system

Abstract

We provide the system. [Solution] A means for generating a program summary obtained from an open-source platform, Means for constructing a knowledge base storing the aforementioned summary, A means for searching the aforementioned knowledge base based on social issues entered by users and proposing related technological ideas and their implementations, A means of presenting the proposed technical idea and implementation to the user, A means of exploring and proposing solutions to urban challenges, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There are a large number of computer programs on open source platforms, but it is difficult to efficiently find useful technical ideas and implementations for solving social issues among them. Also, there is a problem that an enormous amount of time and labor are required to propose appropriate solutions to social issues.

Means for Solving the Problems

[0005] This invention provides a means for generating summaries of computer programs obtained from open-source platforms and storing them in a database. Furthermore, it includes a means for searching the database and suggesting related technological ideas and their implementations when a user inputs a specific social issue. This allows users to efficiently obtain ideas for solving problems and quickly implement them.

[0006] An "open-source platform" refers to an online location where software can be freely used, modified, and shared, and whose source code is publicly available.

[0007] A "computer program" refers to a set of instructions written to perform a specific function on a computer.

[0008] "Means for generating summaries" refers to a method or apparatus that has the function of extracting the key points from lengthy software code or documents and summarizing them in a short, concise form.

[0009] A "database" refers to a system for organizing, managing, and electronically storing large amounts of information in a quickly accessible format.

[0010] A "technical idea" refers to an original way of thinking or a concept for solving a particular technical problem.

[0011] "Means of proposing implementation" refers to a process or function for proposing how to incorporate a specific idea into a concrete, working system or product.

[0012] A "user" refers to an individual or organization that uses a system to solve a specific purpose or problem.

[0013] "Social issues" refer to problems or challenges that arise from social factors and require solutions. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0015] [[ID=<<MASK>>48]] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] The invention's system primarily consists of multiple computer devices (servers and terminals). Here, we illustrate the flow of the system's main functions: program acquisition from an open-source platform, summary generation, database construction, and search and idea generation in response to social issues.

[0036] The server periodically scans open-source platforms and retrieves new program repositories. Next, it uses a generative AI model to summarize the code in each repository in human-readable language. This summary information is stored in a database designed for efficient searching. As a result, the database functions as a massive knowledge base, containing a wide variety of technical ideas and their implementation information.

[0037] The user inputs a social issue they want to solve via their device. This input is sent to a server, which analyzes the issue to generate an appropriate search query. Using the generated query, the server searches its database for and suggests relevant technical ideas and implementation information.

[0038] For example, if a user is looking for a "system to reduce food waste," the server will search for relevant programs and ideas and suggest potentially relevant technical solutions such as a "household inventory management app" or a "local sharing platform." Based on these suggestions, the user can leverage existing implementations and quickly deploy their own project.

[0039] In this way, the invention efficiently extracts and provides ideas for solving social problems faced by many people. Users can utilize the proposed technology to implement valuable projects in a short period of time. This system reduces the burden on users through automated processes and dramatically increases the possibility of solving problems.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The server retrieves the latest repository information from open-source platforms. This involves using APIs to crawl publicly available repositories and collect program data.

[0043] Step 2:

[0044] The server analyzes the collected program data and generates a summary of each program using a generative AI model. The summary is output as natural language text in a format that is easy for humans to understand.

[0045] Step 3:

[0046] The server stores the generated summary in a database. In addition to the summarized information, related metadata (e.g., repository name, author, update date, etc.) is also stored there.

[0047] Step 4:

[0048] Users input the social issue they want to solve via their device. This involves text input, providing keywords and sentences related to the issue.

[0049] Step 5:

[0050] The terminal sends user input information to the server. The server receives this information and generates an appropriate search query based on the entered task.

[0051] Step 6:

[0052] The server uses the generated search query to search the database. It extracts relevant technical ideas and their implementation information from the database and lists the most relevant results.

[0053] Step 7:

[0054] The server sends the extracted search results to the terminal. The terminal receives these results and displays the suggested technical ideas and corresponding implementation information to the user.

[0055] Step 8:

[0056] Users review the presented information, view links to repositories and implementation guides as needed, and then proceed to start and run the project.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] In response to the diverse social challenges of today, there is a need to find appropriate and rapid technological solutions and provide users with ways to effectively utilize them. However, efficiently extracting, summarizing, and appropriately presenting relevant information from a vast program repository is difficult and burdensome for users.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes means for generating a summary of an electronic program obtained from a software platform, means for constructing an information storage device that stores the summary, and means for searching the information storage device based on a social issue input by a user and proposing relevant technical solutions and methods for their implementation. This enables users to quickly discover and implement technical solutions for solving social issues.

[0062] A "software platform" refers to software repositories or code-sharing sites that users can access over the internet.

[0063] An "electronic program" is a series of instructions or code executed by a computer, and is a component of software.

[0064] A "summary" is a concise explanatory text that describes the main functions and features of an electronic program.

[0065] An "information storage device" is a database or storage system capable of storing digital data over long periods of time.

[0066] A "user" is an individual or legal entity that uses this system to solve social problems.

[0067] "Social issues" refer to problems or challenges faced by society as a whole or by a specific community, and include those that require technological solutions.

[0068] A "technical proposal" is a technical idea or concept proposed as a means of solving a specific problem.

[0069] "Implementation method" refers to the specific steps and processes for developing a technical proposal into a concrete form and putting it into practice.

[0070] The system in this invention consists of a user, a server, and a terminal.

[0071] The server first periodically accesses the software platform via the internet to acquire new electronic programs. This process utilizes a Linux® server and Python scripts, employing publicly available APIs. The server inputs the acquired programs into a generating AI model (e.g., an open-source natural language processing model) to generate a summary in a human-readable format. An example of a prompt in this process is, "Please explain the main function and purpose of this code."

[0072] Next, the server saves the generated summary to an information storage device (SQL database). This database is indexed, allowing for efficient searching. This enables the rapid management of multiple technical proposals and their implementation methods.

[0073] On the other hand, users input the social issues they want to solve via their own devices (personal computers or mobile devices). This input is expressed in natural language and sent to the server via the internet.

[0074] The server analyzes the user's request using natural language processing algorithms (e.g., Spacy or NLTK) and extracts relevant keywords. Based on the resulting search queries, the server searches its information storage device, identifies relevant technical proposals and implementation methods, and proposes them to the user.

[0075] For example, if a user searches for "ways to reduce energy consumption," the server will provide relevant suggestions such as "efficient energy management systems" or "smart home technologies." Users can then use these suggestions to quickly and effectively find solutions to their challenges. This process enables users to facilitate the implementation of new projects and contribute to solving social problems.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The server periodically retrieves new electronic programs using the software platform's API. The input is a program repository stored on a specific open-source platform. It filters the data by calling the API and selects relevant repositories based on criteria such as keywords and stars. The output is a list of related repositories.

[0079] Step 2:

[0080] The server inputs the acquired program into a generating AI model to generate a summary. The input is a code block obtained from the repository. Specifically, the server sends a prompt to the generating AI model asking, "Please explain the main function and purpose of this code." The model responds with a summary in natural language. The output is a summarized text in a human-readable format.

[0081] Step 3:

[0082] The server stores the generated summary in an SQL database, which is an information storage device. The input is the summary text generated in the previous step. The server indexes this summary, creating a structure that enables efficient searching. The output is a searchable database entry.

[0083] Step 4:

[0084] The user inputs a social issue they want to solve in natural language via their device. The input is text about the issue the user has in mind. The device sends this information to the server via the internet. The output is the text of the issue received by the server.

[0085] Step 5:

[0086] The server analyzes the user's task and generates a search query. The input is the text of the task sent from the terminal. The server uses natural language processing tools to analyze the text and extract relevant keywords. The output is the search query generated based on these keywords.

[0087] Step 6:

[0088] The server uses the generated query to search the database and identify relevant technical solutions and implementation methods. The input is the search query created in the previous step. The SQL query is executed against the database to retrieve the relevant dataset. The output is a list of technical solutions related to the user's problem.

[0089] Step 7:

[0090] The server presents the identified technical proposals and their implementation methods to the user. The input is a list of technical proposals resulting from a database search. The server sends this information back to the terminal and displays it in a user-friendly format. The output is the list of technical proposals and their implementation methods displayed on the terminal.

[0091] Step 8:

[0092] The user plans and implements a specific project based on the presented technical proposals. The input is information on the technical proposals obtained from the server. The user uses this information to plan the project. The output is the project that is actually planned and implemented.

[0093] (Application Example 1)

[0094] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0095] In modern society, the advancement of urbanization has brought to light a wide variety of challenges, including traffic congestion, energy efficiency, and environmental problems. To address these challenges quickly and easily, it is necessary to efficiently utilize existing technologies and ideas. However, the amount of related information is vast, making its organization and retrieval difficult, thus requiring a rapid response to problem-solving.

[0096] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0097] In this invention, the server includes means for generating summaries of programs obtained from an open-source platform, means for constructing a knowledge base storing the summaries, and means for searching the knowledge base based on social issues input by users and proposing relevant technical ideas and their implementations. This makes it possible to effectively explore solutions to urban problems and quickly present the technical ideas and implementation information that users need.

[0098] An "open-source platform" is a foundation that provides repositories and projects of programs that can be freely accessed on the internet.

[0099] A "summary" is a short, human-readable summary of information about a program obtained from an open-source platform.

[0100] A "knowledge base" is a collection of information that stores generated summaries, enabling efficient searching and information provision.

[0101] "Users" refer to individuals or organizations that use the system to explore solutions to social problems.

[0102] "Social issues" refer to general or specific problems that need to be solved in cities, such as traffic congestion, energy efficiency, and environmental issues.

[0103] A "technical idea" is a conceptual or practical proposal that refers to a solution or method for addressing a specific problem.

[0104] "Implementation" refers to the act or result of transforming a proposed technical idea into a concrete system or process.

[0105] The system that implements this application works through the collaboration of a server and a user's terminal. The server first periodically scans program repositories from open-source platforms on the internet and generates summaries of the retrieved code. These summaries include the program's main functions and uses, and are converted into a human-readable format. A generative AI model such as OpenAI® is used for this summarization process. The generated summaries are stored in a database as a knowledge base, enabling efficient searching.

[0106] Users input specific social issues via smartphones or other devices and query the server. The server analyzes this input and generates queries that address the issues. Using the generated queries, the server searches a knowledge base and presents users with relevant technological ideas and information on their implementation. This information provides a basis for quickly considering solutions to urban challenges, allowing users to explore concrete solutions based on the proposed technologies.

[0107] For example, if a user inputs "measures to alleviate traffic congestion" as a problem, the server can immediately present relevant technical information such as "smart traffic signal control systems" and "technologies to promote the use of public transport."

[0108] Examples of prompts for a generative AI model are as follows:

[0109] "Users are looking for ways to alleviate urban traffic congestion. Please list relevant technical ideas from the latest open-source projects."

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] The server accesses the open-source platform and retrieves new program repositories. The server sends API requests daily or at a configured frequency to collect new codebases. This process yields open-source code as input and a data set of extracted code as output.

[0113] Step 2:

[0114] The server uses a generative AI model to summarize the acquired code. Using the code data obtained in Step 1 as input, it generates a summary that describes the code's functions and features in natural language. This summarization process enables the understanding of programs obtained from open-source platforms.

[0115] Step 3:

[0116] The server stores the generated summaries in a knowledge base. The summary information is entered and organized into a database for efficient searching. This step results in a knowledge base that enables rapid access to information.

[0117] Step 4:

[0118] The user enters a social issue they want to solve on their device. The issue entered here consists of keywords or phrases related to a specific problem and reflects the user's needs. The user's input is sent to the server in the next step.

[0119] Step 5:

[0120] The server analyzes the issues submitted by users and generates appropriate search queries. Using the user issue information obtained in step 4 as input, it generates queries for database searches based on relevant keywords and context. This query generation improves the accuracy and relevance of searches.

[0121] Step 6:

[0122] The server uses the generated query to search the knowledge base and retrieve relevant technical ideas and their implementation information. Using the search query obtained in step 5 as input, it retrieves a list of highly relevant solutions as output. This search process allows users to quickly access the information they are looking for.

[0123] Step 7:

[0124] The server presents the search results to the user. Using the solution information obtained in step 6 as input, it visually displays the results to the user via the terminal. This allows the user to quickly evaluate technical options based on specific urban challenges.

[0125] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0126] The system of the present invention comprises a terminal equipped with a user interface, a server for data processing, and an emotion engine. The purpose of this system is to generate a summary of program data obtained from an open-source platform, store it in a database, and further present relevant technical ideas and their implementations based on the social issues entered by the user and the emotions perceived.

[0127] The device provides an interface for users to input social issues they wish to solve. The input information may include text and audio, and based on this, an emotion engine recognizes the user's emotions. The emotion engine uses natural language processing technology to extract emotions from the text and audio and analyzes their state.

[0128] The server generates search queries based on the user's problem information and emotional state, and searches the database. The information stored in the database includes program summaries, technical ideas, and implementation links summarized by a generative AI model. The server adjusts the order of suggested technical ideas and filters them, taking the user's emotions into consideration.

[0129] For example, if a user enters "I want to find a way to reduce city noise," and the emotion engine recognizes this as a feeling of dissatisfaction, the server will search its database for relevant programs and quickly and preferentially present technical solutions that are expected to have a particularly effective stress-reducing effect. In this way, flexible services tailored to the user's preferences and current emotional state can be provided.

[0130] Ultimately, the terminal visually presents the results to the user and provides detailed implementation guides and links to repositories as needed. Users can then effectively develop their projects based on these suggestions. By linking emotion recognition to technical proposals, this system provides an appropriate and human-centered approach to solving social problems.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] Users input the social issues they want to solve via text or voice through their device. Examples of issues they might provide include "I want to know how to improve urban water quality."

[0134] Step 2:

[0135] The device uses an emotion engine to analyze the user's emotional state from their input. For example, the analysis of the input may detect emotions such as "confusion" or "enthusiasm."

[0136] Step 3:

[0137] The device sends the analyzed information to the server, along with the emotional state and task information. This allows the server to obtain basic data to understand the user's intentions and feelings.

[0138] Step 4:

[0139] The server uses a generative AI model to search a database for summaries of code previously obtained from open-source platforms.

[0140] Step 5:

[0141] The server narrows down the database search results to potential technological ideas and implementations related to the user's social issues.

[0142] Step 6:

[0143] The server takes the output of the emotion engine into consideration and adjusts the order in which it displays technology ideas to prioritize them. For example, presenting a proposal like "environmentally friendly water purification system" first might evoke positive emotions.

[0144] Step 7:

[0145] The server sends the refined technical idea and its implementation information to the terminal.

[0146] Step 8:

[0147] The terminal presents the received information to the user. Through a visual interface, it displays detailed information about the proposed idea and links to related repositories, allowing the user to quickly access concrete solutions.

[0148] Step 9:

[0149] Based on the information provided, users start their own projects and aim to solve problems. If necessary, they can view detailed technical documentation via suggested links to aid in implementation.

[0150] (Example 2)

[0151] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0152] The present invention aims to provide a system that effectively and quickly proposes solutions to social problems faced by users. Specifically, it aims to solve the problem of presenting more appropriate solutions by efficiently summarizing information obtained from diverse sources and proposing relevant technical concepts and implementation methods based on that information, while taking into account the emotional state of the user.

[0153] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0154] In this invention, the server includes information processing means, means for storing data in data storage means, and means for recognizing the user's emotional state using emotion analysis means. This makes it possible to propose appropriate technical concepts that address the user's social problems.

[0155] "Information processing means" refers to the function of a system that processes information obtained from an open-source platform and summarizes its contents.

[0156] A "data storage means" is a function that stores data, including the generated summary, and manages it for later retrieval and use.

[0157] A "user" is an individual or group that uses the system to seek solutions to social problems.

[0158] "Social problems" refer to any challenges or difficulties that users seek to resolve, and their content can be diverse.

[0159] A "technical concept" is an idea for a method or device based on ingenuity to solve a specific problem.

[0160] "Implementation method" refers to the means and processes for concretely carrying out a technical concept.

[0161] "Emotion analysis means" refers to a function that identifies emotions from user input data and reflects them in system operation.

[0162] "Connection information" refers to digital links or identification information for accessing related implementation methods.

[0163] The system of this invention aims to propose relevant technical concepts and implementation methods in response to social problems entered by the user. To achieve this, the system consists of three main components: a terminal, a server, and a database.

[0164] The terminal is equipped with a user interface and provides a means for the user to input the social problem they wish to solve. The input data is in text or voice format and is sent to an emotion analysis system. The emotion analysis system recognizes and analyzes the user's emotions using natural language processing techniques. Common speech recognition software and text analysis algorithms are used to implement this technology.

[0165] The server uses social problem and sentiment data received from the user to search a database for relevant technical solutions. The database stores information obtained from open-source platforms, program summaries compiled by generative AI models, and connection information for relevant technical concepts and implementation methods. Taking the sentiment analysis results into account, the server proposes technical concepts in the order that best suits the user's needs.

[0166] For example, if a user inputs a social problem such as "I want to solve the problem of litter in parks," and the emotion analysis system recognizes the emotion of "anxiety," the server can quickly search for relevant technical concepts and prioritize displaying solutions that are particularly easy to implement and promote the user's sense of security.

[0167] Ultimately, the terminal visually presents the information provided by the server to the user, and provides specific implementation guides and connection information as needed. For example, a prompt might be suggested in the form of, "Please share your creative ideas for solving the park's litter problem."

[0168] In this way, the present invention provides users with optimized technical solutions through emotion analysis, thereby supporting the resolution of social problems.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] Users input a social problem they want to solve using the device's user interface. This input can be in text or voice format, and this information forms the basis for sentiment analysis. For example, they might input a specific problem such as, "I want to find a way to reduce noise in the city."

[0172] Step 2:

[0173] The terminal transmits the input information to the sentiment analysis system. The sentiment analysis system uses natural language processing technology to analyze the user's emotions from the input text and audio. The input here is the text and audio data entered by the user, and the output extracted as a result of the analysis is the user's emotional state (e.g., dissatisfaction, relief, etc.). In this analysis process, the tone of voice and the positive and negative expressions in the text are specifically analyzed.

[0174] Step 3:

[0175] The server receives emotional data obtained from the emotion analysis system and social problems entered by the user, and generates search queries based on them. The input here is the user's social problem information and the analyzed emotional information, and the output is a specific query for database searching. This query generation involves combining keywords that take into account the intensity of the emotions.

[0176] Step 4:

[0177] The server searches the database using the generated query. The database stores information and related technical concepts summarized by the generating AI model. The input is the search query, and the output is a list of proposed technical concepts and implementation methods. Specifically, it performs a matching process with relevant information in the database.

[0178] Step 5:

[0179] The server reorders search results according to the user's emotional state and selects the most appropriate technical concept. The input here is a list of technical concepts obtained in the previous step, and the output is a prioritized list of the adjusted suggestions. Specifically, if the user's emotional state is determined to be one of reassurance, the server will present solutions with lower risk at the top.

[0180] Step 6:

[0181] The terminal visually presents technical concepts and implementation methods provided by the server to the user. Input is a prioritized list from the server, and output is detailed information displayed on the user interface. The user uses this information to consider specific solutions. The terminal also displays connection information for implementation methods as needed.

[0182] (Application Example 2)

[0183] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0184] Conventional technologies are sometimes insufficient to adequately address the various demands that users face in their living environments. In particular, there is a lack of flexible technological proposals that reflect the emotional state of users, making it difficult to provide solutions that meet user needs. This invention aims to support the improvement of living environments by adjusting priorities based on user emotions and proposing more appropriate technological means.

[0185] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0186] In this invention, the server includes means for generating a summary of information obtained from an open-source platform, means for constructing a structure for storing the summary, means for searching the structure and presenting relevant technical means and their implementations based on user input regarding living environment requirements, means for analyzing the user's emotions and adjusting the priority of proposed technical means, and means for presenting the proposed technical means and implementations to the user as visual information. This makes it possible to accurately reflect the user's emotions in technical proposals and adjust their priority accordingly.

[0187] An "open-source platform" is a collection of information sources that aggregate software and data that are permitted to be freely used, modified, and distributed.

[0188] A "summary" is a concise compilation of the main points and overview of information or data.

[0189] "Structure" refers to a framework or format for systematically organizing and storing information and data.

[0190] "Requirements regarding the living environment" refers to specific needs and problems that users seek to improve in their daily lives.

[0191] "Technical means" refers to technical methods or tools used to solve a specific problem.

[0192] "Implementation" refers to actually applying and making a particular technology or method work.

[0193] "Analyzing emotions" refers to the process of recognizing and classifying emotional states based on a user's expressions and actions.

[0194] "Adjusting priorities" means changing the content and order of implementation based on importance and urgency.

[0195] "Visual information" refers to images and visuals displayed on a screen, and is a means of conveying information to the user.

[0196] The system implementing this invention includes a server for processing information, a terminal with a user interface, and an emotion engine for analyzing emotions. The server uses natural language processing techniques to generate summaries of information obtained from open-source platforms. Specifically, it utilizes text analysis libraries such as spaCy and NLTK to extract key features of the information and store them in a structure as summaries. Users input requests regarding their living environment through the terminal, and this input is accepted in either voice or text format.

[0197] The emotion engine analyzes user input and identifies the user's emotional state. To achieve this, it incorporates an emotion analysis algorithm and assigns emotion labels. The server uses this emotion data to search a database for relevant technical solutions, adjusts their priority, and determines the proposed solutions. The proposed solutions and their implementation information are presented to the user in a visualized form. This visual information is provided through a graphical user interface, making the proposals easier for the user to intuitively understand. By adjusting the user's emotions to the proposed solutions, effective improvements to the living environment are expected.

[0198] As a concrete example, suppose a user inputs "I want to alleviate daytime traffic congestion." If the emotion engine detects the user's stress, the server will prioritize suggesting smart traffic management system technologies to smooth traffic flow. These technologies include real-time traffic data analysis and improvements to signal control systems.

[0199] An example of a prompt message would be: "Please suggest technologies related to the problem entered by the user. When doing so, please prioritize solutions based on the emotions or emotional state the user is seeking."

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The terminal receives user-generated requests regarding their living environment in text or voice format. This constitutes the initial input to the system. After input, the terminal sends the data to the server as text.

[0203] Step 2:

[0204] The server analyzes the received text data using natural language processing techniques. Specifically, it extracts keywords from the input content using text analysis libraries (such as spaCy or NLTK) and understands the basic meaning. This clarifies the user's request.

[0205] Step 3:

[0206] The emotion engine analyzes the emotions contained in the input. Using natural language processing algorithms, it identifies emotion labels within the text and outputs emotion categories such as "stress" and "relaxation." This emotion information is needed for subsequent processing.

[0207] Step 4:

[0208] The server searches databases derived from open-source platforms based on interpreted request and sentiment data. It generates search queries to extract summaries and implementation links of relevant technical tools. These queries are optimized using a generative AI model.

[0209] Step 5:

[0210] The server considers sentiment data and adjusts the priority of technical tools accordingly. It sorts the extracted list of technical tools according to sentiment and places them in the order that best suits the user's request.

[0211] Step 6:

[0212] Prioritized technical means and their implementation information are transmitted to the terminal. The terminal presents the suggestions to the user as visual information using a graphical user interface. Based on this information, the user can consider actual actions and improvement measures.

[0213] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0214] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0215] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0219] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0220] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0221] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0222] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0223] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0224] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0225] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0226] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0227] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0228] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0229] The invention's system primarily consists of multiple computer devices (servers and terminals). Here, we illustrate the flow of the system's main functions: program acquisition from an open-source platform, summary generation, database construction, and search and idea generation in response to social issues.

[0230] The server periodically scans open-source platforms and retrieves new program repositories. Next, it uses a generative AI model to summarize the code in each repository in human-readable language. This summary information is stored in a database designed for efficient searching. As a result, the database functions as a massive knowledge base, containing a wide variety of technical ideas and their implementation information.

[0231] The user inputs a social issue they want to solve via their device. This input is sent to a server, which analyzes the issue to generate an appropriate search query. Using the generated query, the server searches its database for and suggests relevant technical ideas and implementation information.

[0232] For example, if a user is looking for a "system to reduce food waste," the server will search for relevant programs and ideas and suggest potentially relevant technical solutions such as a "household inventory management app" or a "local sharing platform." Based on these suggestions, the user can leverage existing implementations and quickly deploy their own project.

[0233] In this way, the invention efficiently extracts and provides ideas for solving social problems faced by many people. Users can utilize the proposed technology to implement valuable projects in a short period of time. This system reduces the burden on users through automated processes and dramatically increases the possibility of solving problems.

[0234] The following describes the processing flow.

[0235] Step 1:

[0236] The server retrieves the latest repository information from open-source platforms. This involves using APIs to crawl publicly available repositories and collect program data.

[0237] Step 2:

[0238] The server analyzes the collected program data and generates a summary of each program using a generative AI model. The summary is output as natural language text in a format that is easy for humans to understand.

[0239] Step 3:

[0240] The server stores the generated summary in a database. In addition to the summarized information, related metadata (e.g., repository name, author, update date, etc.) is also stored there.

[0241] Step 4:

[0242] Users input the social issue they want to solve via their device. This involves text input, providing keywords and sentences related to the issue.

[0243] Step 5:

[0244] The terminal sends user input information to the server. The server receives this information and generates an appropriate search query based on the entered task.

[0245] Step 6:

[0246] The server uses the generated search query to search the database. It extracts relevant technical ideas and their implementation information from the database and lists the most relevant results.

[0247] Step 7:

[0248] The server sends the extracted search results to the terminal. The terminal receives these results and displays the suggested technical ideas and corresponding implementation information to the user.

[0249] Step 8:

[0250] Users review the presented information, view links to repositories and implementation guides as needed, and then proceed to start and run the project.

[0251] (Example 1)

[0252] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0253] In response to the diverse social challenges of today, there is a need to find appropriate and rapid technological solutions and provide users with ways to effectively utilize them. However, efficiently extracting, summarizing, and appropriately presenting relevant information from a vast program repository is difficult and burdensome for users.

[0254] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0255] In this invention, the server includes means for generating a summary of an electronic program obtained from a software platform, means for constructing an information storage device that stores the summary, and means for searching the information storage device based on a social issue input by a user and proposing relevant technical solutions and methods for their implementation. This enables users to quickly discover and implement technical solutions for solving social issues.

[0256] A "software platform" refers to software repositories or code-sharing sites that users can access over the internet.

[0257] An "electronic program" is a series of instructions or code executed by a computer, and is a component of software.

[0258] A "summary" is a concise explanatory text that describes the main functions and features of an electronic program.

[0259] An "information storage device" is a database or storage system capable of storing digital data over long periods of time.

[0260] A "user" is an individual or legal entity that uses this system to solve social problems.

[0261] "Social issues" refer to problems or challenges faced by society as a whole or by a specific community, and include those that require technological solutions.

[0262] A "technical proposal" is a technical idea or concept proposed as a means of solving a specific problem.

[0263] "Implementation method" refers to the specific steps and processes for developing a technical proposal into a concrete form and putting it into practice.

[0264] The system in this invention consists of a user, a server, and a terminal.

[0265] The server first periodically accesses the software platform via the internet to retrieve new electronic programs. This process utilizes a Linux server and Python scripts, employing publicly available APIs. The server inputs the retrieved programs into a generating AI model (e.g., an open-source natural language processing model) to generate a summary in a human-readable format. An example of a prompt in this process is, "Please explain the main function and purpose of this code."

[0266] Next, the server saves the generated summary to an information storage device (SQL database). This database is indexed, allowing for efficient searching. This enables the rapid management of multiple technical proposals and their implementation methods.

[0267] On the other hand, users input the social issues they want to solve via their own devices (personal computers or mobile devices). This input is expressed in natural language and sent to the server via the internet.

[0268] The server analyzes the user's request using natural language processing algorithms (e.g., Spacy or NLTK) and extracts relevant keywords. Based on the resulting search queries, the server searches its information storage device, identifies relevant technical proposals and implementation methods, and proposes them to the user.

[0269] For example, if a user searches for "ways to reduce energy consumption," the server will provide relevant suggestions such as "efficient energy management systems" or "smart home technologies." Users can then use these suggestions to quickly and effectively find solutions to their challenges. This process enables users to facilitate the implementation of new projects and contribute to solving social problems.

[0270] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0271] Step 1:

[0272] The server periodically retrieves new electronic programs using the software platform's API. The input is a program repository stored on a specific open-source platform. It filters the data by calling the API and selects relevant repositories based on criteria such as keywords and stars. The output is a list of related repositories.

[0273] Step 2:

[0274] The server inputs the acquired program into a generating AI model to generate a summary. The input is a code block obtained from the repository. Specifically, the server sends a prompt to the generating AI model asking, "Please explain the main function and purpose of this code." The model responds with a summary in natural language. The output is a summarized text in a human-readable format.

[0275] Step 3:

[0276] The server stores the generated summary in an SQL database, which is an information storage device. The input is the summary text generated in the previous step. The server indexes this summary, creating a structure that enables efficient searching. The output is a searchable database entry.

[0277] Step 4:

[0278] The user inputs a social issue they want to solve in natural language via their device. The input is text about the issue the user has in mind. The device sends this information to the server via the internet. The output is the text of the issue received by the server.

[0279] Step 5:

[0280] The server analyzes the user's task and generates a search query. The input is the text of the task sent from the terminal. The server uses natural language processing tools to analyze the text and extract relevant keywords. The output is the search query generated based on these keywords.

[0281] Step 6:

[0282] The server uses the generated query to search the database and identify relevant technical solutions and implementation methods. The input is the search query created in the previous step. The SQL query is executed against the database to retrieve the relevant dataset. The output is a list of technical solutions related to the user's problem.

[0283] Step 7:

[0284] The server presents the identified technical solution and implementation method to the user. The input is a list of technical solutions that are the results of database searches. The server sends this information back to the terminal and displays it in a user-friendly format. The output is a list of technical solutions and implementation methods displayed on the terminal.

[0285] Step 8:

[0286] The user plans and implements a specific project based on the presented technical solution. The input is the information of the technical solution obtained from the server. The user uses this to plan the project. The output is the actually planned and implemented project.

[0287] (Application Example 1)

[0288] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0289] In modern society, with the progress of urbanization, various problems such as traffic congestion, energy efficiency, and environmental issues have become prominent. To quickly and easily take measures against these problems, it is necessary to efficiently utilize existing technologies and ideas. However, the related information is vast, and its sorting and retrieval are difficult, so a quick response to problem-solving is required.

[0290] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0291] In this invention, the server includes means for generating summaries of programs obtained from an open-source platform, means for constructing a knowledge base storing the summaries, and means for searching the knowledge base based on social issues input by users and proposing relevant technical ideas and their implementations. This makes it possible to effectively explore solutions to urban problems and quickly present the technical ideas and implementation information that users need.

[0292] An "open-source platform" is a foundation that provides repositories and projects of programs that can be freely accessed on the internet.

[0293] A "summary" is a short, human-readable summary of information about a program obtained from an open-source platform.

[0294] A "knowledge base" is a collection of information that stores generated summaries, enabling efficient searching and information provision.

[0295] "Users" refer to individuals or organizations that use the system to explore solutions to social problems.

[0296] "Social issues" refer to general or specific problems that need to be solved in cities, such as traffic congestion, energy efficiency, and environmental issues.

[0297] A "technical idea" is a conceptual or practical proposal that refers to a solution or method for addressing a specific problem.

[0298] "Implementation" refers to the act or result of transforming a proposed technical idea into a concrete system or process.

[0299] The system that implements this application works through the collaboration of a server and a user's terminal. The server first periodically scans program repositories from open-source platforms on the internet and generates summaries of the retrieved code. These summaries include the program's main functions and uses, and are converted into a human-readable format. A generative AI model, such as OpenAI, is used for this summarization process. The generated summaries are stored in a database as a knowledge base, enabling efficient searching.

[0300] Users input specific social issues via smartphones or other devices and query the server. The server analyzes this input and generates queries that address the issues. Using the generated queries, the server searches a knowledge base and presents users with relevant technological ideas and information on their implementation. This information provides a basis for quickly considering solutions to urban challenges, allowing users to explore concrete solutions based on the proposed technologies.

[0301] For example, if a user inputs "measures to alleviate traffic congestion" as a problem, the server can immediately present relevant technical information such as "smart traffic signal control systems" and "technologies to promote the use of public transport."

[0302] Examples of prompts for a generative AI model are as follows:

[0303] "Users are looking for ways to alleviate urban traffic congestion. Please list relevant technical ideas from the latest open-source projects."

[0304] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0305] Step 1:

[0306] The server accesses an open-source platform and retrieves a new program repository. The server sends API requests daily or at a set frequency to collect a new codebase. Through this process, open-source code is obtained as input, and a dataset of the code extracted from it is obtained as output.

[0307] Step 2:

[0308] The server summarizes the code obtained using a generative AI model. Using the code data obtained in Step 1 as input, a summary that summarizes the functions and features of the code in natural language is generated. Through this summarization process, the program obtained from the open-source platform can be understood.

[0309] Step 3:

[0310] <> The server stores the generated summary in a knowledge base. The summary information is input and organized and stored in a database so that efficient retrieval is possible. As a result of this step, a knowledge base is formed that enables quick access to information.

[0311] Step 4:

[0312] The user inputs a social issue to be solved on the terminal. The issues input here are keywords or sentences related to specific problems and reflect the user's needs. The user's input is sent to the server in the next step.

[0313] Step 5:

[0314] The server analyzes the issue sent by the user and generates an appropriate search query. Using the user's issue information obtained in Step 4 as input, a query for database search is generated based on relevant keywords and context. By generating this query, the accuracy and relevance of the search can be improved.

[0315] Step 6:

[0316] The server uses the generated query to search the knowledge base and retrieve relevant technical ideas and their implementation information. Using the search query obtained in step 5 as input, it retrieves a list of highly relevant solutions as output. This search process allows users to quickly access the information they are looking for.

[0317] Step 7:

[0318] The server presents the search results to the user. Using the solution information obtained in step 6 as input, it visually displays the results to the user via the terminal. This allows the user to quickly evaluate technical options based on specific urban challenges.

[0319] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0320] The system of the present invention comprises a terminal equipped with a user interface, a server for data processing, and an emotion engine. The purpose of this system is to generate a summary of program data obtained from an open-source platform, store it in a database, and further present relevant technical ideas and their implementations based on the social issues entered by the user and the emotions perceived.

[0321] The device provides an interface for users to input social issues they wish to solve. The input information may include text and audio, and based on this, an emotion engine recognizes the user's emotions. The emotion engine uses natural language processing technology to extract emotions from the text and audio and analyzes their state.

[0322] The server generates search queries based on the user's problem information and emotional state, and searches the database. The information stored in the database includes program summaries, technical ideas, and implementation links summarized by a generative AI model. The server adjusts the order of suggested technical ideas and filters them, taking the user's emotions into consideration.

[0323] For example, if a user enters "I want to find a way to reduce city noise," and the emotion engine recognizes this as a feeling of dissatisfaction, the server will search its database for relevant programs and quickly and preferentially present technical solutions that are expected to have a particularly effective stress-reducing effect. In this way, flexible services tailored to the user's preferences and current emotional state can be provided.

[0324] Ultimately, the terminal visually presents the results to the user and provides detailed implementation guides and links to repositories as needed. Users can then effectively develop their projects based on these suggestions. By linking emotion recognition to technical proposals, this system provides an appropriate and human-centered approach to solving social problems.

[0325] The following describes the processing flow.

[0326] Step 1:

[0327] Users input the social issues they want to solve via text or voice through their device. Examples of issues they might provide include "I want to know how to improve urban water quality."

[0328] Step 2:

[0329] The device uses an emotion engine to analyze the user's emotional state from their input. For example, the analysis of the input may detect emotions such as "confusion" or "enthusiasm."

[0330] Step 3:

[0331] The device sends the analyzed information to the server, passing on task information along with the user's emotional state. This allows the server to obtain basic data to understand the user's intentions and feelings.

[0332] Step 4:

[0333] The server uses a generative AI model to search a database for summaries of code previously obtained from open-source platforms.

[0334] Step 5:

[0335] The server narrows down the database search results to potential technological ideas and implementations related to the user's social issues.

[0336] Step 6:

[0337] The server takes the output of the emotion engine into consideration and adjusts the order in which it displays technology ideas to prioritize them. For example, presenting a proposal like "environmentally friendly water purification system" first might evoke positive emotions.

[0338] Step 7:

[0339] The server sends the refined technical idea and its implementation information to the terminal.

[0340] Step 8:

[0341] The terminal presents the received information to the user. Through a visual interface, it displays detailed information about the proposed idea and links to related repositories, allowing the user to quickly access concrete solutions.

[0342] Step 9:

[0343] Based on the information provided, users start their own projects and aim to solve problems. If necessary, they can view detailed technical documentation via suggested links to aid in implementation.

[0344] (Example 2)

[0345] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0346] The present invention aims to provide a system that effectively and quickly proposes solutions to social problems faced by users. Specifically, it aims to solve the problem of presenting more appropriate solutions by efficiently summarizing information obtained from diverse sources and proposing relevant technical concepts and implementation methods based on that information, while taking into account the emotional state of the user.

[0347] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0348] In this invention, the server includes information processing means, means for storing data in data storage means, and means for recognizing the user's emotional state using emotion analysis means. This makes it possible to propose appropriate technical concepts that address the user's social problems.

[0349] "Information processing means" refers to the function of a system that processes information obtained from an open-source platform and summarizes its contents.

[0350] A "data storage means" is a function that stores data, including the generated summary, and manages it for later retrieval and use.

[0351] A "user" is an individual or group that uses the system to seek solutions to social problems.

[0352] "Social problems" refer to any challenges or difficulties that users seek to resolve, and their content can be diverse.

[0353] A "technical concept" is an idea for a method or device based on ingenuity to solve a specific problem.

[0354] "Implementation method" refers to the means and processes for concretely carrying out a technical concept.

[0355] "Emotion analysis means" refers to a function that identifies emotions from user input data and reflects them in system operation.

[0356] "Connection information" refers to digital links or identification information for accessing related implementation methods.

[0357] The system of this invention aims to propose relevant technical concepts and implementation methods in response to social problems entered by the user. To achieve this, the system consists of three main components: a terminal, a server, and a database.

[0358] The terminal is equipped with a user interface and provides a means for the user to input the social problem they wish to solve. The input data is in text or voice format and is sent to an emotion analysis system. The emotion analysis system recognizes and analyzes the user's emotions using natural language processing techniques. Common speech recognition software and text analysis algorithms are used to implement this technology.

[0359] The server uses social problem and sentiment data received from the user to search a database for relevant technical solutions. The database stores information obtained from open-source platforms, program summaries compiled by generative AI models, and connection information for relevant technical concepts and implementation methods. Taking the sentiment analysis results into account, the server proposes technical concepts in the order that best suits the user's needs.

[0360] For example, if a user inputs a social problem such as "I want to solve the problem of litter in parks," and the emotion analysis system recognizes the emotion of "anxiety," the server can quickly search for relevant technical concepts and prioritize displaying solutions that are particularly easy to implement and promote the user's sense of security.

[0361] Ultimately, the terminal visually presents the information provided by the server to the user, and provides specific implementation guides and connection information as needed. For example, a prompt might be suggested in the form of, "Please share your creative ideas for solving the park's litter problem."

[0362] In this way, the present invention provides users with optimized technical solutions through emotion analysis, thereby supporting the resolution of social problems.

[0363] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0364] Step 1:

[0365] Users input a social problem they want to solve using the device's user interface. This input can be in text or voice format, and this information forms the basis for sentiment analysis. For example, they might input a specific problem such as, "I want to find a way to reduce noise in the city."

[0366] Step 2:

[0367] The terminal transmits the input information to the sentiment analysis system. The sentiment analysis system uses natural language processing technology to analyze the user's emotions from the input text and audio. The input here is the text and audio data entered by the user, and the output extracted as a result of the analysis is the user's emotional state (e.g., dissatisfaction, relief, etc.). In this analysis process, the tone of voice and the positive and negative expressions in the text are specifically analyzed.

[0368] Step 3:

[0369] The server receives emotional data obtained from the emotion analysis system and social problems entered by the user, and generates search queries based on them. The input here is the user's social problem information and the analyzed emotional information, and the output is a specific query for database searching. This query generation involves combining keywords that take into account the intensity of the emotions.

[0370] Step 4:

[0371] The server searches the database using the generated query. The database stores information and related technical concepts summarized by the generating AI model. The input is the search query, and the output is a list of proposed technical concepts and implementation methods. Specifically, it performs a matching process with relevant information in the database.

[0372] Step 5:

[0373] The server reorders search results according to the user's emotional state and selects the most appropriate technical concept. The input here is a list of technical concepts obtained in the previous step, and the output is a prioritized list of the adjusted suggestions. Specifically, if the user's emotional state is determined to be one of reassurance, the server will present solutions with lower risk at the top.

[0374] Step 6:

[0375] The terminal visually presents technical concepts and implementation methods provided by the server to the user. Input is a prioritized list from the server, and output is detailed information displayed on the user interface. The user uses this information to consider specific solutions. The terminal also displays connection information for implementation methods as needed.

[0376] (Application Example 2)

[0377] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0378] Conventional technologies are sometimes insufficient to adequately address the various demands that users face in their living environments. In particular, there is a lack of flexible technological proposals that reflect the emotional state of users, making it difficult to provide solutions that meet user needs. This invention aims to support the improvement of living environments by adjusting priorities based on user emotions and proposing more appropriate technological means.

[0379] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0380] In this invention, the server includes means for generating a summary of information obtained from an open-source platform, means for constructing a structure for storing the summary, means for searching the structure and presenting relevant technical means and their implementations based on user input regarding living environment requirements, means for analyzing the user's emotions and adjusting the priority of proposed technical means, and means for presenting the proposed technical means and implementations to the user as visual information. This makes it possible to accurately reflect the user's emotions in technical proposals and adjust their priority accordingly.

[0381] An "open-source platform" is a collection of information sources that aggregate software and data that are permitted to be freely used, modified, and distributed.

[0382] A "summary" is a concise compilation of the main points and overview of information or data.

[0383] "Structure" refers to a framework or format for systematically organizing and storing information and data.

[0384] "Requirements regarding the living environment" refers to specific needs and problems that users seek to improve in their daily lives.

[0385] "Technical means" refers to technical methods or tools used to solve a specific problem.

[0386] "Implementation" refers to actually applying and making a particular technology or method work.

[0387] "Analyzing emotions" refers to the process of recognizing and classifying emotional states based on a user's expressions and actions.

[0388] "Adjusting priorities" means changing the content and order of implementation based on importance and urgency.

[0389] "Visual information" refers to images and visuals displayed on a screen, and is a means of conveying information to the user.

[0390] The system implementing this invention includes a server for processing information, a terminal with a user interface, and an emotion engine for analyzing emotions. The server uses natural language processing techniques to generate summaries of information obtained from open-source platforms. Specifically, it utilizes text analysis libraries such as spaCy and NLTK to extract key features of the information and store them in a structure as summaries. Users input requests regarding their living environment through the terminal, and this input is accepted in either voice or text format.

[0391] The emotion engine analyzes user input and identifies the user's emotional state. To achieve this, it incorporates an emotion analysis algorithm and assigns emotion labels. The server uses this emotion data to search a database for relevant technical solutions, adjusts their priority, and determines the proposed solutions. The proposed solutions and their implementation information are presented to the user in a visualized form. This visual information is provided through a graphical user interface, making the proposals easier for the user to intuitively understand. By adjusting the user's emotions to the proposed solutions, effective improvements to the living environment are expected.

[0392] As a concrete example, suppose a user inputs "I want to alleviate daytime traffic congestion." If the emotion engine detects the user's stress, the server will prioritize suggesting smart traffic management system technologies to smooth traffic flow. These technologies include real-time traffic data analysis and improvements to signal control systems.

[0393] An example of a prompt message would be: "Please suggest technologies related to the problem entered by the user. When doing so, please prioritize solutions based on the emotions or emotional state the user is seeking."

[0394] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0395] Step 1:

[0396] The terminal receives user-generated requests regarding their living environment in text or voice format. This constitutes the initial input to the system. After input, the terminal sends the data to the server as text.

[0397] Step 2:

[0398] The server analyzes the received text data using natural language processing techniques. Specifically, it extracts keywords from the input content using text analysis libraries (such as spaCy or NLTK) and understands the basic meaning. This clarifies the user's request.

[0399] Step 3:

[0400] The emotion engine analyzes the emotions contained in the input. Using natural language processing algorithms, it identifies emotion labels within the text and outputs emotion categories such as "stress" and "relaxation." This emotion information is needed for subsequent processing.

[0401] Step 4:

[0402] The server searches databases derived from open-source platforms based on interpreted request and sentiment data. It generates search queries to extract summaries and implementation links of relevant technical tools. These queries are optimized using a generative AI model.

[0403] Step 5:

[0404] The server considers sentiment data and adjusts the priority of technical tools accordingly. It sorts the extracted list of technical tools according to sentiment and places them in the order that best suits the user's request.

[0405] Step 6:

[0406] Prioritized technical means and their implementation information are transmitted to the terminal. The terminal presents the suggestions to the user as visual information using a graphical user interface. Based on this information, the user can consider actual actions and improvement measures.

[0407] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0408] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0409] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0410] [Third Embodiment]

[0411] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0412] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0413] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0414] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0415] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0416] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0417] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0418] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0419] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0420] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0421] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0422] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0423] The invention's system primarily consists of multiple computer devices (servers and terminals). Here, we illustrate the flow of the system's main functions: program acquisition from an open-source platform, summary generation, database construction, and search and idea generation in response to social issues.

[0424] The server periodically scans open-source platforms and retrieves new program repositories. Next, it uses a generative AI model to summarize the code in each repository in human-readable language. This summary information is stored in a database designed for efficient searching. As a result, the database functions as a massive knowledge base, containing a wide variety of technical ideas and their implementation information.

[0425] The user inputs a social issue they want to solve via their device. This input is sent to a server, which analyzes the issue to generate an appropriate search query. Using the generated query, the server searches its database for and suggests relevant technical ideas and implementation information.

[0426] For example, if a user is looking for a "system to reduce food waste," the server will search for relevant programs and ideas and suggest potentially relevant technical solutions such as a "household inventory management app" or a "local sharing platform." Based on these suggestions, the user can leverage existing implementations and quickly deploy their own project.

[0427] In this way, the invention efficiently extracts and provides ideas for solving social problems faced by many people. Users can utilize the proposed technology to implement valuable projects in a short period of time. This system reduces the burden on users through automated processes and dramatically increases the possibility of solving problems.

[0428] The following describes the processing flow.

[0429] Step 1:

[0430] The server retrieves the latest repository information from open-source platforms. This involves using APIs to crawl publicly available repositories and collect program data.

[0431] Step 2:

[0432] The server analyzes the collected program data and generates a summary of each program using a generative AI model. The summary is output as natural language text in a format that is easy for humans to understand.

[0433] Step 3:

[0434] The server stores the generated summary in a database. In addition to the summarized information, related metadata (e.g., repository name, author, update date, etc.) is also stored there.

[0435] Step 4:

[0436] Users input the social issue they want to solve via their device. This involves text input, providing keywords and sentences related to the issue.

[0437] Step 5:

[0438] The terminal sends user input information to the server. The server receives this information and generates an appropriate search query based on the entered task.

[0439] Step 6:

[0440] The server uses the generated search query to search the database. It extracts relevant technical ideas and their implementation information from the database and lists the most relevant results.

[0441] Step 7:

[0442] The server sends the extracted search results to the terminal. The terminal receives these results and displays the suggested technical ideas and corresponding implementation information to the user.

[0443] Step 8:

[0444] Users review the presented information, view links to repositories and implementation guides as needed, and then proceed to start and run the project.

[0445] (Example 1)

[0446] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0447] In response to the diverse social challenges of today, there is a need to find appropriate and rapid technological solutions and provide users with ways to effectively utilize them. However, efficiently extracting, summarizing, and appropriately presenting relevant information from a vast program repository is difficult and burdensome for users.

[0448] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0449] In this invention, the server includes means for generating a summary of an electronic program obtained from a software platform, means for constructing an information storage device that stores the summary, and means for searching the information storage device based on a social issue input by a user and proposing relevant technical solutions and methods for their implementation. This enables users to quickly discover and implement technical solutions for solving social issues.

[0450] A "software platform" refers to software repositories or code-sharing sites that users can access over the internet.

[0451] An "electronic program" is a series of instructions or code executed by a computer, and is a component of software.

[0452] A "summary" is a concise explanatory text that describes the main functions and features of an electronic program.

[0453] An "information storage device" is a database or storage system capable of storing digital data over long periods of time.

[0454] A "user" is an individual or legal entity that uses this system to solve social problems.

[0455] "Social issues" refer to problems or challenges faced by society as a whole or by a specific community, and include those that require technological solutions.

[0456] A "technical proposal" is a technical idea or concept proposed as a means of solving a specific problem.

[0457] "Implementation method" refers to the specific steps and processes for developing a technical proposal into a concrete form and putting it into practice.

[0458] The system in this invention consists of a user, a server, and a terminal.

[0459] The server first periodically accesses the software platform via the internet to retrieve new electronic programs. This process utilizes a Linux server and Python scripts, employing publicly available APIs. The server inputs the retrieved programs into a generating AI model (e.g., an open-source natural language processing model) to generate a summary in a human-readable format. An example of a prompt in this process is, "Please explain the main function and purpose of this code."

[0460] Next, the server saves the generated summary to an information storage device (SQL database). This database is indexed, allowing for efficient searching. This enables the rapid management of multiple technical proposals and their implementation methods.

[0461] On the other hand, users input the social issues they want to solve via their own devices (personal computers or mobile devices). This input is expressed in natural language and sent to the server via the internet.

[0462] The server analyzes the user's request using natural language processing algorithms (e.g., Spacy or NLTK) and extracts relevant keywords. Based on the resulting search queries, the server searches its information storage device, identifies relevant technical proposals and implementation methods, and proposes them to the user.

[0463] For example, if a user searches for "ways to reduce energy consumption," the server will provide relevant suggestions such as "efficient energy management systems" or "smart home technologies." Users can then use these suggestions to quickly and effectively find solutions to their challenges. This process enables users to facilitate the implementation of new projects and contribute to solving social problems.

[0464] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0465] Step 1:

[0466] The server periodically retrieves new electronic programs using the software platform's API. The input is a program repository stored on a specific open-source platform. It filters the data by calling the API and selects relevant repositories based on criteria such as keywords and stars. The output is a list of related repositories.

[0467] Step 2:

[0468] The server inputs the acquired program into a generating AI model to generate a summary. The input is a code block obtained from the repository. Specifically, the server sends a prompt to the generating AI model asking, "Please explain the main function and purpose of this code." The model responds with a summary in natural language. The output is a summarized text in a human-readable format.

[0469] Step 3:

[0470] The server stores the generated summary in an SQL database, which is an information storage device. The input is the summary text generated in the previous step. The server indexes this summary, creating a structure that enables efficient searching. The output is a searchable database entry.

[0471] Step 4:

[0472] The user inputs a social issue they want to solve in natural language via their device. The input is text about the issue the user has in mind. The device sends this information to the server via the internet. The output is the text of the issue received by the server.

[0473] Step 5:

[0474] The server analyzes the user's task and generates a search query. The input is the text of the task sent from the terminal. The server uses natural language processing tools to analyze the text and extract relevant keywords. The output is the search query generated based on these keywords.

[0475] Step 6:

[0476] The server uses the generated query to search the database and identify relevant technical solutions and implementation methods. The input is the search query created in the previous step. The SQL query is executed against the database to retrieve the relevant dataset. The output is a list of technical solutions related to the user's problem.

[0477] Step 7:

[0478] The server presents the identified technical proposals and their implementation methods to the user. The input is a list of technical proposals resulting from a database search. The server sends this information back to the terminal and displays it in a user-friendly format. The output is the list of technical proposals and their implementation methods displayed on the terminal.

[0479] Step 8:

[0480] The user plans and implements a specific project based on the presented technical proposals. The input is information on the technical proposals obtained from the server. The user uses this information to plan the project. The output is the project that is actually planned and implemented.

[0481] (Application Example 1)

[0482] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0483] In modern society, the advancement of urbanization has brought to light a wide variety of challenges, including traffic congestion, energy efficiency, and environmental problems. To address these challenges quickly and easily, it is necessary to efficiently utilize existing technologies and ideas. However, the amount of related information is vast, making its organization and retrieval difficult, thus requiring a rapid response to problem-solving.

[0484] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0485] In this invention, the server includes means for generating summaries of programs obtained from an open-source platform, means for constructing a knowledge base storing the summaries, and means for searching the knowledge base based on social issues input by users and proposing relevant technical ideas and their implementations. This makes it possible to effectively explore solutions to urban problems and quickly present the technical ideas and implementation information that users need.

[0486] An "open-source platform" is a foundation that provides repositories and projects of programs that can be freely accessed on the internet.

[0487] A "summary" is a short, human-readable summary of information about a program obtained from an open-source platform.

[0488] A "knowledge base" is a collection of information that stores generated summaries, enabling efficient searching and information provision.

[0489] "Users" refer to individuals or organizations that use the system to explore solutions to social problems.

[0490] "Social issues" refer to general or specific problems that need to be solved in cities, such as traffic congestion, energy efficiency, and environmental issues.

[0491] A "technical idea" is a conceptual or practical proposal that refers to a solution or method for addressing a specific problem.

[0492] "Implementation" refers to the act or result of transforming a proposed technical idea into a concrete system or process.

[0493] The system that implements this application works through the collaboration of a server and a user's terminal. The server first periodically scans program repositories from open-source platforms on the internet and generates summaries of the retrieved code. These summaries include the program's main functions and uses, and are converted into a human-readable format. A generative AI model, such as OpenAI, is used for this summarization process. The generated summaries are stored in a database as a knowledge base, enabling efficient searching.

[0494] Users input specific social issues via smartphones or other devices and query the server. The server analyzes this input and generates queries that address the issues. Using the generated queries, the server searches a knowledge base and presents users with relevant technological ideas and information on their implementation. This information provides a basis for quickly considering solutions to urban challenges, allowing users to explore concrete solutions based on the proposed technologies.

[0495] For example, if a user inputs "measures to alleviate traffic congestion" as a problem, the server can immediately present relevant technical information such as "smart traffic signal control systems" and "technologies to promote the use of public transport."

[0496] Examples of prompts for a generative AI model are as follows:

[0497] "Users are looking for ways to alleviate urban traffic congestion. Please list relevant technical ideas from the latest open-source projects."

[0498] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0499] Step 1:

[0500] The server accesses the open-source platform and retrieves new program repositories. The server sends API requests daily or at a configured frequency to collect new codebases. This process yields open-source code as input and a data set of extracted code as output.

[0501] Step 2:

[0502] The server uses a generative AI model to summarize the acquired code. Using the code data obtained in Step 1 as input, it generates a summary that describes the code's functions and features in natural language. This summarization process enables the understanding of programs obtained from open-source platforms.

[0503] Step 3:

[0504] The server stores the generated summaries in a knowledge base. The summary information is entered and organized into a database for efficient searching. This step results in a knowledge base that enables rapid access to information.

[0505] Step 4:

[0506] The user enters a social issue they want to solve on their device. The issue entered here consists of keywords or phrases related to a specific problem and reflects the user's needs. The user's input is sent to the server in the next step.

[0507] Step 5:

[0508] The server analyzes the issues submitted by users and generates appropriate search queries. Using the user issue information obtained in step 4 as input, it generates queries for database searches based on relevant keywords and context. This query generation improves the accuracy and relevance of searches.

[0509] Step 6:

[0510] The server uses the generated query to search the knowledge base and retrieve relevant technical ideas and their implementation information. Using the search query obtained in step 5 as input, it retrieves a list of highly relevant solutions as output. This search process allows users to quickly access the information they are looking for.

[0511] Step 7:

[0512] The server presents the search results to the user. Using the solution information obtained in step 6 as input, it visually displays the results to the user via the terminal. This allows the user to quickly evaluate technical options based on specific urban challenges.

[0513] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0514] The system of the present invention comprises a terminal equipped with a user interface, a server for data processing, and an emotion engine. The purpose of this system is to generate a summary of program data obtained from an open-source platform, store it in a database, and further present relevant technical ideas and their implementations based on the social issues entered by the user and the emotions perceived.

[0515] The device provides an interface for users to input social issues they wish to solve. The input information may include text and audio, and based on this, an emotion engine recognizes the user's emotions. The emotion engine uses natural language processing technology to extract emotions from the text and audio and analyzes their state.

[0516] The server generates search queries based on the user's problem information and emotional state, and searches the database. The information stored in the database includes program summaries, technical ideas, and implementation links summarized by a generative AI model. The server adjusts the order of suggested technical ideas and filters them, taking the user's emotions into consideration.

[0517] For example, if a user enters "I want to find a way to reduce city noise," and the emotion engine recognizes this as a feeling of dissatisfaction, the server will search its database for relevant programs and quickly and preferentially present technical solutions that are expected to have a particularly effective stress-reducing effect. In this way, flexible services tailored to the user's preferences and current emotional state can be provided.

[0518] Ultimately, the terminal visually presents the results to the user and provides detailed implementation guides and links to repositories as needed. Users can then effectively develop their projects based on these suggestions. By linking emotion recognition to technical proposals, this system provides an appropriate and human-centered approach to solving social problems.

[0519] The following describes the processing flow.

[0520] Step 1:

[0521] Users input the social issues they want to solve via text or voice through their device. Examples of issues they might provide include "I want to know how to improve urban water quality."

[0522] Step 2:

[0523] The device uses an emotion engine to analyze the user's emotional state from their input. For example, the analysis of the input may detect emotions such as "confusion" or "enthusiasm."

[0524] Step 3:

[0525] The device sends the analyzed information to the server, passing on task information along with the user's emotional state. This allows the server to obtain basic data to understand the user's intentions and feelings.

[0526] Step 4:

[0527] The server uses a generative AI model to search a database for summaries of code previously obtained from open-source platforms.

[0528] Step 5:

[0529] The server narrows down the database search results to potential technological ideas and implementations related to the user's social issues.

[0530] Step 6:

[0531] The server takes the output of the emotion engine into consideration and adjusts the order in which it displays technology ideas to prioritize them. For example, presenting a proposal like "environmentally friendly water purification system" first might evoke positive emotions.

[0532] Step 7:

[0533] The server sends the refined technical idea and its implementation information to the terminal.

[0534] Step 8:

[0535] The terminal presents the received information to the user. Through a visual interface, it displays detailed information about the proposed idea and links to related repositories, allowing the user to quickly access concrete solutions.

[0536] Step 9:

[0537] Based on the information provided, users start their own projects and aim to solve problems. If necessary, they can view detailed technical documentation via suggested links to aid in implementation.

[0538] (Example 2)

[0539] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0540] The present invention aims to provide a system that effectively and quickly proposes solutions to social problems faced by users. Specifically, it aims to solve the problem of presenting more appropriate solutions by efficiently summarizing information obtained from diverse sources and proposing relevant technical concepts and implementation methods based on that information, while taking into account the emotional state of the user.

[0541] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0542] In this invention, the server includes information processing means, means for storing data in data storage means, and means for recognizing the user's emotional state using emotion analysis means. This makes it possible to propose appropriate technical concepts that address the user's social problems.

[0543] "Information processing means" refers to the function of a system that processes information obtained from an open-source platform and summarizes its contents.

[0544] A "data storage means" is a function that stores data, including the generated summary, and manages it for later retrieval and use.

[0545] A "user" is an individual or group that uses the system to seek solutions to social problems.

[0546] "Social problems" refer to any challenges or difficulties that users seek to resolve, and their content can be diverse.

[0547] A "technical concept" is an idea for a method or device based on ingenuity to solve a specific problem.

[0548] "Implementation method" refers to the means and processes for concretely carrying out a technical concept.

[0549] "Emotion analysis means" refers to a function that identifies emotions from user input data and reflects them in system operation.

[0550] "Connection information" refers to digital links or identification information for accessing related implementation methods.

[0551] The system of this invention aims to propose relevant technical concepts and implementation methods in response to social problems entered by the user. To achieve this, the system consists of three main components: a terminal, a server, and a database.

[0552] The terminal is equipped with a user interface and provides a means for the user to input the social problem they wish to solve. The input data is in text or voice format and is sent to an emotion analysis system. The emotion analysis system recognizes and analyzes the user's emotions using natural language processing techniques. Common speech recognition software and text analysis algorithms are used to implement this technology.

[0553] The server uses social problem and sentiment data received from the user to search a database for relevant technical solutions. The database stores information obtained from open-source platforms, program summaries compiled by generative AI models, and connection information for relevant technical concepts and implementation methods. Taking the sentiment analysis results into account, the server proposes technical concepts in the order that best suits the user's needs.

[0554] For example, if a user inputs a social problem such as "I want to solve the problem of litter in parks," and the emotion analysis system recognizes the emotion of "anxiety," the server can quickly search for relevant technical concepts and prioritize displaying solutions that are particularly easy to implement and promote the user's sense of security.

[0555] Ultimately, the terminal visually presents the information provided by the server to the user, and provides specific implementation guides and connection information as needed. For example, a prompt might be suggested in the form of, "Please share your creative ideas for solving the park's litter problem."

[0556] In this way, the present invention provides users with optimized technical solutions through emotion analysis, thereby supporting the resolution of social problems.

[0557] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0558] Step 1:

[0559] Users input a social problem they want to solve using the device's user interface. This input can be in text or voice format, and this information forms the basis for sentiment analysis. For example, they might input a specific problem such as, "I want to find a way to reduce noise in the city."

[0560] Step 2:

[0561] The terminal transmits the input information to the sentiment analysis system. The sentiment analysis system uses natural language processing technology to analyze the user's emotions from the input text and audio. The input here is the text and audio data entered by the user, and the output extracted as a result of the analysis is the user's emotional state (e.g., dissatisfaction, relief, etc.). In this analysis process, the tone of voice and the positive and negative expressions in the text are specifically analyzed.

[0562] Step 3:

[0563] The server receives emotional data obtained from the emotion analysis system and social problems entered by the user, and generates search queries based on them. The input here is the user's social problem information and the analyzed emotional information, and the output is a specific query for database searching. This query generation involves combining keywords that take into account the intensity of the emotions.

[0564] Step 4:

[0565] The server searches the database using the generated query. The database stores information and related technical concepts summarized by the generating AI model. The input is the search query, and the output is a list of proposed technical concepts and implementation methods. Specifically, it performs a matching process with relevant information in the database.

[0566] Step 5:

[0567] The server reorders search results according to the user's emotional state and selects the most appropriate technical concept. The input here is a list of technical concepts obtained in the previous step, and the output is a prioritized list of the adjusted suggestions. Specifically, if the user's emotional state is determined to be one of reassurance, the server will present solutions with lower risk at the top.

[0568] Step 6:

[0569] The terminal visually presents technical concepts and implementation methods provided by the server to the user. Input is a prioritized list from the server, and output is detailed information displayed on the user interface. The user uses this information to consider specific solutions. The terminal also displays connection information for implementation methods as needed.

[0570] (Application Example 2)

[0571] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0572] Conventional technologies are sometimes insufficient to adequately address the various demands that users face in their living environments. In particular, there is a lack of flexible technological proposals that reflect the emotional state of users, making it difficult to provide solutions that meet user needs. This invention aims to support the improvement of living environments by adjusting priorities based on user emotions and proposing more appropriate technological means.

[0573] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0574] In this invention, the server includes means for generating a summary of information obtained from an open-source platform, means for constructing a structure for storing the summary, means for searching the structure and presenting relevant technical means and their implementations based on user input regarding living environment requirements, means for analyzing the user's emotions and adjusting the priority of proposed technical means, and means for presenting the proposed technical means and implementations to the user as visual information. This makes it possible to accurately reflect the user's emotions in technical proposals and adjust their priority accordingly.

[0575] An "open-source platform" is a collection of information sources that aggregate software and data that are permitted to be freely used, modified, and distributed.

[0576] A "summary" is a concise compilation of the main points and overview of information or data.

[0577] "Structure" refers to a framework or format for systematically organizing and storing information and data.

[0578] "Requirements regarding the living environment" refers to specific needs and problems that users seek to improve in their daily lives.

[0579] "Technical means" refers to technical methods or tools used to solve a specific problem.

[0580] "Implementation" refers to actually applying and making a particular technology or method work.

[0581] "Analyzing emotions" refers to the process of recognizing and classifying emotional states based on a user's expressions and actions.

[0582] "Adjusting priorities" means changing the content and order of implementation based on importance and urgency.

[0583] "Visual information" refers to images and visuals displayed on a screen, and is a means of conveying information to the user.

[0584] The system implementing this invention includes a server for processing information, a terminal with a user interface, and an emotion engine for analyzing emotions. The server uses natural language processing techniques to generate summaries of information obtained from open-source platforms. Specifically, it utilizes text analysis libraries such as spaCy and NLTK to extract key features of the information and store them in a structure as summaries. Users input requests regarding their living environment through the terminal, and this input is accepted in either voice or text format.

[0585] The emotion engine analyzes user input and identifies the user's emotional state. To achieve this, it incorporates an emotion analysis algorithm and assigns emotion labels. The server uses this emotion data to search a database for relevant technical solutions, adjusts their priority, and determines the proposed solutions. The proposed solutions and their implementation information are presented to the user in a visualized form. This visual information is provided through a graphical user interface, making the proposals easier for the user to intuitively understand. By adjusting the user's emotions to the proposed solutions, effective improvements to the living environment are expected.

[0586] As a concrete example, suppose a user inputs "I want to alleviate daytime traffic congestion." If the emotion engine detects the user's stress, the server will prioritize suggesting smart traffic management system technologies to smooth traffic flow. These technologies include real-time traffic data analysis and improvements to signal control systems.

[0587] An example of a prompt message would be: "Please suggest technologies related to the problem entered by the user. When doing so, please prioritize solutions based on the emotions or emotional state the user is seeking."

[0588] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0589] Step 1:

[0590] The terminal receives user-generated requests regarding their living environment in text or voice format. This constitutes the initial input to the system. After input, the terminal sends the data to the server as text.

[0591] Step 2:

[0592] The server analyzes the received text data using natural language processing techniques. Specifically, it extracts keywords from the input content using text analysis libraries (such as spaCy or NLTK) and understands the basic meaning. This clarifies the user's request.

[0593] Step 3:

[0594] The emotion engine analyzes the emotions contained in the input. Using natural language processing algorithms, it identifies emotion labels within the text and outputs emotion categories such as "stress" and "relaxation." This emotion information is needed for subsequent processing.

[0595] Step 4:

[0596] The server searches databases derived from open-source platforms based on interpreted request and sentiment data. It generates search queries to extract summaries and implementation links of relevant technical tools. These queries are optimized using a generative AI model.

[0597] Step 5:

[0598] The server considers sentiment data and adjusts the priority of technical tools accordingly. It sorts the extracted list of technical tools according to sentiment and places them in the order that best suits the user's request.

[0599] Step 6:

[0600] Prioritized technical means and their implementation information are transmitted to the terminal. The terminal presents the suggestions to the user as visual information using a graphical user interface. Based on this information, the user can consider actual actions and improvement measures.

[0601] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0602] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0603] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0604] [Fourth Embodiment]

[0605] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0606] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0607] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0608] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0609] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0610] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0611] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0612] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0613] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0614] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0615] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0616] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0617] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0618] The invention's system primarily consists of multiple computer devices (servers and terminals). Here, we illustrate the flow of the system's main functions: program acquisition from an open-source platform, summary generation, database construction, and search and idea generation in response to social issues.

[0619] The server periodically scans open-source platforms and retrieves new program repositories. Next, it uses a generative AI model to summarize the code in each repository in human-readable language. This summary information is stored in a database designed for efficient searching. As a result, the database functions as a massive knowledge base, containing a wide variety of technical ideas and their implementation information.

[0620] The user inputs a social issue they want to solve via their device. This input is sent to a server, which analyzes the issue to generate an appropriate search query. Using the generated query, the server searches its database for and suggests relevant technical ideas and implementation information.

[0621] For example, if a user is looking for a "system to reduce food waste," the server will search for relevant programs and ideas and suggest potentially relevant technical solutions such as a "household inventory management app" or a "local sharing platform." Based on these suggestions, the user can leverage existing implementations and quickly deploy their own project.

[0622] In this way, the invention efficiently extracts and provides ideas for solving social problems faced by many people. Users can utilize the proposed technology to implement valuable projects in a short period of time. This system reduces the burden on users through automated processes and dramatically increases the possibility of solving problems.

[0623] The following describes the processing flow.

[0624] Step 1:

[0625] The server retrieves the latest repository information from open-source platforms. This involves using APIs to crawl publicly available repositories and collect program data.

[0626] Step 2:

[0627] The server analyzes the collected program data and generates a summary of each program using a generative AI model. The summary is output as natural language text in a format that is easy for humans to understand.

[0628] Step 3:

[0629] The server stores the generated summary in a database. In addition to the summarized information, related metadata (e.g., repository name, author, update date, etc.) is also stored there.

[0630] Step 4:

[0631] Users input the social issue they want to solve via their device. This involves text input, providing keywords and sentences related to the issue.

[0632] Step 5:

[0633] The terminal sends user input information to the server. The server receives this information and generates an appropriate search query based on the entered task.

[0634] Step 6:

[0635] The server uses the generated search query to search the database. It extracts relevant technical ideas and their implementation information from the database and lists the most relevant results.

[0636] Step 7:

[0637] The server sends the extracted search results to the terminal. The terminal receives these results and displays the suggested technical ideas and corresponding implementation information to the user.

[0638] Step 8:

[0639] Users review the presented information, view links to repositories and implementation guides as needed, and then proceed to start and run the project.

[0640] (Example 1)

[0641] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0642] In response to the diverse social challenges of today, there is a need to find appropriate and rapid technological solutions and provide users with ways to effectively utilize them. However, efficiently extracting, summarizing, and appropriately presenting relevant information from a vast program repository is difficult and burdensome for users.

[0643] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0644] In this invention, the server includes means for generating a summary of an electronic program obtained from a software platform, means for constructing an information storage device that stores the summary, and means for searching the information storage device based on a social issue input by a user and proposing relevant technical solutions and methods for their implementation. This enables users to quickly discover and implement technical solutions for solving social issues.

[0645] A "software platform" refers to software repositories or code-sharing sites that users can access over the internet.

[0646] An "electronic program" is a series of instructions or code executed by a computer, and is a component of software.

[0647] A "summary" is a concise explanatory text that describes the main functions and features of an electronic program.

[0648] An "information storage device" is a database or storage system capable of storing digital data over long periods of time.

[0649] A "user" is an individual or legal entity that uses this system to solve social problems.

[0650] "Social issues" refer to problems or challenges faced by society as a whole or by a specific community, and include those that require technological solutions.

[0651] A "technical proposal" is a technical idea or concept proposed as a means of solving a specific problem.

[0652] "Implementation method" refers to the specific steps and processes for developing a technical proposal into a concrete form and putting it into practice.

[0653] The system in this invention consists of a user, a server, and a terminal.

[0654] The server first periodically accesses the software platform via the internet to retrieve new electronic programs. This process utilizes a Linux server and Python scripts, employing publicly available APIs. The server inputs the retrieved programs into a generating AI model (e.g., an open-source natural language processing model) to generate a summary in a human-readable format. An example of a prompt in this process is, "Please explain the main function and purpose of this code."

[0655] Next, the server saves the generated summary to an information storage device (SQL database). This database is indexed, allowing for efficient searching. This enables the rapid management of multiple technical proposals and their implementation methods.

[0656] On the other hand, users input the social issues they want to solve via their own devices (personal computers or mobile devices). This input is expressed in natural language and sent to the server via the internet.

[0657] The server analyzes the user's request using natural language processing algorithms (e.g., Spacy or NLTK) and extracts relevant keywords. Based on the resulting search queries, the server searches its information storage device, identifies relevant technical proposals and implementation methods, and proposes them to the user.

[0658] For example, if a user searches for "ways to reduce energy consumption," the server will provide relevant suggestions such as "efficient energy management systems" or "smart home technologies." Users can then use these suggestions to quickly and effectively find solutions to their challenges. This process enables users to facilitate the implementation of new projects and contribute to solving social problems.

[0659] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0660] Step 1:

[0661] The server periodically retrieves new electronic programs using the software platform's API. The input is a program repository stored on a specific open-source platform. It filters the data by calling the API and selects relevant repositories based on criteria such as keywords and stars. The output is a list of related repositories.

[0662] Step 2:

[0663] The server inputs the acquired program into a generating AI model to generate a summary. The input is a code block obtained from the repository. Specifically, the server sends a prompt to the generating AI model asking, "Please explain the main function and purpose of this code." The model responds with a summary in natural language. The output is a summarized text in a human-readable format.

[0664] Step 3:

[0665] The server stores the generated summary in an SQL database, which is an information storage device. The input is the summary text generated in the previous step. The server indexes this summary, creating a structure that enables efficient searching. The output is a searchable database entry.

[0666] Step 4:

[0667] The user inputs a social issue they want to solve in natural language via their device. The input is text about the issue the user has in mind. The device sends this information to the server via the internet. The output is the text of the issue received by the server.

[0668] Step 5:

[0669] The server analyzes the user's task and generates a search query. The input is the text of the task sent from the terminal. The server uses natural language processing tools to analyze the text and extract relevant keywords. The output is the search query generated based on these keywords.

[0670] Step 6:

[0671] The server uses the generated query to search the database and identify relevant technical solutions and implementation methods. The input is the search query created in the previous step. The SQL query is executed against the database to retrieve the relevant dataset. The output is a list of technical solutions related to the user's problem.

[0672] Step 7:

[0673] The server presents the identified technical proposals and their implementation methods to the user. The input is a list of technical proposals resulting from a database search. The server sends this information back to the terminal and displays it in a user-friendly format. The output is the list of technical proposals and their implementation methods displayed on the terminal.

[0674] Step 8:

[0675] The user plans and implements a specific project based on the presented technical proposals. The input is information on the technical proposals obtained from the server. The user uses this information to plan the project. The output is the project that is actually planned and implemented.

[0676] (Application Example 1)

[0677] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0678] In modern society, the advancement of urbanization has brought to light a wide variety of challenges, including traffic congestion, energy efficiency, and environmental problems. To address these challenges quickly and easily, it is necessary to efficiently utilize existing technologies and ideas. However, the amount of related information is vast, making its organization and retrieval difficult, thus requiring a rapid response to problem-solving.

[0679] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0680] In this invention, the server includes means for generating summaries of programs obtained from an open-source platform, means for constructing a knowledge base storing the summaries, and means for searching the knowledge base based on social issues input by users and proposing relevant technical ideas and their implementations. This makes it possible to effectively explore solutions to urban problems and quickly present the technical ideas and implementation information that users need.

[0681] An "open-source platform" is a foundation that provides repositories and projects of programs that can be freely accessed on the internet.

[0682] A "summary" is a short, human-readable summary of information about a program obtained from an open-source platform.

[0683] A "knowledge base" is a collection of information that stores generated summaries, enabling efficient searching and information provision.

[0684] "Users" refer to individuals or organizations that use the system to explore solutions to social problems.

[0685] "Social issues" refer to general or specific problems that need to be solved in cities, such as traffic congestion, energy efficiency, and environmental issues.

[0686] A "technical idea" is a conceptual or practical proposal that refers to a solution or method for addressing a specific problem.

[0687] "Implementation" refers to the act or result of transforming a proposed technical idea into a concrete system or process.

[0688] The system that implements this application works through the collaboration of a server and a user's terminal. The server first periodically scans program repositories from open-source platforms on the internet and generates summaries of the retrieved code. These summaries include the program's main functions and uses, and are converted into a human-readable format. A generative AI model, such as OpenAI, is used for this summarization process. The generated summaries are stored in a database as a knowledge base, enabling efficient searching.

[0689] Users input specific social issues via smartphones or other devices and query the server. The server analyzes this input and generates queries that address the issues. Using the generated queries, the server searches a knowledge base and presents users with relevant technological ideas and information on their implementation. This information provides a basis for quickly considering solutions to urban challenges, allowing users to explore concrete solutions based on the proposed technologies.

[0690] For example, if a user inputs "measures to alleviate traffic congestion" as a problem, the server can immediately present relevant technical information such as "smart traffic signal control systems" and "technologies to promote the use of public transport."

[0691] Examples of prompts for a generative AI model are as follows:

[0692] "Users are looking for ways to alleviate urban traffic congestion. Please list relevant technical ideas from the latest open-source projects."

[0693] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0694] Step 1:

[0695] The server accesses the open-source platform and retrieves new program repositories. The server sends API requests daily or at a configured frequency to collect new codebases. This process yields open-source code as input and a data set of extracted code as output.

[0696] Step 2:

[0697] The server uses a generative AI model to summarize the acquired code. Using the code data obtained in Step 1 as input, it generates a summary that describes the code's functions and features in natural language. This summarization process enables the understanding of programs obtained from open-source platforms.

[0698] Step 3:

[0699] The server stores the generated summaries in a knowledge base. The summary information is entered and organized into a database for efficient searching. This step results in a knowledge base that enables rapid access to information.

[0700] Step 4:

[0701] The user enters a social issue they want to solve on their device. The issue entered here consists of keywords or phrases related to a specific problem and reflects the user's needs. The user's input is sent to the server in the next step.

[0702] Step 5:

[0703] The server analyzes the issues submitted by users and generates appropriate search queries. Using the user issue information obtained in step 4 as input, it generates queries for database searches based on relevant keywords and context. This query generation improves the accuracy and relevance of searches.

[0704] Step 6:

[0705] The server uses the generated query to search the knowledge base and retrieve relevant technical ideas and their implementation information. Using the search query obtained in step 5 as input, it retrieves a list of highly relevant solutions as output. This search process allows users to quickly access the information they are looking for.

[0706] Step 7:

[0707] The server presents the search results to the user. Using the solution information obtained in step 6 as input, it visually displays the results to the user via the terminal. This allows the user to quickly evaluate technical options based on specific urban challenges.

[0708] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0709] The system of the present invention comprises a terminal equipped with a user interface, a server for data processing, and an emotion engine. The purpose of this system is to generate a summary of program data obtained from an open-source platform, store it in a database, and further present relevant technical ideas and their implementations based on the social issues entered by the user and the emotions perceived.

[0710] The device provides an interface for users to input social issues they wish to solve. The input information may include text and audio, and based on this, an emotion engine recognizes the user's emotions. The emotion engine uses natural language processing technology to extract emotions from the text and audio and analyzes their state.

[0711] The server generates search queries based on the user's problem information and emotional state, and searches the database. The information stored in the database includes program summaries, technical ideas, and implementation links summarized by a generative AI model. The server adjusts the order of suggested technical ideas and filters them, taking the user's emotions into consideration.

[0712] For example, if a user enters "I want to find a way to reduce city noise," and the emotion engine recognizes this as a feeling of dissatisfaction, the server will search its database for relevant programs and quickly and preferentially present technical solutions that are expected to have a particularly effective stress-reducing effect. In this way, flexible services tailored to the user's preferences and current emotional state can be provided.

[0713] Ultimately, the terminal visually presents the results to the user and provides detailed implementation guides and links to repositories as needed. Users can then effectively develop their projects based on these suggestions. By linking emotion recognition to technical proposals, this system provides an appropriate and human-centered approach to solving social problems.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] Users input the social issues they want to solve via text or voice through their device. Examples of issues they might provide include "I want to know how to improve urban water quality."

[0717] Step 2:

[0718] The device uses an emotion engine to analyze the user's emotional state from their input. For example, the analysis of the input may detect emotions such as "confusion" or "enthusiasm."

[0719] Step 3:

[0720] The device sends the analyzed information to the server, passing on task information along with the user's emotional state. This allows the server to obtain basic data to understand the user's intentions and feelings.

[0721] Step 4:

[0722] The server uses a generative AI model to search a database for summaries of code previously obtained from open-source platforms.

[0723] Step 5:

[0724] The server narrows down the database search results to potential technological ideas and implementations related to the user's social issues.

[0725] Step 6:

[0726] The server takes the output of the emotion engine into consideration and adjusts the order in which it displays technology ideas to prioritize them. For example, presenting a proposal like "environmentally friendly water purification system" first might evoke positive emotions.

[0727] Step 7:

[0728] The server sends the refined technical idea and its implementation information to the terminal.

[0729] Step 8:

[0730] The terminal presents the received information to the user. Through a visual interface, it displays detailed information about the proposed idea and links to related repositories, allowing the user to quickly access concrete solutions.

[0731] Step 9:

[0732] Based on the information provided, users start their own projects and aim to solve problems. If necessary, they can view detailed technical documentation via suggested links to aid in implementation.

[0733] (Example 2)

[0734] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0735] The present invention aims to provide a system that effectively and quickly proposes solutions to social problems faced by users. Specifically, it aims to solve the problem of presenting more appropriate solutions by efficiently summarizing information obtained from diverse sources and proposing relevant technical concepts and implementation methods based on that information, while taking into account the emotional state of the user.

[0736] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0737] In this invention, the server includes information processing means, means for storing data in data storage means, and means for recognizing the user's emotional state using emotion analysis means. This makes it possible to propose appropriate technical concepts that address the user's social problems.

[0738] "Information processing means" refers to the function of a system that processes information obtained from an open-source platform and summarizes its contents.

[0739] A "data storage means" is a function that stores data, including the generated summary, and manages it for later retrieval and use.

[0740] A "user" is an individual or group that uses the system to seek solutions to social problems.

[0741] "Social problems" refer to any challenges or difficulties that users seek to resolve, and their content can be diverse.

[0742] A "technical concept" is an idea for a method or device based on ingenuity to solve a specific problem.

[0743] "Implementation method" refers to the means and processes for concretely carrying out a technical concept.

[0744] "Emotion analysis means" refers to a function that identifies emotions from user input data and reflects them in system operation.

[0745] "Connection information" refers to digital links or identification information for accessing related implementation methods.

[0746] The system of this invention aims to propose relevant technical concepts and implementation methods in response to social problems entered by the user. To achieve this, the system consists of three main components: a terminal, a server, and a database.

[0747] The terminal is equipped with a user interface and provides a means for the user to input the social problem they wish to solve. The input data is in text or voice format and is sent to an emotion analysis system. The emotion analysis system recognizes and analyzes the user's emotions using natural language processing techniques. Common speech recognition software and text analysis algorithms are used to implement this technology.

[0748] The server uses social problem and sentiment data received from the user to search a database for relevant technical solutions. The database stores information obtained from open-source platforms, program summaries compiled by generative AI models, and connection information for relevant technical concepts and implementation methods. Taking the sentiment analysis results into account, the server proposes technical concepts in the order that best suits the user's needs.

[0749] For example, if a user inputs a social problem such as "I want to solve the problem of litter in parks," and the emotion analysis system recognizes the emotion of "anxiety," the server can quickly search for relevant technical concepts and prioritize displaying solutions that are particularly easy to implement and promote the user's sense of security.

[0750] Ultimately, the terminal visually presents the information provided by the server to the user, and provides specific implementation guides and connection information as needed. For example, a prompt might be suggested in the form of, "Please share your creative ideas for solving the park's litter problem."

[0751] In this way, the present invention provides users with optimized technical solutions through emotion analysis, thereby supporting the resolution of social problems.

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

[0753] Step 1:

[0754] Users input a social problem they want to solve using the device's user interface. This input can be in text or voice format, and this information forms the basis for sentiment analysis. For example, they might input a specific problem such as, "I want to find a way to reduce noise in the city."

[0755] Step 2:

[0756] The terminal transmits the input information to the sentiment analysis system. The sentiment analysis system uses natural language processing technology to analyze the user's emotions from the input text and audio. The input here is the text and audio data entered by the user, and the output extracted as a result of the analysis is the user's emotional state (e.g., dissatisfaction, relief, etc.). In this analysis process, the tone of voice and the positive and negative expressions in the text are specifically analyzed.

[0757] Step 3:

[0758] The server receives emotional data obtained from the emotion analysis system and social problems entered by the user, and generates search queries based on them. The input here is the user's social problem information and the analyzed emotional information, and the output is a specific query for database searching. This query generation involves combining keywords that take into account the intensity of the emotions.

[0759] Step 4:

[0760] The server searches the database using the generated query. The database stores information and related technical concepts summarized by the generating AI model. The input is the search query, and the output is a list of proposed technical concepts and implementation methods. Specifically, it performs a matching process with relevant information in the database.

[0761] Step 5:

[0762] The server reorders search results according to the user's emotional state and selects the most appropriate technical concept. The input here is a list of technical concepts obtained in the previous step, and the output is a prioritized list of the adjusted suggestions. Specifically, if the user's emotional state is determined to be one of reassurance, the server will present solutions with lower risk at the top.

[0763] Step 6:

[0764] The terminal visually presents technical concepts and implementation methods provided by the server to the user. Input is a prioritized list from the server, and output is detailed information displayed on the user interface. The user uses this information to consider specific solutions. The terminal also displays connection information for implementation methods as needed.

[0765] (Application Example 2)

[0766] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0767] Conventional technologies are sometimes insufficient to adequately address the various demands that users face in their living environments. In particular, there is a lack of flexible technological proposals that reflect the emotional state of users, making it difficult to provide solutions that meet user needs. This invention aims to support the improvement of living environments by adjusting priorities based on user emotions and proposing more appropriate technological means.

[0768] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0769] In this invention, the server includes means for generating a summary of information obtained from an open-source platform, means for constructing a structure for storing the summary, means for searching the structure and presenting relevant technical means and their implementations based on user input regarding living environment requirements, means for analyzing the user's emotions and adjusting the priority of proposed technical means, and means for presenting the proposed technical means and implementations to the user as visual information. This makes it possible to accurately reflect the user's emotions in technical proposals and adjust their priority accordingly.

[0770] An "open-source platform" is a collection of information sources that aggregate software and data that are permitted to be freely used, modified, and distributed.

[0771] A "summary" is a concise compilation of the main points and overview of information or data.

[0772] "Structure" refers to a framework or format for systematically organizing and storing information and data.

[0773] "Requirements regarding the living environment" refers to specific needs and problems that users seek to improve in their daily lives.

[0774] "Technical means" refers to technical methods or tools used to solve a specific problem.

[0775] "Implementation" refers to actually applying and making a particular technology or method work.

[0776] "Analyzing emotions" refers to the process of recognizing and classifying emotional states based on a user's expressions and actions.

[0777] "Adjusting priorities" means changing the content and order of implementation based on importance and urgency.

[0778] "Visual information" refers to images and visuals displayed on a screen, and is a means of conveying information to the user.

[0779] The system implementing this invention includes a server for processing information, a terminal with a user interface, and an emotion engine for analyzing emotions. The server uses natural language processing techniques to generate summaries of information obtained from open-source platforms. Specifically, it utilizes text analysis libraries such as spaCy and NLTK to extract key features of the information and store them in a structure as summaries. Users input requests regarding their living environment through the terminal, and this input is accepted in either voice or text format.

[0780] The emotion engine analyzes user input and identifies the user's emotional state. To achieve this, it incorporates an emotion analysis algorithm and assigns emotion labels. The server uses this emotion data to search a database for relevant technical solutions, adjusts their priority, and determines the proposed solutions. The proposed solutions and their implementation information are presented to the user in a visualized form. This visual information is provided through a graphical user interface, making the proposals easier for the user to intuitively understand. By adjusting the user's emotions to the proposed solutions, effective improvements to the living environment are expected.

[0781] As a concrete example, suppose a user inputs "I want to alleviate daytime traffic congestion." If the emotion engine detects the user's stress, the server will prioritize suggesting smart traffic management system technologies to smooth traffic flow. These technologies include real-time traffic data analysis and improvements to signal control systems.

[0782] An example of a prompt message would be: "Please suggest technologies related to the problem entered by the user. When doing so, please prioritize solutions based on the emotions or emotional state the user is seeking."

[0783] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0784] Step 1:

[0785] The terminal receives user-generated requests regarding their living environment in text or voice format. This constitutes the initial input to the system. After input, the terminal sends the data to the server as text.

[0786] Step 2:

[0787] The server analyzes the received text data using natural language processing techniques. Specifically, it extracts keywords from the input content using text analysis libraries (such as spaCy or NLTK) and understands the basic meaning. This clarifies the user's request.

[0788] Step 3:

[0789] The emotion engine analyzes the emotions contained in the input. Using natural language processing algorithms, it identifies emotion labels within the text and outputs emotion categories such as "stress" and "relaxation." This emotion information is needed for subsequent processing.

[0790] Step 4:

[0791] The server searches databases derived from open-source platforms based on interpreted request and sentiment data. It generates search queries to extract summaries and implementation links of relevant technical tools. These queries are optimized using a generative AI model.

[0792] Step 5:

[0793] The server considers sentiment data and adjusts the priority of technical tools accordingly. It sorts the extracted list of technical tools according to sentiment and places them in the order that best suits the user's request.

[0794] Step 6:

[0795] Prioritized technical means and their implementation information are transmitted to the terminal. The terminal presents the suggestions to the user as visual information using a graphical user interface. Based on this information, the user can consider actual actions and improvement measures.

[0796] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0797] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0798] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0799] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0800] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0801] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0802] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0803] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0804] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0805] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0806] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0807] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0808] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0809] 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.

[0810] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0811] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0812] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0813] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0814] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0815] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0816] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0817] The following is further disclosed regarding the embodiments described above.

[0818] (Claim 1)

[0819] A means for generating a summary of a computer program obtained from an open-source platform,

[0820] Means for constructing a database storing the aforementioned summary,

[0821] A means for searching the database based on social issues entered by users and proposing related technological ideas and their implementations,

[0822] A means of presenting the proposed technical idea and implementation to the user,

[0823] A system that includes this.

[0824] (Claim 2)

[0825] The system according to claim 1, further comprising means for analyzing social issues entered by a user and generating keywords corresponding to them.

[0826] (Claim 3)

[0827] The system according to claim 1, wherein the generated summary includes an outline of the relevant technical idea and a link to the relevant implementation.

[0828] "Example 1"

[0829] (Claim 1)

[0830] A means for generating a summary of an electronic program obtained from a software platform,

[0831] Means for constructing an information storage device that stores the aforementioned summary,

[0832] A means for searching the information storage device based on social issues entered by users and proposing related technical proposals and methods for their implementation,

[0833] A means of presenting the proposed technical plan and implementation method to the user,

[0834] A system that includes this.

[0835] (Claim 2)

[0836] The system according to claim 1, further comprising means for analyzing social issues entered by a user and generating corresponding vocabulary.

[0837] (Claim 3)

[0838] The system according to claim 1, wherein the generated summary includes a link between an outline of the relevant technical proposal and a relevant method of implementation.

[0839] "Application Example 1"

[0840] (Claim 1)

[0841] A means for generating a program summary obtained from an open-source platform,

[0842] Means for constructing a knowledge base storing the aforementioned summary,

[0843] A means for searching the aforementioned knowledge base based on social issues entered by users and proposing related technological ideas and their implementations,

[0844] A means of presenting the proposed technical idea and implementation to the user,

[0845] A means of exploring and proposing solutions to urban challenges,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, further comprising means for analyzing social issues entered by users and generating corresponding queries.

[0849] (Claim 3)

[0850] The system according to claim 1, wherein the generated summary includes an overview of the relevant technical idea and a reference to its implementation.

[0851] "Example 2 of combining an emotion engine"

[0852] (Claim 1)

[0853] Information processing means obtained from an open-source platform,

[0854] Means for storing the summary generated by the information processing means in a data storage means,

[0855] A means for searching the data storage means based on social problems entered by users, and proposing related technical concepts and their implementation methods,

[0856] A means for recognizing the user's emotional state using emotion analysis means and adjusting the proposed order of the aforementioned technical concepts,

[0857] A means of presenting the proposed technical concept and implementation method to the user,

[0858] A system that includes this.

[0859] (Claim 2)

[0860] The system according to claim 1, further comprising means for analyzing a social problem entered by a user and generating characteristic words corresponding to it.

[0861] (Claim 3)

[0862] The system according to claim 1, wherein the generated summary includes a summary of the relevant technical concept and connection information of the relevant implementation.

[0863] "Application example 2 when combining with an emotional engine"

[0864] (Claim 1)

[0865] A means of generating a summary of information obtained from an open-source platform,

[0866] Means for constructing a structure that stores the aforementioned summary,

[0867] A means for searching for the aforementioned structure based on user input regarding living environment requirements and presenting related technical means and their implementations,

[0868] A means of analyzing user emotions and adjusting the priority of proposed technological measures,

[0869] A means of presenting the proposed technical means and implementation to the user as visual information,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, further comprising means for analyzing user inputs regarding living environment requirements and generating corresponding keywords.

[0873] (Claim 3)

[0874] The system according to claim 1, wherein the generated summary includes an overview of the relevant technical means and connection information of the relevant implementation. [Explanation of Symbols]

[0875] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for generating a program summary obtained from an open-source platform, Means for constructing a knowledge base storing the aforementioned summary, A means for searching the aforementioned knowledge base based on social issues entered by users and proposing related technological ideas and their implementations, A means of presenting the proposed technical idea and implementation to the user, A means of exploring and proposing solutions to urban challenges, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing social issues entered by users and generating corresponding queries.

3. The system according to claim 1, wherein the generated summary includes an overview of the relevant technical idea and a reference to its implementation.

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