System

Abstract

A system is provided.SOLUTION: A system including a means for acquiring position information of a user, a means for collecting information related to CO2 reduction activities in the world by using a generated AI, a means for analyzing the collected information and extracting activity information related to the position information of the user, a means for converting the extracted information into a format easy to understand for the user, a means for transmitting the converted information to a terminal of the user, a means for inputting and transmitting an activity amount of the user, and a means for evaluating the input activity amount, calculating a reward based on the evaluation, and giving the reward to the user account.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] While CO2 reduction activities are becoming increasingly important as a measure against global warming, individuals often do not understand how to take specific actions. Furthermore, the latest information on CO2 reduction activities being carried out in each region is not effectively distributed, making it difficult to motivate individuals to participate. Furthermore, when individuals actually participate in CO2 reduction activities, there is no system in place to evaluate their results or receive feedback, which prevents continued action. The purpose of this invention is to solve these issues and achieve larger-scale CO2 reductions by providing a system that encourages active individual participation. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with a system that includes: a means for acquiring a user's location information; a means for collecting information on CO2 reduction activities around the world using a generation AI; a means for analyzing the collected information and extracting activity information related to the user's location information; a means for converting the extracted information into a format that is easy for the user to understand; a means for transmitting the converted information to the user's device; a means for inputting and transmitting the user's activity level; and a means for evaluating the input activity level, calculating a reward based on the evaluation, and granting the reward to the user's account. This system allows users to easily obtain information on specific CO2 reduction activities based on their location, thereby increasing their motivation to participate in activities. Furthermore, the information collected by the generation AI is always up-to-date and highly accurate. Furthermore, after the activity, the results are appropriately evaluated and the user is rewarded, encouraging continued activity.

[0006] "User location information" is data that indicates the geographic coordinates (longitude and latitude) of an individual's current location.

[0007] "Generative AI" refers to systems that use artificial intelligence to collect, analyze, and generate data for specific purposes.

[0008] "CO2 reduction activities" refers to specific actions and efforts to reduce carbon dioxide emissions.

[0009] "Means of collecting information" refers to the processes and techniques used to gather the necessary information from various data sources.

[0010] "Means for analyzing information" refers to the means for processing collected data, extracting necessary information from it, and converting it into an easily understandable format.

[0011] "Means for extracting activity information" refers to a technology for extracting specific activity details related to the user's location information from the analyzed data.

[0012] "Transformation means" refers to the processes and techniques used to transform extracted information into a form that is easy for users to understand.

[0013] "Terminal" refers to the device used by the user (smartphone, tablet, PC, etc.).

[0014] "Means for inputting and transmitting activity amount" refers to a function for inputting the activity details performed by the user into the system and transmitting the details to the server.

[0015] "Means for evaluating activity levels" refers to the processes and technologies for calculating and evaluating the effects of activity information entered by the user.

[0016] "Means for calculating rewards" refers to a process or technology that calculates reward points or monetary value for a user based on the assessed activity amount.

[0017] "User account" refers to a database for managing information about users registered in the system and the information about those users.

[0018] "Means for Granting Rewards" means the process or technology by which calculated rewards are added to a user's account and made accessible to the user. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] This invention is a system that provides users with the latest information on CO2 reduction activities based on their location information and rewards them for their contribution to CO2 reduction through their actions. This system uses generation AI to always provide the latest information and help users take action easily.

[0041] Program processing

[0042] 1. Obtaining user location information

[0043] A user accesses an application or website in the system and logs in.

[0044] With the user's consent, the device collects current location information (longitude and latitude).

[0045] The device sends the location information it collects to the server.

[0046] 2. Collection and processing of the latest information

[0047] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[0048] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[0049] The server converts the extracted information into a format that is easy for the user to understand.

[0050] 3. Providing information and encouraging action

[0051] The server sends the converted information to the user's terminal.

[0052] The terminal displays the received information to the user so that the user can view it.

[0053] For example, a notification might appear saying, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[0054] 4. Recording behavior and calculating rewards

[0055] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[0056] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the system.

[0057] The terminal transmits the input activity information to the server.

[0058] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[0059] The server calculates reward points based on the evaluation results and grants them to the user's account.

[0060] An in-app notification will be sent to allow users to check their reward points.

[0061] Specific examples

[0062] Example 1: When a user participates in a tree planting activity

[0063] 1. User Activities

[0064] A user accesses the application and receives information about participating in a tree planting weekend.

[0065] Go to the designated location and plant 10 trees.

[0066] After the activity, participants enter the number of trees planted in the application and report, "I planted 10 trees today."

[0067] 2. System evaluation and rewards

[0068] The terminal sends the user's input to the server.

[0069] The server uses generated AI to evaluate the amount of CO2 reduction equivalent to planting 10 trees and awards, for example, 10 points.

[0070] Reward points will be added to your user account and you will receive a notification.

[0071] This system allows users to always receive the latest information on CO2 reduction activities, take concrete action based on that information, and receive rewards for their results. This encourages active participation by users and contributes to measures against global warming.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] A user logs into an application or website on the system.

[0075] Step 2:

[0076] With the user's consent, the device collects current location information (longitude and latitude).

[0077] Step 3:

[0078] The device sends the location information it collects to the server.

[0079] Step 4:

[0080] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[0081] Step 5:

[0082] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[0083] Step 6:

[0084] The server converts the extracted information into a format that is easy for the user to understand.

[0085] For example, you could convert it into a notification that reads, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[0086] Step 7:

[0087] The server sends the converted information to the user's terminal.

[0088] Step 8:

[0089] The terminal displays the received information to the user so that the user can view it.

[0090] Step 9:

[0091] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[0092] Step 10:

[0093] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the application.

[0094] Step 11:

[0095] The terminal transmits the input activity information to the server.

[0096] Step 12:

[0097] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[0098] Step 13:

[0099] The server calculates reward points based on the evaluation results and grants them to the user's account.

[0100] Step 14:

[0101] The terminal notifies the user of the reward points and allows the user to check the points.

[0102] Example 1

[0103] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0104] Conventional information provision systems for CO2 reduction activities lacked specific action plans and evaluation functions that allowed users to easily participate, making it difficult to visualize an individual's environmental contribution and provide appropriate rewards. Furthermore, they lacked a mechanism to encourage user action by providing the latest information in a timely manner. As a result, many users missed the opportunity to actively participate in CO2 reduction activities.

[0105] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0106] In this invention, the server includes means for acquiring user location information, means for using a generation AI to collect information on CO2 reduction activities around the world, means for analyzing the collected information and extracting activity information related to the user's location information, means for converting the extracted information into a format that is easy for the user to understand, means for transmitting the converted information to the user's device, means for inputting and transmitting the user's activity amount, means for evaluating the input activity amount, calculating a reward based on the amount, and granting the reward to the user's account, means for displaying a reward grant notification on the user's device, and means for analyzing the collected information using natural language processing technology.This allows users to easily obtain the latest CO2 reduction activity information, create specific action plans, and receive appropriate rewards for their actions.

[0107] "User location information" refers to the longitude and latitude data of the user's current location.

[0108] "Generative AI" is a system that uses machine learning and artificial intelligence techniques to generate the models and data needed for specific tasks.

[0109] "CO2 reduction activities" are specific actions or projects aimed at reducing carbon dioxide emissions.

[0110] "Data sources" refers to the websites, news sites, environmental organization websites, social media, etc. from which information is collected.

[0111] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[0112] A "user terminal" is a device used by a user, such as a smartphone or PC.

[0113] "Reward points" are points that users can earn as a result of participating in CO2 reduction activities and are returned to them.

[0114] "Activity information" is specific information such as the date, time, location, and content of CO2 reduction activities in which users can participate.

[0115] "Amount of activity" refers to the specific amount and content of CO2 reduction activities that a user has actually undertaken (e.g., number of trees planted).

[0116] "Evaluation results" are results that show the effectiveness of the CO2 reduction activities carried out by the user in numerical values ​​or points.

[0117] This invention is a system that provides users with the latest information on CO2 reduction activities based on their location information and rewards them for their contribution to CO2 reduction through their actions. This system uses a generative AI model to constantly provide the latest information and help users easily take action.

[0118] Overview of program processing

[0119] This system consists of three main components: a server, a terminal, and a user. The server processes data using a generative AI model and a database. A terminal is a device such as a smartphone or PC that is used by a user. Users access the system through an application or website to provide location information and enter their activities.

[0120] Hardware and Software

[0121] The server can process large amounts of data using a cloud-based infrastructure. Specific examples include cloud services such as Amazon Web Services (AWS®) and Google® Cloud Platform (GCP). The generative AI model uses natural language processing technology. Examples include OpenAI®'s GPT-3® and BERT. Devices that can be used include smartphones running iOS or Android®, and PCs running Windows or macOS®.

[0122] Data processing and calculation

[0123] The server first collects information on CO2 reduction activities from various data sources, including news sites, environmental organization websites, and social media. The collected data is analyzed by a generative AI model to extract activity information related to the user's location. The extracted information is then converted into a user-friendly format using natural language processing technology. Finally, the converted information is sent to the user's device and displayed.

[0124] When a user performs a CO2 reduction activity, they input the activity details and amount into the application. The device sends this input information to the server, which then evaluates the activity using generated AI. Based on the evaluation, reward points are awarded to the user's account. Points can be viewed on the user's device.

[0125] Specific examples

[0126] Example 1: When a user participates in a tree planting activity

[0127] 1. A user accesses the application and receives information about participating in a tree planting weekend.

[0128] 2. The user goes to a designated location and plants 10 trees.

[0129] 3. After the activity, report the number of trees planted in the application and enter "I planted 10 trees today."

[0130] 4. The device sends the user's input to the server, which evaluates it using the generating AI and assigns 10 points to the user's account.

[0131] 5. Users will see the reward points added in the app and receive a notification.

[0132] Prompt Sentence Examples

[0133] You are a user. This weekend, a tree planting event will be held in your town. Please participate and contribute to reducing CO2 emissions. Please participate in the tree planting event and report it on this system after the event.

[0134] In this way, the present invention provides a system that allows users to always obtain the latest information on CO2 reduction activities, take concrete actions based on that information, and receive rewards for their results, thereby encouraging active participation by users and contributing to global warming countermeasures.

[0135] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0136] Step 1:

[0137] A user accesses a system application or website and logs in. After the user enters their username and password and completes authentication, the device begins acquiring location information. Input: User authentication information. Output: Authentication success flag. Specifically, the user enters authentication information on the app's login screen, the device sends it to the server, and authentication is successful.

[0138] Step 2:

[0139] With the user's consent, the device collects current location information (longitude and latitude). Input: User's consent. Output: Location data (longitude, latitude). Specifically, the app displays a pop-up message requesting permission to collect location information, and once the user agrees, the device uses its GPS function to obtain location information.

[0140] Step 3:

[0141] The location information collected by the device is sent to the server. Input: Location information data. Output: Server-side location information storage completion flag. Specifically, the device encrypts the location information and sends it to the server, which then stores it in a database.

[0142] Step 4:

[0143] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, websites of environmental protection organizations, social media, etc.). Input: List of data sources. Output: Collected data. Specifically, the server runs a pre-configured crawling program to collect information from the data sources.

[0144] Step 5:

[0145] The generation AI analyzes the collected information and extracts activity information related to the user's location information. Input: collected data, location data. Output: related activity information. Specifically, the generation AI uses natural language processing technology to analyze the collected data, extract important information such as the activity name, location, date and time, and compare it with the user's location information.

[0146] Step 6:

[0147] The server converts the extracted information into a format that is easy for users to understand. Input: Related activity information. Output: Converted information. Specifically, the server formats the information and summarizes it into user-friendly text.

[0148] Step 7:

[0149] The server sends the converted information to the user's device. Input: Converted information. Output: Flag indicating completion of sending information to the device. Specifically, the server sends the converted information to the user's device in JSON format or similar.

[0150] Step 8:

[0151] The terminal displays the received information to the user so that the user can view it. Input: Converted information. Output: Display of information that can be viewed by the user. Specifically, the application analyzes the received data and displays it in a pop-up notification or on the interface.

[0152] Step 9:

[0153] Based on the information presented, the user carries out specific CO2 reduction activities (e.g., tree planting or participating in environmental protection events). Input: Presented information. Output: Details of the activity to be carried out. Specifically, the user follows the notification and carries out the activity at the specified location and time.

[0154] Step 10:

[0155] After the activity, the user inputs the specific amount and content of the activity they performed (e.g., number of trees planted) into the system. Input: Content of the activity performed. Output: Activity report data. Specifically, the user inputs the content of the activity into a form within the application.

[0156] Step 11:

[0157] The terminal sends the entered activity information to the server. Input: Activity report data. Output: Activity information storage completion flag on the server side. Specifically, the terminal sends the activity report data to the server, and the server stores it in a database.

[0158] Step 12:

[0159] The server uses the generation AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction. Input: Activity report data. Output: Evaluation results. Specifically, the generation AI analyzes the amount and content of the activity and evaluates the effect of CO2 reduction.

[0160] Step 13:

[0161] The server calculates reward points based on the evaluation results and grants them to the user's account. Input: Evaluation results. Output: Reward points. Specifically, the server calculates reward points based on the evaluation results and grants them to the user's account.

[0162] Step 14:

[0163] A notification is sent within the app so that the user can check their reward points. Input: Reward points. Output: Points awarded notification. Specifically, the application notifies the user that points have been awarded and presents a screen where the user can check their points.

[0164] (Application example 1)

[0165] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0166] CO2 reduction activities aimed at environmental protection are most effective when many individuals participate in them. However, at present, there are limited ways for general users to understand what CO2 reduction activities they can participate in or to evaluate the extent to which their activities have contributed to CO2 reduction. Furthermore, there is no adequate reward system in place, which means that general users have little motivation to participate. The purpose of this project is to solve this problem, encourage active participation by users, and promote effective CO2 reduction activities.

[0167] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0168] In this invention, the server includes: means for acquiring user location information; means for using a generation AI to collect information on CO2 reduction activities around the world; means for analyzing the collected information and extracting activity information related to the user's location information; means for converting the extracted information into a format that is easy for the user to understand; means for transmitting the converted information to the user's terminal; means for the terminal to record the user's activity amount and transmit the recorded information to the server; means for evaluating the input activity amount, calculating a reward based on the amount, and granting the reward to the user's account; means for providing instructions to the user including information on eco-activities; and means for making reward points available for use in the store. This allows users to always receive the latest information on CO2 reduction activities and earn rewards based on their activities, thereby enabling them to more actively participate in environmental protection activities.

[0169] The "means for acquiring user location information" refers to a device or software function that collects data necessary to identify the user's current location.

[0170] "Means for collecting information on CO2 reduction activities around the world using generative AI" refers to a device or software function that uses artificial intelligence technology to widely collect the latest information on CO2 reduction activities in various locations.

[0171] "Means for analyzing collected information and extracting activity information related to the user's location information" refers to the function of a device or software that analyzes collected data and identifies and extracts information about CO2 reduction activities related to the user's current location.

[0172] The "means for converting extracted information into a user-friendly format" refers to the function of a device or software that processes the analyzed and extracted information into a format that is easy for the user to understand.

[0173] The "means for transmitting the converted information to the user's terminal" refers to the function of a device or software for transmitting the processed information to the device used by the user.

[0174] "Means for the terminal to record the amount of user activity and send it to the server" refers to the function of a device or software that records the user's behavior on the terminal and sends the data to a central server.

[0175] "Means for evaluating the amount of activity entered, calculating rewards based thereon, and granting rewards to the user account" refers to the function of a device or software that evaluates the amount and quality of activity performed by a user and calculates and grants rewards accordingly.

[0176] The "means for providing a user with instructions including information on eco-friendly activities" refers to a function of a device or software that conveys behavioral instructions and information related to environmental protection to a user.

[0177] "Means for enabling reward points to be used in-store" refers to a device or software function that allows a user to use the reward points they have earned for discounts, payments, etc. at physical stores.

[0178] This invention provides a system that allows users to participate in CO2 reduction activities, receive rewards based on the evaluation of their contributions. The system acquires the user's location information, uses AI to collect and analyze the latest CO2 reduction activity information, and presents it to the user in an easy-to-understand manner. It also records the user's activity level and awards rewards based on the user's contribution.

[0179] Main components and their functions

[0180] 1. How to obtain user location information

[0181] The user's device (e.g., a smartphone) acquires the user's current location using GPS, etc. This location information is used in the next step.

[0182] 2. A means of using generative AI to collect information on CO2 reduction activities around the world

[0183] The server uses generative AI to collect the latest information on CO2 reduction activities from a variety of data sources, including news sites, environmental organization websites, and social media.

[0184] 3. A means of analyzing the collected information and extracting activity information related to the user's location information.

[0185] The server uses the generated AI to analyze the acquired user location information and extract information on CO2 reduction activities in which the user can participate.

[0186] 4. A means of converting the extracted information into a user-friendly format

[0187] The server converts the extracted information into a format that is easy for the user to understand and displays it, for example, through notification messages or an in-app interface.

[0188] 5. Means for transmitting the converted information to the user's terminal

[0189] The converted information is sent from the server to the user's terminal and notified in real time.

[0190] 6. How the device records the user's activity and sends it to the server

[0191] The user's device records the amount of CO2 reduction activity they have actually performed by scanning a QR code (registered trademark) or by manually entering it. This information is sent to the server.

[0192] 7. A means for evaluating the amount of activity entered, calculating rewards based on the amount, and crediting the rewards to the user account.

[0193] The server uses the AI ​​generator to evaluate the amount of activity entered by the user and calculates reward points based on the contribution. The calculated reward is credited to the user's account and notified within the app.

[0194] 8. Means for providing users with instructions including eco-friendly activity information

[0195] The user's device provides the latest information on collected eco-activities and specific instructions for action.

[0196] 9. Means for reward points to be redeemed in-store

[0197] Users can use the reward points they earn for discounts and special offers at physical stores, which can be redeemed by scanning QR codes.

[0198] Specific examples

[0199] Consider a case where a user participates in a tree planting activity on the weekend. When the user launches the "Eco Store Guide" app, the app uses its GPS function to identify the user's current location and collects information about tree planting activities taking place in the area. For example, a notification might be displayed saying, "A tree planting activity is being held in a park near you. Join in and contribute to reducing CO2 emissions!" When the user participates in the activity and enters the number of trees planted, the information is sent to the server and evaluated by the generation AI. Based on the evaluation results, reward points are awarded to the user's account and the user is notified within the app. The awarded points can be used for discounts at affiliated stores, etc.

[0200] Prompt Sentence Examples

[0201] An example of a prompt sent to the generative AI model is, "Please provide us with the latest information on eco-activities. Your current location is latitude 35.6895, longitude 139.6917. We are particularly looking for tree planting activities and eco-bag usage initiatives."

[0202] In this way, users can easily obtain the latest eco-activity information, participate in CO2 reduction activities, and receive rewards according to the degree of their contribution.

[0203] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0204] Step 1:

[0205] The user's device uses the GPS function to identify the user's current location and obtains the location information.

[0206] Input: User consent, device GPS data

[0207] Data processing: Obtain the longitude and latitude of the user's current location and generate location data

[0208] Output: Current location data (longitude, latitude)

[0209] Step 2:

[0210] The server uses a generative AI model to collect information on CO2 reduction activities around the world.

[0211] Input: A list of pre-configured data sources on the server (news sites, environmental organizations' websites, social media, etc.), a prompt

[0212] Data processing: The generative AI model gathers information based on the prompt, analyzes and filters relevant data

[0213] Output: A list of detailed information about CO2 reduction activities

[0214] Step 3:

[0215] The server analyzes and extracts CO2 reduction activity information related to the user's location information.

[0216] Input: User location data, list of collected CO2 reduction activity information

[0217] Data processing: Filter and extract relevant CO2 reduction activity information based on user location information

[0218] Output: CO2 reduction activity information related to user location information

[0219] Step 4:

[0220] The server converts the extracted information into a format that is easy for the user to understand.

[0221] Input: Extracted CO2 reduction activity information

[0222] Data processing: Generate notification messages and interface designs to convey information to users in an easy-to-understand manner.

[0223] Output: Messages and display content to notify the user

[0224] Step 5:

[0225] The server transmits the converted information to the user's terminal.

[0226] Input: Message or display content

[0227] Data processing: Send information using a protocol that transfers messages to the device

[0228] Output: Notifications and messages displayed on the user's device

[0229] Step 6:

[0230] The device records the user's activity level and transmits the data to a server.

[0231] Input: User activity data (e.g. QR code scan, manual input)

[0232] Data processing: Record the acquired activity data, convert it into a data format, and send it to the server.

[0233] Output: Activity data sent to the server

[0234] Step 7:

[0235] The server evaluates the amount of activity entered, calculates a reward based on the amount, and grants the reward to the user account.

[0236] Input: User activity data, reward calculation algorithm

[0237] Data processing: Based on activity data, an AI model evaluates contribution and calculates reward points

[0238] Output: Calculated reward points, points credited to user account

[0239] Step 8:

[0240] The server provides the user with instructions including information on eco-activities.

[0241] Input: Latest eco-activity information

[0242] Data processing: Send information to the user terminal in the specified format

[0243] Output: Eco-activity information and instructions notified to the user

[0244] Step 9:

[0245] The user's terminal allows the reward points to be used in the store.

[0246] Input: Reward points granted to user account, available at stores

[0247] Data processing: Manage the point usage process and generate QR codes for use in stores

[0248] Output: A valid point redemption method at the store (QR code, etc.)

[0249] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0250] This invention is a system that provides the latest information on CO2 reduction activities based on the user's location information, evaluates the user's contribution to CO2 reduction through their actions with rewards, and further increases the user's motivation by recognizing the user's emotional state using an emotion engine and adjusting the way information is presented.By combining generative AI and an emotion engine, this system always provides the latest information and helps users take action easily.

[0251] Program processing

[0252] 1. Obtaining user location information

[0253] A user accesses an application or website in the system and logs in.

[0254] With the user's consent, the device collects current location information (longitude and latitude).

[0255] The device sends the location information it collects to the server.

[0256] 2. Collection and processing of the latest information

[0257] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[0258] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[0259] The emotion engine analyzes the user's voice data and facial expression data to recognize their emotional state, and adjusts the way the collected information is presented to suit the user's emotional state.

[0260] For example, if the user is tired, provide a brief, encouraging message, and if they are proactive, provide a detailed, action-oriented message.

[0261] 3. Providing information and encouraging action

[0262] The server sends the converted information to the user's terminal.

[0263] The terminal displays the received information to the user so that the user can view it.

[0264] For example, a notification might appear saying, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[0265] The emotion engine monitors the user's emotional state and provides information at the appropriate time.

[0266] 4. Recording behavior and calculating rewards

[0267] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[0268] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the system.

[0269] The terminal transmits the input activity information to the server.

[0270] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[0271] The server calculates reward points based on the evaluation results and grants them to the user's account.

[0272] The terminal notifies the user of the reward points and allows the user to check the points.

[0273] Specific examples

[0274] Example 1: When a user participates in a tree planting activity

[0275] 1. User Activities

[0276] The user accesses the application and receives information about participating in a tree planting activity over the weekend, along with an encouraging message from the emotion engine.

[0277] Go to the designated location and plant 10 trees.

[0278] After the activity, participants enter the number of trees planted in the application and report, "I planted 10 trees today."

[0279] 2. System evaluation and rewards

[0280] The terminal sends the user's input to the server.

[0281] The server uses generated AI to evaluate the amount of CO2 reduction equivalent to planting 10 trees and awards, for example, 10 points.

[0282] The server notifies the user of the points and sends a message praising the user's efforts through the emotion engine.

[0283] Reward points will be added to your user account and you will receive a notification.

[0284] This system allows users to always receive the latest information on CO2 reduction activities, take specific actions based on that information, and receive rewards for their results. Furthermore, by using an emotion engine to provide information that corresponds to the user's emotional state, it is possible to motivate users and encourage more proactive CO2 reduction actions.

[0285] The processing flow will be explained below.

[0286] Step 1:

[0287] A user logs into an application or website on the system.

[0288] Step 2:

[0289] With the user's consent, the device collects current location information (longitude and latitude).

[0290] Step 3:

[0291] The device sends the location information it collects to the server.

[0292] Step 4:

[0293] The server uses generated AI to collect information on CO2 reduction activities around the world from multiple data sources (news sites, environmental organization websites, social media, etc.).

[0294] Step 5:

[0295] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[0296] Step 6:

[0297] The emotion engine analyzes the user's voice data and facial expression data to recognize their emotional state.

[0298] For example, the user provides facial expressions and voice through the application's camera and microphone, and the emotion engine evaluates the user's current emotional state.

[0299] Step 7:

[0300] The server converts the collected activity information into a user-friendly format based on the user's emotional state.

[0301] For example, if the user is tired, it generates a brief, encouraging message (e.g., "Why not relax and take part in a simple tree-planting event nearby?"), while if the user is proactive, it generates a detailed, actionable message (e.g., "There's a large-scale tree-planting event near your home. Plant lots of trees and contribute to reducing CO2 emissions!").

[0302] Step 8:

[0303] The server sends the converted information to the user's terminal.

[0304] Step 9:

[0305] The terminal displays the received information to the user so that the user can view it.

[0306] Step 10:

[0307] Based on the displayed information, the user participates in CO2 reduction activities (e.g., tree planting activities or environmental protection events).

[0308] Step 11:

[0309] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the application.

[0310] Step 12:

[0311] The terminal transmits the input activity information to the server.

[0312] Step 13:

[0313] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[0314] Step 14:

[0315] The server calculates reward points based on the evaluation results and grants them to the user's account.

[0316] Step 15:

[0317] The terminal notifies the user of the reward points and allows the user to check the points.

[0318] The emotion engine also reassess the user's emotional state and sends a message praising their efforts (e.g., "Amazing! Your contribution will save the planet!").

[0319] Through these steps, the system provides users with customized information on CO2 reduction activities based on their location information and emotional state, and encourages them to contribute to the environment by evaluating and rewarding their actions.

[0320] Example 2

[0321] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0322] Conventional CO2 reduction activity information provision systems have insufficient collection and analysis of the latest information, making it difficult to provide appropriate information based on the user's location information and emotional state. In addition, there are issues with the cumbersome calculation of rewards based on the user's specific activity level, making it difficult to maintain user motivation.

[0323] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0324] In this invention, the server includes a means for acquiring user location information, a means for using a generation AI to collect information on CO2 reduction activities around the world, and a means for analyzing the collected information and extracting activity information related to the user's location information, thereby making it possible to provide the latest CO2 reduction activity information based on the user's location information.

[0325] The server also includes means for analyzing the user's emotional state, means for adjusting the presentation method of the collected information according to the user's emotional state, means for converting the extracted information into a format that is easy for the user to understand, means for transmitting the converted information to the user's terminal, means for inputting and transmitting the user's activity level, means for evaluating the input activity level, calculating a reward based on it, and adding the reward to the user's account, and means for notifying the user of the reward points. This realizes an effective information provision and reward system that is tailored to the user's emotional state, increases the user's motivation, and promotes more proactive CO2 reduction activities.

[0326] "Means for obtaining user location information" refers to a function that collects longitude and latitude data from the device with the user's consent and transmits it to a server.

[0327] "Means of using generative AI to collect information on CO2 reduction activities around the world" is a function that uses generative AI to obtain information on CO2 reduction activities from a variety of data sources, such as news sites, websites of environmental protection organizations, and social media.

[0328] "Means for analyzing collected information and extracting activity information related to the user's location information" refers to a function that analyzes the data collected by the generation AI and identifies CO2 reduction activities and event information that are closely related to the user's current location.

[0329] The "means for analyzing the user's emotional state" is a function that uses technology for analyzing voice data and facial expression data to recognize the user's emotional state in real time.

[0330] "Means for adjusting the presentation of collected information to match the user's emotional state" refers to a function that dynamically changes the format and content of information provided to the user based on the recognized emotional state.

[0331] The "means of converting extracted information into a user-friendly format" is a function that converts technical terms and complex data into a user-friendly format.

[0332] The "means for transmitting the converted information to the user's device" is a function for transmitting the converted information from the server to the user's device as a push notification or an in-application message.

[0333] "Means for inputting and transmitting user activity data" is a function that provides an interface for users to input details of their activities (e.g., number of trees planted) and transmit that information to the server.

[0334] "Means of evaluating the amount of activity entered, calculating rewards based on that, and granting rewards to the user's account" refers to a function in which the generation AI analyzes the entered activity data, calculates the contribution to CO2 reduction, calculates reward points, and reflects those points in the user's account.

[0335] The "means for notifying the user of the reward points" is a function that notifies the user that the calculated reward points have been added to the user's account.

[0336] The present invention is a system that provides users with up-to-date information on CO2 reduction activities based on their location information, helping them take action and contribute to CO2 reduction. Furthermore, it uses an emotion engine to recognize the user's emotional state and adjusts the way information is presented to increase the user's motivation. An embodiment of this system is described below.

[0337] First, a user accesses the system's application or website and logs in. With the user's consent, the device collects and transmits current location information (longitude and latitude) to the server.

[0338] The server uses a generative AI (e.g., OpenAI's GPT-4 (registered trademark)) to collect information on CO2 reduction activities from various data sources, such as news sites, websites of environmental protection organizations, and social media. This information collection is performed on a regular schedule. The generative AI analyzes the collected data and extracts activity information related to the user's location information.

[0339] The server then uses an emotion engine to analyze the user's voice and facial expression data to recognize their emotional state in real time. The voice recognition tool is Google Cloud Speech-to-Text API, and the facial expression recognition tool is Face++. Based on the acquired emotional state, the server adjusts how the collected information is presented. For example, if the user is determined to be tired, it will provide a concise, encouraging message, while if the user is determined to be proactive, it will provide a detailed, action-oriented message.

[0340] As a concrete example, the following message is provided:

[0341] "This weekend, a tree planting event will be held in your town. Join in and help reduce CO2 emissions!"

[0342] Furthermore, if the user participates in CO2 reduction activities based on the information provided, the amount of activity (e.g., number of trees planted) is reported within the application. The device sends this information to the server, which uses a generation AI to evaluate the amount of activity entered. The server calculates the contribution to CO2 reduction and calculates reward points, which are then added to the user's account. The user is then notified that the reward points have been added.

[0343] Through this series of processes, users can always receive the latest information on CO2 reduction activities, take specific actions based on that information, and receive rewards for their results.In addition, by using the emotion engine to provide information according to the user's emotional state, users' motivation is enhanced, and more proactive CO2 reduction actions can be expected.

[0344] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0345] Step 1:

[0346] A user accesses an application or website in the system and logs in.

[0347] Specifically, the user opens the application, enters their ID and password, and presses the "Login" button.

[0348] Input: User ID and password

[0349] Output: User credentials

[0350] Step 2:

[0351] With the user's consent, the device collects location information (longitude and latitude) and sends it to the server.

[0352] Specifically, the app displays a pop-up asking "Do you want to allow location access?" and the user selects "Allow."

[0353] Input: User consent

[0354] Output: User's location (longitude and latitude)

[0355] Step 3:

[0356] The server uses generated AI to collect information on CO2 reduction activities from a variety of data sources, including news sites, websites of environmental protection organizations, and social media.

[0357] Specifically, the generating AI acquires information based on a regular schedule.

[0358] Input: Raw data such as news articles, blog posts, and social media posts

[0359] Output: Organized information on CO2 reduction activities

[0360] Step 4:

[0361] The server analyzes the collected information using generated AI and extracts activity information related to the user's location.

[0362] Specifically, the generative AI categorizes the collected data and filters relevant information based on location information.

[0363] Input: Organized CO2 reduction activity information, user location information

[0364] Output: Activity information related to the user's location

[0365] Step 5:

[0366] The server uses an emotion engine to analyze the user's voice data and facial expression data and recognize their emotional state.

[0367] Specifically, the user provides data via the smartphone's camera and microphone, and the emotion engine analyzes it in real time.

[0368] Input: User's voice data, facial expression data

[0369] Output: User's emotional state data

[0370] Step 6:

[0371] Based on the results of the emotion engine, the server adjusts the presentation of the collected information to suit the user's emotional state.

[0372] Specifically, the generation AI generates an appropriate message depending on the emotional state.

[0373] Input: User's emotional state data, related activity information

[0374] Output: Messages tailored to your emotional state

[0375] Step 7:

[0376] The server transmits the converted information to the user's terminal.

[0377] Specifically, the server generates a notification message and sends it to the terminal as a push notification.

[0378] Input: Messages tailored to your emotional state

[0379] Output: Notification to the user's device

[0380] Step 8:

[0381] CO2 reduction activities will be carried out based on the information received by the user.

[0382] The user enters the amount and content of their activity into the app, and the device sends the data to the server.

[0383] Specifically, a user participates in an event, and after participating in the event, they enter "I planted 10 trees today" in the app and press the "Send" button.

[0384] Input: User activity details (number of trees planted, etc.)

[0385] Output: Activity details data

[0386] Step 9:

[0387] The server uses generated AI to evaluate the amount of activity entered and calculates the contribution to CO2 reduction.

[0388] Specifically, the generating AI analyzes the user's input data and evaluates it as, for example, "Planting 10 trees = 10 points."

[0389] Input: Activity details data

[0390] Output: Contribution data

[0391] Step 10:

[0392] The server calculates reward points based on the contribution and credits them to the user's account.

[0393] Specifically, after the points are calculated, the server automatically adds the points to the user's account.

[0394] Input: Contribution data

[0395] Output: Reward points

[0396] Step 11:

[0397] The terminal notifies the user of the reward points and allows the user to check the points.

[0398] Specifically, the app will display a notification to the user saying "10 points added!"

[0399] Input: Reward Points

[0400] Output: Point notification

[0401] (Application example 2)

[0402] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0403] Conventional CO2 reduction activity support systems are limited to providing users with location information and the latest information, and lack advice on which route users should take from a security perspective. Furthermore, because they present information without taking into account the user's emotional state, they are unable to provide appropriate support when motivation is low. These issues make it difficult to encourage users to take proactive action, and CO2 reduction activities are not fully effective. Furthermore, there is a need for information provision on CO2 reduction activities that is linked to ensuring safety.

[0404] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0405] In this invention, the server includes means for sorting collected information and security precautions, means for analyzing the user's emotional state using an emotion engine and adjusting the way information is presented, and means for proposing a safe route taking into account the user's location information. This makes it possible to provide information at an appropriate time according to the user's emotional state and to give advice on selecting a safe route, allowing the user to actively and safely participate in CO2 reduction activities.

[0406] "Means for obtaining location information" refers to technical means for identifying the user's current geographical location.

[0407] "Generative AI" is a technology that uses artificial intelligence to generate new information from data.

[0408] An "information collection means" is a method or device for gathering data relevant to a particular purpose.

[0409] "Means of analyzing information" refers to techniques for analyzing collected data and extracting meaningful information.

[0410] "Means for adjusting the method of presenting information" refers to a technique for changing the format and timing of information presented depending on the user's emotional state.

[0411] The "means for inputting and transmitting the amount of activity" refers to a means for recording the amount and content of the user's actions in the system and transmitting them to the server.

[0412] The "means for evaluating the amount of activity and calculating the reward" is a technology for measuring the actions performed by the user and calculating the reward for the user based on the results.

[0413] A "reward granting means" is a technology for recording and adding rewards to a user account.

[0414] "Means for selecting security precautions" refers to a technology that extracts and emphasizes important safety information from the information provided to users.

[0415] An "emotion engine" is a technology that analyzes a user's emotional state from facial expressions, voice, etc.

[0416] The "means for suggesting a safe route" is a technology that takes into account the user's location information and provides the safest route.

[0417] The system for realizing this invention is configured using the following hardware and software, including, as its main elements, a means for acquiring user location information, a means for sorting collected information and security precautions, a means for analyzing the user's emotional state using an emotion engine and adjusting the way information is presented, a means for proposing a safe route taking into account the user's location information, and a means for collecting information using a generative AI.

[0418] 1. Obtaining user location information

[0419] The server obtains location information using the user's smartphone or GPS device. When the user logs in to the application and provides consent for location information collection, the current location information (longitude and latitude) is sent to the server.

[0420] Hardware: GPS devices, smartphones

[0421] Software: Android / iOS SDK, location information acquisition API

[0422] 2. Information collection and analysis

[0423] The server uses generative AI (such as OpenAI GPT-3) to collect the latest information on global CO2 reduction activities and security from multiple sources. The AI ​​analyzes the collected information and extracts activity and security information related to the user's location. This information is formatted to match the user's emotional state.

[0424] Hardware: Servers, database servers

[0425] Software: NLP model, multi-source data collection API

[0426] 3. Adjustment by Emotion Engine

[0427] The emotion engine analyzes the user's voice and facial expression data to recognize their emotional state, and then adjusts how the collected information is presented. For example, if the user is tired, it will provide a concise, encouraging message, while if they are proactive, it will provide a detailed, actionable message.

[0428] Hardware: Audio input device (microphone), camera

[0429] Software: Sentiment Analysis Engine

[0430] 4. Safe Route Suggestion

[0431] The server will suggest the safest route based on the user's location information, allowing users to minimize risks when participating in CO2 reduction activities. For example, routes that avoid dangerous areas at night will be automatically suggested.

[0432] Hardware: GPS devices, smartphones

[0433] Software: Map API, route calculation algorithm

[0434] 5. Recording behavior and calculating rewards

[0435] The server records the content and amount of the user's actions and calculates rewards based on that information. The user inputs their actions through the application, and the server evaluates them using a generative AI. Reward points are calculated based on the evaluation results and awarded to the user's account.

[0436] Hardware: Smartphones, servers

[0437] Software: Database (MySQL (registered trademark) / PostgreSQL), reward management system

[0438] Prompt Sentence Examples

[0439] Here are some examples of prompts to input to the generative AI model:

[0440] Collect the latest information on CO2 reduction activities and security around the world and provide appropriate activity information based on the user's location. Adjust the way information is presented depending on the user's emotional state. For example, if the user is tired, provide an encouraging message, and if they are active, provide a detailed call-to-action message.

[0441] This provides users with CO2 reduction activity information optimized for their location and emotional state, while also ensuring security, allowing users to proactively and safely engage in activities.

[0442] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0443] Step 1:

[0444] Obtaining user location information

[0445] The user logs in to the application and gives consent to obtain location information.

[0446] Input: User consent, public location information

[0447] Data processing: Obtain location information (longitude and latitude) from the GPS chip

[0448] Output: Sends the user's current location to the server

[0449] How it works: An app on your smartphone collects location information from the GPS chip and sends it to a server.

[0450] Step 2:

[0451] Gathering the latest information

[0452] The server uses generated AI to collect information on CO2 reduction activities and security around the world.

[0453] Input: Data sources such as news sites, environmental organization websites, and social media.

[0454] Data processing: Generative AI analyzes information and extracts relevant information

[0455] Output: The latest information collected and analyzed

[0456] How it works: The server retrieves information from multiple data sources through an API, and the generating AI analyzes the data.

[0457] Step 3:

[0458] Emotional state analysis

[0459] The device uses an emotion engine to analyze the user's voice data and facial expression data and recognize their emotional state.

[0460] Input: User's voice data, facial expression data

[0461] Data processing: Identifying emotional states using speech recognition and facial expression analysis algorithms

[0462] Output: The user's current emotional state

[0463] How it works: Your smartphone or connected device captures your voice and facial expression data, which is then analyzed by the emotion engine.

[0464] Step 4:

[0465] Adjusting how information is presented

[0466] The server adjusts how information is presented based on the output of the emotion engine.

[0467] Input: User's emotional state, collected information

[0468] Data processing: determining the appropriate information form and timing

[0469] Output: Tailored information presentation

[0470] How it works: The server optimizes the timing and content of information presentation based on the user's emotional state and location information.

[0471] Step 5:

[0472] Safe route suggestions

[0473] The server takes into account the user's location and suggests the safest route.

[0474] Input: current user location, map information, security notices

[0475] Data calculation: Calculates safe routes and avoids dangerous areas

[0476] Output: Recommended safe route

[0477] How it works: The server uses map APIs and security information to calculate a safe route and send it to the user's smartphone.

[0478] Step 6:

[0479] Recording behavior and calculating rewards

[0480] The user inputs the amount and content of their actions into the application, and the server evaluates them using a generative AI to calculate reward points.

[0481] Input: Activity amount and details of the activity entered by the user

[0482] Data calculation: Evaluating actions and calculating reward points

[0483] Output: Reward points and notification

[0484] How it works: The server records the user's input, and the generating AI evaluates the activity level and calculates reward points. The reward points are added to the user's account and notified.

[0485] Prompt Sentence Examples

[0486] Here are some examples of prompts to input to the generative AI model:

[0487] Collect the latest information on CO2 reduction activities and security around the world and provide appropriate activity information based on the user's location. Adjust the way information is presented depending on the user's emotional state. For example, if the user is tired, provide an encouraging message, and if they are active, provide a detailed call-to-action message.

[0488] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0489] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0490] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0491] [Second embodiment]

[0492] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0493] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0494] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0495] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0496] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0497] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0498] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0499] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0500] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0501] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0502] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0503] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0504] This invention is a system that provides users with the latest information on CO2 reduction activities based on their location information and rewards them for their contribution to CO2 reduction through their actions. This system uses generation AI to always provide the latest information and help users take action easily.

[0505] Program processing

[0506] 1. Obtaining user location information

[0507] A user accesses an application or website in the system and logs in.

[0508] With the user's consent, the device collects current location information (longitude and latitude).

[0509] The device sends the location information it collects to the server.

[0510] 2. Collection and processing of the latest information

[0511] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[0512] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[0513] The server converts the extracted information into a format that is easy for the user to understand.

[0514] 3. Providing information and encouraging action

[0515] The server sends the converted information to the user's terminal.

[0516] The terminal displays the received information to the user so that the user can view it.

[0517] For example, a notification might appear saying, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[0518] 4. Recording behavior and calculating rewards

[0519] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[0520] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the system.

[0521] The terminal transmits the input activity information to the server.

[0522] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[0523] The server calculates reward points based on the evaluation results and grants them to the user's account.

[0524] An in-app notification will be sent to allow users to check their reward points.

[0525] Specific examples

[0526] Example 1: When a user participates in a tree planting activity

[0527] 1. User Activities

[0528] A user accesses the application and receives information about participating in a tree planting weekend.

[0529] Go to the designated location and plant 10 trees.

[0530] After the activity, participants enter the number of trees planted in the application and report, "I planted 10 trees today."

[0531] 2. System evaluation and rewards

[0532] The terminal sends the user's input to the server.

[0533] The server uses generated AI to evaluate the amount of CO2 reduction equivalent to planting 10 trees and awards, for example, 10 points.

[0534] Reward points will be added to your user account and you will receive a notification.

[0535] This system allows users to always receive the latest information on CO2 reduction activities, take concrete action based on that information, and receive rewards for their results. This encourages active participation by users and contributes to measures against global warming.

[0536] The processing flow will be explained below.

[0537] Step 1:

[0538] A user logs into an application or website on the system.

[0539] Step 2:

[0540] With the user's consent, the device collects current location information (longitude and latitude).

[0541] Step 3:

[0542] The device sends the location information it collects to the server.

[0543] Step 4:

[0544] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[0545] Step 5:

[0546] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[0547] Step 6:

[0548] The server converts the extracted information into a format that is easy for the user to understand.

[0549] For example, you could convert it into a notification that reads, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[0550] Step 7:

[0551] The server sends the converted information to the user's terminal.

[0552] Step 8:

[0553] The terminal displays the received information to the user so that the user can view it.

[0554] Step 9:

[0555] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[0556] Step 10:

[0557] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the application.

[0558] Step 11:

[0559] The terminal transmits the input activity information to the server.

[0560] Step 12:

[0561] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[0562] Step 13:

[0563] The server calculates reward points based on the evaluation results and grants them to the user's account.

[0564] Step 14:

[0565] The terminal notifies the user of the reward points and allows the user to check the points.

[0566] Example 1

[0567] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0568] Conventional information provision systems for CO2 reduction activities lacked specific action plans and evaluation functions that allowed users to easily participate, making it difficult to visualize an individual's environmental contribution and provide appropriate rewards. Furthermore, they lacked a mechanism to encourage user action by providing the latest information in a timely manner. As a result, many users missed the opportunity to actively participate in CO2 reduction activities.

[0569] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0570] In this invention, the server includes means for acquiring user location information, means for using a generation AI to collect information on CO2 reduction activities around the world, means for analyzing the collected information and extracting activity information related to the user's location information, means for converting the extracted information into a format that is easy for the user to understand, means for transmitting the converted information to the user's device, means for inputting and transmitting the user's activity amount, means for evaluating the input activity amount, calculating a reward based on the amount, and granting the reward to the user's account, means for displaying a reward grant notification on the user's device, and means for analyzing the collected information using natural language processing technology.This allows users to easily obtain the latest CO2 reduction activity information, create specific action plans, and receive appropriate rewards for their actions.

[0571] "User location information" refers to the longitude and latitude data of the user's current location.

[0572] "Generative AI" is a system that uses machine learning and artificial intelligence techniques to generate the models and data needed for specific tasks.

[0573] "CO2 reduction activities" are specific actions or projects aimed at reducing carbon dioxide emissions.

[0574] "Data sources" refers to the websites, news sites, environmental organization websites, social media, etc. from which information is collected.

[0575] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[0576] A "user terminal" is a device used by a user, such as a smartphone or PC.

[0577] "Reward points" are points that users can earn as a result of participating in CO2 reduction activities and are returned to them.

[0578] "Activity information" is specific information such as the date, time, location, and content of CO2 reduction activities in which users can participate.

[0579] "Amount of activity" refers to the specific amount and content of CO2 reduction activities that a user has actually undertaken (e.g., number of trees planted).

[0580] "Evaluation results" are results that show the effectiveness of the CO2 reduction activities carried out by the user in numerical values ​​or points.

[0581] This invention is a system that provides users with the latest information on CO2 reduction activities based on their location information and rewards them for their contribution to CO2 reduction through their actions. This system uses a generative AI model to constantly provide the latest information and help users easily take action.

[0582] Overview of program processing

[0583] This system consists of three main components: a server, a terminal, and a user. The server processes data using a generative AI model and a database. A terminal is a device such as a smartphone or PC that is used by a user. Users access the system through an application or website to provide location information and enter their activities.

[0584] Hardware and Software

[0585] The server uses cloud-based infrastructure and is capable of processing large amounts of data. Specific examples include cloud services such as Amazon Web Services (AWS) and Google Cloud Platform (GCP). The generative AI model uses natural language processing technology. Examples include OpenAI's GPT-3 and BERT. Devices that can be used include smartphones running iOS or Android, and computers running Windows or macOS.

[0586] Data processing and calculation

[0587] The server first collects information on CO2 reduction activities from various data sources, including news sites, environmental organization websites, and social media. The collected data is analyzed by a generative AI model to extract activity information related to the user's location. The extracted information is then converted into a user-friendly format using natural language processing technology. Finally, the converted information is sent to the user's device and displayed.

[0588] When a user performs a CO2 reduction activity, they input the activity details and amount into the application. The device sends this input information to the server, which then evaluates the activity using generated AI. Based on the evaluation, reward points are awarded to the user's account. Points can be viewed on the user's device.

[0589] Specific examples

[0590] Example 1: When a user participates in a tree planting activity

[0591] 1. A user accesses the application and receives information about participating in a tree planting weekend.

[0592] 2. The user goes to a designated location and plants 10 trees.

[0593] 3. After the activity, report the number of trees planted in the application and enter "I planted 10 trees today."

[0594] 4. The device sends the user's input to the server, which evaluates it using the generating AI and assigns 10 points to the user's account.

[0595] 5. Users will see the reward points added in the app and receive a notification.

[0596] Prompt Sentence Examples

[0597] You are a user. This weekend, a tree planting event will be held in your town. Please participate and contribute to reducing CO2 emissions. Please participate in the tree planting event and report it on this system after the event.

[0598] In this way, the present invention provides a system that allows users to always obtain the latest information on CO2 reduction activities, take concrete actions based on that information, and receive rewards for their results, thereby encouraging active participation by users and contributing to global warming countermeasures.

[0599] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0600] Step 1:

[0601] A user accesses a system application or website and logs in. After the user enters their username and password and completes authentication, the device begins acquiring location information. Input: User authentication information. Output: Authentication success flag. Specifically, the user enters authentication information on the app's login screen, the device sends it to the server, and authentication is successful.

[0602] Step 2:

[0603] With the user's consent, the device collects current location information (longitude and latitude). Input: User's consent. Output: Location data (longitude, latitude). Specifically, the app displays a pop-up message requesting permission to collect location information, and once the user agrees, the device uses its GPS function to obtain location information.

[0604] Step 3:

[0605] The location information collected by the device is sent to the server. Input: Location information data. Output: Server-side location information storage completion flag. Specifically, the device encrypts the location information and sends it to the server, which then stores it in a database.

[0606] Step 4:

[0607] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, websites of environmental protection organizations, social media, etc.). Input: List of data sources. Output: Collected data. Specifically, the server runs a pre-configured crawling program to collect information from the data sources.

[0608] Step 5:

[0609] The generation AI analyzes the collected information and extracts activity information related to the user's location information. Input: collected data, location data. Output: related activity information. Specifically, the generation AI uses natural language processing technology to analyze the collected data, extract important information such as the activity name, location, date and time, and compare it with the user's location information.

[0610] Step 6:

[0611] The server converts the extracted information into a format that is easy for users to understand. Input: Related activity information. Output: Converted information. Specifically, the server formats the information and summarizes it into user-friendly text.

[0612] Step 7:

[0613] The server sends the converted information to the user's device. Input: Converted information. Output: Flag indicating completion of sending information to the device. Specifically, the server sends the converted information to the user's device in JSON format or similar.

[0614] Step 8:

[0615] The terminal displays the received information to the user so that the user can view it. Input: Converted information. Output: Display of information that can be viewed by the user. Specifically, the application analyzes the received data and displays it in a pop-up notification or on the interface.

[0616] Step 9:

[0617] Based on the information presented, the user carries out specific CO2 reduction activities (e.g., tree planting or participating in environmental protection events). Input: Presented information. Output: Details of the activity to be carried out. Specifically, the user follows the notification and carries out the activity at the specified location and time.

[0618] Step 10:

[0619] After the activity, the user inputs the specific amount and content of the activity they performed (e.g., number of trees planted) into the system. Input: Content of the activity performed. Output: Activity report data. Specifically, the user inputs the content of the activity into a form within the application.

[0620] Step 11:

[0621] The terminal sends the entered activity information to the server. Input: Activity report data. Output: Activity information storage completion flag on the server side. Specifically, the terminal sends the activity report data to the server, and the server stores it in a database.

[0622] Step 12:

[0623] The server uses the generation AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction. Input: Activity report data. Output: Evaluation results. Specifically, the generation AI analyzes the amount and content of the activity and evaluates the effect of CO2 reduction.

[0624] Step 13:

[0625] The server calculates reward points based on the evaluation results and grants them to the user's account. Input: Evaluation results. Output: Reward points. Specifically, the server calculates reward points based on the evaluation results and grants them to the user's account.

[0626] Step 14:

[0627] A notification is sent within the app so that the user can check their reward points. Input: Reward points. Output: Points awarded notification. Specifically, the application notifies the user that points have been awarded and presents a screen where the user can check their points.

[0628] (Application example 1)

[0629] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0630] CO2 reduction activities aimed at environmental protection are most effective when many individuals participate in them. However, at present, there are limited ways for general users to understand what CO2 reduction activities they can participate in or to evaluate the extent to which their activities have contributed to CO2 reduction. Furthermore, there is no adequate reward system in place, which means that general users have little motivation to participate. The purpose of this project is to solve this problem, encourage active participation by users, and promote effective CO2 reduction activities.

[0631] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0632] In this invention, the server includes: means for acquiring user location information; means for using a generation AI to collect information on CO2 reduction activities around the world; means for analyzing the collected information and extracting activity information related to the user's location information; means for converting the extracted information into a format that is easy for the user to understand; means for transmitting the converted information to the user's terminal; means for the terminal to record the user's activity amount and transmit the recorded information to the server; means for evaluating the input activity amount, calculating a reward based on the amount, and granting the reward to the user's account; means for providing instructions to the user including information on eco-activities; and means for making reward points available for use in the store. This allows users to always receive the latest information on CO2 reduction activities and earn rewards based on their activities, thereby enabling them to more actively participate in environmental protection activities.

[0633] The "means for acquiring user location information" refers to a device or software function that collects data necessary to identify the user's current location.

[0634] "Means for collecting information on CO2 reduction activities around the world using generative AI" refers to a device or software function that uses artificial intelligence technology to widely collect the latest information on CO2 reduction activities in various locations.

[0635] "Means for analyzing collected information and extracting activity information related to the user's location information" refers to the function of a device or software that analyzes collected data and identifies and extracts information about CO2 reduction activities related to the user's current location.

[0636] The "means for converting extracted information into a user-friendly format" refers to the function of a device or software that processes the analyzed and extracted information into a format that is easy for the user to understand.

[0637] The "means for transmitting the converted information to the user's terminal" refers to the function of a device or software for transmitting the processed information to the device used by the user.

[0638] "Means for the terminal to record the amount of user activity and send it to the server" refers to the function of a device or software that records the user's behavior on the terminal and sends the data to a central server.

[0639] "Means for evaluating the amount of activity entered, calculating rewards based thereon, and granting rewards to the user account" refers to the function of a device or software that evaluates the amount and quality of activity performed by a user and calculates and grants rewards accordingly.

[0640] The "means for providing a user with instructions including information on eco-friendly activities" refers to a function of a device or software that conveys behavioral instructions and information related to environmental protection to a user.

[0641] "Means for enabling reward points to be used in-store" refers to a device or software function that allows a user to use the reward points they have earned for discounts, payments, etc. at physical stores.

[0642] This invention provides a system that allows users to participate in CO2 reduction activities, receive rewards based on the evaluation of their contributions. The system acquires the user's location information, uses AI to collect and analyze the latest CO2 reduction activity information, and presents it to the user in an easy-to-understand manner. It also records the user's activity level and awards rewards based on the user's contribution.

[0643] Main components and their functions

[0644] 1. How to obtain user location information

[0645] The user's device (e.g., a smartphone) acquires the user's current location using GPS, etc. This location information is used in the next step.

[0646] 2. A means of using generative AI to collect information on CO2 reduction activities around the world

[0647] The server uses generative AI to collect the latest information on CO2 reduction activities from a variety of data sources, including news sites, environmental organization websites, and social media.

[0648] 3. A means of analyzing the collected information and extracting activity information related to the user's location information.

[0649] The server uses the generated AI to analyze the acquired user location information and extract information on CO2 reduction activities in which the user can participate.

[0650] 4. A means of converting the extracted information into a user-friendly format

[0651] The server converts the extracted information into a format that is easy for the user to understand and displays it, for example, through notification messages or an in-app interface.

[0652] 5. Means for transmitting the converted information to the user's terminal

[0653] The converted information is sent from the server to the user's terminal and notified in real time.

[0654] 6. How the device records the user's activity and sends it to the server

[0655] The user's device records the amount of CO2 reduction activity they have actually performed by scanning a QR code or manually entering it, and this information is sent to the server.

[0656] 7. A means for evaluating the amount of activity entered, calculating rewards based on the amount, and crediting the rewards to the user account.

[0657] The server uses the AI ​​generator to evaluate the amount of activity entered by the user and calculates reward points based on the contribution. The calculated reward is credited to the user's account and notified within the app.

[0658] 8. Means for providing users with instructions including eco-friendly activity information

[0659] The user's device provides the latest information on collected eco-activities and specific instructions for action.

[0660] 9. Means for reward points to be redeemed in-store

[0661] Users can use the reward points they earn for discounts and special offers at physical stores, which can be redeemed by scanning QR codes.

[0662] Specific examples

[0663] Consider a case where a user participates in a tree planting activity on the weekend. When the user launches the "Eco Store Guide" app, the app uses its GPS function to identify the user's current location and collects information about tree planting activities taking place in the area. For example, a notification might be displayed saying, "A tree planting activity is being held in a park near you. Join in and contribute to reducing CO2 emissions!" When the user participates in the activity and enters the number of trees planted, the information is sent to the server and evaluated by the generation AI. Based on the evaluation results, reward points are awarded to the user's account and the user is notified within the app. The awarded points can be used for discounts at affiliated stores, etc.

[0664] Prompt Sentence Examples

[0665] An example of a prompt sent to the generative AI model is, "Please provide us with the latest information on eco-activities. Your current location is latitude 35.6895, longitude 139.6917. We are particularly looking for tree planting activities and eco-bag usage initiatives."

[0666] In this way, users can easily obtain the latest eco-activity information, participate in CO2 reduction activities, and receive rewards according to the degree of their contribution.

[0667] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0668] Step 1:

[0669] The user's device uses the GPS function to identify the user's current location and obtains the location information.

[0670] Input: User consent, device GPS data

[0671] Data processing: Obtain the longitude and latitude of the user's current location and generate location data

[0672] Output: Current location data (longitude, latitude)

[0673] Step 2:

[0674] The server uses a generative AI model to collect information on CO2 reduction activities around the world.

[0675] Input: A list of pre-configured data sources on the server (news sites, environmental organizations' websites, social media, etc.), a prompt

[0676] Data processing: The generative AI model gathers information based on the prompt, analyzes and filters relevant data

[0677] Output: A list of detailed information about CO2 reduction activities

[0678] Step 3:

[0679] The server analyzes and extracts CO2 reduction activity information related to the user's location information.

[0680] Input: User location data, list of collected CO2 reduction activity information

[0681] Data processing: Filter and extract relevant CO2 reduction activity information based on user location information

[0682] Output: CO2 reduction activity information related to user location information

[0683] Step 4:

[0684] The server converts the extracted information into a format that is easy for the user to understand.

[0685] Input: Extracted CO2 reduction activity information

[0686] Data processing: Generate notification messages and interface designs to convey information to users in an easy-to-understand manner.

[0687] Output: Messages and display content to notify the user

[0688] Step 5:

[0689] The server transmits the converted information to the user's terminal.

[0690] Input: Message or display content

[0691] Data processing: Send information using a protocol that transfers messages to the device

[0692] Output: Notifications and messages displayed on the user's device

[0693] Step 6:

[0694] The device records the user's activity level and transmits the data to a server.

[0695] Input: User activity data (e.g. QR code scan, manual input)

[0696] Data processing: Record the acquired activity data, convert it into a data format, and send it to the server.

[0697] Output: Activity data sent to the server

[0698] Step 7:

[0699] The server evaluates the amount of activity entered, calculates a reward based on the amount, and grants the reward to the user account.

[0700] Input: User activity data, reward calculation algorithm

[0701] Data processing: Based on activity data, an AI model evaluates contribution and calculates reward points

[0702] Output: Calculated reward points, points credited to user account

[0703] Step 8:

[0704] The server provides the user with instructions including information on eco-activities.

[0705] Input: Latest eco-activity information

[0706] Data processing: Send information to the user terminal in the specified format

[0707] Output: Eco-activity information and instructions notified to the user

[0708] Step 9:

[0709] The user's terminal allows the reward points to be used in the store.

[0710] Input: Reward points granted to user account, available at stores

[0711] Data processing: Manage the point usage process and generate QR codes for use in stores

[0712] Output: A valid point redemption method at the store (QR code, etc.)

[0713] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0714] This invention is a system that provides the latest information on CO2 reduction activities based on the user's location information, evaluates the user's contribution to CO2 reduction through their actions with rewards, and further increases the user's motivation by recognizing the user's emotional state using an emotion engine and adjusting the way information is presented.By combining generative AI and an emotion engine, this system always provides the latest information and helps users take action easily.

[0715] Program processing

[0716] 1. Obtaining user location information

[0717] A user accesses an application or website in the system and logs in.

[0718] With the user's consent, the device collects current location information (longitude and latitude).

[0719] The device sends the location information it collects to the server.

[0720] 2. Collection and processing of the latest information

[0721] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[0722] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[0723] The emotion engine analyzes the user's voice data and facial expression data to recognize their emotional state, and adjusts the way the collected information is presented to suit the user's emotional state.

[0724] For example, if the user is tired, provide a brief, encouraging message, and if they are proactive, provide a detailed, action-oriented message.

[0725] 3. Providing information and encouraging action

[0726] The server sends the converted information to the user's terminal.

[0727] The terminal displays the received information to the user so that the user can view it.

[0728] For example, a notification might appear saying, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[0729] The emotion engine monitors the user's emotional state and provides information at the appropriate time.

[0730] 4. Recording behavior and calculating rewards

[0731] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[0732] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the system.

[0733] The terminal transmits the input activity information to the server.

[0734] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[0735] The server calculates reward points based on the evaluation results and grants them to the user's account.

[0736] The terminal notifies the user of the reward points and allows the user to check the points.

[0737] Specific examples

[0738] Example 1: When a user participates in a tree planting activity

[0739] 1. User Activities

[0740] The user accesses the application and receives information about participating in a tree planting activity over the weekend, along with an encouraging message from the emotion engine.

[0741] Go to the designated location and plant 10 trees.

[0742] After the activity, participants enter the number of trees planted in the application and report, "I planted 10 trees today."

[0743] 2. System evaluation and rewards

[0744] The terminal sends the user's input to the server.

[0745] The server uses generated AI to evaluate the amount of CO2 reduction equivalent to planting 10 trees and awards, for example, 10 points.

[0746] The server notifies the user of the points and sends a message praising the user's efforts through the emotion engine.

[0747] Reward points will be added to your user account and you will receive a notification.

[0748] This system allows users to always receive the latest information on CO2 reduction activities, take specific actions based on that information, and receive rewards for their results. Furthermore, by using an emotion engine to provide information that corresponds to the user's emotional state, it is possible to motivate users and encourage more proactive CO2 reduction actions.

[0749] The processing flow will be explained below.

[0750] Step 1:

[0751] A user logs into an application or website on the system.

[0752] Step 2:

[0753] With the user's consent, the device collects current location information (longitude and latitude).

[0754] Step 3:

[0755] The device sends the location information it collects to the server.

[0756] Step 4:

[0757] The server uses generated AI to collect information on CO2 reduction activities around the world from multiple data sources (news sites, environmental organization websites, social media, etc.).

[0758] Step 5:

[0759] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[0760] Step 6:

[0761] The emotion engine analyzes the user's voice data and facial expression data to recognize their emotional state.

[0762] For example, the user provides facial expressions and voice through the application's camera and microphone, and the emotion engine evaluates the user's current emotional state.

[0763] Step 7:

[0764] The server converts the collected activity information into a user-friendly format based on the user's emotional state.

[0765] For example, if the user is tired, it generates a brief, encouraging message (e.g., "Why not relax and take part in a simple tree-planting event nearby?"), while if the user is proactive, it generates a detailed, actionable message (e.g., "There's a large-scale tree-planting event near your home. Plant lots of trees and contribute to reducing CO2 emissions!").

[0766] Step 8:

[0767] The server sends the converted information to the user's terminal.

[0768] Step 9:

[0769] The terminal displays the received information to the user so that the user can view it.

[0770] Step 10:

[0771] Based on the displayed information, the user participates in CO2 reduction activities (e.g., tree planting activities or environmental protection events).

[0772] Step 11:

[0773] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the application.

[0774] Step 12:

[0775] The terminal transmits the input activity information to the server.

[0776] Step 13:

[0777] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[0778] Step 14:

[0779] The server calculates reward points based on the evaluation results and grants them to the user's account.

[0780] Step 15:

[0781] The terminal notifies the user of the reward points and allows the user to check the points.

[0782] The emotion engine also reassess the user's emotional state and sends a message praising their efforts (e.g., "Amazing! Your contribution will save the planet!").

[0783] Through these steps, the system provides users with customized information on CO2 reduction activities based on their location information and emotional state, and encourages them to contribute to the environment by evaluating and rewarding their actions.

[0784] Example 2

[0785] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0786] Conventional CO2 reduction activity information provision systems have insufficient collection and analysis of the latest information, making it difficult to provide appropriate information based on the user's location information and emotional state. In addition, there are issues with the cumbersome calculation of rewards based on the user's specific activity level, making it difficult to maintain user motivation.

[0787] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0788] In this invention, the server includes a means for acquiring user location information, a means for using a generation AI to collect information on CO2 reduction activities around the world, and a means for analyzing the collected information and extracting activity information related to the user's location information, thereby making it possible to provide the latest CO2 reduction activity information based on the user's location information.

[0789] The server also includes means for analyzing the user's emotional state, means for adjusting the presentation method of the collected information according to the user's emotional state, means for converting the extracted information into a format that is easy for the user to understand, means for transmitting the converted information to the user's terminal, means for inputting and transmitting the user's activity level, means for evaluating the input activity level, calculating a reward based on it, and adding the reward to the user's account, and means for notifying the user of the reward points. This realizes an effective information provision and reward system that is tailored to the user's emotional state, increases the user's motivation, and promotes more proactive CO2 reduction activities.

[0790] "Means for obtaining user location information" refers to a function that collects longitude and latitude data from the device with the user's consent and transmits it to a server.

[0791] "Means of using generative AI to collect information on CO2 reduction activities around the world" is a function that uses generative AI to obtain information on CO2 reduction activities from a variety of data sources, such as news sites, websites of environmental protection organizations, and social media.

[0792] "Means for analyzing collected information and extracting activity information related to the user's location information" refers to a function that analyzes the data collected by the generation AI and identifies CO2 reduction activities and event information that are closely related to the user's current location.

[0793] The "means for analyzing the user's emotional state" is a function that uses technology for analyzing voice data and facial expression data to recognize the user's emotional state in real time.

[0794] "Means for adjusting the presentation of collected information to match the user's emotional state" refers to a function that dynamically changes the format and content of information provided to the user based on the recognized emotional state.

[0795] The "means of converting extracted information into a user-friendly format" is a function that converts technical terms and complex data into a user-friendly format.

[0796] The "means for transmitting the converted information to the user's device" is a function for transmitting the converted information from the server to the user's device as a push notification or an in-application message.

[0797] "Means for inputting and transmitting user activity data" is a function that provides an interface for users to input details of their activities (e.g., number of trees planted) and transmit that information to the server.

[0798] "Means of evaluating the amount of activity entered, calculating rewards based on that, and granting rewards to the user's account" refers to a function in which the generation AI analyzes the entered activity data, calculates the contribution to CO2 reduction, calculates reward points, and reflects those points in the user's account.

[0799] The "means for notifying the user of the reward points" is a function that notifies the user that the calculated reward points have been added to the user's account.

[0800] The present invention is a system that provides users with up-to-date information on CO2 reduction activities based on their location information, helping them take action and contribute to CO2 reduction. Furthermore, it uses an emotion engine to recognize the user's emotional state and adjusts the way information is presented to increase the user's motivation. An embodiment of this system is described below.

[0801] First, a user accesses the system's application or website and logs in. With the user's consent, the device collects and transmits current location information (longitude and latitude) to the server.

[0802] The server uses a generative AI (e.g., OpenAI's GPT-4) to collect information on CO2 reduction activities from various data sources, such as news sites, environmental protection organization websites, and social media. This information collection is performed on a regular schedule. The generative AI analyzes the collected data and extracts activity information related to the user's location.

[0803] The server then uses an emotion engine to analyze the user's voice and facial expression data to recognize their emotional state in real time. The voice recognition tool is Google Cloud Speech-to-Text API, and the facial expression recognition tool is Face++. Based on the acquired emotional state, the server adjusts how the collected information is presented. For example, if the user is determined to be tired, it will provide a concise, encouraging message, while if the user is determined to be proactive, it will provide a detailed, action-oriented message.

[0804] As a concrete example, the following message is provided:

[0805] "This weekend, a tree planting event will be held in your town. Join in and help reduce CO2 emissions!"

[0806] Furthermore, if the user participates in CO2 reduction activities based on the information provided, the amount of activity (e.g., number of trees planted) is reported within the application. The device sends this information to the server, which uses a generation AI to evaluate the amount of activity entered. The server calculates the contribution to CO2 reduction and calculates reward points, which are then added to the user's account. The user is then notified that the reward points have been added.

[0807] Through this series of processes, users can always receive the latest information on CO2 reduction activities, take specific actions based on that information, and receive rewards for their results.In addition, by using the emotion engine to provide information according to the user's emotional state, users' motivation is enhanced, and more proactive CO2 reduction actions can be expected.

[0808] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0809] Step 1:

[0810] A user accesses an application or website in the system and logs in.

[0811] Specifically, the user opens the application, enters their ID and password, and presses the "Login" button.

[0812] Input: User ID and password

[0813] Output: User credentials

[0814] Step 2:

[0815] With the user's consent, the device collects location information (longitude and latitude) and sends it to the server.

[0816] Specifically, the app displays a pop-up asking "Do you want to allow location access?" and the user selects "Allow."

[0817] Input: User consent

[0818] Output: User's location (longitude and latitude)

[0819] Step 3:

[0820] The server uses generated AI to collect information on CO2 reduction activities from a variety of data sources, including news sites, websites of environmental protection organizations, and social media.

[0821] Specifically, the generating AI acquires information based on a regular schedule.

[0822] Input: Raw data such as news articles, blog posts, and social media posts

[0823] Output: Organized information on CO2 reduction activities

[0824] Step 4:

[0825] The server analyzes the collected information using generated AI and extracts activity information related to the user's location.

[0826] Specifically, the generative AI categorizes the collected data and filters relevant information based on location information.

[0827] Input: Organized CO2 reduction activity information, user location information

[0828] Output: Activity information related to the user's location

[0829] Step 5:

[0830] The server uses an emotion engine to analyze the user's voice data and facial expression data and recognize their emotional state.

[0831] Specifically, the user provides data via the smartphone's camera and microphone, and the emotion engine analyzes it in real time.

[0832] Input: User's voice data, facial expression data

[0833] Output: User's emotional state data

[0834] Step 6:

[0835] Based on the results of the emotion engine, the server adjusts the presentation of the collected information to suit the user's emotional state.

[0836] Specifically, the generation AI generates an appropriate message depending on the emotional state.

[0837] Input: User's emotional state data, related activity information

[0838] Output: Messages tailored to your emotional state

[0839] Step 7:

[0840] The server transmits the converted information to the user's terminal.

[0841] Specifically, the server generates a notification message and sends it to the terminal as a push notification.

[0842] Input: Messages tailored to your emotional state

[0843] Output: Notification to the user's device

[0844] Step 8:

[0845] CO2 reduction activities will be carried out based on the information received by the user.

[0846] The user enters the amount and content of their activity into the app, and the device sends the data to the server.

[0847] Specifically, a user participates in an event, and after participating in the event, they enter "I planted 10 trees today" in the app and press the "Send" button.

[0848] Input: User activity details (number of trees planted, etc.)

[0849] Output: Activity details data

[0850] Step 9:

[0851] The server uses generated AI to evaluate the amount of activity entered and calculates the contribution to CO2 reduction.

[0852] Specifically, the generating AI analyzes the user's input data and evaluates it as, for example, "Planting 10 trees = 10 points."

[0853] Input: Activity details data

[0854] Output: Contribution data

[0855] Step 10:

[0856] The server calculates reward points based on the contribution and credits them to the user's account.

[0857] Specifically, after the points are calculated, the server automatically adds the points to the user's account.

[0858] Input: Contribution data

[0859] Output: Reward points

[0860] Step 11:

[0861] The terminal notifies the user of the reward points and allows the user to check the points.

[0862] Specifically, the app will display a notification to the user saying "10 points added!"

[0863] Input: Reward Points

[0864] Output: Point notification

[0865] (Application example 2)

[0866] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0867] Conventional CO2 reduction activity support systems are limited to providing users with location information and the latest information, and lack advice on which route users should take from a security perspective. Furthermore, because they present information without taking into account the user's emotional state, they are unable to provide appropriate support when motivation is low. These issues make it difficult to encourage users to take proactive action, and CO2 reduction activities are not fully effective. Furthermore, there is a need for information provision on CO2 reduction activities that is linked to ensuring safety.

[0868] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0869] In this invention, the server includes means for sorting collected information and security precautions, means for analyzing the user's emotional state using an emotion engine and adjusting the way information is presented, and means for proposing a safe route taking into account the user's location information. This makes it possible to provide information at an appropriate time according to the user's emotional state and to give advice on selecting a safe route, allowing the user to actively and safely participate in CO2 reduction activities.

[0870] "Means for obtaining location information" refers to technical means for identifying the user's current geographical location.

[0871] "Generative AI" is a technology that uses artificial intelligence to generate new information from data.

[0872] An "information collection means" is a method or device for gathering data relevant to a particular purpose.

[0873] "Means of analyzing information" refers to techniques for analyzing collected data and extracting meaningful information.

[0874] "Means for adjusting the method of presenting information" refers to a technique for changing the format and timing of information presented depending on the user's emotional state.

[0875] The "means for inputting and transmitting the amount of activity" refers to a means for recording the amount and content of the user's actions in the system and transmitting them to the server.

[0876] The "means for evaluating the amount of activity and calculating the reward" is a technology for measuring the actions performed by the user and calculating the reward for the user based on the results.

[0877] A "reward granting means" is a technology for recording and adding rewards to a user account.

[0878] "Means for selecting security precautions" refers to a technology that extracts and emphasizes important safety information from the information provided to users.

[0879] An "emotion engine" is a technology that analyzes a user's emotional state from facial expressions, voice, etc.

[0880] The "means for suggesting a safe route" is a technology that takes into account the user's location information and provides the safest route.

[0881] The system for realizing this invention is configured using the following hardware and software, including, as its main elements, a means for acquiring user location information, a means for sorting collected information and security precautions, a means for analyzing the user's emotional state using an emotion engine and adjusting the way information is presented, a means for proposing a safe route taking into account the user's location information, and a means for collecting information using a generative AI.

[0882] 1. Obtaining user location information

[0883] The server obtains location information using the user's smartphone or GPS device. When the user logs in to the application and provides consent for location information collection, the current location information (longitude and latitude) is sent to the server.

[0884] Hardware: GPS devices, smartphones

[0885] Software: Android / iOS SDK, location information acquisition API

[0886] 2. Information collection and analysis

[0887] The server uses generative AI (such as OpenAI GPT-3) to collect the latest information on global CO2 reduction activities and security from multiple sources. The AI ​​analyzes the collected information and extracts activity and security information related to the user's location. This information is formatted to match the user's emotional state.

[0888] Hardware: Servers, database servers

[0889] Software: NLP model, multi-source data collection API

[0890] 3. Adjustment by Emotion Engine

[0891] The emotion engine analyzes the user's voice and facial expression data to recognize their emotional state, and then adjusts how the collected information is presented. For example, if the user is tired, it will provide a concise, encouraging message, while if they are proactive, it will provide a detailed, actionable message.

[0892] Hardware: Audio input device (microphone), camera

[0893] Software: Sentiment Analysis Engine

[0894] 4. Safe Route Suggestion

[0895] The server will suggest the safest route based on the user's location information, allowing users to minimize risks when participating in CO2 reduction activities. For example, routes that avoid dangerous areas at night will be automatically suggested.

[0896] Hardware: GPS devices, smartphones

[0897] Software: Map API, route calculation algorithm

[0898] 5. Recording behavior and calculating rewards

[0899] The server records the content and amount of the user's actions and calculates rewards based on that information. The user inputs their actions through the application, and the server evaluates them using a generative AI. Reward points are calculated based on the evaluation results and awarded to the user's account.

[0900] Hardware: Smartphones, servers

[0901] Software: Database (MySQL / PostgreSQL), Reward Management System

[0902] Prompt Sentence Examples

[0903] Here are some examples of prompts to input to the generative AI model:

[0904] Collect the latest information on CO2 reduction activities and security around the world and provide appropriate activity information based on the user's location. Adjust the way information is presented depending on the user's emotional state. For example, if the user is tired, provide an encouraging message, and if they are active, provide a detailed call-to-action message.

[0905] This provides users with CO2 reduction activity information optimized for their location and emotional state, while also ensuring security, allowing users to proactively and safely engage in activities.

[0906] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0907] Step 1:

[0908] Obtaining user location information

[0909] The user logs in to the application and gives consent to obtain location information.

[0910] Input: User consent, public location information

[0911] Data processing: Obtain location information (longitude and latitude) from the GPS chip

[0912] Output: Sends the user's current location to the server

[0913] How it works: An app on your smartphone collects location information from the GPS chip and sends it to a server.

[0914] Step 2:

[0915] Gathering the latest information

[0916] The server uses generated AI to collect information on CO2 reduction activities and security around the world.

[0917] Input: Data sources such as news sites, environmental organization websites, and social media.

[0918] Data processing: Generative AI analyzes information and extracts relevant information

[0919] Output: The latest information collected and analyzed

[0920] How it works: The server retrieves information from multiple data sources through an API, and the generating AI analyzes the data.

[0921] Step 3:

[0922] Emotional state analysis

[0923] The device uses an emotion engine to analyze the user's voice data and facial expression data and recognize their emotional state.

[0924] Input: User's voice data, facial expression data

[0925] Data processing: Identifying emotional states using speech recognition and facial expression analysis algorithms

[0926] Output: The user's current emotional state

[0927] How it works: Your smartphone or connected device captures your voice and facial expression data, which is then analyzed by the emotion engine.

[0928] Step 4:

[0929] Adjusting how information is presented

[0930] The server adjusts how information is presented based on the output of the emotion engine.

[0931] Input: User's emotional state, collected information

[0932] Data processing: determining the appropriate information form and timing

[0933] Output: Tailored information presentation

[0934] How it works: The server optimizes the timing and content of information presentation based on the user's emotional state and location information.

[0935] Step 5:

[0936] Safe route suggestions

[0937] The server takes into account the user's location and suggests the safest route.

[0938] Input: current user location, map information, security notices

[0939] Data calculation: Calculates safe routes and avoids dangerous areas

[0940] Output: Recommended safe route

[0941] How it works: The server uses map APIs and security information to calculate a safe route and send it to the user's smartphone.

[0942] Step 6:

[0943] Recording behavior and calculating rewards

[0944] The user inputs the amount and content of their actions into the application, and the server evaluates them using a generative AI to calculate reward points.

[0945] Input: Activity amount and details of the activity entered by the user

[0946] Data calculation: Evaluating actions and calculating reward points

[0947] Output: Reward points and notification

[0948] How it works: The server records the user's input, and the generating AI evaluates the activity level and calculates reward points. The reward points are added to the user's account and notified.

[0949] Prompt Sentence Examples

[0950] Here are some examples of prompts to input to the generative AI model:

[0951] Collect the latest information on CO2 reduction activities and security around the world and provide appropriate activity information based on the user's location. Adjust the way information is presented depending on the user's emotional state. For example, if the user is tired, provide an encouraging message, and if they are active, provide a detailed call-to-action message.

[0952] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0953] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0954] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0955] [Third embodiment]

[0956] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0957] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0958] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0959] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0960] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0961] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0962] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0963] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0964] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0965] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0966] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0967] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0968] This invention is a system that provides users with the latest information on CO2 reduction activities based on their location information and rewards them for their contribution to CO2 reduction through their actions. This system uses generation AI to always provide the latest information and help users take action easily.

[0969] Program processing

[0970] 1. Obtaining user location information

[0971] A user accesses an application or website in the system and logs in.

[0972] With the user's consent, the device collects current location information (longitude and latitude).

[0973] The device sends the location information it collects to the server.

[0974] 2. Collection and processing of the latest information

[0975] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[0976] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[0977] The server converts the extracted information into a format that is easy for the user to understand.

[0978] 3. Providing information and encouraging action

[0979] The server sends the converted information to the user's terminal.

[0980] The terminal displays the received information to the user so that the user can view it.

[0981] For example, a notification might appear saying, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[0982] 4. Recording behavior and calculating rewards

[0983] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[0984] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the system.

[0985] The terminal transmits the input activity information to the server.

[0986] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[0987] The server calculates reward points based on the evaluation results and grants them to the user's account.

[0988] An in-app notification will be sent to allow users to check their reward points.

[0989] Specific examples

[0990] Example 1: When a user participates in a tree planting activity

[0991] 1. User Activities

[0992] A user accesses the application and receives information about participating in a tree planting weekend.

[0993] Go to the designated location and plant 10 trees.

[0994] After the activity, participants enter the number of trees planted in the application and report, "I planted 10 trees today."

[0995] 2. System evaluation and rewards

[0996] The terminal sends the user's input to the server.

[0997] The server uses generated AI to evaluate the amount of CO2 reduction equivalent to planting 10 trees and awards, for example, 10 points.

[0998] Reward points will be added to your user account and you will receive a notification.

[0999] This system allows users to always receive the latest information on CO2 reduction activities, take concrete action based on that information, and receive rewards for their results. This encourages active participation by users and contributes to measures against global warming.

[1000] The processing flow will be explained below.

[1001] Step 1:

[1002] A user logs into an application or website on the system.

[1003] Step 2:

[1004] With the user's consent, the device collects current location information (longitude and latitude).

[1005] Step 3:

[1006] The device sends the location information it collects to the server.

[1007] Step 4:

[1008] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[1009] Step 5:

[1010] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[1011] Step 6:

[1012] The server converts the extracted information into a format that is easy for the user to understand.

[1013] For example, you could convert it into a notification that reads, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[1014] Step 7:

[1015] The server sends the converted information to the user's terminal.

[1016] Step 8:

[1017] The terminal displays the received information to the user so that the user can view it.

[1018] Step 9:

[1019] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[1020] Step 10:

[1021] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the application.

[1022] Step 11:

[1023] The terminal transmits the input activity information to the server.

[1024] Step 12:

[1025] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[1026] Step 13:

[1027] The server calculates reward points based on the evaluation results and grants them to the user's account.

[1028] Step 14:

[1029] The terminal notifies the user of the reward points and allows the user to check the points.

[1030] Example 1

[1031] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1032] Conventional information provision systems for CO2 reduction activities lacked specific action plans and evaluation functions that allowed users to easily participate, making it difficult to visualize an individual's environmental contribution and provide appropriate rewards. Furthermore, they lacked a mechanism to encourage user action by providing the latest information in a timely manner. As a result, many users missed the opportunity to actively participate in CO2 reduction activities.

[1033] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1034] In this invention, the server includes means for acquiring user location information, means for using a generation AI to collect information on CO2 reduction activities around the world, means for analyzing the collected information and extracting activity information related to the user's location information, means for converting the extracted information into a format that is easy for the user to understand, means for transmitting the converted information to the user's device, means for inputting and transmitting the user's activity amount, means for evaluating the input activity amount, calculating a reward based on the amount, and granting the reward to the user's account, means for displaying a reward grant notification on the user's device, and means for analyzing the collected information using natural language processing technology.This allows users to easily obtain the latest CO2 reduction activity information, create specific action plans, and receive appropriate rewards for their actions.

[1035] "User location information" refers to the longitude and latitude data of the user's current location.

[1036] "Generative AI" is a system that uses machine learning and artificial intelligence techniques to generate the models and data needed for specific tasks.

[1037] "CO2 reduction activities" are specific actions or projects aimed at reducing carbon dioxide emissions.

[1038] "Data sources" refers to the websites, news sites, environmental organization websites, social media, etc. from which information is collected.

[1039] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[1040] A "user terminal" is a device used by a user, such as a smartphone or PC.

[1041] "Reward points" are points that users can earn as a result of participating in CO2 reduction activities and are returned to them.

[1042] "Activity information" is specific information such as the date, time, location, and content of CO2 reduction activities in which users can participate.

[1043] "Amount of activity" refers to the specific amount and content of CO2 reduction activities that a user has actually undertaken (e.g., number of trees planted).

[1044] "Evaluation results" are results that show the effectiveness of the CO2 reduction activities carried out by the user in numerical values ​​or points.

[1045] This invention is a system that provides users with the latest information on CO2 reduction activities based on their location information and rewards them for their contribution to CO2 reduction through their actions. This system uses a generative AI model to constantly provide the latest information and help users easily take action.

[1046] Overview of program processing

[1047] This system consists of three main components: a server, a terminal, and a user. The server processes data using a generative AI model and a database. A terminal is a device such as a smartphone or PC that is used by a user. Users access the system through an application or website to provide location information and enter their activities.

[1048] Hardware and Software

[1049] The server uses cloud-based infrastructure and is capable of processing large amounts of data. Specific examples include cloud services such as Amazon Web Services (AWS) and Google Cloud Platform (GCP). The generative AI model uses natural language processing technology. Examples include OpenAI's GPT-3 and BERT. Devices that can be used include smartphones running iOS or Android, and computers running Windows or macOS.

[1050] Data processing and calculation

[1051] The server first collects information on CO2 reduction activities from various data sources, including news sites, environmental organization websites, and social media. The collected data is analyzed by a generative AI model to extract activity information related to the user's location. The extracted information is then converted into a user-friendly format using natural language processing technology. Finally, the converted information is sent to the user's device and displayed.

[1052] When a user performs a CO2 reduction activity, they input the activity details and amount into the application. The device sends this input information to the server, which then evaluates the activity using generated AI. Based on the evaluation, reward points are awarded to the user's account. Points can be viewed on the user's device.

[1053] Specific examples

[1054] Example 1: When a user participates in a tree planting activity

[1055] 1. A user accesses the application and receives information about participating in a tree planting weekend.

[1056] 2. The user goes to a designated location and plants 10 trees.

[1057] 3. After the activity, report the number of trees planted in the application and enter "I planted 10 trees today."

[1058] 4. The device sends the user's input to the server, which evaluates it using the generating AI and assigns 10 points to the user's account.

[1059] 5. Users will see the reward points added in the app and receive a notification.

[1060] Prompt Sentence Examples

[1061] You are a user. This weekend, a tree planting event will be held in your town. Please participate and contribute to reducing CO2 emissions. Please participate in the tree planting event and report it on this system after the event.

[1062] In this way, the present invention provides a system that allows users to always obtain the latest information on CO2 reduction activities, take concrete actions based on that information, and receive rewards for their results, thereby encouraging active participation by users and contributing to global warming countermeasures.

[1063] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1064] Step 1:

[1065] A user accesses a system application or website and logs in. After the user enters their username and password and completes authentication, the device begins acquiring location information. Input: User authentication information. Output: Authentication success flag. Specifically, the user enters authentication information on the app's login screen, the device sends it to the server, and authentication is successful.

[1066] Step 2:

[1067] With the user's consent, the device collects current location information (longitude and latitude). Input: User's consent. Output: Location data (longitude, latitude). Specifically, the app displays a pop-up message requesting permission to collect location information, and once the user agrees, the device uses its GPS function to obtain location information.

[1068] Step 3:

[1069] The location information collected by the device is sent to the server. Input: Location information data. Output: Server-side location information storage completion flag. Specifically, the device encrypts the location information and sends it to the server, which then stores it in a database.

[1070] Step 4:

[1071] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, websites of environmental protection organizations, social media, etc.). Input: List of data sources. Output: Collected data. Specifically, the server runs a pre-configured crawling program to collect information from the data sources.

[1072] Step 5:

[1073] The generation AI analyzes the collected information and extracts activity information related to the user's location information. Input: collected data, location data. Output: related activity information. Specifically, the generation AI uses natural language processing technology to analyze the collected data, extract important information such as the activity name, location, date and time, and compare it with the user's location information.

[1074] Step 6:

[1075] The server converts the extracted information into a format that is easy for users to understand. Input: Related activity information. Output: Converted information. Specifically, the server formats the information and summarizes it into user-friendly text.

[1076] Step 7:

[1077] The server sends the converted information to the user's device. Input: Converted information. Output: Flag indicating completion of sending information to the device. Specifically, the server sends the converted information to the user's device in JSON format or similar.

[1078] Step 8:

[1079] The terminal displays the received information to the user so that the user can view it. Input: Converted information. Output: Display of information that can be viewed by the user. Specifically, the application analyzes the received data and displays it in a pop-up notification or on the interface.

[1080] Step 9:

[1081] Based on the information presented, the user carries out specific CO2 reduction activities (e.g., tree planting or participating in environmental protection events). Input: Presented information. Output: Details of the activity to be carried out. Specifically, the user follows the notification and carries out the activity at the specified location and time.

[1082] Step 10:

[1083] After the activity, the user inputs the specific amount and content of the activity they performed (e.g., number of trees planted) into the system. Input: Content of the activity performed. Output: Activity report data. Specifically, the user inputs the content of the activity into a form within the application.

[1084] Step 11:

[1085] The terminal sends the entered activity information to the server. Input: Activity report data. Output: Activity information storage completion flag on the server side. Specifically, the terminal sends the activity report data to the server, and the server stores it in a database.

[1086] Step 12:

[1087] The server uses the generation AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction. Input: Activity report data. Output: Evaluation results. Specifically, the generation AI analyzes the amount and content of the activity and evaluates the effect of CO2 reduction.

[1088] Step 13:

[1089] The server calculates reward points based on the evaluation results and grants them to the user's account. Input: Evaluation results. Output: Reward points. Specifically, the server calculates reward points based on the evaluation results and grants them to the user's account.

[1090] Step 14:

[1091] A notification is sent within the app so that the user can check their reward points. Input: Reward points. Output: Points awarded notification. Specifically, the application notifies the user that points have been awarded and presents a screen where the user can check their points.

[1092] (Application example 1)

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

[1094] CO2 reduction activities aimed at environmental protection are most effective when many individuals participate in them. However, at present, there are limited ways for general users to understand what CO2 reduction activities they can participate in or to evaluate the extent to which their activities have contributed to CO2 reduction. Furthermore, there is no adequate reward system in place, which means that general users have little motivation to participate. The purpose of this project is to solve this problem, encourage active participation by users, and promote effective CO2 reduction activities.

[1095] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1096] In this invention, the server includes: means for acquiring user location information; means for using a generation AI to collect information on CO2 reduction activities around the world; means for analyzing the collected information and extracting activity information related to the user's location information; means for converting the extracted information into a format that is easy for the user to understand; means for transmitting the converted information to the user's terminal; means for the terminal to record the user's activity amount and transmit the recorded information to the server; means for evaluating the input activity amount, calculating a reward based on the amount, and granting the reward to the user's account; means for providing instructions to the user including information on eco-activities; and means for making reward points available for use in the store. This allows users to always receive the latest information on CO2 reduction activities and earn rewards based on their activities, thereby enabling them to more actively participate in environmental protection activities.

[1097] The "means for acquiring user location information" refers to a device or software function that collects data necessary to identify the user's current location.

[1098] "Means for collecting information on CO2 reduction activities around the world using generative AI" refers to a device or software function that uses artificial intelligence technology to widely collect the latest information on CO2 reduction activities in various locations.

[1099] "Means for analyzing collected information and extracting activity information related to the user's location information" refers to the function of a device or software that analyzes collected data and identifies and extracts information about CO2 reduction activities related to the user's current location.

[1100] The "means for converting extracted information into a user-friendly format" refers to the function of a device or software that processes the analyzed and extracted information into a format that is easy for the user to understand.

[1101] The "means for transmitting the converted information to the user's terminal" refers to the function of a device or software for transmitting the processed information to the device used by the user.

[1102] "Means for the terminal to record the amount of user activity and send it to the server" refers to the function of a device or software that records the user's behavior on the terminal and sends the data to a central server.

[1103] "Means for evaluating the amount of activity entered, calculating rewards based thereon, and granting rewards to the user account" refers to the function of a device or software that evaluates the amount and quality of activity performed by a user and calculates and grants rewards accordingly.

[1104] The "means for providing a user with instructions including information on eco-friendly activities" refers to a function of a device or software that conveys behavioral instructions and information related to environmental protection to a user.

[1105] "Means for enabling reward points to be used in-store" refers to a device or software function that allows a user to use the reward points they have earned for discounts, payments, etc. at physical stores.

[1106] This invention provides a system that allows users to participate in CO2 reduction activities, receive rewards based on the evaluation of their contributions. The system acquires the user's location information, uses AI to collect and analyze the latest CO2 reduction activity information, and presents it to the user in an easy-to-understand manner. It also records the user's activity level and awards rewards based on the user's contribution.

[1107] Main components and their functions

[1108] 1. How to obtain user location information

[1109] The user's device (e.g., a smartphone) acquires the user's current location using GPS, etc. This location information is used in the next step.

[1110] 2. A means of using generative AI to collect information on CO2 reduction activities around the world

[1111] The server uses generative AI to collect the latest information on CO2 reduction activities from a variety of data sources, including news sites, environmental organization websites, and social media.

[1112] 3. A means of analyzing the collected information and extracting activity information related to the user's location information.

[1113] The server uses the generated AI to analyze the acquired user location information and extract information on CO2 reduction activities in which the user can participate.

[1114] 4. A means of converting the extracted information into a user-friendly format

[1115] The server converts the extracted information into a format that is easy for the user to understand and displays it, for example, through notification messages or an in-app interface.

[1116] 5. Means for transmitting the converted information to the user's terminal

[1117] The converted information is sent from the server to the user's terminal and notified in real time.

[1118] 6. How the device records the user's activity and sends it to the server

[1119] The user's device records the amount of CO2 reduction activity they have actually performed by scanning a QR code or manually entering it, and this information is sent to the server.

[1120] 7. A means for evaluating the amount of activity entered, calculating rewards based on the amount, and crediting the rewards to the user account.

[1121] The server uses the AI ​​generator to evaluate the amount of activity entered by the user and calculates reward points based on the contribution. The calculated reward is credited to the user's account and notified within the app.

[1122] 8. Means for providing users with instructions including eco-friendly activity information

[1123] The user's device provides the latest information on collected eco-activities and specific instructions for action.

[1124] 9. Means for reward points to be redeemed in-store

[1125] Users can use the reward points they earn for discounts and special offers at physical stores, which can be redeemed by scanning QR codes.

[1126] Specific examples

[1127] Consider a case where a user participates in a tree planting activity on the weekend. When the user launches the "Eco Store Guide" app, the app uses its GPS function to identify the user's current location and collects information about tree planting activities taking place in the area. For example, a notification might be displayed saying, "A tree planting activity is being held in a park near you. Join in and contribute to reducing CO2 emissions!" When the user participates in the activity and enters the number of trees planted, the information is sent to the server and evaluated by the generation AI. Based on the evaluation results, reward points are awarded to the user's account and the user is notified within the app. The awarded points can be used for discounts at affiliated stores, etc.

[1128] Prompt Sentence Examples

[1129] An example of a prompt sent to the generative AI model is, "Please provide us with the latest information on eco-activities. Your current location is latitude 35.6895, longitude 139.6917. We are particularly looking for tree planting activities and eco-bag usage initiatives."

[1130] In this way, users can easily obtain the latest eco-activity information, participate in CO2 reduction activities, and receive rewards according to the degree of their contribution.

[1131] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1132] Step 1:

[1133] The user's device uses the GPS function to identify the user's current location and obtains the location information.

[1134] Input: User consent, device GPS data

[1135] Data processing: Obtain the longitude and latitude of the user's current location and generate location data

[1136] Output: Current location data (longitude, latitude)

[1137] Step 2:

[1138] The server uses a generative AI model to collect information on CO2 reduction activities around the world.

[1139] Input: A list of pre-configured data sources on the server (news sites, environmental organizations' websites, social media, etc.), a prompt

[1140] Data processing: The generative AI model gathers information based on the prompt, analyzes and filters relevant data

[1141] Output: A list of detailed information about CO2 reduction activities

[1142] Step 3:

[1143] The server analyzes and extracts CO2 reduction activity information related to the user's location information.

[1144] Input: User location data, list of collected CO2 reduction activity information

[1145] Data processing: Filter and extract relevant CO2 reduction activity information based on user location information

[1146] Output: CO2 reduction activity information related to user location information

[1147] Step 4:

[1148] The server converts the extracted information into a format that is easy for the user to understand.

[1149] Input: Extracted CO2 reduction activity information

[1150] Data processing: Generate notification messages and interface designs to convey information to users in an easy-to-understand manner.

[1151] Output: Messages and display content to notify the user

[1152] Step 5:

[1153] The server transmits the converted information to the user's terminal.

[1154] Input: Message or display content

[1155] Data processing: Send information using a protocol that transfers messages to the device

[1156] Output: Notifications and messages displayed on the user's device

[1157] Step 6:

[1158] The device records the user's activity level and transmits the data to a server.

[1159] Input: User activity data (e.g. QR code scan, manual input)

[1160] Data processing: Record the acquired activity data, convert it into a data format, and send it to the server.

[1161] Output: Activity data sent to the server

[1162] Step 7:

[1163] The server evaluates the amount of activity entered, calculates a reward based on the amount, and grants the reward to the user account.

[1164] Input: User activity data, reward calculation algorithm

[1165] Data processing: Based on activity data, an AI model evaluates contribution and calculates reward points

[1166] Output: Calculated reward points, points credited to user account

[1167] Step 8:

[1168] The server provides the user with instructions including information on eco-activities.

[1169] Input: Latest eco-activity information

[1170] Data processing: Send information to the user terminal in the specified format

[1171] Output: Eco-activity information and instructions notified to the user

[1172] Step 9:

[1173] The user's terminal allows the reward points to be used in the store.

[1174] Input: Reward points granted to user account, available at stores

[1175] Data processing: Manage the point usage process and generate QR codes for use in stores

[1176] Output: A valid point redemption method at the store (QR code, etc.)

[1177] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1178] This invention is a system that provides the latest information on CO2 reduction activities based on the user's location information, evaluates the user's contribution to CO2 reduction through their actions with rewards, and further increases the user's motivation by recognizing the user's emotional state using an emotion engine and adjusting the way information is presented.By combining generative AI and an emotion engine, this system always provides the latest information and helps users take action easily.

[1179] Program processing

[1180] 1. Obtaining user location information

[1181] A user accesses an application or website in the system and logs in.

[1182] With the user's consent, the device collects current location information (longitude and latitude).

[1183] The device sends the location information it collects to the server.

[1184] 2. Collection and processing of the latest information

[1185] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[1186] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[1187] The emotion engine analyzes the user's voice data and facial expression data to recognize their emotional state, and adjusts the way the collected information is presented to suit the user's emotional state.

[1188] For example, if the user is tired, provide a brief, encouraging message, and if they are proactive, provide a detailed, action-oriented message.

[1189] 3. Providing information and encouraging action

[1190] The server sends the converted information to the user's terminal.

[1191] The terminal displays the received information to the user so that the user can view it.

[1192] For example, a notification might appear saying, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[1193] The emotion engine monitors the user's emotional state and provides information at the appropriate time.

[1194] 4. Recording behavior and calculating rewards

[1195] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[1196] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the system.

[1197] The terminal transmits the input activity information to the server.

[1198] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[1199] The server calculates reward points based on the evaluation results and grants them to the user's account.

[1200] The terminal notifies the user of the reward points and allows the user to check the points.

[1201] Specific examples

[1202] Example 1: When a user participates in a tree planting activity

[1203] 1. User Activities

[1204] The user accesses the application and receives information about participating in a tree planting activity over the weekend, along with an encouraging message from the emotion engine.

[1205] Go to the designated location and plant 10 trees.

[1206] After the activity, participants enter the number of trees planted in the application and report, "I planted 10 trees today."

[1207] 2. System evaluation and rewards

[1208] The terminal sends the user's input to the server.

[1209] The server uses generated AI to evaluate the amount of CO2 reduction equivalent to planting 10 trees and awards, for example, 10 points.

[1210] The server notifies the user of the points and sends a message praising the user's efforts through the emotion engine.

[1211] Reward points will be added to your user account and you will receive a notification.

[1212] This system allows users to always receive the latest information on CO2 reduction activities, take specific actions based on that information, and receive rewards for their results. Furthermore, by using an emotion engine to provide information that corresponds to the user's emotional state, it is possible to motivate users and encourage more proactive CO2 reduction actions.

[1213] The processing flow will be explained below.

[1214] Step 1:

[1215] A user logs into an application or website on the system.

[1216] Step 2:

[1217] With the user's consent, the device collects current location information (longitude and latitude).

[1218] Step 3:

[1219] The device sends the location information it collects to the server.

[1220] Step 4:

[1221] The server uses generated AI to collect information on CO2 reduction activities around the world from multiple data sources (news sites, environmental organization websites, social media, etc.).

[1222] Step 5:

[1223] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[1224] Step 6:

[1225] The emotion engine analyzes the user's voice data and facial expression data to recognize their emotional state.

[1226] For example, the user provides facial expressions and voice through the application's camera and microphone, and the emotion engine evaluates the user's current emotional state.

[1227] Step 7:

[1228] The server converts the collected activity information into a user-friendly format based on the user's emotional state.

[1229] For example, if the user is tired, it generates a brief, encouraging message (e.g., "Why not relax and take part in a simple tree-planting event nearby?"), while if the user is proactive, it generates a detailed, actionable message (e.g., "There's a large-scale tree-planting event near your home. Plant lots of trees and contribute to reducing CO2 emissions!").

[1230] Step 8:

[1231] The server sends the converted information to the user's terminal.

[1232] Step 9:

[1233] The terminal displays the received information to the user so that the user can view it.

[1234] Step 10:

[1235] Based on the displayed information, the user participates in CO2 reduction activities (e.g., tree planting activities or environmental protection events).

[1236] Step 11:

[1237] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the application.

[1238] Step 12:

[1239] The terminal transmits the input activity information to the server.

[1240] Step 13:

[1241] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[1242] Step 14:

[1243] The server calculates reward points based on the evaluation results and grants them to the user's account.

[1244] Step 15:

[1245] The terminal notifies the user of the reward points and allows the user to check the points.

[1246] The emotion engine also reassess the user's emotional state and sends a message praising their efforts (e.g., "Amazing! Your contribution will save the planet!").

[1247] Through these steps, the system provides users with customized information on CO2 reduction activities based on their location information and emotional state, and encourages them to contribute to the environment by evaluating and rewarding their actions.

[1248] Example 2

[1249] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1250] Conventional CO2 reduction activity information provision systems have insufficient collection and analysis of the latest information, making it difficult to provide appropriate information based on the user's location information and emotional state. In addition, there are issues with the cumbersome calculation of rewards based on the user's specific activity level, making it difficult to maintain user motivation.

[1251] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1252] In this invention, the server includes a means for acquiring user location information, a means for using a generation AI to collect information on CO2 reduction activities around the world, and a means for analyzing the collected information and extracting activity information related to the user's location information, thereby making it possible to provide the latest CO2 reduction activity information based on the user's location information.

[1253] The server also includes means for analyzing the user's emotional state, means for adjusting the presentation method of the collected information according to the user's emotional state, means for converting the extracted information into a format that is easy for the user to understand, means for transmitting the converted information to the user's terminal, means for inputting and transmitting the user's activity level, means for evaluating the input activity level, calculating a reward based on it, and adding the reward to the user's account, and means for notifying the user of the reward points. This realizes an effective information provision and reward system that is tailored to the user's emotional state, increases the user's motivation, and promotes more proactive CO2 reduction activities.

[1254] "Means for obtaining user location information" refers to a function that collects longitude and latitude data from the device with the user's consent and transmits it to a server.

[1255] "Means of using generative AI to collect information on CO2 reduction activities around the world" is a function that uses generative AI to obtain information on CO2 reduction activities from a variety of data sources, such as news sites, websites of environmental protection organizations, and social media.

[1256] "Means for analyzing collected information and extracting activity information related to the user's location information" refers to a function that analyzes the data collected by the generation AI and identifies CO2 reduction activities and event information that are closely related to the user's current location.

[1257] The "means for analyzing the user's emotional state" is a function that uses technology for analyzing voice data and facial expression data to recognize the user's emotional state in real time.

[1258] "Means for adjusting the presentation of collected information to match the user's emotional state" refers to a function that dynamically changes the format and content of information provided to the user based on the recognized emotional state.

[1259] The "means of converting extracted information into a user-friendly format" is a function that converts technical terms and complex data into a user-friendly format.

[1260] The "means for transmitting the converted information to the user's device" is a function for transmitting the converted information from the server to the user's device as a push notification or an in-application message.

[1261] "Means for inputting and transmitting user activity data" is a function that provides an interface for users to input details of their activities (e.g., number of trees planted) and transmit that information to the server.

[1262] "Means of evaluating the amount of activity entered, calculating rewards based on that, and granting rewards to the user's account" refers to a function in which the generation AI analyzes the entered activity data, calculates the contribution to CO2 reduction, calculates reward points, and reflects those points in the user's account.

[1263] The "means for notifying the user of the reward points" is a function that notifies the user that the calculated reward points have been added to the user's account.

[1264] The present invention is a system that provides users with up-to-date information on CO2 reduction activities based on their location information, helping them take action and contribute to CO2 reduction. Furthermore, it uses an emotion engine to recognize the user's emotional state and adjusts the way information is presented to increase the user's motivation. An embodiment of this system is described below.

[1265] First, a user accesses the system's application or website and logs in. With the user's consent, the device collects and transmits current location information (longitude and latitude) to the server.

[1266] The server uses a generative AI (e.g., OpenAI's GPT-4) to collect information on CO2 reduction activities from various data sources, such as news sites, environmental protection organization websites, and social media. This information collection is performed on a regular schedule. The generative AI analyzes the collected data and extracts activity information related to the user's location.

[1267] The server then uses an emotion engine to analyze the user's voice and facial expression data to recognize their emotional state in real time. The voice recognition tool is Google Cloud Speech-to-Text API, and the facial expression recognition tool is Face++. Based on the acquired emotional state, the server adjusts how the collected information is presented. For example, if the user is determined to be tired, it will provide a concise, encouraging message, while if the user is determined to be proactive, it will provide a detailed, action-oriented message.

[1268] As a concrete example, the following message is provided:

[1269] "This weekend, a tree planting event will be held in your town. Join in and help reduce CO2 emissions!"

[1270] Furthermore, if the user participates in CO2 reduction activities based on the information provided, the amount of activity (e.g., number of trees planted) is reported within the application. The device sends this information to the server, which uses a generation AI to evaluate the amount of activity entered. The server calculates the contribution to CO2 reduction and calculates reward points, which are then added to the user's account. The user is then notified that the reward points have been added.

[1271] Through this series of processes, users can always receive the latest information on CO2 reduction activities, take specific actions based on that information, and receive rewards for their results.In addition, by using the emotion engine to provide information according to the user's emotional state, users' motivation is enhanced, and more proactive CO2 reduction actions can be expected.

[1272] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1273] Step 1:

[1274] A user accesses an application or website in the system and logs in.

[1275] Specifically, the user opens the application, enters their ID and password, and presses the "Login" button.

[1276] Input: User ID and password

[1277] Output: User credentials

[1278] Step 2:

[1279] With the user's consent, the device collects location information (longitude and latitude) and sends it to the server.

[1280] Specifically, the app displays a pop-up asking "Do you want to allow location access?" and the user selects "Allow."

[1281] Input: User consent

[1282] Output: User's location (longitude and latitude)

[1283] Step 3:

[1284] The server uses generated AI to collect information on CO2 reduction activities from a variety of data sources, including news sites, websites of environmental protection organizations, and social media.

[1285] Specifically, the generating AI acquires information based on a regular schedule.

[1286] Input: Raw data such as news articles, blog posts, and social media posts

[1287] Output: Organized information on CO2 reduction activities

[1288] Step 4:

[1289] The server analyzes the collected information using generated AI and extracts activity information related to the user's location.

[1290] Specifically, the generative AI categorizes the collected data and filters relevant information based on location information.

[1291] Input: Organized CO2 reduction activity information, user location information

[1292] Output: Activity information related to the user's location

[1293] Step 5:

[1294] The server uses an emotion engine to analyze the user's voice data and facial expression data and recognize their emotional state.

[1295] Specifically, the user provides data via the smartphone's camera and microphone, and the emotion engine analyzes it in real time.

[1296] Input: User's voice data, facial expression data

[1297] Output: User's emotional state data

[1298] Step 6:

[1299] Based on the results of the emotion engine, the server adjusts the presentation of the collected information to suit the user's emotional state.

[1300] Specifically, the generation AI generates an appropriate message depending on the emotional state.

[1301] Input: User's emotional state data, related activity information

[1302] Output: Messages tailored to your emotional state

[1303] Step 7:

[1304] The server transmits the converted information to the user's terminal.

[1305] Specifically, the server generates a notification message and sends it to the terminal as a push notification.

[1306] Input: Messages tailored to your emotional state

[1307] Output: Notification to the user's device

[1308] Step 8:

[1309] CO2 reduction activities will be carried out based on the information received by the user.

[1310] The user enters the amount and content of their activity into the app, and the device sends the data to the server.

[1311] Specifically, a user participates in an event, and after participating in the event, they enter "I planted 10 trees today" in the app and press the "Send" button.

[1312] Input: User activity details (number of trees planted, etc.)

[1313] Output: Activity details data

[1314] Step 9:

[1315] The server uses generated AI to evaluate the amount of activity entered and calculates the contribution to CO2 reduction.

[1316] Specifically, the generating AI analyzes the user's input data and evaluates it as, for example, "Planting 10 trees = 10 points."

[1317] Input: Activity details data

[1318] Output: Contribution data

[1319] Step 10:

[1320] The server calculates reward points based on the contribution and credits them to the user's account.

[1321] Specifically, after the points are calculated, the server automatically adds the points to the user's account.

[1322] Input: Contribution data

[1323] Output: Reward points

[1324] Step 11:

[1325] The terminal notifies the user of the reward points and allows the user to check the points.

[1326] Specifically, the app will display a notification to the user saying "10 points added!"

[1327] Input: Reward Points

[1328] Output: Point notification

[1329] (Application example 2)

[1330] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1331] Conventional CO2 reduction activity support systems are limited to providing users with location information and the latest information, and lack advice on which route users should take from a security perspective. Furthermore, because they present information without taking into account the user's emotional state, they are unable to provide appropriate support when motivation is low. These issues make it difficult to encourage users to take proactive action, and CO2 reduction activities are not fully effective. Furthermore, there is a need for information provision on CO2 reduction activities that is linked to ensuring safety.

[1332] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1333] In this invention, the server includes means for sorting collected information and security precautions, means for analyzing the user's emotional state using an emotion engine and adjusting the way information is presented, and means for proposing a safe route taking into account the user's location information. This makes it possible to provide information at an appropriate time according to the user's emotional state and to give advice on selecting a safe route, allowing the user to actively and safely participate in CO2 reduction activities.

[1334] "Means for obtaining location information" refers to technical means for identifying the user's current geographical location.

[1335] "Generative AI" is a technology that uses artificial intelligence to generate new information from data.

[1336] An "information collection means" is a method or device for gathering data relevant to a particular purpose.

[1337] "Means of analyzing information" refers to techniques for analyzing collected data and extracting meaningful information.

[1338] "Means for adjusting the method of presenting information" refers to a technique for changing the format and timing of information presented depending on the user's emotional state.

[1339] The "means for inputting and transmitting the amount of activity" refers to a means for recording the amount and content of the user's actions in the system and transmitting them to the server.

[1340] The "means for evaluating the amount of activity and calculating the reward" is a technology for measuring the actions performed by the user and calculating the reward for the user based on the results.

[1341] A "reward granting means" is a technology for recording and adding rewards to a user account.

[1342] "Means for selecting security precautions" refers to a technology that extracts and emphasizes important safety information from the information provided to users.

[1343] An "emotion engine" is a technology that analyzes a user's emotional state from facial expressions, voice, etc.

[1344] The "means for suggesting a safe route" is a technology that takes into account the user's location information and provides the safest route.

[1345] The system for realizing this invention is configured using the following hardware and software, including, as its main elements, a means for acquiring user location information, a means for sorting collected information and security precautions, a means for analyzing the user's emotional state using an emotion engine and adjusting the way information is presented, a means for proposing a safe route taking into account the user's location information, and a means for collecting information using a generative AI.

[1346] 1. Obtaining user location information

[1347] The server obtains location information using the user's smartphone or GPS device. When the user logs in to the application and provides consent for location information collection, the current location information (longitude and latitude) is sent to the server.

[1348] Hardware: GPS devices, smartphones

[1349] Software: Android / iOS SDK, location information acquisition API

[1350] 2. Information collection and analysis

[1351] The server uses generative AI (such as OpenAI GPT-3) to collect the latest information on global CO2 reduction activities and security from multiple sources. The AI ​​analyzes the collected information and extracts activity and security information related to the user's location. This information is formatted to match the user's emotional state.

[1352] Hardware: Servers, database servers

[1353] Software: NLP model, multi-source data collection API

[1354] 3. Adjustment by Emotion Engine

[1355] The emotion engine analyzes the user's voice and facial expression data to recognize their emotional state, and then adjusts how the collected information is presented. For example, if the user is tired, it will provide a concise, encouraging message, while if they are proactive, it will provide a detailed, actionable message.

[1356] Hardware: Audio input device (microphone), camera

[1357] Software: Sentiment Analysis Engine

[1358] 4. Safe Route Suggestion

[1359] The server will suggest the safest route based on the user's location information, allowing users to minimize risks when participating in CO2 reduction activities. For example, routes that avoid dangerous areas at night will be automatically suggested.

[1360] Hardware: GPS devices, smartphones

[1361] Software: Map API, route calculation algorithm

[1362] 5. Recording behavior and calculating rewards

[1363] The server records the content and amount of the user's actions and calculates rewards based on that information. The user inputs their actions through the application, and the server evaluates them using a generative AI. Reward points are calculated based on the evaluation results and awarded to the user's account.

[1364] Hardware: Smartphones, servers

[1365] Software: Database (MySQL / PostgreSQL), Reward Management System

[1366] Prompt Sentence Examples

[1367] Here are some examples of prompts to input to the generative AI model:

[1368] Collect the latest information on CO2 reduction activities and security around the world and provide appropriate activity information based on the user's location. Adjust the way information is presented depending on the user's emotional state. For example, if the user is tired, provide an encouraging message, and if they are active, provide a detailed call-to-action message.

[1369] This provides users with CO2 reduction activity information optimized for their location and emotional state, while also ensuring security, allowing users to proactively and safely engage in activities.

[1370] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1371] Step 1:

[1372] Obtaining user location information

[1373] The user logs in to the application and gives consent to obtain location information.

[1374] Input: User consent, public location information

[1375] Data processing: Obtain location information (longitude and latitude) from the GPS chip

[1376] Output: Sends the user's current location to the server

[1377] How it works: An app on your smartphone collects location information from the GPS chip and sends it to a server.

[1378] Step 2:

[1379] Gathering the latest information

[1380] The server uses generated AI to collect information on CO2 reduction activities and security around the world.

[1381] Input: Data sources such as news sites, environmental organization websites, and social media.

[1382] Data processing: Generative AI analyzes information and extracts relevant information

[1383] Output: The latest information collected and analyzed

[1384] How it works: The server retrieves information from multiple data sources through an API, and the generating AI analyzes the data.

[1385] Step 3:

[1386] Emotional state analysis

[1387] The device uses an emotion engine to analyze the user's voice data and facial expression data and recognize their emotional state.

[1388] Input: User's voice data, facial expression data

[1389] Data processing: Identifying emotional states using speech recognition and facial expression analysis algorithms

[1390] Output: The user's current emotional state

[1391] How it works: Your smartphone or connected device captures your voice and facial expression data, which is then analyzed by the emotion engine.

[1392] Step 4:

[1393] Adjusting how information is presented

[1394] The server adjusts how information is presented based on the output of the emotion engine.

[1395] Input: User's emotional state, collected information

[1396] Data processing: determining the appropriate information form and timing

[1397] Output: Tailored information presentation

[1398] How it works: The server optimizes the timing and content of information presentation based on the user's emotional state and location information.

[1399] Step 5:

[1400] Safe route suggestions

[1401] The server takes into account the user's location and suggests the safest route.

[1402] Input: current user location, map information, security notices

[1403] Data calculation: Calculates safe routes and avoids dangerous areas

[1404] Output: Recommended safe route

[1405] How it works: The server uses map APIs and security information to calculate a safe route and send it to the user's smartphone.

[1406] Step 6:

[1407] Recording behavior and calculating rewards

[1408] The user inputs the amount and content of their actions into the application, and the server evaluates them using a generative AI to calculate reward points.

[1409] Input: Activity amount and details of the activity entered by the user

[1410] Data calculation: Evaluating actions and calculating reward points

[1411] Output: Reward points and notification

[1412] How it works: The server records the user's input, and the generating AI evaluates the activity level and calculates reward points. The reward points are added to the user's account and notified.

[1413] Prompt Sentence Examples

[1414] Here are some examples of prompts to input to the generative AI model:

[1415] Collect the latest information on CO2 reduction activities and security around the world and provide appropriate activity information based on the user's location. Adjust the way information is presented depending on the user's emotional state. For example, if the user is tired, provide an encouraging message, and if they are active, provide a detailed call-to-action message.

[1416] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1417] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1418] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1419] [Fourth embodiment]

[1420] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1421] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1422] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1423] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1424] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1425] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1426] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1427] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1428] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1429] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1430] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1431] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1432] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1433] This invention is a system that provides users with the latest information on CO2 reduction activities based on their location information and rewards them for their contribution to CO2 reduction through their actions. This system uses generation AI to always provide the latest information and help users take action easily.

[1434] Program processing

[1435] 1. Obtaining user location information

[1436] A user accesses an application or website in the system and logs in.

[1437] With the user's consent, the device collects current location information (longitude and latitude).

[1438] The device sends the location information it collects to the server.

[1439] 2. Collection and processing of the latest information

[1440] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[1441] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[1442] The server converts the extracted information into a format that is easy for the user to understand.

[1443] 3. Providing information and encouraging action

[1444] The server sends the converted information to the user's terminal.

[1445] The terminal displays the received information to the user so that the user can view it.

[1446] For example, a notification might appear saying, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[1447] 4. Recording behavior and calculating rewards

[1448] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[1449] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the system.

[1450] The terminal transmits the input activity information to the server.

[1451] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[1452] The server calculates reward points based on the evaluation results and grants them to the user's account.

[1453] An in-app notification will be sent to allow users to check their reward points.

[1454] Specific examples

[1455] Example 1: When a user participates in a tree planting activity

[1456] 1. User Activities

[1457] A user accesses the application and receives information about participating in a tree planting weekend.

[1458] Go to the designated location and plant 10 trees.

[1459] After the activity, participants enter the number of trees planted in the application and report, "I planted 10 trees today."

[1460] 2. System evaluation and rewards

[1461] The terminal sends the user's input to the server.

[1462] The server uses generated AI to evaluate the amount of CO2 reduction equivalent to planting 10 trees and awards, for example, 10 points.

[1463] Reward points will be added to your user account and you will receive a notification.

[1464] This system allows users to always receive the latest information on CO2 reduction activities, take concrete action based on that information, and receive rewards for their results. This encourages active participation by users and contributes to measures against global warming.

[1465] The processing flow will be explained below.

[1466] Step 1:

[1467] A user logs into an application or website on the system.

[1468] Step 2:

[1469] With the user's consent, the device collects current location information (longitude and latitude).

[1470] Step 3:

[1471] The device sends the location information it collects to the server.

[1472] Step 4:

[1473] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[1474] Step 5:

[1475] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[1476] Step 6:

[1477] The server converts the extracted information into a format that is easy for the user to understand.

[1478] For example, you could convert it into a notification that reads, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[1479] Step 7:

[1480] The server sends the converted information to the user's terminal.

[1481] Step 8:

[1482] The terminal displays the received information to the user so that the user can view it.

[1483] Step 9:

[1484] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[1485] Step 10:

[1486] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the application.

[1487] Step 11:

[1488] The terminal transmits the input activity information to the server.

[1489] Step 12:

[1490] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[1491] Step 13:

[1492] The server calculates reward points based on the evaluation results and grants them to the user's account.

[1493] Step 14:

[1494] The terminal notifies the user of the reward points and allows the user to check the points.

[1495] Example 1

[1496] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1497] Conventional information provision systems for CO2 reduction activities lacked specific action plans and evaluation functions that allowed users to easily participate, making it difficult to visualize an individual's environmental contribution and provide appropriate rewards. Furthermore, they lacked a mechanism to encourage user action by providing the latest information in a timely manner. As a result, many users missed the opportunity to actively participate in CO2 reduction activities.

[1498] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1499] In this invention, the server includes means for acquiring user location information, means for using a generation AI to collect information on CO2 reduction activities around the world, means for analyzing the collected information and extracting activity information related to the user's location information, means for converting the extracted information into a format that is easy for the user to understand, means for transmitting the converted information to the user's device, means for inputting and transmitting the user's activity amount, means for evaluating the input activity amount, calculating a reward based on the amount, and granting the reward to the user's account, means for displaying a reward grant notification on the user's device, and means for analyzing the collected information using natural language processing technology.This allows users to easily obtain the latest CO2 reduction activity information, create specific action plans, and receive appropriate rewards for their actions.

[1500] "User location information" refers to the longitude and latitude data of the user's current location.

[1501] "Generative AI" is a system that uses machine learning and artificial intelligence techniques to generate the models and data needed for specific tasks.

[1502] "CO2 reduction activities" are specific actions or projects aimed at reducing carbon dioxide emissions.

[1503] "Data sources" refers to the websites, news sites, environmental organization websites, social media, etc. from which information is collected.

[1504] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[1505] A "user terminal" is a device used by a user, such as a smartphone or PC.

[1506] "Reward points" are points that users can earn as a result of participating in CO2 reduction activities and are returned to them.

[1507] "Activity information" is specific information such as the date, time, location, and content of CO2 reduction activities in which users can participate.

[1508] "Amount of activity" refers to the specific amount and content of CO2 reduction activities that a user has actually undertaken (e.g., number of trees planted).

[1509] "Evaluation results" are results that show the effectiveness of the CO2 reduction activities carried out by the user in numerical values ​​or points.

[1510] This invention is a system that provides users with the latest information on CO2 reduction activities based on their location information and rewards them for their contribution to CO2 reduction through their actions. This system uses a generative AI model to constantly provide the latest information and help users easily take action.

[1511] Overview of program processing

[1512] This system consists of three main components: a server, a terminal, and a user. The server processes data using a generative AI model and a database. A terminal is a device such as a smartphone or PC that is used by a user. Users access the system through an application or website to provide location information and enter their activities.

[1513] Hardware and Software

[1514] The server uses cloud-based infrastructure and is capable of processing large amounts of data. Specific examples include cloud services such as Amazon Web Services (AWS) and Google Cloud Platform (GCP). The generative AI model uses natural language processing technology. Examples include OpenAI's GPT-3 and BERT. Devices that can be used include smartphones running iOS or Android, and computers running Windows or macOS.

[1515] Data processing and calculation

[1516] The server first collects information on CO2 reduction activities from various data sources, including news sites, environmental organization websites, and social media. The collected data is analyzed by a generative AI model to extract activity information related to the user's location. The extracted information is then converted into a user-friendly format using natural language processing technology. Finally, the converted information is sent to the user's device and displayed.

[1517] When a user performs a CO2 reduction activity, they input the activity details and amount into the application. The device sends this input information to the server, which then evaluates the activity using generated AI. Based on the evaluation, reward points are awarded to the user's account. Points can be viewed on the user's device.

[1518] Specific examples

[1519] Example 1: When a user participates in a tree planting activity

[1520] 1. A user accesses the application and receives information about participating in a tree planting weekend.

[1521] 2. The user goes to a designated location and plants 10 trees.

[1522] 3. After the activity, report the number of trees planted in the application and enter "I planted 10 trees today."

[1523] 4. The device sends the user's input to the server, which evaluates it using the generating AI and assigns 10 points to the user's account.

[1524] 5. Users will see the reward points added in the app and receive a notification.

[1525] Prompt Sentence Examples

[1526] You are a user. This weekend, a tree planting event will be held in your town. Please participate and contribute to reducing CO2 emissions. Please participate in the tree planting event and report it on this system after the event.

[1527] In this way, the present invention provides a system that allows users to always obtain the latest information on CO2 reduction activities, take concrete actions based on that information, and receive rewards for their results, thereby encouraging active participation by users and contributing to global warming countermeasures.

[1528] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1529] Step 1:

[1530] A user accesses a system application or website and logs in. After the user enters their username and password and completes authentication, the device begins acquiring location information. Input: User authentication information. Output: Authentication success flag. Specifically, the user enters authentication information on the app's login screen, the device sends it to the server, and authentication is successful.

[1531] Step 2:

[1532] With the user's consent, the device collects current location information (longitude and latitude). Input: User's consent. Output: Location data (longitude, latitude). Specifically, the app displays a pop-up message requesting permission to collect location information, and once the user agrees, the device uses its GPS function to obtain location information.

[1533] Step 3:

[1534] The location information collected by the device is sent to the server. Input: Location information data. Output: Server-side location information storage completion flag. Specifically, the device encrypts the location information and sends it to the server, which then stores it in a database.

[1535] Step 4:

[1536] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, websites of environmental protection organizations, social media, etc.). Input: List of data sources. Output: Collected data. Specifically, the server runs a pre-configured crawling program to collect information from the data sources.

[1537] Step 5:

[1538] The generation AI analyzes the collected information and extracts activity information related to the user's location information. Input: collected data, location data. Output: related activity information. Specifically, the generation AI uses natural language processing technology to analyze the collected data, extract important information such as the activity name, location, date and time, and compare it with the user's location information.

[1539] Step 6:

[1540] The server converts the extracted information into a format that is easy for users to understand. Input: Related activity information. Output: Converted information. Specifically, the server formats the information and summarizes it into user-friendly text.

[1541] Step 7:

[1542] The server sends the converted information to the user's device. Input: Converted information. Output: Flag indicating completion of sending information to the device. Specifically, the server sends the converted information to the user's device in JSON format or similar.

[1543] Step 8:

[1544] The terminal displays the received information to the user so that the user can view it. Input: Converted information. Output: Display of information that can be viewed by the user. Specifically, the application analyzes the received data and displays it in a pop-up notification or on the interface.

[1545] Step 9:

[1546] Based on the information presented, the user carries out specific CO2 reduction activities (e.g., tree planting or participating in environmental protection events). Input: Presented information. Output: Details of the activity to be carried out. Specifically, the user follows the notification and carries out the activity at the specified location and time.

[1547] Step 10:

[1548] After the activity, the user inputs the specific amount and content of the activity they performed (e.g., number of trees planted) into the system. Input: Content of the activity performed. Output: Activity report data. Specifically, the user inputs the content of the activity into a form within the application.

[1549] Step 11:

[1550] The terminal sends the entered activity information to the server. Input: Activity report data. Output: Activity information storage completion flag on the server side. Specifically, the terminal sends the activity report data to the server, and the server stores it in a database.

[1551] Step 12:

[1552] The server uses the generation AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction. Input: Activity report data. Output: Evaluation results. Specifically, the generation AI analyzes the amount and content of the activity and evaluates the effect of CO2 reduction.

[1553] Step 13:

[1554] The server calculates reward points based on the evaluation results and grants them to the user's account. Input: Evaluation results. Output: Reward points. Specifically, the server calculates reward points based on the evaluation results and grants them to the user's account.

[1555] Step 14:

[1556] A notification is sent within the app so that the user can check their reward points. Input: Reward points. Output: Points awarded notification. Specifically, the application notifies the user that points have been awarded and presents a screen where the user can check their points.

[1557] (Application example 1)

[1558] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1559] CO2 reduction activities aimed at environmental protection are most effective when many individuals participate in them. However, at present, there are limited ways for general users to understand what CO2 reduction activities they can participate in or to evaluate the extent to which their activities have contributed to CO2 reduction. Furthermore, there is no adequate reward system in place, which means that general users have little motivation to participate. The purpose of this project is to solve this problem, encourage active participation by users, and promote effective CO2 reduction activities.

[1560] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1561] In this invention, the server includes: means for acquiring user location information; means for using a generation AI to collect information on CO2 reduction activities around the world; means for analyzing the collected information and extracting activity information related to the user's location information; means for converting the extracted information into a format that is easy for the user to understand; means for transmitting the converted information to the user's terminal; means for the terminal to record the user's activity amount and transmit the recorded information to the server; means for evaluating the input activity amount, calculating a reward based on the amount, and granting the reward to the user's account; means for providing instructions to the user including information on eco-activities; and means for making reward points available for use in the store. This allows users to always receive the latest information on CO2 reduction activities and earn rewards based on their activities, thereby enabling them to more actively participate in environmental protection activities.

[1562] The "means for acquiring user location information" refers to a device or software function that collects data necessary to identify the user's current location.

[1563] "Means for collecting information on CO2 reduction activities around the world using generative AI" refers to a device or software function that uses artificial intelligence technology to widely collect the latest information on CO2 reduction activities in various locations.

[1564] "Means for analyzing collected information and extracting activity information related to the user's location information" refers to the function of a device or software that analyzes collected data and identifies and extracts information about CO2 reduction activities related to the user's current location.

[1565] The "means for converting extracted information into a user-friendly format" refers to the function of a device or software that processes the analyzed and extracted information into a format that is easy for the user to understand.

[1566] The "means for transmitting the converted information to the user's terminal" refers to the function of a device or software for transmitting the processed information to the device used by the user.

[1567] "Means for the terminal to record the amount of user activity and send it to the server" refers to the function of a device or software that records the user's behavior on the terminal and sends the data to a central server.

[1568] "Means for evaluating the amount of activity entered, calculating rewards based thereon, and granting rewards to the user account" refers to the function of a device or software that evaluates the amount and quality of activity performed by a user and calculates and grants rewards accordingly.

[1569] The "means for providing a user with instructions including information on eco-friendly activities" refers to a function of a device or software that conveys behavioral instructions and information related to environmental protection to a user.

[1570] "Means for enabling reward points to be used in-store" refers to a device or software function that allows a user to use the reward points they have earned for discounts, payments, etc. at physical stores.

[1571] This invention provides a system that allows users to participate in CO2 reduction activities, receive rewards based on the evaluation of their contributions. The system acquires the user's location information, uses AI to collect and analyze the latest CO2 reduction activity information, and presents it to the user in an easy-to-understand manner. It also records the user's activity level and awards rewards based on the user's contribution.

[1572] Main components and their functions

[1573] 1. How to obtain user location information

[1574] The user's device (e.g., a smartphone) acquires the user's current location using GPS, etc. This location information is used in the next step.

[1575] 2. A means of using generative AI to collect information on CO2 reduction activities around the world

[1576] The server uses generative AI to collect the latest information on CO2 reduction activities from a variety of data sources, including news sites, environmental organization websites, and social media.

[1577] 3. A means of analyzing the collected information and extracting activity information related to the user's location information.

[1578] The server uses the generated AI to analyze the acquired user location information and extract information on CO2 reduction activities in which the user can participate.

[1579] 4. A means of converting the extracted information into a user-friendly format

[1580] The server converts the extracted information into a format that is easy for the user to understand and displays it, for example, through notification messages or an in-app interface.

[1581] 5. Means for transmitting the converted information to the user's terminal

[1582] The converted information is sent from the server to the user's terminal and notified in real time.

[1583] 6. How the device records the user's activity and sends it to the server

[1584] The user's device records the amount of CO2 reduction activity they have actually performed by scanning a QR code or manually entering it, and this information is sent to the server.

[1585] 7. A means for evaluating the amount of activity entered, calculating rewards based on the amount, and crediting the rewards to the user account.

[1586] The server uses the AI ​​generator to evaluate the amount of activity entered by the user and calculates reward points based on the contribution. The calculated reward is credited to the user's account and notified within the app.

[1587] 8. Means for providing users with instructions including eco-friendly activity information

[1588] The user's device provides the latest information on collected eco-activities and specific instructions for action.

[1589] 9. Means for reward points to be redeemed in-store

[1590] Users can use the reward points they earn for discounts and special offers at physical stores, which can be redeemed by scanning QR codes.

[1591] Specific examples

[1592] Consider a case where a user participates in a tree planting activity on the weekend. When the user launches the "Eco Store Guide" app, the app uses its GPS function to identify the user's current location and collects information about tree planting activities taking place in the area. For example, a notification might be displayed saying, "A tree planting activity is being held in a park near you. Join in and contribute to reducing CO2 emissions!" When the user participates in the activity and enters the number of trees planted, the information is sent to the server and evaluated by the generation AI. Based on the evaluation results, reward points are awarded to the user's account and the user is notified within the app. The awarded points can be used for discounts at affiliated stores, etc.

[1593] Prompt Sentence Examples

[1594] An example of a prompt sent to the generative AI model is, "Please provide us with the latest information on eco-activities. Your current location is latitude 35.6895, longitude 139.6917. We are particularly looking for tree planting activities and eco-bag usage initiatives."

[1595] In this way, users can easily obtain the latest eco-activity information, participate in CO2 reduction activities, and receive rewards according to the degree of their contribution.

[1596] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1597] Step 1:

[1598] The user's device uses the GPS function to identify the user's current location and obtains the location information.

[1599] Input: User consent, device GPS data

[1600] Data processing: Obtain the longitude and latitude of the user's current location and generate location data

[1601] Output: Current location data (longitude, latitude)

[1602] Step 2:

[1603] The server uses a generative AI model to collect information on CO2 reduction activities around the world.

[1604] Input: A list of pre-configured data sources on the server (news sites, environmental organizations' websites, social media, etc.), a prompt

[1605] Data processing: The generative AI model gathers information based on the prompt, analyzes and filters relevant data

[1606] Output: A list of detailed information about CO2 reduction activities

[1607] Step 3:

[1608] The server analyzes and extracts CO2 reduction activity information related to the user's location information.

[1609] Input: User location data, list of collected CO2 reduction activity information

[1610] Data processing: Filter and extract relevant CO2 reduction activity information based on user location information

[1611] Output: CO2 reduction activity information related to user location information

[1612] Step 4:

[1613] The server converts the extracted information into a format that is easy for the user to understand.

[1614] Input: Extracted CO2 reduction activity information

[1615] Data processing: Generate notification messages and interface designs to convey information to users in an easy-to-understand manner.

[1616] Output: Messages and display content to notify the user

[1617] Step 5:

[1618] The server transmits the converted information to the user's terminal.

[1619] Input: Message or display content

[1620] Data processing: Send information using a protocol that transfers messages to the device

[1621] Output: Notifications and messages displayed on the user's device

[1622] Step 6:

[1623] The device records the user's activity level and transmits the data to a server.

[1624] Input: User activity data (e.g. QR code scan, manual input)

[1625] Data processing: Record the acquired activity data, convert it into a data format, and send it to the server.

[1626] Output: Activity data sent to the server

[1627] Step 7:

[1628] The server evaluates the amount of activity entered, calculates a reward based on the amount, and grants the reward to the user account.

[1629] Input: User activity data, reward calculation algorithm

[1630] Data processing: Based on activity data, an AI model evaluates contribution and calculates reward points

[1631] Output: Calculated reward points, points credited to user account

[1632] Step 8:

[1633] The server provides the user with instructions including information on eco-activities.

[1634] Input: Latest eco-activity information

[1635] Data processing: Send information to the user terminal in the specified format

[1636] Output: Eco-activity information and instructions notified to the user

[1637] Step 9:

[1638] The user's terminal allows the reward points to be used in the store.

[1639] Input: Reward points granted to user account, available at stores

[1640] Data processing: Manage the point usage process and generate QR codes for use in stores

[1641] Output: A valid point redemption method at the store (QR code, etc.)

[1642] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1643] This invention is a system that provides the latest information on CO2 reduction activities based on the user's location information, evaluates the user's contribution to CO2 reduction through their actions with rewards, and further increases the user's motivation by recognizing the user's emotional state using an emotion engine and adjusting the way information is presented.By combining generative AI and an emotion engine, this system always provides the latest information and helps users take action easily.

[1644] Program processing

[1645] 1. Obtaining user location information

[1646] A user accesses an application or website in the system and logs in.

[1647] With the user's consent, the device collects current location information (longitude and latitude).

[1648] The device sends the location information it collects to the server.

[1649] 2. Collection and processing of the latest information

[1650] The server uses generated AI to collect information on CO2 reduction activities around the world from a variety of data sources (news sites, environmental organization websites, social media, etc.).

[1651] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[1652] The emotion engine analyzes the user's voice data and facial expression data to recognize their emotional state, and adjusts the way the collected information is presented to suit the user's emotional state.

[1653] For example, if the user is tired, provide a brief, encouraging message, and if they are proactive, provide a detailed, action-oriented message.

[1654] 3. Providing information and encouraging action

[1655] The server sends the converted information to the user's terminal.

[1656] The terminal displays the received information to the user so that the user can view it.

[1657] For example, a notification might appear saying, "Tree planting activities are taking place in your town this weekend. Join in and help reduce CO2 emissions!"

[1658] The emotion engine monitors the user's emotional state and provides information at the appropriate time.

[1659] 4. Recording behavior and calculating rewards

[1660] Based on the information provided by the user, the user can carry out specific CO2 reduction activities (e.g., tree planting activities or participating in environmental protection events).

[1661] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the system.

[1662] The terminal transmits the input activity information to the server.

[1663] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[1664] The server calculates reward points based on the evaluation results and grants them to the user's account.

[1665] The terminal notifies the user of the reward points and allows the user to check the points.

[1666] Specific examples

[1667] Example 1: When a user participates in a tree planting activity

[1668] 1. User Activities

[1669] The user accesses the application and receives information about participating in a tree planting activity over the weekend, along with an encouraging message from the emotion engine.

[1670] Go to the designated location and plant 10 trees.

[1671] After the activity, participants enter the number of trees planted in the application and report, "I planted 10 trees today."

[1672] 2. System evaluation and rewards

[1673] The terminal sends the user's input to the server.

[1674] The server uses generated AI to evaluate the amount of CO2 reduction equivalent to planting 10 trees and awards, for example, 10 points.

[1675] The server notifies the user of the points and sends a message praising the user's efforts through the emotion engine.

[1676] Reward points will be added to your user account and you will receive a notification.

[1677] This system allows users to always receive the latest information on CO2 reduction activities, take specific actions based on that information, and receive rewards for their results. Furthermore, by using an emotion engine to provide information that corresponds to the user's emotional state, it is possible to motivate users and encourage more proactive CO2 reduction actions.

[1678] The processing flow will be explained below.

[1679] Step 1:

[1680] A user logs into an application or website on the system.

[1681] Step 2:

[1682] With the user's consent, the device collects current location information (longitude and latitude).

[1683] Step 3:

[1684] The device sends the location information it collects to the server.

[1685] Step 4:

[1686] The server uses generated AI to collect information on CO2 reduction activities around the world from multiple data sources (news sites, environmental organization websites, social media, etc.).

[1687] Step 5:

[1688] The generation AI analyzes the collected information and extracts activity information related to the user's location.

[1689] Step 6:

[1690] The emotion engine analyzes the user's voice data and facial expression data to recognize their emotional state.

[1691] For example, the user provides facial expressions and voice through the application's camera and microphone, and the emotion engine evaluates the user's current emotional state.

[1692] Step 7:

[1693] The server converts the collected activity information into a user-friendly format based on the user's emotional state.

[1694] For example, if the user is tired, it generates a brief, encouraging message (e.g., "Why not relax and take part in a simple tree-planting event nearby?"), while if the user is proactive, it generates a detailed, actionable message (e.g., "There's a large-scale tree-planting event near your home. Plant lots of trees and contribute to reducing CO2 emissions!").

[1695] Step 8:

[1696] The server sends the converted information to the user's terminal.

[1697] Step 9:

[1698] The terminal displays the received information to the user so that the user can view it.

[1699] Step 10:

[1700] Based on the displayed information, the user participates in CO2 reduction activities (e.g., tree planting activities or environmental protection events).

[1701] Step 11:

[1702] After the activity, the user inputs the specific amount and content of the activity (e.g., number of trees planted) into the application.

[1703] Step 12:

[1704] The terminal transmits the input activity information to the server.

[1705] Step 13:

[1706] The server uses generated AI to evaluate the amount of activity entered by the user and calculates the contribution to CO2 reduction.

[1707] Step 14:

[1708] The server calculates reward points based on the evaluation results and grants them to the user's account.

[1709] Step 15:

[1710] The terminal notifies the user of the reward points and allows the user to check the points.

[1711] The emotion engine also reassess the user's emotional state and sends a message praising their efforts (e.g., "Amazing! Your contribution will save the planet!").

[1712] Through these steps, the system provides users with customized information on CO2 reduction activities based on their location information and emotional state, and encourages them to contribute to the environment by evaluating and rewarding their actions.

[1713] Example 2

[1714] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1715] Conventional CO2 reduction activity information provision systems have insufficient collection and analysis of the latest information, making it difficult to provide appropriate information based on the user's location information and emotional state. In addition, there are issues with the cumbersome calculation of rewards based on the user's specific activity level, making it difficult to maintain user motivation.

[1716] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1717] In this invention, the server includes a means for acquiring user location information, a means for using a generation AI to collect information on CO2 reduction activities around the world, and a means for analyzing the collected information and extracting activity information related to the user's location information, thereby making it possible to provide the latest CO2 reduction activity information based on the user's location information.

[1718] The server also includes means for analyzing the user's emotional state, means for adjusting the presentation method of the collected information according to the user's emotional state, means for converting the extracted information into a format that is easy for the user to understand, means for transmitting the converted information to the user's terminal, means for inputting and transmitting the user's activity level, means for evaluating the input activity level, calculating a reward based on it, and adding the reward to the user's account, and means for notifying the user of the reward points. This realizes an effective information provision and reward system that is tailored to the user's emotional state, increases the user's motivation, and promotes more proactive CO2 reduction activities.

[1719] "Means for obtaining user location information" refers to a function that collects longitude and latitude data from the device with the user's consent and transmits it to a server.

[1720] "Means of using generative AI to collect information on CO2 reduction activities around the world" is a function that uses generative AI to obtain information on CO2 reduction activities from a variety of data sources, such as news sites, websites of environmental protection organizations, and social media.

[1721] "Means for analyzing collected information and extracting activity information related to the user's location information" refers to a function that analyzes the data collected by the generation AI and identifies CO2 reduction activities and event information that are closely related to the user's current location.

[1722] The "means for analyzing the user's emotional state" is a function that uses technology for analyzing voice data and facial expression data to recognize the user's emotional state in real time.

[1723] "Means for adjusting the presentation of collected information to match the user's emotional state" refers to a function that dynamically changes the format and content of information provided to the user based on the recognized emotional state.

[1724] The "means of converting extracted information into a user-friendly format" is a function that converts technical terms and complex data into a user-friendly format.

[1725] The "means for transmitting the converted information to the user's device" is a function for transmitting the converted information from the server to the user's device as a push notification or an in-application message.

[1726] "Means for inputting and transmitting user activity data" is a function that provides an interface for users to input details of their activities (e.g., number of trees planted) and transmit that information to the server.

[1727] "Means of evaluating the amount of activity entered, calculating rewards based on that, and granting rewards to the user's account" refers to a function in which the generation AI analyzes the entered activity data, calculates the contribution to CO2 reduction, calculates reward points, and reflects those points in the user's account.

[1728] The "means for notifying the user of the reward points" is a function that notifies the user that the calculated reward points have been added to the user's account.

[1729] The present invention is a system that provides users with up-to-date information on CO2 reduction activities based on their location information, helping them take action and contribute to CO2 reduction. Furthermore, it uses an emotion engine to recognize the user's emotional state and adjusts the way information is presented to increase the user's motivation. An embodiment of this system is described below.

[1730] First, a user accesses the system's application or website and logs in. With the user's consent, the device collects and transmits current location information (longitude and latitude) to the server.

[1731] The server uses a generative AI (e.g., OpenAI's GPT-4) to collect information on CO2 reduction activities from various data sources, such as news sites, environmental protection organization websites, and social media. This information collection is performed on a regular schedule. The generative AI analyzes the collected data and extracts activity information related to the user's location.

[1732] The server then uses an emotion engine to analyze the user's voice and facial expression data to recognize their emotional state in real time. The voice recognition tool is Google Cloud Speech-to-Text API, and the facial expression recognition tool is Face++. Based on the acquired emotional state, the server adjusts how the collected information is presented. For example, if the user is determined to be tired, it will provide a concise, encouraging message, while if the user is determined to be proactive, it will provide a detailed, action-oriented message.

[1733] As a concrete example, the following message is provided:

[1734] "This weekend, a tree planting event will be held in your town. Join in and help reduce CO2 emissions!"

[1735] Furthermore, if the user participates in CO2 reduction activities based on the information provided, the amount of activity (e.g., number of trees planted) is reported within the application. The device sends this information to the server, which uses a generation AI to evaluate the amount of activity entered. The server calculates the contribution to CO2 reduction and calculates reward points, which are then added to the user's account. The user is then notified that the reward points have been added.

[1736] Through this series of processes, users can always receive the latest information on CO2 reduction activities, take specific actions based on that information, and receive rewards for their results.In addition, by using the emotion engine to provide information according to the user's emotional state, users' motivation is enhanced, and more proactive CO2 reduction actions can be expected.

[1737] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1738] Step 1:

[1739] A user accesses an application or website in the system and logs in.

[1740] Specifically, the user opens the application, enters their ID and password, and presses the "Login" button.

[1741] Input: User ID and password

[1742] Output: User credentials

[1743] Step 2:

[1744] With the user's consent, the device collects location information (longitude and latitude) and sends it to the server.

[1745] Specifically, the app displays a pop-up asking "Do you want to allow location access?" and the user selects "Allow."

[1746] Input: User consent

[1747] Output: User's location (longitude and latitude)

[1748] Step 3:

[1749] The server uses generated AI to collect information on CO2 reduction activities from a variety of data sources, including news sites, websites of environmental protection organizations, and social media.

[1750] Specifically, the generating AI acquires information based on a regular schedule.

[1751] Input: Raw data such as news articles, blog posts, and social media posts

[1752] Output: Organized information on CO2 reduction activities

[1753] Step 4:

[1754] The server analyzes the collected information using generated AI and extracts activity information related to the user's location.

[1755] Specifically, the generative AI categorizes the collected data and filters relevant information based on location information.

[1756] Input: Organized CO2 reduction activity information, user location information

[1757] Output: Activity information related to the user's location

[1758] Step 5:

[1759] The server uses an emotion engine to analyze the user's voice data and facial expression data and recognize their emotional state.

[1760] Specifically, the user provides data via the smartphone's camera and microphone, and the emotion engine analyzes it in real time.

[1761] Input: User's voice data, facial expression data

[1762] Output: User's emotional state data

[1763] Step 6:

[1764] Based on the results of the emotion engine, the server adjusts the presentation of the collected information to suit the user's emotional state.

[1765] Specifically, the generation AI generates an appropriate message depending on the emotional state.

[1766] Input: User's emotional state data, related activity information

[1767] Output: Messages tailored to your emotional state

[1768] Step 7:

[1769] The server transmits the converted information to the user's terminal.

[1770] Specifically, the server generates a notification message and sends it to the terminal as a push notification.

[1771] Input: Messages tailored to your emotional state

[1772] Output: Notification to the user's device

[1773] Step 8:

[1774] CO2 reduction activities will be carried out based on the information received by the user.

[1775] The user enters the amount and content of their activity into the app, and the device sends the data to the server.

[1776] Specifically, a user participates in an event, and after participating in the event, they enter "I planted 10 trees today" in the app and press the "Send" button.

[1777] Input: User activity details (number of trees planted, etc.)

[1778] Output: Activity details data

[1779] Step 9:

[1780] The server uses generated AI to evaluate the amount of activity entered and calculates the contribution to CO2 reduction.

[1781] Specifically, the generating AI analyzes the user's input data and evaluates it as, for example, "Planting 10 trees = 10 points."

[1782] Input: Activity details data

[1783] Output: Contribution data

[1784] Step 10:

[1785] The server calculates reward points based on the contribution and credits them to the user's account.

[1786] Specifically, after the points are calculated, the server automatically adds the points to the user's account.

[1787] Input: Contribution data

[1788] Output: Reward points

[1789] Step 11:

[1790] The terminal notifies the user of the reward points and allows the user to check the points.

[1791] Specifically, the app will display a notification to the user saying "10 points added!"

[1792] Input: Reward Points

[1793] Output: Point notification

[1794] (Application example 2)

[1795] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1796] Conventional CO2 reduction activity support systems are limited to providing users with location information and the latest information, and lack advice on which route users should take from a security perspective. Furthermore, because they present information without taking into account the user's emotional state, they are unable to provide appropriate support when motivation is low. These issues make it difficult to encourage users to take proactive action, and CO2 reduction activities are not fully effective. Furthermore, there is a need for information provision on CO2 reduction activities that is linked to ensuring safety.

[1797] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1798] In this invention, the server includes means for sorting collected information and security precautions, means for analyzing the user's emotional state using an emotion engine and adjusting the way information is presented, and means for proposing a safe route taking into account the user's location information. This makes it possible to provide information at an appropriate time according to the user's emotional state and to give advice on selecting a safe route, allowing the user to actively and safely participate in CO2 reduction activities.

[1799] "Means for obtaining location information" refers to technical means for identifying the user's current geographical location.

[1800] "Generative AI" is a technology that uses artificial intelligence to generate new information from data.

[1801] An "information collection means" is a method or device for gathering data relevant to a particular purpose.

[1802] "Means of analyzing information" refers to techniques for analyzing collected data and extracting meaningful information.

[1803] "Means for adjusting the method of presenting information" refers to a technique for changing the format and timing of information presented depending on the user's emotional state.

[1804] The "means for inputting and transmitting the amount of activity" refers to a means for recording the amount and content of the user's actions in the system and transmitting them to the server.

[1805] The "means for evaluating the amount of activity and calculating the reward" is a technology for measuring the actions performed by the user and calculating the reward for the user based on the results.

[1806] A "reward granting means" is a technology for recording and adding rewards to a user account.

[1807] "Means for selecting security precautions" refers to a technology that extracts and emphasizes important safety information from the information provided to users.

[1808] An "emotion engine" is a technology that analyzes a user's emotional state from facial expressions, voice, etc.

[1809] The "means for suggesting a safe route" is a technology that takes into account the user's location information and provides the safest route.

[1810] The system for realizing this invention is configured using the following hardware and software, including, as its main elements, a means for acquiring user location information, a means for sorting collected information and security precautions, a means for analyzing the user's emotional state using an emotion engine and adjusting the way information is presented, a means for proposing a safe route taking into account the user's location information, and a means for collecting information using a generative AI.

[1811] 1. Obtaining user location information

[1812] The server obtains location information using the user's smartphone or GPS device. When the user logs in to the application and provides consent for location information collection, the current location information (longitude and latitude) is sent to the server.

[1813] Hardware: GPS devices, smartphones

[1814] Software: Android / iOS SDK, location information acquisition API

[1815] 2. Information collection and analysis

[1816] The server uses generative AI (such as OpenAI GPT-3) to collect the latest information on global CO2 reduction activities and security from multiple sources. The AI ​​analyzes the collected information and extracts activity and security information related to the user's location. This information is formatted to match the user's emotional state.

[1817] Hardware: Servers, database servers

[1818] Software: NLP model, multi-source data collection API

[1819] 3. Adjustment by Emotion Engine

[1820] The emotion engine analyzes the user's voice and facial expression data to recognize their emotional state, and then adjusts how the collected information is presented. For example, if the user is tired, it will provide a concise, encouraging message, while if they are proactive, it will provide a detailed, actionable message.

[1821] Hardware: Audio input device (microphone), camera

[1822] Software: Sentiment Analysis Engine

[1823] 4. Safe Route Suggestion

[1824] The server will suggest the safest route based on the user's location information, allowing users to minimize risks when participating in CO2 reduction activities. For example, routes that avoid dangerous areas at night will be automatically suggested.

[1825] Hardware: GPS devices, smartphones

[1826] Software: Map API, route calculation algorithm

[1827] 5. Recording behavior and calculating rewards

[1828] The server records the content and amount of the user's actions and calculates rewards based on that information. The user inputs their actions through the application, and the server evaluates them using a generative AI. Reward points are calculated based on the evaluation results and awarded to the user's account.

[1829] Hardware: Smartphones, servers

[1830] Software: Database (MySQL / PostgreSQL), Reward Management System

[1831] Prompt Sentence Examples

[1832] Here are some examples of prompts to input to the generative AI model:

[1833] Collect the latest information on CO2 reduction activities and security around the world and provide appropriate activity information based on the user's location. Adjust the way information is presented depending on the user's emotional state. For example, if the user is tired, provide an encouraging message, and if they are active, provide a detailed call-to-action message.

[1834] This provides users with CO2 reduction activity information optimized for their location and emotional state, while also ensuring security, allowing users to proactively and safely engage in activities.

[1835] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1836] Step 1:

[1837] Obtaining user location information

[1838] The user logs in to the application and gives consent to obtain location information.

[1839] Input: User consent, public location information

[1840] Data processing: Obtain location information (longitude and latitude) from the GPS chip

[1841] Output: Sends the user's current location to the server

[1842] How it works: An app on your smartphone collects location information from the GPS chip and sends it to a server.

[1843] Step 2:

[1844] Gathering the latest information

[1845] The server uses generated AI to collect information on CO2 reduction activities and security around the world.

[1846] Input: Data sources such as news sites, environmental organization websites, and social media.

[1847] Data processing: Generative AI analyzes information and extracts relevant information

[1848] Output: The latest information collected and analyzed

[1849] How it works: The server retrieves information from multiple data sources through an API, and the generating AI analyzes the data.

[1850] Step 3:

[1851] Emotional state analysis

[1852] The device uses an emotion engine to analyze the user's voice data and facial expression data and recognize their emotional state.

[1853] Input: User's voice data, facial expression data

[1854] Data processing: Identifying emotional states using speech recognition and facial expression analysis algorithms

[1855] Output: The user's current emotional state

[1856] How it works: Your smartphone or connected device captures your voice and facial expression data, which is then analyzed by the emotion engine.

[1857] Step 4:

[1858] Adjusting how information is presented

[1859] The server adjusts how information is presented based on the output of the emotion engine.

[1860] Input: User's emotional state, collected information

[1861] Data processing: determining the appropriate information form and timing

[1862] Output: Tailored information presentation

[1863] How it works: The server optimizes the timing and content of information presentation based on the user's emotional state and location information.

[1864] Step 5:

[1865] Safe route suggestions

[1866] The server takes into account the user's location and suggests the safest route.

[1867] Input: current user location, map information, security notices

[1868] Data calculation: Calculates safe routes and avoids dangerous areas

[1869] Output: Recommended safe route

[1870] How it works: The server uses map APIs and security information to calculate a safe route and send it to the user's smartphone.

[1871] Step 6:

[1872] Recording behavior and calculating rewards

[1873] The user inputs the amount and content of their actions into the application, and the server evaluates them using a generative AI to calculate reward points.

[1874] Input: Activity amount and details of the activity entered by the user

[1875] Data calculation: Evaluating actions and calculating reward points

[1876] Output: Reward points and notification

[1877] How it works: The server records the user's input, and the generating AI evaluates the activity level and calculates reward points. The reward points are added to the user's account and notified.

[1878] Prompt Sentence Examples

[1879] Here are some examples of prompts to input to the generative AI model:

[1880] Collect the latest information on CO2 reduction activities and security around the world and provide appropriate activity information based on the user's location. Adjust the way information is presented depending on the user's emotional state. For example, if the user is tired, provide an encouraging message, and if they are active, provide a detailed call-to-action message.

[1881] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1882] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1883] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1884] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1885] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1886] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1887] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1888] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1889] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1890] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1891] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1892] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1893] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1894] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1895] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1896] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1897] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1898] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1899] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1900] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1901] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1902] The following is further disclosed regarding the above embodiment.

[1903] (Claim 1)

[1904] A means for acquiring user location information;

[1905] A means of collecting information on CO2 reduction activities around the world using generative AI, and

[1906] A means for analyzing the collected information and extracting activity information related to the user's location information;

[1907] a means for converting the extracted information into a user-friendly format;

[1908] means for transmitting the converted information to a user terminal;

[1909] A means for inputting and transmitting the amount of activity of the user;

[1910] The system includes a means for evaluating the input activity amount, calculating a reward based thereon, and crediting the reward to a user account.

[1911] (Claim 2)

[1912] 10. The system of claim 1, further comprising means for obtaining collected information from multiple sources and translating the information.

[1913] (Claim 3)

[1914] 10. The system of claim 1, wherein the reward to the user is based on a points system or monetary value.

[1915] "Example 1"

[1916] (Claim 1)

[1917] A means for acquiring user location information;

[1918] A means of collecting information on CO2 reduction activities around the world using generative AI, and

[1919] A means for analyzing the collected information and extracting activity information related to the user's location information;

[1920] a means for converting the extracted information into a user-friendly format;

[1921] means for transmitting the converted information to a user terminal;

[1922] A means for inputting and transmitting the amount of activity of the user;

[1923] means for evaluating the input activity amount, calculating a reward based thereon, and granting the reward to the user account;

[1924] a means for displaying a reward notification on a user's terminal;

[1925] A system that includes a means for analyzing collected information using natural language processing technology.

[1926] (Claim 2)

[1927] 10. The system of claim 1, further comprising means for obtaining collected information from multiple sources and translating the information.

[1928] (Claim 3)

[1929] 10. The system of claim 1, wherein the reward to the user is based on a points system or monetary value.

[1930] "Application Example 1"

[1931] (Claim 1)

[1932] A means for acquiring user location information;

[1933] A means of collecting information on CO2 reduction activities around the world using generative AI, and

[1934] A means for analyzing the collected information and extracting activity information related to the user's location information;

[1935] a means for converting the extracted information into a user-friendly format;

[1936] means for transmitting the converted information to a user terminal;

[1937] A means for the terminal to record the amount of activity of the user and transmit the amount of activity to a server;

[1938] means for evaluating the input activity amount, calculating a reward based thereon, and granting the reward to the user account;

[1939] means for providing instructions to a user, including information on eco-activities;

[1940] a means for enabling reward points to be used in-store;

[1941] A system including:

[1942] (Claim 2)

[1943] 10. The system of claim 1, further comprising means for obtaining collected information from multiple sources and translating the information.

[1944] (Claim 3)

[1945] 10. The system of claim 1, further comprising means for assessing reward points based on participation in eco-activities.

[1946] "Example 2: Combining Emotion Engines"

[1947] (Claim 1)

[1948] A means for acquiring user location information;

[1949] A means of collecting information on CO2 reduction activities around the world using generative AI, and

[1950] A means for analyzing the collected information and extracting activity information related to the user's location information;

[1951] means for analyzing the emotional state of a user;

[1952] means for tailoring the presentation of the collected information to the user's emotional state;

[1953] a means for converting the extracted information into a user-friendly format;

[1954] means for transmitting the converted information to a user terminal;

[1955] A means for inputting and transmitting the amount of activity of the user;

[1956] means for evaluating the input activity amount, calculating a reward based thereon, and granting the reward to the user account;

[1957] The system includes a means for notifying a user of reward points.

[1958] (Claim 2)

[1959] 10. The system of claim 1, further comprising means for obtaining collected information from multiple sources and translating the information.

[1960] (Claim 3)

[1961] 10. The system of claim 1, wherein the reward to the user is based on a points system or monetary value.

[1962] "Application example 2 when combining emotion engines"

[1963] (Claim 1)

[1964] A means for acquiring user location information;

[1965] A means of collecting information on CO2 reduction activities around the world using generative AI, and

[1966] A means for analyzing the collected information and extracting activity information related to the user's location information;

[1967] a means for converting the extracted information into a user-friendly format;

[1968] means for transmitting the converted information to a user terminal;

[1969] A means for inputting and transmitting the amount of activity of the user;

[1970] means for evaluating the input activity amount, calculating a reward based thereon, and granting the reward to the user account;

[1971] The means to screen the collected information and security precautions;

[1972] means for analyzing a user's emotional state using an emotion engine and adjusting how information is presented;

[1973] A system that includes a means for suggesting safe routes taking into account the user's location information.

[1974] (Claim 2)

[1975] 10. The system of claim 1, further comprising means for obtaining collected information from multiple sources and translating the information.

[1976] (Claim 3)

[1977] 10. The system of claim 1, wherein the reward to the user is based on a points system or monetary value. [Explanation of symbols]

[1978] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for acquiring user location information; A means of collecting information on CO2 reduction activities around the world using generative AI, and A means for analyzing the collected information and extracting activity information related to the user's location information; a means for converting the extracted information into a user-friendly format; means for transmitting the converted information to a user terminal; A means for inputting and transmitting the amount of activity of the user; The system includes a means for evaluating the input activity amount, calculating a reward based thereon, and crediting the reward to a user account.

2. 10. The system of claim 1, further comprising means for obtaining collected information from multiple sources and translating the information.

3. 10. The system of claim 1, wherein the reward to the user is based on a points system or a monetary value.

Images