system

Abstract

We provide the system. [Solution] Means for collecting basic user information, A means for analyzing the user's living environment and needs based on the aforementioned basic information, Means of collecting weather data and disaster information from external information provision services, A means for predicting disaster risk based on the aforementioned weather data and disaster information, A means for sending a notification to a user based on the predicted disaster risk, A means of recommending appropriate daily necessities based on the aforementioned living environment and needs, and disaster risk, A system that includes a chatbot for responding to user questions and requests.

Description

Technical Field

[0004] , , ,

[0005] , , ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In conventional e-commerce platforms, appropriate product recommendations based on individual user needs and living environments are often not made. In particular, in the case of disaster risks or emergencies, there is a problem that necessary products are not provided quickly. In addition, due to the lack of personalized product recommendations based on the user's health status and lifestyle patterns, it has been difficult for users to obtain appropriate daily necessities and health products in a timely manner. The present invention aims to solve these problems and assist users in leading a healthy and safe life.

Means for Solving the Problems

[0005] The present invention provides an e-commerce platform that includes means for collecting basic user information and analyzing the user's living environment and needs based on the basic information; means for collecting weather data and disaster information from external information provision services; means for predicting disaster risk based on the weather data and disaster information; means for sending notifications to the user based on the predicted disaster risk; means for recommending appropriate daily necessities based on the living environment and needs and disaster risk; and chatbot means for responding to questions and requests from the user. Furthermore, the invention further includes means for collecting health data from the user's wearable device; means for analyzing the health data and evaluating the user's health status; means for recommending health products and nutritional supplements based on the evaluation results; and means for providing an AI chatbot that operates 24 hours a day, 365 days a year to respond to questions and requests from the user in real time. In addition, the present invention combines these means to provide personalized product suggestions to the user and support the user's safety and comfortable life.

[0006] "Means of collecting basic user information" refers to interfaces and systems that allow users to input basic personal information such as their name, age, gender, and address, and store that information in a database.

[0007] "Means for analyzing living environment and needs" refers to methods for analyzing users' lifestyles and individual requirements using AI algorithms based on collected basic user information.

[0008] "Means for collecting weather data and disaster information" refers to the means of obtaining the latest weather forecasts and disaster information from external information provision services and making them available within the system.

[0009] "Means of predicting disaster risk" refers to methods for analyzing collected weather data and disaster information to assess the disaster risk in the area where the user resides.

[0010] "Means of sending notifications to users" refers to means of sending important information and warnings to users via push notifications or email based on predicted disaster risks.

[0011] "Means of recommending essential goods" refers to methods for suggesting products and services that are necessary for users, according to their living environment, needs, and disaster risks.

[0012] A "chatbot system" refers to an automated response system that uses AI to handle user questions and requests. It operates 24 hours a day, 365 days a year, providing user support.

[0013] "Means of collecting health data" refers to methods for obtaining health-related data such as heart rate, steps taken, and sleep duration from a user's wearable device.

[0014] "Means for evaluating health status" refers to methods for comprehensively evaluating a user's health status by analyzing collected health data using AI algorithms.

[0015] "Means of recommending health products and nutritional supplements" refers to methods for suggesting appropriate health products and nutritional supplements to users based on the results of their health status assessment. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5]It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0019] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0020] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention provides an e-commerce platform that collects basic user information, analyzes their living environment and needs, and proposes personalized daily necessities and health products. Specific embodiments of this system are described below.

[0038] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Furthermore, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information.

[0039] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[0040] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[0041] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[0042] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. The chatbot's responses are saved as logs on the server and used to improve the quality of the service.

[0043] As a concrete example, consider a user who lives in Tokyo. The server obtains information from weather data indicating that a typhoon is approaching Tokyo and assesses the disaster risk as high. Based on this assessment, the server sends the user a push notification with a list of disaster preparedness items such as emergency food, flashlights, and battery packs. The user checks the received notification, selects the necessary items, and purchases them. In this way, the user can prepare for disaster risks.

[0044] Furthermore, if a user regularly uses a wearable device, the device collects and sends data such as the user's heart rate, steps taken, and sleep duration to a server. The server analyzes this data to recognize if the user has recently been lacking exercise and recommends exercise equipment and nutritional supplements. Users can accept these suggestions via the device and purchase products to maintain their health.

[0045] As described above, the present invention provides an e-commerce platform that supports a healthy and safe lifestyle by making personalized suggestions based on the user's living environment and needs.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] The user accesses the SmartLife Assistant application for the first time. The device displays a form for the user to enter basic information (name, age, gender, address, etc.).

[0049] Step 2:

[0050] The user enters the required information into the form and submits it. The device sends the entered information to the server.

[0051] Step 3:

[0052] The server stores the user's basic information in a database. Furthermore, the server uses AI algorithms to analyze the stored basic information and identify the user's living environment and individual needs.

[0053] Step 4:

[0054] The server collects weather and disaster information in real time from external information services. This information is used to assess disaster risk.

[0055] Step 5:

[0056] The server analyzes collected weather data and disaster information to predict the disaster risk in the user's residential area. If the risk increases, the server notifies the user.

[0057] Step 6:

[0058] The device sends disaster risk notifications from the server to the user via push notification, and the user confirms the notification.

[0059] Step 7:

[0060] The server generates a product list to recommend the most suitable daily necessities based on the user's profile and the results of a disaster risk analysis.

[0061] Step 8:

[0062] The terminal displays the generated product list to the user. The user reviews the suggested product list and selects the desired products.

[0063] Step 9:

[0064] The user purchases the selected product. The terminal quickly processes this purchase and arranges delivery via the server.

[0065] Step 10:

[0066] The device periodically collects health data such as heart rate, steps taken, and sleep duration from the user's wearable device and sends it to the server.

[0067] Step 11:

[0068] The server stores the received health data in a database and uses an AI algorithm to evaluate the user's health status.

[0069] Step 12:

[0070] The server recommends the most suitable health products and nutritional supplements to the user based on the health assessment results. The terminal displays a list of health products and nutritional supplements to the user.

[0071] Step 13:

[0072] This system provides an AI chatbot that operates 24 hours a day, 365 days a year. When a user makes a question or request, the device forwards it to the chatbot.

[0073] Step 14:

[0074] The server has the chatbot analyze the question or request and generate an appropriate response. The terminal displays the generated response to the user, allowing the user to obtain the necessary information.

[0075] Step 15:

[0076] All interactions are saved as logs on the server and used to improve the quality of the service.

[0077] (Example 1)

[0078] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0079] Traditional e-commerce platforms lack sufficient mechanisms to provide personalized suggestions tailored to individual user needs and living environments, particularly lacking advanced analysis such as disaster risk prediction and health status assessment. This makes comprehensive life support difficult for users, potentially leading to shortcomings in emergencies and health management. Furthermore, the lack of mechanisms to respond to user questions and requests in real time hinders the improvement of the user experience.

[0080] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0081] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting usage data from external information provision services, means for predicting disaster risk based on the usage data, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate products based on the living environment and needs and disaster risk, and dialogue interface means for responding to questions and requests from the user. This enables personalized suggestions that are tailored to the individual user's needs and living environment. Furthermore, it can provide comprehensive life support through disaster risk prediction and health status assessment. In addition, the user experience can be improved by responding to user questions and requests in real time.

[0082] "Basic information" refers to information such as the user's name, age, gender, and address, which is used to identify the user and understand their individual needs.

[0083] "Living environment" refers to factors that influence a user's daily life, such as their place of residence, family structure, and lifestyle habits.

[0084] "Needs" refer to the demands and desires for products and services that users require.

[0085] "Information provision services" refer to services that supply external data such as weather data, disaster information, and health data.

[0086] "Usage data" refers to data collected from external information provision services, such as weather data and disaster information.

[0087] "Disaster risk" refers to the risks that a particular region or user may face, based on weather data and disaster information.

[0088] "Notifications" refer to information or warning messages sent to users.

[0089] "Products" refer to items that meet the user's needs, including daily necessities and health products recommended by the user.

[0090] A "dialogue interface" refers to chatbots and other dialogue systems used to respond to user questions and requests.

[0091] A "biometric data acquisition device" refers to a wearable device used to acquire health data such as the user's heart rate, steps taken, and sleep duration.

[0092] "Health data" refers to data that indicates the user's health status, such as heart rate, steps taken, and sleep duration.

[0093] "Health status" refers to the user's current physical and mental health condition.

[0094] "Health-related products" refer to products such as supplements and fitness equipment that are recommended according to the user's health condition.

[0095] An "AI dialogue system" refers to a system that uses artificial intelligence to operate 24 hours a day, 365 days a year, and respond to user questions and requests in real time.

[0096] This invention is a system that collects basic user information, analyzes their living environment and needs, and proposes personalized daily necessities and health products. Specific embodiments of this system are described below.

[0097] First, when a user accesses the system for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which then stores that information in a database. As a specific example, the device displays an HTML form, and when the submit button is pressed, it sends the data to the server in JSON format. The server parses the received JSON data and executes an SQL query to save it to the database.

[0098] Next, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information. Specifically, the server periodically runs the AI ​​algorithm, using the user profile information as arguments to analyze the living environment and needs. The analysis results are stored in a database in preparation for the next recommendation process.

[0099] The server also collects weather and disaster information in real time from external information services. Based on this data, it predicts the disaster risk in the user's residential area. When the risk increases, the server generates push notifications or emails to notify the user. The device displays the received notification to the user. Specifically, the server periodically retrieves weather data using an API and performs data analysis using an automated script. If the risk is determined to be high, it generates a notification message and notifies the user via push notifications or email sending APIs.

[0100] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly completes this purchase process and arranges delivery via the server. Specifically, the server runs the recommendation engine and sends the generated product list to the terminal in JSON format. The terminal updates the UI, allowing the user to select products and proceed with the purchase. The purchase information is sent back to the server, which then coordinates with the logistics system to arrange delivery.

[0101] This system also acquires health data such as heart rate, steps, and sleep duration from the user's wearable device in real time and sends it to a server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation, the server recommends the most suitable health products and nutritional supplements to the user, and the device displays this product list to the user. Specifically, the device acquires data from the wearable device using Bluetooth or Wi-Fi and sends it to the server periodically. The server analyzes the received data, generates a health report, and creates a list of recommended products.

[0102] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. Specifically, a user's question is sent to the server via the terminal, and the AI ​​chatbot generates a response using a natural language processing model, which is returned to the user in real time. At the same time, the response content is saved as a log and used to improve service quality.

[0103] For example, if a typhoon is approaching the user's area, the server will assess the disaster risk based on weather data and generate a list of recommended disaster preparedness items such as emergency food and flashlights, notifying the user. The user can then review the list, select the necessary items, and proceed with the purchase. Furthermore, for the user's daily health management, data collected from wearable devices can be analyzed to recommend appropriate health products.

[0104] Example of a prompt:

[0105] 1. "Please send the entered information to the server and save it to the database."

[0106] 2. "Analyze the user's basic information and generate a list of recommended daily necessities and health products."

[0107] 3. "Predict the disaster risk in Tokyo and send a list of disaster preparedness supplies via push notification."

[0108] 4. "Analyze the collected health data and suggest the most suitable health products for the user."

[0109] 5. "Use an AI chatbot to respond to user inquiries in real time."

[0110] As described above, the present invention provides a system that supports a healthy and safe life by making personalized suggestions based on the user's living environment and needs.

[0111] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0112] Step 1:

[0113] Gathering basic information

[0114] Terminal: When the user first accesses the service, a form is displayed for them to enter basic information such as name, age, gender, and address. Input: Input fields of the HTML form. Output: JSON data after the submit button is pressed.

[0115] User: Enter the required information into the form and press the submit button. Input: Basic information such as name, age, gender, and address. Output: Data transmission upon clicking the submit button.

[0116] Terminal: Sends the entered information to the server. Specifically, the terminal performs error checking and converts the data to JSON format. Input: Basic information entered by the user. Output: JSON data.

[0117] Server: Stores received information in the database. Inserts information using SQL queries. Input: JSON data. Output: Database update.

[0118] Step 2:

[0119] Analysis of living environment and needs

[0120] Server: Uses an AI algorithm to analyze the user's living environment and needs based on basic user information stored in the database. Input: Basic user information obtained from the database. Output: Analysis result data.

[0121] Server: Saves analysis results to the database and prepares for the next recommendation process. Specifically, the server calls the AI ​​module and inserts the analysis results into the database as an SQL query. Input: Analysis result data. Output: Database update.

[0122] Step 3:

[0123] Predicting disaster risks

[0124] Server: Collects weather and disaster information in real time from external information services. Input: API requests. Output: Weather data and disaster information.

[0125] Server: Predicts disaster risk in the user's residential area based on acquired data. Input: Weather data, disaster information, user's address. Output: Disaster risk assessment results.

[0126] Server: When risk increases, it generates push notifications and emails to notify users. Specifically, it generates notification messages and uses push notification APIs and email sending APIs. Input: Disaster risk assessment results. Output: Notification messages, push notifications, emails.

[0127] Step 4:

[0128] Product Recommendation and Purchase Procedure

[0129] Server: Recommends appropriate daily necessities based on user profiles and disaster risk analysis results. Input: User profile, disaster risk assessment results. Output: List of recommended products.

[0130] Terminal: Presents a list of recommended products to the user. Input: Product list received from the server. Output: Product list displayed to the user.

[0131] User: Selects the desired items from the presented list and proceeds with the purchase. Input: User selection. Output: Purchase information.

[0132] Terminal: Sends purchase information to the server, which then arranges delivery. Specifically, the terminal converts the purchase information into JSON format and sends it to the server. Input: User's purchase information. Output: Data sent to the server.

[0133] Server: Receives purchase information and coordinates with the logistics system to arrange delivery. Input: Purchase information. Output: Delivery arrangement.

[0134] Step 5:

[0135] Health data collection and product recommendations

[0136] Terminal: Acquires health data such as heart rate, steps, and sleep duration in real time from the user's wearable device. Input: Data from the wearable device. Output: Health data.

[0137] Terminal: Sends acquired health data to the server. Specifically, it collects data using Bluetooth or Wi-Fi and periodically sends it to the server. Input: Health data. Output: Data transmission to the server.

[0138] Server: Stores received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Input: Health data. Output: Evaluation results.

[0139] Server: Based on evaluation results, it recommends the most suitable health products and nutritional supplements to the user. Specifically, it uses an AI module to perform evaluations and generate a list of appropriate products. Input: Evaluation results. Output: Recommended list of health products.

[0140] Terminal: Displays a list of recommended products to the user. Input: Product list received from the server. Output: Product list displayed to the user.

[0141] Step 6:

[0142] AI chatbot support

[0143] Server: Provides an AI chatbot that operates 24 / 7. Input: User questions and requests from the terminal. Output: Chatbot's response.

[0144] User: Interacts with the chatbot via their device and sends questions and requests. Input: User's questions and requests. Output: Chatbot's response display.

[0145] Server: The chatbot uses an AI model to respond to user questions. Specifically, it uses a natural language processing model to analyze user input and generate an appropriate response. Input: User's question. Output: Chatbot's response.

[0146] Server: Saves response content to logs to improve service quality. Input: Chatbot response. Output: Log data.

[0147] (Application Example 1)

[0148] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0149] Modern consumers have diverse needs and individual lifestyles, requiring personalized product recommendations tailored to their specific circumstances. However, conventional systems struggle to achieve this efficiently. Furthermore, there is a lack of means to monitor disaster risks and health conditions in real time and provide appropriate products based on that information. In addition, support systems capable of responding to user inquiries at any time are inadequate. To address these challenges, a system is needed that provides advanced data collection, analysis, product recommendations, and real-time support.

[0150] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0151] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, means for linking with a wearable device to collect and analyze the user's health data, means for displaying personalized product recommendations in a virtual store, and chatbot means for responding to questions and requests from the user. This enables personalized product recommendations and appropriate support that meet the diverse needs of the user.

[0152] "Means of collecting basic user information" refers to a system that allows users to input personal information such as their name, age, gender, and address via a terminal and transmit it to a server.

[0153] "Means for analyzing the user's living environment and needs based on the aforementioned basic information" refers to a process for determining the user's lifestyle patterns and individual needs using an AI algorithm based on the collected basic information.

[0154] "Means of collecting weather data and disaster information from external information provision services" refers to technologies for obtaining weather data and disaster information in real time via the internet.

[0155] "Means for predicting disaster risk based on the aforementioned weather data and disaster information" refers to a method for analyzing acquired weather data and disaster information to predict the risk of disaster occurrence in a specific area.

[0156] "Means for sending notifications to users based on the predicted disaster risk" refers to a function that sends warnings to users' devices via push notifications or email when the disaster risk increases.

[0157] "Means for recommending appropriate daily necessities based on the aforementioned living environment, needs, and disaster risk" refers to an algorithm that selects and recommends necessary daily necessities to the user based on the user's profile and disaster risk analysis.

[0158] A "wearable device integration method for collecting and analyzing user health data" is a system that acquires health data such as heart rate, steps taken, and sleep duration in real time from wearable devices worn by the user, and analyzes this data.

[0159] "A means of displaying personalized product recommendations in a virtual store" refers to a function that displays the most suitable products for each individual user in a virtual space, taking into account the user's basic information, living environment, needs, disaster risk, and health data.

[0160] A "chatbot tool for responding to user questions and requests" is an AI chatbot that responds to user questions and requests via their device in real time, 24 hours a day, 365 days a year.

[0161] This invention relates to a virtual store system that collects basic user information, analyzes their living environment and needs, and recommends personalized products. Specific embodiments of this system are described below.

[0162] First, when a user accesses the virtual store application for the first time, the terminal displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The terminal sends the submitted information to the server, which stores that information in a database. Next, the server uses an AI algorithm to analyze the user's living environment and needs based on the stored basic information.

[0163] The server also collects weather and disaster information in real time from external information services. Using this data, the server predicts the disaster risk in the user's area. This risk prediction is performed regularly, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays this notification to the user, allowing them to receive the necessary information.

[0164] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly processes the purchase and arranges delivery via the server.

[0165] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[0166] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. The chatbot's responses are saved as logs on the server and used to improve the quality of the service.

[0167] Hardware and software to be used

[0168] Hardware: Smartphones, head-mounted displays, wearable devices

[0169] Software and libraries: Python, Flask (web framework), AI analysis algorithms (e.g., TensorFlow, Scikit-learn), databases (e.g., PostgreSQL, MongoDB)

[0170] Examples of specific cases and prompt statements

[0171] As a concrete example, a user opens the application and enters basic information. The server analyzes this information and, if it recognizes that the disaster risk is high in Tokyo, sends the user a push notification with a list of emergency food supplies and flashlights. Furthermore, based on data from the user's wearable device, if a lack of exercise is detected, it recommends exercise equipment and nutritional supplements.

[0172] Example of a prompt:

[0173] "My name is Taro Yamada. I'm 30 years old and currently live in Tokyo. Do you have any recommendations for health products or everyday necessities these days?"

[0174] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0175] Step 1:

[0176] When a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). Once the user submits the entered basic information, the device sends it to the server.

[0177] Input: Basic information such as name, age, gender, and address.

[0178] Data processing: Convert input data to JSON format.

[0179] Output: Basic information in JSON format sent to the server

[0180] Step 2:

[0181] The server stores the received basic information in a database. After this storage process, the server uses an AI algorithm to analyze the user's living environment and needs based on the basic information.

[0182] Input: Basic information in JSON format

[0183] Data processing: Data storage in databases, analysis using AI algorithms.

[0184] Output: Analysis results of the user's living environment and needs

[0185] Step 3:

[0186] The server collects weather and disaster information in real time from external information services. Based on this information, the server predicts the disaster risk in the user's area.

[0187] Input: Weather data, disaster information

[0188] Data processing: Analysis of weather data and disaster information, prediction of disaster risk.

[0189] Output: Disaster risk prediction results

[0190] Step 4:

[0191] If the risk of disaster increases, the server will send push notifications or emails to users. The device will then display these notifications to the user.

[0192] Input: Disaster risk prediction results

[0193] Data processing: Creating and sending push notifications and emails.

[0194] Output: Notification sent to the user's device

[0195] Step 5:

[0196] The server recommends appropriate daily necessities based on the user's living environment, needs, and disaster risk. This is then displayed on the user's device.

[0197] Input: Analysis results of the user's living environment and needs, disaster risk prediction results

[0198] Data processing: Generating personalized product lists

[0199] Output: Product recommendation list displayed on the user's device

[0200] Step 6:

[0201] The device acquires health data such as heart rate, steps taken, and sleep duration from the user's wearable device in real time and sends it to the server.

[0202] Input: Health data from wearable devices

[0203] Data processing: Format conversion and transmission of acquired data.

[0204] Output: Health data sent to the server

[0205] Step 7:

[0206] The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on the evaluation results, it recommends the most suitable health products and nutritional supplements to the user.

[0207] Input: Health data

[0208] Data processing: Storage in a database, evaluation using AI algorithms.

[0209] Output: Recommended list of health products and nutritional supplements

[0210] Step 8:

[0211] The server provides an AI chatbot that operates 24 / 7, 365 days a year, responding to user questions and requests in real time. Users can interact with the chatbot via their devices and receive the information and support they need.

[0212] Input: Questions and requests from users

[0213] Data processing: Response generation by chatbot

[0214] Output: Real-time response to the user

[0215] Example of a prompt:

[0216] "My name is Taro Yamada. I'm 30 years old and currently live in Tokyo. Do you have any recommendations for health products or everyday necessities these days?"

[0217] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0218] This invention is an e-commerce platform that collects basic user information and health data, analyzes the user's living environment and needs, and recommends appropriate daily necessities and health products. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it provides optimal notifications and recommendations based on the user's emotional state. The following describes a specific embodiment of this system.

[0219] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Furthermore, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information.

[0220] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[0221] Furthermore, the server recommends essential goods based on the user's profile and disaster risk analysis. The recommended product list is presented to the user via the terminal, allowing the user to select the necessary items and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[0222] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[0223] Furthermore, the present invention includes an emotion engine that recognizes the user's emotional state. The emotion engine collects emotional data in real time from the user's voice, facial expressions, and entered text. The server analyzes this emotional data to identify the user's current emotional state. For example, if the user is feeling stressed, it recommends relaxation products. It can also adjust the content and frequency of notifications according to the emotional state. In this way, it provides the user with more effective and personalized support.

[0224] As a concrete example, when a user is using a smartphone, the device sends the user's voice and facial expressions to an emotion engine. Based on this data, the server determines that the user is tired and generates a list of relaxation products. The device notifies the user of this list, and the user can select and purchase the most suitable product from the list.

[0225] Furthermore, if a user regularly uses a wearable device, the device collects and transmits the user's health data to a server. The server combines this health data with emotional data to comprehensively evaluate the user's health and emotional state. For example, it might recommend exercise equipment or relaxation supplements to a user who is stressed due to lack of exercise. The user can accept these suggestions via the device and purchase products that are optimal for both their health and emotional well-being.

[0226] As described above, the present invention, by including an emotion engine, provides an e-commerce platform that offers more personalized suggestions based on the user's living environment, health condition, and emotional state, thereby supporting the user's healthy, safe, and comfortable life.

[0227] The following describes the processing flow.

[0228] Step 1:

[0229] The user accesses the SmartLife Assistant application for the first time. The device displays a form for the user to enter basic information (name, age, gender, address, etc.).

[0230] Step 2:

[0231] The user enters the required information into the form and submits it. The device sends the entered information to the server.

[0232] Step 3:

[0233] The server stores the user's basic information in a database. Furthermore, the server uses AI algorithms to analyze the stored basic information and identify the user's living environment and individual needs.

[0234] Step 4:

[0235] The server collects weather and disaster information in real time from external information services. The collected data is used to assess disaster risk.

[0236] Step 5:

[0237] The server analyzes collected weather data and disaster information to predict the disaster risk in the user's residential area. If the risk increases, the server notifies the user.

[0238] Step 6:

[0239] The device sends disaster risk notifications from the server to the user via push notification. The user checks the notification.

[0240] Step 7:

[0241] The server generates a product list to recommend the most suitable daily necessities based on the user's profile and the results of a disaster risk analysis.

[0242] Step 8:

[0243] The terminal displays the generated product list to the user. The user reviews the suggested product list and selects the desired products.

[0244] Step 9:

[0245] The user purchases the selected product. The terminal quickly processes this purchase and arranges delivery via the server.

[0246] Step 10:

[0247] The device periodically collects health data such as heart rate, steps taken, and sleep duration from the user's wearable device and sends it to the server.

[0248] Step 11:

[0249] The server stores the received health data in a database and uses an AI algorithm to evaluate the user's health status.

[0250] Step 12:

[0251] The server recommends the most suitable health products and nutritional supplements to the user based on the health assessment results. The terminal displays a list of health products and nutritional supplements to the user.

[0252] Step 13:

[0253] The device transmits the user's voice, facial expressions, and entered text to the emotion engine. The emotion engine collects emotion data in real time.

[0254] Step 14:

[0255] The server analyzes the emotional data sent from the emotion engine to identify the user's emotional state. If necessary, it adjusts the user's profile based on the evaluation results.

[0256] Step 15:

[0257] The server adjusts the content and frequency of notifications and recommendation lists based on the user's emotional state. For example, if a user is feeling stressed, it will recommend relaxation products.

[0258] Step 16:

[0259] This system provides an AI chatbot that operates 24 hours a day, 365 days a year. When a user makes a question or request, the device forwards it to the chatbot.

[0260] Step 17:

[0261] The server has the chatbot analyze the question or request and generate an appropriate response. The terminal displays the generated response to the user, allowing the user to obtain the necessary information.

[0262] Step 18:

[0263] All interactions are saved as logs on the server and used to improve the quality of the service.

[0264] (Example 2)

[0265] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0266] Traditional e-commerce platforms are limited to simple recommendation functions based on basic user information, lacking personalized suggestions that take into account users' emotional and health states. Furthermore, they fail to adequately provide urgent information, such as safety measures and health management notifications based on disaster risks. As a result, it has been difficult to support users in leading healthy, safe, and comfortable lives.

[0267] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0268] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, dialogue agent means for responding to questions and requests from the user, emotion engine means for recognizing emotional states and providing optimal notifications and recommendations, means for analyzing the user's voice, facial expressions and text and collecting emotional data, means for adjusting notification content and recommendations based on the analyzed emotional data, means for collecting health data from the user's wearable device, means for analyzing the health data and evaluating the user's health status, means for recommending health products and nutritional supplements based on the evaluation results, and means for providing an AI dialogue agent that operates 24 hours a day, 365 days a year and responding to questions and requests from the user in real time. This enables personalized suggestions based on the user's living environment, health status and emotional status, and can support the user's healthy, safe, and comfortable life.

[0269] "User basic information" refers to personal information such as the user's name, age, gender, and address.

[0270] "Analysis of living environment and needs" refers to the process of analyzing and evaluating a user's living environment and individual needs based on their basic information.

[0271] "External information provision services" refer to services that supply real-time data provided from external sources, such as weather data and disaster information.

[0272] "Disaster risk prediction" refers to the process of estimating the likelihood of a disaster occurring in a specific area based on weather data and disaster information collected from external information services.

[0273] "Means of sending notifications" refers to methods of communicating important information to users, such as predicted disaster risks.

[0274] "Means of recommending daily necessities" refers to a function that suggests the most suitable products considering the user's living environment, needs, and disaster risk.

[0275] A "conversational agent" refers to a response system equipped with artificial intelligence to handle questions and requests from users.

[0276] An "emotion engine" refers to a system that recognizes a user's emotional state and uses that information to provide notifications and product recommendations.

[0277] "Emotional data" refers to information about a user's emotions extracted from their voice, facial expressions, and entered text.

[0278] "Adjusting notification content and recommendations based on analyzed sentiment data" refers to the process of adaptively changing the content and frequency of notifications and product recommendations based on the user's emotional state.

[0279] A "wearable device" refers to a device that a user wears to measure and collect health data such as heart rate, steps taken, and sleep duration.

[0280] "Collecting health data" refers to the process of acquiring data such as heart rate, steps taken, and sleep duration from wearable devices.

[0281] "Means for evaluating a user's health status" refers to a method of comprehensively evaluating a user's health status by analyzing collected health data.

[0282] "Recommendation of health products and dietary supplements" refers to the function of proposing the most suitable health products and dietary supplements to users based on the evaluation results.

[0283] "AI chat agent" refers to a system equipped with artificial intelligence that operates 24 hours a day, 365 days a year, and responds to questions and requests from users in real time.

[0284] Mode for Carrying Out the Invention

[0285] The present invention is an e-commerce platform that collects basic information and health data of users, analyzes living environments and needs, and recommends appropriate daily necessities and health products. Furthermore, by incorporating an emotion engine that recognizes the emotions of users, it makes optimal notifications and recommendations based on the emotional state of users. Specific embodiments of this system will be described below.

[0286] Equipment and Hardware / Software Used

[0287] 1. Preparation of Terminal

[0288] An interface for inputting basic information is provided on the terminal (such as a smartphone, tablet, PC, etc.) used by the user.

[0289] Wearable devices (such as smartwatches) are used to collect the health data of users in real time and transmit it to the terminal.

[0290] 2. Functions of Server

[0291] The server has a database for collecting and storing the basic information input by the user and the health data transmitted from the wearable device.

[0292] The server collects real-time data from external information providing services (such as weather data and disaster information providing services).

[0293] The server uses an emotion engine to analyze emotional data from the user's voice, facial expressions, and input text.

[0294] 3. Execution of the AI ​​algorithm

[0295] The AI ​​algorithm embedded in the server analyzes the user's living environment and needs based on the user's basic information, health data, and emotional data.

[0296] It analyzes weather data and disaster information collected in real time to predict disaster risks.

[0297] 4. Notification and Recommendation System

[0298] The server generates a list of appropriate daily necessities and health products based on disaster risks and user needs.

[0299] The server sends push notifications and emails to terminals, providing users with urgent notifications and product recommendations.

[0300] The device displays these notifications and recommendation lists to the user, who can respond as needed.

[0301] Specific examples and prompt statements

[0302] 1. Collection and analysis of basic information and sentiment data

[0303] Users enter basic information such as their name, age, gender, and address into a form on their smartphone and submit it.

[0304] The device sends this information to the server, where it is stored in the database.

[0305] The server collects the user's voice and facial expressions in real time and analyzes them using an emotion engine.

[0306] For example, when it is determined that the user is feeling stressed, a list of relaxation goods is generated.

[0307] Prompt sentence example:

[0308] "Please recommend the most suitable relaxation goods based on the user's basic information and current emotional state."

[0309] 2. Integrated analysis of health data and emotional data

[0310] Data such as heart rate, number of steps, and sleep time are transmitted to the terminal from a smartwatch or the like that the user uses daily.

[0311] The terminal transmits this data to the server, and the server analyzes the data.

[0312] The server combines the health data and emotional data, evaluates the user's health state and emotional state, and recommends appropriate health products and nutritional supplements.

[0313] Prompt sentence example:

[0314] "Please propose appropriate nutritional supplements for the user based on the health data and emotional data obtained in real time."

[0315] The purpose of this system is to provide more personalized recommendations based on the user's living environment, health state, and emotional state by including an emotion engine, and to support the user's healthy, safe, and comfortable life. Through emergency notifications based on disaster risks and personalized product recommendations, the user can respond quickly and accurately.

[0316] The flow of the specific process in Example 2 will be described using FIG. 13.

[0317] Step 1:

[0318] Collection of basic information

[0319] When a user accesses the site for the first time, they enter basic information such as their name, age, gender, and address into a form that appears on their device.

[0320] Input: Basic user information such as name, age, gender, and address.

[0321] The terminal sends the basic information entered by the user to the server.

[0322] The server stores this information in the database.

[0323] Output: Basic user information stored in the database.

[0324] Step 2:

[0325] Analysis of living environment and needs

[0326] The server uses an AI algorithm to analyze basic user information obtained from the database.

[0327] Input: Basic user information stored in the database.

[0328] The server uses an AI model to analyze patterns in living environments and needs.

[0329] Output: Analytical data regarding the user's living environment and needs.

[0330] Step 3:

[0331] Real-time data collection

[0332] The server collects weather data and disaster information in real time from external information provision services.

[0333] Input: Weather data and disaster information obtained from external information provision services.

[0334] The server stores this information in a database and performs the necessary data processing.

[0335] Output: Real-time data stored in the database.

[0336] Step 4:

[0337] Predicting disaster risks

[0338] The server uses real-time data to predict the disaster risk in the user's residential area using an AI algorithm.

[0339] Input: Real-time data, user's residential area information.

[0340] The server analyzes weather data and disaster information and outputs the likelihood of a disaster occurring in a specific area.

[0341] Output: Disaster risk prediction results.

[0342] Step 5:

[0343] Sending an emergency notification

[0344] The server generates emergency notifications for users based on the predicted disaster risk.

[0345] Input: Disaster risk prediction results.

[0346] The terminal displays emergency notifications sent from the server to the user.

[0347] Output: Emergency notification displayed to the user.

[0348] Step 6:

[0349] Recommendations for daily necessities

[0350] The server uses an AI algorithm to recommend the most suitable daily necessities based on the user's basic information, living environment, needs, and disaster risk.

[0351] Input: User's basic information, living environment, needs, and disaster risk.

[0352] The server uses an AI model to generate a product list tailored to the user.

[0353] The terminal displays the generated product list to the user.

[0354] Output: A list of recommended daily necessities displayed to the user.

[0355] Step 7:

[0356] Purchase procedure

[0357] The user selects the desired product from the provided product list.

[0358] Input: The product selected by the user.

[0359] The terminal completes the purchase process and arranges for delivery via the server.

[0360] Output: Purchased items for which shipping arrangements have been completed.

[0361] Step 8:

[0362] Collection of health data

[0363] The device collects health data such as heart rate, steps taken, and sleep duration from the user's wearable devices.

[0364] Input: Health data collected from wearable devices.

[0365] The device sends the collected health data to the server.

[0366] Output: Health data stored on the server.

[0367] Step 9:

[0368] Health status assessment

[0369] The server analyzes the collected health data using an AI algorithm to assess the user's health status.

[0370] Input: Health data collected from wearable devices.

[0371] The server analyzes health data and outputs an overall health assessment.

[0372] Output: User health assessment results.

[0373] Step 10:

[0374] Recommendations for health products and nutritional supplements

[0375] Based on the health assessment results, the server uses an AI model to recommend the most suitable health products and nutritional supplements to the user.

[0376] Input: User's health assessment results.

[0377] The server generates a list of the most suitable products and sends it to the terminal.

[0378] The device displays these product lists to the user.

[0379] Output: A list of recommended health products and nutritional supplements displayed to the user.

[0380] Step 11:

[0381] Recognition of emotional states by an emotion engine

[0382] The device runs an emotion engine that collects emotional data from the user's voice, facial expressions, and entered text.

[0383] Input: User's voice, facial expressions, and text data.

[0384] The device sends the collected emotional data to the server, which then analyzes it.

[0385] Output: Analyzed user sentiment data.

[0386] Step 12:

[0387] Adjusting notifications and recommendations based on emotions

[0388] The server adjusts notification content and recommendations based on the analyzed sentiment data.

[0389] Input: Analyzed sentiment data, user profile information.

[0390] The server uses sentiment data to provide notifications and product recommendations tailored to the user's needs.

[0391] The device displays this customized information to the user.

[0392] Output: Customized notifications and recommendations displayed to the user.

[0393] Using the above procedure, this system provides personalized suggestions based on the user's living environment, health condition, and emotional state, supporting a healthy, safe, and comfortable life.

[0394] (Application Example 2)

[0395] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0396] Traditional e-commerce platforms can collect basic user information and health data and recommend products based on lifestyle and needs, but they have a challenge in providing appropriate product recommendations that respond to users' emotional states and real-time situations. In particular, when users are feeling stressed or fatigued, the platform may fail to recommend products that are appropriate to their emotions, raising concerns about decreased user satisfaction and perceived value. Against this backdrop, there is a need for more accurate and personalized product recommendations through comprehensive data analysis that includes users' emotional states.

[0397] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, means for collecting and analyzing emotional data from the user's voice, facial expressions, text input, and wearable devices, means for evaluating the user's emotional state based on the emotional data and recommending products and services that are appropriate to the emotional state, means for displaying recommended products and services through a user interface and supporting the purchase procedure, and chatbot means for responding to questions and requests from the user. This enables more accurate personalized product recommendations based on a comprehensive analysis of the user's basic information, health data, and emotional state.

[0398] "Basic user information" refers to data necessary to identify an individual user and understand their living environment and needs, such as name, age, gender, and address.

[0399] "Living environment" refers to all information related to the user's daily life, including the characteristics of the area where the user lives, their lifestyle habits, and their work environment.

[0400] "Needs" refer to the user's demands, desires, and necessities, and they change based on the user's living environment and circumstances.

[0401] "Weather data" refers to information about the climate of a specific region, such as weather forecasts, temperature, precipitation, and wind speed.

[0402] "Disaster information" refers to real-time data on natural disasters such as earthquakes, typhoons, heavy rains, and floods.

[0403] "Disaster risk" refers to the probability of a natural disaster occurring and the extent of its impact, as predicted based on collected weather data and disaster information.

[0404] A "notification" is an alert or message sent to a user's device to convey important information or recommendations.

[0405] "Daily necessities" are goods and services that are necessary to support the daily lives of users.

[0406] "Recommendation" refers to the act of suggesting the most suitable products or services based on the user's living environment, needs, disaster risks, etc.

[0407] "Voice data" refers to information about a user's speech and voice, and is collected using speech recognition technology.

[0408] "Facial expression data" refers to emotional information obtained by analyzing a user's facial expressions, and is collected through devices such as cameras.

[0409] "Text input" refers to character information entered by the user through keyboard input or a touch interface.

[0410] A "wearable device" is an electronic device worn by the user that provides health and activity data in real time.

[0411] "Emotional data" refers to information that indicates a user's emotional state, obtained from sources such as voice, facial expressions, and text input.

[0412] "Analysis" is the process of examining collected data to derive specific patterns or conclusions.

[0413] "Evaluation" is the act of judging a user's health and emotional state based on information obtained through analysis.

[0414] A "user interface" refers to the screens and operating methods that allow the user and the system to interact directly.

[0415] A "chatbot" is automated software that uses artificial intelligence to interact with humans in natural language and respond to questions and requests.

[0416] This invention is a system that comprehensively evaluates a user's basic information, health data, and emotional data to recommend personalized products and services. Specific embodiments for carrying out this invention are described below.

[0417] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Based on the stored basic information, the server uses an AI algorithm to analyze the user's living environment and individual needs.

[0418] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[0419] Furthermore, the server recommends essential goods based on the user's profile and disaster risk analysis. The recommended product list is presented to the user via the terminal, allowing the user to select the necessary items and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[0420] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this list of products to the user.

[0421] Furthermore, the present invention includes an emotion engine that recognizes the user's emotional state. The emotion engine collects emotional data in real time from the user's voice, facial expressions, and entered text. The server analyzes this emotional data to identify the user's current emotional state. For example, if the user is feeling stressed, it recommends relaxation products. It can also adjust the content and frequency of notifications according to the emotional state. In this way, it provides the user with more effective and personalized support.

[0422] As a concrete example, when a user is wearing smart glasses, the device sends the user's voice and facial expressions to an emotion engine. Based on this data, the server determines that the user is tired and generates a list of relaxation products. The device notifies the user of this list, and the user can select and purchase the most suitable product from the list. Also, if a user uses a wearable device on a daily basis, the device collects the user's health data and sends it to the server. The server combines the health data and emotion data to comprehensively evaluate the user's health and emotional state. For example, it might recommend exercise equipment or relaxation supplements to a user who is stressed due to lack of exercise. The user can accept these suggestions via the device and purchase the most suitable products from both a health and emotional perspective.

[0423] The main hardware used includes smart glasses, microphones, cameras, and wearable devices. The main software used includes FaceAPI, SpeechAPI, Bluetooth SDK, TensorFlow, PyTorch, Recommendation Engine API, React Native, and Flutter.

[0424] Example input prompts for a generative AI model:

[0425] "If the camera detects that the user has a tired expression, it will recommend relaxation products."

[0426] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0427] Step 1:

[0428] When a user accesses the system for the first time, the terminal displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The entered information is sent to the server via the terminal, and the server stores this information in a database. As part of the input data processing, the data format is standardized and errors are checked. The output is the formatted basic information stored in the database.

[0429] Step 2:

[0430] The server uses stored basic information and AI algorithms to analyze the user's living environment and needs. The AI ​​algorithms used perform personalized analysis based on the user's attribute information. The input data is the user's basic information, and the output is an analysis result showing the user's living environment and individual needs. Statistical models and machine learning models are applied to process the data for analysis.

[0431] Step 3:

[0432] The server collects weather and disaster information in real time from external information services. This is done via a RESTful API. The input is data obtainable from the API endpoints of external services, and the output is weather data and disaster information. Data ingestion and formatting are performed.

[0433] Step 4:

[0434] The server predicts the disaster risk in the user's area based on collected weather data and disaster information. This prediction is performed periodically, and an AI model is used to assess the risk. The input data consists of weather data and disaster information, and the output is the disaster risk assessment result. Data processing includes time series data analysis and the application of risk models.

[0435] Step 5:

[0436] When risk increases, the server sends important safety notifications to users via push notifications or email. The input data is the disaster risk assessment results, and the output is the content of the push notifications or emails. Specific operations include generating notification content and sending it to the user's device.

[0437] Step 6:

[0438] The server recommends the most suitable daily necessities based on the user's profile and disaster risk analysis results. The recommendation system uses the user's attribute information, needs, and disaster risk as input to generate a recommendation list. The output is a list of recommended daily necessities. As part of the data processing, a recommendation engine is applied.

[0439] Step 7:

[0440] The terminal presents the user with a list of recommended products, allowing the user to select the desired items from the list and proceed with the purchase. The input data is the recommended product list, and the output is the user's selected products and their purchase procedure information. Specifically, it provides a GUI presentation and support for the purchase flow.

[0441] Step 8:

[0442] The terminal acquires health data such as heart rate, steps, and sleep duration in real time from the user's wearable device and transmits it to the server. The input data is the health data acquired from the wearable device, and the output is the health data transmitted to the server. Specific operations include establishing Bluetooth communication and acquiring data.

[0443] Step 9:

[0444] The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. The input data is health data, and the output is the evaluation result of the health status. As a data calculation, a health model is applied and evaluated.

[0445] Step 10:

[0446] Based on the evaluation results, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user. The input data is the results of the health status evaluation, and the output is a list of recommended health products. Specifically, notifications are generated and displayed on the screen.

[0447] Step 11:

[0448] The device collects emotional data in real time from the user's voice, facial expressions, and text input, and sends it to the server. Input data includes voice, facial expressions, and text data, while output is the emotional data sent to the server. Specific operations include voice recognition and facial expression analysis.

[0449] Step 12:

[0450] The server analyzes emotional data to identify the user's current emotional state. The input data is emotional data, and the output is an evaluation of the emotional state. The emotional analysis engine is applied as part of the data processing.

[0451] Step 13:

[0452] This system recommends products and services that are appropriate to the user's emotional state. The input data is an evaluation of the emotional state, and the output is a list of recommended products and services. Specifically, it generates recommendations based on the user's emotions.

[0453] Step 14:

[0454] This system displays recommended products and services through a user interface and supports the purchase process. The input data is a list of recommended products and services, and the output is information confirming the completion of the purchase process. Specific actions include displaying the purchase screen and supporting the purchase flow.

[0455] Step 15:

[0456] This system provides a chatbot mechanism to handle user questions and requests, and provides real-time responses to those requests. Input data consists of user questions and requests, and output is the chatbot's response data. Specifically, it performs natural language processing and response generation.

[0457] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0458] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0459] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0460] [Second Embodiment]

[0461] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0462] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0463] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0464] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0465] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0466] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0467] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0468] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0469] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0470] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0471] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0472] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0473] This invention provides an e-commerce platform that collects basic user information, analyzes their living environment and needs, and proposes personalized daily necessities and health products. Specific embodiments of this system are described below.

[0474] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Furthermore, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information.

[0475] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[0476] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[0477] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[0478] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. The chatbot's responses are saved as logs on the server and used to improve the quality of the service.

[0479] As a concrete example, consider a user who lives in Tokyo. The server obtains information from weather data indicating that a typhoon is approaching Tokyo and assesses the disaster risk as high. Based on this assessment, the server sends the user a push notification with a list of disaster preparedness items such as emergency food, flashlights, and battery packs. The user checks the received notification, selects the necessary items, and purchases them. In this way, the user can prepare for disaster risks.

[0480] Furthermore, if a user regularly uses a wearable device, the device collects and sends data such as the user's heart rate, steps taken, and sleep duration to a server. The server analyzes this data to recognize if the user has recently been lacking exercise and recommends exercise equipment and nutritional supplements. Users can accept these suggestions via the device and purchase products to maintain their health.

[0481] As described above, the present invention provides an e-commerce platform that supports a healthy and safe lifestyle by making personalized suggestions based on the user's living environment and needs.

[0482] The following describes the processing flow.

[0483] Step 1:

[0484] The user accesses the SmartLife Assistant application for the first time. The device displays a form for the user to enter basic information (name, age, gender, address, etc.).

[0485] Step 2:

[0486] The user enters the required information into the form and submits it. The device sends the entered information to the server.

[0487] Step 3:

[0488] The server stores the user's basic information in a database. Furthermore, the server uses AI algorithms to analyze the stored basic information and identify the user's living environment and individual needs.

[0489] Step 4:

[0490] The server collects weather and disaster information in real time from external information services. This information is used to assess disaster risk.

[0491] Step 5:

[0492] The server analyzes collected weather data and disaster information to predict the disaster risk in the user's residential area. If the risk increases, the server notifies the user.

[0493] Step 6:

[0494] The device sends disaster risk notifications from the server to the user via push notification, and the user confirms the notification.

[0495] Step 7:

[0496] The server generates a product list to recommend the most suitable daily necessities based on the user's profile and the results of a disaster risk analysis.

[0497] Step 8:

[0498] The terminal displays the generated product list to the user. The user reviews the suggested product list and selects the desired products.

[0499] Step 9:

[0500] The user purchases the selected product. The terminal quickly processes this purchase and arranges delivery via the server.

[0501] Step 10:

[0502] The device periodically collects health data such as heart rate, steps taken, and sleep duration from the user's wearable device and sends it to the server.

[0503] Step 11:

[0504] The server stores the received health data in a database and uses an AI algorithm to evaluate the user's health status.

[0505] Step 12:

[0506] The server recommends the most suitable health products and nutritional supplements to the user based on the health assessment results. The terminal displays a list of health products and nutritional supplements to the user.

[0507] Step 13:

[0508] This system provides an AI chatbot that operates 24 hours a day, 365 days a year. When a user makes a question or request, the device forwards it to the chatbot.

[0509] Step 14:

[0510] The server has the chatbot analyze the question or request and generate an appropriate response. The terminal displays the generated response to the user, allowing the user to obtain the necessary information.

[0511] Step 15:

[0512] All interactions are saved as logs on the server and used to improve the quality of the service.

[0513] (Example 1)

[0514] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0515] Traditional e-commerce platforms lack sufficient mechanisms to provide personalized suggestions tailored to individual user needs and living environments, particularly lacking advanced analysis such as disaster risk prediction and health status assessment. This makes comprehensive life support difficult for users, potentially leading to shortcomings in emergencies and health management. Furthermore, the lack of mechanisms to respond to user questions and requests in real time hinders the improvement of the user experience.

[0516] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0517] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting usage data from external information provision services, means for predicting disaster risk based on the usage data, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate products based on the living environment and needs and disaster risk, and dialogue interface means for responding to questions and requests from the user. This enables personalized suggestions that are tailored to the individual user's needs and living environment. Furthermore, it can provide comprehensive life support through disaster risk prediction and health status assessment. In addition, the user experience can be improved by responding to user questions and requests in real time.

[0518] "Basic information" refers to information such as the user's name, age, gender, and address, which is used to identify the user and understand their individual needs.

[0519] "Living environment" refers to factors that influence a user's daily life, such as their place of residence, family structure, and lifestyle habits.

[0520] "Needs" refer to the demands and desires for products and services that users require.

[0521] "Information provision services" refer to services that supply external data such as weather data, disaster information, and health data.

[0522] "Usage data" refers to data collected from external information provision services, such as weather data and disaster information.

[0523] "Disaster risk" refers to the risks that a particular region or user may face, based on weather data and disaster information.

[0524] "Notifications" refer to information or warning messages sent to users.

[0525] "Products" refer to items that meet the user's needs, including daily necessities and health products recommended by the user.

[0526] A "dialogue interface" refers to chatbots and other dialogue systems used to respond to user questions and requests.

[0527] A "biometric data acquisition device" refers to a wearable device used to acquire health data such as the user's heart rate, steps taken, and sleep duration.

[0528] "Health data" refers to data that indicates the user's health status, such as heart rate, steps taken, and sleep duration.

[0529] "Health status" refers to the user's current physical and mental health condition.

[0530] "Health-related products" refer to products such as supplements and fitness equipment that are recommended according to the user's health condition.

[0531] An "AI dialogue system" refers to a system that uses artificial intelligence to operate 24 hours a day, 365 days a year, and respond to user questions and requests in real time.

[0532] This invention is a system that collects basic user information, analyzes their living environment and needs, and proposes personalized daily necessities and health products. Specific embodiments of this system are described below.

[0533] First, when a user accesses the system for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which then stores that information in a database. As a specific example, the device displays an HTML form, and when the submit button is pressed, it sends the data to the server in JSON format. The server parses the received JSON data and executes an SQL query to save it to the database.

[0534] Next, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information. Specifically, the server periodically runs the AI ​​algorithm, using the user profile information as arguments to analyze the living environment and needs. The analysis results are stored in a database in preparation for the next recommendation process.

[0535] The server also collects weather and disaster information in real time from external information services. Based on this data, it predicts the disaster risk in the user's residential area. When the risk increases, the server generates push notifications or emails to notify the user. The device displays the received notification to the user. Specifically, the server periodically retrieves weather data using an API and performs data analysis using an automated script. If the risk is determined to be high, it generates a notification message and notifies the user via push notifications or email sending APIs.

[0536] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly completes this purchase process and arranges delivery via the server. Specifically, the server runs the recommendation engine and sends the generated product list to the terminal in JSON format. The terminal updates the UI, allowing the user to select products and proceed with the purchase. The purchase information is sent back to the server, which then coordinates with the logistics system to arrange delivery.

[0537] This system also acquires health data such as heart rate, steps, and sleep duration from the user's wearable device in real time and sends it to a server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation, the server recommends the most suitable health products and nutritional supplements to the user, and the device displays this product list to the user. Specifically, the device acquires data from the wearable device using Bluetooth or Wi-Fi and sends it to the server periodically. The server analyzes the received data, generates a health report, and creates a list of recommended products.

[0538] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. Specifically, a user's question is sent to the server via the terminal, and the AI ​​chatbot generates a response using a natural language processing model, which is returned to the user in real time. At the same time, the response content is saved as a log and used to improve service quality.

[0539] For example, if a typhoon is approaching the user's area, the server will assess the disaster risk based on weather data and generate a list of recommended disaster preparedness items such as emergency food and flashlights, notifying the user. The user can then review the list, select the necessary items, and proceed with the purchase. Furthermore, for the user's daily health management, data collected from wearable devices can be analyzed to recommend appropriate health products.

[0540] Example of a prompt:

[0541] 1. "Please send the entered information to the server and save it to the database."

[0542] 2. "Analyze the user's basic information and generate a list of recommended daily necessities and health products."

[0543] 3. "Predict the disaster risk in Tokyo and send a list of disaster preparedness supplies via push notification."

[0544] 4. "Analyze the collected health data and suggest the most suitable health products for the user."

[0545] 5. "Use an AI chatbot to respond to user inquiries in real time."

[0546] As described above, the present invention provides a system that supports a healthy and safe life by making personalized suggestions based on the user's living environment and needs.

[0547] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0548] Step 1:

[0549] Gathering basic information

[0550] Terminal: When the user first accesses the service, a form is displayed for them to enter basic information such as name, age, gender, and address. Input: Input fields of the HTML form. Output: JSON data after the submit button is pressed.

[0551] User: Enter the required information into the form and press the submit button. Input: Basic information such as name, age, gender, and address. Output: Data transmission upon clicking the submit button.

[0552] Terminal: Sends the entered information to the server. Specifically, the terminal performs error checking and converts the data to JSON format. Input: Basic information entered by the user. Output: JSON data.

[0553] Server: Stores received information in the database. Inserts information using SQL queries. Input: JSON data. Output: Database update.

[0554] Step 2:

[0555] Analysis of living environment and needs

[0556] Server: Uses an AI algorithm to analyze the user's living environment and needs based on basic user information stored in the database. Input: Basic user information obtained from the database. Output: Analysis result data.

[0557] Server: Saves analysis results to the database and prepares for the next recommendation process. Specifically, the server calls the AI ​​module and inserts the analysis results into the database as an SQL query. Input: Analysis result data. Output: Database update.

[0558] Step 3:

[0559] Predicting disaster risks

[0560] Server: Collects weather and disaster information in real time from external information services. Input: API requests. Output: Weather data and disaster information.

[0561] Server: Predicts disaster risk in the user's residential area based on acquired data. Input: Weather data, disaster information, user's address. Output: Disaster risk assessment results.

[0562] Server: When risk increases, it generates push notifications and emails to notify users. Specifically, it generates notification messages and uses push notification APIs and email sending APIs. Input: Disaster risk assessment results. Output: Notification messages, push notifications, emails.

[0563] Step 4:

[0564] Product Recommendation and Purchase Procedure

[0565] Server: Recommends appropriate daily necessities based on user profiles and disaster risk analysis results. Input: User profile, disaster risk assessment results. Output: List of recommended products.

[0566] Terminal: Presents a list of recommended products to the user. Input: Product list received from the server. Output: Product list displayed to the user.

[0567] User: Selects the desired items from the presented list and proceeds with the purchase. Input: User selection. Output: Purchase information.

[0568] Terminal: Sends purchase information to the server, which then arranges delivery. Specifically, the terminal converts the purchase information into JSON format and sends it to the server. Input: User's purchase information. Output: Data sent to the server.

[0569] Server: Receives purchase information and coordinates with the logistics system to arrange delivery. Input: Purchase information. Output: Delivery arrangement.

[0570] Step 5:

[0571] Health data collection and product recommendations

[0572] Terminal: Acquires health data such as heart rate, steps, and sleep duration in real time from the user's wearable device. Input: Data from the wearable device. Output: Health data.

[0573] Terminal: Sends acquired health data to the server. Specifically, it collects data using Bluetooth or Wi-Fi and periodically sends it to the server. Input: Health data. Output: Data transmission to the server.

[0574] Server: Stores received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Input: Health data. Output: Evaluation results.

[0575] Server: Based on evaluation results, it recommends the most suitable health products and nutritional supplements to the user. Specifically, it uses an AI module to perform evaluations and generate a list of appropriate products. Input: Evaluation results. Output: Recommended list of health products.

[0576] Terminal: Displays a list of recommended products to the user. Input: Product list received from the server. Output: Product list displayed to the user.

[0577] Step 6:

[0578] AI chatbot support

[0579] Server: Provides an AI chatbot that operates 24 / 7. Input: User questions and requests from the terminal. Output: Chatbot's response.

[0580] User: Interacts with the chatbot via their device and sends questions and requests. Input: User's questions and requests. Output: Chatbot's response display.

[0581] Server: The chatbot uses an AI model to respond to user questions. Specifically, it uses a natural language processing model to analyze user input and generate an appropriate response. Input: User's question. Output: Chatbot's response.

[0582] Server: Saves response content to logs to improve service quality. Input: Chatbot response. Output: Log data.

[0583] (Application Example 1)

[0584] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0585] Modern consumers have diverse needs and individual lifestyles, requiring personalized product recommendations tailored to their specific circumstances. However, conventional systems struggle to achieve this efficiently. Furthermore, there is a lack of means to monitor disaster risks and health conditions in real time and provide appropriate products based on that information. In addition, support systems capable of responding to user inquiries at any time are inadequate. To address these challenges, a system is needed that provides advanced data collection, analysis, product recommendations, and real-time support.

[0586] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0587] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, means for linking with a wearable device to collect and analyze the user's health data, means for displaying personalized product recommendations in a virtual store, and chatbot means for responding to questions and requests from the user. This enables personalized product recommendations and appropriate support that meet the diverse needs of the user.

[0588] "Means of collecting basic user information" refers to a system that allows users to input personal information such as their name, age, gender, and address via a terminal and transmit it to a server.

[0589] "Means for analyzing the user's living environment and needs based on the aforementioned basic information" refers to a process for determining the user's lifestyle patterns and individual needs using an AI algorithm based on the collected basic information.

[0590] "Means of collecting weather data and disaster information from external information provision services" refers to technologies for obtaining weather data and disaster information in real time via the internet.

[0591] "Means for predicting disaster risk based on the aforementioned weather data and disaster information" refers to a method for analyzing acquired weather data and disaster information to predict the risk of disaster occurrence in a specific area.

[0592] "Means for sending notifications to users based on the predicted disaster risk" refers to a function that sends warnings to users' devices via push notifications or email when the disaster risk increases.

[0593] "Means for recommending appropriate daily necessities based on the aforementioned living environment, needs, and disaster risk" refers to an algorithm that selects and recommends necessary daily necessities to the user based on the user's profile and disaster risk analysis.

[0594] A "wearable device integration method for collecting and analyzing user health data" is a system that acquires health data such as heart rate, steps taken, and sleep duration in real time from wearable devices worn by the user, and analyzes this data.

[0595] "A means of displaying personalized product recommendations in a virtual store" refers to a function that displays the most suitable products for each individual user in a virtual space, taking into account the user's basic information, living environment, needs, disaster risk, and health data.

[0596] A "chatbot tool for responding to user questions and requests" is an AI chatbot that responds to user questions and requests via their device in real time, 24 hours a day, 365 days a year.

[0597] This invention relates to a virtual store system that collects basic user information, analyzes their living environment and needs, and recommends personalized products. Specific embodiments of this system are described below.

[0598] First, when a user accesses the virtual store application for the first time, the terminal displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The terminal sends the submitted information to the server, which stores that information in a database. Next, the server uses an AI algorithm to analyze the user's living environment and needs based on the stored basic information.

[0599] The server also collects weather and disaster information in real time from external information services. Using this data, the server predicts the disaster risk in the user's area. This risk prediction is performed regularly, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays this notification to the user, allowing them to receive the necessary information.

[0600] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly processes the purchase and arranges delivery via the server.

[0601] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[0602] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. The chatbot's responses are saved as logs on the server and used to improve the quality of the service.

[0603] Hardware and software to be used

[0604] Hardware: Smartphones, head-mounted displays, wearable devices

[0605] Software and libraries: Python, Flask (web framework), AI analysis algorithms (e.g., TensorFlow, Scikit-learn), databases (e.g., PostgreSQL, MongoDB)

[0606] Examples of specific cases and prompt statements

[0607] As a concrete example, a user opens the application and enters basic information. The server analyzes this information and, if it recognizes that the disaster risk is high in Tokyo, sends the user a push notification with a list of emergency food supplies and flashlights. Furthermore, based on data from the user's wearable device, if a lack of exercise is detected, it recommends exercise equipment and nutritional supplements.

[0608] Example of a prompt:

[0609] "My name is Taro Yamada. I'm 30 years old and currently live in Tokyo. Do you have any recommendations for health products or everyday necessities these days?"

[0610] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0611] Step 1:

[0612] When a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). Once the user submits the entered basic information, the device sends it to the server.

[0613] Input: Basic information such as name, age, gender, and address.

[0614] Data processing: Convert input data to JSON format.

[0615] Output: Basic information in JSON format sent to the server

[0616] Step 2:

[0617] The server stores the received basic information in a database. After this storage process, the server uses an AI algorithm to analyze the user's living environment and needs based on the basic information.

[0618] Input: Basic information in JSON format

[0619] Data processing: Data storage in databases, analysis using AI algorithms.

[0620] Output: Analysis results of the user's living environment and needs

[0621] Step 3:

[0622] The server collects weather and disaster information in real time from external information services. Based on this information, the server predicts the disaster risk in the user's area.

[0623] Input: Weather data, disaster information

[0624] Data processing: Analysis of weather data and disaster information, prediction of disaster risk.

[0625] Output: Disaster risk prediction results

[0626] Step 4:

[0627] If the risk of disaster increases, the server will send push notifications or emails to users. The device will then display these notifications to the user.

[0628] Input: Disaster risk prediction results

[0629] Data processing: Creating and sending push notifications and emails.

[0630] Output: Notification sent to the user's device

[0631] Step 5:

[0632] The server recommends appropriate daily necessities based on the user's living environment, needs, and disaster risk. This is then displayed on the user's device.

[0633] Input: Analysis results of the user's living environment and needs, disaster risk prediction results

[0634] Data processing: Generating personalized product lists

[0635] Output: Product recommendation list displayed on the user's device

[0636] Step 6:

[0637] The device acquires health data such as heart rate, steps taken, and sleep duration from the user's wearable device in real time and sends it to the server.

[0638] Input: Health data from wearable devices

[0639] Data processing: Format conversion and transmission of acquired data.

[0640] Output: Health data sent to the server

[0641] Step 7:

[0642] The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on the evaluation results, it recommends the most suitable health products and nutritional supplements to the user.

[0643] Input: Health data

[0644] Data processing: Storage in a database, evaluation using AI algorithms.

[0645] Output: Recommended list of health products and nutritional supplements

[0646] Step 8:

[0647] The server provides an AI chatbot that operates 24 / 7, 365 days a year, responding to user questions and requests in real time. Users can interact with the chatbot via their devices and receive the information and support they need.

[0648] Input: Questions and requests from users

[0649] Data processing: Response generation by chatbot

[0650] Output: Real-time response to the user

[0651] Example of a prompt:

[0652] "My name is Taro Yamada. I'm 30 years old and currently live in Tokyo. Do you have any recommendations for health products or everyday necessities these days?"

[0653] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0654] This invention is an e-commerce platform that collects basic user information and health data, analyzes the user's living environment and needs, and recommends appropriate daily necessities and health products. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it provides optimal notifications and recommendations based on the user's emotional state. The following describes a specific embodiment of this system.

[0655] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Furthermore, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information.

[0656] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[0657] Furthermore, the server recommends essential goods based on the user's profile and disaster risk analysis. The recommended product list is presented to the user via the terminal, allowing the user to select the necessary items and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[0658] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[0659] Furthermore, the present invention includes an emotion engine that recognizes the user's emotional state. The emotion engine collects emotional data in real time from the user's voice, facial expressions, and entered text. The server analyzes this emotional data to identify the user's current emotional state. For example, if the user is feeling stressed, it recommends relaxation products. It can also adjust the content and frequency of notifications according to the emotional state. In this way, it provides the user with more effective and personalized support.

[0660] As a concrete example, when a user is using a smartphone, the device sends the user's voice and facial expressions to an emotion engine. Based on this data, the server determines that the user is tired and generates a list of relaxation products. The device notifies the user of this list, and the user can select and purchase the most suitable product from the list.

[0661] Furthermore, if a user regularly uses a wearable device, the device collects and transmits the user's health data to a server. The server combines this health data with emotional data to comprehensively evaluate the user's health and emotional state. For example, it might recommend exercise equipment or relaxation supplements to a user who is stressed due to lack of exercise. The user can accept these suggestions via the device and purchase products that are optimal for both their health and emotional well-being.

[0662] As described above, the present invention, by including an emotion engine, provides an e-commerce platform that offers more personalized suggestions based on the user's living environment, health condition, and emotional state, thereby supporting the user's healthy, safe, and comfortable life.

[0663] The following describes the processing flow.

[0664] Step 1:

[0665] The user accesses the SmartLife Assistant application for the first time. The device displays a form for the user to enter basic information (name, age, gender, address, etc.).

[0666] Step 2:

[0667] The user enters the required information into the form and submits it. The device sends the entered information to the server.

[0668] Step 3:

[0669] The server stores the user's basic information in a database. Furthermore, the server uses AI algorithms to analyze the stored basic information and identify the user's living environment and individual needs.

[0670] Step 4:

[0671] The server collects weather and disaster information in real time from external information services. The collected data is used to assess disaster risk.

[0672] Step 5:

[0673] The server analyzes collected weather data and disaster information to predict the disaster risk in the user's residential area. If the risk increases, the server notifies the user.

[0674] Step 6:

[0675] The device sends disaster risk notifications from the server to the user via push notification. The user checks the notification.

[0676] Step 7:

[0677] The server generates a product list to recommend the most suitable daily necessities based on the user's profile and the results of a disaster risk analysis.

[0678] Step 8:

[0679] The terminal displays the generated product list to the user. The user reviews the suggested product list and selects the desired products.

[0680] Step 9:

[0681] The user purchases the selected product. The terminal quickly processes this purchase and arranges delivery via the server.

[0682] Step 10:

[0683] The device periodically collects health data such as heart rate, steps taken, and sleep duration from the user's wearable device and sends it to the server.

[0684] Step 11:

[0685] The server stores the received health data in a database and uses an AI algorithm to evaluate the user's health status.

[0686] Step 12:

[0687] The server recommends the most suitable health products and nutritional supplements to the user based on the health assessment results. The terminal displays a list of health products and nutritional supplements to the user.

[0688] Step 13:

[0689] The device transmits the user's voice, facial expressions, and entered text to the emotion engine. The emotion engine collects emotion data in real time.

[0690] Step 14:

[0691] The server analyzes the emotional data sent from the emotion engine to identify the user's emotional state. If necessary, it adjusts the user's profile based on the evaluation results.

[0692] Step 15:

[0693] The server adjusts the content and frequency of notifications and recommendation lists based on the user's emotional state. For example, if a user is feeling stressed, it will recommend relaxation products.

[0694] Step 16:

[0695] This system provides an AI chatbot that operates 24 hours a day, 365 days a year. When a user makes a question or request, the device forwards it to the chatbot.

[0696] Step 17:

[0697] The server has the chatbot analyze the question or request and generate an appropriate response. The terminal displays the generated response to the user, allowing the user to obtain the necessary information.

[0698] Step 18:

[0699] All interactions are saved as logs on the server and used to improve the quality of the service.

[0700] (Example 2)

[0701] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0702] Traditional e-commerce platforms are limited to simple recommendation functions based on basic user information, lacking personalized suggestions that take into account users' emotional and health states. Furthermore, they fail to adequately provide urgent information, such as safety measures and health management notifications based on disaster risks. As a result, it has been difficult to support users in leading healthy, safe, and comfortable lives.

[0703] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0704] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, dialogue agent means for responding to questions and requests from the user, emotion engine means for recognizing emotional states and providing optimal notifications and recommendations, means for analyzing the user's voice, facial expressions and text and collecting emotional data, means for adjusting notification content and recommendations based on the analyzed emotional data, means for collecting health data from the user's wearable device, means for analyzing the health data and evaluating the user's health status, means for recommending health products and nutritional supplements based on the evaluation results, and means for providing an AI dialogue agent that operates 24 hours a day, 365 days a year and responding to questions and requests from the user in real time. This enables personalized suggestions based on the user's living environment, health status and emotional status, and can support the user's healthy, safe, and comfortable life.

[0705] "User basic information" refers to personal information such as the user's name, age, gender, and address.

[0706] "Analysis of living environment and needs" refers to the process of analyzing and evaluating a user's living environment and individual needs based on their basic information.

[0707] "External information provision services" refer to services that supply real-time data provided from external sources, such as weather data and disaster information.

[0708] "Disaster risk prediction" refers to the process of estimating the likelihood of a disaster occurring in a specific area based on weather data and disaster information collected from external information services.

[0709] "Means of sending notifications" refers to methods of communicating important information to users, such as predicted disaster risks.

[0710] "Means of recommending daily necessities" refers to a function that suggests the most suitable products considering the user's living environment, needs, and disaster risk.

[0711] A "conversational agent" refers to a response system equipped with artificial intelligence to handle questions and requests from users.

[0712] An "emotion engine" refers to a system that recognizes a user's emotional state and uses that information to provide notifications and product recommendations.

[0713] "Emotional data" refers to information about a user's emotions extracted from their voice, facial expressions, and entered text.

[0714] "Adjusting notification content and recommendations based on analyzed sentiment data" refers to the process of adaptively changing the content and frequency of notifications and product recommendations based on the user's emotional state.

[0715] A "wearable device" refers to a device that a user wears to measure and collect health data such as heart rate, steps taken, and sleep duration.

[0716] "Collecting health data" refers to the process of acquiring data such as heart rate, steps taken, and sleep duration from wearable devices.

[0717] "Means for evaluating a user's health status" refers to a method of comprehensively evaluating a user's health status by analyzing collected health data.

[0718] "Recommendation of health products and nutritional supplements" refers to a function that suggests the most suitable health products and nutritional supplements to the user based on evaluation results.

[0719] An "AI conversational agent" refers to a system equipped with artificial intelligence that operates 24 hours a day, 365 days a year, and responds to user questions and requests in real time.

[0720] Modes for carrying out the invention

[0721] This invention is an e-commerce platform that collects basic user information and health data, analyzes their living environment and needs, and recommends appropriate daily necessities and health products. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it provides optimal notifications and recommendations based on the user's emotional state. A specific embodiment of this system is described below.

[0722] Equipment and hardware / software used

[0723] 1. Preparing the device

[0724] The devices used by users (smartphones, tablets, PCs, etc.) are equipped with an interface for entering basic information.

[0725] Wearable devices (such as smartwatches) are used to collect users' health data in real time and transmit it to the device.

[0726] 2. Server Functions

[0727] The server has a database that collects and stores basic information entered by users and health data transmitted from wearable devices.

[0728] The server collects real-time data from external information services (such as weather data and disaster information services).

[0729] The server uses an emotion engine to analyze emotional data from the user's voice, facial expressions, and input text.

[0730] 3. Execution of the AI ​​algorithm

[0731] The AI ​​algorithm embedded in the server analyzes the user's living environment and needs based on the user's basic information, health data, and emotional data.

[0732] It analyzes weather data and disaster information collected in real time to predict disaster risks.

[0733] 4. Notification and Recommendation System

[0734] The server generates a list of appropriate daily necessities and health products based on disaster risks and user needs.

[0735] The server sends push notifications and emails to terminals, providing users with urgent notifications and product recommendations.

[0736] The device displays these notifications and recommendation lists to the user, who can respond as needed.

[0737] Specific examples and prompt statements

[0738] 1. Collection and analysis of basic information and sentiment data

[0739] Users enter basic information such as their name, age, gender, and address into a form on their smartphone and submit it.

[0740] The device sends this information to the server, where it is stored in the database.

[0741] The server collects the user's voice and facial expressions in real time and analyzes them using an emotion engine.

[0742] For example, if the system determines that the user is experiencing stress, a list of relaxation products will be generated.

[0743] Prompt example:

[0744] "Please recommend the most suitable relaxation products based on the user's basic information and current emotional state."

[0745] 2. Integrated analysis of health data and emotional data

[0746] Data such as heart rate, steps taken, and sleep duration are transmitted to the device from smartwatches and other devices that the user uses daily.

[0747] The terminal sends this data to the server, which then analyzes the data.

[0748] The server combines health data and emotional data to assess the user's health and emotional state and recommend appropriate health products and nutritional supplements.

[0749] Prompt example:

[0750] "Based on real-time health and emotional data, please suggest appropriate nutritional supplements to users."

[0751] The goal of this system is to support users in leading healthy, safe, and comfortable lives by providing more personalized suggestions based on their living environment, health status, and emotional state, through the inclusion of an emotion engine. Users will be able to respond quickly and accurately through emergency notifications based on disaster risk and personalized product recommendations.

[0752] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0753] Step 1:

[0754] Gathering basic information

[0755] When a user accesses the site for the first time, they enter basic information such as their name, age, gender, and address into a form that appears on their device.

[0756] Input: Basic user information such as name, age, gender, and address.

[0757] The terminal sends the basic information entered by the user to the server.

[0758] The server stores this information in the database.

[0759] Output: Basic user information stored in the database.

[0760] Step 2:

[0761] Analysis of living environment and needs

[0762] The server uses an AI algorithm to analyze basic user information obtained from the database.

[0763] Input: Basic user information stored in the database.

[0764] The server uses an AI model to analyze patterns in living environments and needs.

[0765] Output: Analytical data regarding the user's living environment and needs.

[0766] Step 3:

[0767] Real-time data collection

[0768] The server collects weather data and disaster information in real time from external information provision services.

[0769] Input: Weather data and disaster information obtained from external information provision services.

[0770] The server stores this information in a database and performs the necessary data processing.

[0771] Output: Real-time data stored in the database.

[0772] Step 4:

[0773] Predicting disaster risks

[0774] The server uses real-time data to predict the disaster risk in the user's residential area using an AI algorithm.

[0775] Input: Real-time data, user's residential area information.

[0776] The server analyzes weather data and disaster information and outputs the likelihood of a disaster occurring in a specific area.

[0777] Output: Disaster risk prediction results.

[0778] Step 5:

[0779] Sending an emergency notification

[0780] The server generates emergency notifications for users based on the predicted disaster risk.

[0781] Input: Disaster risk prediction results.

[0782] The terminal displays emergency notifications sent from the server to the user.

[0783] Output: Emergency notification displayed to the user.

[0784] Step 6:

[0785] Recommendations for daily necessities

[0786] The server uses an AI algorithm to recommend the most suitable daily necessities based on the user's basic information, living environment, needs, and disaster risk.

[0787] Input: User's basic information, living environment, needs, and disaster risk.

[0788] The server uses an AI model to generate a product list tailored to the user.

[0789] The terminal displays the generated product list to the user.

[0790] Output: A list of recommended daily necessities displayed to the user.

[0791] Step 7:

[0792] Purchase procedure

[0793] The user selects the desired product from the provided product list.

[0794] Input: The product selected by the user.

[0795] The terminal completes the purchase process and arranges for delivery via the server.

[0796] Output: Purchased items for which shipping arrangements have been completed.

[0797] Step 8:

[0798] Collection of health data

[0799] The device collects health data such as heart rate, steps taken, and sleep duration from the user's wearable devices.

[0800] Input: Health data collected from wearable devices.

[0801] The device sends the collected health data to the server.

[0802] Output: Health data stored on the server.

[0803] Step 9:

[0804] Health status assessment

[0805] The server analyzes the collected health data using an AI algorithm to assess the user's health status.

[0806] Input: Health data collected from wearable devices.

[0807] The server analyzes health data and outputs an overall health assessment.

[0808] Output: User health assessment results.

[0809] Step 10:

[0810] Recommendations for health products and nutritional supplements

[0811] Based on the health assessment results, the server uses an AI model to recommend the most suitable health products and nutritional supplements to the user.

[0812] Input: User's health assessment results.

[0813] The server generates a list of the most suitable products and sends it to the terminal.

[0814] The device displays these product lists to the user.

[0815] Output: A list of recommended health products and nutritional supplements displayed to the user.

[0816] Step 11:

[0817] Recognition of emotional states by an emotion engine

[0818] The device runs an emotion engine that collects emotional data from the user's voice, facial expressions, and entered text.

[0819] Input: User's voice, facial expressions, and text data.

[0820] The device sends the collected emotional data to the server, which then analyzes it.

[0821] Output: Analyzed user sentiment data.

[0822] Step 12:

[0823] Adjusting notifications and recommendations based on emotions

[0824] The server adjusts notification content and recommendations based on the analyzed sentiment data.

[0825] Input: Analyzed sentiment data, user profile information.

[0826] The server uses sentiment data to provide notifications and product recommendations tailored to the user's needs.

[0827] The device displays this customized information to the user.

[0828] Output: Customized notifications and recommendations displayed to the user.

[0829] Using the above procedure, this system provides personalized suggestions based on the user's living environment, health condition, and emotional state, supporting a healthy, safe, and comfortable life.

[0830] (Application Example 2)

[0831] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0832] Traditional e-commerce platforms can collect basic user information and health data and recommend products based on lifestyle and needs, but they have a challenge in providing appropriate product recommendations that respond to users' emotional states and real-time situations. In particular, when users are feeling stressed or fatigued, the platform may fail to recommend products that are appropriate to their emotions, raising concerns about decreased user satisfaction and perceived value. Against this backdrop, there is a need for more accurate and personalized product recommendations through comprehensive data analysis that includes users' emotional states.

[0833] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, means for collecting and analyzing emotional data from the user's voice, facial expressions, text input, and wearable devices, means for evaluating the user's emotional state based on the emotional data and recommending products and services that are appropriate to the emotional state, means for displaying recommended products and services through a user interface and supporting the purchase procedure, and chatbot means for responding to questions and requests from the user. This enables more accurate personalized product recommendations based on a comprehensive analysis of the user's basic information, health data, and emotional state.

[0834] "Basic user information" refers to data necessary to identify an individual user and understand their living environment and needs, such as name, age, gender, and address.

[0835] "Living environment" refers to all information related to the user's daily life, including the characteristics of the area where the user lives, their lifestyle habits, and their work environment.

[0836] "Needs" refer to the user's demands, desires, and necessities, and they change based on the user's living environment and circumstances.

[0837] "Weather data" refers to information about the climate of a specific region, such as weather forecasts, temperature, precipitation, and wind speed.

[0838] "Disaster information" refers to real-time data on natural disasters such as earthquakes, typhoons, heavy rains, and floods.

[0839] "Disaster risk" refers to the probability of a natural disaster occurring and the extent of its impact, as predicted based on collected weather data and disaster information.

[0840] A "notification" is an alert or message sent to a user's device to convey important information or recommendations.

[0841] "Daily necessities" are goods and services that are necessary to support the daily lives of users.

[0842] "Recommendation" refers to the act of suggesting the most suitable products or services based on the user's living environment, needs, disaster risks, etc.

[0843] "Voice data" refers to information about a user's speech and voice, and is collected using speech recognition technology.

[0844] "Facial expression data" refers to emotional information obtained by analyzing a user's facial expressions, and is collected through devices such as cameras.

[0845] "Text input" refers to character information entered by the user through keyboard input or a touch interface.

[0846] A "wearable device" is an electronic device worn by the user that provides health and activity data in real time.

[0847] "Emotional data" refers to information that indicates a user's emotional state, obtained from sources such as voice, facial expressions, and text input.

[0848] "Analysis" is the process of examining collected data to derive specific patterns or conclusions.

[0849] "Evaluation" is the act of judging a user's health and emotional state based on information obtained through analysis.

[0850] A "user interface" refers to the screens and operating methods that allow the user and the system to interact directly.

[0851] A "chatbot" is automated software that uses artificial intelligence to interact with humans in natural language and respond to questions and requests.

[0852] This invention is a system that comprehensively evaluates a user's basic information, health data, and emotional data to recommend personalized products and services. Specific embodiments for carrying out this invention are described below.

[0853] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Based on the stored basic information, the server uses an AI algorithm to analyze the user's living environment and individual needs.

[0854] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[0855] Furthermore, the server recommends essential goods based on the user's profile and disaster risk analysis. The recommended product list is presented to the user via the terminal, allowing the user to select the necessary items and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[0856] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this list of products to the user.

[0857] Furthermore, the present invention includes an emotion engine that recognizes the user's emotional state. The emotion engine collects emotional data in real time from the user's voice, facial expressions, and entered text. The server analyzes this emotional data to identify the user's current emotional state. For example, if the user is feeling stressed, it recommends relaxation products. It can also adjust the content and frequency of notifications according to the emotional state. In this way, it provides the user with more effective and personalized support.

[0858] As a concrete example, when a user is wearing smart glasses, the device sends the user's voice and facial expressions to an emotion engine. Based on this data, the server determines that the user is tired and generates a list of relaxation products. The device notifies the user of this list, and the user can select and purchase the most suitable product from the list. Also, if a user uses a wearable device on a daily basis, the device collects the user's health data and sends it to the server. The server combines the health data and emotion data to comprehensively evaluate the user's health and emotional state. For example, it might recommend exercise equipment or relaxation supplements to a user who is stressed due to lack of exercise. The user can accept these suggestions via the device and purchase the most suitable products from both a health and emotional perspective.

[0859] The main hardware used includes smart glasses, microphones, cameras, and wearable devices. The main software used includes FaceAPI, SpeechAPI, Bluetooth SDK, TensorFlow, PyTorch, Recommendation Engine API, React Native, and Flutter.

[0860] Example input prompts for a generative AI model:

[0861] "If the camera detects that the user has a tired expression, it will recommend relaxation products."

[0862] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0863] Step 1:

[0864] When a user accesses the system for the first time, the terminal displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The entered information is sent to the server via the terminal, and the server stores this information in a database. As part of the input data processing, the data format is standardized and errors are checked. The output is the formatted basic information stored in the database.

[0865] Step 2:

[0866] The server uses stored basic information and AI algorithms to analyze the user's living environment and needs. The AI ​​algorithms used perform personalized analysis based on the user's attribute information. The input data is the user's basic information, and the output is an analysis result showing the user's living environment and individual needs. Statistical models and machine learning models are applied to process the data for analysis.

[0867] Step 3:

[0868] The server collects weather and disaster information in real time from external information services. This is done via a RESTful API. The input is data obtainable from the API endpoints of external services, and the output is weather data and disaster information. Data ingestion and formatting are performed.

[0869] Step 4:

[0870] The server predicts the disaster risk in the user's area based on collected weather data and disaster information. This prediction is performed periodically, and an AI model is used to assess the risk. The input data consists of weather data and disaster information, and the output is the disaster risk assessment result. Data processing includes time series data analysis and the application of risk models.

[0871] Step 5:

[0872] When risk increases, the server sends important safety notifications to users via push notifications or email. The input data is the disaster risk assessment results, and the output is the content of the push notifications or emails. Specific operations include generating notification content and sending it to the user's device.

[0873] Step 6:

[0874] The server recommends the most suitable daily necessities based on the user's profile and disaster risk analysis results. The recommendation system uses the user's attribute information, needs, and disaster risk as input to generate a recommendation list. The output is a list of recommended daily necessities. As part of the data processing, a recommendation engine is applied.

[0875] Step 7:

[0876] The terminal presents the user with a list of recommended products, allowing the user to select the desired items from the list and proceed with the purchase. The input data is the recommended product list, and the output is the user's selected products and their purchase procedure information. Specifically, it provides a GUI presentation and support for the purchase flow.

[0877] Step 8:

[0878] The terminal acquires health data such as heart rate, steps, and sleep duration in real time from the user's wearable device and transmits it to the server. The input data is the health data acquired from the wearable device, and the output is the health data transmitted to the server. Specific operations include establishing Bluetooth communication and acquiring data.

[0879] Step 9:

[0880] The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. The input data is health data, and the output is the evaluation result of the health status. As a data calculation, a health model is applied and evaluated.

[0881] Step 10:

[0882] Based on the evaluation results, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user. The input data is the results of the health status evaluation, and the output is a list of recommended health products. Specifically, notifications are generated and displayed on the screen.

[0883] Step 11:

[0884] The device collects emotional data in real time from the user's voice, facial expressions, and text input, and sends it to the server. Input data includes voice, facial expressions, and text data, while output is the emotional data sent to the server. Specific operations include voice recognition and facial expression analysis.

[0885] Step 12:

[0886] The server analyzes emotional data to identify the user's current emotional state. The input data is emotional data, and the output is an evaluation of the emotional state. The emotional analysis engine is applied as part of the data processing.

[0887] Step 13:

[0888] This system recommends products and services that are appropriate to the user's emotional state. The input data is an evaluation of the emotional state, and the output is a list of recommended products and services. Specifically, it generates recommendations based on the user's emotions.

[0889] Step 14:

[0890] This system displays recommended products and services through a user interface and supports the purchase process. The input data is a list of recommended products and services, and the output is information confirming the completion of the purchase process. Specific actions include displaying the purchase screen and supporting the purchase flow.

[0891] Step 15:

[0892] This system provides a chatbot mechanism to handle user questions and requests, and provides real-time responses to those requests. Input data consists of user questions and requests, and output is the chatbot's response data. Specifically, it performs natural language processing and response generation.

[0893] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0894] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0895] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0896] [Third Embodiment]

[0897] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0898] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0899] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0900] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0901] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0902] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0903] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0904] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0905] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0906] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0907] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0908] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0909] This invention provides an e-commerce platform that collects basic user information, analyzes their living environment and needs, and proposes personalized daily necessities and health products. Specific embodiments of this system are described below.

[0910] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Furthermore, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information.

[0911] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[0912] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[0913] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[0914] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. The chatbot's responses are saved as logs on the server and used to improve the quality of the service.

[0915] As a concrete example, consider a user who lives in Tokyo. The server obtains information from weather data indicating that a typhoon is approaching Tokyo and assesses the disaster risk as high. Based on this assessment, the server sends the user a push notification with a list of disaster preparedness items such as emergency food, flashlights, and battery packs. The user checks the received notification, selects the necessary items, and purchases them. In this way, the user can prepare for disaster risks.

[0916] Furthermore, if a user regularly uses a wearable device, the device collects and sends data such as the user's heart rate, steps taken, and sleep duration to a server. The server analyzes this data to recognize if the user has recently been lacking exercise and recommends exercise equipment and nutritional supplements. Users can accept these suggestions via the device and purchase products to maintain their health.

[0917] As described above, the present invention provides an e-commerce platform that supports a healthy and safe lifestyle by making personalized suggestions based on the user's living environment and needs.

[0918] The following describes the processing flow.

[0919] Step 1:

[0920] The user accesses the SmartLife Assistant application for the first time. The device displays a form for the user to enter basic information (name, age, gender, address, etc.).

[0921] Step 2:

[0922] The user enters the required information into the form and submits it. The device sends the entered information to the server.

[0923] Step 3:

[0924] The server stores the user's basic information in a database. Furthermore, the server uses AI algorithms to analyze the stored basic information and identify the user's living environment and individual needs.

[0925] Step 4:

[0926] The server collects weather and disaster information in real time from external information services. This information is used to assess disaster risk.

[0927] Step 5:

[0928] The server analyzes collected weather data and disaster information to predict the disaster risk in the user's residential area. If the risk increases, the server notifies the user.

[0929] Step 6:

[0930] The device sends disaster risk notifications from the server to the user via push notification, and the user confirms the notification.

[0931] Step 7:

[0932] The server generates a product list to recommend the most suitable daily necessities based on the user's profile and the results of a disaster risk analysis.

[0933] Step 8:

[0934] The terminal displays the generated product list to the user. The user reviews the suggested product list and selects the desired products.

[0935] Step 9:

[0936] The user purchases the selected product. The terminal quickly processes this purchase and arranges delivery via the server.

[0937] Step 10:

[0938] The device periodically collects health data such as heart rate, steps taken, and sleep duration from the user's wearable device and sends it to the server.

[0939] Step 11:

[0940] The server stores the received health data in a database and uses an AI algorithm to evaluate the user's health status.

[0941] Step 12:

[0942] The server recommends the most suitable health products and nutritional supplements to the user based on the health assessment results. The terminal displays a list of health products and nutritional supplements to the user.

[0943] Step 13:

[0944] This system provides an AI chatbot that operates 24 hours a day, 365 days a year. When a user makes a question or request, the device forwards it to the chatbot.

[0945] Step 14:

[0946] The server has the chatbot analyze the question or request and generate an appropriate response. The terminal displays the generated response to the user, allowing the user to obtain the necessary information.

[0947] Step 15:

[0948] All interactions are saved as logs on the server and used to improve the quality of the service.

[0949] (Example 1)

[0950] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0951] Traditional e-commerce platforms lack sufficient mechanisms to provide personalized suggestions tailored to individual user needs and living environments, particularly lacking advanced analysis such as disaster risk prediction and health status assessment. This makes comprehensive life support difficult for users, potentially leading to shortcomings in emergencies and health management. Furthermore, the lack of mechanisms to respond to user questions and requests in real time hinders the improvement of the user experience.

[0952] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0953] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting usage data from external information provision services, means for predicting disaster risk based on the usage data, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate products based on the living environment and needs and disaster risk, and dialogue interface means for responding to questions and requests from the user. This enables personalized suggestions that are tailored to the individual user's needs and living environment. Furthermore, it can provide comprehensive life support through disaster risk prediction and health status assessment. In addition, the user experience can be improved by responding to user questions and requests in real time.

[0954] "Basic information" refers to information such as the user's name, age, gender, and address, which is used to identify the user and understand their individual needs.

[0955] "Living environment" refers to factors that influence a user's daily life, such as their place of residence, family structure, and lifestyle habits.

[0956] "Needs" refer to the demands and desires for products and services that users require.

[0957] "Information provision services" refer to services that supply external data such as weather data, disaster information, and health data.

[0958] "Usage data" refers to data collected from external information provision services, such as weather data and disaster information.

[0959] "Disaster risk" refers to the risks that a particular region or user may face, based on weather data and disaster information.

[0960] "Notifications" refer to information or warning messages sent to users.

[0961] "Products" refer to items that meet the user's needs, including daily necessities and health products recommended by the user.

[0962] A "dialogue interface" refers to chatbots and other dialogue systems used to respond to user questions and requests.

[0963] A "biometric data acquisition device" refers to a wearable device used to acquire health data such as the user's heart rate, steps taken, and sleep duration.

[0964] "Health data" refers to data that indicates the user's health status, such as heart rate, steps taken, and sleep duration.

[0965] "Health status" refers to the user's current physical and mental health condition.

[0966] "Health-related products" refer to products such as supplements and fitness equipment that are recommended according to the user's health condition.

[0967] An "AI dialogue system" refers to a system that uses artificial intelligence to operate 24 hours a day, 365 days a year, and respond to user questions and requests in real time.

[0968] This invention is a system that collects basic user information, analyzes their living environment and needs, and proposes personalized daily necessities and health products. Specific embodiments of this system are described below.

[0969] First, when a user accesses the system for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which then stores that information in a database. As a specific example, the device displays an HTML form, and when the submit button is pressed, it sends the data to the server in JSON format. The server parses the received JSON data and executes an SQL query to save it to the database.

[0970] Next, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information. Specifically, the server periodically runs the AI ​​algorithm, using the user profile information as arguments to analyze the living environment and needs. The analysis results are stored in a database in preparation for the next recommendation process.

[0971] The server also collects weather and disaster information in real time from external information services. Based on this data, it predicts the disaster risk in the user's residential area. When the risk increases, the server generates push notifications or emails to notify the user. The device displays the received notification to the user. Specifically, the server periodically retrieves weather data using an API and performs data analysis using an automated script. If the risk is determined to be high, it generates a notification message and notifies the user via push notifications or email sending APIs.

[0972] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly completes this purchase process and arranges delivery via the server. Specifically, the server runs the recommendation engine and sends the generated product list to the terminal in JSON format. The terminal updates the UI, allowing the user to select products and proceed with the purchase. The purchase information is sent back to the server, which then coordinates with the logistics system to arrange delivery.

[0973] This system also acquires health data such as heart rate, steps, and sleep duration from the user's wearable device in real time and sends it to a server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation, the server recommends the most suitable health products and nutritional supplements to the user, and the device displays this product list to the user. Specifically, the device acquires data from the wearable device using Bluetooth or Wi-Fi and sends it to the server periodically. The server analyzes the received data, generates a health report, and creates a list of recommended products.

[0974] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. Specifically, a user's question is sent to the server via the terminal, and the AI ​​chatbot generates a response using a natural language processing model, which is returned to the user in real time. At the same time, the response content is saved as a log and used to improve service quality.

[0975] For example, if a typhoon is approaching the user's area, the server will assess the disaster risk based on weather data and generate a list of recommended disaster preparedness items such as emergency food and flashlights, notifying the user. The user can then review the list, select the necessary items, and proceed with the purchase. Furthermore, for the user's daily health management, data collected from wearable devices can be analyzed to recommend appropriate health products.

[0976] Example of a prompt:

[0977] 1. "Please send the entered information to the server and save it to the database."

[0978] 2. "Analyze the user's basic information and generate a list of recommended daily necessities and health products."

[0979] 3. "Predict the disaster risk in Tokyo and send a list of disaster preparedness supplies via push notification."

[0980] 4. "Analyze the collected health data and suggest the most suitable health products for the user."

[0981] 5. "Use an AI chatbot to respond to user inquiries in real time."

[0982] As described above, the present invention provides a system that supports a healthy and safe life by making personalized suggestions based on the user's living environment and needs.

[0983] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0984] Step 1:

[0985] Gathering basic information

[0986] Terminal: When the user first accesses the service, a form is displayed for them to enter basic information such as name, age, gender, and address. Input: Input fields of the HTML form. Output: JSON data after the submit button is pressed.

[0987] User: Enter the required information into the form and press the submit button. Input: Basic information such as name, age, gender, and address. Output: Data transmission upon clicking the submit button.

[0988] Terminal: Sends the entered information to the server. Specifically, the terminal performs error checking and converts the data to JSON format. Input: Basic information entered by the user. Output: JSON data.

[0989] Server: Stores received information in the database. Inserts information using SQL queries. Input: JSON data. Output: Database update.

[0990] Step 2:

[0991] Analysis of living environment and needs

[0992] Server: Uses an AI algorithm to analyze the user's living environment and needs based on basic user information stored in the database. Input: Basic user information obtained from the database. Output: Analysis result data.

[0993] Server: Saves analysis results to the database and prepares for the next recommendation process. Specifically, the server calls the AI ​​module and inserts the analysis results into the database as an SQL query. Input: Analysis result data. Output: Database update.

[0994] Step 3:

[0995] Predicting disaster risks

[0996] Server: Collects weather and disaster information in real time from external information services. Input: API requests. Output: Weather data and disaster information.

[0997] Server: Predicts disaster risk in the user's residential area based on acquired data. Input: Weather data, disaster information, user's address. Output: Disaster risk assessment results.

[0998] Server: When risk increases, it generates push notifications and emails to notify users. Specifically, it generates notification messages and uses push notification APIs and email sending APIs. Input: Disaster risk assessment results. Output: Notification messages, push notifications, emails.

[0999] Step 4:

[1000] Product Recommendation and Purchase Procedure

[1001] Server: Recommends appropriate daily necessities based on user profiles and disaster risk analysis results. Input: User profile, disaster risk assessment results. Output: List of recommended products.

[1002] Terminal: Presents a list of recommended products to the user. Input: Product list received from the server. Output: Product list displayed to the user.

[1003] User: Selects the desired items from the presented list and proceeds with the purchase. Input: User selection. Output: Purchase information.

[1004] Terminal: Sends purchase information to the server, which then arranges delivery. Specifically, the terminal converts the purchase information into JSON format and sends it to the server. Input: User's purchase information. Output: Data sent to the server.

[1005] Server: Receives purchase information and coordinates with the logistics system to arrange delivery. Input: Purchase information. Output: Delivery arrangement.

[1006] Step 5:

[1007] Health data collection and product recommendations

[1008] Terminal: Acquires health data such as heart rate, steps, and sleep duration in real time from the user's wearable device. Input: Data from the wearable device. Output: Health data.

[1009] Terminal: Sends acquired health data to the server. Specifically, it collects data using Bluetooth or Wi-Fi and periodically sends it to the server. Input: Health data. Output: Data transmission to the server.

[1010] Server: Stores received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Input: Health data. Output: Evaluation results.

[1011] Server: Based on evaluation results, it recommends the most suitable health products and nutritional supplements to the user. Specifically, it uses an AI module to perform evaluations and generate a list of appropriate products. Input: Evaluation results. Output: Recommended list of health products.

[1012] Terminal: Displays a list of recommended products to the user. Input: Product list received from the server. Output: Product list displayed to the user.

[1013] Step 6:

[1014] AI chatbot support

[1015] Server: Provides an AI chatbot that operates 24 / 7. Input: User questions and requests from the terminal. Output: Chatbot's response.

[1016] User: Interacts with the chatbot via their device and sends questions and requests. Input: User's questions and requests. Output: Chatbot's response display.

[1017] Server: The chatbot uses an AI model to respond to user questions. Specifically, it uses a natural language processing model to analyze user input and generate an appropriate response. Input: User's question. Output: Chatbot's response.

[1018] Server: Saves response content to logs to improve service quality. Input: Chatbot response. Output: Log data.

[1019] (Application Example 1)

[1020] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1021] Modern consumers have diverse needs and individual lifestyles, requiring personalized product recommendations tailored to their specific circumstances. However, conventional systems struggle to achieve this efficiently. Furthermore, there is a lack of means to monitor disaster risks and health conditions in real time and provide appropriate products based on that information. In addition, support systems capable of responding to user inquiries at any time are inadequate. To address these challenges, a system is needed that provides advanced data collection, analysis, product recommendations, and real-time support.

[1022] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1023] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, means for linking with a wearable device to collect and analyze the user's health data, means for displaying personalized product recommendations in a virtual store, and chatbot means for responding to questions and requests from the user. This enables personalized product recommendations and appropriate support that meet the diverse needs of the user.

[1024] "Means of collecting basic user information" refers to a system that allows users to input personal information such as their name, age, gender, and address via a terminal and transmit it to a server.

[1025] "Means for analyzing the user's living environment and needs based on the aforementioned basic information" refers to a process for determining the user's lifestyle patterns and individual needs using an AI algorithm based on the collected basic information.

[1026] "Means of collecting weather data and disaster information from external information provision services" refers to technologies for obtaining weather data and disaster information in real time via the internet.

[1027] "Means for predicting disaster risk based on the aforementioned weather data and disaster information" refers to a method for analyzing acquired weather data and disaster information to predict the risk of disaster occurrence in a specific area.

[1028] "Means for sending notifications to users based on the predicted disaster risk" refers to a function that sends warnings to users' devices via push notifications or email when the disaster risk increases.

[1029] "Means for recommending appropriate daily necessities based on the aforementioned living environment, needs, and disaster risk" refers to an algorithm that selects and recommends necessary daily necessities to the user based on the user's profile and disaster risk analysis.

[1030] A "wearable device integration method for collecting and analyzing user health data" is a system that acquires health data such as heart rate, steps taken, and sleep duration in real time from wearable devices worn by the user, and analyzes this data.

[1031] "A means of displaying personalized product recommendations in a virtual store" refers to a function that displays the most suitable products for each individual user in a virtual space, taking into account the user's basic information, living environment, needs, disaster risk, and health data.

[1032] A "chatbot tool for responding to user questions and requests" is an AI chatbot that responds to user questions and requests via their device in real time, 24 hours a day, 365 days a year.

[1033] This invention relates to a virtual store system that collects basic user information, analyzes their living environment and needs, and recommends personalized products. Specific embodiments of this system are described below.

[1034] First, when a user accesses the virtual store application for the first time, the terminal displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The terminal sends the submitted information to the server, which stores that information in a database. Next, the server uses an AI algorithm to analyze the user's living environment and needs based on the stored basic information.

[1035] The server also collects weather and disaster information in real time from external information services. Using this data, the server predicts the disaster risk in the user's area. This risk prediction is performed regularly, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays this notification to the user, allowing them to receive the necessary information.

[1036] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly processes the purchase and arranges delivery via the server.

[1037] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[1038] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. The chatbot's responses are saved as logs on the server and used to improve the quality of the service.

[1039] Hardware and software to be used

[1040] Hardware: Smartphones, head-mounted displays, wearable devices

[1041] Software and libraries: Python, Flask (web framework), AI analysis algorithms (e.g., TensorFlow, Scikit-learn), databases (e.g., PostgreSQL, MongoDB)

[1042] Examples of specific cases and prompt statements

[1043] As a concrete example, a user opens the application and enters basic information. The server analyzes this information and, if it recognizes that the disaster risk is high in Tokyo, sends the user a push notification with a list of emergency food supplies and flashlights. Furthermore, based on data from the user's wearable device, if a lack of exercise is detected, it recommends exercise equipment and nutritional supplements.

[1044] Example of a prompt:

[1045] "My name is Taro Yamada. I'm 30 years old and currently live in Tokyo. Do you have any recommendations for health products or everyday necessities these days?"

[1046] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1047] Step 1:

[1048] When a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). Once the user submits the entered basic information, the device sends it to the server.

[1049] Input: Basic information such as name, age, gender, and address.

[1050] Data processing: Convert input data to JSON format.

[1051] Output: Basic information in JSON format sent to the server

[1052] Step 2:

[1053] The server stores the received basic information in a database. After this storage process, the server uses an AI algorithm to analyze the user's living environment and needs based on the basic information.

[1054] Input: Basic information in JSON format

[1055] Data processing: Data storage in databases, analysis using AI algorithms.

[1056] Output: Analysis results of the user's living environment and needs

[1057] Step 3:

[1058] The server collects weather and disaster information in real time from external information services. Based on this information, the server predicts the disaster risk in the user's area.

[1059] Input: Weather data, disaster information

[1060] Data processing: Analysis of weather data and disaster information, prediction of disaster risk.

[1061] Output: Disaster risk prediction results

[1062] Step 4:

[1063] If the risk of disaster increases, the server will send push notifications or emails to users. The device will then display these notifications to the user.

[1064] Input: Disaster risk prediction results

[1065] Data processing: Creating and sending push notifications and emails.

[1066] Output: Notification sent to the user's device

[1067] Step 5:

[1068] The server recommends appropriate daily necessities based on the user's living environment, needs, and disaster risk. This is then displayed on the user's device.

[1069] Input: Analysis results of the user's living environment and needs, disaster risk prediction results

[1070] Data processing: Generating personalized product lists

[1071] Output: Product recommendation list displayed on the user's device

[1072] Step 6:

[1073] The device acquires health data such as heart rate, steps taken, and sleep duration from the user's wearable device in real time and sends it to the server.

[1074] Input: Health data from wearable devices

[1075] Data processing: Format conversion and transmission of acquired data.

[1076] Output: Health data sent to the server

[1077] Step 7:

[1078] The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on the evaluation results, it recommends the most suitable health products and nutritional supplements to the user.

[1079] Input: Health data

[1080] Data processing: Storage in a database, evaluation using AI algorithms.

[1081] Output: Recommended list of health products and nutritional supplements

[1082] Step 8:

[1083] The server provides an AI chatbot that operates 24 / 7, 365 days a year, responding to user questions and requests in real time. Users can interact with the chatbot via their devices and receive the information and support they need.

[1084] Input: Questions and requests from users

[1085] Data processing: Response generation by chatbot

[1086] Output: Real-time response to the user

[1087] Example of a prompt:

[1088] "My name is Taro Yamada. I'm 30 years old and currently live in Tokyo. Do you have any recommendations for health products or everyday necessities these days?"

[1089] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1090] This invention is an e-commerce platform that collects basic user information and health data, analyzes the user's living environment and needs, and recommends appropriate daily necessities and health products. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it provides optimal notifications and recommendations based on the user's emotional state. The following describes a specific embodiment of this system.

[1091] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Furthermore, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information.

[1092] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[1093] Furthermore, the server recommends essential goods based on the user's profile and disaster risk analysis. The recommended product list is presented to the user via the terminal, allowing the user to select the necessary items and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[1094] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[1095] Furthermore, the present invention includes an emotion engine that recognizes the user's emotional state. The emotion engine collects emotional data in real time from the user's voice, facial expressions, and entered text. The server analyzes this emotional data to identify the user's current emotional state. For example, if the user is feeling stressed, it recommends relaxation products. It can also adjust the content and frequency of notifications according to the emotional state. In this way, it provides the user with more effective and personalized support.

[1096] As a concrete example, when a user is using a smartphone, the device sends the user's voice and facial expressions to an emotion engine. Based on this data, the server determines that the user is tired and generates a list of relaxation products. The device notifies the user of this list, and the user can select and purchase the most suitable product from the list.

[1097] Furthermore, if a user regularly uses a wearable device, the device collects and transmits the user's health data to a server. The server combines this health data with emotional data to comprehensively evaluate the user's health and emotional state. For example, it might recommend exercise equipment or relaxation supplements to a user who is stressed due to lack of exercise. The user can accept these suggestions via the device and purchase products that are optimal for both their health and emotional well-being.

[1098] As described above, the present invention, by including an emotion engine, provides an e-commerce platform that offers more personalized suggestions based on the user's living environment, health condition, and emotional state, thereby supporting the user's healthy, safe, and comfortable life.

[1099] The following describes the processing flow.

[1100] Step 1:

[1101] The user accesses the SmartLife Assistant application for the first time. The device displays a form for the user to enter basic information (name, age, gender, address, etc.).

[1102] Step 2:

[1103] The user enters the required information into the form and submits it. The device sends the entered information to the server.

[1104] Step 3:

[1105] The server stores the user's basic information in a database. Furthermore, the server uses AI algorithms to analyze the stored basic information and identify the user's living environment and individual needs.

[1106] Step 4:

[1107] The server collects weather and disaster information in real time from external information services. The collected data is used to assess disaster risk.

[1108] Step 5:

[1109] The server analyzes collected weather data and disaster information to predict the disaster risk in the user's residential area. If the risk increases, the server notifies the user.

[1110] Step 6:

[1111] The device sends disaster risk notifications from the server to the user via push notification. The user checks the notification.

[1112] Step 7:

[1113] The server generates a product list to recommend the most suitable daily necessities based on the user's profile and the results of a disaster risk analysis.

[1114] Step 8:

[1115] The terminal displays the generated product list to the user. The user reviews the suggested product list and selects the desired products.

[1116] Step 9:

[1117] The user purchases the selected product. The terminal quickly processes this purchase and arranges delivery via the server.

[1118] Step 10:

[1119] The device periodically collects health data such as heart rate, steps taken, and sleep duration from the user's wearable device and sends it to the server.

[1120] Step 11:

[1121] The server stores the received health data in a database and uses an AI algorithm to evaluate the user's health status.

[1122] Step 12:

[1123] The server recommends the most suitable health products and nutritional supplements to the user based on the health assessment results. The terminal displays a list of health products and nutritional supplements to the user.

[1124] Step 13:

[1125] The device transmits the user's voice, facial expressions, and entered text to the emotion engine. The emotion engine collects emotion data in real time.

[1126] Step 14:

[1127] The server analyzes the emotional data sent from the emotion engine to identify the user's emotional state. If necessary, it adjusts the user's profile based on the evaluation results.

[1128] Step 15:

[1129] The server adjusts the content and frequency of notifications and recommendation lists based on the user's emotional state. For example, if a user is feeling stressed, it will recommend relaxation products.

[1130] Step 16:

[1131] This system provides an AI chatbot that operates 24 hours a day, 365 days a year. When a user makes a question or request, the device forwards it to the chatbot.

[1132] Step 17:

[1133] The server has the chatbot analyze the question or request and generate an appropriate response. The terminal displays the generated response to the user, allowing the user to obtain the necessary information.

[1134] Step 18:

[1135] All interactions are saved as logs on the server and used to improve the quality of the service.

[1136] (Example 2)

[1137] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1138] Traditional e-commerce platforms are limited to simple recommendation functions based on basic user information, lacking personalized suggestions that take into account users' emotional and health states. Furthermore, they fail to adequately provide urgent information, such as safety measures and health management notifications based on disaster risks. As a result, it has been difficult to support users in leading healthy, safe, and comfortable lives.

[1139] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1140] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, dialogue agent means for responding to questions and requests from the user, emotion engine means for recognizing emotional states and providing optimal notifications and recommendations, means for analyzing the user's voice, facial expressions and text and collecting emotional data, means for adjusting notification content and recommendations based on the analyzed emotional data, means for collecting health data from the user's wearable device, means for analyzing the health data and evaluating the user's health status, means for recommending health products and nutritional supplements based on the evaluation results, and means for providing an AI dialogue agent that operates 24 hours a day, 365 days a year and responding to questions and requests from the user in real time. This enables personalized suggestions based on the user's living environment, health status and emotional status, and can support the user's healthy, safe, and comfortable life.

[1141] "User basic information" refers to personal information such as the user's name, age, gender, and address.

[1142] "Analysis of living environment and needs" refers to the process of analyzing and evaluating a user's living environment and individual needs based on their basic information.

[1143] "External information provision services" refer to services that supply real-time data provided from external sources, such as weather data and disaster information.

[1144] "Disaster risk prediction" refers to the process of estimating the likelihood of a disaster occurring in a specific area based on weather data and disaster information collected from external information services.

[1145] "Means of sending notifications" refers to methods of communicating important information to users, such as predicted disaster risks.

[1146] "Means of recommending daily necessities" refers to a function that suggests the most suitable products considering the user's living environment, needs, and disaster risk.

[1147] A "conversational agent" refers to a response system equipped with artificial intelligence to handle questions and requests from users.

[1148] An "emotion engine" refers to a system that recognizes a user's emotional state and uses that information to provide notifications and product recommendations.

[1149] "Emotional data" refers to information about a user's emotions extracted from their voice, facial expressions, and entered text.

[1150] "Adjusting notification content and recommendations based on analyzed sentiment data" refers to the process of adaptively changing the content and frequency of notifications and product recommendations based on the user's emotional state.

[1151] A "wearable device" refers to a device that a user wears to measure and collect health data such as heart rate, steps taken, and sleep duration.

[1152] "Collecting health data" refers to the process of acquiring data such as heart rate, steps taken, and sleep duration from wearable devices.

[1153] "Means for evaluating a user's health status" refers to a method of comprehensively evaluating a user's health status by analyzing collected health data.

[1154] "Recommendation of health products and nutritional supplements" refers to a function that suggests the most suitable health products and nutritional supplements to the user based on evaluation results.

[1155] An "AI conversational agent" refers to a system equipped with artificial intelligence that operates 24 hours a day, 365 days a year, and responds to user questions and requests in real time.

[1156] Modes for carrying out the invention

[1157] This invention is an e-commerce platform that collects basic user information and health data, analyzes their living environment and needs, and recommends appropriate daily necessities and health products. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it provides optimal notifications and recommendations based on the user's emotional state. A specific embodiment of this system is described below.

[1158] Equipment and hardware / software used

[1159] 1. Preparing the device

[1160] The devices used by users (smartphones, tablets, PCs, etc.) are equipped with an interface for entering basic information.

[1161] Wearable devices (such as smartwatches) are used to collect users' health data in real time and transmit it to the device.

[1162] 2. Server Functions

[1163] The server has a database that collects and stores basic information entered by users and health data transmitted from wearable devices.

[1164] The server collects real-time data from external information services (such as weather data and disaster information services).

[1165] The server uses an emotion engine to analyze emotional data from the user's voice, facial expressions, and input text.

[1166] 3. Execution of the AI ​​algorithm

[1167] The AI ​​algorithm embedded in the server analyzes the user's living environment and needs based on the user's basic information, health data, and emotional data.

[1168] It analyzes weather data and disaster information collected in real time to predict disaster risks.

[1169] 4. Notification and Recommendation System

[1170] The server generates a list of appropriate daily necessities and health products based on disaster risks and user needs.

[1171] The server sends push notifications and emails to terminals, providing users with urgent notifications and product recommendations.

[1172] The device displays these notifications and recommendation lists to the user, who can respond as needed.

[1173] Specific examples and prompt statements

[1174] 1. Collection and analysis of basic information and sentiment data

[1175] Users enter basic information such as their name, age, gender, and address into a form on their smartphone and submit it.

[1176] The device sends this information to the server, where it is stored in the database.

[1177] The server collects the user's voice and facial expressions in real time and analyzes them using an emotion engine.

[1178] For example, if the system determines that the user is experiencing stress, a list of relaxation products will be generated.

[1179] Prompt example:

[1180] "Please recommend the most suitable relaxation products based on the user's basic information and current emotional state."

[1181] 2. Integrated analysis of health data and emotional data

[1182] Data such as heart rate, steps taken, and sleep duration are transmitted to the device from smartwatches and other devices that the user uses daily.

[1183] The terminal sends this data to the server, which then analyzes the data.

[1184] The server combines health data and emotional data to assess the user's health and emotional state and recommend appropriate health products and nutritional supplements.

[1185] Prompt example:

[1186] "Based on real-time health and emotional data, please suggest appropriate nutritional supplements to users."

[1187] The goal of this system is to support users in leading healthy, safe, and comfortable lives by providing more personalized suggestions based on their living environment, health status, and emotional state, through the inclusion of an emotion engine. Users will be able to respond quickly and accurately through emergency notifications based on disaster risk and personalized product recommendations.

[1188] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1189] Step 1:

[1190] Gathering basic information

[1191] When a user accesses the site for the first time, they enter basic information such as their name, age, gender, and address into a form that appears on their device.

[1192] Input: Basic user information such as name, age, gender, and address.

[1193] The terminal sends the basic information entered by the user to the server.

[1194] The server stores this information in the database.

[1195] Output: Basic user information stored in the database.

[1196] Step 2:

[1197] Analysis of living environment and needs

[1198] The server uses an AI algorithm to analyze basic user information obtained from the database.

[1199] Input: Basic user information stored in the database.

[1200] The server uses an AI model to analyze patterns in living environments and needs.

[1201] Output: Analytical data regarding the user's living environment and needs.

[1202] Step 3:

[1203] Real-time data collection

[1204] The server collects weather data and disaster information in real time from external information provision services.

[1205] Input: Weather data and disaster information obtained from external information provision services.

[1206] The server stores this information in a database and performs the necessary data processing.

[1207] Output: Real-time data stored in the database.

[1208] Step 4:

[1209] Predicting disaster risks

[1210] The server uses real-time data to predict the disaster risk in the user's residential area using an AI algorithm.

[1211] Input: Real-time data, user's residential area information.

[1212] The server analyzes weather data and disaster information and outputs the likelihood of a disaster occurring in a specific area.

[1213] Output: Disaster risk prediction results.

[1214] Step 5:

[1215] Sending an emergency notification

[1216] The server generates emergency notifications for users based on the predicted disaster risk.

[1217] Input: Disaster risk prediction results.

[1218] The terminal displays emergency notifications sent from the server to the user.

[1219] Output: Emergency notification displayed to the user.

[1220] Step 6:

[1221] Recommendations for daily necessities

[1222] The server uses an AI algorithm to recommend the most suitable daily necessities based on the user's basic information, living environment, needs, and disaster risk.

[1223] Input: User's basic information, living environment, needs, and disaster risk.

[1224] The server uses an AI model to generate a product list tailored to the user.

[1225] The terminal displays the generated product list to the user.

[1226] Output: A list of recommended daily necessities displayed to the user.

[1227] Step 7:

[1228] Purchase procedure

[1229] The user selects the desired product from the provided product list.

[1230] Input: The product selected by the user.

[1231] The terminal completes the purchase process and arranges for delivery via the server.

[1232] Output: Purchased items for which shipping arrangements have been completed.

[1233] Step 8:

[1234] Collection of health data

[1235] The device collects health data such as heart rate, steps taken, and sleep duration from the user's wearable devices.

[1236] Input: Health data collected from wearable devices.

[1237] The device sends the collected health data to the server.

[1238] Output: Health data stored on the server.

[1239] Step 9:

[1240] Health status assessment

[1241] The server analyzes the collected health data using an AI algorithm to assess the user's health status.

[1242] Input: Health data collected from wearable devices.

[1243] The server analyzes health data and outputs an overall health assessment.

[1244] Output: User health assessment results.

[1245] Step 10:

[1246] Recommendations for health products and nutritional supplements

[1247] Based on the health assessment results, the server uses an AI model to recommend the most suitable health products and nutritional supplements to the user.

[1248] Input: User's health assessment results.

[1249] The server generates a list of the most suitable products and sends it to the terminal.

[1250] The device displays these product lists to the user.

[1251] Output: A list of recommended health products and nutritional supplements displayed to the user.

[1252] Step 11:

[1253] Recognition of emotional states by an emotion engine

[1254] The device runs an emotion engine that collects emotional data from the user's voice, facial expressions, and entered text.

[1255] Input: User's voice, facial expressions, and text data.

[1256] The device sends the collected emotional data to the server, which then analyzes it.

[1257] Output: Analyzed user sentiment data.

[1258] Step 12:

[1259] Adjusting notifications and recommendations based on emotions

[1260] The server adjusts notification content and recommendations based on the analyzed sentiment data.

[1261] Input: Analyzed sentiment data, user profile information.

[1262] The server uses sentiment data to provide notifications and product recommendations tailored to the user's needs.

[1263] The device displays this customized information to the user.

[1264] Output: Customized notifications and recommendations displayed to the user.

[1265] Using the above procedure, this system provides personalized suggestions based on the user's living environment, health condition, and emotional state, supporting a healthy, safe, and comfortable life.

[1266] (Application Example 2)

[1267] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1268] Traditional e-commerce platforms can collect basic user information and health data and recommend products based on lifestyle and needs, but they have a challenge in providing appropriate product recommendations that respond to users' emotional states and real-time situations. In particular, when users are feeling stressed or fatigued, the platform may fail to recommend products that are appropriate to their emotions, raising concerns about decreased user satisfaction and perceived value. Against this backdrop, there is a need for more accurate and personalized product recommendations through comprehensive data analysis that includes users' emotional states.

[1269] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, means for collecting and analyzing emotional data from the user's voice, facial expressions, text input, and wearable devices, means for evaluating the user's emotional state based on the emotional data and recommending products and services that are appropriate to the emotional state, means for displaying recommended products and services through a user interface and supporting the purchase procedure, and chatbot means for responding to questions and requests from the user. This enables more accurate personalized product recommendations based on a comprehensive analysis of the user's basic information, health data, and emotional state.

[1270] "Basic user information" refers to data necessary to identify an individual user and understand their living environment and needs, such as name, age, gender, and address.

[1271] "Living environment" refers to all information related to the user's daily life, including the characteristics of the area where the user lives, their lifestyle habits, and their work environment.

[1272] "Needs" refer to the user's demands, desires, and necessities, and they change based on the user's living environment and circumstances.

[1273] "Weather data" refers to information about the climate of a specific region, such as weather forecasts, temperature, precipitation, and wind speed.

[1274] "Disaster information" refers to real-time data on natural disasters such as earthquakes, typhoons, heavy rains, and floods.

[1275] "Disaster risk" refers to the probability of a natural disaster occurring and the extent of its impact, as predicted based on collected weather data and disaster information.

[1276] A "notification" is an alert or message sent to a user's device to convey important information or recommendations.

[1277] "Daily necessities" are goods and services that are necessary to support the daily lives of users.

[1278] "Recommendation" refers to the act of suggesting the most suitable products or services based on the user's living environment, needs, disaster risks, etc.

[1279] "Voice data" refers to information about a user's speech and voice, and is collected using speech recognition technology.

[1280] "Facial expression data" refers to emotional information obtained by analyzing a user's facial expressions, and is collected through devices such as cameras.

[1281] "Text input" refers to character information entered by the user through keyboard input or a touch interface.

[1282] A "wearable device" is an electronic device worn by the user that provides health and activity data in real time.

[1283] "Emotional data" refers to information that indicates a user's emotional state, obtained from sources such as voice, facial expressions, and text input.

[1284] "Analysis" is the process of examining collected data to derive specific patterns or conclusions.

[1285] "Evaluation" is the act of judging a user's health and emotional state based on information obtained through analysis.

[1286] A "user interface" refers to the screens and operating methods that allow the user and the system to interact directly.

[1287] A "chatbot" is automated software that uses artificial intelligence to interact with humans in natural language and respond to questions and requests.

[1288] This invention is a system that comprehensively evaluates a user's basic information, health data, and emotional data to recommend personalized products and services. Specific embodiments for carrying out this invention are described below.

[1289] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Based on the stored basic information, the server uses an AI algorithm to analyze the user's living environment and individual needs.

[1290] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[1291] Furthermore, the server recommends essential goods based on the user's profile and disaster risk analysis. The recommended product list is presented to the user via the terminal, allowing the user to select the necessary items and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[1292] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this list of products to the user.

[1293] Furthermore, the present invention includes an emotion engine that recognizes the user's emotional state. The emotion engine collects emotional data in real time from the user's voice, facial expressions, and entered text. The server analyzes this emotional data to identify the user's current emotional state. For example, if the user is feeling stressed, it recommends relaxation products. It can also adjust the content and frequency of notifications according to the emotional state. In this way, it provides the user with more effective and personalized support.

[1294] As a concrete example, when a user is wearing smart glasses, the device sends the user's voice and facial expressions to an emotion engine. Based on this data, the server determines that the user is tired and generates a list of relaxation products. The device notifies the user of this list, and the user can select and purchase the most suitable product from the list. Also, if a user uses a wearable device on a daily basis, the device collects the user's health data and sends it to the server. The server combines the health data and emotion data to comprehensively evaluate the user's health and emotional state. For example, it might recommend exercise equipment or relaxation supplements to a user who is stressed due to lack of exercise. The user can accept these suggestions via the device and purchase the most suitable products from both a health and emotional perspective.

[1295] The main hardware used includes smart glasses, microphones, cameras, and wearable devices. The main software used includes FaceAPI, SpeechAPI, Bluetooth SDK, TensorFlow, PyTorch, Recommendation Engine API, React Native, and Flutter.

[1296] Example input prompts for a generative AI model:

[1297] "If the camera detects that the user has a tired expression, it will recommend relaxation products."

[1298] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1299] Step 1:

[1300] When a user accesses the system for the first time, the terminal displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The entered information is sent to the server via the terminal, and the server stores this information in a database. As part of the input data processing, the data format is standardized and errors are checked. The output is the formatted basic information stored in the database.

[1301] Step 2:

[1302] The server uses stored basic information and AI algorithms to analyze the user's living environment and needs. The AI ​​algorithms used perform personalized analysis based on the user's attribute information. The input data is the user's basic information, and the output is an analysis result showing the user's living environment and individual needs. Statistical models and machine learning models are applied to process the data for analysis.

[1303] Step 3:

[1304] The server collects weather and disaster information in real time from external information services. This is done via a RESTful API. The input is data obtainable from the API endpoints of external services, and the output is weather data and disaster information. Data ingestion and formatting are performed.

[1305] Step 4:

[1306] The server predicts the disaster risk in the user's area based on collected weather data and disaster information. This prediction is performed periodically, and an AI model is used to assess the risk. The input data consists of weather data and disaster information, and the output is the disaster risk assessment result. Data processing includes time series data analysis and the application of risk models.

[1307] Step 5:

[1308] When risk increases, the server sends important safety notifications to users via push notifications or email. The input data is the disaster risk assessment results, and the output is the content of the push notifications or emails. Specific operations include generating notification content and sending it to the user's device.

[1309] Step 6:

[1310] The server recommends the most suitable daily necessities based on the user's profile and disaster risk analysis results. The recommendation system uses the user's attribute information, needs, and disaster risk as input to generate a recommendation list. The output is a list of recommended daily necessities. As part of the data processing, a recommendation engine is applied.

[1311] Step 7:

[1312] The terminal presents the user with a list of recommended products, allowing the user to select the desired items from the list and proceed with the purchase. The input data is the recommended product list, and the output is the user's selected products and their purchase procedure information. Specifically, it provides a GUI presentation and support for the purchase flow.

[1313] Step 8:

[1314] The terminal acquires health data such as heart rate, steps, and sleep duration in real time from the user's wearable device and transmits it to the server. The input data is the health data acquired from the wearable device, and the output is the health data transmitted to the server. Specific operations include establishing Bluetooth communication and acquiring data.

[1315] Step 9:

[1316] The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. The input data is health data, and the output is the evaluation result of the health status. As a data calculation, a health model is applied and evaluated.

[1317] Step 10:

[1318] Based on the evaluation results, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user. The input data is the results of the health status evaluation, and the output is a list of recommended health products. Specifically, notifications are generated and displayed on the screen.

[1319] Step 11:

[1320] The device collects emotional data in real time from the user's voice, facial expressions, and text input, and sends it to the server. Input data includes voice, facial expressions, and text data, while output is the emotional data sent to the server. Specific operations include voice recognition and facial expression analysis.

[1321] Step 12:

[1322] The server analyzes emotional data to identify the user's current emotional state. The input data is emotional data, and the output is an evaluation of the emotional state. The emotional analysis engine is applied as part of the data processing.

[1323] Step 13:

[1324] This system recommends products and services that are appropriate to the user's emotional state. The input data is an evaluation of the emotional state, and the output is a list of recommended products and services. Specifically, it generates recommendations based on the user's emotions.

[1325] Step 14:

[1326] This system displays recommended products and services through a user interface and supports the purchase process. The input data is a list of recommended products and services, and the output is information confirming the completion of the purchase process. Specific actions include displaying the purchase screen and supporting the purchase flow.

[1327] Step 15:

[1328] This system provides a chatbot mechanism to handle user questions and requests, and provides real-time responses to those requests. Input data consists of user questions and requests, and output is the chatbot's response data. Specifically, it performs natural language processing and response generation.

[1329] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1330] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1331] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1332] [Fourth Embodiment]

[1333] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1334] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1335] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1336] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1337] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1338] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1339] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1340] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1341] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1342] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1343] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1344] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1345] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1346] This invention provides an e-commerce platform that collects basic user information, analyzes their living environment and needs, and proposes personalized daily necessities and health products. Specific embodiments of this system are described below.

[1347] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Furthermore, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information.

[1348] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[1349] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[1350] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[1351] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. The chatbot's responses are saved as logs on the server and used to improve the quality of the service.

[1352] As a concrete example, consider a user who lives in Tokyo. The server obtains information from weather data indicating that a typhoon is approaching Tokyo and assesses the disaster risk as high. Based on this assessment, the server sends the user a push notification with a list of disaster preparedness items such as emergency food, flashlights, and battery packs. The user checks the received notification, selects the necessary items, and purchases them. In this way, the user can prepare for disaster risks.

[1353] Furthermore, if a user regularly uses a wearable device, the device collects and sends data such as the user's heart rate, steps taken, and sleep duration to a server. The server analyzes this data to recognize if the user has recently been lacking exercise and recommends exercise equipment and nutritional supplements. Users can accept these suggestions via the device and purchase products to maintain their health.

[1354] As described above, the present invention provides an e-commerce platform that supports a healthy and safe lifestyle by making personalized suggestions based on the user's living environment and needs.

[1355] The following describes the processing flow.

[1356] Step 1:

[1357] The user accesses the SmartLife Assistant application for the first time. The device displays a form for the user to enter basic information (name, age, gender, address, etc.).

[1358] Step 2:

[1359] The user enters the required information into the form and submits it. The device sends the entered information to the server.

[1360] Step 3:

[1361] The server stores the user's basic information in a database. Furthermore, the server uses AI algorithms to analyze the stored basic information and identify the user's living environment and individual needs.

[1362] Step 4:

[1363] The server collects weather and disaster information in real time from external information services. This information is used to assess disaster risk.

[1364] Step 5:

[1365] The server analyzes collected weather data and disaster information to predict the disaster risk in the user's residential area. If the risk increases, the server notifies the user.

[1366] Step 6:

[1367] The device sends disaster risk notifications from the server to the user via push notification, and the user confirms the notification.

[1368] Step 7:

[1369] The server generates a product list to recommend the most suitable daily necessities based on the user's profile and the results of a disaster risk analysis.

[1370] Step 8:

[1371] The terminal displays the generated product list to the user. The user reviews the suggested product list and selects the desired products.

[1372] Step 9:

[1373] The user purchases the selected product. The terminal quickly processes this purchase and arranges delivery via the server.

[1374] Step 10:

[1375] The device periodically collects health data such as heart rate, steps taken, and sleep duration from the user's wearable device and sends it to the server.

[1376] Step 11:

[1377] The server stores the received health data in a database and uses an AI algorithm to evaluate the user's health status.

[1378] Step 12:

[1379] The server recommends the most suitable health products and nutritional supplements to the user based on the health assessment results. The terminal displays a list of health products and nutritional supplements to the user.

[1380] Step 13:

[1381] This system provides an AI chatbot that operates 24 hours a day, 365 days a year. When a user makes a question or request, the device forwards it to the chatbot.

[1382] Step 14:

[1383] The server has the chatbot analyze the question or request and generate an appropriate response. The terminal displays the generated response to the user, allowing the user to obtain the necessary information.

[1384] Step 15:

[1385] All interactions are saved as logs on the server and used to improve the quality of the service.

[1386] (Example 1)

[1387] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1388] Traditional e-commerce platforms lack sufficient mechanisms to provide personalized suggestions tailored to individual user needs and living environments, particularly lacking advanced analysis such as disaster risk prediction and health status assessment. This makes comprehensive life support difficult for users, potentially leading to shortcomings in emergencies and health management. Furthermore, the lack of mechanisms to respond to user questions and requests in real time hinders the improvement of the user experience.

[1389] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1390] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting usage data from external information provision services, means for predicting disaster risk based on the usage data, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate products based on the living environment and needs and disaster risk, and dialogue interface means for responding to questions and requests from the user. This enables personalized suggestions that are tailored to the individual user's needs and living environment. Furthermore, it can provide comprehensive life support through disaster risk prediction and health status assessment. In addition, the user experience can be improved by responding to user questions and requests in real time.

[1391] "Basic information" refers to information such as the user's name, age, gender, and address, which is used to identify the user and understand their individual needs.

[1392] "Living environment" refers to factors that influence a user's daily life, such as their place of residence, family structure, and lifestyle habits.

[1393] "Needs" refer to the demands and desires for products and services that users require.

[1394] "Information provision services" refer to services that supply external data such as weather data, disaster information, and health data.

[1395] "Usage data" refers to data collected from external information provision services, such as weather data and disaster information.

[1396] "Disaster risk" refers to the risks that a particular region or user may face, based on weather data and disaster information.

[1397] "Notifications" refer to information or warning messages sent to users.

[1398] "Products" refer to items that meet the user's needs, including daily necessities and health products recommended by the user.

[1399] A "dialogue interface" refers to chatbots and other dialogue systems used to respond to user questions and requests.

[1400] A "biometric data acquisition device" refers to a wearable device used to acquire health data such as the user's heart rate, steps taken, and sleep duration.

[1401] "Health data" refers to data that indicates the user's health status, such as heart rate, steps taken, and sleep duration.

[1402] "Health status" refers to the user's current physical and mental health condition.

[1403] "Health-related products" refer to products such as supplements and fitness equipment that are recommended according to the user's health condition.

[1404] An "AI dialogue system" refers to a system that uses artificial intelligence to operate 24 hours a day, 365 days a year, and respond to user questions and requests in real time.

[1405] This invention is a system that collects basic user information, analyzes their living environment and needs, and proposes personalized daily necessities and health products. Specific embodiments of this system are described below.

[1406] First, when a user accesses the system for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which then stores that information in a database. As a specific example, the device displays an HTML form, and when the submit button is pressed, it sends the data to the server in JSON format. The server parses the received JSON data and executes an SQL query to save it to the database.

[1407] Next, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information. Specifically, the server periodically runs the AI ​​algorithm, using the user profile information as arguments to analyze the living environment and needs. The analysis results are stored in a database in preparation for the next recommendation process.

[1408] The server also collects weather and disaster information in real time from external information services. Based on this data, it predicts the disaster risk in the user's residential area. When the risk increases, the server generates push notifications or emails to notify the user. The device displays the received notification to the user. Specifically, the server periodically retrieves weather data using an API and performs data analysis using an automated script. If the risk is determined to be high, it generates a notification message and notifies the user via push notifications or email sending APIs.

[1409] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly completes this purchase process and arranges delivery via the server. Specifically, the server runs the recommendation engine and sends the generated product list to the terminal in JSON format. The terminal updates the UI, allowing the user to select products and proceed with the purchase. The purchase information is sent back to the server, which then coordinates with the logistics system to arrange delivery.

[1410] This system also acquires health data such as heart rate, steps, and sleep duration from the user's wearable device in real time and sends it to a server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation, the server recommends the most suitable health products and nutritional supplements to the user, and the device displays this product list to the user. Specifically, the device acquires data from the wearable device using Bluetooth or Wi-Fi and sends it to the server periodically. The server analyzes the received data, generates a health report, and creates a list of recommended products.

[1411] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. Specifically, a user's question is sent to the server via the terminal, and the AI ​​chatbot generates a response using a natural language processing model, which is returned to the user in real time. At the same time, the response content is saved as a log and used to improve service quality.

[1412] For example, if a typhoon is approaching the user's area, the server will assess the disaster risk based on weather data and generate a list of recommended disaster preparedness items such as emergency food and flashlights, notifying the user. The user can then review the list, select the necessary items, and proceed with the purchase. Furthermore, for the user's daily health management, data collected from wearable devices can be analyzed to recommend appropriate health products.

[1413] Example of a prompt:

[1414] 1. "Please send the entered information to the server and save it to the database."

[1415] 2. "Analyze the user's basic information and generate a list of recommended daily necessities and health products."

[1416] 3. "Predict the disaster risk in Tokyo and send a list of disaster preparedness supplies via push notification."

[1417] 4. "Analyze the collected health data and suggest the most suitable health products for the user."

[1418] 5. "Use an AI chatbot to respond to user inquiries in real time."

[1419] As described above, the present invention provides a system that supports a healthy and safe life by making personalized suggestions based on the user's living environment and needs.

[1420] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1421] Step 1:

[1422] Gathering basic information

[1423] Terminal: When the user first accesses the service, a form is displayed for them to enter basic information such as name, age, gender, and address. Input: Input fields of the HTML form. Output: JSON data after the submit button is pressed.

[1424] User: Enter the required information into the form and press the submit button. Input: Basic information such as name, age, gender, and address. Output: Data transmission upon clicking the submit button.

[1425] Terminal: Sends the entered information to the server. Specifically, the terminal performs error checking and converts the data to JSON format. Input: Basic information entered by the user. Output: JSON data.

[1426] Server: Stores received information in the database. Inserts information using SQL queries. Input: JSON data. Output: Database update.

[1427] Step 2:

[1428] Analysis of living environment and needs

[1429] Server: Uses an AI algorithm to analyze the user's living environment and needs based on basic user information stored in the database. Input: Basic user information obtained from the database. Output: Analysis result data.

[1430] Server: Saves analysis results to the database and prepares for the next recommendation process. Specifically, the server calls the AI ​​module and inserts the analysis results into the database as an SQL query. Input: Analysis result data. Output: Database update.

[1431] Step 3:

[1432] Predicting disaster risks

[1433] Server: Collects weather and disaster information in real time from external information services. Input: API requests. Output: Weather data and disaster information.

[1434] Server: Predicts disaster risk in the user's residential area based on acquired data. Input: Weather data, disaster information, user's address. Output: Disaster risk assessment results.

[1435] Server: When risk increases, it generates push notifications and emails to notify users. Specifically, it generates notification messages and uses push notification APIs and email sending APIs. Input: Disaster risk assessment results. Output: Notification messages, push notifications, emails.

[1436] Step 4:

[1437] Product Recommendation and Purchase Procedure

[1438] Server: Recommends appropriate daily necessities based on user profiles and disaster risk analysis results. Input: User profile, disaster risk assessment results. Output: List of recommended products.

[1439] Terminal: Presents a list of recommended products to the user. Input: Product list received from the server. Output: Product list displayed to the user.

[1440] User: Selects the desired items from the presented list and proceeds with the purchase. Input: User selection. Output: Purchase information.

[1441] Terminal: Sends purchase information to the server, which then arranges delivery. Specifically, the terminal converts the purchase information into JSON format and sends it to the server. Input: User's purchase information. Output: Data sent to the server.

[1442] Server: Receives purchase information and coordinates with the logistics system to arrange delivery. Input: Purchase information. Output: Delivery arrangement.

[1443] Step 5:

[1444] Health data collection and product recommendations

[1445] Terminal: Acquires health data such as heart rate, steps, and sleep duration in real time from the user's wearable device. Input: Data from the wearable device. Output: Health data.

[1446] Terminal: Sends acquired health data to the server. Specifically, it collects data using Bluetooth or Wi-Fi and periodically sends it to the server. Input: Health data. Output: Data transmission to the server.

[1447] Server: Stores received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Input: Health data. Output: Evaluation results.

[1448] Server: Based on evaluation results, it recommends the most suitable health products and nutritional supplements to the user. Specifically, it uses an AI module to perform evaluations and generate a list of appropriate products. Input: Evaluation results. Output: Recommended list of health products.

[1449] Terminal: Displays a list of recommended products to the user. Input: Product list received from the server. Output: Product list displayed to the user.

[1450] Step 6:

[1451] AI chatbot support

[1452] Server: Provides an AI chatbot that operates 24 / 7. Input: User questions and requests from the terminal. Output: Chatbot's response.

[1453] User: Interacts with the chatbot via their device and sends questions and requests. Input: User's questions and requests. Output: Chatbot's response display.

[1454] Server: The chatbot uses an AI model to respond to user questions. Specifically, it uses a natural language processing model to analyze user input and generate an appropriate response. Input: User's question. Output: Chatbot's response.

[1455] Server: Saves response content to logs to improve service quality. Input: Chatbot response. Output: Log data.

[1456] (Application Example 1)

[1457] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1458] Modern consumers have diverse needs and individual lifestyles, requiring personalized product recommendations tailored to their specific circumstances. However, conventional systems struggle to achieve this efficiently. Furthermore, there is a lack of means to monitor disaster risks and health conditions in real time and provide appropriate products based on that information. In addition, support systems capable of responding to user inquiries at any time are inadequate. To address these challenges, a system is needed that provides advanced data collection, analysis, product recommendations, and real-time support.

[1459] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1460] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, means for linking with a wearable device to collect and analyze the user's health data, means for displaying personalized product recommendations in a virtual store, and chatbot means for responding to questions and requests from the user. This enables personalized product recommendations and appropriate support that meet the diverse needs of the user.

[1461] "Means of collecting basic user information" refers to a system that allows users to input personal information such as their name, age, gender, and address via a terminal and transmit it to a server.

[1462] "Means for analyzing the user's living environment and needs based on the aforementioned basic information" refers to a process for determining the user's lifestyle patterns and individual needs using an AI algorithm based on the collected basic information.

[1463] "Means of collecting weather data and disaster information from external information provision services" refers to technologies for obtaining weather data and disaster information in real time via the internet.

[1464] "Means for predicting disaster risk based on the aforementioned weather data and disaster information" refers to a method for analyzing acquired weather data and disaster information to predict the risk of disaster occurrence in a specific area.

[1465] "Means for sending notifications to users based on the predicted disaster risk" refers to a function that sends warnings to users' devices via push notifications or email when the disaster risk increases.

[1466] "Means for recommending appropriate daily necessities based on the aforementioned living environment, needs, and disaster risk" refers to an algorithm that selects and recommends necessary daily necessities to the user based on the user's profile and disaster risk analysis.

[1467] A "wearable device integration method for collecting and analyzing user health data" is a system that acquires health data such as heart rate, steps taken, and sleep duration in real time from wearable devices worn by the user, and analyzes this data.

[1468] "A means of displaying personalized product recommendations in a virtual store" refers to a function that displays the most suitable products for each individual user in a virtual space, taking into account the user's basic information, living environment, needs, disaster risk, and health data.

[1469] A "chatbot tool for responding to user questions and requests" is an AI chatbot that responds to user questions and requests via their device in real time, 24 hours a day, 365 days a year.

[1470] This invention relates to a virtual store system that collects basic user information, analyzes their living environment and needs, and recommends personalized products. Specific embodiments of this system are described below.

[1471] First, when a user accesses the virtual store application for the first time, the terminal displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The terminal sends the submitted information to the server, which stores that information in a database. Next, the server uses an AI algorithm to analyze the user's living environment and needs based on the stored basic information.

[1472] The server also collects weather and disaster information in real time from external information services. Using this data, the server predicts the disaster risk in the user's area. This risk prediction is performed regularly, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays this notification to the user, allowing them to receive the necessary information.

[1473] Furthermore, the server recommends appropriate daily necessities based on the user profile and disaster risk analysis results. The recommended product list is presented to the user via the terminal, and the user can select the necessary items from the list and proceed with the purchase. The terminal quickly processes the purchase and arranges delivery via the server.

[1474] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[1475] Furthermore, this invention provides an AI chatbot that operates 24 hours a day, 365 days a year, responding to user questions and requests in real time. This chatbot runs on a server and provides support through interaction with the user. Users can interact with the chatbot via their terminal and receive the necessary information and support. The chatbot's responses are saved as logs on the server and used to improve the quality of the service.

[1476] Hardware and software to be used

[1477] Hardware: Smartphones, head-mounted displays, wearable devices

[1478] Software and libraries: Python, Flask (web framework), AI analysis algorithms (e.g., TensorFlow, Scikit-learn), databases (e.g., PostgreSQL, MongoDB)

[1479] Examples of specific cases and prompt statements

[1480] As a concrete example, a user opens the application and enters basic information. The server analyzes this information and, if it recognizes that the disaster risk is high in Tokyo, sends the user a push notification with a list of emergency food supplies and flashlights. Furthermore, based on data from the user's wearable device, if a lack of exercise is detected, it recommends exercise equipment and nutritional supplements.

[1481] Example of a prompt:

[1482] "My name is Taro Yamada. I'm 30 years old and currently live in Tokyo. Do you have any recommendations for health products or everyday necessities these days?"

[1483] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1484] Step 1:

[1485] When a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). Once the user submits the entered basic information, the device sends it to the server.

[1486] Input: Basic information such as name, age, gender, and address.

[1487] Data processing: Convert input data to JSON format.

[1488] Output: Basic information in JSON format sent to the server

[1489] Step 2:

[1490] The server stores the received basic information in a database. After this storage process, the server uses an AI algorithm to analyze the user's living environment and needs based on the basic information.

[1491] Input: Basic information in JSON format

[1492] Data processing: Data storage in databases, analysis using AI algorithms.

[1493] Output: Analysis results of the user's living environment and needs

[1494] Step 3:

[1495] The server collects weather and disaster information in real time from external information services. Based on this information, the server predicts the disaster risk in the user's area.

[1496] Input: Weather data, disaster information

[1497] Data processing: Analysis of weather data and disaster information, prediction of disaster risk.

[1498] Output: Disaster risk prediction results

[1499] Step 4:

[1500] If the risk of disaster increases, the server will send push notifications or emails to users. The device will then display these notifications to the user.

[1501] Input: Disaster risk prediction results

[1502] Data processing: Creating and sending push notifications and emails.

[1503] Output: Notification sent to the user's device

[1504] Step 5:

[1505] The server recommends appropriate daily necessities based on the user's living environment, needs, and disaster risk. This is then displayed on the user's device.

[1506] Input: Analysis results of the user's living environment and needs, disaster risk prediction results

[1507] Data processing: Generating personalized product lists

[1508] Output: Product recommendation list displayed on the user's device

[1509] Step 6:

[1510] The device acquires health data such as heart rate, steps taken, and sleep duration from the user's wearable device in real time and sends it to the server.

[1511] Input: Health data from wearable devices

[1512] Data processing: Format conversion and transmission of acquired data.

[1513] Output: Health data sent to the server

[1514] Step 7:

[1515] The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on the evaluation results, it recommends the most suitable health products and nutritional supplements to the user.

[1516] Input: Health data

[1517] Data processing: Storage in a database, evaluation using AI algorithms.

[1518] Output: Recommended list of health products and nutritional supplements

[1519] Step 8:

[1520] The server provides an AI chatbot that operates 24 / 7, 365 days a year, responding to user questions and requests in real time. Users can interact with the chatbot via their devices and receive the information and support they need.

[1521] Input: Questions and requests from users

[1522] Data processing: Response generation by chatbot

[1523] Output: Real-time response to the user

[1524] Example of a prompt:

[1525] "My name is Taro Yamada. I'm 30 years old and currently live in Tokyo. Do you have any recommendations for health products or everyday necessities these days?"

[1526] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1527] This invention is an e-commerce platform that collects basic user information and health data, analyzes the user's living environment and needs, and recommends appropriate daily necessities and health products. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it provides optimal notifications and recommendations based on the user's emotional state. The following describes a specific embodiment of this system.

[1528] First, when a user accesses the service for the first time, the device displays a form for the user to enter basic information (name, age, gender, address, etc.). The user enters the required information into this form and submits it. The device sends the entered information to the server, which stores that information in a database. Furthermore, the server uses an AI algorithm to analyze the user's living environment and individual needs based on the stored basic information.

[1529] Next, the server collects weather and disaster information in real time from external information services and uses this data to predict the disaster risk in the user's area. This risk prediction is performed periodically, and if the risk increases, the server sends important safety notices to the user via push notifications or email. The device displays these notices to the user, allowing them to receive the necessary information.

[1530] Furthermore, the server recommends essential goods based on the user's profile and disaster risk analysis. The recommended product list is presented to the user via the terminal, allowing the user to select the necessary items and proceed with the purchase. The terminal quickly processes this purchase and arranges delivery via the server.

[1531] This system also has the function of collecting user health data. The terminal acquires health data such as heart rate, steps taken, and sleep duration in real time from the user's wearable device and sends it to the server. The server stores the received health data in a database and uses an AI algorithm to comprehensively evaluate the user's health status. Based on this evaluation result, the server recommends the most suitable health products and nutritional supplements to the user, and the terminal displays this product list to the user.

[1532] Furthermore, the present invention includes an emotion engine that recognizes the user's emotional state. The emotion engine collects emotional data in real time from the user's voice, facial expressions, and entered text. The server analyzes this emotional data to identify the user's current emotional state. For example, if the user is feeling stressed, it recommends relaxation products. It can also adjust the content and frequency of notifications according to the emotional state. In this way, it provides the user with more effective and personalized support.

[1533] As a concrete example, when a user is using a smartphone, the device sends the user's voice and facial expressions to an emotion engine. Based on this data, the server determines that the user is tired and generates a list of relaxation products. The device notifies the user of this list, and the user can select and purchase the most suitable product from the list.

[1534] Furthermore, if a user regularly uses a wearable device, the device collects and transmits the user's health data to a server. The server combines this health data with emotional data to comprehensively evaluate the user's health and emotional state. For example, it might recommend exercise equipment or relaxation supplements to a user who is stressed due to lack of exercise. The user can accept these suggestions via the device and purchase products that are optimal for both their health and emotional well-being.

[1535] As described above, the present invention, by including an emotion engine, provides an e-commerce platform that offers more personalized suggestions based on the user's living environment, health condition, and emotional state, thereby supporting the user's healthy, safe, and comfortable life.

[1536] The following describes the processing flow.

[1537] Step 1:

[1538] The user accesses the SmartLife Assistant application for the first time. The device displays a form for the user to enter basic information (name, age, gender, address, etc.).

[1539] Step 2:

[1540] The user enters the required information into the form and submits it. The device sends the entered information to the server.

[1541] Step 3:

[1542] The server stores the user's basic information in a database. Furthermore, the server uses AI algorithms to analyze the stored basic information and identify the user's living environment and individual needs.

[1543] Step 4:

[1544] The server collects weather and disaster information in real time from external information services. The collected data is used to assess disaster risk.

[1545] Step 5:

[1546] The server analyzes collected weather data and disaster information to predict the disaster risk in the user's residential area. If the risk increases, the server notifies the user.

[1547] Step 6:

[1548] The device sends disaster risk notifications from the server to the user via push notification. The user checks the notification.

[1549] Step 7:

[1550] The server generates a product list to recommend the most suitable daily necessities based on the user's profile and the results of a disaster risk analysis.

[1551] Step 8:

[1552] The terminal displays the generated product list to the user. The user reviews the suggested product list and selects the desired products.

[1553] Step 9:

[1554] The user purchases the selected product. The terminal quickly processes this purchase and arranges delivery via the server.

[1555] Step 10:

[1556] The device periodically collects health data such as heart rate, steps taken, and sleep duration from the user's wearable device and sends it to the server.

[1557] Step 11:

[1558] The server stores the received health data in a database and uses an AI algorithm to evaluate the user's health status.

[1559] Step 12:

[1560] The server recommends the most suitable health products and nutritional supplements to the user based on the health assessment results. The terminal displays a list of health products and nutritional supplements to the user.

[1561] Step 13:

[1562] The device transmits the user's voice, facial expressions, and entered text to the emotion engine. The emotion engine collects emotion data in real time.

[1563] Step 14:

[1564] The server analyzes the emotional data sent from the emotion engine to identify the user's emotional state. If necessary, it adjusts the user's profile based on the evaluation results.

[1565] Step 15:

[1566] The server adjusts the content and frequency of notifications and recommendation lists based on the user's emotional state. For example, if a user is feeling stressed, it will recommend relaxation products.

[1567] Step 16:

[1568] This system provides an AI chatbot that operates 24 hours a day, 365 days a year. When a user makes a question or request, the device forwards it to the chatbot.

[1569] Step 17:

[1570] The server has the chatbot analyze the question or request and generate an appropriate response. The terminal displays the generated response to the user, allowing the user to obtain the necessary information.

[1571] Step 18:

[1572] All interactions are saved as logs on the server and used to improve the quality of the service.

[1573] (Example 2)

[1574] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1575] Traditional e-commerce platforms are limited to simple recommendation functions based on basic user information, lacking personalized suggestions that take into account users' emotional and health states. Furthermore, they fail to adequately provide urgent information, such as safety measures and health management notifications based on disaster risks. As a result, it has been difficult to support users in leading healthy, safe, and comfortable lives.

[1576] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1577] In this invention, the server includes means for collecting basic user information, means for analyzing the user's living environment and needs based on the basic information, means for collecting weather data and disaster information from external information provision services, means for predicting disaster risk based on the weather data and disaster information, means for sending notifications to the user based on the predicted disaster risk, means for recommending appropriate daily necessities based on the living environment and needs and disaster risk, dialogue agent means for responding to questions and requests from the user, emotion engine means for recognizing emotional states and providing optimal notifications and recommendations, means for analyzing the user's voice, facial expressions and text and collecting emotional data, means for adjusting notification content and recommendations based on the analyzed emotional data, means for collecting health data from the user's wearable device, means for analyzing the health data and evaluating the user's health status, means for recommending health products and nutritional supplements based on the evaluation results, and means for providing an AI dialogue agent that operates 24 hours a day, 365 days a year and responding to questions and requests from the user in real time. This enables personalized suggestions based on the user's living environment, health status and emotional status, and can support the user's healthy, safe, and comfortable life.

[1578] "User basic information" refers to personal information such as the user's name, age, gender, and address.

[1579] "Analysis of living environment and needs" refers to the process of analyzing and evaluating a user's living environment and individual needs based on their basic information.

[1580] "External information provision services" refer to services that supply real-time data provided from external sources, such as weather data and disaster information.

[1581] "Disaster risk prediction" refers to the process of estimating the likelihood of a disaster occurring in a specific area based on weather data and disaster information collected from external information services.

[1582] "Means of sending notifications" refers to methods of communicating important information to users, such as predicted disaster risks.

[1583] "Means of recommending daily necessities" refers to a function that suggests the most suitable products considering the user's living environment, needs, and disaster risk.

[1584] A "conversational agent" refers to a response system equipped with artificial intelligence to handle questions and requests from users.

[1585] An "emotion engine" refers to a system that recognizes a user's emotional state and uses that information to provide notifications and product recommendations.

[1586] "Emotional data" refers to information about a user's emotions extracted from their voice, facial expressions, and entered text.

[1587] "Adjusting notification content and recommendations based on analyzed sentiment data" refers to the process of adaptively changing the content and frequency of notifications and product recommendations based on the user's emotional state.

[1588] A "wearable device" refers to a device that a user wears to measure and collect health data such as heart rate, steps taken, and sleep duration.

[1589] "Collecting health data" refers to the process of acquiring data such as heart rate, steps taken, and sleep duration from wearable devices.

[1590] "Means for evaluating a user's health status" refers to a method of comprehensively evaluating a user's health status by analyzing collected health data.

[1591] "Recommendation of health products and nutritional supplements" refers to a function that suggests the most suitable health products and nutritional supplements to the user based on evaluation results.

[1592] An "AI conversational agent" refers to a system equipped with artificial intelligence that operates 24 hours a day, 365 days a year, and responds to user questions and requests in real time.

[1593] Modes for carrying out the invention

[1594] This invention is an e-commerce platform that collects basic user information and health data, analyzes their living environment and needs, and recommends appropriate daily necessities and health products. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it provides optimal notifications and recommendations based on the user's emotional state. A specific embodiment of this system is described below.

[1595] Equipment and hardware / software used

[1596] 1. Preparing the device

[1597] The devices used by users (smartphones, tablets, PCs, etc.) are equipped with an interface for entering basic information.

[1598] Wearable devices (such as smartwatches) are used to collect users' health data in real time and transmit it to the device.

[1599] 2. Server Functions

[1600] The server has a database that collects and stores basic information entered by users and health data transmitted from wearable devices.

[1601] The server collects real-time data from external information services (such as weather data and disaster information services).

[1602] The server uses an emotion engine to analyze emotional data from the user's voice, facial expressions, and input text.

[1603] 3. Execution of the AI ​​algorithm

[1604] The AI ​​algorithm embedded in the server analyzes the user's living environment and needs based on the user's basic information, health data, and emotional data.

[1605] It analyzes weather data and disaster information collected in real time to predict disaster risks.

[1606] 4. Notification and Recommendation System

[1607] The server generates a list of appropriate daily necessities and health products based on disaster risks and user needs.

[1608] The server sends push notifications and emails to terminals, providing users with urgent notifications and product recommendations.

[1609] The device displays these notifications and recommendation lists to the user, who can respond as needed.

[1610] Specific examples and prompt statements

[1611] 1. Collection and analysis of basic information and sentiment data

[1612] Users enter basic information such as their name, age, gender, and address into a form on their smartphone and submit it.

[1613] The device sends this information to the server, where it is stored in the database.

[1614] The server collects the user's voice and facial expressions in real time and analyzes them using an emotion engine.

[1615] For example, if the system determines that the user is experiencing stress, a list of relaxation products will be generated.

[1616] Prompt example:

[1617] "Please recommend the most suitable relaxation products based on the user's basic information and current emotional state."

[1618] 2. Integrated analysis of health data and emotional data

[1619] Data such as heart rate, steps taken, and sleep duration are transmitted to the device from smartwatches and other devices that the user uses daily.

[1620] The terminal sends this data to the server, which then analyzes the data.

[1621] The server combines health data and emotional data to assess the user's health and emotional state and recommend appropriate health products and nutritional supplements.

[1622] Prompt example:

[1623] "Based on real-time health and emotional data, please suggest appropriate nutritional supplements to users."

[1624] The goal of this system is to support users in leading healthy, safe, and comfortable lives by providing more personalized suggestions based on their living environment, health status, and emotional state, through the inclusion of an emotion engine. Users will be able to respond quickly and accurately through emergency notifications based on disaster risk and personalized product recommendations.

[1625] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1626] Step 1:

[1627] Gathering basic information

[1628] When a user accesses the site for the first time, they enter basic information such as their name, age, gender, and address into a form that appears on their device.

[1629] Input: Basic user information such as name, age, gender, and address.

[1630] The terminal sends the basic information entered by the user to the server.

[1631] The server stores this information in the database.

[1632] Output: Basic user information stored in the database.

[1633] Step 2:

[1634] Analysis of living environment and needs

[1635] The server uses an AI algorithm to analyze basic user information obtained from the database.

[1636] Input: Basic user information stored in the database.

[1637] The server uses an AI model to analyze patterns in living environments and needs.

[1638] Output: Analytical data regarding the user's living environment and needs.

[1639] Step 3:

[1640] Real-time data collection

[1641] The server collects weather data and disaster information in real time from external information provision services.

[1642] Input: Weather data and disaster information obtained from external information provision services.

[1643] The server stores this information in a database and performs the necessary data processing.

[1644] Output: Real-time data stored in the database.

[1645] Step 4:

[1646] Predicting disaster risks

[1647] The server uses real-time data to predict the disaster risk in the user's residential area using an AI algorithm.

[1648] Input: Real-time data, user's residential area information.

[1649] The server analyzes weather data and disaster information and outputs the likelihood of a disaster occurring in a specific area.

[1650] Output: Disaster risk prediction results.

[1651] Step 5:

[1652] Sending an emergency notification

[1653] The server generates emergency notifications for users based on the predicted disaster risk.

[1654] Input: Disaster risk prediction results.

[1655] The terminal displays emergency notifications sent from the server to the user.

[1656] Output: Emergency notification displayed to the user.

[1657] Step 6:

[1658] Recommendations for daily necessities

[1659] The server uses an AI algorithm to recommend the most suitable daily necessities based on the user's basic information, living environment, needs, and disaster risk.

[1660] Input: User's basic information, living environment, needs, and disaster risk.

[1661] The server uses an AI model to generate a product list tailored to the user.

[1662] The terminal displays the generated product list to the user.

[1663] Output: A list of recommended daily necessities displayed to the user.

[1664] Step 7:

[1665] Purchase procedure

[1666] The user selects the desired product from the provided product list.

[1667] Input: The product selected by the user.

[1668] The terminal completes the purchase process and arranges for delivery via the server.

[1669] Output: Purchased items for which shipping arrangements have been completed.

[1670] Step 8:

[1671] Collection of health data

[1672] The device collects health data such as heart rate, steps taken, and sleep duration from the user's wearable devices.

[1673] Input: Health data collected from wearable devices.

[1674] The device sends the collected health data to the server.

[1675] Output: Health data stored on the server.

[1676] Step 9:

[1677] Health status assessment

[1678] The server analyzes the collected health data using an AI...

Claims

1. Means for collecting basic user information, A means for analyzing the user's living environment and needs based on the aforementioned basic information, Means of collecting weather data and disaster information from external information provision services, A means for predicting disaster risk based on the aforementioned weather data and disaster information, A means for sending a notification to a user based on the predicted disaster risk, A means of recommending appropriate daily necessities based on the aforementioned living environment and needs, and disaster risk, A system that includes a chatbot for responding to user questions and requests.

2. A means of collecting health data from a user's wearable device, A means for analyzing the aforementioned health data and evaluating the user's health status, The system according to claim 1, further comprising means for recommending health products or nutritional supplements based on the evaluation results.

3. The system according to claim 1, further comprising means for providing an AI chatbot that operates 24 hours a day, 365 days a year, and for responding to user questions and requests in real time.

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