System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving registration information of a user; means for analyzing a skill of the user based on the registration information; means for proposing an optimal work or activity based on the skill; and means for notifying the user of a result of the proposal.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 modern society, it is difficult for forestry workers and forest conservationists to efficiently find the most suitable jobs and activities. For this reason, there is an increasing need to effectively connect stakeholders in forest protection and sustainable forest management. Furthermore, there is a need for concrete efforts to improve the global environment and achieve carbon neutrality, but there is a lack of a platform to support these efforts. This system is intended to solve these issues. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing the following means. Specifically, the system includes a means for receiving user registration information and a means for analyzing the user's skills based on the registration information. It also includes a means for proposing optimal jobs and activities based on the skills and a means for notifying the user of the results of the proposal. This system accurately grasps the user's skills and interests and uses an algorithm using artificial intelligence to suggest optimal jobs and activities, thereby supporting matching between different industries and realizing sustainable forest conservation. The system is also expected to contribute to carbon neutrality.

[0006] "User" means any natural or legal person who uses the System and has an interest in forest-related tasks or activities.

[0007] "Registration Information" refers to personal information, skill information, and other related information provided by a User to the System.

[0008] "Skills" refer to the abilities and knowledge required for a user to perform a specific job or activity.

[0009] "Analyzing" is the process of evaluating a user's skills and interests based on their registration information to identify the most suitable jobs and activities.

[0010] "Best jobs and activities" refer to forest-related jobs and volunteer activities that best suit the user based on the analysis results.

[0011] "Means" refers to the methods or techniques used to achieve a particular goal.

[0012] "Suggestion" refers to the act of presenting the most suitable job or activity to the user based on the analysis results.

[0013] "Notification" refers to the process of communicating the results of a proposal to the user, and includes methods such as email, in-app notification, and SMS.

[0014] "Matching" is the process of using AI algorithms to select and connect users with jobs and activities that best suit their skills and interests. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] This invention is a system that matches a wide range of forest-related jobs with the aim of protecting forests and improving sustainable living environments. The system suggests optimal jobs and activities based on the user's skills and promotes communication and information sharing among users. The system also makes full use of artificial intelligence (AI) technology to precisely suggest optimal jobs and activities for users.

[0037] System configuration

[0038] 1. Server:

[0039] The server receives the registration information entered by the user and stores it in a database. The server also analyzes the user's information, performs matching processing, and operates an algorithm to suggest the most suitable jobs and activities.

[0040] 2. Terminal:

[0041] Users access the system using a terminal and enter their registration information and skill information. The terminal communicates with the server, receives notifications and suggestions from the server, and displays them to the user.

[0042] 3. User:

[0043] Users use the system based on their skills and interests by registering their user information and then checking the system's suggestions for suitable jobs and activities.

[0044] Program processing

[0045] The specific processing of this system will be explained in natural language below.

[0046] 1. User enters registration information:

[0047] Users access the system from a terminal and enter required information into a registration form, including their username, skills, and job or activity interests.

[0048] 2. Data transmission by the device:

[0049] The information entered by the user is sent from the terminal to the server, which receives the information and stores it in a database.

[0050] 3. User information registration by the server:

[0051] The server stores the received user information in a database and performs analysis to identify the most suitable jobs and activities based on the user's skills and interests.

[0052] 4. The server performs the matching process:

[0053] The server uses AI algorithms to analyze the user's skills and search the database for the most suitable jobs and activities. Based on the analysis results, it generates the best matching results.

[0054] 5. Server generates matching results:

[0055] The server generates matching results and formulates a response to notify the user, which includes details of the jobs and activities that are most suitable for the user.

[0056] 6. Receiving and displaying results on the device:

[0057] The device receives the response from the server and displays it in an easy-to-read format for the user, who can then review the results and take specific actions to participate in the jobs or activities that interest them.

[0058] Specific examples

[0059] For example, user "Taro Tanaka" has forestry-related skills such as "logging," "chainsaw operation," and "tree planting." Taro Tanaka accesses the system and registers these skills. The server receives Taro Tanaka's information and stores it in a database. An AI algorithm is used to analyze Taro Tanaka's skills and suggests "forestry worker" or "volunteer tree planting" as suitable jobs. The server sends this suggestion result to Taro Tanaka's device as a response, and Taro Tanaka can check the proposed jobs on his device. If Taro Tanaka is interested in the proposed jobs and takes specific action, he can participate in sustainable forest conservation.

[0060] In this way, this system can contribute to nature conservation and improving living conditions.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] Users access the system from a terminal and fill out a registration form, including their username, skills, and job and activity interests.

[0064] Step 2:

[0065] The terminal collects the information entered by the user and sends it to the server. Specifically, the terminal sends the registration information to the server via an HTTP request.

[0066] Step 3:

[0067] The server analyzes the registration information received from the device and saves it in a database, which stores the user's basic information and skill information.

[0068] Step 4:

[0069] The server analyzes the user's skills based on the user information stored in the database, which is the process of identifying and tagging the skills that the user possesses.

[0070] Step 5:

[0071] The server uses AI algorithms to find the best jobs and activities based on the user's skills and interests, comparing the job information in the database with the user's skills to identify matching jobs and activities.

[0072] Step 6:

[0073] The server generates the results of the matching process and forms a response to notify the user, including details of the jobs and activities that are best suited for the user.

[0074] Step 7:

[0075] The device receives the response from the server and displays the results to the user, who can then view the details of the proposed tasks and activities on the device screen.

[0076] Step 8:

[0077] Based on the displayed suggestions, users can select specific actions (such as applying or contacting the organization) and participate in sustainable forest conservation.

[0078] Example 1

[0079] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0080] In modern society, forest conservation and the improvement of sustainable living environments are important issues. However, it is extremely difficult for people interested in forest-related occupations and activities to find the most suitable job or activity based on their skills. Conventional methods have a low matching accuracy between users' skills and occupations or activities, making it difficult for users to select occupations or activities that are efficient for them. To solve this problem, the present invention aims to provide a more precise and efficient matching system that makes full use of artificial intelligence technology.

[0081] 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.

[0082] In this invention, the server includes means for receiving registration information of a user, means for storing the registration information in a database, means for analyzing the user's skills based on the registration information, means for searching for optimal jobs or activities based on the skills using an artificial intelligence model, means for generating the proposal results in JSON format, means for notifying the user's terminal of the proposal results, and means for displaying the proposal results on the user's terminal, thereby enabling users to easily find jobs or activities that are optimal for their skills.

[0083] The "means for receiving user registration information" is a function that allows the system to receive information about personal information, skills, and jobs and activities of interest provided by the user.

[0084] The "means for storing the registration information in a database" is a function for recording the received user registration information in a database in order to store it permanently.

[0085] The "means for analyzing the skills of the user based on the registered information" is a function for analyzing the skills possessed by the user using the saved user information.

[0086] "Means for searching for optimal jobs or activities based on the skills using an artificial intelligence model" refers to a function that analyzes a user's skill data using artificial intelligence technology (e.g., a TensorFlow model) and identifies the most suitable job or activity.

[0087] The "means for generating the proposal results in JSON format" is a function for formatting the data obtained as a result of the matching process in JSON format and preparing it as a response from the system.

[0088] The "means for notifying the user terminal of the proposal result" is a function for transmitting the proposal result generated by the server to the user terminal via the network and notifying the user terminal.

[0089] The "means for displaying the proposal results on the user's terminal" is a function for the terminal to analyze the proposal results received from the server and display them in an easy-to-understand manner for the user.

[0090] The present invention is a system for protecting forests and improving sustainable living environments, and suggests optimal jobs and activities based on the user's skills. Specific embodiments for carrying out the present invention are described below.

[0091] This system mainly consists of a server, terminals, and users.

[0092] 1. Server configuration and functions

[0093] The server receives the user's registration information, stores it in a database, analyzes their skills based on the information, and proposes the most suitable jobs and activities. Specifically, the server uses the following hardware and software:

[0094] Hardware: High-performance server (with CPU, memory, and large-capacity storage)

[0095] software:

[0096] Database management system (e.g. MySQL)

[0097] AI analysis model (e.g. TensorFlow)

[0098] JSON parser and HTTP communication library (e.g. FastAPI)

[0099] The server first receives registration information from the user via the device and securely communicates it using the HTTPS protocol. The server then stores the received information in a MySQL database. The stored data is analyzed using a TensorFlow model to suggest optimal jobs and activities based on the user's skills. The proposed results are generated in JSON format and sent as a response to the device.

[0100] 2. Device configuration and functions

[0101] A terminal is a device through which a user accesses the system and enters registration information. Specifically, this includes a smartphone or a PC. The following software is used on the terminal:

[0102] Browser or dedicated application

[0103] Front-end libraries (e.g. React.js)

[0104] When a user accesses the system from a terminal, a registration form is displayed. The user enters their name, skills, and job and activity interests in this form and presses the submit button. The terminal converts this information into JSON format and sends it to the server using the HTTPS protocol. When the terminal receives the proposal results from the server, it analyzes them and displays them in an easy-to-read format for the user.

[0105] 3. User Operation

[0106] Users access the system using their terminal and enter their registration information. For example, if user "Yamada Jiro" has the skills "tree cutting" and "tree planting," he enters this information into the form and submits it. At this time, the server analyzes Yamada Jiro's skill information and uses an AI model to suggest the most suitable jobs and activities. The results of these suggestions are sent to the terminal, where Yamada Jiro can view them and take specific actions to participate in activities that interest him.

[0107] Examples and prompts

[0108] For example, if user "Yamada Jiro" has forestry-related skills such as "logging," "chainsaw operation," and "tree planting," he registers these skills in the system. The server receives Yamada Jiro's information and stores it in a database. An AI model using TensorFlow analyzes Yamada Jiro's skills and suggests "forestry worker" or "tree planting volunteer" as the most suitable jobs. The server sends these suggestions to the device in JSON format, allowing Yamada Jiro to check this information on his own device.

[0109] Prompt Sentence Examples

[0110] "Build a system that suggests the best jobs for users with forest conservation skill sets."

[0111] "Create an AI model that takes user skills as input and matches them with the best forestry-related jobs."

[0112] Through this system, users can easily find jobs and activities that best suit their skills, thereby making a significant contribution to protecting nature and improving living conditions.

[0113] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0114] Step 1:

[0115] User enters registration information

[0116] Users access the system using a terminal and enter their information into the registration form. The input data includes their username, skills (e.g., "tree cutting," "chainsaw operation," "tree planting," etc.), and jobs or activities of interest. Once the input is complete, the user presses the send button, and this data is sent from the terminal to the server. The input data is in JSON format.

[0117] Step 2:

[0118] Sending data by the device

[0119] The terminal sends the registration information provided by the user to the server. Specifically, the terminal encodes the input data in JSON format and securely transmits the data to the server using the HTTPS protocol. The server endpoint is, for example, / api / user / register. The input in this case is the registration information provided by the user, and the output is an HTTPS request to the server.

[0120] Step 3:

[0121] Registration of user information by the server

[0122] The server receives the user information sent from the terminal and stores it in the database. Specifically, the server parses the received JSON data and saves it as a new user record in the MySQL database. The SQL query used is an INSERT statement. The input to this step is the JSON data sent from the terminal, and the output is the user information stored in the database.

[0123] Step 4:

[0124] Matching is performed by the server

[0125] The server uses an AI model to analyze the optimal jobs and activities based on the stored user information. This process uses TensorFlow. The server inputs the stored skill data into the AI ​​model, extracts the skill characteristics, and searches the database for jobs and activities based on them. The output is a list of jobs and activities optimal for the user. The input to this step is the user skills stored in the database, and the output is the analysis results from the AI ​​model.

[0126] Step 5:

[0127] Server-generated matching results

[0128] The server proposes optimal jobs and activities to the user based on the analysis results obtained from the AI ​​model. Specifically, it generates detailed information about the proposal in JSON format. These details include the job title, job description, location, and how to apply. The input to this step is the analysis results from the AI ​​model, and the output is a JSON response containing the proposal results.

[0129] Step 6:

[0130] Receiving and displaying results on the device

[0131] The device receives the response from the server and displays it to the user. Specifically, it parses the received JSON data and displays it on the UI using a front-end framework such as React.js. The user can view detailed information about the proposed jobs and activities and take specific actions to participate in activities that interest them. The input is the JSON response from the server, and the output is the proposal results displayed on the user's screen.

[0132] This processing step allows users to easily find jobs and activities that best suit their skills.

[0133] (Application example 1)

[0134] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0135] In conventional factories, there has been a lack of systems that efficiently match the skills of robot workers with task requirements, which has led to reduced work efficiency and problems with collaboration between humans and robots. Furthermore, the inability to assign the right tasks to the right robots has hindered productivity improvement. To solve these problems, the present invention aims to provide a system that performs optimal matching based on robot skill information and the required task skills.

[0136] 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.

[0137] In this invention, the server includes means for receiving user registration information, means for analyzing the user's skills based on the registration information, means for proposing optimal jobs and activities based on the skills, means for notifying the user of the results of the proposal, means for receiving and saving robot skill information, means for analyzing the required skills of tasks, means for comparing the robot skill information with the required skills of tasks and assigning optimal tasks, and means for displaying the assignment results. This makes it possible to efficiently match robot operators with tasks in a factory, thereby improving productivity and optimizing work efficiency.

[0138] "Users" are individuals or companies who use the system to enter their skills and registration information.

[0139] "Registration information" refers to information that users enter into the system, including data such as skills, interests, and work experience.

[0140] "Skills" are information that represents the specialized abilities, techniques, and aptitudes possessed by users and robots.

[0141] "Analysis" refers to data processing and evaluation to identify the most suitable jobs and tasks based on registration information and skill information.

[0142] "Proposal" is the act of the system showing the user or robot the optimal job or task based on the analysis results.

[0143] "Server" is the central computer of the system, and is a device that receives, stores, analyzes, and performs proposal functions for data.

[0144] A "robot" is a mechanical device that performs work in a factory, has skill information, and is used to perform specific tasks.

[0145] A "task" refers to a specific task or activity to be performed within a factory, with required skills and conditions specified.

[0146] "Required skills" is information that indicates the abilities and techniques required to perform a specific task.

[0147] "Matching" is the process or act of comparing the skill information of the robot or user with the skills required for the task to find the optimal combination.

[0148] "Notification" refers to the act of the system communicating the proposal results and matching results to the user or robot administrator.

[0149] "Comparison" refers to the act of comparing two or more elements, namely the robot's skill information and the required skills of the task, and evaluating the degree of agreement.

[0150] The present invention provides a system for realizing efficient task allocation for robot workers in a factory. The system includes a server, a terminal, a user, and a robot.

[0151] The server receives the user's registration information and stores it in a database. The server analyzes the user's skills based on this registration information and runs an algorithm to suggest the most suitable jobs and activities. The main software used by the server includes Python and scikit-learn, which vectorize the user's skill information and compare it with the required skills of the task.

[0152] Specifically, the system receives registration information and stores it in a database. Next, it generates a skill vector using an AI model (e.g., TfidfVectorizer) based on the registered skill information. The required skills of the task are then similarly vectorized and analyzed using methods such as cosine similarity. This allows it to identify the optimal combination of robot and task and generate a proposal.

[0153] The terminal is used by users to access the system and enter their registration information and skill information. Notifications and proposals from the server are also displayed on the terminal. Terminals can be smartphones, tablets, or PCs.

[0154] Users access the system through their devices and input their skills and interests. The server then suggests suitable jobs and activities and notifies the user. For example, if a user has skills such as "welding," "cutting," and "assembly," the server will suggest tasks such as "welder" or "assembler" based on those skills.

[0155] In addition, robots can register their own skill information with the server to perform tasks within the factory. The server uses this information to assign the robot the most suitable tasks. For example, if a robot has the skills of "painting" and "spraying," the server will suggest tasks such as "painting work" based on that.

[0156] As an example of this system-wide behavior, the following prompt sentence is used:

[0157] "Robot A has welding and cutting skills. We currently have a task to perform welding and cutting work. Which robot is best?"

[0158] "Robot B has the skills to paint and spray, and we currently have a painting task. Which robot is best suited to the task?"

[0159] This invention enables efficient matching of robot operators with tasks within a factory, improving productivity and optimizing work efficiency.

[0160] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0161] Step 1:

[0162] A user accesses the system using a terminal and enters the necessary information into the registration form, including the user name, skills, and jobs and activities that the user is interested in. This input data is considered the initial input.

[0163] Step 2:

[0164] The device sends the information entered by the user to the server. The specific data is text data such as username, skills, interests, etc., and is transferred to the server via a communication protocol. The server receives this data and stores it as an initial database entry.

[0165] Step 3:

[0166] The server stores the received user information in a database and vectorizes the registered skill information using an AI model (e.g., TfidfVectorizer). The vectorized skill information is used for subsequent analysis processing. The input is text data, and the output is vector data.

[0167] Step 4:

[0168] When a user creates a new task, they input the required skills and details of the task into the terminal and send it to the server. The terminal accurately transfers this task information to the server and stores it in the task database. The input is the text data of the task, and the output is a task database entry.

[0169] Step 5:

[0170] The server also vectorizes the required skill information of the task and calculates the cosine similarity between the skill vector and the task vector. This evaluates the degree to which the skill information of the registered robot or user matches the required skill of the task. The input is vector data, and the output is a similarity score.

[0171] Step 6:

[0172] The server matches the best robots and users to each task based on the cosine similarity score. The robots and users with the highest scores are selected and recorded as the matching results. The input is the similarity score, and the output is the best matching information.

[0173] Step 7:

[0174] The server generates a response based on the generated matching results and notifies the device. The results include details of the robot and user best suited for each task. The device receives the results and displays them in an easy-to-read format for the user. The input is the matching information, and the output is notification data.

[0175] Step 8:

[0176] The user checks the notification results through their terminal and takes specific actions for the proposed work or task. The user uses an interface to confirm acceptance of a new task or start of work, and sends the results to the server. The input is the user's action data, and the output is the action result.

[0177] Through these steps, efficient matching of robots and tasks within the factory is achieved.

[0178] 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.

[0179] This invention aims to protect forests and improve sustainable living environments by suggesting optimal jobs and activities based on the user's emotional state using a system that combines an emotion engine. By taking into account not only the user's skills but also their emotions, this system achieves more precise and personalized suggestions.

[0180] System configuration

[0181] 1. Server:

[0182] The server receives the registration information entered by the user and stores it in a database. Furthermore, the server has an algorithm for analyzing the user's skills and emotions and executing the matching process. The server also uses an emotion engine to analyze the user's emotional state and suggest optimal jobs and activities based on that data.

[0183] 2. Terminal:

[0184] Users access the system using a terminal and enter their registration information, skill information, and current emotional state. The terminal communicates with the server, receives notifications and suggestions from the server, and displays them to the user.

[0185] 3. User:

[0186] Users use the system based on their skills, interests, and emotional state. Specifically, they register their user information, check the optimal jobs and activities suggested by the system, and even input their own emotional state.

[0187] Program processing

[0188] The specific processing of this system will be explained in natural language below.

[0189] 1. User enters registration information:

[0190] Users access the system from a terminal and fill out a registration form with required information, including their username, skills, and job and activity interests, as well as their current emotional state.

[0191] 2. Data transmission by the device:

[0192] The information entered by the user is sent from the device to the server. Specifically, the device sends the registration information and emotional state to the server via an HTTP request.

[0193] 3. User information registration by the server:

[0194] The server analyzes the registration information and emotional state received from the device and stores it in a database, which stores the user's basic information, skill information, and emotional information.

[0195] 4. Skill and emotion analysis by the server:

[0196] The server analyzes the user's skills and emotional state based on the user information stored in the database. This analysis is a process of identifying and tagging both the skills and emotions possessed by the user.

[0197] 5. The server performs the matching process:

[0198] The server uses AI algorithms to search for the best jobs and activities based on the user's skills and emotional state, comparing job information in the database with the user's skills and emotions to identify matching jobs and activities.

[0199] 6. Server-based suggestion adjustment based on emotions:

[0200] The server also uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions accordingly: for example, if the user is under stress, it will prioritize activities that will reduce stress.

[0201] 7. Server generates matching results:

[0202] The server generates a matching result and formulates a response to notify the user, including details of the job or activity that best suits the user and adjustments that take into account their emotional state.

[0203] 8. Receiving and displaying results on the device:

[0204] The device receives the response from the server and displays the results to the user, who can view the details of the suggested tasks and activities, as well as adjustments that take into account the user's emotional state, on the device screen.

[0205] 9. User confirms the results and selects an action:

[0206] Based on the displayed suggestions, users can select specific actions (such as applying or contacting the organization) to participate in sustainable forest conservation. By taking emotional state into consideration in this way, more personalized suggestions can be made, increasing user satisfaction.

[0207] Specific examples

[0208] For example, user "Sato Hanako" accesses the system and registers her skills of "tree planting" and "forest cultivation," and selects "feeling stressed" as her current emotional state. The server receives this information and stores it in a database. After analyzing it using an AI algorithm, it suggests "forest therapy guide" and "tree planting volunteer" to Sato Hanako. The emotion engine also takes into account her stress level and prioritizes recommending "forest therapy guide," which is expected to have a particularly relaxing effect.

[0209] The results of these suggestions are displayed on the device, and Sato Hanako uses this information to participate in the activities as a "forest therapy guide." In this way, by using this system, optimal suggestions are made that reflect the user's skills and emotional state, contributing to sustainable forest conservation activities.

[0210] The processing flow will be explained below.

[0211] Step 1:

[0212] Users access the system from a terminal and enter required information into a registration form, including their username, skills, and job and activity interests, as well as their current emotional state.

[0213] Step 2:

[0214] The device collects the information entered by the user and sends it to the server via an HTTP request, specifically, the user's username, skill information, job and activity interests, and emotional state.

[0215] Step 3:

[0216] The server analyzes the registration information and emotional state received from the device and stores them in a database, which stores the user's basic information, skill information, and emotional information.

[0217] Step 4:

[0218] The server analyzes the user's skills and emotional state based on the user information stored in the database. Specifically, it performs an analysis process to identify the user's skill set and current emotional state and tag them.

[0219] Step 5:

[0220] The server uses an AI algorithm to search for the best jobs and activities based on the user's skills and emotional state. It compares the job information in the database with the user's skills and emotions to identify matching jobs and activities. For example, based on the skill of "planting a tree" and the emotional state of "feeling stressed," activities with a relaxing effect will be prioritized.

[0221] Step 6:

[0222] The server also uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions accordingly. For example, if the user is under stress, it will prioritize activities that will help reduce stress.

[0223] Step 7:

[0224] The server generates a response based on the results of the matching process and emotion-based adjustments, including details of the optimal task or activity for the user and adjustments that take into account the user's emotional state.

[0225] Step 8:

[0226] The device receives the response from the server and displays the results to the user, including details of the suggested tasks and activities, as well as adjustments that take into account the user's emotional state.

[0227] Step 9:

[0228] The user can check the suggestions displayed on the device and select a specific action. For example, the user can select the "Forest Therapy Guide" suggestion and participate in the activity to contribute to sustainable forest conservation.

[0229] In this way, the system can suggest optimal tasks and activities that take into account the user's skills and emotional state, increasing user satisfaction and contributing to sustainable forest conservation.

[0230] Example 2

[0231] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0232] Previous job and activity suggestion systems mainly based their suggestions on the user's skills and rarely took the user's emotional state into consideration. This meant that they were unable to provide appropriate suggestions to users who felt stressed or dissatisfied, making it difficult to increase user satisfaction. Furthermore, they lacked the ability to analyze the user's emotional state in real time and adjust the suggestions accordingly.

[0233] 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.

[0234] In this invention, the server includes means for receiving registration information of a user, means for analyzing the user's skills based on the registration information, means for analyzing the user's emotional state based on the registration information, means for proposing optimal jobs and activities based on the skills and emotional state, means for adjusting the content of the proposal in real time based on the emotional state, and means for notifying the user of the proposal results. This enables more precise and personalized proposals that take the user's emotional state into consideration, thereby increasing user satisfaction.

[0235] "User" refers to a person who uses the system to input registration information, skills, and emotional state and is then suggested suitable jobs and activities.

[0236] "Registration Information" refers to information used within the system, such as a user's name, skills, and emotional state.

[0237] "Skills" refers to the knowledge, abilities, and experience that a user possesses, and serve as the basis for making proposals.

[0238] "Emotional state" refers to the emotional state the user is currently feeling, information that is used to tailor suggestions.

[0239] "Server" refers to the central computer system that receives and analyzes users' registration information and makes optimal suggestions.

[0240] "Analysis" refers to the process by which the system processes, understands, and classifies data such as registration information, skills, and emotional state.

[0241] "Suggestion" refers to the act of suggesting the best job or activity based on the user's skills and emotional state.

[0242] "Real-time" means that the system processes the information it receives immediately and reflects the results immediately.

[0243] "Notification" refers to the act of the system communicating analysis results and suggestions to the user.

[0244] This invention aims to protect forests and improve sustainable living environments by proposing optimal tasks and activities based on the user's emotional state. The system is primarily composed of three elements: a server, a terminal, and the user.

[0245] System Configuration

[0246] 1. Server:

[0247] The server has the function of receiving registration information entered by the user and storing it in a database.

[0248] The server is equipped with algorithms to analyze the user's skills and emotional state.

[0249] It is equipped with an emotion engine that analyzes the user's emotional state in real time and adjusts the suggestions it makes.

[0250] A proposal result is generated and notified to the user.

[0251] 2. Terminal:

[0252] Users use terminals to access the system and enter information.

[0253] The terminal communicates with the server, receives notifications and proposal results from the server, and displays them.

[0254] 3. User:

[0255] The user uses the terminal to input their registration information, skill information, and emotional state.

[0256] Review and select the suggested tasks and activities.

[0257] Example

[0258] For example, when a user named "Hanako Sato" accesses the system, a registration form appears on the device's web page. She enters her name, her skills of "tree planting" and "forest cultivation," and her current emotional state as "feeling stressed." The device then sends this information to the server.

[0259] The server analyzes the information it receives and stores it in a database, using natural language processing (NLP) techniques to tag skills and emotional states. AI algorithms within the server then search for the most suitable jobs and activities based on these tags. For example, for the skill "tree planting" and the emotional state "feeling stressed," "forest therapy guide" and "tree planting volunteer" are suggested.

[0260] Furthermore, the emotion engine adjusts the suggestions in real time based on the analysis results stored on the server. For example, if Sato Hanako is feeling stressed, the Forest Therapy Guide, which is expected to have a relaxing effect, will be recommended first.

[0261] The results of these proposals are sent from the server to the device and displayed on the device screen. Hanako Sato checks the proposed jobs and activities and participates in the activities as a "forest therapy guide."

[0262] Examples of prompts used in queries

[0263] Based on the prompt sentence, "What kind of activity would have a relaxing effect on a user who is feeling stressed?", the emotion engine makes appropriate suggestions.

[0264] Hardware and software used

[0265] Server: High-performance cloud server (e.g. AWS, Google Cloud)

[0266] Emotion engine: Analysis engine using NLP technology (e.g., OpenAI, Google AI)

[0267] Database: Relational database (e.g. MySQL, PostgreSQL)

[0268] Terminals: General-purpose devices such as PCs, smartphones, and tablets

[0269] This allows for more refined and personalized suggestions that take into account the user's emotional state, enabling them to actively participate in sustainable forest conservation efforts.

[0270] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0271] Step 1:

[0272] Users access the system using their own terminals and enter the necessary information (user name, skills, job interests and activities, emotional state) into the registration form. For example, "Hanako Sato" enters the skills "tree planting" and "forest cultivation" and selects "feeling stressed" as her emotional state. Once the input is complete, the terminal sends this information to the server.

[0273] Step 2:

[0274] The device forms the information entered by the user into an HTTP request and sends it to the server. This request contains the user's name, skills, activities of interest, and emotional state in JSON format. Input data: User name, skills, emotional state, activities of interest. Output data: HTTP request containing these.

[0275] Step 3:

[0276] The server analyzes the HTTP request received from the terminal and extracts the user information. It then stores this information in a database. Input data: User information contained in the HTTP request. Output data: User record in the database.

[0277] Step 4:

[0278] The server analyzes the user's skills and emotional state based on the stored user information. Specifically, it uses NLP technology to identify the user's skills and emotional state and tag them appropriately. Input data: User information in the database. Output data: Tagged skills and emotional state.

[0279] Step 5:

[0280] The server uses AI algorithms to search for the best jobs and activities based on tagged user information. It compares the activity information in the database with the user's skills and emotional state to identify the best match. Input data: tagged skills and emotional state. Output data: list of suggested jobs and activities.

[0281] Step 6:

[0282] The server uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions based on the results. For example, if a user is feeling stressed, it will prioritize suggestions of activities that are expected to have a relaxing effect. Input data: A list of suggested tasks and activities and the user's emotional state. Output data: Adjusted suggestions.

[0283] Step 7:

[0284] The server generates the final matching result and creates a response to notify the user. This response includes adjustments that take into account the user's best suited job or activity details and emotional state. Input data: Adjusted suggestions. Output data: Response (JSON format) sent to the user.

[0285] Step 8:

[0286] The device receives the response from the server and displays the results to the user. The user can check the details of the proposed work or activity and the adjustments that take into account the emotional state on the device screen. Input data: Response from the server. Output data: Proposal results displayed to the user.

[0287] Step 9:

[0288] The user selects a specific action (such as applying or participating) based on the proposal results displayed on the device. For example, "Hanako Sato" decides to participate in the activity as a "forest therapy guide." Input data: Proposal results displayed on the device. Output data: Action selected by the user.

[0289] (Application example 2)

[0290] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0291] While conventional systems can suggest optimal jobs and activities based on a user's skills and interests, they are unable to provide personalized suggestions that take into account the user's emotional state. This makes it difficult to provide appropriate suggestions when the user is in a specific emotional state, resulting in a lack of improvement in the user experience.

[0292] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving registration information of a user, means for analyzing the user's skills based on the registration information, means for proposing optimal jobs and activities based on the skills and emotional state, means for notifying the user of the results of the proposal, and means for using an emotion engine to analyze the emotional state. This enables more precise and personalized proposals that take into account not only the user's skills and interests but also their emotional state.

[0293] "User" means an individual or organization that uses the System.

[0294] "Registration Information" refers collectively to personal information, skill information, and information regarding interests and concerns that a User provides to the System.

[0295] "Skills" refer to specific abilities or expertise possessed by a user.

[0296] "Emotional state" refers to the user's psychological and emotional state, and is information analyzed in real time.

[0297] "Optimal tasks and activities" refers to the most suitable tasks and actions suggested based on the user's skills and emotional state.

[0298] "Proposal results" are detailed information about optimal jobs and activities generated by the system.

[0299] An "emotion engine" is an algorithm or software for analyzing a user's emotional state.

[0300] "Cross-industry matching" refers to the process of suggesting jobs and activities in different industries or fields based on users' skills and interests.

[0301] "Artificial intelligence algorithms" are computational methods that use machine learning and other AI technologies to generate optimal proposals.

[0302] This invention relates to a system that suggests optimal products and services based on the user's emotional state and skills, thereby improving the customer experience in physical stores.

[0303] System configuration

[0304] 1. Server

[0305] The server receives the user's registration information and stores it in a database. Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state and, based on that data, suggests optimal products and services. Specifically, the server uses the following hardware and software:

[0306] Hardware: The server is a commercial server equipped with a high-performance processor and sufficient memory.

[0307] Software: The server-side framework uses Node.js or Python / Django, the database uses PostgreSQL or MySQL, and the sentiment analysis engine uses Microsoft Azure Emotion API or Affectiva.

[0308] 2. Terminal

[0309] Users access the system using a device such as a smartphone or smart glasses and enter their registration information, skill information, and current emotional state. The device communicates with the server, receives notifications and suggestions from the server, and displays them to the user. Specifically, the system uses the following hardware and software:

[0310] Hardware: Smartphones (iOS, Android), smart glasses (e.g. Google Glass, Vuzix), digital signage.

[0311] Software: React Native and Flutter are used as mobile app development frameworks.

[0312] 3. User

[0313] Users use a smartphone app to enter their registration information (such as skills, interests, and shopping goals), and then capture their emotional state through smart glasses or a head-mounted display.The system then provides real-time suggestions, allowing them to select the most suitable products and services.

[0314] Specific examples

[0315] For example, suppose user "Yamada Taro" visits a store and puts on the smart glasses. He inputs into the smartphone app that he is interested in "fashion" and that his goal is to "relieve stress." If emotion analysis determines that his current emotional state indicates "fatigue," the system will prioritize suggestions such as relaxing aroma diffusers and a comfortable clothing section. These suggestions are displayed on Yamada Taro's smartphone and on digital signage within the store.

[0316] Prompt Sentence Examples

[0317] "The client seems a little tired at the moment. Please suggest a product that will help them relax."

[0318] "Show your stressed customers the best service."

[0319] "Provide the latest trends to fashion-conscious customers."

[0320] In this way, the system according to the present invention can provide personalized suggestions that take into account the user's skills and emotional state.

[0321] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0322] Step 1:

[0323] Users access the system using a smartphone app and enter their registration and skill information, including their name, interests and activities, and their current shopping objectives.

[0324] Step 2:

[0325] The terminal sends the user information entered in step 1 to the server via an HTTP request. This request includes the user's skill information and registration information, which the server stores in a database.

[0326] Step 3:

[0327] Users wear smart glasses or head-mounted displays and use facial recognition sensors and microphones to capture their emotional state in real time. The emotion engine analyzes this sensor data to identify the user's emotional state.

[0328] Step 4:

[0329] The device transmits the analyzed emotional state data to the server, which includes specific emotional information such as the stress or happiness the user is feeling.

[0330] Step 5:

[0331] The server uses an AI algorithm to search for optimal products and services based on the user's skill information and emotional state information stored in the database. Specifically, it combines an emotion analysis engine with an AI model to generate recommendations that are optimal for the user's skills and emotional state.

[0332] Step 6:

[0333] The server then sends the generated recommendations to the device via WebSocket or HTTP response, which includes detailed information about the most suitable products and services that take the user's emotional state into account.

[0334] Step 7:

[0335] The device receives the recommendations from the server and displays them to the user. Appropriate recommendations are displayed in real time on smartphones, smart glasses, and in-store digital signage.

[0336] Step 8:

[0337] Users can then select products and services based on the suggestions displayed and enjoy a shopping experience in a physical store. This process enables personalized shopping suggestions based on the user's emotional state and skills.

[0338] 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.

[0339] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0340] 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.

[0341] [Second embodiment]

[0342] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0343] 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.

[0344] 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).

[0345] 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.

[0346] 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.

[0347] 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).

[0348] 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.

[0349] 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.

[0350] 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.

[0351] 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.

[0352] 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.

[0353] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0354] This invention is a system that matches a wide range of forest-related jobs with the aim of protecting forests and improving sustainable living environments. The system suggests optimal jobs and activities based on the user's skills and promotes communication and information sharing among users. The system also makes full use of artificial intelligence (AI) technology to precisely suggest optimal jobs and activities for users.

[0355] System configuration

[0356] 1. Server:

[0357] The server receives the registration information entered by the user and stores it in a database. The server also analyzes the user's information, performs matching processing, and operates an algorithm to suggest the most suitable jobs and activities.

[0358] 2. Terminal:

[0359] Users access the system using a terminal and enter their registration information and skill information. The terminal communicates with the server, receives notifications and suggestions from the server, and displays them to the user.

[0360] 3. User:

[0361] Users use the system based on their skills and interests by registering their user information and then checking the system's suggestions for suitable jobs and activities.

[0362] Program processing

[0363] The specific processing of this system will be explained in natural language below.

[0364] 1. User enters registration information:

[0365] Users access the system from a terminal and enter required information into a registration form, including their username, skills, and job or activity interests.

[0366] 2. Data transmission by the device:

[0367] The information entered by the user is sent from the terminal to the server, which receives the information and stores it in a database.

[0368] 3. User information registration by the server:

[0369] The server stores the received user information in a database and performs analysis to identify the most suitable jobs and activities based on the user's skills and interests.

[0370] 4. The server performs the matching process:

[0371] The server uses AI algorithms to analyze the user's skills and search the database for the most suitable jobs and activities. Based on the analysis results, it generates the best matching results.

[0372] 5. Server generates matching results:

[0373] The server generates matching results and formulates a response to notify the user, which includes details of the jobs and activities that are most suitable for the user.

[0374] 6. Receiving and displaying results on the device:

[0375] The device receives the response from the server and displays it in an easy-to-read format for the user, who can then review the results and take specific actions to participate in the jobs or activities that interest them.

[0376] Specific examples

[0377] For example, user "Taro Tanaka" has forestry-related skills such as "logging," "chainsaw operation," and "tree planting." Taro Tanaka accesses the system and registers these skills. The server receives Taro Tanaka's information and stores it in a database. An AI algorithm is used to analyze Taro Tanaka's skills and suggests "forestry worker" or "volunteer tree planting" as suitable jobs. The server sends this suggestion result to Taro Tanaka's device as a response, and Taro Tanaka can check the proposed jobs on his device. If Taro Tanaka is interested in the proposed jobs and takes specific action, he can participate in sustainable forest conservation.

[0378] In this way, this system can contribute to nature conservation and improving living conditions.

[0379] The processing flow will be explained below.

[0380] Step 1:

[0381] Users access the system from a terminal and fill out a registration form, including their username, skills, and job and activity interests.

[0382] Step 2:

[0383] The terminal collects the information entered by the user and sends it to the server. Specifically, the terminal sends the registration information to the server via an HTTP request.

[0384] Step 3:

[0385] The server analyzes the registration information received from the device and saves it in a database, which stores the user's basic information and skill information.

[0386] Step 4:

[0387] The server analyzes the user's skills based on the user information stored in the database, which is the process of identifying and tagging the skills that the user possesses.

[0388] Step 5:

[0389] The server uses AI algorithms to find the best jobs and activities based on the user's skills and interests, comparing the job information in the database with the user's skills to identify matching jobs and activities.

[0390] Step 6:

[0391] The server generates the results of the matching process and forms a response to notify the user, including details of the jobs and activities that are best suited for the user.

[0392] Step 7:

[0393] The device receives the response from the server and displays the results to the user, who can then view the details of the proposed tasks and activities on the device screen.

[0394] Step 8:

[0395] Based on the displayed suggestions, users can select specific actions (such as applying or contacting the organization) and participate in sustainable forest conservation.

[0396] Example 1

[0397] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0398] In modern society, forest conservation and the improvement of sustainable living environments are important issues. However, it is extremely difficult for people interested in forest-related occupations and activities to find the most suitable job or activity based on their skills. Conventional methods have a low matching accuracy between users' skills and occupations or activities, making it difficult for users to select occupations or activities that are efficient for them. To solve this problem, the present invention aims to provide a more precise and efficient matching system that makes full use of artificial intelligence technology.

[0399] 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.

[0400] In this invention, the server includes means for receiving registration information of a user, means for storing the registration information in a database, means for analyzing the user's skills based on the registration information, means for searching for optimal jobs or activities based on the skills using an artificial intelligence model, means for generating the proposal results in JSON format, means for notifying the user's terminal of the proposal results, and means for displaying the proposal results on the user's terminal, thereby enabling users to easily find jobs or activities that are optimal for their skills.

[0401] The "means for receiving user registration information" is a function that allows the system to receive information about personal information, skills, and jobs and activities of interest provided by the user.

[0402] The "means for storing the registration information in a database" is a function for recording the received user registration information in a database in order to store it permanently.

[0403] The "means for analyzing the skills of the user based on the registered information" is a function for analyzing the skills possessed by the user using the saved user information.

[0404] "Means for searching for optimal jobs or activities based on the skills using an artificial intelligence model" refers to a function that analyzes a user's skill data using artificial intelligence technology (e.g., a TensorFlow model) and identifies the most suitable job or activity.

[0405] The "means for generating the proposal results in JSON format" is a function for formatting the data obtained as a result of the matching process in JSON format and preparing it as a response from the system.

[0406] The "means for notifying the user terminal of the proposal result" is a function for transmitting the proposal result generated by the server to the user terminal via the network and notifying the user terminal.

[0407] The "means for displaying the proposal results on the user's terminal" is a function for the terminal to analyze the proposal results received from the server and display them in an easy-to-understand manner for the user.

[0408] The present invention is a system for protecting forests and improving sustainable living environments, and suggests optimal jobs and activities based on the user's skills. Specific embodiments for carrying out the present invention are described below.

[0409] This system mainly consists of a server, terminals, and users.

[0410] 1. Server configuration and functions

[0411] The server receives the user's registration information, stores it in a database, analyzes their skills based on the information, and proposes the most suitable jobs and activities. Specifically, the server uses the following hardware and software:

[0412] Hardware: High-performance server (with CPU, memory, and large-capacity storage)

[0413] software:

[0414] Database management system (e.g. MySQL)

[0415] AI analysis model (e.g. TensorFlow)

[0416] JSON parser and HTTP communication library (e.g. FastAPI)

[0417] The server first receives registration information from the user via the device and securely communicates it using the HTTPS protocol. The server then stores the received information in a MySQL database. The stored data is analyzed using a TensorFlow model to suggest optimal jobs and activities based on the user's skills. The proposed results are generated in JSON format and sent as a response to the device.

[0418] 2. Device configuration and functions

[0419] A terminal is a device through which a user accesses the system and enters registration information. Specifically, this includes a smartphone or a PC. The following software is used on the terminal:

[0420] Browser or dedicated application

[0421] Front-end libraries (e.g. React.js)

[0422] When a user accesses the system from a terminal, a registration form is displayed. The user enters their name, skills, and job and activity interests in this form and presses the submit button. The terminal converts this information into JSON format and sends it to the server using the HTTPS protocol. When the terminal receives the proposal results from the server, it analyzes them and displays them in an easy-to-read format for the user.

[0423] 3. User Operation

[0424] Users access the system using their terminal and enter their registration information. For example, if user "Yamada Jiro" has the skills "tree cutting" and "tree planting," he enters this information into the form and submits it. At this time, the server analyzes Yamada Jiro's skill information and uses an AI model to suggest the most suitable jobs and activities. The results of these suggestions are sent to the terminal, where Yamada Jiro can view them and take specific actions to participate in activities that interest him.

[0425] Examples and prompts

[0426] For example, if user "Yamada Jiro" has forestry-related skills such as "logging," "chainsaw operation," and "tree planting," he registers these skills in the system. The server receives Yamada Jiro's information and stores it in a database. An AI model using TensorFlow analyzes Yamada Jiro's skills and suggests "forestry worker" or "tree planting volunteer" as the most suitable jobs. The server sends these suggestions to the device in JSON format, allowing Yamada Jiro to check this information on his own device.

[0427] Prompt Sentence Examples

[0428] "Build a system that suggests the best jobs for users with forest conservation skill sets."

[0429] "Create an AI model that takes user skills as input and matches them with the best forestry-related jobs."

[0430] Through this system, users can easily find jobs and activities that best suit their skills, thereby making a significant contribution to protecting nature and improving living conditions.

[0431] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0432] Step 1:

[0433] User enters registration information

[0434] Users access the system using a terminal and enter their information into the registration form. The input data includes their username, skills (e.g., "tree cutting," "chainsaw operation," "tree planting," etc.), and jobs or activities of interest. Once the input is complete, the user presses the send button, and this data is sent from the terminal to the server. The input data is in JSON format.

[0435] Step 2:

[0436] Sending data by the device

[0437] The terminal sends the registration information provided by the user to the server. Specifically, the terminal encodes the input data in JSON format and securely transmits the data to the server using the HTTPS protocol. The server endpoint is, for example, / api / user / register. The input in this case is the registration information provided by the user, and the output is an HTTPS request to the server.

[0438] Step 3:

[0439] Registration of user information by the server

[0440] The server receives the user information sent from the terminal and stores it in the database. Specifically, the server parses the received JSON data and saves it as a new user record in the MySQL database. The SQL query used is an INSERT statement. The input to this step is the JSON data sent from the terminal, and the output is the user information stored in the database.

[0441] Step 4:

[0442] Matching is performed by the server

[0443] The server uses an AI model to analyze the optimal jobs and activities based on the stored user information. This process uses TensorFlow. The server inputs the stored skill data into the AI ​​model, extracts the skill characteristics, and searches the database for jobs and activities based on them. The output is a list of jobs and activities optimal for the user. The input to this step is the user skills stored in the database, and the output is the analysis results from the AI ​​model.

[0444] Step 5:

[0445] Server-generated matching results

[0446] The server proposes optimal jobs and activities to the user based on the analysis results obtained from the AI ​​model. Specifically, it generates detailed information about the proposal in JSON format. These details include the job title, job description, location, and how to apply. The input to this step is the analysis results from the AI ​​model, and the output is a JSON response containing the proposal results.

[0447] Step 6:

[0448] Receiving and displaying results on the device

[0449] The device receives the response from the server and displays it to the user. Specifically, it parses the received JSON data and displays it on the UI using a front-end framework such as React.js. The user can view detailed information about the proposed jobs and activities and take specific actions to participate in activities that interest them. The input is the JSON response from the server, and the output is the proposal results displayed on the user's screen.

[0450] This processing step allows users to easily find jobs and activities that best suit their skills.

[0451] (Application example 1)

[0452] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0453] In conventional factories, there has been a lack of systems that efficiently match the skills of robot workers with task requirements, which has led to reduced work efficiency and problems with collaboration between humans and robots. Furthermore, the inability to assign the right tasks to the right robots has hindered productivity improvement. To solve these problems, the present invention aims to provide a system that performs optimal matching based on robot skill information and the required task skills.

[0454] 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.

[0455] In this invention, the server includes means for receiving user registration information, means for analyzing the user's skills based on the registration information, means for proposing optimal jobs and activities based on the skills, means for notifying the user of the results of the proposal, means for receiving and saving robot skill information, means for analyzing the required skills of tasks, means for comparing the robot skill information with the required skills of tasks and assigning optimal tasks, and means for displaying the assignment results. This makes it possible to efficiently match robot operators with tasks in a factory, thereby improving productivity and optimizing work efficiency.

[0456] "Users" are individuals or companies who use the system to enter their skills and registration information.

[0457] "Registration information" refers to information that users enter into the system, including data such as skills, interests, and work experience.

[0458] "Skills" are information that represents the specialized abilities, techniques, and aptitudes possessed by users and robots.

[0459] "Analysis" refers to data processing and evaluation to identify the most suitable jobs and tasks based on registration information and skill information.

[0460] "Proposal" is the act of the system showing the user or robot the optimal job or task based on the analysis results.

[0461] "Server" is the central computer of the system, and is a device that receives, stores, analyzes, and performs proposal functions for data.

[0462] A "robot" is a mechanical device that performs work in a factory, has skill information, and is used to perform specific tasks.

[0463] A "task" refers to a specific task or activity to be performed within a factory, with required skills and conditions specified.

[0464] "Required skills" is information that indicates the abilities and techniques required to perform a specific task.

[0465] "Matching" is the process or act of comparing the skill information of the robot or user with the skills required for the task to find the optimal combination.

[0466] "Notification" refers to the act of the system communicating the proposal results and matching results to the user or robot administrator.

[0467] "Comparison" refers to the act of comparing two or more elements, namely the robot's skill information and the required skills of the task, and evaluating the degree of agreement.

[0468] The present invention provides a system for realizing efficient task allocation for robot workers in a factory. The system includes a server, a terminal, a user, and a robot.

[0469] The server receives the user's registration information and stores it in a database. The server analyzes the user's skills based on this registration information and runs an algorithm to suggest the most suitable jobs and activities. The main software used by the server includes Python and scikit-learn, which vectorize the user's skill information and compare it with the required skills of the task.

[0470] Specifically, the system receives registration information and stores it in a database. Next, it generates a skill vector using an AI model (e.g., TfidfVectorizer) based on the registered skill information. The required skills of the task are then similarly vectorized and analyzed using methods such as cosine similarity. This allows it to identify the optimal combination of robot and task and generate a proposal.

[0471] The terminal is used by users to access the system and enter their registration information and skill information. Notifications and proposals from the server are also displayed on the terminal. Terminals can be smartphones, tablets, or PCs.

[0472] Users access the system through their devices and input their skills and interests. The server then suggests suitable jobs and activities and notifies the user. For example, if a user has skills such as "welding," "cutting," and "assembly," the server will suggest tasks such as "welder" or "assembler" based on those skills.

[0473] In addition, robots can register their own skill information with the server to perform tasks within the factory. The server uses this information to assign the robot the most suitable tasks. For example, if a robot has the skills of "painting" and "spraying," the server will suggest tasks such as "painting work" based on that.

[0474] As an example of this system-wide behavior, the following prompt sentence is used:

[0475] "Robot A has welding and cutting skills. We currently have a task to perform welding and cutting work. Which robot is best?"

[0476] "Robot B has the skills to paint and spray, and we currently have a painting task. Which robot is best suited to the task?"

[0477] This invention enables efficient matching of robot operators with tasks within a factory, improving productivity and optimizing work efficiency.

[0478] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0479] Step 1:

[0480] A user accesses the system using a terminal and enters the necessary information into the registration form, including the user name, skills, and jobs and activities that the user is interested in. This input data is considered the initial input.

[0481] Step 2:

[0482] The device sends the information entered by the user to the server. The specific data is text data such as username, skills, interests, etc., and is transferred to the server via a communication protocol. The server receives this data and stores it as an initial database entry.

[0483] Step 3:

[0484] The server stores the received user information in a database and vectorizes the registered skill information using an AI model (e.g., TfidfVectorizer). The vectorized skill information is used for subsequent analysis processing. The input is text data, and the output is vector data.

[0485] Step 4:

[0486] When a user creates a new task, they input the required skills and details of the task into the terminal and send it to the server. The terminal accurately transfers this task information to the server and stores it in the task database. The input is the text data of the task, and the output is a task database entry.

[0487] Step 5:

[0488] The server also vectorizes the required skill information of the task and calculates the cosine similarity between the skill vector and the task vector. This evaluates the degree to which the skill information of the registered robot or user matches the required skill of the task. The input is vector data, and the output is a similarity score.

[0489] Step 6:

[0490] The server matches the best robots and users to each task based on the cosine similarity score. The robots and users with the highest scores are selected and recorded as the matching results. The input is the similarity score, and the output is the best matching information.

[0491] Step 7:

[0492] The server generates a response based on the generated matching results and notifies the device. The results include details of the robot and user best suited for each task. The device receives the results and displays them in an easy-to-read format for the user. The input is the matching information, and the output is notification data.

[0493] Step 8:

[0494] The user checks the notification results through their terminal and takes specific actions for the proposed work or task. The user uses an interface to confirm acceptance of a new task or start of work, and sends the results to the server. The input is the user's action data, and the output is the action result.

[0495] Through these steps, efficient matching of robots and tasks within the factory is achieved.

[0496] 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.

[0497] This invention aims to protect forests and improve sustainable living environments by suggesting optimal jobs and activities based on the user's emotional state using a system that combines an emotion engine. By taking into account not only the user's skills but also their emotions, this system achieves more precise and personalized suggestions.

[0498] System configuration

[0499] 1. Server:

[0500] The server receives the registration information entered by the user and stores it in a database. Furthermore, the server has an algorithm for analyzing the user's skills and emotions and executing the matching process. The server also uses an emotion engine to analyze the user's emotional state and suggest optimal jobs and activities based on that data.

[0501] 2. Terminal:

[0502] Users access the system using a terminal and enter their registration information, skill information, and current emotional state. The terminal communicates with the server, receives notifications and suggestions from the server, and displays them to the user.

[0503] 3. User:

[0504] Users use the system based on their skills, interests, and emotional state. Specifically, they register their user information, check the optimal jobs and activities suggested by the system, and even input their own emotional state.

[0505] Program processing

[0506] The specific processing of this system will be explained in natural language below.

[0507] 1. User enters registration information:

[0508] Users access the system from a terminal and fill out a registration form with required information, including their username, skills, and job and activity interests, as well as their current emotional state.

[0509] 2. Data transmission by the device:

[0510] The information entered by the user is sent from the device to the server. Specifically, the device sends the registration information and emotional state to the server via an HTTP request.

[0511] 3. User information registration by the server:

[0512] The server analyzes the registration information and emotional state received from the device and stores it in a database, which stores the user's basic information, skill information, and emotional information.

[0513] 4. Skill and emotion analysis by the server:

[0514] The server analyzes the user's skills and emotional state based on the user information stored in the database. This analysis is a process of identifying and tagging both the skills and emotions possessed by the user.

[0515] 5. The server performs the matching process:

[0516] The server uses AI algorithms to search for the best jobs and activities based on the user's skills and emotional state, comparing job information in the database with the user's skills and emotions to identify matching jobs and activities.

[0517] 6. Server-based suggestion adjustment based on emotions:

[0518] The server also uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions accordingly: for example, if the user is under stress, it will prioritize activities that will reduce stress.

[0519] 7. Server generates matching results:

[0520] The server generates a matching result and formulates a response to notify the user, including details of the job or activity that best suits the user and adjustments that take into account their emotional state.

[0521] 8. Receiving and displaying results on the device:

[0522] The device receives the response from the server and displays the results to the user, who can view the details of the suggested tasks and activities, as well as adjustments that take into account the user's emotional state, on the device screen.

[0523] 9. User confirms the results and selects an action:

[0524] Based on the displayed suggestions, users can select specific actions (such as applying or contacting the organization) to participate in sustainable forest conservation. By taking emotional state into consideration in this way, more personalized suggestions can be made, increasing user satisfaction.

[0525] Specific examples

[0526] For example, user "Sato Hanako" accesses the system and registers her skills of "tree planting" and "forest cultivation," and selects "feeling stressed" as her current emotional state. The server receives this information and stores it in a database. After analyzing it using an AI algorithm, it suggests "forest therapy guide" and "tree planting volunteer" to Sato Hanako. The emotion engine also takes into account her stress level and prioritizes recommending "forest therapy guide," which is expected to have a particularly relaxing effect.

[0527] The results of these suggestions are displayed on the device, and Sato Hanako uses this information to participate in the activities as a "forest therapy guide." In this way, by using this system, optimal suggestions are made that reflect the user's skills and emotional state, contributing to sustainable forest conservation activities.

[0528] The processing flow will be explained below.

[0529] Step 1:

[0530] Users access the system from a terminal and enter required information into a registration form, including their username, skills, and job and activity interests, as well as their current emotional state.

[0531] Step 2:

[0532] The device collects the information entered by the user and sends it to the server via an HTTP request, specifically, the user's username, skill information, job and activity interests, and emotional state.

[0533] Step 3:

[0534] The server analyzes the registration information and emotional state received from the device and stores them in a database, which stores the user's basic information, skill information, and emotional information.

[0535] Step 4:

[0536] The server analyzes the user's skills and emotional state based on the user information stored in the database. Specifically, it performs an analysis process to identify the user's skill set and current emotional state and tag them.

[0537] Step 5:

[0538] The server uses an AI algorithm to search for the best jobs and activities based on the user's skills and emotional state. It compares the job information in the database with the user's skills and emotions to identify matching jobs and activities. For example, based on the skill of "planting a tree" and the emotional state of "feeling stressed," activities with a relaxing effect will be prioritized.

[0539] Step 6:

[0540] The server also uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions accordingly. For example, if the user is under stress, it will prioritize activities that will help reduce stress.

[0541] Step 7:

[0542] The server generates a response based on the results of the matching process and emotion-based adjustments, including details of the optimal task or activity for the user and adjustments that take into account the user's emotional state.

[0543] Step 8:

[0544] The device receives the response from the server and displays the results to the user, including details of the suggested tasks and activities, as well as adjustments that take into account the user's emotional state.

[0545] Step 9:

[0546] The user can check the suggestions displayed on the device and select a specific action. For example, the user can select the "Forest Therapy Guide" suggestion and participate in the activity to contribute to sustainable forest conservation.

[0547] In this way, the system can suggest optimal tasks and activities that take into account the user's skills and emotional state, increasing user satisfaction and contributing to sustainable forest conservation.

[0548] Example 2

[0549] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0550] Previous job and activity suggestion systems mainly based their suggestions on the user's skills and rarely took the user's emotional state into consideration. This meant that they were unable to provide appropriate suggestions to users who felt stressed or dissatisfied, making it difficult to increase user satisfaction. Furthermore, they lacked the ability to analyze the user's emotional state in real time and adjust the suggestions accordingly.

[0551] 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.

[0552] In this invention, the server includes means for receiving registration information of a user, means for analyzing the user's skills based on the registration information, means for analyzing the user's emotional state based on the registration information, means for proposing optimal jobs and activities based on the skills and emotional state, means for adjusting the content of the proposal in real time based on the emotional state, and means for notifying the user of the proposal results. This enables more precise and personalized proposals that take the user's emotional state into consideration, thereby increasing user satisfaction.

[0553] "User" refers to a person who uses the system to input registration information, skills, and emotional state and is then suggested suitable jobs and activities.

[0554] "Registration Information" refers to information used within the system, such as a user's name, skills, and emotional state.

[0555] "Skills" refers to the knowledge, abilities, and experience that a user possesses, and serve as the basis for making proposals.

[0556] "Emotional state" refers to the emotional state the user is currently feeling, information that is used to tailor suggestions.

[0557] "Server" refers to the central computer system that receives and analyzes users' registration information and makes optimal suggestions.

[0558] "Analysis" refers to the process by which the system processes, understands, and classifies data such as registration information, skills, and emotional state.

[0559] "Suggestion" refers to the act of suggesting the best job or activity based on the user's skills and emotional state.

[0560] "Real-time" means that the system processes the information it receives immediately and reflects the results immediately.

[0561] "Notification" refers to the act of the system communicating analysis results and suggestions to the user.

[0562] This invention aims to protect forests and improve sustainable living environments by proposing optimal tasks and activities based on the user's emotional state. The system is primarily composed of three elements: a server, a terminal, and the user.

[0563] System Configuration

[0564] 1. Server:

[0565] The server has the function of receiving registration information entered by the user and storing it in a database.

[0566] The server is equipped with algorithms to analyze the user's skills and emotional state.

[0567] It is equipped with an emotion engine that analyzes the user's emotional state in real time and adjusts the suggestions it makes.

[0568] A proposal result is generated and notified to the user.

[0569] 2. Terminal:

[0570] Users use terminals to access the system and enter information.

[0571] The terminal communicates with the server, receives notifications and proposal results from the server, and displays them.

[0572] 3. User:

[0573] The user uses the terminal to input their registration information, skill information, and emotional state.

[0574] Review and select the suggested tasks and activities.

[0575] Example

[0576] For example, when a user named "Hanako Sato" accesses the system, a registration form appears on the device's web page. She enters her name, her skills of "tree planting" and "forest cultivation," and her current emotional state as "feeling stressed." The device then sends this information to the server.

[0577] The server analyzes the information it receives and stores it in a database, using natural language processing (NLP) techniques to tag skills and emotional states. AI algorithms within the server then search for the most suitable jobs and activities based on these tags. For example, for the skill "tree planting" and the emotional state "feeling stressed," "forest therapy guide" and "tree planting volunteer" are suggested.

[0578] Furthermore, the emotion engine adjusts the suggestions in real time based on the analysis results stored on the server. For example, if Sato Hanako is feeling stressed, the Forest Therapy Guide, which is expected to have a relaxing effect, will be recommended first.

[0579] The results of these proposals are sent from the server to the device and displayed on the device screen. Hanako Sato checks the proposed jobs and activities and participates in the activities as a "forest therapy guide."

[0580] Examples of prompts used in queries

[0581] Based on the prompt sentence, "What kind of activity would have a relaxing effect on a user who is feeling stressed?", the emotion engine makes appropriate suggestions.

[0582] Hardware and software used

[0583] Server: High-performance cloud server (e.g. AWS, Google Cloud)

[0584] Emotion engine: Analysis engine using NLP technology (e.g., OpenAI, Google AI)

[0585] Database: Relational database (e.g. MySQL, PostgreSQL)

[0586] Terminals: General-purpose devices such as PCs, smartphones, and tablets

[0587] This allows for more refined and personalized suggestions that take into account the user's emotional state, enabling them to actively participate in sustainable forest conservation efforts.

[0588] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0589] Step 1:

[0590] Users access the system using their own terminals and enter the necessary information (user name, skills, job interests and activities, emotional state) into the registration form. For example, "Hanako Sato" enters the skills "tree planting" and "forest cultivation" and selects "feeling stressed" as her emotional state. Once the input is complete, the terminal sends this information to the server.

[0591] Step 2:

[0592] The device forms the information entered by the user into an HTTP request and sends it to the server. This request contains the user's name, skills, activities of interest, and emotional state in JSON format. Input data: User name, skills, emotional state, activities of interest. Output data: HTTP request containing these.

[0593] Step 3:

[0594] The server analyzes the HTTP request received from the terminal and extracts the user information. It then stores this information in a database. Input data: User information contained in the HTTP request. Output data: User record in the database.

[0595] Step 4:

[0596] The server analyzes the user's skills and emotional state based on the stored user information. Specifically, it uses NLP technology to identify the user's skills and emotional state and tag them appropriately. Input data: User information in the database. Output data: Tagged skills and emotional state.

[0597] Step 5:

[0598] The server uses AI algorithms to search for the best jobs and activities based on tagged user information. It compares the activity information in the database with the user's skills and emotional state to identify the best match. Input data: tagged skills and emotional state. Output data: list of suggested jobs and activities.

[0599] Step 6:

[0600] The server uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions based on the results. For example, if a user is feeling stressed, it will prioritize suggestions of activities that are expected to have a relaxing effect. Input data: A list of suggested tasks and activities and the user's emotional state. Output data: Adjusted suggestions.

[0601] Step 7:

[0602] The server generates the final matching result and creates a response to notify the user. This response includes adjustments that take into account the user's best suited job or activity details and emotional state. Input data: Adjusted suggestions. Output data: Response (JSON format) sent to the user.

[0603] Step 8:

[0604] The device receives the response from the server and displays the results to the user. The user can check the details of the proposed work or activity and the adjustments that take into account the emotional state on the device screen. Input data: Response from the server. Output data: Proposal results displayed to the user.

[0605] Step 9:

[0606] The user selects a specific action (such as applying or participating) based on the proposal results displayed on the device. For example, "Hanako Sato" decides to participate in the activity as a "forest therapy guide." Input data: Proposal results displayed on the device. Output data: Action selected by the user.

[0607] (Application example 2)

[0608] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0609] While conventional systems can suggest optimal jobs and activities based on a user's skills and interests, they are unable to provide personalized suggestions that take into account the user's emotional state. This makes it difficult to provide appropriate suggestions when the user is in a specific emotional state, resulting in a lack of improvement in the user experience.

[0610] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving registration information of a user, means for analyzing the user's skills based on the registration information, means for proposing optimal jobs and activities based on the skills and emotional state, means for notifying the user of the results of the proposal, and means for using an emotion engine to analyze the emotional state. This enables more precise and personalized proposals that take into account not only the user's skills and interests but also their emotional state.

[0611] "User" means an individual or organization that uses the System.

[0612] "Registration Information" refers collectively to personal information, skill information, and information regarding interests and concerns that a User provides to the System.

[0613] "Skills" refer to specific abilities or expertise possessed by a user.

[0614] "Emotional state" refers to the user's psychological and emotional state, and is information analyzed in real time.

[0615] "Optimal tasks and activities" refers to the most suitable tasks and actions suggested based on the user's skills and emotional state.

[0616] "Proposal results" are detailed information about optimal jobs and activities generated by the system.

[0617] An "emotion engine" is an algorithm or software for analyzing a user's emotional state.

[0618] "Cross-industry matching" refers to the process of suggesting jobs and activities in different industries or fields based on users' skills and interests.

[0619] "Artificial intelligence algorithms" are computational methods that use machine learning and other AI technologies to generate optimal proposals.

[0620] This invention relates to a system that suggests optimal products and services based on the user's emotional state and skills, thereby improving the customer experience in physical stores.

[0621] System configuration

[0622] 1. Server

[0623] The server receives the user's registration information and stores it in a database. Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state and, based on that data, suggests optimal products and services. Specifically, the server uses the following hardware and software:

[0624] Hardware: The server is a commercial server equipped with a high-performance processor and sufficient memory.

[0625] Software: The server-side framework uses Node.js or Python / Django, the database uses PostgreSQL or MySQL, and the sentiment analysis engine uses Microsoft Azure Emotion API or Affectiva.

[0626] 2. Terminal

[0627] Users access the system using a device such as a smartphone or smart glasses and enter their registration information, skill information, and current emotional state. The device communicates with the server, receives notifications and suggestions from the server, and displays them to the user. Specifically, the system uses the following hardware and software:

[0628] Hardware: Smartphones (iOS, Android), smart glasses (e.g. Google Glass, Vuzix), digital signage.

[0629] Software: React Native and Flutter are used as mobile app development frameworks.

[0630] 3. User

[0631] Users use a smartphone app to enter their registration information (such as skills, interests, and shopping goals), and then capture their emotional state through smart glasses or a head-mounted display.The system then provides real-time suggestions, allowing them to select the most suitable products and services.

[0632] Specific examples

[0633] For example, suppose user "Yamada Taro" visits a store and puts on the smart glasses. He inputs into the smartphone app that he is interested in "fashion" and that his goal is to "relieve stress." If emotion analysis determines that his current emotional state indicates "fatigue," the system will prioritize suggestions such as relaxing aroma diffusers and a comfortable clothing section. These suggestions are displayed on Yamada Taro's smartphone and on digital signage within the store.

[0634] Prompt Sentence Examples

[0635] "The client seems a little tired at the moment. Please suggest a product that will help them relax."

[0636] "Show your stressed customers the best service."

[0637] "Provide the latest trends to fashion-conscious customers."

[0638] In this way, the system according to the present invention can provide personalized suggestions that take into account the user's skills and emotional state.

[0639] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0640] Step 1:

[0641] Users access the system using a smartphone app and enter their registration and skill information, including their name, interests and activities, and their current shopping objectives.

[0642] Step 2:

[0643] The terminal sends the user information entered in step 1 to the server via an HTTP request. This request includes the user's skill information and registration information, which the server stores in a database.

[0644] Step 3:

[0645] Users wear smart glasses or head-mounted displays and use facial recognition sensors and microphones to capture their emotional state in real time. The emotion engine analyzes this sensor data to identify the user's emotional state.

[0646] Step 4:

[0647] The device transmits the analyzed emotional state data to the server, which includes specific emotional information such as the stress or happiness the user is feeling.

[0648] Step 5:

[0649] The server uses an AI algorithm to search for optimal products and services based on the user's skill information and emotional state information stored in the database. Specifically, it combines an emotion analysis engine with an AI model to generate recommendations that are optimal for the user's skills and emotional state.

[0650] Step 6:

[0651] The server then sends the generated recommendations to the device via WebSocket or HTTP response, which includes detailed information about the most suitable products and services that take the user's emotional state into account.

[0652] Step 7:

[0653] The device receives the recommendations from the server and displays them to the user. Appropriate recommendations are displayed in real time on smartphones, smart glasses, and in-store digital signage.

[0654] Step 8:

[0655] Users can then select products and services based on the suggestions displayed and enjoy a shopping experience in a physical store. This process enables personalized shopping suggestions based on the user's emotional state and skills.

[0656] 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.

[0657] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0658] 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.

[0659] [Third embodiment]

[0660] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0661] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0662] 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).

[0663] 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.

[0664] 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.

[0665] 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).

[0666] 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.

[0667] 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.

[0668] 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.

[0669] 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.

[0670] 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.

[0671] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0672] This invention is a system that matches a wide range of forest-related jobs with the aim of protecting forests and improving sustainable living environments. The system suggests optimal jobs and activities based on the user's skills and promotes communication and information sharing among users. The system also makes full use of artificial intelligence (AI) technology to precisely suggest optimal jobs and activities for users.

[0673] System configuration

[0674] 1. Server:

[0675] The server receives the registration information entered by the user and stores it in a database. The server also analyzes the user's information, performs matching processing, and operates an algorithm to suggest the most suitable jobs and activities.

[0676] 2. Terminal:

[0677] Users access the system using a terminal and enter their registration information and skill information. The terminal communicates with the server, receives notifications and suggestions from the server, and displays them to the user.

[0678] 3. User:

[0679] Users use the system based on their skills and interests by registering their user information and then checking the system's suggestions for suitable jobs and activities.

[0680] Program processing

[0681] The specific processing of this system will be explained in natural language below.

[0682] 1. User enters registration information:

[0683] Users access the system from a terminal and enter required information into a registration form, including their username, skills, and job or activity interests.

[0684] 2. Data transmission by the device:

[0685] The information entered by the user is sent from the terminal to the server, which receives the information and stores it in a database.

[0686] 3. User information registration by the server:

[0687] The server stores the received user information in a database and performs analysis to identify the most suitable jobs and activities based on the user's skills and interests.

[0688] 4. The server performs the matching process:

[0689] The server uses AI algorithms to analyze the user's skills and search the database for the most suitable jobs and activities. Based on the analysis results, it generates the best matching results.

[0690] 5. Server generates matching results:

[0691] The server generates matching results and formulates a response to notify the user, which includes details of the jobs and activities that are most suitable for the user.

[0692] 6. Receiving and displaying results on the device:

[0693] The device receives the response from the server and displays it in an easy-to-read format for the user, who can then review the results and take specific actions to participate in the jobs or activities that interest them.

[0694] Specific examples

[0695] For example, user "Taro Tanaka" has forestry-related skills such as "logging," "chainsaw operation," and "tree planting." Taro Tanaka accesses the system and registers these skills. The server receives Taro Tanaka's information and stores it in a database. An AI algorithm is used to analyze Taro Tanaka's skills and suggests "forestry worker" or "volunteer tree planting" as suitable jobs. The server sends this suggestion result to Taro Tanaka's device as a response, and Taro Tanaka can check the proposed jobs on his device. If Taro Tanaka is interested in the proposed jobs and takes specific action, he can participate in sustainable forest conservation.

[0696] In this way, this system can contribute to nature conservation and improving living conditions.

[0697] The processing flow will be explained below.

[0698] Step 1:

[0699] Users access the system from a terminal and fill out a registration form, including their username, skills, and job and activity interests.

[0700] Step 2:

[0701] The terminal collects the information entered by the user and sends it to the server. Specifically, the terminal sends the registration information to the server via an HTTP request.

[0702] Step 3:

[0703] The server analyzes the registration information received from the device and saves it in a database, which stores the user's basic information and skill information.

[0704] Step 4:

[0705] The server analyzes the user's skills based on the user information stored in the database, which is the process of identifying and tagging the skills that the user possesses.

[0706] Step 5:

[0707] The server uses AI algorithms to find the best jobs and activities based on the user's skills and interests, comparing the job information in the database with the user's skills to identify matching jobs and activities.

[0708] Step 6:

[0709] The server generates the results of the matching process and forms a response to notify the user, including details of the jobs and activities that are best suited for the user.

[0710] Step 7:

[0711] The device receives the response from the server and displays the results to the user, who can then view the details of the proposed tasks and activities on the device screen.

[0712] Step 8:

[0713] Based on the displayed suggestions, users can select specific actions (such as applying or contacting the organization) and participate in sustainable forest conservation.

[0714] Example 1

[0715] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0716] In modern society, forest conservation and the improvement of sustainable living environments are important issues. However, it is extremely difficult for people interested in forest-related occupations and activities to find the most suitable job or activity based on their skills. Conventional methods have a low matching accuracy between users' skills and occupations or activities, making it difficult for users to select occupations or activities that are efficient for them. To solve this problem, the present invention aims to provide a more precise and efficient matching system that makes full use of artificial intelligence technology.

[0717] 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.

[0718] In this invention, the server includes means for receiving registration information of a user, means for storing the registration information in a database, means for analyzing the user's skills based on the registration information, means for searching for optimal jobs or activities based on the skills using an artificial intelligence model, means for generating the proposal results in JSON format, means for notifying the user's terminal of the proposal results, and means for displaying the proposal results on the user's terminal, thereby enabling users to easily find jobs or activities that are optimal for their skills.

[0719] The "means for receiving user registration information" is a function that allows the system to receive information about personal information, skills, and jobs and activities of interest provided by the user.

[0720] The "means for storing the registration information in a database" is a function for recording the received user registration information in a database in order to store it permanently.

[0721] The "means for analyzing the skills of the user based on the registered information" is a function for analyzing the skills possessed by the user using the saved user information.

[0722] "Means for searching for optimal jobs or activities based on the skills using an artificial intelligence model" refers to a function that analyzes a user's skill data using artificial intelligence technology (e.g., a TensorFlow model) and identifies the most suitable job or activity.

[0723] The "means for generating the proposal results in JSON format" is a function for formatting the data obtained as a result of the matching process in JSON format and preparing it as a response from the system.

[0724] The "means for notifying the user terminal of the proposal result" is a function for transmitting the proposal result generated by the server to the user terminal via the network and notifying the user terminal.

[0725] The "means for displaying the proposal results on the user's terminal" is a function for the terminal to analyze the proposal results received from the server and display them in an easy-to-understand manner for the user.

[0726] The present invention is a system for protecting forests and improving sustainable living environments, and suggests optimal jobs and activities based on the user's skills. Specific embodiments for carrying out the present invention are described below.

[0727] This system mainly consists of a server, terminals, and users.

[0728] 1. Server configuration and functions

[0729] The server receives the user's registration information, stores it in a database, analyzes their skills based on the information, and proposes the most suitable jobs and activities. Specifically, the server uses the following hardware and software:

[0730] Hardware: High-performance server (with CPU, memory, and large-capacity storage)

[0731] software:

[0732] Database management system (e.g. MySQL)

[0733] AI analysis model (e.g. TensorFlow)

[0734] JSON parser and HTTP communication library (e.g. FastAPI)

[0735] The server first receives registration information from the user via the device and securely communicates it using the HTTPS protocol. The server then stores the received information in a MySQL database. The stored data is analyzed using a TensorFlow model to suggest optimal jobs and activities based on the user's skills. The proposed results are generated in JSON format and sent as a response to the device.

[0736] 2. Device configuration and functions

[0737] A terminal is a device through which a user accesses the system and enters registration information. Specifically, this includes a smartphone or a PC. The following software is used on the terminal:

[0738] Browser or dedicated application

[0739] Front-end libraries (e.g. React.js)

[0740] When a user accesses the system from a terminal, a registration form is displayed. The user enters their name, skills, and job and activity interests in this form and presses the submit button. The terminal converts this information into JSON format and sends it to the server using the HTTPS protocol. When the terminal receives the proposal results from the server, it analyzes them and displays them in an easy-to-read format for the user.

[0741] 3. User Operation

[0742] Users access the system using their terminal and enter their registration information. For example, if user "Yamada Jiro" has the skills "tree cutting" and "tree planting," he enters this information into the form and submits it. At this time, the server analyzes Yamada Jiro's skill information and uses an AI model to suggest the most suitable jobs and activities. The results of these suggestions are sent to the terminal, where Yamada Jiro can view them and take specific actions to participate in activities that interest him.

[0743] Examples and prompts

[0744] For example, if user "Yamada Jiro" has forestry-related skills such as "logging," "chainsaw operation," and "tree planting," he registers these skills in the system. The server receives Yamada Jiro's information and stores it in a database. An AI model using TensorFlow analyzes Yamada Jiro's skills and suggests "forestry worker" or "tree planting volunteer" as the most suitable jobs. The server sends these suggestions to the device in JSON format, allowing Yamada Jiro to check this information on his own device.

[0745] Prompt Sentence Examples

[0746] "Build a system that suggests the best jobs for users with forest conservation skill sets."

[0747] "Create an AI model that takes user skills as input and matches them with the best forestry-related jobs."

[0748] Through this system, users can easily find jobs and activities that best suit their skills, thereby making a significant contribution to protecting nature and improving living conditions.

[0749] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0750] Step 1:

[0751] User enters registration information

[0752] Users access the system using a terminal and enter their information into the registration form. The input data includes their username, skills (e.g., "tree cutting," "chainsaw operation," "tree planting," etc.), and jobs or activities of interest. Once the input is complete, the user presses the send button, and this data is sent from the terminal to the server. The input data is in JSON format.

[0753] Step 2:

[0754] Sending data by the device

[0755] The terminal sends the registration information provided by the user to the server. Specifically, the terminal encodes the input data in JSON format and securely transmits the data to the server using the HTTPS protocol. The server endpoint is, for example, / api / user / register. The input in this case is the registration information provided by the user, and the output is an HTTPS request to the server.

[0756] Step 3:

[0757] Registration of user information by the server

[0758] The server receives the user information sent from the terminal and stores it in the database. Specifically, the server parses the received JSON data and saves it as a new user record in the MySQL database. The SQL query used is an INSERT statement. The input to this step is the JSON data sent from the terminal, and the output is the user information stored in the database.

[0759] Step 4:

[0760] Matching is performed by the server

[0761] The server uses an AI model to analyze the optimal jobs and activities based on the stored user information. This process uses TensorFlow. The server inputs the stored skill data into the AI ​​model, extracts the skill characteristics, and searches the database for jobs and activities based on them. The output is a list of jobs and activities optimal for the user. The input to this step is the user skills stored in the database, and the output is the analysis results from the AI ​​model.

[0762] Step 5:

[0763] Server-generated matching results

[0764] The server proposes optimal jobs and activities to the user based on the analysis results obtained from the AI ​​model. Specifically, it generates detailed information about the proposal in JSON format. These details include the job title, job description, location, and how to apply. The input to this step is the analysis results from the AI ​​model, and the output is a JSON response containing the proposal results.

[0765] Step 6:

[0766] Receiving and displaying results on the device

[0767] The device receives the response from the server and displays it to the user. Specifically, it parses the received JSON data and displays it on the UI using a front-end framework such as React.js. The user can view detailed information about the proposed jobs and activities and take specific actions to participate in activities that interest them. The input is the JSON response from the server, and the output is the proposal results displayed on the user's screen.

[0768] This processing step allows users to easily find jobs and activities that best suit their skills.

[0769] (Application example 1)

[0770] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0771] In conventional factories, there has been a lack of systems that efficiently match the skills of robot workers with task requirements, which has led to reduced work efficiency and problems with collaboration between humans and robots. Furthermore, the inability to assign the right tasks to the right robots has hindered productivity improvement. To solve these problems, the present invention aims to provide a system that performs optimal matching based on robot skill information and the required task skills.

[0772] 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.

[0773] In this invention, the server includes means for receiving user registration information, means for analyzing the user's skills based on the registration information, means for proposing optimal jobs and activities based on the skills, means for notifying the user of the results of the proposal, means for receiving and saving robot skill information, means for analyzing the required skills of tasks, means for comparing the robot skill information with the required skills of tasks and assigning optimal tasks, and means for displaying the assignment results. This makes it possible to efficiently match robot operators with tasks in a factory, thereby improving productivity and optimizing work efficiency.

[0774] "Users" are individuals or companies who use the system to enter their skills and registration information.

[0775] "Registration information" refers to information that users enter into the system, including data such as skills, interests, and work experience.

[0776] "Skills" are information that represents the specialized abilities, techniques, and aptitudes possessed by users and robots.

[0777] "Analysis" refers to data processing and evaluation to identify the most suitable jobs and tasks based on registration information and skill information.

[0778] "Proposal" is the act of the system showing the user or robot the optimal job or task based on the analysis results.

[0779] "Server" is the central computer of the system, and is a device that receives, stores, analyzes, and performs proposal functions for data.

[0780] A "robot" is a mechanical device that performs work in a factory, has skill information, and is used to perform specific tasks.

[0781] A "task" refers to a specific task or activity to be performed within a factory, with required skills and conditions specified.

[0782] "Required skills" is information that indicates the abilities and techniques required to perform a specific task.

[0783] "Matching" is the process or act of comparing the skill information of the robot or user with the skills required for the task to find the optimal combination.

[0784] "Notification" refers to the act of the system communicating the proposal results and matching results to the user or robot administrator.

[0785] "Comparison" refers to the act of comparing two or more elements, namely the robot's skill information and the required skills of the task, and evaluating the degree of agreement.

[0786] The present invention provides a system for realizing efficient task allocation for robot workers in a factory. The system includes a server, a terminal, a user, and a robot.

[0787] The server receives the user's registration information and stores it in a database. The server analyzes the user's skills based on this registration information and runs an algorithm to suggest the most suitable jobs and activities. The main software used by the server includes Python and scikit-learn, which vectorize the user's skill information and compare it with the required skills of the task.

[0788] Specifically, the system receives registration information and stores it in a database. Next, it generates a skill vector using an AI model (e.g., TfidfVectorizer) based on the registered skill information. The required skills of the task are then similarly vectorized and analyzed using methods such as cosine similarity. This allows it to identify the optimal combination of robot and task and generate a proposal.

[0789] The terminal is used by users to access the system and enter their registration information and skill information. Notifications and proposals from the server are also displayed on the terminal. Terminals can be smartphones, tablets, or PCs.

[0790] Users access the system through their devices and input their skills and interests. The server then suggests suitable jobs and activities and notifies the user. For example, if a user has skills such as "welding," "cutting," and "assembly," the server will suggest tasks such as "welder" or "assembler" based on those skills.

[0791] In addition, robots can register their own skill information with the server to perform tasks within the factory. The server uses this information to assign the robot the most suitable tasks. For example, if a robot has the skills of "painting" and "spraying," the server will suggest tasks such as "painting work" based on that.

[0792] As an example of this system-wide behavior, the following prompt sentence is used:

[0793] "Robot A has welding and cutting skills. We currently have a task to perform welding and cutting work. Which robot is best?"

[0794] "Robot B has the skills to paint and spray, and we currently have a painting task. Which robot is best suited to the task?"

[0795] This invention enables efficient matching of robot operators with tasks within a factory, improving productivity and optimizing work efficiency.

[0796] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0797] Step 1:

[0798] A user accesses the system using a terminal and enters the necessary information into the registration form, including the user name, skills, and jobs and activities that the user is interested in. This input data is considered the initial input.

[0799] Step 2:

[0800] The device sends the information entered by the user to the server. The specific data is text data such as username, skills, interests, etc., and is transferred to the server via a communication protocol. The server receives this data and stores it as an initial database entry.

[0801] Step 3:

[0802] The server stores the received user information in a database and vectorizes the registered skill information using an AI model (e.g., TfidfVectorizer). The vectorized skill information is used for subsequent analysis processing. The input is text data, and the output is vector data.

[0803] Step 4:

[0804] When a user creates a new task, they input the required skills and details of the task into the terminal and send it to the server. The terminal accurately transfers this task information to the server and stores it in the task database. The input is the text data of the task, and the output is a task database entry.

[0805] Step 5:

[0806] The server also vectorizes the required skill information of the task and calculates the cosine similarity between the skill vector and the task vector. This evaluates the degree to which the skill information of the registered robot or user matches the required skill of the task. The input is vector data, and the output is a similarity score.

[0807] Step 6:

[0808] The server matches the best robots and users to each task based on the cosine similarity score. The robots and users with the highest scores are selected and recorded as the matching results. The input is the similarity score, and the output is the best matching information.

[0809] Step 7:

[0810] The server generates a response based on the generated matching results and notifies the device. The results include details of the robot and user best suited for each task. The device receives the results and displays them in an easy-to-read format for the user. The input is the matching information, and the output is notification data.

[0811] Step 8:

[0812] The user checks the notification results through their terminal and takes specific actions for the proposed work or task. The user uses an interface to confirm acceptance of a new task or start of work, and sends the results to the server. The input is the user's action data, and the output is the action result.

[0813] Through these steps, efficient matching of robots and tasks within the factory is achieved.

[0814] 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.

[0815] This invention aims to protect forests and improve sustainable living environments by suggesting optimal jobs and activities based on the user's emotional state using a system that combines an emotion engine. By taking into account not only the user's skills but also their emotions, this system achieves more precise and personalized suggestions.

[0816] System configuration

[0817] 1. Server:

[0818] The server receives the registration information entered by the user and stores it in a database. Furthermore, the server has an algorithm for analyzing the user's skills and emotions and executing the matching process. The server also uses an emotion engine to analyze the user's emotional state and suggest optimal jobs and activities based on that data.

[0819] 2. Terminal:

[0820] Users access the system using a terminal and enter their registration information, skill information, and current emotional state. The terminal communicates with the server, receives notifications and suggestions from the server, and displays them to the user.

[0821] 3. User:

[0822] Users use the system based on their skills, interests, and emotional state. Specifically, they register their user information, check the optimal jobs and activities suggested by the system, and even input their own emotional state.

[0823] Program processing

[0824] The specific processing of this system will be explained in natural language below.

[0825] 1. User enters registration information:

[0826] Users access the system from a terminal and fill out a registration form with required information, including their username, skills, and job and activity interests, as well as their current emotional state.

[0827] 2. Data transmission by the device:

[0828] The information entered by the user is sent from the device to the server. Specifically, the device sends the registration information and emotional state to the server via an HTTP request.

[0829] 3. User information registration by the server:

[0830] The server analyzes the registration information and emotional state received from the device and stores it in a database, which stores the user's basic information, skill information, and emotional information.

[0831] 4. Skill and emotion analysis by the server:

[0832] The server analyzes the user's skills and emotional state based on the user information stored in the database. This analysis is a process of identifying and tagging both the skills and emotions possessed by the user.

[0833] 5. The server performs the matching process:

[0834] The server uses AI algorithms to search for the best jobs and activities based on the user's skills and emotional state, comparing job information in the database with the user's skills and emotions to identify matching jobs and activities.

[0835] 6. Server-based suggestion adjustment based on emotions:

[0836] The server also uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions accordingly: for example, if the user is under stress, it will prioritize activities that will reduce stress.

[0837] 7. Server generates matching results:

[0838] The server generates a matching result and formulates a response to notify the user, including details of the job or activity that best suits the user and adjustments that take into account their emotional state.

[0839] 8. Receiving and displaying results on the device:

[0840] The device receives the response from the server and displays the results to the user, who can view the details of the suggested tasks and activities, as well as adjustments that take into account the user's emotional state, on the device screen.

[0841] 9. User confirms the results and selects an action:

[0842] Based on the displayed suggestions, users can select specific actions (such as applying or contacting the organization) to participate in sustainable forest conservation. By taking emotional state into consideration in this way, more personalized suggestions can be made, increasing user satisfaction.

[0843] Specific examples

[0844] For example, user "Sato Hanako" accesses the system and registers her skills of "tree planting" and "forest cultivation," and selects "feeling stressed" as her current emotional state. The server receives this information and stores it in a database. After analyzing it using an AI algorithm, it suggests "forest therapy guide" and "tree planting volunteer" to Sato Hanako. The emotion engine also takes into account her stress level and prioritizes recommending "forest therapy guide," which is expected to have a particularly relaxing effect.

[0845] The results of these suggestions are displayed on the device, and Sato Hanako uses this information to participate in the activities as a "forest therapy guide." In this way, by using this system, optimal suggestions are made that reflect the user's skills and emotional state, contributing to sustainable forest conservation activities.

[0846] The processing flow will be explained below.

[0847] Step 1:

[0848] Users access the system from a terminal and enter required information into a registration form, including their username, skills, and job and activity interests, as well as their current emotional state.

[0849] Step 2:

[0850] The device collects the information entered by the user and sends it to the server via an HTTP request, specifically, the user's username, skill information, job and activity interests, and emotional state.

[0851] Step 3:

[0852] The server analyzes the registration information and emotional state received from the device and stores them in a database, which stores the user's basic information, skill information, and emotional information.

[0853] Step 4:

[0854] The server analyzes the user's skills and emotional state based on the user information stored in the database. Specifically, it performs an analysis process to identify the user's skill set and current emotional state and tag them.

[0855] Step 5:

[0856] The server uses an AI algorithm to search for the best jobs and activities based on the user's skills and emotional state. It compares the job information in the database with the user's skills and emotions to identify matching jobs and activities. For example, based on the skill of "planting a tree" and the emotional state of "feeling stressed," activities with a relaxing effect will be prioritized.

[0857] Step 6:

[0858] The server also uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions accordingly. For example, if the user is under stress, it will prioritize activities that will help reduce stress.

[0859] Step 7:

[0860] The server generates a response based on the results of the matching process and emotion-based adjustments, including details of the optimal task or activity for the user and adjustments that take into account the user's emotional state.

[0861] Step 8:

[0862] The device receives the response from the server and displays the results to the user, including details of the suggested tasks and activities, as well as adjustments that take into account the user's emotional state.

[0863] Step 9:

[0864] The user can check the suggestions displayed on the device and select a specific action. For example, the user can select the "Forest Therapy Guide" suggestion and participate in the activity to contribute to sustainable forest conservation.

[0865] In this way, the system can suggest optimal tasks and activities that take into account the user's skills and emotional state, increasing user satisfaction and contributing to sustainable forest conservation.

[0866] Example 2

[0867] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0868] Previous job and activity suggestion systems mainly based their suggestions on the user's skills and rarely took the user's emotional state into consideration. This meant that they were unable to provide appropriate suggestions to users who felt stressed or dissatisfied, making it difficult to increase user satisfaction. Furthermore, they lacked the ability to analyze the user's emotional state in real time and adjust the suggestions accordingly.

[0869] 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.

[0870] In this invention, the server includes means for receiving registration information of a user, means for analyzing the user's skills based on the registration information, means for analyzing the user's emotional state based on the registration information, means for proposing optimal jobs and activities based on the skills and emotional state, means for adjusting the content of the proposal in real time based on the emotional state, and means for notifying the user of the proposal results. This enables more precise and personalized proposals that take the user's emotional state into consideration, thereby increasing user satisfaction.

[0871] "User" refers to a person who uses the system to input registration information, skills, and emotional state and is then suggested suitable jobs and activities.

[0872] "Registration Information" refers to information used within the system, such as a user's name, skills, and emotional state.

[0873] "Skills" refers to the knowledge, abilities, and experience that a user possesses, and serve as the basis for making proposals.

[0874] "Emotional state" refers to the emotional state the user is currently feeling, information that is used to tailor suggestions.

[0875] "Server" refers to the central computer system that receives and analyzes users' registration information and makes optimal suggestions.

[0876] "Analysis" refers to the process by which the system processes, understands, and classifies data such as registration information, skills, and emotional state.

[0877] "Suggestion" refers to the act of suggesting the best job or activity based on the user's skills and emotional state.

[0878] "Real-time" means that the system processes the information it receives immediately and reflects the results immediately.

[0879] "Notification" refers to the act of the system communicating analysis results and suggestions to the user.

[0880] This invention aims to protect forests and improve sustainable living environments by proposing optimal tasks and activities based on the user's emotional state. The system is primarily composed of three elements: a server, a terminal, and the user.

[0881] System Configuration

[0882] 1. Server:

[0883] The server has the function of receiving registration information entered by the user and storing it in a database.

[0884] The server is equipped with algorithms to analyze the user's skills and emotional state.

[0885] It is equipped with an emotion engine that analyzes the user's emotional state in real time and adjusts the suggestions it makes.

[0886] A proposal result is generated and notified to the user.

[0887] 2. Terminal:

[0888] Users use terminals to access the system and enter information.

[0889] The terminal communicates with the server, receives notifications and proposal results from the server, and displays them.

[0890] 3. User:

[0891] The user uses the terminal to input their registration information, skill information, and emotional state.

[0892] Review and select the suggested tasks and activities.

[0893] Example

[0894] For example, when a user named "Hanako Sato" accesses the system, a registration form appears on the device's web page. She enters her name, her skills of "tree planting" and "forest cultivation," and her current emotional state as "feeling stressed." The device then sends this information to the server.

[0895] The server analyzes the information it receives and stores it in a database, using natural language processing (NLP) techniques to tag skills and emotional states. AI algorithms within the server then search for the most suitable jobs and activities based on these tags. For example, for the skill "tree planting" and the emotional state "feeling stressed," "forest therapy guide" and "tree planting volunteer" are suggested.

[0896] Furthermore, the emotion engine adjusts the suggestions in real time based on the analysis results stored on the server. For example, if Sato Hanako is feeling stressed, the Forest Therapy Guide, which is expected to have a relaxing effect, will be recommended first.

[0897] The results of these proposals are sent from the server to the device and displayed on the device screen. Hanako Sato checks the proposed jobs and activities and participates in the activities as a "forest therapy guide."

[0898] Examples of prompts used in queries

[0899] Based on the prompt sentence, "What kind of activity would have a relaxing effect on a user who is feeling stressed?", the emotion engine makes appropriate suggestions.

[0900] Hardware and software used

[0901] Server: High-performance cloud server (e.g. AWS, Google Cloud)

[0902] Emotion engine: Analysis engine using NLP technology (e.g., OpenAI, Google AI)

[0903] Database: Relational database (e.g. MySQL, PostgreSQL)

[0904] Terminals: General-purpose devices such as PCs, smartphones, and tablets

[0905] This allows for more refined and personalized suggestions that take into account the user's emotional state, enabling them to actively participate in sustainable forest conservation efforts.

[0906] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0907] Step 1:

[0908] Users access the system using their own terminals and enter the necessary information (user name, skills, job interests and activities, emotional state) into the registration form. For example, "Hanako Sato" enters the skills "tree planting" and "forest cultivation" and selects "feeling stressed" as her emotional state. Once the input is complete, the terminal sends this information to the server.

[0909] Step 2:

[0910] The device forms the information entered by the user into an HTTP request and sends it to the server. This request contains the user's name, skills, activities of interest, and emotional state in JSON format. Input data: User name, skills, emotional state, activities of interest. Output data: HTTP request containing these.

[0911] Step 3:

[0912] The server analyzes the HTTP request received from the terminal and extracts the user information. It then stores this information in a database. Input data: User information contained in the HTTP request. Output data: User record in the database.

[0913] Step 4:

[0914] The server analyzes the user's skills and emotional state based on the stored user information. Specifically, it uses NLP technology to identify the user's skills and emotional state and tag them appropriately. Input data: User information in the database. Output data: Tagged skills and emotional state.

[0915] Step 5:

[0916] The server uses AI algorithms to search for the best jobs and activities based on tagged user information. It compares the activity information in the database with the user's skills and emotional state to identify the best match. Input data: tagged skills and emotional state. Output data: list of suggested jobs and activities.

[0917] Step 6:

[0918] The server uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions based on the results. For example, if a user is feeling stressed, it will prioritize suggestions of activities that are expected to have a relaxing effect. Input data: A list of suggested tasks and activities and the user's emotional state. Output data: Adjusted suggestions.

[0919] Step 7:

[0920] The server generates the final matching result and creates a response to notify the user. This response includes adjustments that take into account the user's best suited job or activity details and emotional state. Input data: Adjusted suggestions. Output data: Response (JSON format) sent to the user.

[0921] Step 8:

[0922] The device receives the response from the server and displays the results to the user. The user can check the details of the proposed work or activity and the adjustments that take into account the emotional state on the device screen. Input data: Response from the server. Output data: Proposal results displayed to the user.

[0923] Step 9:

[0924] The user selects a specific action (such as applying or participating) based on the proposal results displayed on the device. For example, "Hanako Sato" decides to participate in the activity as a "forest therapy guide." Input data: Proposal results displayed on the device. Output data: Action selected by the user.

[0925] (Application example 2)

[0926] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0927] While conventional systems can suggest optimal jobs and activities based on a user's skills and interests, they are unable to provide personalized suggestions that take into account the user's emotional state. This makes it difficult to provide appropriate suggestions when the user is in a specific emotional state, resulting in a lack of improvement in the user experience.

[0928] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving registration information of a user, means for analyzing the user's skills based on the registration information, means for proposing optimal jobs and activities based on the skills and emotional state, means for notifying the user of the results of the proposal, and means for using an emotion engine to analyze the emotional state. This enables more precise and personalized proposals that take into account not only the user's skills and interests but also their emotional state.

[0929] "User" means an individual or organization that uses the System.

[0930] "Registration Information" refers collectively to personal information, skill information, and information regarding interests and concerns that a User provides to the System.

[0931] "Skills" refer to specific abilities or expertise possessed by a user.

[0932] "Emotional state" refers to the user's psychological and emotional state, and is information analyzed in real time.

[0933] "Optimal tasks and activities" refers to the most suitable tasks and actions suggested based on the user's skills and emotional state.

[0934] "Proposal results" are detailed information about optimal jobs and activities generated by the system.

[0935] An "emotion engine" is an algorithm or software for analyzing a user's emotional state.

[0936] "Cross-industry matching" refers to the process of suggesting jobs and activities in different industries or fields based on users' skills and interests.

[0937] "Artificial intelligence algorithms" are computational methods that use machine learning and other AI technologies to generate optimal proposals.

[0938] This invention relates to a system that suggests optimal products and services based on the user's emotional state and skills, thereby improving the customer experience in physical stores.

[0939] System configuration

[0940] 1. Server

[0941] The server receives the user's registration information and stores it in a database. Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state and, based on that data, suggests optimal products and services. Specifically, the server uses the following hardware and software:

[0942] Hardware: The server is a commercial server equipped with a high-performance processor and sufficient memory.

[0943] Software: The server-side framework uses Node.js or Python / Django, the database uses PostgreSQL or MySQL, and the sentiment analysis engine uses Microsoft Azure Emotion API or Affectiva.

[0944] 2. Terminal

[0945] Users access the system using a device such as a smartphone or smart glasses and enter their registration information, skill information, and current emotional state. The device communicates with the server, receives notifications and suggestions from the server, and displays them to the user. Specifically, the system uses the following hardware and software:

[0946] Hardware: Smartphones (iOS, Android), smart glasses (e.g. Google Glass, Vuzix), digital signage.

[0947] Software: React Native and Flutter are used as mobile app development frameworks.

[0948] 3. User

[0949] Users use a smartphone app to enter their registration information (such as skills, interests, and shopping goals), and then capture their emotional state through smart glasses or a head-mounted display.The system then provides real-time suggestions, allowing them to select the most suitable products and services.

[0950] Specific examples

[0951] For example, suppose user "Yamada Taro" visits a store and puts on the smart glasses. He inputs into the smartphone app that he is interested in "fashion" and that his goal is to "relieve stress." If emotion analysis determines that his current emotional state indicates "fatigue," the system will prioritize suggestions such as relaxing aroma diffusers and a comfortable clothing section. These suggestions are displayed on Yamada Taro's smartphone and on digital signage within the store.

[0952] Prompt Sentence Examples

[0953] "The client seems a little tired at the moment. Please suggest a product that will help them relax."

[0954] "Show your stressed customers the best service."

[0955] "Provide the latest trends to fashion-conscious customers."

[0956] In this way, the system according to the present invention can provide personalized suggestions that take into account the user's skills and emotional state.

[0957] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0958] Step 1:

[0959] Users access the system using a smartphone app and enter their registration and skill information, including their name, interests and activities, and their current shopping objectives.

[0960] Step 2:

[0961] The terminal sends the user information entered in step 1 to the server via an HTTP request. This request includes the user's skill information and registration information, which the server stores in a database.

[0962] Step 3:

[0963] Users wear smart glasses or head-mounted displays and use facial recognition sensors and microphones to capture their emotional state in real time. The emotion engine analyzes this sensor data to identify the user's emotional state.

[0964] Step 4:

[0965] The device transmits the analyzed emotional state data to the server, which includes specific emotional information such as the stress or happiness the user is feeling.

[0966] Step 5:

[0967] The server uses an AI algorithm to search for optimal products and services based on the user's skill information and emotional state information stored in the database. Specifically, it combines an emotion analysis engine with an AI model to generate recommendations that are optimal for the user's skills and emotional state.

[0968] Step 6:

[0969] The server then sends the generated recommendations to the device via WebSocket or HTTP response, which includes detailed information about the most suitable products and services that take the user's emotional state into account.

[0970] Step 7:

[0971] The device receives the recommendations from the server and displays them to the user. Appropriate recommendations are displayed in real time on smartphones, smart glasses, and in-store digital signage.

[0972] Step 8:

[0973] Users can then select products and services based on the suggestions displayed and enjoy a shopping experience in a physical store. This process enables personalized shopping suggestions based on the user's emotional state and skills.

[0974] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0975] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0976] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[0977] [Fourth embodiment]

[0978] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0979] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0980] 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).

[0981] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0982] 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.

[0983] 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).

[0984] 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.

[0985] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0986] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0987] 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.

[0988] 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.

[0989] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0990] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0991] This invention is a system that matches a wide range of forest-related jobs with the aim of protecting forests and improving sustainable living environments. The system suggests optimal jobs and activities based on the user's skills and promotes communication and information sharing among users. The system also makes full use of artificial intelligence (AI) technology to precisely suggest optimal jobs and activities for users.

[0992] System configuration

[0993] 1. Server:

[0994] The server receives the registration information entered by the user and stores it in a database. The server also analyzes the user's information, performs matching processing, and operates an algorithm to suggest the most suitable jobs and activities.

[0995] 2. Terminal:

[0996] Users access the system using a terminal and enter their registration information and skill information. The terminal communicates with the server, receives notifications and suggestions from the server, and displays them to the user.

[0997] 3. User:

[0998] Users use the system based on their skills and interests by registering their user information and then checking the system's suggestions for suitable jobs and activities.

[0999] Program processing

[1000] The specific processing of this system will be explained in natural language below.

[1001] 1. User enters registration information:

[1002] Users access the system from a terminal and enter required information into a registration form, including their username, skills, and job or activity interests.

[1003] 2. Data transmission by the device:

[1004] The information entered by the user is sent from the terminal to the server, which receives the information and stores it in a database.

[1005] 3. User information registration by the server:

[1006] The server stores the received user information in a database and performs analysis to identify the most suitable jobs and activities based on the user's skills and interests.

[1007] 4. The server performs the matching process:

[1008] The server uses AI algorithms to analyze the user's skills and search the database for the most suitable jobs and activities. Based on the analysis results, it generates the best matching results.

[1009] 5. Server generates matching results:

[1010] The server generates matching results and formulates a response to notify the user, which includes details of the jobs and activities that are most suitable for the user.

[1011] 6. Receiving and displaying results on the device:

[1012] The device receives the response from the server and displays it in an easy-to-read format for the user, who can then review the results and take specific actions to participate in the jobs or activities that interest them.

[1013] Specific examples

[1014] For example, user "Taro Tanaka" has forestry-related skills such as "logging," "chainsaw operation," and "tree planting." Taro Tanaka accesses the system and registers these skills. The server receives Taro Tanaka's information and stores it in a database. An AI algorithm is used to analyze Taro Tanaka's skills and suggests "forestry worker" or "volunteer tree planting" as suitable jobs. The server sends this suggestion result to Taro Tanaka's device as a response, and Taro Tanaka can check the proposed jobs on his device. If Taro Tanaka is interested in the proposed jobs and takes specific action, he can participate in sustainable forest conservation.

[1015] In this way, this system can contribute to nature conservation and improving living conditions.

[1016] The processing flow will be explained below.

[1017] Step 1:

[1018] Users access the system from a terminal and fill out a registration form, including their username, skills, and job and activity interests.

[1019] Step 2:

[1020] The terminal collects the information entered by the user and sends it to the server. Specifically, the terminal sends the registration information to the server via an HTTP request.

[1021] Step 3:

[1022] The server analyzes the registration information received from the device and saves it in a database, which stores the user's basic information and skill information.

[1023] Step 4:

[1024] The server analyzes the user's skills based on the user information stored in the database, which is the process of identifying and tagging the skills that the user possesses.

[1025] Step 5:

[1026] The server uses AI algorithms to find the best jobs and activities based on the user's skills and interests, comparing the job information in the database with the user's skills to identify matching jobs and activities.

[1027] Step 6:

[1028] The server generates the results of the matching process and forms a response to notify the user, including details of the jobs and activities that are best suited for the user.

[1029] Step 7:

[1030] The device receives the response from the server and displays the results to the user, who can then view the details of the proposed tasks and activities on the device screen.

[1031] Step 8:

[1032] Based on the displayed suggestions, users can select specific actions (such as applying or contacting the organization) and participate in sustainable forest conservation.

[1033] Example 1

[1034] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1035] In modern society, forest conservation and the improvement of sustainable living environments are important issues. However, it is extremely difficult for people interested in forest-related occupations and activities to find the most suitable job or activity based on their skills. Conventional methods have a low matching accuracy between users' skills and occupations or activities, making it difficult for users to select occupations or activities that are efficient for them. To solve this problem, the present invention aims to provide a more precise and efficient matching system that makes full use of artificial intelligence technology.

[1036] 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.

[1037] In this invention, the server includes means for receiving registration information of a user, means for storing the registration information in a database, means for analyzing the user's skills based on the registration information, means for searching for optimal jobs or activities based on the skills using an artificial intelligence model, means for generating the proposal results in JSON format, means for notifying the user's terminal of the proposal results, and means for displaying the proposal results on the user's terminal, thereby enabling users to easily find jobs or activities that are optimal for their skills.

[1038] The "means for receiving user registration information" is a function that allows the system to receive information about personal information, skills, and jobs and activities of interest provided by the user.

[1039] The "means for storing the registration information in a database" is a function for recording the received user registration information in a database in order to store it permanently.

[1040] The "means for analyzing the skills of the user based on the registered information" is a function for analyzing the skills possessed by the user using the saved user information.

[1041] "Means for searching for optimal jobs or activities based on the skills using an artificial intelligence model" refers to a function that analyzes a user's skill data using artificial intelligence technology (e.g., a TensorFlow model) and identifies the most suitable job or activity.

[1042] The "means for generating the proposal results in JSON format" is a function for formatting the data obtained as a result of the matching process in JSON format and preparing it as a response from the system.

[1043] The "means for notifying the user terminal of the proposal result" is a function for transmitting the proposal result generated by the server to the user terminal via the network and notifying the user terminal.

[1044] The "means for displaying the proposal results on the user's terminal" is a function for the terminal to analyze the proposal results received from the server and display them in an easy-to-understand manner for the user.

[1045] The present invention is a system for protecting forests and improving sustainable living environments, and suggests optimal jobs and activities based on the user's skills. Specific embodiments for carrying out the present invention are described below.

[1046] This system mainly consists of a server, terminals, and users.

[1047] 1. Server configuration and functions

[1048] The server receives the user's registration information, stores it in a database, analyzes their skills based on the information, and proposes the most suitable jobs and activities. Specifically, the server uses the following hardware and software:

[1049] Hardware: High-performance server (with CPU, memory, and large-capacity storage)

[1050] software:

[1051] Database management system (e.g. MySQL)

[1052] AI analysis model (e.g. TensorFlow)

[1053] JSON parser and HTTP communication library (e.g. FastAPI)

[1054] The server first receives registration information from the user via the device and securely communicates it using the HTTPS protocol. The server then stores the received information in a MySQL database. The stored data is analyzed using a TensorFlow model to suggest optimal jobs and activities based on the user's skills. The proposed results are generated in JSON format and sent as a response to the device.

[1055] 2. Device configuration and functions

[1056] A terminal is a device through which a user accesses the system and enters registration information. Specifically, this includes a smartphone or a PC. The following software is used on the terminal:

[1057] Browser or dedicated application

[1058] Front-end libraries (e.g. React.js)

[1059] When a user accesses the system from a terminal, a registration form is displayed. The user enters their name, skills, and job and activity interests in this form and presses the submit button. The terminal converts this information into JSON format and sends it to the server using the HTTPS protocol. When the terminal receives the proposal results from the server, it analyzes them and displays them in an easy-to-read format for the user.

[1060] 3. User Operation

[1061] Users access the system using their terminal and enter their registration information. For example, if user "Yamada Jiro" has the skills "tree cutting" and "tree planting," he enters this information into the form and submits it. At this time, the server analyzes Yamada Jiro's skill information and uses an AI model to suggest the most suitable jobs and activities. The results of these suggestions are sent to the terminal, where Yamada Jiro can view them and take specific actions to participate in activities that interest him.

[1062] Examples and prompts

[1063] For example, if user "Yamada Jiro" has forestry-related skills such as "logging," "chainsaw operation," and "tree planting," he registers these skills in the system. The server receives Yamada Jiro's information and stores it in a database. An AI model using TensorFlow analyzes Yamada Jiro's skills and suggests "forestry worker" or "tree planting volunteer" as the most suitable jobs. The server sends these suggestions to the device in JSON format, allowing Yamada Jiro to check this information on his own device.

[1064] Prompt Sentence Examples

[1065] "Build a system that suggests the best jobs for users with forest conservation skill sets."

[1066] "Create an AI model that takes user skills as input and matches them with the best forestry-related jobs."

[1067] Through this system, users can easily find jobs and activities that best suit their skills, thereby making a significant contribution to protecting nature and improving living conditions.

[1068] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1069] Step 1:

[1070] User enters registration information

[1071] Users access the system using a terminal and enter their information into the registration form. The input data includes their username, skills (e.g., "tree cutting," "chainsaw operation," "tree planting," etc.), and jobs or activities of interest. Once the input is complete, the user presses the send button, and this data is sent from the terminal to the server. The input data is in JSON format.

[1072] Step 2:

[1073] Sending data by the device

[1074] The terminal sends the registration information provided by the user to the server. Specifically, the terminal encodes the input data in JSON format and securely transmits the data to the server using the HTTPS protocol. The server endpoint is, for example, / api / user / register. The input in this case is the registration information provided by the user, and the output is an HTTPS request to the server.

[1075] Step 3:

[1076] Registration of user information by the server

[1077] The server receives the user information sent from the terminal and stores it in the database. Specifically, the server parses the received JSON data and saves it as a new user record in the MySQL database. The SQL query used is an INSERT statement. The input to this step is the JSON data sent from the terminal, and the output is the user information stored in the database.

[1078] Step 4:

[1079] Matching is performed by the server

[1080] The server uses an AI model to analyze the optimal jobs and activities based on the stored user information. This process uses TensorFlow. The server inputs the stored skill data into the AI ​​model, extracts the skill characteristics, and searches the database for jobs and activities based on them. The output is a list of jobs and activities optimal for the user. The input to this step is the user skills stored in the database, and the output is the analysis results from the AI ​​model.

[1081] Step 5:

[1082] Server-generated matching results

[1083] The server proposes optimal jobs and activities to the user based on the analysis results obtained from the AI ​​model. Specifically, it generates detailed information about the proposal in JSON format. These details include the job title, job description, location, and how to apply. The input to this step is the analysis results from the AI ​​model, and the output is a JSON response containing the proposal results.

[1084] Step 6:

[1085] Receiving and displaying results on the device

[1086] The device receives the response from the server and displays it to the user. Specifically, it parses the received JSON data and displays it on the UI using a front-end framework such as React.js. The user can view detailed information about the proposed jobs and activities and take specific actions to participate in activities that interest them. The input is the JSON response from the server, and the output is the proposal results displayed on the user's screen.

[1087] This processing step allows users to easily find jobs and activities that best suit their skills.

[1088] (Application example 1)

[1089] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1090] In conventional factories, there has been a lack of systems that efficiently match the skills of robot workers with task requirements, which has led to reduced work efficiency and problems with collaboration between humans and robots. Furthermore, the inability to assign the right tasks to the right robots has hindered productivity improvement. To solve these problems, the present invention aims to provide a system that performs optimal matching based on robot skill information and the required task skills.

[1091] 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.

[1092] In this invention, the server includes means for receiving user registration information, means for analyzing the user's skills based on the registration information, means for proposing optimal jobs and activities based on the skills, means for notifying the user of the results of the proposal, means for receiving and saving robot skill information, means for analyzing the required skills of tasks, means for comparing the robot skill information with the required skills of tasks and assigning optimal tasks, and means for displaying the assignment results. This makes it possible to efficiently match robot operators with tasks in a factory, thereby improving productivity and optimizing work efficiency.

[1093] "Users" are individuals or companies who use the system to enter their skills and registration information.

[1094] "Registration information" refers to information that users enter into the system, including data such as skills, interests, and work experience.

[1095] "Skills" are information that represents the specialized abilities, techniques, and aptitudes possessed by users and robots.

[1096] "Analysis" refers to data processing and evaluation to identify the most suitable jobs and tasks based on registration information and skill information.

[1097] "Proposal" is the act of the system showing the user or robot the optimal job or task based on the analysis results.

[1098] "Server" is the central computer of the system, and is a device that receives, stores, analyzes, and performs proposal functions for data.

[1099] A "robot" is a mechanical device that performs work in a factory, has skill information, and is used to perform specific tasks.

[1100] A "task" refers to a specific task or activity to be performed within a factory, with required skills and conditions specified.

[1101] "Required skills" is information that indicates the abilities and techniques required to perform a specific task.

[1102] "Matching" is the process or act of comparing the skill information of the robot or user with the skills required for the task to find the optimal combination.

[1103] "Notification" refers to the act of the system communicating the proposal results and matching results to the user or robot administrator.

[1104] "Comparison" refers to the act of comparing two or more elements, namely the robot's skill information and the required skills of the task, and evaluating the degree of agreement.

[1105] The present invention provides a system for realizing efficient task allocation for robot workers in a factory. The system includes a server, a terminal, a user, and a robot.

[1106] The server receives the user's registration information and stores it in a database. The server analyzes the user's skills based on this registration information and runs an algorithm to suggest the most suitable jobs and activities. The main software used by the server includes Python and scikit-learn, which vectorize the user's skill information and compare it with the required skills of the task.

[1107] Specifically, the system receives registration information and stores it in a database. Next, it generates a skill vector using an AI model (e.g., TfidfVectorizer) based on the registered skill information. The required skills of the task are then similarly vectorized and analyzed using methods such as cosine similarity. This allows it to identify the optimal combination of robot and task and generate a proposal.

[1108] The terminal is used by users to access the system and enter their registration information and skill information. Notifications and proposals from the server are also displayed on the terminal. Terminals can be smartphones, tablets, or PCs.

[1109] Users access the system through their devices and input their skills and interests. The server then suggests suitable jobs and activities and notifies the user. For example, if a user has skills such as "welding," "cutting," and "assembly," the server will suggest tasks such as "welder" or "assembler" based on those skills.

[1110] In addition, robots can register their own skill information with the server to perform tasks within the factory. The server uses this information to assign the robot the most suitable tasks. For example, if a robot has the skills of "painting" and "spraying," the server will suggest tasks such as "painting work" based on that.

[1111] As an example of this system-wide behavior, the following prompt sentence is used:

[1112] "Robot A has welding and cutting skills. We currently have a task to perform welding and cutting work. Which robot is best?"

[1113] "Robot B has the skills to paint and spray, and we currently have a painting task. Which robot is best suited to the task?"

[1114] This invention enables efficient matching of robot operators with tasks within a factory, improving productivity and optimizing work efficiency.

[1115] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1116] Step 1:

[1117] A user accesses the system using a terminal and enters the necessary information into the registration form, including the user name, skills, and jobs and activities that the user is interested in. This input data is considered the initial input.

[1118] Step 2:

[1119] The device sends the information entered by the user to the server. The specific data is text data such as username, skills, interests, etc., and is transferred to the server via a communication protocol. The server receives this data and stores it as an initial database entry.

[1120] Step 3:

[1121] The server stores the received user information in a database and vectorizes the registered skill information using an AI model (e.g., TfidfVectorizer). The vectorized skill information is used for subsequent analysis processing. The input is text data, and the output is vector data.

[1122] Step 4:

[1123] When a user creates a new task, they input the required skills and details of the task into the terminal and send it to the server. The terminal accurately transfers this task information to the server and stores it in the task database. The input is the text data of the task, and the output is a task database entry.

[1124] Step 5:

[1125] The server also vectorizes the required skill information of the task and calculates the cosine similarity between the skill vector and the task vector. This evaluates the degree to which the skill information of the registered robot or user matches the required skill of the task. The input is vector data, and the output is a similarity score.

[1126] Step 6:

[1127] The server matches the best robots and users to each task based on the cosine similarity score. The robots and users with the highest scores are selected and recorded as the matching results. The input is the similarity score, and the output is the best matching information.

[1128] Step 7:

[1129] The server generates a response based on the generated matching results and notifies the device. The results include details of the robot and user best suited for each task. The device receives the results and displays them in an easy-to-read format for the user. The input is the matching information, and the output is notification data.

[1130] Step 8:

[1131] The user checks the notification results through their terminal and takes specific actions for the proposed work or task. The user uses an interface to confirm acceptance of a new task or start of work, and sends the results to the server. The input is the user's action data, and the output is the action result.

[1132] Through these steps, efficient matching of robots and tasks within the factory is achieved.

[1133] 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.

[1134] This invention aims to protect forests and improve sustainable living environments by suggesting optimal jobs and activities based on the user's emotional state using a system that combines an emotion engine. By taking into account not only the user's skills but also their emotions, this system achieves more precise and personalized suggestions.

[1135] System configuration

[1136] 1. Server:

[1137] The server receives the registration information entered by the user and stores it in a database. Furthermore, the server has an algorithm for analyzing the user's skills and emotions and executing the matching process. The server also uses an emotion engine to analyze the user's emotional state and suggest optimal jobs and activities based on that data.

[1138] 2. Terminal:

[1139] Users access the system using a terminal and enter their registration information, skill information, and current emotional state. The terminal communicates with the server, receives notifications and suggestions from the server, and displays them to the user.

[1140] 3. User:

[1141] Users use the system based on their skills, interests, and emotional state. Specifically, they register their user information, check the optimal jobs and activities suggested by the system, and even input their own emotional state.

[1142] Program processing

[1143] The specific processing of this system will be explained in natural language below.

[1144] 1. User enters registration information:

[1145] Users access the system from a terminal and fill out a registration form with required information, including their username, skills, and job and activity interests, as well as their current emotional state.

[1146] 2. Data transmission by the device:

[1147] The information entered by the user is sent from the device to the server. Specifically, the device sends the registration information and emotional state to the server via an HTTP request.

[1148] 3. User information registration by the server:

[1149] The server analyzes the registration information and emotional state received from the device and stores it in a database, which stores the user's basic information, skill information, and emotional information.

[1150] 4. Skill and emotion analysis by the server:

[1151] The server analyzes the user's skills and emotional state based on the user information stored in the database. This analysis is a process of identifying and tagging both the skills and emotions possessed by the user.

[1152] 5. The server performs the matching process:

[1153] The server uses AI algorithms to search for the best jobs and activities based on the user's skills and emotional state, comparing job information in the database with the user's skills and emotions to identify matching jobs and activities.

[1154] 6. Server-based suggestion adjustment based on emotions:

[1155] The server also uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions accordingly: for example, if the user is under stress, it will prioritize activities that will reduce stress.

[1156] 7. Server generates matching results:

[1157] The server generates a matching result and formulates a response to notify the user, including details of the job or activity that best suits the user and adjustments that take into account their emotional state.

[1158] 8. Receiving and displaying results on the device:

[1159] The device receives the response from the server and displays the results to the user, who can view the details of the suggested tasks and activities, as well as adjustments that take into account the user's emotional state, on the device screen.

[1160] 9. User confirms the results and selects an action:

[1161] Based on the displayed suggestions, users can select specific actions (such as applying or contacting the organization) to participate in sustainable forest conservation. By taking emotional state into consideration in this way, more personalized suggestions can be made, increasing user satisfaction.

[1162] Specific examples

[1163] For example, user "Sato Hanako" accesses the system and registers her skills of "tree planting" and "forest cultivation," and selects "feeling stressed" as her current emotional state. The server receives this information and stores it in a database. After analyzing it using an AI algorithm, it suggests "forest therapy guide" and "tree planting volunteer" to Sato Hanako. The emotion engine also takes into account her stress level and prioritizes recommending "forest therapy guide," which is expected to have a particularly relaxing effect.

[1164] The results of these suggestions are displayed on the device, and Sato Hanako uses this information to participate in the activities as a "forest therapy guide." In this way, by using this system, optimal suggestions are made that reflect the user's skills and emotional state, contributing to sustainable forest conservation activities.

[1165] The processing flow will be explained below.

[1166] Step 1:

[1167] Users access the system from a terminal and enter required information into a registration form, including their username, skills, and job and activity interests, as well as their current emotional state.

[1168] Step 2:

[1169] The device collects the information entered by the user and sends it to the server via an HTTP request, specifically, the user's username, skill information, job and activity interests, and emotional state.

[1170] Step 3:

[1171] The server analyzes the registration information and emotional state received from the device and stores them in a database, which stores the user's basic information, skill information, and emotional information.

[1172] Step 4:

[1173] The server analyzes the user's skills and emotional state based on the user information stored in the database. Specifically, it performs an analysis process to identify the user's skill set and current emotional state and tag them.

[1174] Step 5:

[1175] The server uses an AI algorithm to search for the best jobs and activities based on the user's skills and emotional state. It compares the job information in the database with the user's skills and emotions to identify matching jobs and activities. For example, based on the skill of "planting a tree" and the emotional state of "feeling stressed," activities with a relaxing effect will be prioritized.

[1176] Step 6:

[1177] The server also uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions accordingly. For example, if the user is under stress, it will prioritize activities that will help reduce stress.

[1178] Step 7:

[1179] The server generates a response based on the results of the matching process and emotion-based adjustments, including details of the optimal task or activity for the user and adjustments that take into account the user's emotional state.

[1180] Step 8:

[1181] The device receives the response from the server and displays the results to the user, including details of the suggested tasks and activities, as well as adjustments that take into account the user's emotional state.

[1182] Step 9:

[1183] The user can check the suggestions displayed on the device and select a specific action. For example, the user can select the "Forest Therapy Guide" suggestion and participate in the activity to contribute to sustainable forest conservation.

[1184] In this way, the system can suggest optimal tasks and activities that take into account the user's skills and emotional state, increasing user satisfaction and contributing to sustainable forest conservation.

[1185] Example 2

[1186] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1187] Previous job and activity suggestion systems mainly based their suggestions on the user's skills and rarely took the user's emotional state into consideration. This meant that they were unable to provide appropriate suggestions to users who felt stressed or dissatisfied, making it difficult to increase user satisfaction. Furthermore, they lacked the ability to analyze the user's emotional state in real time and adjust the suggestions accordingly.

[1188] 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.

[1189] In this invention, the server includes means for receiving registration information of a user, means for analyzing the user's skills based on the registration information, means for analyzing the user's emotional state based on the registration information, means for proposing optimal jobs and activities based on the skills and emotional state, means for adjusting the content of the proposal in real time based on the emotional state, and means for notifying the user of the proposal results. This enables more precise and personalized proposals that take the user's emotional state into consideration, thereby increasing user satisfaction.

[1190] "User" refers to a person who uses the system to input registration information, skills, and emotional state and is then suggested suitable jobs and activities.

[1191] "Registration Information" refers to information used within the system, such as a user's name, skills, and emotional state.

[1192] "Skills" refers to the knowledge, abilities, and experience that a user possesses, and serve as the basis for making proposals.

[1193] "Emotional state" refers to the emotional state the user is currently feeling, information that is used to tailor suggestions.

[1194] "Server" refers to the central computer system that receives and analyzes users' registration information and makes optimal suggestions.

[1195] "Analysis" refers to the process by which the system processes, understands, and classifies data such as registration information, skills, and emotional state.

[1196] "Suggestion" refers to the act of suggesting the best job or activity based on the user's skills and emotional state.

[1197] "Real-time" means that the system processes the information it receives immediately and reflects the results immediately.

[1198] "Notification" refers to the act of the system communicating analysis results and suggestions to the user.

[1199] This invention aims to protect forests and improve sustainable living environments by proposing optimal tasks and activities based on the user's emotional state. The system is primarily composed of three elements: a server, a terminal, and the user.

[1200] System Configuration

[1201] 1. Server:

[1202] The server has the function of receiving registration information entered by the user and storing it in a database.

[1203] The server is equipped with algorithms to analyze the user's skills and emotional state.

[1204] It is equipped with an emotion engine that analyzes the user's emotional state in real time and adjusts the suggestions it makes.

[1205] A proposal result is generated and notified to the user.

[1206] 2. Terminal:

[1207] Users use terminals to access the system and enter information.

[1208] The terminal communicates with the server, receives notifications and proposal results from the server, and displays them.

[1209] 3. User:

[1210] The user uses the terminal to input their registration information, skill information, and emotional state.

[1211] Review and select the suggested tasks and activities.

[1212] Example

[1213] For example, when a user named "Hanako Sato" accesses the system, a registration form appears on the device's web page. She enters her name, her skills of "tree planting" and "forest cultivation," and her current emotional state as "feeling stressed." The device then sends this information to the server.

[1214] The server analyzes the information it receives and stores it in a database, using natural language processing (NLP) techniques to tag skills and emotional states. AI algorithms within the server then search for the most suitable jobs and activities based on these tags. For example, for the skill "tree planting" and the emotional state "feeling stressed," "forest therapy guide" and "tree planting volunteer" are suggested.

[1215] Furthermore, the emotion engine adjusts the suggestions in real time based on the analysis results stored on the server. For example, if Sato Hanako is feeling stressed, the Forest Therapy Guide, which is expected to have a relaxing effect, will be recommended first.

[1216] The results of these proposals are sent from the server to the device and displayed on the device screen. Hanako Sato checks the proposed jobs and activities and participates in the activities as a "forest therapy guide."

[1217] Examples of prompts used in queries

[1218] Based on the prompt sentence, "What kind of activity would have a relaxing effect on a user who is feeling stressed?", the emotion engine makes appropriate suggestions.

[1219] Hardware and software used

[1220] Server: High-performance cloud server (e.g. AWS, Google Cloud)

[1221] Emotion engine: Analysis engine using NLP technology (e.g., OpenAI, Google AI)

[1222] Database: Relational database (e.g. MySQL, PostgreSQL)

[1223] Terminals: General-purpose devices such as PCs, smartphones, and tablets

[1224] This allows for more refined and personalized suggestions that take into account the user's emotional state, enabling them to actively participate in sustainable forest conservation efforts.

[1225] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1226] Step 1:

[1227] Users access the system using their own terminals and enter the necessary information (user name, skills, job interests and activities, emotional state) into the registration form. For example, "Hanako Sato" enters the skills "tree planting" and "forest cultivation" and selects "feeling stressed" as her emotional state. Once the input is complete, the terminal sends this information to the server.

[1228] Step 2:

[1229] The device forms the information entered by the user into an HTTP request and sends it to the server. This request contains the user's name, skills, activities of interest, and emotional state in JSON format. Input data: User name, skills, emotional state, activities of interest. Output data: HTTP request containing these.

[1230] Step 3:

[1231] The server analyzes the HTTP request received from the terminal and extracts the user information. It then stores this information in a database. Input data: User information contained in the HTTP request. Output data: User record in the database.

[1232] Step 4:

[1233] The server analyzes the user's skills and emotional state based on the stored user information. Specifically, it uses NLP technology to identify the user's skills and emotional state and tag them appropriately. Input data: User information in the database. Output data: Tagged skills and emotional state.

[1234] Step 5:

[1235] The server uses AI algorithms to search for the best jobs and activities based on tagged user information. It compares the activity information in the database with the user's skills and emotional state to identify the best match. Input data: tagged skills and emotional state. Output data: list of suggested jobs and activities.

[1236] Step 6:

[1237] The server uses an emotion engine to analyze the user's emotional state in real time and adjusts the suggestions based on the results. For example, if a user is feeling stressed, it will prioritize suggestions of activities that are expected to have a relaxing effect. Input data: A list of suggested tasks and activities and the user's emotional state. Output data: Adjusted suggestions.

[1238] Step 7:

[1239] The server generates the final matching result and creates a response to notify the user. This response includes adjustments that take into account the user's best suited job or activity details and emotional state. Input data: Adjusted suggestions. Output data: Response (JSON format) sent to the user.

[1240] Step 8:

[1241] The device receives the response from the server and displays the results to the user. The user can check the details of the proposed work or activity and the adjustments that take into account the emotional state on the device screen. Input data: Response from the server. Output data: Proposal results displayed to the user.

[1242] Step 9:

[1243] The user selects a specific action (such as applying or participating) based on the proposal results displayed on the device. For example, "Hanako Sato" decides to participate in the activity as a "forest therapy guide." Input data: Proposal results displayed on the device. Output data: Action selected by the user.

[1244] (Application example 2)

[1245] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1246] While conventional systems can suggest optimal jobs and activities based on a user's skills and interests, they are unable to provide personalized suggestions that take into account the user's emotional state. This makes it difficult to provide appropriate suggestions when the user is in a specific emotional state, resulting in a lack of improvement in the user experience.

[1247] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving registration information of a user, means for analyzing the user's skills based on the registration information, means for proposing optimal jobs and activities based on the skills and emotional state, means for notifying the user of the results of the proposal, and means for using an emotion engine to analyze the emotional state. This enables more precise and personalized proposals that take into account not only the user's skills and interests but also their emotional state.

[1248] "User" means an individual or organization that uses the System.

[1249] "Registration Information" refers collectively to personal information, skill information, and information regarding interests and concerns that a User provides to the System.

[1250] "Skills" refer to specific abilities or expertise possessed by a user.

[1251] "Emotional state" refers to the user's psychological and emotional state, and is information analyzed in real time.

[1252] "Optimal tasks and activities" refers to the most suitable tasks and actions suggested based on the user's skills and emotional state.

[1253] "Proposal results" are detailed information about optimal jobs and activities generated by the system.

[1254] An "emotion engine" is an algorithm or software for analyzing a user's emotional state.

[1255] "Cross-industry matching" refers to the process of suggesting jobs and activities in different industries or fields based on users' skills and interests.

[1256] "Artificial intelligence algorithms" are computational methods that use machine learning and other AI technologies to generate optimal proposals.

[1257] This invention relates to a system that suggests optimal products and services based on the user's emotional state and skills, thereby improving the customer experience in physical stores.

[1258] System configuration

[1259] 1. Server

[1260] The server receives the user's registration information and stores it in a database. Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state and, based on that data, suggests optimal products and services. Specifically, the server uses the following hardware and software:

[1261] Hardware: The server is a commercial server equipped with a high-performance processor and sufficient memory.

[1262] Software: The server-side framework uses Node.js or Python / Django, the database uses PostgreSQL or MySQL, and the sentiment analysis engine uses Microsoft Azure Emotion API or Affectiva.

[1263] 2. Terminal

[1264] Users access the system using a device such as a smartphone or smart glasses and enter their registration information, skill information, and current emotional state. The device communicates with the server, receives notifications and suggestions from the server, and displays them to the user. Specifically, the system uses the following hardware and software:

[1265] Hardware: Smartphones (iOS, Android), smart glasses (e.g. Google Glass, Vuzix), digital signage.

[1266] Software: React Native and Flutter are used as mobile app development frameworks.

[1267] 3. User

[1268] Users use a smartphone app to enter their registration information (such as skills, interests, and shopping goals), and then capture their emotional state through smart glasses or a head-mounted display.The system then provides real-time suggestions, allowing them to select the most suitable products and services.

[1269] Specific examples

[1270] For example, suppose user "Yamada Taro" visits a store and puts on the smart glasses. He inputs into the smartphone app that he is interested in "fashion" and that his goal is to "relieve stress." If emotion analysis determines that his current emotional state indicates "fatigue," the system will prioritize suggestions such as relaxing aroma diffusers and a comfortable clothing section. These suggestions are displayed on Yamada Taro's smartphone and on digital signage within the store.

[1271] Prompt Sentence Examples

[1272] "The client seems a little tired at the moment. Please suggest a product that will help them relax."

[1273] "Show your stressed customers the best service."

[1274] "Provide the latest trends to fashion-conscious customers."

[1275] In this way, the system according to the present invention can provide personalized suggestions that take into account the user's skills and emotional state.

[1276] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1277] Step 1:

[1278] Users access the system using a smartphone app and enter their registration and skill information, including their name, interests and activities, and their current shopping objectives.

[1279] Step 2:

[1280] The terminal sends the user information entered in step 1 to the server via an HTTP request. This request includes the user's skill information and registration information, which the server stores in a database.

[1281] Step 3:

[1282] Users wear smart glasses or head-mounted displays and use facial recognition sensors and microphones to capture their emotional state in real time. The emotion engine analyzes this sensor data to identify the user's emotional state.

[1283] Step 4:

[1284] The device transmits the analyzed emotional state data to the server, which includes specific emotional information such as the stress or happiness the user is feeling.

[1285] Step 5:

[1286] The server uses an AI algorithm to search for optimal products and services based on the user's skill information and emotional state information stored in the database. Specifically, it combines an emotion analysis engine with an AI model to generate recommendations that are optimal for the user's skills and emotional state.

[1287] Step 6:

[1288] The server then sends the generated recommendations to the device via WebSocket or HTTP response, which includes detailed information about the most suitable products and services that take the user's emotional state into account.

[1289] Step 7:

[1290] The device receives the recommendations from the server and displays them to the user. Appropriate recommendations are displayed in real time on smartphones, smart glasses, and in-store digital signage.

[1291] Step 8:

[1292] Users can then select products and services based on the suggestions displayed and enjoy a shopping experience in a physical store. This process enables personalized shopping suggestions based on the user's emotional state and skills.

[1293] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1294] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1295] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1296] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1297] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1298] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1299] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1300] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1301] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1302] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1303] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1304] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1305] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1306] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1307] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1308] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1309] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1310] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1311] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1312] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1313] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1314] The following is further disclosed regarding the above embodiment.

[1315] (Claim 1)

[1316] means for receiving user registration information;

[1317] means for analyzing the skills of users based on the registration information;

[1318] a means for suggesting optimal jobs or activities based on said skills;

[1319] means for notifying a user of the proposal result;

[1320] A system including:

[1321] (Claim 2)

[1322] The system of claim 1, wherein the system suggests jobs and activities in different fields that match the user's interests and skills in order to perform cross-industry matching.

[1323] (Claim 3)

[1324] 10. The system of claim 1, wherein an artificial intelligence algorithm is used to suggest the optimal job or activity.

[1325] "Example 1"

[1326] (Claim 1)

[1327] means for receiving user registration information;

[1328] means for storing the registration information in a database;

[1329] means for analyzing the skills of users based on the registration information;

[1330] means for searching for optimal jobs or activities based on said skills using an artificial intelligence model;

[1331] means for generating the proposal results in JSON format;

[1332] means for notifying a user terminal of the proposal result;

[1333] means for displaying the proposal results on a user's terminal;

[1334] A system including:

[1335] (Claim 2)

[1336] The system of claim 1, wherein the system suggests jobs and activities in different fields that match the user's interests and skills in order to perform cross-industry matching.

[1337] (Claim 3)

[1338] 10. The system of claim 1, wherein the system uses a generative AI model to analyze a user's skills and suggest optimal jobs and activities.

[1339] "Application Example 1"

[1340] (Claim 1)

[1341] means for receiving user registration information;

[1342] means for analyzing the skills of users based on the registration information;

[1343] a means for suggesting optimal jobs or activities based on said skills;

[1344] means for notifying a user of the proposal result;

[1345] means for receiving and storing robot skill information;

[1346] A means of analyzing the skill requirements of a task;

[1347] A means for comparing the robot's skill information with the required skill of the task and assigning the optimal task;

[1348] means for displaying the allocation result;

[1349] A system including:

[1350] (Claim 2)

[1351] The system of claim 1, wherein the system suggests jobs and activities in different fields that match the user's interests and skills in order to perform cross-industry matching.

[1352] (Claim 3)

[1353] 10. The system of claim 1, wherein an artificial intelligence algorithm is used to suggest the optimal job or activity.

[1354] "Example 2: Combining Emotion Engines"

[1355] (Claim 1)

[1356] means for receiving user registration information;

[1357] means for analyzing the skills of users based on the registration information;

[1358] means for analyzing the emotional state of the user based on the registered information;

[1359] means for suggesting optimal tasks or activities based on said skills and emotional state;

[1360] means for adjusting the suggestions in real time based on the emotional state;

[1361] means for notifying a user of the proposal result;

[1362] A system including:

[1363] (Claim 2)

[1364] The system of claim 1, wherein the system suggests jobs and activities in different fields that match the user's interests and skills in order to perform cross-industry matching.

[1365] (Claim 3)

[1366] 10. The system of claim 1, wherein an artificial intelligence algorithm is used to suggest the optimal job or activity.

[1367] "Application example 2 when combining emotion engines"

[1368] (Claim 1)

[1369] means for receiving user registration information;

[1370] means for analyzing the skills of users based on the registration information;

[1371] means for suggesting optimal tasks or activities based on said skills and emotional state;

[1372] means for notifying a user of the proposal result;

[1373] means for using an emotion engine to analyze an emotional state;

[1374] A system including:

[1375] (Claim 2)

[1376] The system of claim 1, wherein the system suggests jobs and activities in different fields that match the user's interests, skills, and emotional state in order to perform cross-industry matching.

[1377] (Claim 3)

[1378] 10. The system of claim 1, wherein the system uses an artificial intelligence algorithm and a sentiment analysis engine to suggest the optimal job or activity. [Explanation of symbols]

[1379] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving user registration information; means for analyzing the skills of users based on the registration information; a means for suggesting optimal jobs or activities based on said skills; means for notifying a user of the proposal result; A system including:

2. The system according to claim 1, wherein the system suggests jobs and activities in different fields that match the user's interests and skills in order to perform cross-industry matching.

3. The system of claim 1 , wherein the system uses an artificial intelligence algorithm to suggest the optimal job or activity.

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