

[2193] The data is sent to the server in real time and the analysis results are returned.

[2194] System Operation

[2195] 1. Data Collection

[2196] A user enters an event into a calendar application and grants access to GPS and emotion recognition features.

[2197] The device periodically collects calendar information, GPS data, and emotional state data from the camera and microphone and sends it to a central processing server.

[2198] 2. Data Analysis

[2199] The server stores the received calendar information, location information, and emotional state data in cloud storage.

[2200] The server uses an emotion engine to analyze the emotional state data and identify the user's psychological state.

[2201] The server uses the generated AI model to analyze user behavior patterns and assess the risk of loss.

[2202] 3. Insurance plan selection and application

[2203] The server selects the most suitable insurance plan based on the assessed risk score and emotional state.

[2204] The selected insurance plan will be automatically applied to the user and a notification will be sent via the app.

[2205] Specific examples

[2206] Example 1: When walking alone at night

[2207] 1. If a user goes out alone at night, enter that information into the calendar.

[2208] 2. The device sends calendar information, GPS data, and emotional state data obtained from the camera to the server.

[2209] 3. The server uses an emotion engine to detect when a user is alone at night and exhibits an anxious emotional state.

[2210] 4. The server-generated AI model assesses that there is a high risk of loss due to "going out alone at night."

[2211] 5. The server selects the best insurance plan and notifies the user that they are at high risk.

[2212] 6. The user checks the notification in the app and adjusts their insurance as needed.

[2213] Example prompts for generative AI models

[2214] When the user's emotional state is "unstable" and their location is in a "high crime area," the risk assessment score is set high and a warning is sent to the user saying, "Going out alone late at night is risky. Please choose a safe route."

[2215] As described above, users can receive security assistance based on their emotional state and take safety into consideration.

[2216] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2217] Program processing steps

[2218] Step 1:

[2219] A user enters an event into a calendar app and grants access to GPS and emotion recognition, allowing the device to obtain the user's schedule information, location, and emotional state.

[2220] Input: User's calendar information, GPS information, emotion recognition permission information

[2221] Output: Permission to access user schedule, location, and emotion recognition data

[2222] Step 2:

[2223] The device periodically collects calendar information, GPS data, and emotional state data captured from the camera and microphone, and transmits this data to a central processing server.

[2224] Input: Calendar information, GPS data, emotional state data

[2225] Output: Send collected data to the server

[2226] Step 3:

[2227] The server stores the received calendar information, location information, and emotional state data in cloud storage for later analysis.

[2228] Input: Calendar information, GPS data, and emotional state data sent from the device

[2229] Output: User data stored in cloud storage

[2230] Step 4:

[2231] The server analyzes the emotional state data using an emotion engine to identify the user's psychological state, for example, using Affectiva or Microsoft Azure Cognitive Services to convert the emotion data into an emotion score.

[2232] Input: Emotional state data stored in cloud storage

[2233] Output: Emotion score (analysis result of psychological state)

[2234] Step 5:

[2235] The server analyzes the stored behavioral pattern data using a generative AI model, such as Hugging Face Transformers or Google TensorFlow, to assess the risk of loss based on the user's behavioral patterns and current emotional state.

[2236] Input: Calendar information, location information, sentiment score

[2237] Output: Loss risk assessment score

[2238] Step 6:

[2239] The server selects the optimal insurance plan based on the assessed risk score and emotional state, thereby determining the best insurance plan for the user.

[2240] Input: Loss risk assessment score, sentiment score

[2241] Output: Selected optimal insurance plan

[2242] Step 7:

[2243] The server automatically applies the selected insurance plan to the user and sends a notification through the app, ensuring the user receives the appropriate insurance cover in real time.

[2244] Input: Selected optimal insurance plan

[2245] Output: Insurance plan coverage notification

[2246] Step 8:

[2247] If the risk of loss increases, the server will send a warning notification to the user and suggest appropriate security measures, allowing the user to take defensive measures against the risk in real time.

[2248] Input: Loss Risk Assessment Score

[2249] Output: Warning notice and security suggestion

[2250] Through this series of processing steps, users can receive the optimal insurance plan and real-time security assistance based on various information, including their emotional state.

[2251] 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.

[2252] 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.

[2253] 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.

[2254] 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.

[2255] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2256] 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.

[2257] 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).

[2258] 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.

[2259] 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."

[2260] 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.

[2261] The system according to the present disclosure has been described a...

Claims

1. A means for obtaining schedule information for a user; A means for obtaining user location information; a means for assessing the risk of loss based on the acquired schedule information and location information; A means for selecting the most suitable insurance plan based on the evaluation results; A means for automatically applying the selected insurance plan to the user; A system including:

2. A means to pre-consult and pre-configure users' insurance preferences; Further provide a means to tailor insurance plans based on user preferences The system of claim 1 .

3. A means to notify users in real time when there is an increased risk of loss, Further provide means to provide appropriate suggestions and support to users The system of claim 1 .

4. Provide a means to utilize generative models that analyze user behavior patterns and loss risk The system of claim 1 .

5. Provide a means to send and update user settings in real time The system of claim 1 . The above claims constitute the draft of the patent application.

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