System

Abstract

To provide a system.SOLUTION: A system includes: means for analyzing the profile and interest of a user and the current state; providing a proposal and a recycling method on sustainable living and information tailored to individual users on energy-saving tips on the basis of the analysis results; means for presenting a method and concrete actions for minimizing the impact on the environment; means for collecting user data, performing preprocessing, and analyzing the interests and preferences of the user; means for acquiring the current situation data from an external data source; means for generating a response to the user using a generative AI model; and means for providing the user with the generated response.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] In today's society, it is difficult to provide individual users with concrete actions to achieve sustainable living, recycling methods, energy-saving tips, etc. It is also difficult to provide information on environmentally friendly products and services based on the user's profile, interests, and current situation. [Means for solving the problem]

[0005] The present invention provides a means for analyzing a user's profile, interests, and current situation, a means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, and a means for suggesting ways to minimize environmental impact and specific actions. Furthermore, the present invention also provides a means for providing information on environmentally friendly products and services, and a means for customizing the provided information to each user. This makes it possible to provide environmentally friendly information optimized for each individual user. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The present invention is a system that uses AI. This system has a means for analyzing a user's profile, interests, and current situation. For example, the system analyzes the user's social media posts, purchase history, search history, etc. to understand the user's interests and preferences. The system also takes into account the user's current situation, such as the season, weather, and local environmental issues.

[0029] "Example 2"

[0030] Next, based on the analysis results, the system has the means to provide information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips. For example, it can make environmentally conscious suggestions related to the user's areas of interest. It can also provide recycling methods and energy-saving tips that are suited to the user's living environment and lifestyle.

[0031] "Example 3"

[0032] Furthermore, the site has a means for providing information on environmentally friendly products and services. For example, it provides information on environmentally friendly products and services related to products and services that the user is interested in. This allows the user to learn about environmentally friendly products and services that match their interests and preferences.

[0033] "Example 4"

[0034] Finally, it has the means to customize the information provided to users, for example, by adjusting the content and format of the information provided based on user reactions and feedback, thereby making it possible to provide more useful and attractive information to users.

[0035] The processing flow of each embodiment will be described below.

[0036] "Example 1"

[0037] Step 1: The system collects the user's social media posts, purchase history, search history, etc.

[0038] Step 2: Based on the collected data, AI analyzes the user's profile, interests, and current situation.

[0039] Step 3: Based on the analysis results, provide users with suggestions for sustainable living, recycling methods, energy-saving tips, etc.

[0040] "Example 2"

[0041] Step 1: The system makes environmentally friendly suggestions related to the user's interests and preferences.

[0042] Step 2: Provide users with recycling and energy-saving tips tailored to their living environment and lifestyle.

[0043] "Example 3"

[0044] Step 1: The system provides information on environmentally friendly products and services related to the products and services in which the user is interested.

[0045] "Example 4"

[0046] Step 1: The system collects user responses and feedback.

[0047] Step 2: Adjust the content and format of the information you provide based on the responses and feedback you receive.

[0048] Example 1

[0049] Next, a description will be given of Example 1 of Form 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."

[0050] Conventional systems struggled to provide information that fully took into account the user's profile, interests, and current situation, making it impossible to provide optimal recommendations for each individual user. Furthermore, there was a lack of effective methods for providing concrete actions to minimize environmental impact and suggestions for sustainable living.

[0051] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for presenting methods and specific actions for minimizing environmental impact; means for collecting and preprocessing user data and analyzing the user's interests and preferences; means for acquiring current situation data from an external data source; means for generating a response to the user using a generative AI model; and means for providing the generated response to the user. This makes it possible to make optimal suggestions taking into account the user's interests and current situation.

[0052] A "user profile" is a collection of data including a user's personal information, interests, preferences, behavioral history, etc.

[0053] "Interests" refers to the topics, activities, hobbies, etc. that a user is interested in.

[0054] "Current situation" refers to the environment or conditions in which the user finds themselves, such as the season, weather, or specific local conditions.

[0055] "Means of analysis" refers to methods and technologies for analyzing a user's profile, interests, and current situation and extracting meaningful information.

[0056] "Sustainable Living Suggestions" refers to specific advice and information to promote environmentally friendly lifestyles and behaviors.

[0057] "Recycling methods" refer to specific steps or methods for converting waste into a reusable form.

[0058] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[0059] "Methods of minimizing environmental impact" refers to specific actions and measures taken to reduce the burden on the environment.

[0060] "Means of suggesting specific actions" refers to techniques and methods for suggesting actions or methods that can be taken by users.

[0061] "Means of collecting data" refers to the methods and technologies used to obtain data about user behavior and interests.

[0062] "Preprocessing means" refers to methods and techniques for preparing collected data in a form that is easy to analyze.

[0063] "Interest and preference analysis means" refers to methods and technologies used to identify users' interests and preferences.

[0064] "External data sources" refers to external information sources used to understand the user's current situation.

[0065] A "generative AI model" refers to a model that uses artificial intelligence to generate responses and suggestions for users.

[0066] "Response generation means" refers to the technology or method for creating an appropriate response based on the user's profile and current situation.

[0067] "Means for providing a response" refers to the method or technology used to communicate the generated response to the user.

[0068] MODE FOR CARRYING OUT THE INVENTION

[0069] This invention is a system that analyzes a user's profile, interests, and current situation, and provides suggestions for sustainable living, recycling methods, energy-saving tips, etc. Specific embodiments of this system are described below.

[0070] Hardware and software used

[0071] The server uses the following hardware and software for data collection, pre-processing, analysis, and response generation:

[0072] Hardware: High-performance server (e.g., Intel Xeon processor, 32GB RAM or more)

[0073] Software: Python programming language, TENSORFLOW®, PyTorch, NLTK, spaCy, MySQL® or MongoDB, external APIs (e.g., OpenWeatherMap API)

[0074] The terminal uses the following hardware and software to receive input from the user and display responses from the server:

[0075] Hardware: Smartphones, tablets, computers

[0076] Software: web browser, mobile application

[0077] Data collection and preprocessing

[0078] The server collects data such as users' social media posts, purchase history, search history, etc. This includes retrieving data from social media platforms and e-commerce sites through APIs. For example, it uses the Twitter API to retrieve users' tweets and the Amazon API to collect purchase history.

[0079] The collected data is preprocessed by cleaning the text data (removing unnecessary characters and symbols), tokenizing it (splitting it into words and phrases), and removing stop words. This is done using natural language processing libraries such as NLTK and spaCy.

[0080] Analysis of user interests and preferences

[0081] The server analyzes the user's interests and preferences based on the preprocessed data. Specifically, it uses machine learning models (e.g., TF-IDF, Word2Vec) to identify the user's interests. The results of this analysis are stored in a database as a user profile.

[0082] Get current status data

[0083] The server retrieves data from external APIs (e.g., OpenWeatherMap API) to take into account the user's current situation (season, weather, local environmental issues, etc.), thereby providing real-time weather information and local specific conditions.

[0084] Response generation using generative AI models

[0085] The server generates appropriate responses using a generative AI model (e.g., GPT-3 (registered trademark), BERT) based on the user's profile data and current situation data. The generative AI model takes this data as input and generates optimal suggestions and answers for the user.

[0086] Providing a response

[0087] The device displays the responses received from the server to the user, who can then review the suggestions and answers and ask further questions if necessary.

[0088] Examples of concrete examples and prompts

[0089] As a concrete example, consider a case where a user asks, "What outdoor activities are recommended for this weekend?" The server understands the user's outdoor interests from their past search history and social media posts, and retrieves current weather data. For example, if the weather is sunny, it will suggest hiking or a picnic.

[0090] Example prompt sentence:

[0091] User profile data:

[0092] Social media post: "I went hiking recently. It was so much fun!"

[0093] Purchase history: "Purchase outdoor equipment"

[0094] Search history: "Hiking trails near me"

[0095] Current weather data:

[0096] Region: Tokyo

[0097] Weather: Sunny

[0098] Prompt for the generative AI model:

[0099] "User is interested in outdoor activities and the weather is sunny right now. Can you suggest some outdoor activities for this weekend?"

[0100] In this way, the system makes appropriate suggestions that take into account the user's interests and current situation.

[0101] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0102] Step 1: Collect user data

[0103] The server collects data such as users' social media posts, purchase history, and search history. Specifically, it obtains data from social media platforms and e-commerce sites through APIs. For example, it uses the Twitter API to obtain users' tweets and the e-commerce site's API to collect purchase history. The input is the user's account information, and the output is the collected raw data.

[0104] Step 2: Preprocessing the data

[0105] The server preprocesses the collected data. Specifically, it cleans the text data (removes unnecessary characters and symbols), tokenizes it (divides it into words and phrases), and removes stop words. This is done using natural language processing libraries such as NLTK and spaCy. The input is the collected raw data, and the output is the preprocessed, clean data.

[0106] Step 3: Analyzing user interests and preferences

[0107] The server analyzes the user's interests and preferences based on the preprocessed data. Specifically, it uses machine learning models (e.g., TF-IDF, Word2Vec) to identify the user's interests. The results of this analysis are stored in a database as a user profile. The input is the preprocessed, clean data, and the output is profile data that indicates the user's interests and preferences.

[0108] Step 4: Get current situation data

[0109] The server retrieves data from external APIs (e.g., OpenWeatherMap API) to take into account the user's current situation (season, weather, local environmental issues, etc.), thereby understanding real-time weather information and local specific conditions. The input is the user's location, and the output is current situation data.

[0110] Step 5: Generative AI model generates a response

[0111] The server generates an appropriate response using a generative AI model (e.g., GPT-3, BERT) based on the user's profile data and current situation data. The generative AI model takes these data as input and generates optimal suggestions or answers for the user. The input is the user profile data and current situation data, and the output is the generated response.

[0112] Step 6: Providing a response

[0113] The terminal displays the responses received from the server to the user, who can then review the suggestions and answers and ask further questions if necessary. The input is the response generated, and the output is the information displayed to the user.

[0114] (Application example 1)

[0115] Next, a description will be given of Application Example 1 of Embodiment 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."

[0116] In modern society, providing personalized advertisements based on users' interests and preferences is important, but conventional systems have difficulty generating advertisements that fully consider the user's profile and current situation. There is also a need to simultaneously provide environmentally friendly information and suggestions for sustainable living, but there is a lack of efficient ways to achieve this. Furthermore, a system is needed that can comprehensively analyze a variety of data, such as users' social media posts, purchase history, and search history, to generate optimal advertisements.

[0117] 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.

[0118] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for analyzing the user's social media posts, purchase history, and search history to understand the user's interests and preferences, and means for generating and displaying advertisements that are optimal for the user, taking into account current conditions such as the season, weather, and local environmental issues. This makes it possible to comprehensively analyze a variety of user data and simultaneously provide personalized advertisements and environmentally friendly information.

[0119] A "user profile" is a collection of data including a user's personal information, behavioral history, interests, preferences, etc.

[0120] "Interests" refer to the things or areas in which a user is interested.

[0121] "Current situation" includes the environment and conditions in which the user finds himself, such as the season, weather, and local environmental issues.

[0122] "Means of analysis" refers to methods and technologies for analyzing a user's profile, interests, and current situation and extracting relevant information.

[0123] "Sustainable Living Advice" means providing advice and information to promote environmentally friendly lifestyles and behaviours.

[0124] "Recycling method" refers to the specific procedures and methods for reusing used products and waste materials.

[0125] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[0126] "Methods of minimizing environmental impact" refers to specific measures and actions taken to reduce the burden on the environment.

[0127] "Means of presenting specific actions" refers to methods or techniques that show users specific actions they can actually take.

[0128] "SNS posts" refer to comments, photos, videos, etc. posted by users on social networking services.

[0129] "Purchase history" refers to a record of products and services a user has purchased in the past.

[0130] "Search history" refers to a record of searches a user has conducted on the Internet.

[0131] "Season" refers to the changes in weather that occur throughout the year.

[0132] "Weather" refers to the weather conditions in a particular area and at a particular time.

[0133] "Regional environmental issues" refers to environmental challenges and problems in a particular region.

[0134] "Means for generating and displaying advertisements" refers to methods and technologies for creating and displaying advertisements that are optimal for the user based on the user's interests and current situation.

[0135] A system for implementing this invention analyzes a user's profile, interests, and current situation to generate and display personalized advertisements. Specific embodiments are described below.

[0136] System Configuration

[0137] The system consists of the following main components:

[0138] 1. User device: The device used by the user, such as a smartphone or computer.

[0139] 2. Server: The central system that collects data, analyzes it, and generates advertisements.

[0140] 3. Database: Stores data such as user profiles, social media posts, purchase history, and search history.

[0141] Hardware and software used

[0142] Hardware: smartphones, PCs, servers

[0143] Software: Python, database management system (e.g., MySQL), API (SNS data, weather data, etc.)

[0144] Data collection and analysis

[0145] The server collects users' social media posts, purchase history, and search history. This data is obtained through APIs and stored in a database. The server then analyzes this data to understand users' interests and preferences.

[0146] Considering the current situation

[0147] The server obtains current information about the season, weather, local environmental issues, etc. This data is also collected in real time through APIs and stored in a database.

[0148] Ad generation and display

[0149] The server uses a generative AI model to generate optimal ads for users based on the collected user data and current situation data, and these ads are then displayed on the user's device.

[0150] Specific examples

[0151] For example, if a user posts on social media that they "love traveling" and recently purchased a "camera," an ad will be displayed on a sunny spring day saying, "Check out our travel guidebooks perfect for spring!"

[0152] Prompt Sentence Examples

[0153] "Generate ads that are best suited to users based on their social media posts, purchase history, and search history, taking into account the current season, weather, and local information."

[0154] In this way, it is possible to comprehensively analyze a variety of user data and simultaneously provide personalized advertising and environmentally friendly information.

[0155] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0156] Step 1:

[0157] The server collects users' social media posts, purchase history, and search history. This data is obtained through APIs and stored in a database. The input is the user's social media posts, purchase history, and search history, and the output is the user data stored in the database. Specifically, the server sends requests to each API and stores the obtained data in the database.

[0158] Step 2:

[0159] The server analyzes the user data stored in the database to understand the user's interests and preferences. The input is the user data stored in the database, and the output is the analysis results regarding the user's interests and preferences. Specifically, the server uses a data analysis algorithm to analyze the user data and extract the interests and preferences.

[0160] Step 3:

[0161] The server obtains current information such as the season, weather, and local environmental issues. This data is also collected in real time through APIs and stored in a database. The input is data on the season, weather, and local environmental issues, and the output is the current situation data stored in the database. Specifically, the server sends requests to each API and stores the obtained data in the database.

[0162] Step 4:

[0163] The server uses a generative AI model to generate the optimal ad for the user based on the collected user data and current situation data. The input is user data and current situation data, and the output is the generated ad. Specifically, the server inputs a prompt sentence into the generative AI model to generate the optimal ad.

[0164] Step 5:

[0165] The server sends the generated advertisement to the user terminal for display. The input is the generated advertisement, and the output is the advertisement displayed on the user terminal. In specific operations, the server sends advertisement data to the user terminal, and the terminal displays it.

[0166] Step 6:

[0167] Users review the ads displayed and take action if necessary. The input is the displayed ad, and the output is the user's action, such as clicking on the ad or purchasing a related product or service.

[0168] Example 2

[0169] Next, a description will be given of Example 2 of Form 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."

[0170] In modern society, achieving a sustainable lifestyle requires specific proposals and guidelines tailored to each individual user. However, existing systems do not adequately provide customized information based on the user's living environment and lifestyle, making it difficult to achieve a sustainable lifestyle.

[0171] 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.

[0172] In this invention, the server includes means for inputting data related to the user's living environment and lifestyle, means for transmitting the input data to the server, means for the server to receive and preprocess the data, means for inputting the preprocessed data into a machine learning model and analyzing it, means for generating suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for transmitting the generated information to the terminal, and means for displaying the information received by the terminal to the user. This makes it possible to provide specific sustainable living suggestions and guidelines for action tailored to the user.

[0173] "Data about the user's living environment and lifestyle" refers to information such as the user's energy consumption in daily life, the home appliances they use, and their recycling habits.

[0174] "Input means" refers to interfaces such as applications or web forms through which users input data about their living environment and lifestyle.

[0175] "Means of sending to the server" refers to the communication protocol and network infrastructure used to send the data entered by the user to the server.

[0176] "Preprocessing means" refers to algorithms and software used to process the data received by the server, such as filling in missing values ​​and normalizing the data.

[0177] "Means for inputting and analyzing machine learning models" refers to software and hardware used to run machine learning algorithms on pre-processed data and analyze user data.

[0178] "Means for generating sustainable living suggestions, recycling methods, and energy-saving tips" refers to algorithms and software that generate specific guidelines and advice for users based on the analysis results of machine learning models.

[0179] "Means for transmitting generated information to the terminal" refers to the communications protocol and network infrastructure used to transmit the server-generated suggestions and hints to the user's terminal.

[0180] "Means for displaying to the user the information received by the terminal" refers to a display or application that visually displays the information received by the user's terminal from the server.

[0181] This invention is a system that collects data on a user's living environment and lifestyle, and provides suggestions for sustainable living, recycling methods, and energy-saving tips. Specific embodiments of this system are described below.

[0182] First, users use a dedicated application or web form to enter data about their living environment and lifestyle, such as their household energy consumption, the appliances they use, and their recycling habits.

[0183] The device then sends the entered data to the server using the HTTPS protocol to ensure data security.

[0184] The server receives the data sent from the device. The received data is converted into a data frame using Pandas. Next, preprocessing such as filling in missing values ​​and normalizing the data is performed. For example, missing values ​​are filled in with the mean value, and numerical data is normalized to the range of 0 to 1.

[0185] The preprocessed data is then fed into a machine learning model generated using Scikit-learn and TensorFlow, which then performs analysis of the user's data for sustainable living, such as analyzing electricity consumption patterns and assessing potential energy savings.

[0186] The server generates personalized recommendations based on the analysis results, such as "By setting the refrigerator temperature appropriately, you can reduce your annual electricity consumption by 10%."

[0187] The generated suggestions and hints are sent from the server to the device, again using the HTTPS protocol to ensure data security.

[0188] The device receives the information from the server and displays it to the user, who can then take specific actions to practice sustainable living based on the information displayed.

[0189] As a concrete example, if a user is interested in "ways to save energy at home," the following prompt sentence can be input into the generative AI model:

[0190] Generate suggestions for energy conservation methods at home based on the user's living environment data.

[0191] Using this prompt, the generative AI model can provide specific energy-saving tips tailored to the user.

[0192] As described above, the present invention is a system that provides suggestions for a sustainable lifestyle based on the user's living environment and lifestyle, and can provide the user with specific guidelines for action.

[0193] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0194] Step 1:

[0195] The user inputs data about their living environment and lifestyle.

[0196] Users use dedicated applications or web forms to enter information such as their household energy consumption, the appliances they use, their recycling habits, etc. The input data can include numerical and textual data.

[0197] Step 2:

[0198] The terminal transmits the input data to the server.

[0199] The terminal sends the data entered by the user to the server in real time using the HTTPS protocol to ensure data security. The input data is sent to the server in JSON format.

[0200] Step 3:

[0201] The server receives the data and performs pre-processing.

[0202] The server receives the data sent from the device. The received data is converted into a data frame using Pandas. Next, preprocessing such as filling in missing values ​​and normalizing the data is performed. For example, missing values ​​are filled in with the mean value, and numerical data is normalized to the range from 0 to 1. As a result of the preprocessing, a clean dataset is obtained.

[0203] Step 4:

[0204] The server inputs the preprocessed data into a machine learning model for analysis.

[0205] The server inputs the preprocessed data into a machine learning model generated using Scikit-learn and TensorFlow. The model then performs analysis on sustainable living based on the user's data. For example, it analyzes electricity consumption patterns and evaluates energy conservation opportunities. As a result of the analysis, specific recommendations are generated for the user.

[0206] Step 5:

[0207] Based on the analysis results, the server generates suggestions for sustainable living, recycling methods, and energy-saving tips.

[0208] The server generates suggestions tailored to the user based on the analysis results of the machine learning model. For example, it generates specific advice such as, "By setting the refrigerator temperature appropriately, you can reduce your annual electricity consumption by 10%." The generated suggestions are saved in text format.

[0209] Step 6:

[0210] The server transmits the generated information to the terminal.

[0211] The server then sends the generated suggestions and hints to the device, again using the HTTPS protocol to ensure data security. The data is sent to the device in JSON format.

[0212] Step 7:

[0213] The terminal displays the received information to the user.

[0214] The device receives the information from the server and displays it to the user, who can then take specific actions to practice sustainable living based on the information displayed. For example, the application's notification function can be used to notify the user of suggestions in real time.

[0215] (Application example 2)

[0216] Next, a description will be given of Application Example 2 of Form 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."

[0217] In modern society, in order to achieve a sustainable lifestyle, it is important for individual consumers to take environmentally conscious actions. However, consumers often do not have enough information to understand what actions have a positive impact on the environment. In addition, there is a lack of means to provide real-time information on environmental considerations while shopping in physical stores, making it difficult for consumers to take appropriate actions immediately.

[0218] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for suggesting ways to minimize environmental impact and specific actions; means for providing environmentally conscious information related to a product when the user scans the product; and means for displaying the provided information on the user's smartphone. This allows consumers to obtain environmentally conscious information in real time while shopping in a physical store, enabling them to immediately take specific actions to achieve a sustainable lifestyle.

[0219] A "user profile" is a collection of data including a user's personal information, interests, behavioral history, etc.

[0220] "Interests" is information about areas or topics that a user is interested in.

[0221] "Current situation" refers to real-time information such as the user's current geographic location, time, and activity status.

[0222] "Analysis results" are data and insights generated based on a user's profile, interests, and current situation.

[0223] "Sustainable living" refers to living in a way that is environmentally friendly, does not waste resources, and is sustainable in the long term.

[0224] "Suggestion" refers to a specific action or option offered to the user.

[0225] A "recycling method" is a specific procedure or method for converting used products or waste into a reusable form.

[0226] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[0227] "Environmental impact" refers to the impact that a user's actions and choices have on the natural environment.

[0228] "Specific actions" are concrete actions or steps that users can actually take.

[0229] "Scanning a product" refers to the act of reading the barcode or QR code (registered trademark) of a product using a smartphone or other device.

[0230] "Environmentally friendly information" refers to environmentally friendly information such as the product's manufacturing process, materials, and recycling methods.

[0231] A "smartphone" is a type of mobile phone that can connect to the Internet and use applications.

[0232] The system for implementing this invention analyzes a user's profile, interests, and current situation, and provides suggestions for sustainable living, recycling methods, and energy-saving tips. Specific embodiments of this system are described below.

[0233] First, a dedicated application is installed on the user's smartphone. This application has a function that allows the user to scan products. When the user scans a product in a physical store, the product ID is sent to the server.

[0234] The server, built using the Flask framework, receives a product ID and then calls an external API to retrieve relevant eco-friendly information about that product, such as the product's manufacturing process, materials, and recycling methods. The retrieved information is then customized based on the user's profile, interests, and current situation.

[0235] The customized information is then displayed in real time on the user's smartphone, giving them specific advice on how to take environmentally friendly actions in the moment.

[0236] The required hardware is a smartphone, and the required software is Flask (a Python web framework) and requests (a Python library for sending HTTP requests).

[0237] For example, if a user scans an "eco bag" in a physical store, tips on how to recycle the bag and how to save energy will be displayed. For example, "This eco bag is made from recycled materials. After use, it can be reused by bringing it to a designated recycling center. By using this eco bag, you can reduce the use of approximately 50 plastic bags per year."

[0238] Examples of prompts to input to a generative AI model include:

[0239] "Create an app that, when a user scans an item, provides eco-friendly information related to that item. For example, if a user scans an eco-bag, it displays tips on how to recycle the bag and how to save energy."

[0240] In this way, users can be provided with information about sustainable living through their physical shopping experience.

[0241] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0242] Step 1:

[0243] A user scans an item in a physical store. The user uses the smartphone camera to read the barcode or QR code of the item. The input is the product ID, which is sent to the application as the output.

[0244] Step 2:

[0245] The device (smartphone) sends the acquired product ID to the server. An HTTP request containing the product ID as input is generated. The product ID is sent to the server as output.

[0246] Step 3:

[0247] The server calls an external API based on the received product ID to obtain environmentally friendly information related to that product. An API request containing the product ID is generated as input, and the environmentally friendly information is obtained as output.

[0248] Step 4:

[0249] The server customizes the acquired environmentally conscious information based on the user's profile, interests, and current situation. The environmentally conscious information and the user's profile data are used as input. The customized environmentally conscious information is generated as output.

[0250] Step 5:

[0251] The server sends the customized environmentally conscious information to the device (smartphone). An HTTP response is generated that includes the customized environmentally conscious information as input. The environmentally conscious information is sent to the device as output.

[0252] Step 6:

[0253] The terminal (smartphone) displays the received environmentally conscious information to the user. The customized environmentally conscious information is used as input. The environmentally conscious information is displayed on the smartphone screen as output.

[0254] Step 7:

[0255] The user takes sustainable actions based on the displayed environmentally friendly information. The displayed information is used as input. The output prompts the user to take specific actions.

[0256] Example 3

[0257] Next, a third embodiment of the third embodiment will be described. 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."

[0258] Conventional systems do not adequately provide information on environmentally friendly products and services that are tailored to users' interests and preferences. In addition, they lack the functionality to customize information based on user feedback, making it difficult to provide useful and attractive information to users.

[0259] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0260] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for receiving search keywords entered by the user and collecting information on related environmentally friendly products and services, means for displaying the collected information to the user, and means for receiving user feedback and reflecting it in future information provision. This makes it possible to provide information on environmentally friendly products and services tailored to the user's interests and preferences, thereby providing useful and attractive information to the user.

[0261] A "user profile" is a collection of data including a user's personal information, interests, preferences, behavioral history, etc.

[0262] "Interests" refers to specific areas, topics, products, services, etc. that a user is interested in.

[0263] "Current situation" refers to information such as the user's current geographic location, time, environmental conditions, and device used.

[0264] "Means of analysis" refers to algorithms and software used to analyze a user's profile, interests, and current situation and extract relevant information.

[0265] "Sustainable Living Suggestions" refers to specific advice and information to promote environmentally friendly lifestyles and behaviors.

[0266] "Recycling method" refers to the specific procedures and methods for reusing used products and waste materials.

[0267] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[0268] "Methods of minimizing environmental impact" refers to specific actions and measures to reduce the burden on the environment.

[0269] "Specific actions" refer to concrete actions or steps that users can actually take.

[0270] "Search keywords" refer to words or phrases that users enter to search for information that interests them.

[0271] "Environmentally friendly products and services" refers to products and services designed to reduce the burden on the environment.

[0272] "Means of collecting information" refers to the algorithms and software used to obtain the required information from databases and external sources.

[0273] "Means for displaying information" refers to the interface or device used to visually present collected information to the user.

[0274] "Feedback" refers to ratings and comments made by users on information provided.

[0275] "Means of receiving feedback" refers to algorithms or software used to collect ratings and comments from users.

[0276] "Means of reflecting this in information provision" refers to algorithms and software that analyze the collected feedback and use it in future information provision.

[0277] The present invention is a system that provides users with information about environmentally friendly products and services and customizes the information based on user feedback. A specific embodiment of this system is described below.

[0278] System Overview

[0279] The system consists of three main components: the server, the terminal, and the user. The server collects, analyzes, and processes data and feedback. The terminal receives input from the user and displays information from the server. The user searches for information and provides feedback through the terminal.

[0280] Hardware and software used

[0281] Server: Use a cloud service (e.g., Amazon Web Services, Google (registered trademark) Cloud Platform).

[0282] Database: Use a relational database such as AWS (registered trademark) RDS (Relational Database Service).

[0283] Machine learning models: Learn user preferences using TensorFlow and PyTorch.

[0284] Device: Use iOS or ANDROID (registered trademark) mobile applications or a web browser.

[0285] Program processing

[0286] The server receives the search keywords entered by the user and collects information on related environmentally friendly products and services from a database. The collected information is sent to the device in JSON format. The device displays the received information to the user. The user provides feedback on the displayed information. The device then sends the user's feedback to the server. The server analyzes the received feedback and reflects it in future information provision.

[0287] Specific examples

[0288] For example, consider a case where a user is interested in "eco bags." When the user types "eco bags" into the device's search bar, the device sends this keyword to the server. The server uses AWS RDS to search a database and collects information on environmentally friendly products related to "eco bags." The collected information is sent to the device in JSON format. The device displays the information to the user using a list view or card view. When the user provides feedback such as "this eco bag has a nice design," the device sends this feedback to the server. The server uses TensorFlow to analyze the feedback and reflect it in future information provision.

[0289] Prompt Sentence Examples

[0290] An example of a prompt to input to a generative AI model is as follows:

[0291] When a user searches for "eco bag," provide them with relevant eco-friendly eco-bag information and customize future offers based on their feedback.

[0292] In this way, the user can learn about environmentally friendly products and services that match his or her interests and preferences. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0293] Step 1:

[0294] The user enters a search keyword.

[0295] Users enter keywords for products or services they are interested in into the device's search bar, for example, "eco bag." The entered keywords are temporarily stored in the device's memory.

[0296] Step 2:

[0297] The device sends the search keywords to the server.

[0298] The device sends the search keywords entered by the user to the server using an HTTP request. The input data is packaged in JSON format and sent to the server's API endpoint. The output is the search keywords received by the server.

[0299] Step 3:

[0300] The server collects information on related environmentally friendly products and services.

[0301] The server searches the database based on the received search keywords to collect information on related environmentally friendly products and services. Specifically, it executes a database query using AWS RDS. The input is the search keyword, and the output is a list of related information.

[0302] Step 4:

[0303] The server sends the collected information to the terminal.

[0304] The server sends the collected information to the terminal as an HTTP response in JSON format. The input is a list of related information, and the output is the JSON data received by the terminal.

[0305] Step 5:

[0306] The device displays the information to the user.

[0307] The device parses the information received from the server and displays it visually to the user. For example, in the case of a mobile app, it might display the information using a list view or card view. The input is JSON data, and the output is the information displayed to the user.

[0308] Step 6:

[0309] Users provide feedback on the information.

[0310] The user provides feedback on the displayed information. For example, they can comment, "This eco bag has a good design." The input is the user's feedback, and the output is the feedback data stored on the device.

[0311] Step 7:

[0312] The device sends the feedback to the server.

[0313] The terminal sends user feedback to the server using an HTTP request. The input is the feedback data, and the output is the feedback data received by the server.

[0314] Step 8:

[0315] The server will analyze the feedback and reflect it in future information provision.

[0316] The server analyzes the received feedback. Specifically, it uses TensorFlow to train a machine learning model to learn the user's preferences. The input is the feedback data, and the output is an updated machine learning model. From then on, the content and format of the information provided to the user are adjusted.

[0317] (Application example 3)

[0318] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0319] Today's consumers are increasingly conscious of choosing environmentally friendly products and services, but they often do not know what products are environmentally friendly or how to obtain that information. Furthermore, because the information provided is uniform, it may not match the interests or preferences of individual users. Furthermore, there is a lack of a mechanism for customizing information based on user feedback, making it difficult to provide useful and attractive information to users.

[0320] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for presenting methods and specific actions for minimizing environmental impact; means for recommending environmentally friendly products related to the product the user is viewing; means for improving the recommendation algorithm based on user feedback; and means for providing customized information on environmentally friendly products. This allows users to easily obtain information on environmentally friendly products and services that match their interests and preferences, and enables the provision of customized information that reflects their feedback.

[0321] A "user profile" is a collection of data including a user's personal information, interests, preferences, behavioral history, etc.

[0322] "Interests" refers to information about products, services, topics, etc. that a user is interested in.

[0323] "Current situation" refers to the environment or condition in which the user is placed, such as location, time of day, season, etc.

[0324] "Means of analysis" refers to methods and technologies used to analyze collected data and identify users' interests, preferences, and behavioral patterns.

[0325] "Sustainable Living Suggestions" is information that provides specific advice and methods for living an environmentally conscious life.

[0326] "Recycling methods" are specific procedures and methods for reusing used products and waste materials.

[0327] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[0328] "Means of providing information" refers to methods and technologies for conveying necessary information to users in an appropriate format.

[0329] "Methods of minimizing environmental impact" are specific actions or measures taken to reduce the burden on the environment.

[0330] "Means of suggesting specific actions" are methods or techniques that provide users with a specific action plan that they can actually take.

[0331] "Environmentally friendly products" are products designed to minimize the burden on the environment at each stage of production, use, and disposal.

[0332] "Recommendation methods" are methods and technologies for selecting and presenting appropriate products and services based on the user's interests and preferences.

[0333] "Feedback" refers to the evaluation or opinion a user gives of the information provided or the recommended products.

[0334] A "recommendation algorithm" is a calculation method or program for selecting the most suitable products or services based on user data.

[0335] "Customized information" is information that is tailored to a user's individual interests, preferences, and behavioral patterns.

[0336] The system for implementing this invention includes a plurality of means for analyzing a user's profile, interests, and current situation, and providing information on environmentally friendly products and services. Specific embodiments are described below.

[0337] System Configuration

[0338] 1. Data collection methods:

[0339] The server collects your profile, interests, and current situation, including your browsing history, purchase history, and location information.

[0340] Hardware used: Smartphone

[0341] Software used: Firebase (database), Google Analytics (user behavior tracking)

[0342] 2. Data analysis methods:

[0343] The server analyzes the collected data to identify the user's interests and preferences.

[0344] Software used: Python, Pandas, Scikit-learn (machine learning library)

[0345] 3. Recommendation Algorithm:

[0346] The server runs an algorithm to recommend environmentally friendly products related to the product the user is viewing.

[0347] Software used: TensorFlow (deep learning library)

[0348] 4. Feedback collection methods:

[0349] The server collects user feedback and improves the recommendation algorithm.

[0350] Software used: Firebase (database), Python

[0351] 5. Information provision method:

[0352] The server provides the user with customized information on environmentally friendly products.

[0353] Software used: React Native (mobile app development framework)

[0354] Processing flow

[0355] 1. Data Collection:

[0356] When users browse online shopping sites using their smartphones, user behavior data is collected using Firebase and Google Analytics.

[0357] 2. Data Analysis:

[0358] The server analyzes the collected data using Python and Pandas to identify users' interests and preferences.

[0359] 3. Run the recommendation algorithm:

[0360] Using TensorFlow, we recommend environmentally friendly products related to the product the user is viewing.

[0361] 4. Gathering feedback and improving the algorithm:

[0362] When users provide feedback on recommended products, the data is stored in Firebase and used to improve the recommendation algorithm using Python.

[0363] 5. Information provision:

[0364] Using React Native, customized information about environmentally friendly products is provided to users.

[0365] Specific examples

[0366] For example, if a user browses for "plastic water bottles," the system will recommend "stainless steel reusable water bottles." If the user purchases a "reusable water bottle," the system will recommend related products such as "reusable straws" and "eco bags" the next time the user browses.

[0367] Prompt Sentence Examples

[0368] An example of a prompt for the generative AI model is as follows:

[0369] Recommend eco-friendly products related to the product the user is browsing. Consider the user's past browsing and purchase history to choose the most suitable products.

[0370] In this way, a system can be realized that provides users with useful and attractive information about environmentally friendly products.

[0371] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0372] Step 1:

[0373] When a user browses an online shopping site using a smartphone, the device collects user behavior data using Firebase and Google Analytics. Specifically, data such as the products the user viewed, the links they clicked, and the length of time they spent on the site is collected in real time and stored in the Firebase database. The input is user behavior data, and the output is the behavior data stored in Firebase.

[0374] Step 2:

[0375] The server periodically retrieves user behavior data stored in Firebase and analyzes it using Python and Pandas. Specifically, it processes the data to identify the user's interests and preferences based on the user's browsing history and purchase history. The input is the behavioral data retrieved from Firebase, and the output is the analysis results that identify the user's interests and preferences.

[0376] Step 3:

[0377] The server uses TensorFlow to run an algorithm that recommends environmentally friendly products related to the product the user is viewing. Specifically, based on the analysis results, the server selects the most suitable environmentally friendly products for the user and generates a recommendation list. The input is the analysis results, and the output is the recommendation list.

[0378] Step 4:

[0379] When a user provides feedback on a recommended product, the device stores that feedback data in Firebase. Specifically, the user enters ratings and comments such as "good" or "bad" and sends them to Firebase. The input is the user's feedback data, and the output is the feedback data stored in Firebase.

[0380] Step 5:

[0381] The server retrieves the feedback data stored in Firebase and uses Python to improve the recommendation algorithm. Specifically, it analyzes the feedback data and adjusts the parameters of the recommendation algorithm to improve the accuracy of the next recommendation. The input is the feedback data, and the output is an improved recommendation algorithm.

[0382] Step 6:

[0383] The server uses React Native to provide users with customized information about environmentally friendly products. Specifically, it displays appropriate product information on the user's smartphone based on the recommendation list. The input is the recommendation list, and the output is the product information displayed on the user's smartphone.

[0384] In this way, a system can be realized that provides users with useful and attractive information about environmentally friendly products.

[0385] 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.

[0386] "Example 1"

[0387] One embodiment of the present invention is a system that incorporates an emotion engine that recognizes a user's emotions. This system analyzes the user's profile, interests, and current situation, and based on the analysis results, provides information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips. Furthermore, the emotion engine recognizes the user's emotions and provides information and suggestions based on those emotions. For example, if the system recognizes that the user is feeling stressed, it may suggest relaxing ambient music or eco-friendly activities that are believed to help relieve stress.

[0388] "Example 2"

[0389] Another embodiment of the present invention is a system for providing information on environmentally friendly products and services. This system recognizes the user's emotions and suggests products and services that correspond to those emotions. For example, if the system recognizes that the user is feeling joy, it suggests eco-friendly products and services that may further enhance that joy.

[0390] "Example 3"

[0391] Furthermore, a system for customizing information provided to a user is also an embodiment of the present invention. This system recognizes the user's emotions and adjusts the way information is provided depending on the emotions. For example, if it recognizes that the user is feeling depressed, it customizes the information provided to take into account the user's emotional state, such as by emphasizing positive information.

[0392] The processing flow of each embodiment will be described below.

[0393] "Example 1"

[0394] Step 1: Analyze the user's profile, interests, and current situation.

[0395] Step 2: Recognize the user's emotions using the emotion engine.

[0396] Step 3: Based on the analysis and emotion recognition results, provide suggestions for sustainable living, recycling methods, energy-saving tips, etc.

[0397] Step 4: If the system recognizes that the user is feeling stressed, it will suggest relaxing ambient music or eco-friendly activities that are believed to help relieve stress.

[0398] "Example 2"

[0399] Step 1: Recognize the user's emotions.

[0400] Step 2: Provide information about eco-friendly products and services that correspond to the user's emotions. Step 3: If it is recognized that the user is feeling joy, suggest eco-friendly products and services that may further amplify that joy.

[0401] "Example 3"

[0402] Step 1: Recognize the user's emotions.

[0403] Step 2: Tailor the information you provide to the user based on their emotions.

[0404] Step 3: If the system detects that the user is feeling down, it will customize the experience to take into account the user's emotional state, such as by emphasizing positive information.

[0405] Example 1

[0406] Next, a description will be given of Example 1 of Form 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."

[0407] Conventional systems were not able to analyze users' profiles, interests, and current situations, nor were they able to recognize their emotions and provide information and suggestions based on those emotions. Furthermore, they lacked the ability to generate messages to users using generative AI models, making it difficult to provide more personalized information to users. This led to problems such as a decline in user satisfaction and engagement.

[0408] 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.

[0409] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for recognizing the user's emotions, means for providing information and suggestions according to the user's emotions based on the emotion recognition results, and means for generating messages to be provided to the user using a generative AI model. This makes it possible to provide personalized information according to the user's emotions and interests.

[0410] A "user profile" is data that includes a user's personal information, interests, preferences, behavioral history, etc.

[0411] "Interests" are information related to topics or areas that interest a user.

[0412] "Current situation" refers to information about the environment and conditions in which the user finds themselves, such as the season, weather, and local environmental issues.

[0413] "Means of analysis" are methods and tools used to analyze collected data and understand user profiles, interests, and current situations.

[0414] "Sustainable Living Suggestions" are advice and information to encourage environmentally conscious lifestyles and behaviors.

[0415] "Recycling methods" are specific procedures and methods for reusing used products and waste materials.

[0416] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[0417] "Methods of minimizing environmental impact" are specific actions or measures taken to reduce the burden on the environment.

[0418] "Means of providing specific actions" is a way to provide a specific action plan that users can actually take.

[0419] "Means of recognizing emotions" are technologies and tools for analyzing and understanding a user's emotional state.

[0420] "Emotion recognition result" is data on the user's emotional state obtained by emotion recognition means.

[0421] A "generative AI model" is an algorithm or program that uses artificial intelligence to generate text or information.

[0422] "Means for generating a message" refers to a method for creating a message to be provided to a user using a generative AI model.

[0423] This invention is a system that analyzes a user's profile, interests, and current situation to make suggestions for sustainable living. The system has the ability to recognize the user's emotions and provide information and suggestions according to those emotions. It also uses a generative AI model to generate messages to be provided to the user.

[0424] Hardware and software used

[0425] Hardware: Servers, terminals (PCs, smartphones)

[0426] Software: emotion engines, data analysis tools (e.g., Python pandas, scikit-learn), generative AI models (e.g., GPT-4®)

[0427] Data collection

[0428] The server collects data such as the user's social media posts, purchase history, and search history. For example, it uses the Twitter API to collect the user's tweets and obtains their Amazon purchase history via the API. The device obtains current weather information based on the user's location. For example, it obtains current weather data using the OpenWeatherMap API.

[0429] Data analysis

[0430] The server analyzes the collected data using Python's pandas and scikit-learn. It analyzes social media posts using text analysis tools (e.g., NLTK) to understand the user's interests and preferences. It analyzes purchase history to identify the product categories the user recently purchased. It evaluates the user's living environment based on current weather data and seasonal information.

[0431] emotion recognition

[0432] The server uses an emotion engine to analyze emotions from users' social media posts. For example, if a user's post contains keywords such as "tired" or "stressed," it determines that the user is feeling stressed. Based on the results of the emotion engine, the server records the user's emotional state in a database.

[0433] Information provision

[0434] The server generates optimal suggestions for the user based on the results of data analysis and emotion recognition. It uses a generative AI model (e.g., GPT-4) to generate a message to provide to the user. For example, it generates a message such as, "We recommend a playlist of relaxing ambient music." The device notifies the user of the generated message. For example, it sends the suggestion to the user using a smartphone push notification.

[0435] Specific examples

[0436] Example 1: When a user posts on social media that they've been feeling stressed lately

[0437] The server retrieves the user's latest tweets using the Twitter API. It uses an emotion engine to determine whether the tweets indicate "stress." It then uses a generative AI model (e.g., GPT-4) to generate a message such as "We recommend a playlist of relaxing ambient music." The device then sends the generated message to the user via a push notification on their smartphone.

[0438] Example 2: When a user searches for "interested in eco-activities"

[0439] The server analyzes the user's search history and identifies keywords related to "eco-activities." Using a generative AI model (e.g., GPT-4), it generates a message such as, "Want to know about local environmental issues? Here are some easy eco-activities you can start." The device then sends the generated message to the user via a push notification on their smartphone.

[0440] Prompt Sentence Examples

[0441] "If the user is feeling stressed, generate a message suggesting relaxing ambient music."

[0442] "If a user is interested in eco-friendly activities, generate a message that provides information about local environmental issues and suggests easy eco-friendly activities to start."

[0443] The above is an embodiment of the present invention.

[0444] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0445] Step 1: Data collection

[0446] The server collects data such as the user's social media posts, purchase history, and search history. Specifically, it retrieves the user's tweets using the Twitter API and their Amazon purchase history via an API. The device obtains current weather information based on the user's location information. For example, it obtains current weather data using the OpenWeatherMap API.

[0447] Input: User's social media account information, online shopping site account information, location information

[0448] Output: SNS posting data, purchase history data, weather data

[0449] Step 2: Data analysis

[0450] The server analyzes the collected data using Python's pandas and scikit-learn. It analyzes social media posts using text analysis tools (e.g., NLTK) to understand the user's interests and preferences. It analyzes purchase history to identify the product categories the user recently purchased. It evaluates the user's living environment based on current weather data and seasonal information.

[0451] Input: SNS posting data, purchase history data, weather data

[0452] Output: User interest and preference data, product category data, living environment data

[0453] Step 3: Emotion Recognition

[0454] The server uses an emotion engine to analyze emotions from users' social media posts. For example, if a user's post contains keywords such as "tired" or "stressed," it determines that the user is feeling stressed. Based on the results of the emotion engine, the server records the user's emotional state in a database.

[0455] Input: SNS post data

[0456] Output: User emotion data

[0457] Step 4: Provide information

[0458] The server generates optimal suggestions for the user based on the results of data analysis and emotion recognition. It uses a generative AI model (e.g., GPT-4) to generate a message to provide to the user. For example, it generates a message such as, "We recommend a playlist of relaxing ambient music." The device notifies the user of the generated message. For example, it sends the suggestion to the user using a smartphone push notification.

[0459] Input: User interest and preference data, product category data, living environment data, user emotion data

[0460] Output: The message to provide to the user

[0461] Specific examples of operation

[0462] Example 1: When a user posts on social media that they've been feeling stressed lately

[0463] Step 1: The server uses the Twitter API to retrieve the user's latest tweets.

[0464] Input: User's SNS account information

[0465] Output: SNS post data

[0466] Step 2: The server analyzes the collected social media posting data using a text analysis tool (e.g., NLTK) to understand the user's interests and preferences.

[0467] Input: SNS post data

[0468] Output: User interest and preference data

[0469] Step 3: The server uses an emotion engine to determine that the tweet content indicates "stress."

[0470] Input: SNS post data

[0471] Output: User emotion data

[0472] Step 4: The server uses a generative AI model (e.g., GPT-4) to generate a message such as, "We recommend a playlist of relaxing ambient music." The device then sends the generated message to the user via a push notification on their smartphone.

[0473] Input: User interest and preference data, user emotional data

[0474] Output: The message to provide to the user

[0475] Example 2: When a user searches for "interested in eco-activities"

[0476] Step 1: The server analyzes the user's search history and identifies keywords related to "eco-activities."

[0477] Input: User search history data

[0478] Output: User interest and preference data

[0479] Step 2: The server analyzes the collected search history data to understand the user's interests and preferences.

[0480] Input: Search history data

[0481] Output: User interest and preference data

[0482] Step 3: The server uses the emotion engine to analyze the user's emotional state.

[0483] Input: Search history data

[0484] Output: User emotion data

[0485] Step 4: The server uses a generative AI model (e.g., GPT-4) to generate a message such as, "Want to know about local environmental issues? Here are some easy eco-friendly activities you can start." The device then sends the generated message to the user via a push notification on their smartphone.

[0486] Input: User interest and preference data, user emotional data

[0487] Output: The message to provide to the user

[0488] (Application example 1)

[0489] Next, a description will be given of Application Example 1 of Embodiment 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."

[0490] Previous sustainable living recommendation systems were limited to analyzing users' profiles, interests, and current situations, and had the problem of not being able to respond to individual needs such as user emotions or recommending eco-friendly products in physical stores. They also lacked the functionality to suggest appropriate relaxation methods when users were feeling stressed. This could result in a decrease in user satisfaction and contribution to sustainable living.

[0491] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for presenting methods for minimizing environmental impact and specific actions; means for recognizing the user's emotions and providing information and suggestions based on those emotions; means for recommending eco-friendly and recyclable products in physical stores; and means for suggesting relaxing ambient music when the user is feeling stressed. This makes it possible to respond to individual needs, such as user emotions and eco-friendly product recommendations in physical stores, and improve user satisfaction and contribution to sustainable living.

[0492] A "user profile" is a collection of data that includes a user's personal information, interests, preferences, past behavioral history, etc.

[0493] "Interests" refers to the topics, fields, activities, etc. that a user is interested in.

[0494] "Current situation" refers to the environment or conditions in which the user finds themselves, such as the season, weather, local environmental issues, etc.

[0495] "Sustainable living" refers to living in a way that is environmentally friendly, does not waste resources, and is sustainable in the long term.

[0496] "Recycling method" refers to the specific procedures and methods for reusing used products and materials.

[0497] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[0498] "Methods of minimizing environmental impact" refers to specific measures and actions taken to reduce the burden on the environment.

[0499] "Emotion recognition" refers to determining a user's emotional state from their facial expressions, behavior, input data, etc.

[0500] "Brick and mortar store" refers to a commercial establishment or retail outlet that exists in a physical location.

[0501] "Eco products" refer to products made using environmentally friendly materials and manufacturing methods.

[0502] "Recyclable products" refer to products that can be reused or reprocessed after use.

[0503] "Relaxing ambient music" refers to music that has a relaxing effect when listened to.

[0504] The system for implementing this invention analyzes a user's profile, interests, and current situation to provide suggestions for sustainable living, recycling methods, and energy-saving tips. It also has the ability to recognize the user's emotions and provide information and suggestions based on those emotions. It also recommends eco-friendly and recyclable products in physical stores, and suggests relaxing ambient music when the user is feeling stressed.

[0505] Hardware and software used

[0506] Hardware: Smartphone

[0507] Software: Python, EmotionRecognizer library, Weather API, Product Recommendation system

[0508] Data processing and calculation

[0509] User profile analysis

[0510] The server obtains the user's profile, interests, purchase history, and location information, and takes into account the current weather and season, allowing for a comprehensive analysis of the user's interests and current situation.

[0511] emotion recognition

[0512] The server uses the EmotionRecognizer library to recognize emotions from the user's input data, which allows it to determine whether the user is feeling stressed and make appropriate suggestions.

[0513] Proposal generation

[0514] The server generates relaxing ambient music and eco-friendly activities based on the recognized emotions. For example, if the user is feeling stressed, the server will suggest relaxing ambient music.

[0515] Eco-friendly product recommendations

[0516] The server recommends eco-friendly and recyclable products in physical stores based on the user's interests and current situation, allowing the user to choose specific products that will help them practice sustainable living.

[0517] Specific examples

[0518] User Interest

[0519] The user is interested in "sustainability" and "recycling." The current weather is "sunny" and the season is "spring." The user is "stressed."

[0520] Prompt Sentence Examples

[0521] The user is interested in "sustainability" and "recycling." The current weather is "sunny" and the season is "spring." The user is feeling "stressed." Please suggest some relaxing ambient music. Also, please recommend some eco-friendly products.

[0522] In this way, it is possible to create a system that comprehensively analyzes a user's profile, interests, current situation, and emotions, and provides suggestions for sustainable living, recycling methods, and energy-saving tips.

[0523] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0524] Step 1:

[0525] The server retrieves the user's profile, interests, purchase history, and location information, including personal information provided by the user and past behavioral data. The inputs include the user's ID, location, and past purchase history, and the output is a comprehensive profile of the user.

[0526] Step 2:

[0527] The server calls the Weather API to take into account the current weather and season based on the profile data it has acquired. The input is the user's location information, and the output is the current weather and season information.

[0528] Step 3:

[0529] The server uses the EmotionRecognizer library to recognize emotions from user input data. The input is the user's text and voice data, and the output is the user's emotional state (e.g., stressed, relaxed).

[0530] Step 4:

[0531] The server generates relaxing ambient music and eco-activities suggestions based on the recognized emotions. The input is the user's emotional state, and the output is links to relaxing music and eco-activities suggestions.

[0532] Step 5:

[0533] The server recommends eco-friendly and recyclable products in physical stores based on the user's interests and current situation. The inputs are the user's interests, weather information, and seasonal information, and the output is a list of eco-friendly and recyclable products.

[0534] Step 6:

[0535] The terminal displays the suggestions and recommended products received from the server to the user. The input is the suggestion data and product list from the server, and the output is the information displayed on the user's screen.

[0536] Step 7:

[0537] The user checks the displayed suggestions and product list, and makes a selection or purchase as necessary. The input is the information displayed on the terminal, and the output is the user's selection and purchase data.

[0538] Step 8:

[0539] The server then updates the user's profile with their selections and purchase data, and uses this data for future suggestions and recommendations. The input is the user's selections and purchase data, and the output is an updated user profile.

[0540] Example 2

[0541] Next, a description will be given of Example 2 of Form 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."

[0542] In modern society, achieving a sustainable lifestyle requires specific proposals and guidelines for action tailored to each individual user. However, conventional systems have difficulty providing customized information based on a user's living environment and lifestyle, and have not suggested products or services that reflect the user's emotions. This has made it difficult for users to take concrete actions to practice a sustainable lifestyle.

[0543] 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.

[0544] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for recognizing the user's emotions and suggesting products and services based on those emotions, means for collecting information about the user's living environment and lifestyle and generating suggestions for sustainable living based on the information, means for analyzing the user's facial expressions and tone of voice to identify emotions, means for integrating and analyzing the collected data and generating optimal suggestions for the user, means for providing the generated suggestions to the user, and means for collecting user feedback and improving the accuracy of the system. This makes it possible to provide customized information based on the user's living environment and lifestyle, and to suggest products and services based on the user's emotions.

[0545] "User profile" refers to data such as a user's personal information, interests, preferences, living environment, and lifestyle.

[0546] "Means of analysis" refers to the methods and techniques used to analyze collected data and understand user characteristics and needs.

[0547] "Sustainable Living Suggestions" refers to specific advice and information to promote environmentally friendly lifestyles and behaviors.

[0548] "Recycling methods" refer to specific steps or methods for converting waste into a reusable form.

[0549] "Energy saving tips" refers to specific advice or methods for reducing energy consumption.

[0550] "Means of providing information" refers to the methods and techniques used to communicate analysis results and recommendations to users.

[0551] "Methods of minimizing environmental impact" refers to specific actions and measures taken to reduce the burden on the environment.

[0552] "Means of suggesting specific actions" refers to methods or technologies that provide specific instructions or advice for users to actually take action.

[0553] "Means for recognizing emotions" refers to methods and technologies for identifying emotions by analyzing a user's facial expressions and tone of voice.

[0554] "Means for suggesting products and services" refers to methods and technologies for recommending appropriate products and services based on the user's needs and emotions.

[0555] "Means of collecting information about living environment and lifestyle" refers to methods and technologies for collecting data about a user's living environment and lifestyle.

[0556] "Means for generating proposals" refers to methods and technologies for creating optimal proposals for users based on collected data.

[0557] "Means for analyzing facial expressions and tone of voice" refers to methods and technologies for analyzing a user's facial expressions and tone of voice using a camera or microphone.

[0558] "Means for integrating and analyzing data" refers to methods and technologies for integrating information collected from multiple data sources and analyzing it comprehensively.

[0559] "Means for providing suggestions" refers to the methods and techniques used to communicate generated suggestions to users.

[0560] "Feedback collection methods" refers to methods and techniques for collecting opinions and ratings from users.

[0561] "Means for improving the accuracy of the system" refers to methods and techniques for improving the performance and accuracy of the system based on the collected feedback.

[0562] This invention is a system that provides sustainable living suggestions, recycling methods, and energy-saving tips based on the user's living environment and lifestyle. It also has the function of recognizing the user's emotions and suggesting environmentally friendly products and services according to those emotions.

[0563] Hardware and software used

[0564] Hardware

[0565] Device: The device used by the user, such as a smartphone, computer, or tablet.

[0566] Camera: A device for capturing the user's facial expressions.

[0567] Microphone: A device used to collect the tone of a user's voice.

[0568] software

[0569] Data analysis software: Python

[0570] Machine learning frameworks: TensorFlow, PyTorch

[0571] Emotion recognition software: OpenCV, Google Cloud Vision API

[0572] Program processing

[0573] Data collection

[0574] Users access the system using a terminal and input information about their living environment and lifestyle, such as answering questions like, "Where do you live?" and "How much energy do you usually consume?"

[0575] emotion recognition

[0576] The device uses a camera and microphone to capture the user's facial expressions and tone of voice, allowing the system to analyze the user's emotions in real time. For example, if the user is smiling while speaking, the system will recognize that the user is happy.

[0577] Data analysis

[0578] The server integrates and analyzes the collected data. It uses Python for data analysis and TensorFlow and PyTorch for machine learning model execution. For example, if a user is interested in recycling, the server will research the recycling rules in the user's area and suggest specific recycling methods.

[0579] Proposal generation

[0580] The server generates sustainable living recommendations based on the analysis, including specific information like, "In your area, plastics can be recycled every Tuesday."

[0581] Providing suggestions

[0582] The server provides the generated suggestions to the user, who then displays the suggestions as notifications on their device.

[0583] Feedback collection

[0584] The user receives suggestions provided by the server, tries them out, and provides feedback on whether the suggestions were useful or not, which is used to improve the accuracy of the system.

[0585] Examples and prompts

[0586] For example, if the user is interested in "energy saving," the following specific actions will be taken:

[0587] 1. A user accesses the system and types in, "I want information about energy conservation."

[0588] 2. Your device uses the camera and microphone to collect your facial expressions and tone of voice.

[0589] 3. The server analyzes the collected data to ensure that users are interested in saving energy.

[0590] 4. The server generates and provides "home energy-saving tips" to the user, including specific advice such as "Replacing light bulbs with LEDs can save approximately 20% of energy per year."

[0591] 5. The user receives the suggestions, tries out the LED bulbs, and provides feedback on whether the suggestions were helpful.

[0592] Example prompt sentence:

[0593] "How do I recycle in my area?"

[0594] "Please tell me some tips on how to save energy at home."

[0595] Please tell me some eco-friendly products.

[0596] "I'm looking for an eco-friendly service."

[0597] In this way, the system provides users with information to make their lives more sustainable.

[0598] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0599] Step 1:

[0600] A user accesses the system and inputs information about their living environment and lifestyle.

[0601] Input: Questions about the user's living environment and lifestyle (e.g., "Where do you live?", "How much energy do you usually consume?")

[0602] Output: User response data

[0603] Specific operation: Users access the system using a device such as a smartphone or PC and answer the questions displayed. The answer data is sent to the server.

[0604] Step 2:

[0605] The device uses a camera and microphone to collect data to recognize the user's emotions.

[0606] Input: User's facial expression and tone of voice

[0607] Output: Emotion recognition data

[0608] How it works: The device captures the user's facial expressions with a camera and collects the user's tone of voice with a microphone. These data are analyzed in real time and sent to the server as emotion recognition data.

[0609] Step 3:

[0610] The server analyzes the collected data and generates optimal sustainable living recommendations for the user.

[0611] Input: User response data, emotion recognition data

[0612] Output: Sustainable living suggestions

[0613] Specific operation: The server analyzes data using Python and runs machine learning models using TensorFlow and PyTorch. For example, if a user is interested in recycling, the server will research the recycling rules in the user's area and suggest specific recycling methods.

[0614] Step 4:

[0615] The server provides the generated suggestions to the user.

[0616] Input: Sustainable Living Proposals

[0617] Output: User notification

[0618] Specific behavior: The server sends the generated suggestions to the user's device as notifications, containing specific information such as "In your area, plastics can be recycled every Tuesday."

[0619] Step 5:

[0620] The user receives the suggestions and provides feedback if necessary.

[0621] Input: User feedback

[0622] Output: Feedback data

[0623] Specific behavior: The user receives suggestions provided by the server, tries them out, and provides feedback on whether the suggestions were useful. The feedback data is sent to the server and used to improve the accuracy of the system.

[0624] (Application example 2)

[0625] Next, a description will be given of Application Example 2 of Form 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."

[0626] While conventional sustainable living recommendation systems provide information based on a user's profile and interests, they are unable to take user emotions into account when making recommendations, resulting in low user satisfaction and engagement. Furthermore, there was no system that could recognize a user's emotions in real time using a smartphone's camera and microphone and make recommendations accordingly.

[0627] 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.

[0628] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for recognizing the user's emotions and suggesting products and services based on those emotions, means for analyzing the user's facial expressions and voice using the smartphone's camera and microphone, means for predicting the user's emotions using an emotion recognition model, means for generating suggestions for sustainable living and information on eco-friendly products based on the predicted emotions, and means for displaying the generated suggestions and information to the user. This makes it possible to provide suggestions for sustainable living and information on eco-friendly products based on the user's emotions.

[0629] A "user profile" is data that includes a user's personal information, interests, preferences, behavioral history, etc.

[0630] "Interests" are areas or topics that a user is interested in.

[0631] "Current situation" refers to the environment or state in which the user is located, such as location information or activity status.

[0632] "Analysis results" refers to information and data obtained based on a user's profile, interests, and current situation.

[0633] "Sustainable living" refers to a lifestyle that is environmentally friendly, does not waste resources, and is sustainable in the long term.

[0634] A "suggestion" is a presentation of specific actions or options to the user.

[0635] "Recycling methods" refer to specific means and procedures for reusing used products and waste materials.

[0636] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[0637] "Environmental impact" refers to the effects or consequences of a user's actions or choices on the environment.

[0638] A "specific action" is a concrete action that a user can actually take.

[0639] "Emotion" refers to the user's psychological state or mood.

[0640] "Goods and Services" means any products or services offered that are available for purchase or use by Users.

[0641] A "smartphone camera" refers to the camera device built into a smartphone.

[0642] A "microphone" is a device used to record sound.

[0643] "Facial expressions" refer to the user's facial movements and expressions.

[0644] "Voice" refers to the sound produced by the user.

[0645] An "emotion recognition model" is a machine learning model that predicts emotions from a user's facial expressions and voice.

[0646] "Prediction" is the estimation of future conditions or outcomes based on data.

[0647] "Eco-friendly products" are products that are manufactured with consideration for the environment.

[0648] "Generating information" means creating new information based on data.

[0649] "Displaying" means providing information visually to the user.

[0650] The system for implementing this invention analyzes a user's profile, interests, and current situation to provide suggestions for sustainable living, recycling methods, and energy-saving tips. It also has the ability to recognize a user's emotions and suggest products and services that correspond to those emotions.

[0651] Hardware and software used

[0652] Hardware: Smartphone camera and microphone

[0653] Software: OpenCV, Keras, emotion recognition model

[0654] Data processing and calculation

[0655] 1. User profile analysis:

[0656] The server collects and analyzes the user's profile, interests, and current situation. The profile includes the user's personal information, interests, preferences, and behavioral history.

[0657] 2. Emotion recognition:

[0658] It uses the smartphone's camera and microphone to capture the user's facial expressions and voice in real time, performs face detection using OpenCV, and predicts the user's emotions using an emotion recognition model loaded in Keras.

[0659] 3. Proposal generation:

[0660] Based on the predicted emotions, the system generates suggestions for sustainable living and eco-friendly products. For example, if the user is feeling joy, it will suggest eco-friendly products that will amplify that emotion.

[0661] 4. Display information:

[0662] The generated suggestions and information are displayed on the smartphone screen, allowing users to get real-time information on sustainable living.

[0663] Specific examples

[0664] For example, when a user uses their smartphone camera, the app analyzes their facial expressions and, if it detects that they are happy, it will display a suggestion such as, "Check out our eco-friendly products!"

[0665] Prompt Sentence Examples

[0666] "Create an application that analyzes the user's facial expressions and suggests eco-friendly products if they show signs of happiness."

[0667] In this way, it becomes possible to provide suggestions for sustainable living and information on eco-friendly products that correspond to the user's emotions.

[0668] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0669] Step 1:

[0670] The server collects the user's profile, interests, and current situation. The input includes the user's personal information, interests, preferences, and behavioral history. Based on this data, the server generates a user profile and performs analysis. The output is the user's profile information.

[0671] Step 2:

[0672] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice in real time. The input includes camera footage and audio data. This data is then subjected to face detection using OpenCV and audio data is collected. The output is facial position information and audio data.

[0673] Step 3:

[0674] The server inputs the face-detected image data into the emotion recognition model loaded in Keras to predict the user's emotion. The input includes face location information and image data. The emotion recognition model is used to predict the user's emotion. The output is the predicted emotion information.

[0675] Step 4:

[0676] The server generates sustainable living suggestions and eco-friendly product information based on the predicted emotion information and the user's profile information. The input includes emotion information and profile information. Based on this data, a generative AI model is used to generate suggestions. The output is the recommendation information.

[0677] Step 5:

[0678] The terminal displays the generated recommendation information on the smartphone screen.,The recommendation information is included as input.,It is displayed on the smartphone display to provide it to the user visually.,As output, the user can obtain information on sustainable living in,real time.

[0679] Step 6:

[0680] The user selects an action based on the displayed suggestion information. The input includes the displayed suggestion information. The user uses this information to select a specific action related to sustainable living. The output is the user's action.

[0681] Example 3

[0682] Next, a third embodiment of the third embodiment will be described. 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."

[0683] Conventional information provision systems lacked sufficient customization based on the user's interests and emotional state, making it difficult to provide optimal information to the user. Furthermore, there was a lack of effective means to provide information on environmentally friendly products and services, making it difficult for users to take concrete action to achieve sustainable lifestyles.

[0684] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes: means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for suggesting ways to minimize environmental impact and specific actions; means for providing information on environmentally friendly products and services related to the user's interests; means for adjusting the content and format of the information to be provided based on the user's feedback and emotional state; means for generating information in natural language using a generative AI model; and means for recognizing the user's emotional state using emotion recognition software. This makes it possible to provide optimal information according to the user's interests and emotions, thereby promoting specific actions for achieving sustainable living.

[0685] A "user profile" is data that includes a user's personal information, interests, preferences, past behavioral history, etc.

[0686] "Interests" refers to information about products, services, topics, etc. that a user is interested in.

[0687] "Current situation" refers to data that refers to the user's current environment or state, such as location information or activity status.

[0688] "Means of analysis" refers to technologies and methods for analyzing a user's profile, interests, and current situation and extracting relevant information.

[0689] "Sustainable Living Suggestions" is information that provides specific advice and methods for living an environmentally conscious life.

[0690] "Recycling methods" refers to information that indicates specific procedures and methods for reusing waste materials.

[0691] "Energy saving tips" are information that provides specific advice and methods for reducing energy consumption.

[0692] "Methods for minimizing environmental impact" refers to information that points to specific actions and measures for reducing the burden on the environment.

[0693] "Means of suggesting specific actions" are techniques or methods that provide specific instructions or methods that allow users to actually take action.

[0694] "Environmentally friendly products and services" are products and services that aim to reduce the burden on the environment.

[0695] "Feedback" is data that refers to the evaluations and opinions that users give about the information provided.

[0696] "Emotional state" refers to information that indicates the user's current emotions and mood.

[0697] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate information in natural language.

[0698] "Emotion recognition software" is software that analyzes and recognizes emotions from a user's text or voice.

[0699] This invention is a system that provides and customizes information about environmentally friendly products and services based on the user's interests and emotional state. This system is realized using a server, a terminal, a generative AI model, and emotion recognition software.

[0700] Hardware and software used

[0701] Hardware: Servers, user devices (PCs, smartphones, tablets, etc.)

[0702] Software: generative AI models (e.g., GPT-4), emotion recognition software, database management systems (e.g., MySQL)

[0703] Specific operation of the system

[0704] Collecting user interest information

[0705] User: Enters information about a product or service they are interested in into the device, such as keywords like "eco-friendly detergent" or "eco-friendly travel plans."

[0706] Terminal: Receives information entered by the user and sends it to the server.

[0707] Server: Stores the received information in a database, specifically by associating the user ID with keywords of interest.

[0708] Providing information on environmentally friendly products

[0709] Server: Searches a database for information on environmentally friendly products and services related to the user's interests. For example, retrieves a list of products related to "eco-friendly detergents."

[0710] Generative AI model: Generates easy-to-understand explanations for users based on search results. The prompt is "If the user is looking for an eco-friendly detergent, please describe the features of this detergent."

[0711] Terminal: Display the generated information to the user, for example, "This detergent is highly biodegradable and made with environmentally friendly ingredients."

[0712] Collecting user feedback

[0713] Users: Enter feedback on the information provided, such as "This information was helpful" or "I'd like more information."

[0714] Terminal: Receives user feedback and sends it to the server.

[0715] Server: Saves the feedback in a database. Specifically, it associates the user ID with the feedback content and saves it.

[0716] Customize your information

[0717] Server: Analyzes user feedback and past responses. For example, if a user requests more information, the server prepares to provide more information in response to that request.

[0718] Emotion recognition software: Recognizes the emotional state of a user, for example by using text analysis to read emotions from user comments.

[0719] Generative AI model: Adjusts the content and format of the information provided depending on the user's emotional state. The prompt used is "If the user is perceived as depressed, please provide positive information with emphasis."

[0720] On the device: Show customized information to the user. For example, if the device detects that the user is feeling depressed, it will emphasize positive messages such as "Using this detergent will help protect the environment."

[0721] Examples of concrete examples and prompts

[0722] Examples:

[0723] User: I'm looking for an eco-friendly cleaner.

[0724] Server: Searches the database for information about environmentally friendly detergents and generates descriptions using a generative AI model.

[0725] Terminal: Display "This detergent is highly biodegradable and made with environmentally friendly ingredients."

[0726] User: Enters feedback saying "This information was helpful."

[0727] Server: Your feedback will be saved and used for future updates.

[0728] Example prompt sentence:

[0729] "If a user is looking for an eco-friendly cleaner, explain the features of that cleaner."

[0730] "If you perceive a user as depressed, highlight and provide positive information."

[0731] In this way, the system provides and customizes information on environmentally friendly products and services according to the user's interests and emotions. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0732] Step 1: Collecting user interests

[0733] User: Enters information about a product or service they are interested in into the device, such as keywords like "eco-friendly detergent" or "eco-friendly travel plans."

[0734] Input: The keyword entered by the user.

[0735] Terminal: Receives information entered by the user and sends it to the server.

[0736] Output: User interest information sent to the server.

[0737] What it does: The device receives user input in real time, formats it, and sends it to the server.

[0738] Step 2: Providing information about environmentally friendly products

[0739] Server: Searches a database for information on environmentally friendly products and services related to the user's interests. For example, retrieves a list of products related to "eco-friendly detergents."

[0740] Input: User interests.

[0741] Data processing: Perform database queries and extract relevant product information.

[0742] Generative AI model: Generates easy-to-understand explanations for users based on search results. The prompt is "If the user is looking for an eco-friendly detergent, please describe the features of this detergent."

[0743] Output: The generated description.

[0744] Specific operation: The server inputs information obtained from the database into the generative AI model and generates an explanation in natural language.

[0745] Step 3: View the generated information

[0746] Terminal: Display the generated information to the user, for example, "This detergent is highly biodegradable and made with environmentally friendly ingredients."

[0747] Input: The generated description.

[0748] Output: Information displayed to the user.

[0749] Specific operation: The device displays the generated explanation received from the server on the user interface.

[0750] Step 4: Gather user feedback

[0751] Users: Enter feedback on the information provided, such as "This information was helpful" or "I'd like more information."

[0752] Input: User feedback.

[0753] Terminal: Receives user feedback and sends it to the server.

[0754] Output: Feedback information sent to the server.

[0755] What it does: The device receives user feedback in real time, formats it, and sends it to the server.

[0756] Step 5: Store and analyze feedback

[0757] Server: Stores the feedback in a database and analyzes the user's feedback and past responses. For example, if a user requests more information, the server prepares to provide more information in response to the request.

[0758] Input: User feedback.

[0759] Data processing: The feedback information is stored in a database and analytical algorithms are applied.

[0760] Output: Analysis results.

[0761] What it does: The server stores the feedback and uses analytical algorithms to analyze user requests and trends.

[0762] Step 6: Emotion recognition and information customization

[0763] Emotion recognition software: Recognizes the emotional state of a user, for example by using text analysis to read emotions from user comments.

[0764] Input: User feedback.

[0765] Data processing: Emotion recognition through text analysis.

[0766] Generative AI model: Adjusts the content and format of the information provided depending on the user's emotional state. The prompt used is "If the user is perceived as depressed, please provide positive information with emphasis."

[0767] Output: Customized information.

[0768] How it works: Emotion recognition software analyzes the feedback, and the generative AI model customizes the information based on the results.

[0769] Step 7: Displaying customized information

[0770] On the device: Show customized information to the user. For example, if the device detects that the user is feeling depressed, it will emphasize positive messages such as "Using this detergent will help protect the environment."

[0771] Input: Customized information.

[0772] Output: Customized information that is displayed to the user.

[0773] Specific operation: The terminal displays the customized information received from the server on the user interface.

[0774] In this way, the system provides and customizes information about environmentally friendly products and services according to the user's interests and emotions.

[0775] (Application example 3)

[0776] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0777] Conventional information provision systems do not take into account the user's emotions or past behavioral history, making it difficult to provide optimal information for the user. Furthermore, there is a lack of information on environmentally friendly products and services, making it difficult for users to take concrete actions to achieve a sustainable lifestyle. Furthermore, because information is not provided according to the user's emotional state, there is also the issue of not being able to increase user satisfaction.

[0778] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes: means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for suggesting ways to minimize environmental impact and specific actions; means for recognizing the user's emotions and adjusting the information provision method based on those emotions; means for recommending environmentally friendly products and services; and means for customizing information based on the user's past purchase history, browsing history, and feedback. This enables the provision of optimal information taking into account the user's emotions and past behavioral history, making it easier for the user to take specific actions to achieve a sustainable lifestyle. Furthermore, since information is provided according to the user's emotional state, user satisfaction can be increased.

[0779] A "user profile" is a collection of data including a user's personal information, interests, preferences, behavioral history, etc.

[0780] "Interests" are specific areas or topics that a user is interested in.

[0781] "Current situation" refers to the environment or state in which the user is located, such as location information or activity status.

[0782] "Sustainable living" refers to living in a way that is environmentally friendly, does not waste resources, and is sustainable in the long term.

[0783] A "suggestion" is the provision of information to the user to suggest actions or options.

[0784] "Recycling methods" refer to specific procedures and methods for reusing used products and materials.

[0785] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[0786] "Environmental impact" refers to the impact that a user's actions and choices have on the natural environment.

[0787] A "specific action" is a concrete action that a user can actually take.

[0788] "Emotion recognition" means determining a user's emotional state from their facial expressions and behavior.

[0789] "Adjusting the way information is provided" means changing the content and format of the information provided depending on the user's emotions and situation.

[0790] "Environmentally friendly products and services" are products and services designed to minimize the burden on the environment.

[0791] "Recommending" means recommending a particular product or service to a user.

[0792] "Past purchase history" refers to a record of products or services previously purchased by a user.

[0793] "Browsing history" refers to a record of web pages and product information that a user has viewed in the past.

[0794] "Feedback" refers to opinions and evaluations from users.

[0795] "Customize" means tailoring information or services to a user's individual needs and preferences.

[0796] The system for implementing this invention analyzes a user's profile, interests, and current situation to provide suggestions for sustainable living, recycling methods, energy-saving tips, etc. It also has the ability to recognize a user's emotions and adjust the information delivery method based on those emotions. It also recommends environmentally friendly products and services and customizes the information based on the user's past purchase history, browsing history, and feedback.

[0797] Hardware and software used

[0798] Hardware: Smartphone (camera, processor)

[0799] Software: Python, TensorFlow, JSON

[0800] Data processing and calculation

[0801] 1. Emotion recognition:

[0802] It takes a picture of the user's face using a smartphone camera and uses a TensorFlow model to recognize emotions.

[0803] The emotion recognition model determines emotions from the user's facial expressions and outputs the results.

[0804] 2. Load user data:

[0805] Read the user's past purchase history and browsing history from a JSON file.

[0806] Based on the data read, the user's interests and preferences are analyzed.

[0807] 3. Recommending environmentally friendly products:

[0808] Recommend environmentally friendly products and services based on user data.

[0809] Use recommendation algorithms to select the best products and services for users.

[0810] 4. Customization of information provided:

[0811] Adjust the content and format of the information you provide depending on the emotions you recognize.

[0812] For example, if a user is feeling down, provide them with positive information.

[0813] Specific examples

[0814] Users open the "Eco Shopping Assistant" app on their smartphone and take a photo of their face. The app recognizes the user's emotions and recommends eco-friendly products based on their past purchase history. If the user is feeling down, it will highlight positive information.

[0815] Prompt Sentence Examples

[0816] Users open the "Eco Shopping Assistant" app on their smartphone and take a photo of their face. The app recognizes the user's emotions and recommends eco-friendly products based on their past purchase history. If the user is feeling down, it will highlight positive information.

[0817] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0818] Step 1:

[0819] A user launches the "Eco Shopping Assistant" app on their smartphone and takes a picture of their face with the camera. The input is the user's face image, and the output is facial image data. This facial image data is input into the emotion recognition model.

[0820] Step 2:

[0821] The server receives the facial image data and uses a TensorFlow model to recognize emotions. The input is the facial image data, and the output is the user's emotional state (e.g., joy, sadness, surprise, etc.). The emotion recognition model extracts features from the facial image and classifies the emotion.

[0822] Step 3:

[0823] The server adjusts the information presentation method based on the user's emotional state. The input is the user's emotional state, and the output is the adjusted information presentation method. For example, if the user is feeling depressed, it is set to emphasize positive information.

[0824] Step 4:

[0825] The server reads the user's past purchase history and browsing history from a JSON file. The input is the user ID, and the output is the user's past purchase history and browsing history data. This data is used to analyze the user's interests and preferences.

[0826] Step 5:

[0827] The server recommends eco-friendly products and services based on the user's past purchase history and browsing history. The input is the user's past purchase history and browsing history data, and the output is a list of recommended eco-friendly products and services. A recommendation algorithm is used to select the most suitable products and services for the user.

[0828] Step 6:

[0829] The server provides users with tailored information delivery methods and recommended products and services. The input is the tailored information delivery method and a list of recommended products and services, and the output is the information displayed to the user. Based on the provided information, users can take specific actions to achieve sustainable living.

[0830] Step 7:

[0831] The user provides feedback on the provided information. The input is the user's feedback, and the output is feedback data. This feedback data is used to customize future information provision.

[0832] 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.

[0833] 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> ) 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.

[0834] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0835] 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.

[0836] [Second embodiment]

[0837] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0838] 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.

[0839] 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).

[0840] 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.

[0841] 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.

[0842] 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).

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0849] "Example 1"

[0850] The present invention is a system that uses AI. This system has a means for analyzing a user's profile, interests, and current situation. For example, the system analyzes the user's social media posts, purchase history, search history, etc. to understand the user's interests and preferences. The system also takes into account the user's current situation, such as the season, weather, and local environmental issues.

[0851] "Example 2"

[0852] Next, based on the analysis results, the system has the means to provide information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips. For example, it can make environmentally conscious suggestions related to the user's areas of interest. It can also provide recycling methods and energy-saving tips that are suited to the user's living environment and lifestyle.

[0853] "Example 3"

[0854] Furthermore, the site has a means for providing information on environmentally friendly products and services. For example, it provides information on environmentally friendly products and services related to products and services that the user is interested in. This allows the user to learn about environmentally friendly products and services that match their interests and preferences.

[0855] "Example 4"

[0856] Finally, it has the means to customize the information provided to users, for example, by adjusting the content and format of the information provided based on user reactions and feedback, thereby making it possible to provide more useful and attractive information to users.

[0857] The processing flow of each embodiment will be described below.

[0858] "Example 1"

[0859] Step 1: The system collects the user's social media posts, purchase history, search history, etc.

[0860] Step 2: Based on the collected data, AI analyzes the user's profile, interests, and current situation.

[0861] Step 3: Based on the analysis results, provide users with suggestions for sustainable living, recycling methods, energy-saving tips, etc.

[0862] "Example 2"

[0863] Step 1: The system makes environmentally friendly suggestions related to the user's interests and preferences.

[0864] Step 2: Provide users with recycling and energy-saving tips tailored to their living environment and lifestyle.

[0865] "Example 3"

[0866] Step 1: The system provides information on environmentally friendly products and services related to the products and services in which the user is interested.

[0867] "Example 4"

[0868] Step 1: The system collects user responses and feedback.

[0869] Step 2: Adjust the content and format of the information you provide based on the responses and feedback you receive.

[0870] Example 1

[0871] Next, a description will be given of Example 1 of Form 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."

[0872] Conventional systems struggled to provide information that fully took into account the user's profile, interests, and current situation, making it impossible to provide optimal recommendations for each individual user. Furthermore, there was a lack of effective methods for providing concrete actions to minimize environmental impact and suggestions for sustainable living.

[0873] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for presenting methods and specific actions for minimizing environmental impact; means for collecting and preprocessing user data and analyzing the user's interests and preferences; means for acquiring current situation data from an external data source; means for generating a response to the user using a generative AI model; and means for providing the generated response to the user. This makes it possible to make optimal suggestions taking into account the user's interests and current situation.

[0874] A "user profile" is a collection of data including a user's personal information, interests, preferences, behavioral history, etc.

[0875] "Interests" refers to the topics, activities, hobbies, etc. that a user is interested in.

[0876] "Current situation" refers to the environment or conditions in which the user finds themselves, such as the season, weather, or specific local conditions.

[0877] "Means of analysis" refers to methods and technologies for analyzing a user's profile, interests, and current situation and extracting meaningful information.

[0878] "Sustainable Living Suggestions" refers to specific advice and information to promote environmentally friendly lifestyles and behaviors.

[0879] "Recycling methods" refer to specific steps or methods for converting waste into a reusable form.

[0880] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[0881] "Methods of minimizing environmental impact" refers to specific actions and measures taken to reduce the burden on the environment.

[0882] "Means of suggesting specific actions" refers to techniques and methods for suggesting actions or methods that can be taken by users.

[0883] "Means of collecting data" refers to the methods and technologies used to obtain data about user behavior and interests.

[0884] "Preprocessing means" refers to methods and techniques for preparing collected data in a form that is easy to analyze.

[0885] "Interest and preference analysis means" refers to methods and technologies used to identify users' interests and preferences.

[0886] "External data sources" refers to external information sources used to understand the user's current situation.

[0887] A "generative AI model" refers to a model that uses artificial intelligence to generate responses and suggestions for users.

[0888] "Response generation means" refers to the technology or method for creating an appropriate response based on the user's profile and current situation.

[0889] "Means for providing a response" refers to the method or technology used to communicate the generated response to the user.

[0890] MODE FOR CARRYING OUT THE INVENTION

[0891] This invention is a system that analyzes a user's profile, interests, and current situation, and provides suggestions for sustainable living, recycling methods, energy-saving tips, etc. Specific embodiments of this system are described below.

[0892] Hardware and software used

[0893] The server uses the following hardware and software for data collection, pre-processing, analysis, and response generation:

[0894] Hardware: High-performance server (e.g., Intel Xeon processor, 32GB RAM or more)

[0895] Software: Python programming language, TensorFlow, PyTorch, NLTK, spaCy, MySQL or MongoDB, external APIs (e.g., OpenWeatherMap API)

[0896] The terminal uses the following hardware and software to receive input from the user and display responses from the server:

[0897] Hardware: Smartphones, tablets, computers

[0898] Software: web browser, mobile application

[0899] Data collection and preprocessing

[0900] The server collects data such as users' social media posts, purchase history, search history, etc. This includes retrieving data from social media platforms and e-commerce sites through APIs. For example, it uses the Twitter API to retrieve users' tweets and the Amazon API to collect purchase history.

[0901] The collected data is preprocessed by cleaning the text data (removing unnecessary characters and symbols), tokenizing it (splitting it into words and phrases), and removing stop words. This is done using natural language processing libraries such as NLTK and spaCy.

[0902] Analysis of user interests and preferences

[0903] The server analyzes the user's interests and preferences based on the preprocessed data. Specifically, it uses machine learning models (e.g., TF-IDF, Word2Vec) to identify the user's interests. The results of this analysis are stored in a database as a user profile.

[0904] Get current status data

[0905] The server retrieves data from external APIs (e.g., OpenWeatherMap API) to take into account the user's current situation (season, weather, local environmental issues, etc.), thereby providing real-time weather information and local specific conditions.

[0906] Response generation using generative AI models

[0907] The server generates appropriate responses using a generative AI model (e.g., GPT-3, BERT) based on the user's profile data and current situation data. The generative AI model takes these data as input and generates optimal suggestions and answers for the user.

[0908] Providing a response

[0909] The device displays the responses received from the server to the user, who can then review the suggestions and answers and ask further questions if necessary.

[0910] Examples of concrete examples and prompts

[0911] As a concrete example, consider a case where a user asks, "What outdoor activities are recommended for this weekend?" The server understands the user's outdoor interests from their past search history and social media posts, and retrieves current weather data. For example, if the weather is sunny, it will suggest hiking or a picnic.

[0912] Example prompt sentence:

[0913] User profile data:

[0914] Social media post: "I went hiking recently. It was so much fun!"

[0915] Purchase history: "Purchase outdoor equipment"

[0916] Search history: "Hiking trails near me"

[0917] Current weather data:

[0918] Region: Tokyo

[0919] Weather: Sunny

[0920] Prompt for the generative AI model:

[0921] "User is interested in outdoor activities and the weather is sunny right now. Can you suggest some outdoor activities for this weekend?"

[0922] In this way, the system makes appropriate suggestions that take into account the user's interests and current situation.

[0923] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0924] Step 1: Collect user data

[0925] The server collects data such as users' social media posts, purchase history, and search history. Specifically, it obtains data from social media platforms and e-commerce sites through APIs. For example, it uses the Twitter API to obtain users' tweets and the e-commerce site's API to collect purchase history. The input is the user's account information, and the output is the collected raw data.

[0926] Step 2: Preprocessing the data

[0927] The server preprocesses the collected data. Specifically, it cleans the text data (removes unnecessary characters and symbols), tokenizes it (divides it into words and phrases), and removes stop words. This is done using natural language processing libraries such as NLTK and spaCy. The input is the collected raw data, and the output is the preprocessed, clean data.

[0928] Step 3: Analyzing user interests and preferences

[0929] The server analyzes the user's interests and preferences based on the preprocessed data. Specifically, it uses machine learning models (e.g., TF-IDF, Word2Vec) to identify the user's interests. The results of this analysis are stored in a database as a user profile. The input is the preprocessed, clean data, and the output is profile data that indicates the user's interests and preferences.

[0930] Step 4: Get current situation data

[0931] The server retrieves data from external APIs (e.g., OpenWeatherMap API) to take into account the user's current situation (season, weather, local environmental issues, etc.), thereby understanding real-time weather information and local specific conditions. The input is the user's location, and the output is current situation data.

[0932] Step 5: Generative AI model generates a response

[0933] The server generates an appropriate response using a generative AI model (e.g., GPT-3, BERT) based on the user's profile data and current situation data. The generative AI model takes these data as input and generates optimal suggestions or answers for the user. The input is the user profile data and current situation data, and the output is the generated response.

[0934] Step 6: Providing a response

[0935] The terminal displays the responses received from the server to the user, who can then review the suggestions and answers and ask further questions if necessary. The input is the response generated, and the output is the information displayed to the user.

[0936] (Application example 1)

[0937] Next, a description will be given of Application Example 1 of Form 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."

[0938] In modern society, providing personalized advertisements based on users' interests and preferences is important, but conventional systems have difficulty generating advertisements that fully consider the user's profile and current situation. There is also a need to simultaneously provide environmentally friendly information and suggestions for sustainable living, but there is a lack of efficient ways to achieve this. Furthermore, a system is needed that can comprehensively analyze a variety of data, such as users' social media posts, purchase history, and search history, to generate optimal advertisements.

[0939] 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.

[0940] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for analyzing the user's social media posts, purchase history, and search history to understand the user's interests and preferences, and means for generating and displaying advertisements that are optimal for the user, taking into account current conditions such as the season, weather, and local environmental issues. This makes it possible to comprehensively analyze a variety of user data and simultaneously provide personalized advertisements and environmentally friendly information.

[0941] A "user profile" is a collection of data including a user's personal information, behavioral history, interests, preferences, etc.

[0942] "Interests" refer to the things or areas in which a user is interested.

[0943] "Current situation" includes the environment and conditions in which the user finds himself, such as the season, weather, and local environmental issues.

[0944] "Means of analysis" refers to methods and technologies for analyzing a user's profile, interests, and current situation and extracting relevant information.

[0945] "Sustainable Living Advice" means providing advice and information to promote environmentally friendly lifestyles and behaviours.

[0946] "Recycling method" refers to the specific procedures and methods for reusing used products and waste materials.

[0947] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[0948] "Methods of minimizing environmental impact" refers to specific measures and actions taken to reduce the burden on the environment.

[0949] "Means of presenting specific actions" refers to methods or techniques that show users specific actions they can actually take.

[0950] "SNS posts" refer to comments, photos, videos, etc. posted by users on social networking services.

[0951] "Purchase history" refers to a record of products and services a user has purchased in the past.

[0952] "Search history" refers to a record of searches a user has conducted on the Internet.

[0953] "Season" refers to the changes in weather that occur throughout the year.

[0954] "Weather" refers to the weather conditions in a particular area and at a particular time.

[0955] "Regional environmental issues" refers to environmental challenges and problems in a particular region.

[0956] "Means for generating and displaying advertisements" refers to methods and technologies for creating and displaying advertisements that are optimal for the user based on the user's interests and current situation.

[0957] A system for implementing this invention analyzes a user's profile, interests, and current situation to generate and display personalized advertisements. Specific embodiments are described below.

[0958] System Configuration

[0959] The system consists of the following main components:

[0960] 1. User device: The device used by the user, such as a smartphone or computer.

[0961] 2. Server: The central system that collects data, analyzes it, and generates advertisements.

[0962] 3. Database: Stores data such as user profiles, social media posts, purchase history, and search history.

[0963] Hardware and software used

[0964] Hardware: smartphones, PCs, servers

[0965] Software: Python, database management system (e.g., MySQL), API (SNS data, weather data, etc.)

[0966] Data collection and analysis

[0967] The server collects users' social media posts, purchase history, and search history. This data is obtained through APIs and stored in a database. The server then analyzes this data to understand users' interests and preferences.

[0968] Considering the current situation

[0969] The server obtains current information about the season, weather, local environmental issues, etc. This data is also collected in real time through APIs and stored in a database.

[0970] Ad generation and display

[0971] The server uses a generative AI model to generate optimal ads for users based on the collected user data and current situation data, and these ads are then displayed on the user's device.

[0972] Specific examples

[0973] For example, if a user posts on social media that they "love traveling" and recently purchased a "camera," an ad will be displayed on a sunny spring day saying, "Check out our travel guidebooks perfect for spring!"

[0974] Prompt Sentence Examples

[0975] "Generate ads that are best suited to users based on their social media posts, purchase history, and search history, taking into account the current season, weather, and local information."

[0976] In this way, it is possible to comprehensively analyze a variety of user data and simultaneously provide personalized advertising and environmentally friendly information.

[0977] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0978] Step 1:

[0979] The server collects users' social media posts, purchase history, and search history. This data is obtained through APIs and stored in a database. The input is the user's social media posts, purchase history, and search history, and the output is the user data stored in the database. Specifically, the server sends requests to each API and stores the obtained data in the database.

[0980] Step 2:

[0981] The server analyzes the user data stored in the database to understand the user's interests and preferences. The input is the user data stored in the database, and the output is the analysis results regarding the user's interests and preferences. Specifically, the server uses a data analysis algorithm to analyze the user data and extract the interests and preferences.

[0982] Step 3:

[0983] The server obtains current information such as the season, weather, and local environmental issues. This data is also collected in real time through APIs and stored in a database. The input is data on the season, weather, and local environmental issues, and the output is the current situation data stored in the database. Specifically, the server sends requests to each API and stores the obtained data in the database.

[0984] Step 4:

[0985] The server uses a generative AI model to generate the optimal ad for the user based on the collected user data and current situation data. The input is user data and current situation data, and the output is the generated ad. Specifically, the server inputs a prompt sentence into the generative AI model to generate the optimal ad.

[0986] Step 5:

[0987] The server sends the generated advertisement to the user terminal for display. The input is the generated advertisement, and the output is the advertisement displayed on the user terminal. In specific operations, the server sends advertisement data to the user terminal, and the terminal displays it.

[0988] Step 6:

[0989] Users review the ads displayed and take action if necessary. The input is the displayed ad, and the output is the user's action, such as clicking on the ad or purchasing a related product or service.

[0990] Example 2

[0991] Next, a description will be given of Example 2 of Form 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."

[0992] In modern society, achieving a sustainable lifestyle requires specific proposals and guidelines tailored to each individual user. However, existing systems do not adequately provide customized information based on the user's living environment and lifestyle, making it difficult to achieve a sustainable lifestyle.

[0993] 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.

[0994] In this invention, the server includes means for inputting data related to the user's living environment and lifestyle, means for transmitting the input data to the server, means for the server to receive and preprocess the data, means for inputting the preprocessed data into a machine learning model and analyzing it, means for generating suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for transmitting the generated information to the terminal, and means for displaying the information received by the terminal to the user. This makes it possible to provide specific sustainable living suggestions and guidelines for action tailored to the user.

[0995] "Data about the user's living environment and lifestyle" refers to information such as the user's energy consumption in daily life, the home appliances they use, and their recycling habits.

[0996] "Input means" refers to interfaces such as applications or web forms through which users input data about their living environment and lifestyle.

[0997] "Means of sending to the server" refers to the communication protocol and network infrastructure used to send the data entered by the user to the server.

[0998] "Preprocessing means" refers to algorithms and software used to process the data received by the server, such as filling in missing values ​​and normalizing the data.

[0999] "Means for inputting and analyzing machine learning models" refers to software and hardware used to run machine learning algorithms on pre-processed data and analyze user data.

[1000] "Means for generating sustainable living suggestions, recycling methods, and energy-saving tips" refers to algorithms and software that generate specific guidelines and advice for users based on the analysis results of machine learning models.

[1001] "Means for transmitting generated information to the terminal" refers to the communications protocol and network infrastructure used to transmit the server-generated suggestions and hints to the user's terminal.

[1002] "Means for displaying to the user the information received by the terminal" refers to a display or application that visually displays the information received by the user's terminal from the server.

[1003] This invention is a system that collects data on a user's living environment and lifestyle, and provides suggestions for sustainable living, recycling methods, and energy-saving tips. Specific embodiments of this system are described below.

[1004] First, users use a dedicated application or web form to enter data about their living environment and lifestyle, such as their household energy consumption, the appliances they use, and their recycling habits.

[1005] The device then sends the entered data to the server using the HTTPS protocol to ensure data security.

[1006] The server receives the data sent from the device. The received data is converted into a data frame using Pandas. Next, preprocessing such as filling in missing values ​​and normalizing the data is performed. For example, missing values ​​are filled in with the mean value, and numerical data is normalized to the range of 0 to 1.

[1007] The preprocessed data is then fed into a machine learning model generated using Scikit-learn and TensorFlow, which then performs analysis of the user's data for sustainable living, such as analyzing electricity consumption patterns and assessing potential energy savings.

[1008] The server generates personalized recommendations based on the analysis results, such as "By setting the refrigerator temperature appropriately, you can reduce your annual electricity consumption by 10%."

[1009] The generated suggestions and hints are sent from the server to the device, again using the HTTPS protocol to ensure data security.

[1010] The device receives the information from the server and displays it to the user, who can then take specific actions to practice sustainable living based on the information displayed.

[1011] As a concrete example, if a user is interested in "ways to save energy at home," the following prompt sentence can be input into the generative AI model:

[1012] Generate suggestions for energy conservation methods at home based on the user's living environment data.

[1013] Using this prompt, the generative AI model can provide specific energy-saving tips tailored to the user.

[1014] As described above, the present invention is a system that provides suggestions for a sustainable lifestyle based on the user's living environment and lifestyle, and can provide the user with specific guidelines for action.

[1015] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1016] Step 1:

[1017] The user inputs data about their living environment and lifestyle.

[1018] Users use dedicated applications or web forms to enter information such as their household energy consumption, the appliances they use, their recycling habits, etc. The input data can include numerical and textual data.

[1019] Step 2:

[1020] The terminal transmits the input data to the server.

[1021] The terminal sends the data entered by the user to the server in real time using the HTTPS protocol to ensure data security. The input data is sent to the server in JSON format.

[1022] Step 3:

[1023] The server receives the data and performs pre-processing.

[1024] The server receives the data sent from the device. The received data is converted into a data frame using Pandas. Next, preprocessing such as filling in missing values ​​and normalizing the data is performed. For example, missing values ​​are filled in with the mean value, and numerical data is normalized to the range from 0 to 1. As a result of the preprocessing, a clean dataset is obtained.

[1025] Step 4:

[1026] The server inputs the preprocessed data into a machine learning model for analysis.

[1027] The server inputs the preprocessed data into a machine learning model generated using Scikit-learn and TensorFlow. The model then performs analysis on sustainable living based on the user's data. For example, it analyzes electricity consumption patterns and evaluates energy conservation opportunities. As a result of the analysis, specific recommendations are generated for the user.

[1028] Step 5:

[1029] Based on the analysis results, the server generates suggestions for sustainable living, recycling methods, and energy-saving tips.

[1030] The server generates suggestions tailored to the user based on the analysis results of the machine learning model. For example, it generates specific advice such as, "By setting the refrigerator temperature appropriately, you can reduce your annual electricity consumption by 10%." The generated suggestions are saved in text format.

[1031] Step 6:

[1032] The server transmits the generated information to the terminal.

[1033] The server then sends the generated suggestions and hints to the device, again using the HTTPS protocol to ensure data security. The data is sent to the device in JSON format.

[1034] Step 7:

[1035] The terminal displays the received information to the user.

[1036] The device receives the information from the server and displays it to the user, who can then take specific actions to practice sustainable living based on the information displayed. For example, the application's notification function can be used to notify the user of suggestions in real time.

[1037] (Application example 2)

[1038] Next, a description will be given of Application Example 2 of Form 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."

[1039] In modern society, in order to achieve a sustainable lifestyle, it is important for individual consumers to take environmentally conscious actions. However, consumers often do not have enough information to understand what actions have a positive impact on the environment. In addition, there is a lack of means to provide real-time information on environmental considerations while shopping in physical stores, making it difficult for consumers to take appropriate actions immediately.

[1040] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for suggesting ways to minimize environmental impact and specific actions; means for providing environmentally conscious information related to a product when the user scans the product; and means for displaying the provided information on the user's smartphone. This allows consumers to obtain environmentally conscious information in real time while shopping in a physical store, enabling them to immediately take specific actions to achieve a sustainable lifestyle.

[1041] A "user profile" is a collection of data including a user's personal information, interests, behavioral history, etc.

[1042] "Interests" is information about areas or topics that a user is interested in.

[1043] "Current situation" refers to real-time information such as the user's current geographic location, time, and activity status.

[1044] "Analysis results" are data and insights generated based on a user's profile, interests, and current situation.

[1045] "Sustainable living" refers to living in a way that is environmentally friendly, does not waste resources, and is sustainable in the long term.

[1046] "Suggestion" refers to a specific action or option offered to the user.

[1047] A "recycling method" is a specific procedure or method for converting used products or waste into a reusable form.

[1048] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[1049] "Environmental impact" refers to the impact that a user's actions and choices have on the natural environment.

[1050] "Specific actions" are concrete actions or steps that users can actually take.

[1051] "Scanning an item" refers to the act of using a smartphone or other device to read the barcode or QR code on an item.

[1052] "Environmentally friendly information" refers to environmentally friendly information such as the product's manufacturing process, materials, and recycling methods.

[1053] A "smartphone" is a type of mobile phone that can connect to the Internet and use applications.

[1054] The system for implementing this invention analyzes a user's profile, interests, and current situation, and provides suggestions for sustainable living, recycling methods, and energy-saving tips. Specific embodiments of this system are described below.

[1055] First, a dedicated application is installed on the user's smartphone. This application has a function that allows the user to scan products. When the user scans a product in a physical store, the product ID is sent to the server.

[1056] The server, built using the Flask framework, receives a product ID and then calls an external API to retrieve relevant eco-friendly information about that product, such as the product's manufacturing process, materials, and recycling methods. The retrieved information is then customized based on the user's profile, interests, and current situation.

[1057] The customized information is then displayed in real time on the user's smartphone, giving them specific advice on how to take environmentally friendly actions in the moment.

[1058] The required hardware is a smartphone, and the required software is Flask (a Python web framework) and requests (a Python library for sending HTTP requests).

[1059] For example, if a user scans an "eco bag" in a physical store, tips on how to recycle the bag and how to save energy will be displayed. For example, "This eco bag is made from recycled materials. After use, it can be reused by bringing it to a designated recycling center. By using this eco bag, you can reduce the use of approximately 50 plastic bags per year."

[1060] Examples of prompts to input to a generative AI model include:

[1061] "Create an app that, when a user scans an item, provides eco-friendly information related to that item. For example, if a user scans an eco-bag, it displays tips on how to recycle the bag and how to save energy."

[1062] In this way, users can be provided with information about sustainable living through their physical shopping experience.

[1063] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1064] Step 1:

[1065] A user scans an item in a physical store. The user uses the smartphone camera to read the barcode or QR code of the item. The input is the product ID, which is sent to the application as the output.

[1066] Step 2:

[1067] The device (smartphone) sends the acquired product ID to the server. An HTTP request containing the product ID as input is generated. The product ID is sent to the server as output.

[1068] Step 3:

[1069] The server calls an external API based on the received product ID to obtain environmentally friendly information related to that product. An API request containing the product ID is generated as input, and the environmentally friendly information is obtained as output.

[1070] Step 4:

[1071] The server customizes the acquired environmentally conscious information based on the user's profile, interests, and current situation. The environmentally conscious information and the user's profile data are used as input. The customized environmentally conscious information is generated as output.

[1072] Step 5:

[1073] The server sends the customized environmentally conscious information to the device (smartphone). An HTTP response is generated that includes the customized environmentally conscious information as input. The environmentally conscious information is sent to the device as output.

[1074] Step 6:

[1075] The terminal (smartphone) displays the received environmentally conscious information to the user. The customized environmentally conscious information is used as input. The environmentally conscious information is displayed on the smartphone screen as output.

[1076] Step 7:

[1077] The user takes sustainable actions based on the displayed environmentally friendly information. The displayed information is used as input. The output prompts the user to take specific actions.

[1078] Example 3

[1079] Next, a description will be given of Example 3 of Form Example 3. 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."

[1080] Conventional systems do not adequately provide information on environmentally friendly products and services that are tailored to users' interests and preferences. In addition, they lack the functionality to customize information based on user feedback, making it difficult to provide useful and attractive information to users.

[1081] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1082] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for receiving search keywords entered by the user and collecting information on related environmentally friendly products and services, means for displaying the collected information to the user, and means for receiving user feedback and reflecting it in future information provision. This makes it possible to provide information on environmentally friendly products and services tailored to the user's interests and preferences, thereby providing useful and attractive information to the user.

[1083] A "user profile" is a collection of data including a user's personal information, interests, preferences, behavioral history, etc.

[1084] "Interests" refers to specific areas, topics, products, services, etc. that a user is interested in.

[1085] "Current situation" refers to information such as the user's current geographic location, time, environmental conditions, and device used.

[1086] "Means of analysis" refers to algorithms and software used to analyze a user's profile, interests, and current situation and extract relevant information.

[1087] "Sustainable Living Suggestions" refers to specific advice and information to promote environmentally friendly lifestyles and behaviors.

[1088] "Recycling method" refers to the specific procedures and methods for reusing used products and waste materials.

[1089] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[1090] "Methods of minimizing environmental impact" refers to specific actions and measures to reduce the burden on the environment.

[1091] "Specific actions" refer to concrete actions or steps that users can actually take.

[1092] "Search keywords" refer to words or phrases that users enter to search for information that interests them.

[1093] "Environmentally friendly products and services" refers to products and services designed to reduce the burden on the environment.

[1094] "Means of collecting information" refers to the algorithms and software used to obtain the required information from databases and external sources.

[1095] "Means for displaying information" refers to the interface or device used to visually present collected information to the user.

[1096] "Feedback" refers to ratings and comments made by users on information provided.

[1097] "Means of receiving feedback" refers to algorithms or software used to collect ratings and comments from users.

[1098] "Means of reflecting this in information provision" refers to algorithms and software that analyze the collected feedback and use it in future information provision.

[1099] The present invention is a system that provides users with information about environmentally friendly products and services and customizes the information based on user feedback. A specific embodiment of this system is described below.

[1100] System Overview

[1101] The system consists of three main components: the server, the terminal, and the user. The server collects, analyzes, and processes data and feedback. The terminal receives input from the user and displays information from the server. The user searches for information and provides feedback through the terminal.

[1102] Hardware and software used

[1103] Server: Use a cloud service (e.g., Amazon Web Services, Google Cloud Platform).

[1104] Database: Use a relational database such as AWS RDS (Relational Database Service).

[1105] Machine learning models: Learn user preferences using TensorFlow and PyTorch.

[1106] Device: Using the iOS or Android mobile application or a web browser.

[1107] Program processing

[1108] The server receives the search keywords entered by the user and collects information on related environmentally friendly products and services from a database. The collected information is sent to the device in JSON format. The device displays the received information to the user. The user provides feedback on the displayed information. The device then sends the user's feedback to the server. The server analyzes the received feedback and reflects it in future information provision.

[1109] Specific examples

[1110] For example, consider a case where a user is interested in "eco bags." When the user types "eco bags" into the device's search bar, the device sends this keyword to the server. The server uses AWS RDS to search a database and collects information on environmentally friendly products related to "eco bags." The collected information is sent to the device in JSON format. The device displays the information to the user using a list view or card view. When the user provides feedback such as "this eco bag has a nice design," the device sends this feedback to the server. The server uses TensorFlow to analyze the feedback and reflect it in future information provision.

[1111] Prompt Sentence Examples

[1112] An example of a prompt to input to a generative AI model is as follows:

[1113] When a user searches for "eco bag," provide them with relevant eco-friendly eco-bag information and customize future offers based on their feedback.

[1114] In this way, the user can learn about environmentally friendly products and services that match his or her interests and preferences. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1115] Step 1:

[1116] The user enters a search keyword.

[1117] Users enter keywords for products or services they are interested in into the device's search bar, for example, "eco bag." The entered keywords are temporarily stored in the device's memory.

[1118] Step 2:

[1119] The device sends the search keywords to the server.

[1120] The device sends the search keywords entered by the user to the server using an HTTP request. The input data is packaged in JSON format and sent to the server's API endpoint. The output is the search keywords received by the server.

[1121] Step 3:

[1122] The server collects information on related environmentally friendly products and services.

[1123] The server searches the database based on the received search keywords to collect information on related environmentally friendly products and services. Specifically, it executes a database query using AWS RDS. The input is the search keyword, and the output is a list of related information.

[1124] Step 4:

[1125] The server sends the collected information to the terminal.

[1126] The server sends the collected information to the terminal as an HTTP response in JSON format. The input is a list of related information, and the output is the JSON data received by the terminal.

[1127] Step 5:

[1128] The device displays the information to the user.

[1129] The device parses the information received from the server and displays it visually to the user. For example, in the case of a mobile app, it might display the information using a list view or card view. The input is JSON data, and the output is the information displayed to the user.

[1130] Step 6:

[1131] Users provide feedback on the information.

[1132] The user provides feedback on the displayed information. For example, they can comment, "This eco bag has a good design." The input is the user's feedback, and the output is the feedback data stored on the device.

[1133] Step 7:

[1134] The device sends the feedback to the server.

[1135] The terminal sends user feedback to the server using an HTTP request. The input is the feedback data, and the output is the feedback data received by the server.

[1136] Step 8:

[1137] The server will analyze the feedback and reflect it in future information provision.

[1138] The server analyzes the received feedback. Specifically, it uses TensorFlow to train a machine learning model to learn the user's preferences. The input is the feedback data, and the output is an updated machine learning model. From then on, the content and format of the information provided to the user are adjusted.

[1139] (Application example 3)

[1140] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1141] Today's consumers are increasingly conscious of choosing environmentally friendly products and services, but they often do not know what products are environmentally friendly or how to obtain that information. Furthermore, because the information provided is uniform, it may not match the interests or preferences of individual users. Furthermore, there is a lack of a mechanism for customizing information based on user feedback, making it difficult to provide useful and attractive information to users.

[1142] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for presenting methods and specific actions for minimizing environmental impact; means for recommending environmentally friendly products related to the product the user is viewing; means for improving the recommendation algorithm based on user feedback; and means for providing customized information on environmentally friendly products. This allows users to easily obtain information on environmentally friendly products and services that match their interests and preferences, and enables the provision of customized information that reflects their feedback.

[1143] A "user profile" is a collection of data including a user's personal information, interests, preferences, behavioral history, etc.

[1144] "Interests" refers to information about products, services, topics, etc. that a user is interested in.

[1145] "Current situation" refers to the environment or condition in which the user is placed, such as location, time of day, season, etc.

[1146] "Means of analysis" refers to methods and technologies used to analyze collected data and identify users' interests, preferences, and behavioral patterns.

[1147] "Sustainable Living Suggestions" is information that provides specific advice and methods for living an environmentally conscious life.

[1148] "Recycling methods" are specific procedures and methods for reusing used products and waste materials.

[1149] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[1150] "Means of providing information" refers to methods and technologies for conveying necessary information to users in an appropriate format.

[1151] "Methods of minimizing environmental impact" are specific actions or measures taken to reduce the burden on the environment.

[1152] "Means of suggesting specific actions" are methods or techniques that provide users with a specific action plan that they can actually take.

[1153] "Environmentally friendly products" are products designed to minimize the burden on the environment at each stage of production, use, and disposal.

[1154] "Recommendation methods" are methods and technologies for selecting and presenting appropriate products and services based on the user's interests and preferences.

[1155] "Feedback" refers to the evaluation or opinion a user gives of the information provided or the recommended products.

[1156] A "recommendation algorithm" is a calculation method or program for selecting the most suitable products or services based on user data.

[1157] "Customized information" is information that is tailored to a user's individual interests, preferences, and behavioral patterns.

[1158] The system for implementing this invention includes a plurality of means for analyzing a user's profile, interests, and current situation, and providing information on environmentally friendly products and services. Specific embodiments are described below.

[1159] System Configuration

[1160] 1. Data collection methods:

[1161] The server collects your profile, interests, and current situation, including your browsing history, purchase history, and location information.

[1162] Hardware used: Smartphone

[1163] Software used: Firebase (database), Google Analytics (user behavior tracking)

[1164] 2. Data analysis methods:

[1165] The server analyzes the collected data to identify the user's interests and preferences.

[1166] Software used: Python, Pandas, Scikit-learn (machine learning library)

[1167] 3. Recommendation Algorithm:

[1168] The server runs an algorithm to recommend environmentally friendly products related to the product the user is viewing.

[1169] Software used: TensorFlow (deep learning library)

[1170] 4. Feedback collection methods:

[1171] The server collects user feedback and improves the recommendation algorithm.

[1172] Software used: Firebase (database), Python

[1173] 5. Information provision method:

[1174] The server provides the user with customized information on environmentally friendly products.

[1175] Software used: React Native (mobile app development framework)

[1176] Processing flow

[1177] 1. Data Collection:

[1178] When users browse online shopping sites using their smartphones, user behavior data is collected using Firebase and Google Analytics.

[1179] 2. Data Analysis:

[1180] The server analyzes the collected data using Python and Pandas to identify users' interests and preferences.

[1181] 3. Run the recommendation algorithm:

[1182] Using TensorFlow, we recommend environmentally friendly products related to the product the user is viewing.

[1183] 4. Gathering feedback and improving the algorithm:

[1184] When users provide feedback on recommended products, the data is stored in Firebase and used to improve the recommendation algorithm using Python.

[1185] 5. Information provision:

[1186] Using React Native, customized information about environmentally friendly products is provided to users.

[1187] Specific examples

[1188] For example, if a user browses for "plastic water bottles," the system will recommend "stainless steel reusable water bottles." If the user purchases a "reusable water bottle," the system will recommend related products such as "reusable straws" and "eco bags" the next time the user browses.

[1189] Prompt Sentence Examples

[1190] An example of a prompt for the generative AI model is as follows:

[1191] Recommend eco-friendly products related to the product the user is browsing. Consider the user's past browsing and purchase history to choose the most suitable products.

[1192] In this way, a system can be realized that provides users with useful and attractive information about environmentally friendly products.

[1193] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1194] Step 1:

[1195] When a user browses an online shopping site using a smartphone, the device collects user behavior data using Firebase and Google Analytics. Specifically, data such as the products the user viewed, the links they clicked, and the length of time they spent on the site is collected in real time and stored in the Firebase database. The input is user behavior data, and the output is the behavior data stored in Firebase.

[1196] Step 2:

[1197] The server periodically retrieves user behavior data stored in Firebase and analyzes it using Python and Pandas. Specifically, it processes the data to identify the user's interests and preferences based on the user's browsing history and purchase history. The input is the behavioral data retrieved from Firebase, and the output is the analysis results that identify the user's interests and preferences.

[1198] Step 3:

[1199] The server uses TensorFlow to run an algorithm that recommends environmentally friendly products related to the product the user is viewing. Specifically, based on the analysis results, the server selects the most suitable environmentally friendly products for the user and generates a recommendation list. The input is the analysis results, and the output is the recommendation list.

[1200] Step 4:

[1201] When a user provides feedback on a recommended product, the device stores that feedback data in Firebase. Specifically, the user enters ratings and comments such as "good" or "bad" and sends them to Firebase. The input is the user's feedback data, and the output is the feedback data stored in Firebase.

[1202] Step 5:

[1203] The server retrieves the feedback data stored in Firebase and uses Python to improve the recommendation algorithm. Specifically, it analyzes the feedback data and adjusts the parameters of the recommendation algorithm to improve the accuracy of the next recommendation. The input is the feedback data, and the output is an improved recommendation algorithm.

[1204] Step 6:

[1205] The server uses React Native to provide users with customized information about environmentally friendly products. Specifically, it displays appropriate product information on the user's smartphone based on the recommendation list. The input is the recommendation list, and the output is the product information displayed on the user's smartphone.

[1206] In this way, a system can be realized that provides users with useful and attractive information about environmentally friendly products.

[1207] 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.

[1208] "Example 1"

[1209] One embodiment of the present invention is a system that incorporates an emotion engine that recognizes a user's emotions. This system analyzes the user's profile, interests, and current situation, and based on the analysis results, provides information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips. Furthermore, the emotion engine recognizes the user's emotions and provides information and suggestions based on those emotions. For example, if the system recognizes that the user is feeling stressed, it may suggest relaxing ambient music or eco-friendly activities that are believed to help relieve stress.

[1210] "Example 2"

[1211] Another embodiment of the present invention is a system for providing information on environmentally friendly products and services. This system recognizes the user's emotions and suggests products and services that correspond to those emotions. For example, if the system recognizes that the user is feeling joy, it suggests eco-friendly products and services that may further enhance that joy.

[1212] "Example 3"

[1213] Furthermore, a system for customizing information provided to a user is also an embodiment of the present invention. This system recognizes the user's emotions and adjusts the way information is provided depending on the emotions. For example, if it recognizes that the user is feeling depressed, it customizes the information provided to take into account the user's emotional state, such as by emphasizing positive information.

[1214] The processing flow of each embodiment will be described below.

[1215] "Example 1"

[1216] Step 1: Analyze the user's profile, interests, and current situation.

[1217] Step 2: Recognize the user's emotions using the emotion engine.

[1218] Step 3: Based on the analysis and emotion recognition results, provide suggestions for sustainable living, recycling methods, energy-saving tips, etc.

[1219] Step 4: If the system recognizes that the user is feeling stressed, it will suggest relaxing ambient music or eco-friendly activities that are believed to help relieve stress.

[1220] "Example 2"

[1221] Step 1: Recognize the user's emotions.

[1222] Step 2: Provide information about eco-friendly products and services that correspond to the user's emotions. Step 3: If it is recognized that the user is feeling joy, suggest eco-friendly products and services that may further amplify that joy.

[1223] "Example 3"

[1224] Step 1: Recognize the user's emotions.

[1225] Step 2: Tailor the information you provide to the user based on their emotions.

[1226] Step 3: If the system detects that the user is feeling down, it will customize the experience to take into account the user's emotional state, such as by emphasizing positive information.

[1227] Example 1

[1228] Next, a description will be given of Example 1 of Form 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."

[1229] Conventional systems were not able to analyze users' profiles, interests, and current situations, nor were they able to recognize their emotions and provide information and suggestions based on those emotions. Furthermore, they lacked the ability to generate messages to users using generative AI models, making it difficult to provide more personalized information to users. This led to problems such as a decline in user satisfaction and engagement.

[1230] 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.

[1231] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for recognizing the user's emotions, means for providing information and suggestions according to the user's emotions based on the emotion recognition results, and means for generating messages to be provided to the user using a generative AI model. This makes it possible to provide personalized information according to the user's emotions and interests.

[1232] A "user profile" is data that includes a user's personal information, interests, preferences, behavioral history, etc.

[1233] "Interests" are information related to topics or areas that interest a user.

[1234] "Current situation" refers to information about the environment and conditions in which the user finds themselves, such as the season, weather, and local environmental issues.

[1235] "Means of analysis" are methods and tools used to analyze collected data and understand user profiles, interests, and current situations.

[1236] "Sustainable Living Suggestions" are advice and information to encourage environmentally conscious lifestyles and behaviors.

[1237] "Recycling methods" are specific procedures and methods for reusing used products and waste materials.

[1238] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[1239] "Methods of minimizing environmental impact" are specific actions or measures taken to reduce the burden on the environment.

[1240] "Means of providing specific actions" is a way to provide a specific action plan that users can actually take.

[1241] "Means of recognizing emotions" are technologies and tools for analyzing and understanding a user's emotional state.

[1242] "Emotion recognition result" is data on the user's emotional state obtained by emotion recognition means.

[1243] A "generative AI model" is an algorithm or program that uses artificial intelligence to generate text or information.

[1244] "Means for generating a message" refers to a method for creating a message to be provided to a user using a generative AI model.

[1245] This invention is a system that analyzes a user's profile, interests, and current situation to make suggestions for sustainable living. The system has the ability to recognize the user's emotions and provide information and suggestions according to those emotions. It also uses a generative AI model to generate messages to be provided to the user.

[1246] Hardware and software used

[1247] Hardware: Servers, terminals (PCs, smartphones)

[1248] Software: sentiment engines, data analysis tools (e.g., Python pandas, scikit-learn), generative AI models (e.g., GPT-4)

[1249] Data collection

[1250] The server collects data such as the user's social media posts, purchase history, and search history. For example, it uses the Twitter API to collect the user's tweets and obtains their Amazon purchase history via the API. The device obtains current weather information based on the user's location. For example, it obtains current weather data using the OpenWeatherMap API.

[1251] Data analysis

[1252] The server analyzes the collected data using Python's pandas and scikit-learn. It analyzes social media posts using text analysis tools (e.g., NLTK) to understand the user's interests and preferences. It analyzes purchase history to identify the product categories the user recently purchased. It evaluates the user's living environment based on current weather data and seasonal information.

[1253] emotion recognition

[1254] The server uses an emotion engine to analyze emotions from users' social media posts. For example, if a user's post contains keywords such as "tired" or "stressed," it determines that the user is feeling stressed. Based on the results of the emotion engine, the server records the user's emotional state in a database.

[1255] Information provision

[1256] The server generates optimal suggestions for the user based on the results of data analysis and emotion recognition. It uses a generative AI model (e.g., GPT-4) to generate a message to provide to the user. For example, it generates a message such as, "We recommend a playlist of relaxing ambient music." The device notifies the user of the generated message. For example, it sends the suggestion to the user using a smartphone push notification.

[1257] Specific examples

[1258] Example 1: When a user posts on social media that they've been feeling stressed lately

[1259] The server retrieves the user's latest tweets using the Twitter API. It uses an emotion engine to determine whether the tweets indicate "stress." It then uses a generative AI model (e.g., GPT-4) to generate a message such as "We recommend a playlist of relaxing ambient music." The device then sends the generated message to the user via a push notification on their smartphone.

[1260] Example 2: When a user searches for "interested in eco-activities"

[1261] The server analyzes the user's search history and identifies keywords related to "eco-activities." Using a generative AI model (e.g., GPT-4), it generates a message such as, "Want to know about local environmental issues? Here are some easy eco-activities you can start." The device then sends the generated message to the user via a push notification on their smartphone.

[1262] Prompt Sentence Examples

[1263] "If the user is feeling stressed, generate a message suggesting relaxing ambient music."

[1264] "If a user is interested in eco-friendly activities, generate a message that provides information about local environmental issues and suggests easy eco-friendly activities to start."

[1265] The above is an embodiment of the present invention.

[1266] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1267] Step 1: Data collection

[1268] The server collects data such as the user's social media posts, purchase history, and search history. Specifically, it retrieves the user's tweets using the Twitter API and their Amazon purchase history via an API. The device obtains current weather information based on the user's location information. For example, it obtains current weather data using the OpenWeatherMap API.

[1269] Input: User's social media account information, online shopping site account information, location information

[1270] Output: SNS posting data, purchase history data, weather data

[1271] Step 2: Data analysis

[1272] The server analyzes the collected data using Python's pandas and scikit-learn. It analyzes social media posts using text analysis tools (e.g., NLTK) to understand the user's interests and preferences. It analyzes purchase history to identify the product categories the user recently purchased. It evaluates the user's living environment based on current weather data and seasonal information.

[1273] Input: SNS posting data, purchase history data, weather data

[1274] Output: User interest and preference data, product category data, living environment data

[1275] Step 3: Emotion Recognition

[1276] The server uses an emotion engine to analyze emotions from users' social media posts. For example, if a user's post contains keywords such as "tired" or "stressed," it determines that the user is feeling stressed. Based on the results of the emotion engine, the server records the user's emotional state in a database.

[1277] Input: SNS post data

[1278] Output: User emotion data

[1279] Step 4: Provide information

[1280] The server generates optimal suggestions for the user based on the results of data analysis and emotion recognition. It uses a generative AI model (e.g., GPT-4) to generate a message to provide to the user. For example, it generates a message such as, "We recommend a playlist of relaxing ambient music." The device notifies the user of the generated message. For example, it sends the suggestion to the user using a smartphone push notification.

[1281] Input: User interest and preference data, product category data, living environment data, user emotion data

[1282] Output: The message to provide to the user

[1283] Specific examples of operation

[1284] Example 1: When a user posts on social media that they've been feeling stressed lately

[1285] Step 1: The server uses the Twitter API to retrieve the user's latest tweets.

[1286] Input: User's SNS account information

[1287] Output: SNS post data

[1288] Step 2: The server analyzes the collected social media posting data using a text analysis tool (e.g., NLTK) to understand the user's interests and preferences.

[1289] Input: SNS post data

[1290] Output: User interest and preference data

[1291] Step 3: The server uses an emotion engine to determine that the tweet content indicates "stress."

[1292] Input: SNS post data

[1293] Output: User emotion data

[1294] Step 4: The server uses a generative AI model (e.g., GPT-4) to generate a message such as, "We recommend a playlist of relaxing ambient music." The device then sends the generated message to the user via a push notification on their smartphone.

[1295] Input: User interest and preference data, user emotional data

[1296] Output: The message to provide to the user

[1297] Example 2: When a user searches for "interested in eco-activities"

[1298] Step 1: The server analyzes the user's search history and identifies keywords related to "eco-activities."

[1299] Input: User search history data

[1300] Output: User interest and preference data

[1301] Step 2: The server analyzes the collected search history data to understand the user's interests and preferences.

[1302] Input: Search history data

[1303] Output: User interest and preference data

[1304] Step 3: The server uses the emotion engine to analyze the user's emotional state.

[1305] Input: Search history data

[1306] Output: User emotion data

[1307] Step 4: The server uses a generative AI model (e.g., GPT-4) to generate a message such as, "Want to know about local environmental issues? Here are some easy eco-friendly activities you can start." The device then sends the generated message to the user via a push notification on their smartphone.

[1308] Input: User interest and preference data, user emotional data

[1309] Output: The message to provide to the user

[1310] (Application example 1)

[1311] Next, a description will be given of Application Example 1 of Form 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."

[1312] Previous sustainable living recommendation systems were limited to analyzing users' profiles, interests, and current situations, and had the problem of not being able to respond to individual needs such as user emotions or recommending eco-friendly products in physical stores. They also lacked the functionality to suggest appropriate relaxation methods when users were feeling stressed. This could result in a decrease in user satisfaction and contribution to sustainable living.

[1313] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for presenting methods for minimizing environmental impact and specific actions; means for recognizing the user's emotions and providing information and suggestions based on those emotions; means for recommending eco-friendly and recyclable products in physical stores; and means for suggesting relaxing ambient music when the user is feeling stressed. This makes it possible to respond to individual needs, such as user emotions and eco-friendly product recommendations in physical stores, and improve user satisfaction and contribution to sustainable living.

[1314] A "user profile" is a collection of data that includes a user's personal information, interests, preferences, past behavioral history, etc.

[1315] "Interests" refers to the topics, fields, activities, etc. that a user is interested in.

[1316] "Current situation" refers to the environment or conditions in which the user finds themselves, such as the season, weather, local environmental issues, etc.

[1317] "Sustainable living" refers to living in a way that is environmentally friendly, does not waste resources, and is sustainable in the long term.

[1318] "Recycling method" refers to the specific procedures and methods for reusing used products and materials.

[1319] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[1320] "Methods of minimizing environmental impact" refers to specific measures and actions taken to reduce the burden on the environment.

[1321] "Emotion recognition" refers to determining a user's emotional state from their facial expressions, behavior, input data, etc.

[1322] "Brick and mortar store" refers to a commercial establishment or retail outlet that exists in a physical location.

[1323] "Eco products" refer to products made using environmentally friendly materials and manufacturing methods.

[1324] "Recyclable products" refer to products that can be reused or reprocessed after use.

[1325] "Relaxing ambient music" refers to music that has a relaxing effect when listened to.

[1326] The system for implementing this invention analyzes a user's profile, interests, and current situation to provide suggestions for sustainable living, recycling methods, and energy-saving tips. It also has the ability to recognize the user's emotions and provide information and suggestions based on those emotions. It also recommends eco-friendly and recyclable products in physical stores, and suggests relaxing ambient music when the user is feeling stressed.

[1327] Hardware and software used

[1328] Hardware: Smartphone

[1329] Software: Python, EmotionRecognizer library, Weather API, Product Recommendation system

[1330] Data processing and calculation

[1331] User profile analysis

[1332] The server obtains the user's profile, interests, purchase history, and location information, and takes into account the current weather and season, allowing for a comprehensive analysis of the user's interests and current situation.

[1333] emotion recognition

[1334] The server uses the EmotionRecognizer library to recognize emotions from the user's input data, which allows it to determine whether the user is feeling stressed and make appropriate suggestions.

[1335] Proposal generation

[1336] The server generates relaxing ambient music and eco-friendly activities based on the recognized emotions. For example, if the user is feeling stressed, the server will suggest relaxing ambient music.

[1337] Eco-friendly product recommendations

[1338] The server recommends eco-friendly and recyclable products in physical stores based on the user's interests and current situation, allowing the user to choose specific products that will help them practice sustainable living.

[1339] Specific examples

[1340] User Interest

[1341] The user is interested in "sustainability" and "recycling." The current weather is "sunny" and the season is "spring." The user is "stressed."

[1342] Prompt Sentence Examples

[1343] The user is interested in "sustainability" and "recycling." The current weather is "sunny" and the season is "spring." The user is feeling "stressed." Please suggest some relaxing ambient music. Also, please recommend some eco-friendly products.

[1344] In this way, it is possible to create a system that comprehensively analyzes a user's profile, interests, current situation, and emotions, and provides suggestions for sustainable living, recycling methods, and energy-saving tips.

[1345] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1346] Step 1:

[1347] The server retrieves the user's profile, interests, purchase history, and location information, including personal information provided by the user and past behavioral data. The inputs include the user's ID, location, and past purchase history, and the output is a comprehensive profile of the user.

[1348] Step 2:

[1349] The server calls the Weather API to take into account the current weather and season based on the profile data it has acquired. The input is the user's location information, and the output is the current weather and season information.

[1350] Step 3:

[1351] The server uses the EmotionRecognizer library to recognize emotions from user input data. The input is the user's text and voice data, and the output is the user's emotional state (e.g., stressed, relaxed).

[1352] Step 4:

[1353] The server generates relaxing ambient music and eco-activities suggestions based on the recognized emotions. The input is the user's emotional state, and the output is links to relaxing music and eco-activities suggestions.

[1354] Step 5:

[1355] The server recommends eco-friendly and recyclable products in physical stores based on the user's interests and current situation. The inputs are the user's interests, weather information, and seasonal information, and the output is a list of eco-friendly and recyclable products.

[1356] Step 6:

[1357] The terminal displays the suggestions and recommended products received from the server to the user. The input is the suggestion data and product list from the server, and the output is the information displayed on the user's screen.

[1358] Step 7:

[1359] The user checks the displayed suggestions and product list, and makes a selection or purchase as necessary. The input is the information displayed on the terminal, and the output is the user's selection and purchase data.

[1360] Step 8:

[1361] The server then updates the user's profile with their selections and purchase data, and uses this data for future suggestions and recommendations. The input is the user's selections and purchase data, and the output is an updated user profile.

[1362] Example 2

[1363] Next, a description will be given of Example 2 of Form 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."

[1364] In modern society, achieving a sustainable lifestyle requires specific proposals and guidelines for action tailored to each individual user. However, conventional systems have difficulty providing customized information based on a user's living environment and lifestyle, and have not suggested products or services that reflect the user's emotions. This has made it difficult for users to take concrete actions to practice a sustainable lifestyle.

[1365] 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.

[1366] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for recognizing the user's emotions and suggesting products and services based on those emotions, means for collecting information about the user's living environment and lifestyle and generating suggestions for sustainable living based on the information, means for analyzing the user's facial expressions and tone of voice to identify emotions, means for integrating and analyzing the collected data and generating optimal suggestions for the user, means for providing the generated suggestions to the user, and means for collecting user feedback and improving the accuracy of the system. This makes it possible to provide customized information based on the user's living environment and lifestyle, and to suggest products and services based on the user's emotions.

[1367] "User profile" refers to data such as a user's personal information, interests, preferences, living environment, and lifestyle.

[1368] "Means of analysis" refers to the methods and techniques used to analyze collected data and understand user characteristics and needs.

[1369] "Sustainable Living Suggestions" refers to specific advice and information to promote environmentally friendly lifestyles and behaviors.

[1370] "Recycling methods" refer to specific steps or methods for converting waste into a reusable form.

[1371] "Energy saving tips" refers to specific advice or methods for reducing energy consumption.

[1372] "Means of providing information" refers to the methods and techniques used to communicate analysis results and recommendations to users.

[1373] "Methods of minimizing environmental impact" refers to specific actions and measures taken to reduce the burden on the environment.

[1374] "Means of suggesting specific actions" refers to methods or technologies that provide specific instructions or advice for users to actually take action.

[1375] "Means for recognizing emotions" refers to methods and technologies for identifying emotions by analyzing a user's facial expressions and tone of voice.

[1376] "Means for suggesting products and services" refers to methods and technologies for recommending appropriate products and services based on the user's needs and emotions.

[1377] "Means of collecting information about living environment and lifestyle" refers to methods and technologies for collecting data about a user's living environment and lifestyle.

[1378] "Means for generating proposals" refers to methods and technologies for creating optimal proposals for users based on collected data.

[1379] "Means for analyzing facial expressions and tone of voice" refers to methods and technologies for analyzing a user's facial expressions and tone of voice using a camera or microphone.

[1380] "Means for integrating and analyzing data" refers to methods and technologies for integrating information collected from multiple data sources and analyzing it comprehensively.

[1381] "Means for providing suggestions" refers to the methods and techniques used to communicate generated suggestions to users.

[1382] "Feedback collection methods" refers to methods and techniques for collecting opinions and ratings from users.

[1383] "Means for improving the accuracy of the system" refers to methods and techniques for improving the performance and accuracy of the system based on the collected feedback.

[1384] This invention is a system that provides sustainable living suggestions, recycling methods, and energy-saving tips based on the user's living environment and lifestyle. It also has the function of recognizing the user's emotions and suggesting environmentally friendly products and services according to those emotions.

[1385] Hardware and software used

[1386] Hardware

[1387] Device: The device used by the user, such as a smartphone, computer, or tablet.

[1388] Camera: A device for capturing the user's facial expressions.

[1389] Microphone: A device used to collect the tone of a user's voice.

[1390] software

[1391] Data analysis software: Python

[1392] Machine learning frameworks: TensorFlow, PyTorch

[1393] Emotion recognition software: OpenCV, Google Cloud Vision API

[1394] Program processing

[1395] Data collection

[1396] Users access the system using a terminal and input information about their living environment and lifestyle, such as answering questions like, "Where do you live?" and "How much energy do you usually consume?"

[1397] emotion recognition

[1398] The device uses a camera and microphone to capture the user's facial expressions and tone of voice, allowing the system to analyze the user's emotions in real time. For example, if the user is smiling while speaking, the system will recognize that the user is happy.

[1399] Data analysis

[1400] The server integrates and analyzes the collected data. It uses Python for data analysis and TensorFlow and PyTorch for machine learning model execution. For example, if a user is interested in recycling, the server will research the recycling rules in the user's area and suggest specific recycling methods.

[1401] Proposal generation

[1402] The server generates sustainable living recommendations based on the analysis, including specific information like, "In your area, plastics can be recycled every Tuesday."

[1403] Providing suggestions

[1404] The server provides the generated suggestions to the user, who then displays the suggestions as notifications on their device.

[1405] Feedback collection

[1406] The user receives suggestions provided by the server, tries them out, and provides feedback on whether the suggestions were useful or not, which is used to improve the accuracy of the system.

[1407] Examples and prompts

[1408] For example, if the user is interested in "energy saving," the following specific actions will be taken:

[1409] 1. A user accesses the system and types in, "I want information about energy conservation."

[1410] 2. Your device uses the camera and microphone to collect your facial expressions and tone of voice.

[1411] 3. The server analyzes the collected data to ensure that users are interested in saving energy.

[1412] 4. The server generates and provides "home energy-saving tips" to the user, including specific advice such as "Replacing light bulbs with LEDs can save approximately 20% of energy per year."

[1413] 5. The user receives the suggestions, tries out the LED bulbs, and provides feedback on whether the suggestions were helpful.

[1414] Example prompt sentence:

[1415] "How do I recycle in my area?"

[1416] "Please tell me some tips on how to save energy at home."

[1417] Please tell me some eco-friendly products.

[1418] "I'm looking for an eco-friendly service."

[1419] In this way, the system provides users with information to make their lives more sustainable.

[1420] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1421] Step 1:

[1422] A user accesses the system and inputs information about their living environment and lifestyle.

[1423] Input: Questions about the user's living environment and lifestyle (e.g., "Where do you live?", "How much energy do you usually consume?")

[1424] Output: User response data

[1425] Specific operation: Users access the system using a device such as a smartphone or PC and answer the questions displayed. The answer data is sent to the server.

[1426] Step 2:

[1427] The device uses a camera and microphone to collect data to recognize the user's emotions.

[1428] Input: User's facial expression and tone of voice

[1429] Output: Emotion recognition data

[1430] How it works: The device captures the user's facial expressions with a camera and collects the user's tone of voice with a microphone. These data are analyzed in real time and sent to the server as emotion recognition data.

[1431] Step 3:

[1432] The server analyzes the collected data and generates optimal sustainable living recommendations for the user.

[1433] Input: User response data, emotion recognition data

[1434] Output: Sustainable living suggestions

[1435] Specific operation: The server analyzes data using Python and runs machine learning models using TensorFlow and PyTorch. For example, if a user is interested in recycling, the server will research the recycling rules in the user's area and suggest specific recycling methods.

[1436] Step 4:

[1437] The server provides the generated suggestions to the user.

[1438] Input: Sustainable Living Proposals

[1439] Output: User notification

[1440] Specific behavior: The server sends the generated suggestions to the user's device as notifications, containing specific information such as "In your area, plastics can be recycled every Tuesday."

[1441] Step 5:

[1442] The user receives the suggestions and provides feedback if necessary.

[1443] Input: User feedback

[1444] Output: Feedback data

[1445] Specific behavior: The user receives suggestions provided by the server, tries them out, and provides feedback on whether the suggestions were useful. The feedback data is sent to the server and used to improve the accuracy of the system.

[1446] (Application example 2)

[1447] Next, a description will be given of Application Example 2 of Form 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."

[1448] While conventional sustainable living recommendation systems provide information based on a user's profile and interests, they are unable to take user emotions into account when making recommendations, resulting in low user satisfaction and engagement. Furthermore, there was no system that could recognize a user's emotions in real time using a smartphone's camera and microphone and make recommendations accordingly.

[1449] 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.

[1450] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for recognizing the user's emotions and suggesting products and services based on those emotions, means for analyzing the user's facial expressions and voice using the smartphone's camera and microphone, means for predicting the user's emotions using an emotion recognition model, means for generating suggestions for sustainable living and information on eco-friendly products based on the predicted emotions, and means for displaying the generated suggestions and information to the user. This makes it possible to provide suggestions for sustainable living and information on eco-friendly products based on the user's emotions.

[1451] A "user profile" is data that includes a user's personal information, interests, preferences, behavioral history, etc.

[1452] "Interests" are areas or topics that a user is interested in.

[1453] "Current situation" refers to the environment or state in which the user is located, such as location information or activity status.

[1454] "Analysis results" refers to information and data obtained based on a user's profile, interests, and current situation.

[1455] "Sustainable living" refers to a lifestyle that is environmentally friendly, does not waste resources, and is sustainable in the long term.

[1456] A "suggestion" is a presentation of specific actions or options to the user.

[1457] "Recycling methods" refer to specific means and procedures for reusing used products and waste materials.

[1458] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[1459] "Environmental impact" refers to the effects or consequences of a user's actions or choices on the environment.

[1460] A "specific action" is a concrete action that a user can actually take.

[1461] "Emotion" refers to the user's psychological state or mood.

[1462] "Goods and Services" means any products or services offered that are available for purchase or use by Users.

[1463] A "smartphone camera" refers to the camera device built into a smartphone.

[1464] A "microphone" is a device used to record sound.

[1465] "Facial expressions" refer to the user's facial movements and expressions.

[1466] "Voice" refers to the sound produced by the user.

[1467] An "emotion recognition model" is a machine learning model that predicts emotions from a user's facial expressions and voice.

[1468] "Prediction" is the estimation of future conditions or outcomes based on data.

[1469] "Eco-friendly products" are products that are manufactured with consideration for the environment.

[1470] "Generating information" means creating new information based on data.

[1471] "Displaying" means providing information visually to the user.

[1472] The system for implementing this invention analyzes a user's profile, interests, and current situation to provide suggestions for sustainable living, recycling methods, and energy-saving tips. It also has the ability to recognize a user's emotions and suggest products and services that correspond to those emotions.

[1473] Hardware and software used

[1474] Hardware: Smartphone camera and microphone

[1475] Software: OpenCV, Keras, emotion recognition model

[1476] Data processing and calculation

[1477] 1. User profile analysis:

[1478] The server collects and analyzes the user's profile, interests, and current situation. The profile includes the user's personal information, interests, preferences, and behavioral history.

[1479] 2. Emotion recognition:

[1480] It uses the smartphone's camera and microphone to capture the user's facial expressions and voice in real time, performs face detection using OpenCV, and predicts the user's emotions using an emotion recognition model loaded in Keras.

[1481] 3. Proposal generation:

[1482] Based on the predicted emotions, the system generates suggestions for sustainable living and eco-friendly products. For example, if the user is feeling joy, it will suggest eco-friendly products that will amplify that emotion.

[1483] 4. Display information:

[1484] The generated suggestions and information are displayed on the smartphone screen, allowing users to get real-time information on sustainable living.

[1485] Specific examples

[1486] For example, when a user uses their smartphone camera, the app analyzes their facial expressions and, if it detects that they are happy, it will display a suggestion such as, "Check out our eco-friendly products!"

[1487] Prompt Sentence Examples

[1488] "Create an application that analyzes the user's facial expressions and suggests eco-friendly products if they show signs of happiness."

[1489] In this way, it becomes possible to provide suggestions for sustainable living and information on eco-friendly products that correspond to the user's emotions.

[1490] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1491] Step 1:

[1492] The server collects the user's profile, interests, and current situation. The input includes the user's personal information, interests, preferences, and behavioral history. Based on this data, the server generates a user profile and performs analysis. The output is the user's profile information.

[1493] Step 2:

[1494] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice in real time. The input includes camera footage and audio data. This data is then subjected to face detection using OpenCV and audio data is collected. The output is facial position information and audio data.

[1495] Step 3:

[1496] The server inputs the face-detected image data into the emotion recognition model loaded in Keras to predict the user's emotion. The input includes face location information and image data. The emotion recognition model is used to predict the user's emotion. The output is the predicted emotion information.

[1497] Step 4:

[1498] The server generates sustainable living suggestions and eco-friendly product information based on the predicted emotion information and the user's profile information. The input includes emotion information and profile information. Based on this data, a generative AI model is used to generate suggestions. The output is the recommendation information.

[1499] Step 5:

[1500] The terminal displays the generated recommendation information on the smartphone screen.,The recommendation information is included as input.,It is displayed on the smartphone display to provide it to the user visually.,As output, the user can obtain information on sustainable living in,real time.

[1501] Step 6:

[1502] The user selects an action based on the displayed suggestion information. The input includes the displayed suggestion information. The user uses this information to select a specific action related to sustainable living. The output is the user's action.

[1503] Example 3

[1504] Next, a description will be given of Example 3 of Form Example 3. 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."

[1505] Conventional information provision systems lacked sufficient customization based on the user's interests and emotional state, making it difficult to provide optimal information to the user. Furthermore, there was a lack of effective means to provide information on environmentally friendly products and services, making it difficult for users to take concrete action to achieve sustainable lifestyles.

[1506] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes: means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for suggesting ways to minimize environmental impact and specific actions; means for providing information on environmentally friendly products and services related to the user's interests; means for adjusting the content and format of the information to be provided based on the user's feedback and emotional state; means for generating information in natural language using a generative AI model; and means for recognizing the user's emotional state using emotion recognition software. This makes it possible to provide optimal information according to the user's interests and emotions, thereby promoting specific actions for achieving sustainable living.

[1507] A "user profile" is data that includes a user's personal information, interests, preferences, past behavioral history, etc.

[1508] "Interests" refers to information about products, services, topics, etc. that a user is interested in.

[1509] "Current situation" refers to data that refers to the user's current environment or state, such as location information or activity status.

[1510] "Means of analysis" refers to technologies and methods for analyzing a user's profile, interests, and current situation and extracting relevant information.

[1511] "Sustainable Living Suggestions" is information that provides specific advice and methods for living an environmentally conscious life.

[1512] "Recycling methods" refers to information that indicates specific procedures and methods for reusing waste materials.

[1513] "Energy saving tips" are information that provides specific advice and methods for reducing energy consumption.

[1514] "Methods for minimizing environmental impact" refers to information that points to specific actions and measures for reducing the burden on the environment.

[1515] "Means of suggesting specific actions" are techniques or methods that provide specific instructions or methods that allow users to actually take action.

[1516] "Environmentally friendly products and services" are products and services that aim to reduce the burden on the environment.

[1517] "Feedback" is data that refers to the evaluations and opinions that users give about the information provided.

[1518] "Emotional state" refers to information that indicates the user's current emotions and mood.

[1519] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate information in natural language.

[1520] "Emotion recognition software" is software that analyzes and recognizes emotions from a user's text or voice.

[1521] This invention is a system that provides and customizes information about environmentally friendly products and services based on the user's interests and emotional state. This system is realized using a server, a terminal, a generative AI model, and emotion recognition software.

[1522] Hardware and software used

[1523] Hardware: Servers, user devices (PCs, smartphones, tablets, etc.)

[1524] Software: generative AI models (e.g., GPT-4), emotion recognition software, database management systems (e.g., MySQL)

[1525] Specific operation of the system

[1526] Collecting user interest information

[1527] User: Enters information about a product or service they are interested in into the device, such as keywords like "eco-friendly detergent" or "eco-friendly travel plans."

[1528] Terminal: Receives information entered by the user and sends it to the server.

[1529] Server: Stores the received information in a database, specifically by associating the user ID with keywords of interest.

[1530] Providing information on environmentally friendly products

[1531] Server: Searches a database for information on environmentally friendly products and services related to the user's interests. For example, retrieves a list of products related to "eco-friendly detergents."

[1532] Generative AI model: Generates easy-to-understand explanations for users based on search results. The prompt is "If the user is looking for an eco-friendly detergent, please describe the features of this detergent."

[1533] Terminal: Display the generated information to the user, for example, "This detergent is highly biodegradable and made with environmentally friendly ingredients."

[1534] Collecting user feedback

[1535] Users: Enter feedback on the information provided, such as "This information was helpful" or "I'd like more information."

[1536] Terminal: Receives user feedback and sends it to the server.

[1537] Server: Saves the feedback in a database. Specifically, it associates the user ID with the feedback content and saves it.

[1538] Customize your information

[1539] Server: Analyzes user feedback and past responses. For example, if a user requests more information, the server prepares to provide more information in response to that request.

[1540] Emotion recognition software: Recognizes the emotional state of a user, for example by using text analysis to read emotions from user comments.

[1541] Generative AI model: Adjusts the content and format of the information provided depending on the user's emotional state. The prompt used is "If the user is perceived as depressed, please provide positive information with emphasis."

[1542] On the device: Show customized information to the user. For example, if the device detects that the user is feeling depressed, it will emphasize positive messages such as "Using this detergent will help protect the environment."

[1543] Examples of concrete examples and prompts

[1544] Examples:

[1545] User: I'm looking for an eco-friendly cleaner.

[1546] Server: Searches the database for information about environmentally friendly detergents and generates descriptions using a generative AI model.

[1547] Terminal: Display "This detergent is highly biodegradable and made with environmentally friendly ingredients."

[1548] User: Enters feedback saying "This information was helpful."

[1549] Server: Your feedback will be saved and used for future updates.

[1550] Example prompt sentence:

[1551] "If a user is looking for an eco-friendly cleaner, explain the features of that cleaner."

[1552] "If you perceive a user as depressed, highlight and provide positive information."

[1553] In this way, the system provides and customizes information on environmentally friendly products and services according to the user's interests and emotions. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1554] Step 1: Collecting user interests

[1555] User: Enters information about a product or service they are interested in into the device, such as keywords like "eco-friendly detergent" or "eco-friendly travel plans."

[1556] Input: The keyword entered by the user.

[1557] Terminal: Receives information entered by the user and sends it to the server.

[1558] Output: User interest information sent to the server.

[1559] What it does: The device receives user input in real time, formats it, and sends it to the server.

[1560] Step 2: Providing information about environmentally friendly products

[1561] Server: Searches a database for information on environmentally friendly products and services related to the user's interests. For example, retrieves a list of products related to "eco-friendly detergents."

[1562] Input: User interests.

[1563] Data processing: Perform database queries and extract relevant product information.

[1564] Generative AI model: Generates easy-to-understand explanations for users based on search results. The prompt is "If the user is looking for an eco-friendly detergent, please describe the features of this detergent."

[1565] Output: The generated description.

[1566] Specific operation: The server inputs information obtained from the database into the generative AI model and generates an explanation in natural language.

[1567] Step 3: View the generated information

[1568] Terminal: Display the generated information to the user, for example, "This detergent is highly biodegradable and made with environmentally friendly ingredients."

[1569] Input: The generated description.

[1570] Output: Information displayed to the user.

[1571] Specific operation: The device displays the generated explanation received from the server on the user interface.

[1572] Step 4: Gather user feedback

[1573] Users: Enter feedback on the information provided, such as "This information was helpful" or "I'd like more information."

[1574] Input: User feedback.

[1575] Terminal: Receives user feedback and sends it to the server.

[1576] Output: Feedback information sent to the server.

[1577] What it does: The device receives user feedback in real time, formats it, and sends it to the server.

[1578] Step 5: Store and analyze feedback

[1579] Server: Stores the feedback in a database and analyzes the user's feedback and past responses. For example, if a user requests more information, the server prepares to provide more information in response to the request.

[1580] Input: User feedback.

[1581] Data processing: The feedback information is stored in a database and analytical algorithms are applied.

[1582] Output: Analysis results.

[1583] What it does: The server stores the feedback and uses analytical algorithms to analyze user requests and trends.

[1584] Step 6: Emotion recognition and information customization

[1585] Emotion recognition software: Recognizes the emotional state of a user, for example by using text analysis to read emotions from user comments.

[1586] Input: User feedback.

[1587] Data processing: Emotion recognition through text analysis.

[1588] Generative AI model: Adjusts the content and format of the information provided depending on the user's emotional state. The prompt used is "If the user is perceived as depressed, please provide positive information with emphasis."

[1589] Output: Customized information.

[1590] How it works: Emotion recognition software analyzes the feedback, and the generative AI model customizes the information based on the results.

[1591] Step 7: Displaying customized information

[1592] On the device: Show customized information to the user. For example, if the device detects that the user is feeling depressed, it will emphasize positive messages such as "Using this detergent will help protect the environment."

[1593] Input: Customized information.

[1594] Output: Customized information that is displayed to the user.

[1595] Specific operation: The terminal displays the customized information received from the server on the user interface.

[1596] In this way, the system provides and customizes information about environmentally friendly products and services according to the user's interests and emotions.

[1597] (Application example 3)

[1598] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1599] Conventional information provision systems do not take into account the user's emotions or past behavioral history, making it difficult to provide optimal information for the user. Furthermore, there is a lack of information on environmentally friendly products and services, making it difficult for users to take concrete actions to achieve a sustainable lifestyle. Furthermore, because information is not provided according to the user's emotional state, there is also the issue of not being able to increase user satisfaction.

[1600] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes: means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for suggesting ways to minimize environmental impact and specific actions; means for recognizing the user's emotions and adjusting the information provision method based on those emotions; means for recommending environmentally friendly products and services; and means for customizing information based on the user's past purchase history, browsing history, and feedback. This enables the provision of optimal information taking into account the user's emotions and past behavioral history, making it easier for the user to take specific actions to achieve a sustainable lifestyle. Furthermore, since information is provided according to the user's emotional state, user satisfaction can be increased.

[1601] A "user profile" is a collection of data including a user's personal information, interests, preferences, behavioral history, etc.

[1602] "Interests" are specific areas or topics that a user is interested in.

[1603] "Current situation" refers to the environment or state in which the user is located, such as location information or activity status.

[1604] "Sustainable living" refers to living in a way that is environmentally friendly, does not waste resources, and is sustainable in the long term.

[1605] A "suggestion" is the provision of information to the user to suggest actions or options.

[1606] "Recycling methods" refer to specific procedures and methods for reusing used products and materials.

[1607] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[1608] "Environmental impact" refers to the impact that a user's actions and choices have on the natural environment.

[1609] A "specific action" is a concrete action that a user can actually take.

[1610] "Emotion recognition" means determining a user's emotional state from their facial expressions and behavior.

[1611] "Adjusting the way information is provided" means changing the content and format of the information provided depending on the user's emotions and situation.

[1612] "Environmentally friendly products and services" are products and services designed to minimize the burden on the environment.

[1613] "Recommending" means recommending a particular product or service to a user.

[1614] "Past purchase history" refers to a record of products or services previously purchased by a user.

[1615] "Browsing history" refers to a record of web pages and product information that a user has viewed in the past.

[1616] "Feedback" refers to opinions and evaluations from users.

[1617] "Customize" means tailoring information or services to a user's individual needs and preferences.

[1618] The system for implementing this invention analyzes a user's profile, interests, and current situation to provide suggestions for sustainable living, recycling methods, energy-saving tips, etc. It also has the ability to recognize a user's emotions and adjust the information delivery method based on those emotions. It also recommends environmentally friendly products and services and customizes the information based on the user's past purchase history, browsing history, and feedback.

[1619] Hardware and software used

[1620] Hardware: Smartphone (camera, processor)

[1621] Software: Python, TensorFlow, JSON

[1622] Data processing and calculation

[1623] 1. Emotion recognition:

[1624] It takes a picture of the user's face using a smartphone camera and uses a TensorFlow model to recognize emotions.

[1625] The emotion recognition model determines emotions from the user's facial expressions and outputs the results.

[1626] 2. Load user data:

[1627] Read the user's past purchase history and browsing history from a JSON file.

[1628] Based on the data read, the user's interests and preferences are analyzed.

[1629] 3. Recommending environmentally friendly products:

[1630] Recommend environmentally friendly products and services based on user data.

[1631] Use recommendation algorithms to select the best products and services for users.

[1632] 4. Customization of information provided:

[1633] Adjust the content and format of the information you provide depending on the emotions you recognize.

[1634] For example, if a user is feeling down, provide them with positive information.

[1635] Specific examples

[1636] Users open the "Eco Shopping Assistant" app on their smartphone and take a photo of their face. The app recognizes the user's emotions and recommends eco-friendly products based on their past purchase history. If the user is feeling down, it will highlight positive information.

[1637] Prompt Sentence Examples

[1638] Users open the "Eco Shopping Assistant" app on their smartphone and take a photo of their face. The app recognizes the user's emotions and recommends eco-friendly products based on their past purchase history. If the user is feeling down, it will highlight positive information.

[1639] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1640] Step 1:

[1641] A user launches the "Eco Shopping Assistant" app on their smartphone and takes a picture of their face with the camera. The input is the user's face image, and the output is facial image data. This facial image data is input into the emotion recognition model.

[1642] Step 2:

[1643] The server receives the facial image data and uses a TensorFlow model to recognize emotions. The input is the facial image data, and the output is the user's emotional state (e.g., joy, sadness, surprise, etc.). The emotion recognition model extracts features from the facial image and classifies the emotion.

[1644] Step 3:

[1645] The server adjusts the information presentation method based on the user's emotional state. The input is the user's emotional state, and the output is the adjusted information presentation method. For example, if the user is feeling depressed, it is set to emphasize positive information.

[1646] Step 4:

[1647] The server reads the user's past purchase history and browsing history from a JSON file. The input is the user ID, and the output is the user's past purchase history and browsing history data. This data is used to analyze the user's interests and preferences.

[1648] Step 5:

[1649] The server recommends eco-friendly products and services based on the user's past purchase history and browsing history. The input is the user's past purchase history and browsing history data, and the output is a list of recommended eco-friendly products and services. A recommendation algorithm is used to select the most suitable products and services for the user.

[1650] Step 6:

[1651] The server provides users with tailored information delivery methods and recommended products and services. The input is the tailored information delivery method and a list of recommended products and services, and the output is the information displayed to the user. Based on the provided information, users can take specific actions to achieve sustainable living.

[1652] Step 7:

[1653] The user provides feedback on the provided information. The input is the user's feedback, and the output is feedback data. This feedback data is used to customize future information provision.

[1654] 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.

[1655] 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> ) 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.

[1656] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1657] 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.

[1658] [Third embodiment]

[1659] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1660] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1661] 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).

[1662] 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.

[1663] 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.

[1664] 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).

[1665] 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.

[1666] 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.

[1667] 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.

[1668] 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.

[1669] 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.

[1670] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1671] "Example 1"

[1672] The present invention is a system that uses AI. This system has a means for analyzing a user's profile, interests, and current situation. For example, the system analyzes the user's social media posts, purchase history, search history, etc. to understand the user's interests and preferences. The system also takes into account the user's current situation, such as the season, weather, and local environmental issues.

[1673] "Example 2"

[1674] Next, based on the analysis results, the system has the means to provide information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips. For example, it can make environmentally conscious suggestions related to the user's areas of interest. It can also provide recycling methods and energy-saving tips that are suited to the user's living environment and lifestyle.

[1675] "Example 3"

[1676] Furthermore, the site has a means for providing information on environmentally friendly products and services. For example, it provides information on environmentally friendly products and services related to products and services that the user is interested in. This allows the user to learn about environmentally friendly products and services that match their interests and preferences.

[1677] "Example 4"

[1678] Finally, it has the means to customize the information provided to users, for example, by adjusting the content and format of the information provided based on user reactions and feedback, thereby making it possible to provide more useful and attractive information to users.

[1679] The processing flow of each embodiment will be described below.

[1680] "Example 1"

[1681] Step 1: The system collects the user's social media posts, purchase history, search history, etc.

[1682] Step 2: Based on the collected data, AI analyzes the user's profile, interests, and current situation.

[1683] Step 3: Based on the analysis results, provide users with suggestions for sustainable living, recycling methods, energy-saving tips, etc.

[1684] "Example 2"

[1685] Step 1: The system makes environmentally friendly suggestions related to the user's interests and preferences.

[1686] Step 2: Provide users with recycling and energy-saving tips tailored to their living environment and lifestyle.

[1687] "Example 3"

[1688] Step 1: The system provides information on environmentally friendly products and services related to the products and services in which the user is interested.

[1689] "Example 4"

[1690] Step 1: The system collects user responses and feedback.

[1691] Step 2: Adjust the content and format of the information you provide based on the responses and feedback you receive.

[1692] Example 1

[1693] Next, a description will be given of Example 1 of Form 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."

[1694] Conventional systems struggled to provide information that fully took into account the user's profile, interests, and current situation, making it impossible to provide optimal recommendations for each individual user. Furthermore, there was a lack of effective methods for providing concrete actions to minimize environmental impact and suggestions for sustainable living.

[1695] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for presenting methods and specific actions for minimizing environmental impact; means for collecting and preprocessing user data and analyzing the user's interests and preferences; means for acquiring current situation data from an external data source; means for generating a response to the user using a generative AI model; and means for providing the generated response to the user. This makes it possible to make optimal suggestions taking into account the user's interests and current situation.

[1696] A "user profile" is a collection of data including a user's personal information, interests, preferences, behavioral history, etc.

[1697] "Interests" refers to the topics, activities, hobbies, etc. that a user is interested in.

[1698] "Current situation" refers to the environment or conditions in which the user finds themselves, such as the season, weather, or specific local conditions.

[1699] "Means of analysis" refers to methods and technologies for analyzing a user's profile, interests, and current situation and extracting meaningful information.

[1700] "Sustainable Living Suggestions" refers to specific advice and information to promote environmentally friendly lifestyles and behaviors.

[1701] "Recycling methods" refer to specific steps or methods for converting waste into a reusable form.

[1702] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[1703] "Methods of minimizing environmental impact" refers to specific actions and measures taken to reduce the burden on the environment.

[1704] "Means of suggesting specific actions" refers to techniques and methods for suggesting actions or methods that can be taken by users.

[1705] "Means of collecting data" refers to the methods and technologies used to obtain data about user behavior and interests.

[1706] "Preprocessing means" refers to methods and techniques for preparing collected data in a form that is easy to analyze.

[1707] "Interest and preference analysis means" refers to methods and technologies used to identify users' interests and preferences.

[1708] "External data sources" refers to external information sources used to understand the user's current situation.

[1709] A "generative AI model" refers to a model that uses artificial intelligence to generate responses and suggestions for users.

[1710] "Response generation means" refers to the technology or method for creating an appropriate response based on the user's profile and current situation.

[1711] "Means for providing a response" refers to the method or technology used to communicate the generated response to the user.

[1712] MODE FOR CARRYING OUT THE INVENTION

[1713] This invention is a system that analyzes a user's profile, interests, and current situation, and provides suggestions for sustainable living, recycling methods, energy-saving tips, etc. Specific embodiments of this system are described below.

[1714] Hardware and software used

[1715] The server uses the following hardware and software for data collection, pre-processing, analysis, and response generation:

[1716] Hardware: High-performance server (e.g., Intel Xeon processor, 32GB RAM or more)

[1717] Software: Python programming language, TensorFlow, PyTorch, NLTK, spaCy, MySQL or MongoDB, external APIs (e.g., OpenWeatherMap API)

[1718] The terminal uses the following hardware and software to receive input from the user and display responses from the server:

[1719] Hardware: Smartphones, tablets, computers

[1720] Software: web browser, mobile application

[1721] Data collection and preprocessing

[1722] The server collects data such as users' social media posts, purchase history, search history, etc. This includes retrieving data from social media platforms and e-commerce sites through APIs. For example, it uses the Twitter API to retrieve users' tweets and the Amazon API to collect purchase history.

[1723] The collected data is preprocessed by cleaning the text data (removing unnecessary characters and symbols), tokenizing it (splitting it into words and phrases), and removing stop words. This is done using natural language processing libraries such as NLTK and spaCy.

[1724] Analysis of user interests and preferences

[1725] The server analyzes the user's interests and preferences based on the preprocessed data. Specifically, it uses machine learning models (e.g., TF-IDF, Word2Vec) to identify the user's interests. The results of this analysis are stored in a database as a user profile.

[1726] Get current status data

[1727] The server retrieves data from external APIs (e.g., OpenWeatherMap API) to take into account the user's current situation (season, weather, local environmental issues, etc.), thereby providing real-time weather information and local specific conditions.

[1728] Response generation using generative AI models

[1729] The server generates appropriate responses using a generative AI model (e.g., GPT-3, BERT) based on the user's profile data and current situation data. The generative AI model takes these data as input and generates optimal suggestions and answers for the user.

[1730] Providing a response

[1731] The device displays the responses received from the server to the user, who can then review the suggestions and answers and ask further questions if necessary.

[1732] Examples of concrete examples and prompts

[1733] As a concrete example, consider a case where a user asks, "What outdoor activities are recommended for this weekend?" The server understands the user's outdoor interests from their past search history and social media posts, and retrieves current weather data. For example, if the weather is sunny, it will suggest hiking or a picnic.

[1734] Example prompt sentence:

[1735] User profile data:

[1736] Social media post: "I went hiking recently. It was so much fun!"

[1737] Purchase history: "Purchase outdoor equipment"

[1738] Search history: "Hiking trails near me"

[1739] Current weather data:

[1740] Region: Tokyo

[1741] Weather: Sunny

[1742] Prompt for the generative AI model:

[1743] "User is interested in outdoor activities and the weather is sunny right now. Can you suggest some outdoor activities for this weekend?"

[1744] In this way, the system makes appropriate suggestions that take into account the user's interests and current situation.

[1745] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1746] Step 1: Collect user data

[1747] The server collects data such as users' social media posts, purchase history, and search history. Specifically, it obtains data from social media platforms and e-commerce sites through APIs. For example, it uses the Twitter API to obtain users' tweets and the e-commerce site's API to collect purchase history. The input is the user's account information, and the output is the collected raw data.

[1748] Step 2: Preprocessing the data

[1749] The server preprocesses the collected data. Specifically, it cleans the text data (removes unnecessary characters and symbols), tokenizes it (divides it into words and phrases), and removes stop words. This is done using natural language processing libraries such as NLTK and spaCy. The input is the collected raw data, and the output is the preprocessed, clean data.

[1750] Step 3: Analyzing user interests and preferences

[1751] The server analyzes the user's interests and preferences based on the preprocessed data. Specifically, it uses machine learning models (e.g., TF-IDF, Word2Vec) to identify the user's interests. The results of this analysis are stored in a database as a user profile. The input is the preprocessed, clean data, and the output is profile data that indicates the user's interests and preferences.

[1752] Step 4: Get current situation data

[1753] The server retrieves data from external APIs (e.g., OpenWeatherMap API) to take into account the user's current situation (season, weather, local environmental issues, etc.), thereby understanding real-time weather information and local specific conditions. The input is the user's location, and the output is current situation data.

[1754] Step 5: Generative AI model generates a response

[1755] The server generates an appropriate response using a generative AI model (e.g., GPT-3, BERT) based on the user's profile data and current situation data. The generative AI model takes these data as input and generates optimal suggestions or answers for the user. The input is the user profile data and current situation data, and the output is the generated response.

[1756] Step 6: Providing a response

[1757] The terminal displays the responses received from the server to the user, who can then review the suggestions and answers and ask further questions if necessary. The input is the response generated, and the output is the information displayed to the user.

[1758] (Application example 1)

[1759] Next, a description will be given of Application Example 1 of Form 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."

[1760] In modern society, providing personalized advertisements based on users' interests and preferences is important, but conventional systems have difficulty generating advertisements that fully consider the user's profile and current situation. There is also a need to simultaneously provide environmentally friendly information and suggestions for sustainable living, but there is a lack of efficient ways to achieve this. Furthermore, a system is needed that can comprehensively analyze a variety of data, such as users' social media posts, purchase history, and search history, to generate optimal advertisements.

[1761] 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.

[1762] In this invention, the server includes means for analyzing a user's profile, interests, and current situation, means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for presenting methods for minimizing environmental impact and specific actions, means for analyzing the user's social media posts, purchase history, and search history to understand the user's interests and preferences, and means for generating and displaying advertisements that are optimal for the user, taking into account current conditions such as the season, weather, and local environmental issues. This makes it possible to comprehensively analyze a variety of user data and simultaneously provide personalized advertisements and environmentally friendly information.

[1763] A "user profile" is a collection of data including a user's personal information, behavioral history, interests, preferences, etc.

[1764] "Interests" refer to the things or areas in which a user is interested.

[1765] "Current situation" includes the environment and conditions in which the user finds himself, such as the season, weather, and local environmental issues.

[1766] "Means of analysis" refers to methods and technologies for analyzing a user's profile, interests, and current situation and extracting relevant information.

[1767] "Sustainable Living Advice" means providing advice and information to promote environmentally friendly lifestyles and behaviours.

[1768] "Recycling method" refers to the specific procedures and methods for reusing used products and waste materials.

[1769] "Energy saving tips" refers to specific advice and methods for reducing energy consumption.

[1770] "Methods of minimizing environmental impact" refers to specific measures and actions taken to reduce the burden on the environment.

[1771] "Means of presenting specific actions" refers to methods or techniques that show users specific actions they can actually take.

[1772] "SNS posts" refer to comments, photos, videos, etc. posted by users on social networking services.

[1773] "Purchase history" refers to a record of products and services a user has purchased in the past.

[1774] "Search history" refers to a record of searches a user has conducted on the Internet.

[1775] "Season" refers to the changes in weather that occur throughout the year.

[1776] "Weather" refers to the weather conditions in a particular area and at a particular time.

[1777] "Regional environmental issues" refers to environmental challenges and problems in a particular region.

[1778] "Means for generating and displaying advertisements" refers to methods and technologies for creating and displaying advertisements that are optimal for the user based on the user's interests and current situation.

[1779] A system for implementing this invention analyzes a user's profile, interests, and current situation to generate and display personalized advertisements. Specific embodiments are described below.

[1780] System Configuration

[1781] The system consists of the following main components:

[1782] 1. User device: The device used by the user, such as a smartphone or computer.

[1783] 2. Server: The central system that collects data, analyzes it, and generates advertisements.

[1784] 3. Database: Stores data such as user profiles, social media posts, purchase history, and search history.

[1785] Hardware and software used

[1786] Hardware: smartphones, PCs, servers

[1787] Software: Python, database management system (e.g., MySQL), API (SNS data, weather data, etc.)

[1788] Data collection and analysis

[1789] The server collects users' social media posts, purchase history, and search history. This data is obtained through APIs and stored in a database. The server then analyzes this data to understand users' interests and preferences.

[1790] Considering the current situation

[1791] The server obtains current information about the season, weather, local environmental issues, etc. This data is also collected in real time through APIs and stored in a database.

[1792] Ad generation and display

[1793] The server uses a generative AI model to generate optimal ads for users based on the collected user data and current situation data, and these ads are then displayed on the user's device.

[1794] Specific examples

[1795] For example, if a user posts on social media that they "love traveling" and recently purchased a "camera," an ad will be displayed on a sunny spring day saying, "Check out our travel guidebooks perfect for spring!"

[1796] Prompt Sentence Examples

[1797] "Generate ads that are best suited to users based on their social media posts, purchase history, and search history, taking into account the current season, weather, and local information."

[1798] In this way, it is possible to comprehensively analyze a variety of user data and simultaneously provide personalized advertising and environmentally friendly information.

[1799] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1800] Step 1:

[1801] The server collects users' social media posts, purchase history, and search history. This data is obtained through APIs and stored in a database. The input is the user's social media posts, purchase history, and search history, and the output is the user data stored in the database. Specifically, the server sends requests to each API and stores the obtained data in the database.

[1802] Step 2:

[1803] The server analyzes the user data stored in the database to understand the user's interests and preferences. The input is the user data stored in the database, and the output is the analysis results regarding the user's interests and preferences. Specifically, the server uses a data analysis algorithm to analyze the user data and extract the interests and preferences.

[1804] Step 3:

[1805] The server obtains current information such as the season, weather, and local environmental issues. This data is also collected in real time through APIs and stored in a database. The input is data on the season, weather, and local environmental issues, and the output is the current situation data stored in the database. Specifically, the server sends requests to each API and stores the obtained data in the database.

[1806] Step 4:

[1807] The server uses a generative AI model to generate the optimal ad for the user based on the collected user data and current situation data. The input is user data and current situation data, and the output is the generated ad. Specifically, the server inputs a prompt sentence into the generative AI model to generate the optimal ad.

[1808] Step 5:

[1809] The server sends the generated advertisement to the user terminal for display. The input is the generated advertisement, and the output is the advertisement displayed on the user terminal. In specific operations, the server sends advertisement data to the user terminal, and the terminal displays it.

[1810] Step 6:

[1811] Users review the ads displayed and take action if necessary. The input is the displayed ad, and the output is the user's action, such as clicking on the ad or purchasing a related product or service.

[1812] Example 2

[1813] Next, a description will be given of Example 2 of Form 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."

[1814] In modern society, achieving a sustainable lifestyle requires specific proposals and guidelines tailored to each individual user. However, existing systems do not adequately provide customized information based on the user's living environment and lifestyle, making it difficult to achieve a sustainable lifestyle.

[1815] 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.

[1816] In this invention, the server includes means for inputting data related to the user's living environment and lifestyle, means for transmitting the input data to the server, means for the server to receive and preprocess the data, means for inputting the preprocessed data into a machine learning model and analyzing it, means for generating suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results, means for transmitting the generated information to the terminal, and means for displaying the information received by the terminal to the user. This makes it possible to provide specific sustainable living suggestions and guidelines for action tailored to the user.

[1817] "Data about the user's living environment and lifestyle" refers to information such as the user's energy consumption in daily life, the home appliances they use, and their recycling habits.

[1818] "Input means" refers to interfaces such as applications or web forms through which users input data about their living environment and lifestyle.

[1819] "Means of sending to the server" refers to the communication protocol and network infrastructure used to send the data entered by the user to the server.

[1820] "Preprocessing means" refers to algorithms and software used to process the data received by the server, such as filling in missing values ​​and normalizing the data.

[1821] "Means for inputting and analyzing machine learning models" refers to software and hardware used to run machine learning algorithms on pre-processed data and analyze user data.

[1822] "Means for generating sustainable living suggestions, recycling methods, and energy-saving tips" refers to algorithms and software that generate specific guidelines and advice for users based on the analysis results of machine learning models.

[1823] "Means for transmitting generated information to the terminal" refers to the communications protocol and network infrastructure used to transmit the server-generated suggestions and hints to the user's terminal.

[1824] "Means for displaying to the user the information received by the terminal" refers to a display or application that visually displays the information received by the user's terminal from the server.

[1825] This invention is a system that collects data on a user's living environment and lifestyle, and provides suggestions for sustainable living, recycling methods, and energy-saving tips. Specific embodiments of this system are described below.

[1826] First, users use a dedicated application or web form to enter data about their living environment and lifestyle, such as their household energy consumption, the appliances they use, and their recycling habits.

[1827] The device then sends the entered data to the server using the HTTPS protocol to ensure data security.

[1828] The server receives the data sent from the device. The received data is converted into a data frame using Pandas. Next, preprocessing such as filling in missing values ​​and normalizing the data is performed. For example, missing values ​​are filled in with the mean value, and numerical data is normalized to the range of 0 to 1.

[1829] The preprocessed data is then fed into a machine learning model generated using Scikit-learn and TensorFlow, which then performs analysis of the user's data for sustainable living, such as analyzing electricity consumption patterns and assessing potential energy savings.

[1830] The server generates personalized recommendations based on the analysis results, such as "By setting the refrigerator temperature appropriately, you can reduce your annual electricity consumption by 10%."

[1831] The generated suggestions and hints are sent from the server to the device, again using the HTTPS protocol to ensure data security.

[1832] The device receives the information from the server and displays it to the user, who can then take specific actions to practice sustainable living based on the information displayed.

[1833] As a concrete example, if a user is interested in "ways to save energy at home," the following prompt sentence can be input into the generative AI model:

[1834] Generate suggestions for energy conservation methods at home based on the user's living environment data.

[1835] Using this prompt, the generative AI model can provide specific energy-saving tips tailored to the user.

[1836] As described above, the present invention is a system that provides suggestions for a sustainable lifestyle based on the user's living environment and lifestyle, and can provide the user with specific guidelines for action.

[1837] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1838] Step 1:

[1839] The user inputs data about their living environment and lifestyle.

[1840] Users use dedicated applications or web forms to enter information such as their household energy consumption, the appliances they use, their recycling habits, etc. The input data can include numerical and textual data.

[1841] Step 2:

[1842] The terminal transmits the input data to the server.

[1843] The terminal sends the data entered by the user to the server in real time using the HTTPS protocol to ensure data security. The input data is sent to the server in JSON format.

[1844] Step 3:

[1845] The server receives the data and performs pre-processing.

[1846] The server receives the data sent from the device. The received data is converted into a data frame using Pandas. Next, preprocessing such as filling in missing values ​​and normalizing the data is performed. For example, missing values ​​are filled in with the mean value, and numerical data is normalized to the range from 0 to 1. As a result of the preprocessing, a clean dataset is obtained.

[1847] Step 4:

[1848] The server inputs the preprocessed data into a machine learning model for analysis.

[1849] The server inputs the preprocessed data into a machine learning model generated using Scikit-learn and TensorFlow. The model then performs analysis on sustainable living based on the user's data. For example, it analyzes electricity consumption patterns and evaluates energy conservation opportunities. As a result of the analysis, specific recommendations are generated for the user.

[1850] Step 5:

[1851] Based on the analysis results, the server generates suggestions for sustainable living, recycling methods, and energy-saving tips.

[1852] The server generates suggestions tailored to the user based on the analysis results of the machine learning model. For example, it generates specific advice such as, "By setting the refrigerator temperature appropriately, you can reduce your annual electricity consumption by 10%." The generated suggestions are saved in text format.

[1853] Step 6:

[1854] The server transmits the generated information to the terminal.

[1855] The server then sends the generated suggestions and hints to the device, again using the HTTPS protocol to ensure data security. The data is sent to the device in JSON format.

[1856] Step 7:

[1857] The terminal displays the received information to the user.

[1858] The device receives the information from the server and displays it to the user, who can then take specific actions to practice sustainable living based on the information displayed. For example, the application's notification function can be used to notify the user of suggestions in real time.

[1859] (Application example 2)

[1860] Next, a description will be given of Application Example 2 of Form 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."

[1861] In modern society, in order to achieve a sustainable lifestyle, it is important for individual consumers to take environmentally conscious actions. However, consumers often do not have enough information to understand what actions have a positive impact on the environment. In addition, there is a lack of means to provide real-time information on environmental considerations while shopping in physical stores, making it difficult for consumers to take appropriate actions immediately.

[1862] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a user's profile, interests, and current situation; means for providing information tailored to each individual user, such as suggestions for sustainable living, recycling methods, and energy-saving tips based on the analysis results; means for suggesting ways to minimize environmental impact and specific actions; means for providing environmentally conscious information related to a product when the user scans the product; and means for displaying the provided information on the user's smartphone. This allows consumers to obtain environmentally conscious information in real time while shopping in a physical store, enabling them to immediately take specific actions to achieve a sustainable lifestyle.

[1863] A "user profile" is a collection of data including a user's personal information, interests, behavioral history, etc.

[1864] "Interests" is information about areas or topics that a user is interested in.

[1865] "Current situation" refers to real-time information such as the user's current geographic location, time, and activity status.

[1866] "Analysis results" are data and insights generated based on a user's profile, interests, and current situation.

[1867] "Sustainable living" refers to living in a way that is environmentally friendly, does not waste resources, and is sustainable in the long term.

[1868] "Suggestion" refers to a specific action or option offered to the user.

[1869] A "recycling method" is a specific procedure or method for converting used products or waste into a reusable form.

[1870] "Energy saving tips" are specific advice and methods for reducing energy consumption.

[1871] "Environmental impact" refers to the impact that a user's actions and choices have on the natural environment.

[1872] "Specific actions" are concrete actions or steps that users can actually take.

[1873] "Scanning an item" refers to the act of using a smartphone or other device to read the barcode or QR code on an item.

[1874] "Environmentally friendly information" refers to environmentally friendly information such as the product's manufacturing process, materials, and recycling methods.

[1875] A "smartphone" is a type of mobile phone that can connect to the Internet and use applications.

[1876] The system for implementing this invention analyzes a user's profile, interests, and current situation, and provides suggestions for sustainable living, recycling methods, and energy-saving tips. Specific embodiments of this system are described below.

[1877] First, a dedicated application is installed on the user's smartphone. This application has a function that allows the user to scan products. When the user scans a product in a physical store, the product ID is sent to the server.

[1878] The server, built using the Flask framework, receives a product ID and then calls an external API to retrieve relevant eco-friendly information about that p...

Claims

1. Means of analysing users' profiles, interests and current situations; A means for providing information tailored to each of the users regarding suggestions for sustainable living, recycling methods, and energy saving tips based on the analysis results by the analyzing means; A means for presenting to the user methods and specific actions for minimizing the impact on the environment; means for collecting, pre-processing and analyzing the user's interests and preferences; means for obtaining current context data of said user from an external data source; means for generating a response to the user based on a current situation of the user using a generative AI model; a means for providing the generated response to a user; A system including:

2. 10. The system according to claim 1, further comprising a means for providing information on environmentally friendly products and services.

3. 10. The system of claim 1, further comprising means for customizing the information provided to a user.

Images