system

Abstract

The system according to this embodiment aims to sustainably preserve traditional crafts and regional culture and develop them as a tourism business. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, a proposal unit, and a commercialization unit. The collection unit collects detailed information and material information from the target craftsman. The analysis unit analyzes the information collected by the collection unit. The proposal unit proposes an experiential tour based on the analysis results obtained by the analysis unit. The commercialization unit commercializes the content proposed by the proposal unit into a tourism business.

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] In the conventional technology, it is difficult to sustainably inherit traditional crafts and regional cultures, and there are particularly problems in the succession of the business in terms of human resources.

[0005] The system according to the embodiment aims to sustainably inherit traditional crafts and regional cultures and develop them as a tourism business.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a collection unit, an analysis unit, a proposal unit, and a commercialization unit. The collection unit collects detailed information and material information from target artisans. The analysis unit analyzes the information collected by the collection unit. The proposal unit proposes an experiential tour based on the analysis results obtained by the analysis unit. The commercialization unit commercializes the content proposed by the proposal unit into a tourism business. [Effects of the Invention]

[0007] The system according to this embodiment can sustainably pass on traditional crafts and regional culture and develop them as a tourism business. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, etc. The communication I / F manages communication between multiple computers. Examples of communication standards applicable to the communication I / F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] 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 only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] 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.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice 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 unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (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.

[0022] 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.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The system according to an embodiment of the present invention is a system for sustainably passing down Japanese craftsmanship that has been inherited for over 100 years. This system collects detailed information and material information from target craftsmen and uses it to train an AI. Next, it analyzes the needs of foreign visitors to Japan through social media and other means, extracts priority tour elements, and creates a database. Furthermore, an AI agent proposes experiential tours tailored to the national characteristics and preferences of each country to local organizations, which are then used to develop tourism businesses. This system enables the commercialization of the passion of the craftsmen and the historical stories behind them for inbound tourism, ensuring stable income for the craftsmen and preserving cultural heritage. In addition, foreign tourists visiting Japan can have valuable experiences that they cannot learn about online, and repeat visits are expected. For example, it collects detailed information and material information from target craftsmen. In this process, detailed information such as the craftsman's techniques, commitment, and historical background is collected and used to train the AI. For example, by training the AI ​​on the procedures of specific techniques and the characteristics of the materials used, detailed information on craftsmanship is created in a database. Next, it analyzes the needs of foreign visitors to Japan through social media and other means. AI analyzes posts and comments on social media to understand what experiences foreign tourists are seeking. For example, it extracts needs such as "experiencing Japanese culture" or "walking through ancient cities and historical towns" and creates a database of priority tour elements. Furthermore, the AI ​​agent proposes experiential tours tailored to the national characteristics and preferences of each country to local organizations. Based on the collected information, the AI ​​agent proposes the most suitable experiential tours for tourists from each country. For example, it might propose tours that include traditional craft experiences and introductions to local culture to tourists from a specific country. These proposals are then used in collaboration with local organizations to develop tourism businesses. This system enables the business development of cultural heritage by commercializing the passion of those involved and the historical stories behind them for inbound tourism, ensuring stable income for those involved and preserving cultural heritage. In addition, foreign tourists visiting Japan can have valuable experiences that they cannot learn about online, which is likely to encourage repeat visits. For example, foreign tourists who experience traditional Japanese crafts and are impressed by the techniques and history are likely to return. In this way, the system can simultaneously achieve the transmission of craftsmanship and the development of the tourism industry.

[0029] The system according to this embodiment comprises a collection unit, an analysis unit, a proposal unit, and a commercialization unit. The collection unit collects detailed information and material information from the target craftsman. For example, the collection unit collects detailed information such as the craftsman's skills, commitment, and historical background. For example, the collection unit can collect information such as the procedures for specific techniques and the characteristics of the materials used. The collection unit can also record the craftsman's work scene and production process. For example, the collection unit can conduct interviews with craftsmen to collect information on how to pass on their skills and their commitment to production. The analysis unit analyzes the information collected by the collection unit. For example, the analysis unit analyzes the characteristics and technical details of the craftsman's skills based on the collected information. For example, the analysis unit can analyze the historical background and cultural significance of the craftsman's skills based on the collected information. For example, the analysis unit can propose methods for preserving and passing on the craftsman's skills based on the collected information. For example, the analysis unit can analyze the market value and demand for the craftsman's skills based on the collected information. The proposal unit proposes an experiential tour based on the analysis results obtained by the analysis unit. The proposal department, for example, proposes experiential tours best suited to travelers from various countries. For example, the proposal department can propose tours that include traditional craft experiences and introductions to local culture to travelers from a specific country. The proposal department can also propose customized tours tailored to travelers' needs based on the collected information. For example, the proposal department can propose tours that allow travelers to experience specific technologies or cultures based on their interests. The commercialization department turns the proposals made by the proposal department into tourism businesses. For example, the commercialization department develops plans for actually operating the proposed experiential tours. For example, the commercialization department can secure resources to realize the proposed tours by collaborating with local organizations and tourism businesses. The commercialization department can also market and promote the proposed tours. For example, the commercialization department can build a revenue model for the proposed tours and develop plans for operating them as sustainable businesses. In this way, the system according to the embodiment can collect and analyze detailed information on craftsmanship, propose experiential tours, and commercialize them into tourism businesses, thereby enabling the transmission of craftsmanship and the development of the tourism industry.

[0030] The data collection department gathers detailed information and material information from the target craftsmen. For example, the department collects detailed information such as the craftsmen's techniques, their commitment to their craft, and their historical background. Specifically, it records in detail what kind of techniques the craftsmen possess, how those techniques have developed, and the craftsmen's thoughts and commitment to those techniques. The data collection department can collect information such as the procedures for specific techniques and the characteristics of the materials used. This includes the criteria for selecting the tools and materials used by the craftsmen, as well as the ingenuity and precautions taken during the production process. The data collection department can also record the craftsmen at work and the production process. This allows for a visual understanding of how the craftsmen's techniques are put into practice. The data collection department can also conduct interviews with craftsmen to collect information on how their techniques are passed down and their commitment to their craft. In the interviews, they will ask in detail how the craftsmen learned their techniques, how they pass them on to the next generation, and about the difficulties and successes they have experienced in that process. This allows the data collection department to grasp the overall picture of the craftsmanship and collect detailed information. Furthermore, the data collection department digitizes this information and stores it in a database so that it can be used for later analysis and proposals. The collection department is required to build trusting relationships with craftsmen while continuously collecting and updating information. This allows the collection department to contribute to the preservation and transmission of craftsmanship and play a crucial role in supporting the foundation of the entire system.

[0031] The Analysis Department analyzes the information collected by the Data Collection Department. For example, the Analysis Department analyzes the characteristics and technical details of craftsmanship based on the collected information. Specifically, it classifies the collected technical information and clarifies the characteristics and uniqueness of each technique. For example, the Analysis Department can analyze the historical background and cultural significance of craftsmanship based on the collected information. This includes investigating the historical process by which the technique has developed and the impact it has had on the region and culture. The Analysis Department can also propose methods for preserving and passing on craftsmanship based on the collected information. For example, this could include digital archiving of the technique or designing training programs for the next generation of craftsmen. The Analysis Department can also analyze the market value and demand for craftsmanship based on the collected information. This includes analyzing current market trends and consumer preferences to clarify how craftsmanship is valued and what kind of demand exists. Furthermore, the Analysis Department can use AI to analyze the collected data and extract patterns and trends. For example, it can use natural language processing technology to analyze interview content and extract common themes and important keywords. Furthermore, by using image recognition technology to analyze video footage of the work process, the system can automatically identify the characteristics of the techniques and the work procedures. This allows the analysis department to analyze the collected information from multiple perspectives and make concrete proposals for the preservation and transmission of traditional craftsmanship.

[0032] The Proposal Department proposes experiential tours based on the analysis results obtained by the Analysis Department. For example, the Proposal Department proposes experiential tours that are best suited to travelers from each country. Specifically, they design tours that allow travelers to experience artisanal skills based on their interests. For example, the Proposal Department can propose tours to travelers from a particular country that include experiences of traditional crafts and introductions to local culture. This could include workshops where travelers visit artisans' studios and experience the techniques firsthand, or guided tours that teach about local history and culture. The Proposal Department can also propose customized tours tailored to travelers' needs based on the collected information. For example, they can offer an experiential program specializing in a particular technique for travelers interested in that technique. They can also propose programs that allow families and groups to experience multiple techniques. The Proposal Department can also propose tours that allow travelers to experience specific techniques or cultures based on their interests. This could include opportunities to interact with artisans and observe demonstrations of their techniques. Furthermore, the Proposal Department can collect traveler feedback and use it to improve the tour content. For example, they can review the program content and operation methods based on tour participants' satisfaction and opinions to provide a more attractive experience. Furthermore, the proposal department can utilize the digital platform to handle tour bookings and provide information. This allows the proposal department to offer attractive experiential tours to travelers, contributing to the dissemination of traditional craftsmanship and the development of the tourism industry.

[0033] The Commercialization Department is responsible for commercializing the ideas proposed by the Proposal Department. For example, the Commercialization Department develops plans for actually operating the proposed experiential tours. Specifically, this involves designing the tour schedule and content in detail and securing the necessary resources for operation. The Commercialization Department can, for example, collaborate with local organizations and tourism businesses to secure the resources needed to realize the proposed tours. This includes arranging artisans and guides, securing tour locations, and preparing necessary equipment and materials. The Commercialization Department can also market and promote the proposed tours. For example, it can utilize digital marketing to promote the tour's appeal through social media and websites to attract travelers. It can also partner with travel agencies and tourism information websites to promote tour sales. The Commercialization Department can, for example, develop a revenue model for the proposed tours and develop plans for operating it as a sustainable business. This includes pricing, cost management, and revenue distribution methods. Furthermore, the Commercialization Department is required to monitor the tour's operation and continuously strive for improvement. For example, based on participant feedback, the tour content and operation methods can be reviewed to provide a better experience. Furthermore, the business development department can utilize local tourism resources and contribute to the revitalization of the local economy. In this way, the business development department can realize proposed tours and operate them as sustainable tourism businesses, thereby contributing to the preservation of traditional craftsmanship and the development of the tourism industry.

[0034] The system includes an SNS collection unit that collects SNS data. The SNS collection unit collects posts and comments on SNS, for example. The SNS collection unit can also collect posts related to specific hashtags or keywords, for example. Furthermore, the SNS collection unit can analyze the collected data to understand the needs of foreign tourists. The SNS collection unit can also collect trends and popular posts on SNS and analyze the interests of tourists, for example. The SNS collection unit can also collect images and videos on SNS and analyze the visual information, for example. This makes it easier to understand the needs of foreign tourists by collecting SNS data. Some or all of the above processing in the SNS collection unit may be performed using AI, for example, or without AI. For example, the SNS collection unit can input posts and comments on SNS into a generating AI and have the generating AI perform the collection of related data.

[0035] The system includes a needs analysis unit that analyzes the needs of foreign travelers. The needs analysis unit analyzes the needs of foreign travelers, for example, based on collected social media data. The needs analysis unit can, for example, understand travelers' interests and concerns and analyze what kind of experiences they are seeking. The needs analysis unit can also analyze the services and activities that travelers expect, based on the collected data. The needs analysis unit can also understand needs, for example, based on travelers' past travel history and feedback. The needs analysis unit can also analyze individual needs, for example, based on travelers' profile information. By analyzing the needs of foreign travelers, it is possible to propose more appropriate experiential tours. Some or all of the above processing in the needs analysis unit may be performed using AI, for example, or without AI. For example, the needs analysis unit can input collected social media data into a generating AI and have the generating AI perform the analysis of travelers' needs.

[0036] The system includes a country-specific suggestion section that proposes tours tailored to the national characteristics and preferences of each country. This section analyzes, for example, the cultural background and general preferences of travelers in each country. It can also identify preferred activities and food preferences for travelers from a particular country. Furthermore, based on the collected data, the section can propose the most suitable experiential tours for travelers in each country. For example, it can propose tours to travelers from a specific country that include experiences of traditional crafts or introductions to local culture. The section can also propose customized tours based on travelers' country-specific travel trends and interests. This improves the satisfaction of foreign travelers by proposing tours tailored to the national characteristics and preferences of each country. Some or all of the above processing in the country-specific suggestion section may be performed using AI, or not. For example, the country-specific suggestion section can input traveler data from each country into a generating AI and have the generating AI propose the most suitable tours.

[0037] The data collection unit can collect detailed information such as the skills and dedication of artisans and the historical background. For example, the data collection unit can collect information on the types and procedures of artisans' skills. For example, the data collection unit can collect details of artisans' production processes and the tools they use. The data collection unit can also collect information on artisans' dedication and commitment to production. For example, the data collection unit can collect information on the criteria for selecting materials used by artisans and methods of quality control. For example, the data collection unit can collect information on the historical background of artisanal skills and the development process of those skills. For example, the data collection unit can collect information on how artisanal skills relate to the history and culture of the region. This makes it easier to pass on artisanal skills by collecting detailed information such as the skills, dedication, and historical background of artisans. Some or all of the above processing in the data collection unit may be performed using AI, for example, or not using AI. For example, the data collection unit can input information on artisans' skills and dedication into a generating AI and have the generating AI perform the collection of detailed information.

[0038] The analysis department can understand the experiences that foreign travelers desire based on the collected information. For example, the analysis department can analyze the collected information to understand what kind of experiences travelers are looking for. For example, the analysis department can understand popular activities and expected services based on travelers' interests and preferences. The analysis department can also analyze travelers' past feedback and ratings based on the collected information. For example, the analysis department can understand individual needs based on travelers' profile information. This allows for the proposal of more appropriate experiential tours by understanding the experiences that foreign travelers desire. Some or all of the above processing in the analysis department may be performed using AI, for example, or not using AI. For example, the analysis department can input the collected information into a generating AI and have the generating AI perform an analysis of travelers' needs.

[0039] The suggestion unit can propose experiential tours best suited to travelers from each country. For example, the suggestion unit can propose experiential tours best suited to travelers from each country based on collected information. For example, the suggestion unit can propose tours that include traditional craft experiences or introductions to local culture to travelers from a specific country. The suggestion unit can also propose customized tours tailored to the needs of travelers. For example, the suggestion unit can propose tours that allow travelers to experience specific technologies or cultures based on their interests. This improves the satisfaction of foreign travelers by proposing experiential tours best suited to travelers from each country. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or not using AI. For example, the suggestion unit can input collected information into a generating AI and have the generating AI produce optimal tour suggestions.

[0040] The Commercialization Department can commercialize the proposed content as a tourism business. For example, the Commercialization Department can develop a plan for actually operating the proposed experiential tour. For example, the Commercialization Department can secure resources to realize the proposed tour by collaborating with local organizations and tourism businesses. The Commercialization Department can also market and promote the proposed tour. For example, the Commercialization Department can build a revenue model for the proposed tour and develop a plan for operating it as a sustainable business. In this way, commercializing the proposed content as a tourism business makes it possible to pass on craftsmanship and develop the tourism industry. Some or all of the above processes in the Commercialization Department may be performed using AI, for example, or not using AI. For example, the Commercialization Department can input the proposed tour plan into a generating AI and have the generating AI execute the tourism commercialization plan.

[0041] The data collection unit can analyze an artisan's past works and activity history to select the most suitable information collection method. For example, the data collection unit can analyze an artisan's past works and prioritize the collection of information related to specific techniques. For example, the data collection unit can select the most effective interview method based on an artisan's activity history. The data collection unit can also collect relevant material information by referring to an artisan's past projects. This allows the system to select the most suitable information collection method by analyzing an artisan's past works and activity history. Some or all of the above processes in the data collection unit may be performed using AI, for example, or not. For example, the data collection unit can input an artisan's past works and activity history into a generating AI and have the generating AI select the most suitable information collection method.

[0042] The data collection unit can filter information based on the craftsman's current projects and areas of interest during the information gathering process. For example, the data collection unit can prioritize collecting information related to the craftsman's current projects. For example, the data collection unit can filter relevant technical information based on the craftsman's areas of interest. The data collection unit can also collect material information related to the craftsman's current activities. This allows for the collection of more relevant information by filtering information based on the craftsman's current projects and areas of interest. Some or all of the above processing in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input information about the craftsman's current projects and areas of interest into a generating AI and have the generating AI perform the information filtering.

[0043] The data collection unit can prioritize the collection of highly relevant information by considering the geographical location of the craftsman during information gathering. For example, the data collection unit can prioritize the collection of information related to the area where the craftsman lives. For example, the data collection unit can collect nearby material information based on the location of the craftsman's workshop. The data collection unit can also prioritize the collection of information related to the craftsman's activity range. By considering the geographical location of the craftsman when collecting information, more relevant information can be collected. Some or all of the above processing in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input the geographical location of the craftsman into a generating AI and have the generating AI perform the collection of highly relevant information.

[0044] The data collection unit can analyze the social media activities of artisans and collect relevant information during the information gathering process. For example, the data collection unit can collect relevant technical information based on information shared by artisans on social media. For example, the data collection unit can collect information on materials of interest from the artisans' social media activities. The data collection unit can also analyze comments from the artisans' followers and collect relevant information. This allows for the effective collection of relevant information by analyzing the artisans' social media activities. Some or all of the above-described processes in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input data on the artisans' social media activities into a generating AI and have the generating AI collect relevant information.

[0045] The analysis unit can adjust the level of detail of the analysis based on the importance of the collected information. For example, the analysis unit can perform a detailed analysis on important information, and a concise analysis on general information. Furthermore, the analysis unit can perform an analysis tailored to the progress of a specific project. By adjusting the level of detail based on the importance of the collected information, more effective analysis becomes possible. Some or all of the above processes in the analysis unit may be performed using AI, or not. For example, the analysis unit can input the importance of the collected information into a generating AI and have the generating AI adjust the level of detail of the analysis.

[0046] The analysis unit can apply different analysis algorithms depending on the category of information during analysis. For example, the analysis unit can apply a technical analysis algorithm to technical information. For example, the analysis unit can apply an analysis algorithm based on material properties to material information. Furthermore, the analysis unit can apply a historical analysis algorithm to historical background information. By applying different analysis algorithms depending on the category of information, more accurate analysis becomes possible. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the category of information into a generating AI and have the generating AI execute the application of different analysis algorithms.

[0047] The analysis unit can determine the priority of analysis based on when the information was collected. For example, the analysis unit can prioritize the analysis of the latest information. For example, it can analyze past information as needed. Furthermore, for information related to a specific project, the analysis unit can perform analysis according to the progress of the project. This allows for more effective analysis by determining the priority of analysis based on when the information was collected. Some or all of the above processes in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the information collection timing into a generating AI and have the generating AI determine the analysis priority.

[0048] The analysis unit can adjust the order of analysis based on the relevance of the information during the analysis process. For example, the analysis unit can prioritize the analysis of important information. For example, it can postpone the analysis of general information. Furthermore, the analysis unit can analyze information related to a specific project according to the project's progress. By adjusting the order of analysis based on the relevance of the information, more effective analysis becomes possible. Some or all of the above processes in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the relevance of the information into a generating AI and have the generating AI adjust the order of analysis.

[0049] The proposal unit can adjust the level of detail in its proposals based on the importance of the experiential tours. For example, it can provide detailed proposals for important experiential tours, and concise proposals for general experiential tours. It can also provide proposals tailored to the importance of specific countries for travelers from those countries. By adjusting the level of detail in proposals based on the importance of the experiential tours, more effective proposals can be made. Some or all of the above processing in the proposal unit may be performed using AI, for example, or without AI. For example, the proposal unit can input the importance of the experiential tours into a generating AI and have the generating AI adjust the level of detail in the proposals.

[0050] The proposal unit can apply different proposal algorithms depending on the category of the experiential tour during the proposal process. For example, the proposal unit can apply a cultural proposal algorithm to a cultural experiential tour. For example, the proposal unit can apply a technical proposal algorithm to a technology experiential tour. Furthermore, the proposal unit can apply a historical proposal algorithm to a historical experiential tour. By applying different proposal algorithms depending on the category of the experiential tour, more effective proposals can be made. Some or all of the above processing in the proposal unit may be performed using AI, for example, or without AI. For example, the proposal unit can input the category of the experiential tour into a generating AI and have the generating AI execute the application of different proposal algorithms.

[0051] The proposal department can determine the priority of proposals based on the submission timing of the experiential tours. For example, the proposal department will prioritize proposals for the most recent experiential tours. For example, it can make proposals for past experiential tours as needed. Furthermore, the proposal department can make proposals tailored to the submission timing of travelers from specific countries. This allows for more effective proposals by prioritizing proposals based on the submission timing of the experiential tours. Some or all of the above processing in the proposal department may be performed using AI, for example, or not. For example, the proposal department can input the submission timing of the experiential tours into a generating AI and have the generating AI determine the priority of proposals.

[0052] The suggestion unit can adjust the order of suggestions based on the relevance of the experiential tours. For example, it can prioritize suggesting important experiential tours, while delaying suggesting general experiential tours. Furthermore, it can provide country-specific suggestions to travelers from specific countries. This allows for more effective suggestions by adjusting the order of suggestions based on the relevance of the experiential tours. Some or all of the above processing in the suggestion unit may be performed using AI, or not. For example, the suggestion unit can input the relevance of the experiential tours into a generating AI and have the generating AI adjust the order of suggestions.

[0053] The commercialization department can analyze the craftsman's past commercialization history to select the optimal commercialization method at the time of commercialization. For example, the commercialization department can select the most successful method based on the craftsman's past commercialization history. For example, the commercialization department can avoid failed methods based on the craftsman's past commercialization history. The commercialization department can also analyze the craftsman's past commercialization history to select the most effective method. In this way, the optimal commercialization method can be selected by analyzing the craftsman's past commercialization history. Some or all of the above processes in the commercialization department may be performed using AI, for example, or not using AI. For example, the commercialization department can input the craftsman's past commercialization history into a generating AI and have the generating AI perform the selection of the optimal commercialization method.

[0054] The commercialization department can customize the means of commercialization based on the craftsman's current living situation. For example, if the craftsman is busy, the commercialization department can propose a simple and efficient commercialization method. For example, if the craftsman has ample time, the commercialization department can propose a detailed commercialization method. The commercialization department can also provide flexible commercialization methods according to the craftsman's living situation. This makes it possible to commercialize more effectively by customizing the means of commercialization based on the craftsman's current living situation. Some or all of the above processes in the commercialization department may be performed using AI, for example, or not using AI. For example, the commercialization department can input the craftsman's current living situation into a generating AI and have the generating AI perform the customization of the commercialization method.

[0055] The commercialization department can select the optimal commercialization method when commercializing a product, taking into account the geographical location information of the craftsman. For example, the commercialization department can select a commercialization method related to the area where the craftsman lives. For example, the commercialization department can select a commercialization method that targets nearby markets based on the location of the craftsman's workshop. The commercialization department can also select a commercialization method related to the craftsman's area of ​​activity. By selecting a commercialization method that takes into account the geographical location information of the craftsman, more effective commercialization becomes possible. Some or all of the above processes in the commercialization department may be performed using AI, for example, or not using AI. For example, the commercialization department can input the geographical location information of the craftsman into a generating AI and have the generating AI select the optimal commercialization method.

[0056] The commercialization department can analyze the social media activities of artisans and propose commercialization methods at the time of commercialization. For example, the commercialization department can propose relevant commercialization methods based on information shared by artisans on social media. For example, the commercialization department can propose commercialization methods targeting markets of interest based on the artisans' social media activities. The commercialization department can also analyze comments from artisans' followers and propose relevant commercialization methods. In this way, by analyzing the artisans' social media activities, relevant commercialization methods can be effectively proposed. Some or all of the above processes in the commercialization department may be performed using AI, for example, or not using AI. For example, the commercialization department can input data on artisans' social media activities into a generating AI and have the generating AI execute the proposal of commercialization methods.

[0057] The SNS data collection unit can analyze the past SNS posting history of foreign tourists and select the optimal collection method. For example, the SNS data collection unit can prioritize collecting relevant data based on the past SNS posting history of foreign tourists. For example, the SNS data collection unit can select the most effective collection method from the posting history of foreign tourists. The SNS data collection unit can also analyze the past posting history of foreign tourists and collect the most relevant data. This allows for the selection of the optimal collection method by analyzing the past SNS posting history of foreign tourists. Some or all of the above processing in the SNS data collection unit may be performed using AI, for example, or without AI. For example, the SNS data collection unit can input the past SNS posting history of foreign tourists into a generating AI and have the generating AI select the optimal collection method.

[0058] The SNS data collection unit can prioritize the collection of highly relevant data by considering the geographical location information of foreign tourists when collecting SNS data. For example, the SNS data collection unit can prioritize the collection of data related to the area that the foreign tourist is visiting. For example, the SNS data collection unit can collect data on nearby tourist spots based on the foreign tourist's location information. The SNS data collection unit can also prioritize the collection of data related to the foreign tourist's activity range. By collecting data while considering the geographical location information of foreign tourists, more relevant data can be collected. Some or all of the above processing in the SNS data collection unit may be performed using AI, for example, or without AI. For example, the SNS data collection unit can input the geographical location information of foreign tourists into a generating AI and have the generating AI perform the collection of highly relevant data.

[0059] The needs analysis unit can adjust the level of detail of its analysis based on the importance of the collected social media data during the needs analysis process. For example, the needs analysis unit can perform a detailed analysis on important social media data, and a concise analysis on general social media data. Furthermore, the needs analysis unit can perform country-specific importance analyses on social media data related to travelers from specific countries. This allows for more effective needs analysis by adjusting the level of detail based on the importance of the collected social media data. Some or all of the above-described processes in the needs analysis unit may be performed using AI, or not. For example, the needs analysis unit can input the importance of the collected social media data into a generating AI and have the generating AI adjust the level of detail of the analysis.

[0060] The Needs Analysis Department can determine the priority of analysis based on the timing of SNS data collection during the needs analysis process. For example, the Needs Analysis Department can prioritize the analysis of the most recent SNS data. For example, it can analyze past SNS data as needed. Furthermore, the Needs Analysis Department can perform country-specific analysis of SNS data related to travelers from a particular country, according to the collection timing of that country. This allows for more effective needs analysis by determining the priority of analysis based on the timing of SNS data collection. Some or all of the above processes in the Needs Analysis Department may be performed using AI, for example, or without AI. For example, the Needs Analysis Department can input the timing of SNS data collection into a generating AI and have the generating AI determine the priority of analysis.

[0061] The country-specific proposal unit can adjust the level of detail of its proposals based on the importance of travelers in each country. For example, it can provide detailed proposals to travelers in important countries, and concise proposals to travelers in general countries. It can also provide proposals tailored to the importance of specific countries for travelers in particular countries. By adjusting the level of detail of proposals based on the importance of travelers in each country, more effective proposals can be made. Some or all of the above processing in the country-specific proposal unit may be performed using AI, for example, or not. For example, the country-specific proposal unit can input the importance of travelers in each country into a generating AI and have the generating AI adjust the level of detail of the proposals.

[0062] The country-specific proposal department can determine the priority of proposals based on the submission timing of travelers in each country when submitting proposals. For example, the country-specific proposal department will prioritize proposals to travelers from countries that have recently submitted proposals. For example, the country-specific proposal department can make proposals to travelers from countries that have previously submitted proposals as needed. Furthermore, the country-specific proposal department can make proposals to travelers from specific countries according to their country-specific submission timing. This allows for more effective proposals by determining the priority of proposals based on the submission timing of travelers in each country. Some or all of the above processing in the country-specific proposal department may be performed using AI, for example, or not. For example, the country-specific proposal department can input the submission timing of travelers in each country into a generating AI and have the generating AI determine the priority of proposals.

[0063] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0064] The system can also include a digital archive that preserves the skills of artisans as a digital archive. This digital archive can, for example, record artisans' skills using 3D scans or high-resolution video and save them as digital data. Furthermore, it can recreate artisans' skills using VR or AR technology, passing them on to future generations. The digital archive can also publish artisans' skills on an online platform, making them accessible to people worldwide. This makes it easier to pass on and widely disseminate artisans' skills by preserving them as a digital archive.

[0065] The system can also include an evaluation unit that assesses the skills of craftsmen. This unit, for example, uses experts or AI to evaluate a craftsman's skills and quantifies their level. It can also compare a craftsman's skills to those of other craftsmen to assess their relative strengths and weaknesses. Furthermore, the evaluation unit can periodically assess the craftsman's progress and support skill improvement. This allows for the promotion of skill improvement and increased motivation among craftsmen by evaluating their abilities.

[0066] The system could also include an education department for learning craftsmanship. This department could, for example, offer online courses for learning craftsmanship. It could also, for example, organize workshops and seminars for learning craftsmanship. Furthermore, it could create and provide educational materials and guidebooks for learning craftsmanship. This would facilitate the transmission of skills and cultivate the next generation of craftsmen by providing educational opportunities for learning craftsmanship.

[0067] The system can also include a promotion department to spread awareness of the artisans' skills. This department could, for example, operate websites or social media accounts showcasing the artisans' techniques. It could also produce and publish videos or documentaries introducing the artisans' skills. Furthermore, the promotion department could organize events and exhibitions to showcase the artisans' skills. Through these promotional activities, awareness of the artisans' skills can be increased, and demand can be stimulated.

[0068] The system can also include an intellectual property department to protect the skills of artisans. This department can, for example, register and protect artisans' skills as patents or trademarks. It can also take legal action to protect artisans' skills from imitation and misuse. Furthermore, the intellectual property department can offer artisans' skills under licensing agreements and generate revenue. This allows for intellectual property management to protect artisans' skills, preventing misuse and safeguarding their rights.

[0069] The following briefly describes the processing flow for example form 1.

[0070] Step 1: The collection team gathers detailed information and material information from the target craftsmen. For example, they can collect information such as the craftsmen's skills and dedication, historical background, procedures for specific techniques, characteristics of the materials used, scenes of the craftsmen at work and the production process, and interviews about how techniques are passed down and their commitment to production. Step 2: The analysis department analyzes the information collected by the collection department. For example, they can analyze the characteristics and technical details of craftsmanship, historical background and cultural significance, preservation and transmission methods, market value and demand, etc. Step 3: The proposal department proposes experiential tours based on the analysis results obtained by the analysis department. For example, they can propose experiential tours best suited to travelers from each country, tours that include traditional craft experiences and introductions to local culture for travelers from specific countries, customized tours tailored to travelers' needs, and tours that allow travelers to experience specific technologies or cultures based on their interests. Step 4: The Commercialization Department will commercialize the ideas proposed by the Proposal Department into tourism businesses. For example, they can develop a plan to actually operate the proposed experiential tour, secure resources in cooperation with local organizations and tourism businesses, market and promote the tour, and develop a plan to build a revenue model and operate it as a sustainable business.

[0071] (Example of form 2) The system according to an embodiment of the present invention is a system for sustainably passing down Japanese craftsmanship that has been inherited for over 100 years. This system collects detailed information and material information from target craftsmen and uses it to train an AI. Next, it analyzes the needs of foreign visitors to Japan through social media and other means, extracts priority tour elements, and creates a database. Furthermore, an AI agent proposes experiential tours tailored to the national characteristics and preferences of each country to local organizations, which are then used to develop tourism businesses. This system enables the commercialization of the passion of the craftsmen and the historical stories behind them for inbound tourism, ensuring stable income for the craftsmen and preserving cultural heritage. In addition, foreign tourists visiting Japan can have valuable experiences that they cannot learn about online, and repeat visits are expected. For example, it collects detailed information and material information from target craftsmen. In this process, detailed information such as the craftsman's techniques, commitment, and historical background is collected and used to train the AI. For example, by training the AI ​​on the procedures of specific techniques and the characteristics of the materials used, detailed information on craftsmanship is created in a database. Next, it analyzes the needs of foreign visitors to Japan through social media and other means. AI analyzes posts and comments on social media to understand what experiences foreign tourists are seeking. For example, it extracts needs such as "experiencing Japanese culture" or "walking through ancient cities and historical towns" and creates a database of priority tour elements. Furthermore, the AI ​​agent proposes experiential tours tailored to the national characteristics and preferences of each country to local organizations. Based on the collected information, the AI ​​agent proposes the most suitable experiential tours for tourists from each country. For example, it might propose tours that include traditional craft experiences and introductions to local culture to tourists from a specific country. These proposals are then used in collaboration with local organizations to develop tourism businesses. This system enables the business development of cultural heritage by commercializing the passion of those involved and the historical stories behind them for inbound tourism, ensuring stable income for those involved and preserving cultural heritage. In addition, foreign tourists visiting Japan can have valuable experiences that they cannot learn about online, which is likely to encourage repeat visits. For example, foreign tourists who experience traditional Japanese crafts and are impressed by the techniques and history are likely to return. In this way, the system can simultaneously achieve the transmission of craftsmanship and the development of the tourism industry.

[0072] The system according to this embodiment comprises a collection unit, an analysis unit, a proposal unit, and a commercialization unit. The collection unit collects detailed information and material information from the target craftsman. For example, the collection unit collects detailed information such as the craftsman's skills, commitment, and historical background. For example, the collection unit can collect information such as the procedures for specific techniques and the characteristics of the materials used. The collection unit can also record the craftsman's work scene and production process. For example, the collection unit can conduct interviews with craftsmen to collect information on how to pass on their skills and their commitment to production. The analysis unit analyzes the information collected by the collection unit. For example, the analysis unit analyzes the characteristics and technical details of the craftsman's skills based on the collected information. For example, the analysis unit can analyze the historical background and cultural significance of the craftsman's skills based on the collected information. For example, the analysis unit can propose methods for preserving and passing on the craftsman's skills based on the collected information. For example, the analysis unit can analyze the market value and demand for the craftsman's skills based on the collected information. The proposal unit proposes an experiential tour based on the analysis results obtained by the analysis unit. The proposal department, for example, proposes experiential tours best suited to travelers from various countries. For example, the proposal department can propose tours that include traditional craft experiences and introductions to local culture to travelers from a specific country. The proposal department can also propose customized tours tailored to travelers' needs based on the collected information. For example, the proposal department can propose tours that allow travelers to experience specific technologies or cultures based on their interests. The commercialization department turns the proposals made by the proposal department into tourism businesses. For example, the commercialization department develops plans for actually operating the proposed experiential tours. For example, the commercialization department can secure resources to realize the proposed tours by collaborating with local organizations and tourism businesses. The commercialization department can also market and promote the proposed tours. For example, the commercialization department can build a revenue model for the proposed tours and develop plans for operating them as sustainable businesses. In this way, the system according to the embodiment can collect and analyze detailed information on craftsmanship, propose experiential tours, and commercialize them into tourism businesses, thereby enabling the transmission of craftsmanship and the development of the tourism industry.

[0073] The data collection department gathers detailed information and material information from the target craftsmen. For example, the department collects detailed information such as the craftsmen's techniques, their commitment to their craft, and their historical background. Specifically, it records in detail what kind of techniques the craftsmen possess, how those techniques have developed, and the craftsmen's thoughts and commitment to those techniques. The data collection department can collect information such as the procedures for specific techniques and the characteristics of the materials used. This includes the criteria for selecting the tools and materials used by the craftsmen, as well as the ingenuity and precautions taken during the production process. The data collection department can also record the craftsmen at work and the production process. This allows for a visual understanding of how the craftsmen's techniques are put into practice. The data collection department can also conduct interviews with craftsmen to collect information on how their techniques are passed down and their commitment to their craft. In the interviews, they will ask in detail how the craftsmen learned their techniques, how they pass them on to the next generation, and about the difficulties and successes they have experienced in that process. This allows the data collection department to grasp the overall picture of the craftsmanship and collect detailed information. Furthermore, the data collection department digitizes this information and stores it in a database so that it can be used for later analysis and proposals. The collection department is required to build trusting relationships with craftsmen while continuously collecting and updating information. This allows the collection department to contribute to the preservation and transmission of craftsmanship and play a crucial role in supporting the foundation of the entire system.

[0074] The Analysis Department analyzes the information collected by the Data Collection Department. For example, the Analysis Department analyzes the characteristics and technical details of craftsmanship based on the collected information. Specifically, it classifies the collected technical information and clarifies the characteristics and uniqueness of each technique. For example, the Analysis Department can analyze the historical background and cultural significance of craftsmanship based on the collected information. This includes investigating the historical process by which the technique has developed and the impact it has had on the region and culture. The Analysis Department can also propose methods for preserving and passing on craftsmanship based on the collected information. For example, this could include digital archiving of the technique or designing training programs for the next generation of craftsmen. The Analysis Department can also analyze the market value and demand for craftsmanship based on the collected information. This includes analyzing current market trends and consumer preferences to clarify how craftsmanship is valued and what kind of demand exists. Furthermore, the Analysis Department can use AI to analyze the collected data and extract patterns and trends. For example, it can use natural language processing technology to analyze interview content and extract common themes and important keywords. Furthermore, by using image recognition technology to analyze video footage of the work process, the system can automatically identify the characteristics of the techniques and the work procedures. This allows the analysis department to analyze the collected information from multiple perspectives and make concrete proposals for the preservation and transmission of traditional craftsmanship.

[0075] The Proposal Department proposes experiential tours based on the analysis results obtained by the Analysis Department. For example, the Proposal Department proposes experiential tours that are best suited to travelers from each country. Specifically, they design tours that allow travelers to experience artisanal skills based on their interests. For example, the Proposal Department can propose tours to travelers from a particular country that include experiences of traditional crafts and introductions to local culture. This could include workshops where travelers visit artisans' studios and experience the techniques firsthand, or guided tours that teach about local history and culture. The Proposal Department can also propose customized tours tailored to travelers' needs based on the collected information. For example, they can offer an experiential program specializing in a particular technique for travelers interested in that technique. They can also propose programs that allow families and groups to experience multiple techniques. The Proposal Department can also propose tours that allow travelers to experience specific techniques or cultures based on their interests. This could include opportunities to interact with artisans and observe demonstrations of their techniques. Furthermore, the Proposal Department can collect traveler feedback and use it to improve the tour content. For example, they can review the program content and operation methods based on tour participants' satisfaction and opinions to provide a more attractive experience. Furthermore, the proposal department can utilize the digital platform to handle tour bookings and provide information. This allows the proposal department to offer attractive experiential tours to travelers, contributing to the dissemination of traditional craftsmanship and the development of the tourism industry.

[0076] The Commercialization Department is responsible for commercializing the ideas proposed by the Proposal Department. For example, the Commercialization Department develops plans for actually operating the proposed experiential tours. Specifically, this involves designing the tour schedule and content in detail and securing the necessary resources for operation. The Commercialization Department can, for example, collaborate with local organizations and tourism businesses to secure the resources needed to realize the proposed tours. This includes arranging artisans and guides, securing tour locations, and preparing necessary equipment and materials. The Commercialization Department can also market and promote the proposed tours. For example, it can utilize digital marketing to promote the tour's appeal through social media and websites to attract travelers. It can also partner with travel agencies and tourism information websites to promote tour sales. The Commercialization Department can, for example, develop a revenue model for the proposed tours and develop plans for operating it as a sustainable business. This includes pricing, cost management, and revenue distribution methods. Furthermore, the Commercialization Department is required to monitor the tour's operation and continuously strive for improvement. For example, based on participant feedback, the tour content and operation methods can be reviewed to provide a better experience. Furthermore, the business development department can utilize local tourism resources and contribute to the revitalization of the local economy. In this way, the business development department can realize proposed tours and operate them as sustainable tourism businesses, thereby contributing to the preservation of traditional craftsmanship and the development of the tourism industry.

[0077] The system includes an SNS collection unit that collects SNS data. The SNS collection unit collects posts and comments on SNS, for example. The SNS collection unit can also collect posts related to specific hashtags or keywords, for example. Furthermore, the SNS collection unit can analyze the collected data to understand the needs of foreign tourists. The SNS collection unit can also collect trends and popular posts on SNS and analyze the interests of tourists, for example. The SNS collection unit can also collect images and videos on SNS and analyze the visual information, for example. This makes it easier to understand the needs of foreign tourists by collecting SNS data. Some or all of the above processing in the SNS collection unit may be performed using AI, for example, or without AI. For example, the SNS collection unit can input posts and comments on SNS into a generating AI and have the generating AI perform the collection of related data.

[0078] The system includes a needs analysis unit that analyzes the needs of foreign travelers. The needs analysis unit analyzes the needs of foreign travelers, for example, based on collected social media data. The needs analysis unit can, for example, understand travelers' interests and concerns and analyze what kind of experiences they are seeking. The needs analysis unit can also analyze the services and activities that travelers expect, based on the collected data. The needs analysis unit can also understand needs, for example, based on travelers' past travel history and feedback. The needs analysis unit can also analyze individual needs, for example, based on travelers' profile information. By analyzing the needs of foreign travelers, it is possible to propose more appropriate experiential tours. Some or all of the above processing in the needs analysis unit may be performed using AI, for example, or without AI. For example, the needs analysis unit can input collected social media data into a generating AI and have the generating AI perform the analysis of travelers' needs.

[0079] The system includes a country-specific suggestion section that proposes tours tailored to the national characteristics and preferences of each country. This section analyzes, for example, the cultural background and general preferences of travelers in each country. It can also identify preferred activities and food preferences for travelers from a particular country. Furthermore, based on the collected data, the section can propose the most suitable experiential tours for travelers in each country. For example, it can propose tours to travelers from a specific country that include experiences of traditional crafts or introductions to local culture. The section can also propose customized tours based on travelers' country-specific travel trends and interests. This improves the satisfaction of foreign travelers by proposing tours tailored to the national characteristics and preferences of each country. Some or all of the above processing in the country-specific suggestion section may be performed using AI, or not. For example, the country-specific suggestion section can input traveler data from each country into a generating AI and have the generating AI propose the most suitable tours.

[0080] The data collection unit can collect detailed information such as the skills and dedication of artisans and the historical background. For example, the data collection unit can collect information on the types and procedures of artisans' skills. For example, the data collection unit can collect details of artisans' production processes and the tools they use. The data collection unit can also collect information on artisans' dedication and commitment to production. For example, the data collection unit can collect information on the criteria for selecting materials used by artisans and methods of quality control. For example, the data collection unit can collect information on the historical background of artisanal skills and the development process of those skills. For example, the data collection unit can collect information on how artisanal skills relate to the history and culture of the region. This makes it easier to pass on artisanal skills by collecting detailed information such as the skills, dedication, and historical background of artisans. Some or all of the above processing in the data collection unit may be performed using AI, for example, or not using AI. For example, the data collection unit can input information on artisans' skills and dedication into a generating AI and have the generating AI perform the collection of detailed information.

[0081] The analysis department can understand the experiences that foreign travelers desire based on the collected information. For example, the analysis department can analyze the collected information to understand what kind of experiences travelers are looking for. For example, the analysis department can understand popular activities and expected services based on travelers' interests and preferences. The analysis department can also analyze travelers' past feedback and ratings based on the collected information. For example, the analysis department can understand individual needs based on travelers' profile information. This allows for the proposal of more appropriate experiential tours by understanding the experiences that foreign travelers desire. Some or all of the above processing in the analysis department may be performed using AI, for example, or not using AI. For example, the analysis department can input the collected information into a generating AI and have the generating AI perform an analysis of travelers' needs.

[0082] The suggestion unit can propose experiential tours best suited to travelers from each country. For example, the suggestion unit can propose experiential tours best suited to travelers from each country based on collected information. For example, the suggestion unit can propose tours that include traditional craft experiences or introductions to local culture to travelers from a specific country. The suggestion unit can also propose customized tours tailored to the needs of travelers. For example, the suggestion unit can propose tours that allow travelers to experience specific technologies or cultures based on their interests. This improves the satisfaction of foreign travelers by proposing experiential tours best suited to travelers from each country. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or not using AI. For example, the suggestion unit can input collected information into a generating AI and have the generating AI produce optimal tour suggestions.

[0083] The Commercialization Department can commercialize the proposed content as a tourism business. For example, the Commercialization Department can develop a plan for actually operating the proposed experiential tour. For example, the Commercialization Department can secure resources to realize the proposed tour by collaborating with local organizations and tourism businesses. The Commercialization Department can also market and promote the proposed tour. For example, the Commercialization Department can build a revenue model for the proposed tour and develop a plan for operating it as a sustainable business. In this way, commercializing the proposed content as a tourism business makes it possible to pass on craftsmanship and develop the tourism industry. Some or all of the above processes in the Commercialization Department may be performed using AI, for example, or not using AI. For example, the Commercialization Department can input the proposed tour plan into a generating AI and have the generating AI execute the tourism commercialization plan.

[0084] The data collection unit can estimate the emotions of the craftsman and adjust the timing of information collection based on the estimated emotions. For example, the data collection unit can avoid collecting information during times when the craftsman is concentrating. For example, the data collection unit can collect information during times when the craftsman is relaxed. Furthermore, the data collection unit can collect information during periods when the craftsman is emotionally stable. By adjusting the timing of information collection based on the craftsman's emotions, more effective information collection becomes possible. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input the craftsman's emotion data into the generative AI and have the generative AI adjust the timing of information collection.

[0085] The data collection unit can analyze an artisan's past works and activity history to select the most suitable information collection method. For example, the data collection unit can analyze an artisan's past works and prioritize the collection of information related to specific techniques. For example, the data collection unit can select the most effective interview method based on an artisan's activity history. The data collection unit can also collect relevant material information by referring to an artisan's past projects. This allows the system to select the most suitable information collection method by analyzing an artisan's past works and activity history. Some or all of the above processes in the data collection unit may be performed using AI, for example, or not. For example, the data collection unit can input an artisan's past works and activity history into a generating AI and have the generating AI select the most suitable information collection method.

[0086] The data collection unit can filter information based on the craftsman's current projects and areas of interest during the information gathering process. For example, the data collection unit can prioritize collecting information related to the craftsman's current projects. For example, the data collection unit can filter relevant technical information based on the craftsman's areas of interest. The data collection unit can also collect material information related to the craftsman's current activities. This allows for the collection of more relevant information by filtering information based on the craftsman's current projects and areas of interest. Some or all of the above processing in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input information about the craftsman's current projects and areas of interest into a generating AI and have the generating AI perform the information filtering.

[0087] The data collection unit can estimate the emotions of the craftsman and determine the priority of information to collect based on the estimated emotions. For example, if the craftsman is stressed, the data collection unit will prioritize collecting important information. For example, if the craftsman is relaxed, the data collection unit can collect detailed information. Furthermore, if the craftsman is emotionally stable, the data collection unit can also collect a wide range of information. This allows for more effective information collection by prioritizing information based on the craftsman's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the data collection unit may be performed using AI, for example, or not using AI. For example, the data collection unit can input the craftsman's emotion data into a generative AI and have the generative AI determine the priority of information.

[0088] The data collection unit can prioritize the collection of highly relevant information by considering the geographical location of the craftsman during information gathering. For example, the data collection unit can prioritize the collection of information related to the area where the craftsman lives. For example, the data collection unit can collect nearby material information based on the location of the craftsman's workshop. The data collection unit can also prioritize the collection of information related to the craftsman's activity range. By considering the geographical location of the craftsman when collecting information, more relevant information can be collected. Some or all of the above processing in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input the geographical location of the craftsman into a generating AI and have the generating AI perform the collection of highly relevant information.

[0089] The data collection unit can analyze the social media activities of artisans and collect relevant information during the information gathering process. For example, the data collection unit can collect relevant technical information based on information shared by artisans on social media. For example, the data collection unit can collect information on materials of interest from the artisans' social media activities. The data collection unit can also analyze comments from the artisans' followers and collect relevant information. This allows for the effective collection of relevant information by analyzing the artisans' social media activities. Some or all of the above-described processes in the data collection unit may be performed using AI, for example, or without AI. For example, the data collection unit can input data on the artisans' social media activities into a generating AI and have the generating AI collect relevant information.

[0090] The analysis unit can estimate the emotions of the craftsman and adjust the presentation of the analysis based on the estimated emotions. For example, if the craftsman is relaxed, the analysis unit can provide detailed analysis results. For example, if the craftsman is stressed, the analysis unit can provide concise analysis results. Furthermore, if the craftsman is emotionally stable, the analysis unit can provide visually easy-to-understand analysis results. In this way, by adjusting the presentation of the analysis based on the emotions of the craftsman, more effective analysis results can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the analysis unit may be performed using AI, for example, or not using AI. For example, the analysis unit can input the craftsman's emotion data into the generative AI and have the generative AI adjust the presentation of the analysis.

[0091] The analysis unit can adjust the level of detail of the analysis based on the importance of the collected information. For example, the analysis unit can perform a detailed analysis on important information, and a concise analysis on general information. Furthermore, the analysis unit can perform an analysis tailored to the progress of a specific project. By adjusting the level of detail based on the importance of the collected information, more effective analysis becomes possible. Some or all of the above processes in the analysis unit may be performed using AI, or not. For example, the analysis unit can input the importance of the collected information into a generating AI and have the generating AI adjust the level of detail of the analysis.

[0092] The analysis unit can apply different analysis algorithms depending on the category of information during analysis. For example, the analysis unit can apply a technical analysis algorithm to technical information. For example, the analysis unit can apply an analysis algorithm based on material properties to material information. Furthermore, the analysis unit can apply a historical analysis algorithm to historical background information. By applying different analysis algorithms depending on the category of information, more accurate analysis becomes possible. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the category of information into a generating AI and have the generating AI execute the application of different analysis algorithms.

[0093] The analysis unit can estimate the emotions of the craftsman and adjust the length of the analysis based on the estimated emotions. For example, if the craftsman is relaxed, the analysis unit can provide a detailed analysis. For example, if the craftsman is stressed, the analysis unit can provide a concise analysis. Furthermore, if the craftsman is emotionally stable, the analysis unit can provide a visually easy-to-understand analysis. By adjusting the length of the analysis based on the craftsman's emotions, more effective analysis results can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the analysis unit may be performed using AI, for example, or not using AI. For example, the analysis unit can input the craftsman's emotion data into the generative AI and have the generative AI adjust the length of the analysis.

[0094] The analysis unit can determine the priority of analysis based on when the information was collected. For example, the analysis unit can prioritize the analysis of the latest information. For example, it can analyze past information as needed. Furthermore, for information related to a specific project, the analysis unit can perform analysis according to the progress of the project. This allows for more effective analysis by determining the priority of analysis based on when the information was collected. Some or all of the above processes in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the information collection timing into a generating AI and have the generating AI determine the analysis priority.

[0095] The analysis unit can adjust the order of analysis based on the relevance of the information during the analysis process. For example, the analysis unit can prioritize the analysis of important information. For example, it can postpone the analysis of general information. Furthermore, the analysis unit can analyze information related to a specific project according to the project's progress. By adjusting the order of analysis based on the relevance of the information, more effective analysis becomes possible. Some or all of the above processes in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the relevance of the information into a generating AI and have the generating AI adjust the order of analysis.

[0096] The proposal unit can estimate the craftsman's emotions and adjust the way the proposal is presented based on the estimated emotions. For example, if the craftsman is relaxed, the proposal unit can provide a detailed proposal. If the craftsman is stressed, the proposal unit can provide a concise proposal. Furthermore, if the craftsman is emotionally stable, the proposal unit can provide a visually easy-to-understand proposal. This allows for more effective proposals by adjusting the way the proposal is presented based on the craftsman's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the proposal unit may be performed using AI or not. For example, the proposal unit can input the craftsman's emotion data into the generative AI and have the generative AI adjust the way the proposal is presented.

[0097] The proposal unit can adjust the level of detail in its proposals based on the importance of the experiential tours. For example, it can provide detailed proposals for important experiential tours, and concise proposals for general experiential tours. It can also provide proposals tailored to the importance of specific countries for travelers from those countries. By adjusting the level of detail in proposals based on the importance of the experiential tours, more effective proposals can be made. Some or all of the above processing in the proposal unit may be performed using AI, for example, or without AI. For example, the proposal unit can input the importance of the experiential tours into a generating AI and have the generating AI adjust the level of detail in the proposals.

[0098] The proposal unit can apply different proposal algorithms depending on the category of the experiential tour during the proposal process. For example, the proposal unit can apply a cultural proposal algorithm to a cultural experiential tour. For example, the proposal unit can apply a technical proposal algorithm to a technology experiential tour. Furthermore, the proposal unit can apply a historical proposal algorithm to a historical experiential tour. By applying different proposal algorithms depending on the category of the experiential tour, more effective proposals can be made. Some or all of the above processing in the proposal unit may be performed using AI, for example, or without AI. For example, the proposal unit can input the category of the experiential tour into a generating AI and have the generating AI execute the application of different proposal algorithms.

[0099] The suggestion unit can estimate the craftsman's emotions and adjust the length of the suggestion based on the estimated emotions. For example, if the craftsman is relaxed, the suggestion unit can provide a detailed suggestion. If the craftsman is stressed, the suggestion unit can provide a concise suggestion. Furthermore, if the craftsman is emotionally stable, the suggestion unit can provide a visually easy-to-understand suggestion. By adjusting the length of the suggestion based on the craftsman's emotions, more effective suggestions become possible. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the suggestion unit may be performed using AI or not. For example, the suggestion unit can input the craftsman's emotion data into the generative AI and have the generative AI adjust the length of the suggestion.

[0100] The proposal department can determine the priority of proposals based on the submission timing of the experiential tours. For example, the proposal department will prioritize proposals for the most recent experiential tours. For example, it can make proposals for past experiential tours as needed. Furthermore, the proposal department can make proposals tailored to the submission timing of travelers from specific countries. This allows for more effective proposals by prioritizing proposals based on the submission timing of the experiential tours. Some or all of the above processing in the proposal department may be performed using AI, for example, or not. For example, the proposal department can input the submission timing of the experiential tours into a generating AI and have the generating AI determine the priority of proposals.

[0101] The suggestion unit can adjust the order of suggestions based on the relevance of the experiential tours. For example, it can prioritize suggesting important experiential tours, while delaying suggesting general experiential tours. Furthermore, it can provide country-specific suggestions to travelers from specific countries. This allows for more effective suggestions by adjusting the order of suggestions based on the relevance of the experiential tours. Some or all of the above processing in the suggestion unit may be performed using AI, or not. For example, the suggestion unit can input the relevance of the experiential tours into a generating AI and have the generating AI adjust the order of suggestions.

[0102] The commercialization department can estimate the emotions of craftsmen and adjust the commercialization method based on the estimated emotions of the craftsmen. For example, if the craftsman is relaxed, the commercialization department can provide a detailed commercialization plan. For example, if the craftsman is stressed, the commercialization department can provide a concise commercialization plan. Furthermore, if the craftsman is emotionally stable, the commercialization department can provide a visually easy-to-understand commercialization plan. This allows for more effective commercialization by adjusting the commercialization method based on the emotions of the craftsmen. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the commercialization department may be performed using AI, for example, or not using AI. For example, the commercialization department can input the craftsman's emotion data into a generative AI and have the generative AI perform the adjustment of the commercialization method.

[0103] The commercialization department can analyze the craftsman's past commercialization history to select the optimal commercialization method at the time of commercialization. For example, the commercialization department can select the most successful method based on the craftsman's past commercialization history. For example, the commercialization department can avoid failed methods based on the craftsman's past commercialization history. The commercialization department can also analyze the craftsman's past commercialization history to select the most effective method. In this way, the optimal commercialization method can be selected by analyzing the craftsman's past commercialization history. Some or all of the above processes in the commercialization department may be performed using AI, for example, or not using AI. For example, the commercialization department can input the craftsman's past commercialization history into a generating AI and have the generating AI perform the selection of the optimal commercialization method.

[0104] The commercialization department can customize the means of commercialization based on the craftsman's current living situation. For example, if the craftsman is busy, the commercialization department can propose a simple and efficient commercialization method. For example, if the craftsman has ample time, the commercialization department can propose a detailed commercialization method. The commercialization department can also provide flexible commercialization methods according to the craftsman's living situation. This makes it possible to commercialize more effectively by customizing the means of commercialization based on the craftsman's current living situation. Some or all of the above processes in the commercialization department may be performed using AI, for example, or not using AI. For example, the commercialization department can input the craftsman's current living situation into a generating AI and have the generating AI perform the customization of the commercialization method.

[0105] The commercialization department can estimate the emotions of craftsmen and determine the priority of commercialization based on the estimated emotions. For example, if a craftsman is relaxed, the commercialization department may prioritize important commercializations. If a craftsman is stressed, the commercialization department may prioritize simple commercializations. Furthermore, if a craftsman is emotionally stable, the commercialization department may prioritize broad commercializations. This allows for more effective commercialization by determining the priority of commercializations based on the emotions of the craftsmen. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the commercialization department may be performed using AI or not. For example, the commercialization department can input craftsman emotion data into a generative AI and have the generative AI determine the priority of commercializations.

[0106] The commercialization department can select the optimal commercialization method when commercializing a product, taking into account the geographical location information of the craftsman. For example, the commercialization department can select a commercialization method related to the area where the craftsman lives. For example, the commercialization department can select a commercialization method that targets nearby markets based on the location of the craftsman's workshop. The commercialization department can also select a commercialization method related to the craftsman's area of ​​activity. By selecting a commercialization method that takes into account the geographical location information of the craftsman, more effective commercialization becomes possible. Some or all of the above processes in the commercialization department may be performed using AI, for example, or not using AI. For example, the commercialization department can input the geographical location information of the craftsman into a generating AI and have the generating AI select the optimal commercialization method.

[0107] The commercialization department can analyze the social media activities of artisans and propose commercialization methods at the time of commercialization. For example, the commercialization department can propose relevant commercialization methods based on information shared by artisans on social media. For example, the commercialization department can propose commercialization methods targeting markets of interest based on the artisans' social media activities. The commercialization department can also analyze comments from artisans' followers and propose relevant commercialization methods. In this way, by analyzing the artisans' social media activities, relevant commercialization methods can be effectively proposed. Some or all of the above processes in the commercialization department may be performed using AI, for example, or not using AI. For example, the commercialization department can input data on artisans' social media activities into a generating AI and have the generating AI execute the proposal of commercialization methods.

[0108] The SNS data collection unit can estimate the emotions of foreign tourists and adjust the timing of SNS data collection based on the estimated emotions. For example, if a foreign tourist is excited, the SNS data collection unit can collect SNS data in real time. For example, if a foreign tourist is relaxed, the SNS data collection unit can collect detailed SNS data. Furthermore, if a foreign tourist is emotionally stable, the SNS data collection unit can collect a wide range of SNS data. This allows for more effective data collection by adjusting the timing of SNS data collection based on the emotions of foreign tourists. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the SNS data collection unit may be performed using AI, for example, or without AI. For example, the SNS data collection unit can input the emotions of foreign tourists into the generative AI and have the generative AI adjust the timing of SNS data collection.

[0109] The SNS data collection unit can analyze the past SNS posting history of foreign tourists and select the optimal collection method. For example, the SNS data collection unit can prioritize collecting relevant data based on the past SNS posting history of foreign tourists. For example, the SNS data collection unit can select the most effective collection method from the posting history of foreign tourists. The SNS data collection unit can also analyze the past posting history of foreign tourists and collect the most relevant data. This allows for the selection of the optimal collection method by analyzing the past SNS posting history of foreign tourists. Some or all of the above processing in the SNS data collection unit may be performed using AI, for example, or without AI. For example, the SNS data collection unit can input the past SNS posting history of foreign tourists into a generating AI and have the generating AI select the optimal collection method.

[0110] The SNS data collection unit can estimate the emotions of foreign tourists and determine the priority of SNS data to collect based on the estimated emotions. For example, if a foreign tourist is excited, the SNS data collection unit will prioritize collecting important data. For example, if a foreign tourist is relaxed, the SNS data collection unit can collect detailed data. Furthermore, if a foreign tourist is emotionally stable, the SNS data collection unit can collect a wide range of data. This allows for more effective data collection by prioritizing the SNS data to collect based on the emotions of foreign tourists. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the SNS data collection unit may be performed using AI, for example, or not using AI. For example, the SNS data collection unit can input foreign tourist emotion data into a generative AI and have the generative AI determine the priority of SNS data.

[0111] The SNS data collection unit can prioritize the collection of highly relevant data by considering the geographical location information of foreign tourists when collecting SNS data. For example, the SNS data collection unit can prioritize the collection of data related to the area that the foreign tourist is visiting. For example, the SNS data collection unit can collect data on nearby tourist spots based on the foreign tourist's location information. The SNS data collection unit can also prioritize the collection of data related to the foreign tourist's activity range. By collecting data while considering the geographical location information of foreign tourists, more relevant data can be collected. Some or all of the above processing in the SNS data collection unit may be performed using AI, for example, or without AI. For example, the SNS data collection unit can input the geographical location information of foreign tourists into a generating AI and have the generating AI perform the collection of highly relevant data.

[0112] The needs analysis unit can estimate the emotions of foreign tourists and adjust the presentation of the needs analysis based on the estimated emotions. For example, if a foreign tourist is excited, the needs analysis unit can provide a detailed needs analysis. For example, if a foreign tourist is relaxed, the needs analysis unit can provide a concise needs analysis. Furthermore, if a foreign tourist is emotionally stable, the needs analysis unit can provide a visually easy-to-understand needs analysis. This allows for more effective needs analysis by adjusting the presentation of the needs analysis based on the emotions of the foreign tourist. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the needs analysis unit may be performed using AI, for example, or not using AI. For example, the needs analysis unit can input the emotions of foreign tourists into the generative AI and have the generative AI adjust the presentation of the needs analysis.

[0113] The needs analysis unit can adjust the level of detail of its analysis based on the importance of the collected social media data during the needs analysis process. For example, the needs analysis unit can perform a detailed analysis on important social media data, and a concise analysis on general social media data. Furthermore, the needs analysis unit can perform country-specific importance analyses on social media data related to travelers from specific countries. This allows for more effective needs analysis by adjusting the level of detail based on the importance of the collected social media data. Some or all of the above-described processes in the needs analysis unit may be performed using AI, or not. For example, the needs analysis unit can input the importance of the collected social media data into a generating AI and have the generating AI adjust the level of detail of the analysis.

[0114] The needs analysis unit can estimate the emotions of foreign tourists and adjust the length of the needs analysis based on the estimated emotions. For example, if a foreign tourist is excited, the needs analysis unit can provide a detailed needs analysis. For example, if a foreign tourist is relaxed, the needs analysis unit can provide a concise needs analysis. Furthermore, if a foreign tourist is emotionally stable, the needs analysis unit can provide a visually easy-to-understand needs analysis. This allows for more effective needs analysis by adjusting the length of the needs analysis based on the emotions of the foreign tourist. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the needs analysis unit may be performed using AI, for example, or not using AI. For example, the needs analysis unit can input the emotions of foreign tourists into the generative AI and have the generative AI adjust the length of the needs analysis.

[0115] The Needs Analysis Department can determine the priority of analysis based on the timing of SNS data collection during the needs analysis process. For example, the Needs Analysis Department can prioritize the analysis of the most recent SNS data. For example, it can analyze past SNS data as needed. Furthermore, the Needs Analysis Department can perform country-specific analysis of SNS data related to travelers from a particular country, according to the collection timing of that country. This allows for more effective needs analysis by determining the priority of analysis based on the timing of SNS data collection. Some or all of the above processes in the Needs Analysis Department may be performed using AI, for example, or without AI. For example, the Needs Analysis Department can input the timing of SNS data collection into a generating AI and have the generating AI determine the priority of analysis.

[0116] The country-specific suggestion unit can estimate the emotions of foreign tourists and adjust the way country-specific suggestions are presented based on the estimated emotions. For example, if a foreign tourist is excited, the country-specific suggestion unit can provide detailed suggestions. If a foreign tourist is relaxed, the country-specific suggestion unit can provide concise suggestions. Furthermore, if a foreign tourist is emotionally stable, the country-specific suggestion unit can provide visually easy-to-understand suggestions. This allows for more effective suggestions by adjusting the way country-specific suggestions are presented based on the emotions of foreign tourists. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the country-specific suggestion unit may be performed using AI or not. For example, the country-specific suggestion unit can input foreign tourist emotion data into a generative AI and have the generative AI adjust the way country-specific suggestions are presented.

[0117] The country-specific proposal unit can adjust the level of detail of its proposals based on the importance of travelers in each country. For example, it can provide detailed proposals to travelers in important countries, and concise proposals to travelers in general countries. It can also provide proposals tailored to the importance of specific countries for travelers in particular countries. By adjusting the level of detail of proposals based on the importance of travelers in each country, more effective proposals can be made. Some or all of the above processing in the country-specific proposal unit may be performed using AI, for example, or not. For example, the country-specific proposal unit can input the importance of travelers in each country into a generating AI and have the generating AI adjust the level of detail of the proposals.

[0118] The country-specific suggestion unit can estimate the emotions of foreign tourists and adjust the length of country-specific suggestions based on the estimated emotions. For example, if a foreign tourist is excited, the country-specific suggestion unit can provide detailed suggestions. For example, if a foreign tourist is relaxed, the country-specific suggestion unit can provide concise suggestions. Furthermore, if a foreign tourist is emotionally stable, the country-specific suggestion unit can provide visually easy-to-understand suggestions. This allows for more effective suggestions by adjusting the length of country-specific suggestions based on the emotions of foreign tourists. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the country-specific suggestion unit may be performed using AI or not using AI. For example, the country-specific suggestion unit can input foreign tourist emotion data into a generative AI and have the generative AI adjust the length of country-specific suggestions.

[0119] The country-specific proposal department can determine the priority of proposals based on the submission timing of travelers in each country when submitting proposals. For example, the country-specific proposal department will prioritize proposals to travelers from countries that have recently submitted proposals. For example, the country-specific proposal department can make proposals to travelers from countries that have previously submitted proposals as needed. Furthermore, the country-specific proposal department can make proposals to travelers from specific countries according to their country-specific submission timing. This allows for more effective proposals by determining the priority of proposals based on the submission timing of travelers in each country. Some or all of the above processing in the country-specific proposal department may be performed using AI, for example, or not. For example, the country-specific proposal department can input the submission timing of travelers in each country into a generating AI and have the generating AI determine the priority of proposals.

[0120] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0121] The system can also include a digital archive that preserves the skills of artisans as a digital archive. This digital archive can, for example, record artisans' skills using 3D scans or high-resolution video and save them as digital data. Furthermore, it can recreate artisans' skills using VR or AR technology, passing them on to future generations. The digital archive can also publish artisans' skills on an online platform, making them accessible to people worldwide. This makes it easier to pass on and widely disseminate artisans' skills by preserving them as a digital archive.

[0122] The system can also include an evaluation unit that assesses the skills of craftsmen. This unit, for example, uses experts or AI to evaluate a craftsman's skills and quantifies their level. It can also compare a craftsman's skills to those of other craftsmen to assess their relative strengths and weaknesses. Furthermore, the evaluation unit can periodically assess the craftsman's progress and support skill improvement. This allows for the promotion of skill improvement and increased motivation among craftsmen by evaluating their abilities.

[0123] The system could also include an education department for learning craftsmanship. This department could, for example, offer online courses for learning craftsmanship. It could also, for example, organize workshops and seminars for learning craftsmanship. Furthermore, it could create and provide educational materials and guidebooks for learning craftsmanship. This would facilitate the transmission of skills and cultivate the next generation of craftsmen by providing educational opportunities for learning craftsmanship.

[0124] The system can also include a promotion department to spread awareness of the artisans' skills. This department could, for example, operate websites or social media accounts showcasing the artisans' techniques. It could also produce and publish videos or documentaries introducing the artisans' skills. Furthermore, the promotion department could organize events and exhibitions to showcase the artisans' skills. Through these promotional activities, awareness of the artisans' skills can be increased, and demand can be stimulated.

[0125] The system can also include an intellectual property department to protect the skills of artisans. This department can, for example, register and protect artisans' skills as patents or trademarks. It can also take legal action to protect artisans' skills from imitation and misuse. Furthermore, the intellectual property department can offer artisans' skills under licensing agreements and generate revenue. This allows for intellectual property management to protect artisans' skills, preventing misuse and safeguarding their rights.

[0126] The system can estimate the emotions of a craftsman and adjust its instruction methods based on those emotions. For example, if the craftsman is relaxed, it can provide detailed instruction. If the craftsman is stressed, it can provide concise instruction. Furthermore, if the craftsman is emotionally stable, it can provide visually easy-to-understand instruction. This allows for more effective technical instruction by adjusting the instruction methods based on the craftsman's emotions.

[0127] The system can estimate the emotions of a craftsman and adjust the evaluation method of their skills based on those emotions. For example, if the craftsman is relaxed, a detailed evaluation can be performed. If the craftsman is stressed, a concise evaluation can be given. Furthermore, if the craftsman is emotionally stable, a visually easy-to-understand evaluation can be provided. By adjusting the evaluation method of skills based on the craftsman's emotions, a more effective skill evaluation becomes possible.

[0128] The system can estimate the emotions of the craftsman and adjust the method of preserving the technique based on those emotions. For example, if the craftsman is relaxed, detailed preservation can be performed. If the craftsman is stressed, concise preservation can be performed. Furthermore, if the craftsman is emotionally stable, visually easy-to-understand preservation can be performed. In this way, by adjusting the method of preserving the technique based on the craftsman's emotions, more effective technique preservation becomes possible.

[0129] The system can estimate the emotions of craftsmen and adjust the promotional methods for their skills based on those estimates. For example, if a craftsman is relaxed, a detailed promotion can be given. If a craftsman is stressed, a concise promotion can be given. Furthermore, if a craftsman is emotionally stable, a visually easy-to-understand promotion can be given. This allows for more effective skill promotion by adjusting the promotional methods based on the craftsman's emotions.

[0130] The system can estimate a craftsman's emotions and adjust the training method based on those emotions. For example, if a craftsman is relaxed, detailed training can be provided. If a craftsman is stressed, concise training can be given. Furthermore, if a craftsman is emotionally stable, visually easy-to-understand training can be provided. This allows for more effective technical training by adjusting the training method based on the craftsman's emotions.

[0131] The following briefly describes the processing flow for example form 2.

[0132] Step 1: The collection team gathers detailed information and material information from the target craftsmen. For example, they can collect information such as the craftsmen's skills and dedication, historical background, procedures for specific techniques, characteristics of the materials used, scenes of the craftsmen at work and the production process, and interviews about how techniques are passed down and their commitment to production. Step 2: The analysis department analyzes the information collected by the collection department. For example, they can analyze the characteristics and technical details of craftsmanship, historical background and cultural significance, preservation and transmission methods, market value and demand, etc. Step 3: The proposal department proposes experiential tours based on the analysis results obtained by the analysis department. For example, they can propose experiential tours best suited to travelers from each country, tours that include traditional craft experiences and introductions to local culture for travelers from specific countries, customized tours tailored to travelers' needs, and tours that allow travelers to experience specific technologies or cultures based on their interests. Step 4: The Commercialization Department will commercialize the ideas proposed by the Proposal Department into tourism businesses. For example, they can develop a plan to actually operate the proposed experiential tour, secure resources in cooperation with local organizations and tourism businesses, market and promote the tour, and develop a plan to build a revenue model and operate it as a sustainable business.

[0133] 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.

[0134] Data generation model 58 is a form of 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> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. 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 (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0135] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0136] Each of the multiple elements described above, including the collection unit, analysis unit, proposal unit, commercialization unit, SNS collection unit, needs analysis unit, and country-specific proposal unit, is implemented, for example, by at least one of the smart device 14 and the data processing unit 12. For example, the collection unit uses the camera 42 and microphone 38B of the smart device 14 to collect detailed information about artisans and material information, and transmits it to the data processing unit 12 via the control unit 46A. The analysis unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and analyzes the collected information. The proposal unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and proposes an experiential tour based on the analysis results. The commercialization unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and commercializes the proposed tour as a tourism business. The SNS collection unit collects SNS data using the communication I / F 44 of the smart device 14, and transmits it to the data processing unit 12. The needs analysis unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and analyzes the needs of foreign tourists based on the collected SNS data. The country-specific proposal section is implemented, for example, by the specific processing unit 290 of the data processing device 12, and proposes the most suitable experiential tours for travelers in each country. The correspondence between each section and the device or control unit is not limited to the example described above and can be modified in various ways.

[0137] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0138] 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.

[0139] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0140] 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.

[0141] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0142] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0143] 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.

[0144] 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 by the processor 28. The storage 32 stores the specific processing program 56.

[0145] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0146] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0147] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0148] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0149] 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.

[0150] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0151] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0152] Each of the multiple elements described above, including the collection unit, analysis unit, proposal unit, commercialization unit, SNS collection unit, needs analysis unit, and country-specific proposal unit, is implemented, for example, by at least one of the smart glasses 214 and the data processing unit 12. For example, the collection unit uses the camera 42 and microphone 238 of the smart glasses 214 to collect detailed information about artisans and material information, and transmits it to the data processing unit 12 via the control unit 46A. The analysis unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and analyzes the collected information. The proposal unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and proposes an experiential tour based on the analysis results. The commercialization unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and commercializes the proposed tour as a tourism business. The SNS collection unit collects SNS data using the communication I / F 44 of the smart glasses 214, and transmits it to the data processing unit 12. The needs analysis unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and analyzes the needs of foreign tourists based on the collected SNS data. The country-specific proposal section is implemented, for example, by the specific processing unit 290 of the data processing device 12, and proposes the most suitable experiential tours for travelers in each country. The correspondence between each section and the device or control unit is not limited to the example described above and can be modified in various ways.

[0153] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0154] 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.

[0155] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0156] 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.

[0157] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0158] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0159] 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.

[0160] 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.

[0161] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0162] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0163] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0164] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0165] 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.

[0166] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0167] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0168] Each of the multiple elements described above, including the collection unit, analysis unit, proposal unit, commercialization unit, SNS collection unit, needs analysis unit, and country-specific proposal unit, is implemented by, for example, at least one of the headset terminal 314 and the data processing unit 12. For example, the collection unit uses the camera 42 and microphone 238 of the headset terminal 314 to collect detailed information on artisans and material information, and transmits it to the data processing unit 12 via the control unit 46A. The analysis unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 to analyze the collected information. The proposal unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 to propose an experiential tour based on the analysis results. The commercialization unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 to commercialize the proposed tour as a tourism business. The SNS collection unit collects SNS data using the communication I / F 44 of the headset terminal 314 and transmits it to the data processing unit 12. The needs analysis unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and analyzes the needs of foreign travelers based on collected SNS data. The country-specific proposal unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and proposes the most suitable experiential tours for travelers in each country. The correspondence between each unit and the devices and control units is not limited to the examples described above, and various modifications are possible.

[0169] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0170] 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.

[0171] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0172] 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.

[0173] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0174] 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 image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0175] 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.

[0176] 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. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0177] 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.

[0178] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0179] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0180] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0181] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0182] 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.

[0183] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0184] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0185] Each of the multiple elements described above, including the collection unit, analysis unit, proposal unit, commercialization unit, SNS collection unit, needs analysis unit, and country-specific proposal unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the collection unit uses the camera 42 and microphone 238 of the robot 414 to collect detailed information about artisans and material information, and transmits it to the data processing unit 12 via the control unit 46A. The analysis unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 to analyze the collected information. The proposal unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 to propose an experiential tour based on the analysis results. The commercialization unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 to commercialize the proposed tour as a tourism business. The SNS collection unit collects SNS data using the communication I / F 44 of the robot 414 and transmits it to the data processing unit 12. The needs analysis unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 to analyze the needs of foreign tourists based on the collected SNS data. The country-specific proposal section is implemented, for example, by the specific processing unit 290 of the data processing device 12, and proposes the most suitable experiential tours for travelers in each country. The correspondence between each section and the device or control unit is not limited to the example described above and can be modified in various ways.

[0186] 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.

[0187] Figure 9 shows the 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.

[0188] 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.

[0189] 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.

[0190] 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, and motorcycles, 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 based, for example, 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.

[0191] 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."

[0192] 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.

[0193] 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 method for the specific process may be used, which includes computer 22 and multiple other computers.

[0194] 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.

[0195] 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.

[0196] 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.

[0197] 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.

[0198] 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.

[0199] 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.

[0200] 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.

[0201] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0202] 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 other things 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.

[0203] 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.

[0204] (Note 1) A collection department that gathers detailed information and material information from the target craftsmen, An analysis unit analyzes the information collected by the aforementioned collection unit, Based on the analysis results obtained by the aforementioned analysis unit, the proposal unit proposes an experiential tour. The system comprises a business development unit that commercializes the content proposed by the aforementioned proposal unit into a tourism business. A system characterized by the following features. (Note 2) Equipped with an SNS collection unit to collect SNS data. The system described in Appendix 1, characterized by the features described herein. (Note 3) We have a needs analysis department that analyzes the needs of foreign tourists. The system described in Appendix 1, characterized by the features described herein. (Note 4) The company has a country-specific proposal department that offers tours tailored to the national characteristics and preferences of each country. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned collection unit is Collect detailed information about the craftsman's skills, dedication, and historical background. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned analysis unit is Based on the collected information, we will understand the experiences that foreign tourists are looking for. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned proposal section is, We propose experiential tours that are perfect for travelers from all countries. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned commercialization department, Turning the proposed ideas into a tourism business The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned collection unit is The system estimates the emotions of the craftsmen and adjusts the timing of information gathering based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned collection unit is Analyze the craftsman's past works and activity history to select the most suitable information gathering method. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned collection unit is When gathering information, filter it based on the craftsman's current projects and areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned collection unit is The system estimates the emotions of the craftsmen and prioritizes the information to collect based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned collection unit is When gathering information, prioritize collecting highly relevant information by considering the geographical location of the craftsmen. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned collection unit is When gathering information, we analyze the social media activity of artisans and collect relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned analysis unit is We estimate the emotions of the craftsmen and adjust the way the analysis is expressed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned analysis unit is During the analysis, adjust the level of detail based on the importance of the collected information. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned analysis unit is During analysis, different analytical algorithms are applied depending on the category of information. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned analysis unit is The emotions of the craftsman are estimated, and the length of the analysis is adjusted based on the estimated emotions of the craftsman. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned analysis unit is During analysis, prioritize the analysis based on when the information was collected. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned analysis unit is During analysis, adjust the order of analysis based on the relevance of the information. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned proposal section is, We estimate the emotions of the craftsman and adjust the way the proposal is expressed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned proposal section is, When making a proposal, adjust the level of detail based on the importance of the experiential tour. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned proposal section is, When making a proposal, different proposal algorithms are applied depending on the category of the experiential tour. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned proposal section is, Estimate the craftsman's emotions and adjust the length of the proposal based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned proposal section is, When submitting proposals, prioritize them based on the submission timing of the experiential tours. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned proposal section is, When making proposals, adjust the order of suggestions based on the relevance of the experiential tours. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned commercialization department, We estimate the emotions of the craftsmen and adjust the commercialization method based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned commercialization department, When commercializing a product, the craftsman's past commercialization history is analyzed to select the most suitable commercialization method. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned commercialization department, When commercializing the product, the means of commercialization are customized based on the current living conditions of the craftsmen. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned commercialization department, We estimate the emotions of craftsmen and determine the priority of commercialization based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned commercialization department, When commercializing a project, the optimal commercialization method will be selected by considering the geographical location information of the craftsmen. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned commercialization department, When commercializing a product, we analyze the social media activities of artisans and propose methods for commercialization. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned SNS collection unit, We estimate the emotions of foreign tourists and adjust the timing of SNS data collection based on the estimated emotions. The system described in Appendix 2, characterized by the features described herein. (Note 34) The aforementioned SNS collection unit, We analyze the past social media posting history of foreign tourists to select the optimal data collection method. The system described in Appendix 2, characterized by the features described herein. (Note 35) The aforementioned SNS collection unit, We estimate the sentiments of foreign tourists and prioritize the social media data to collect based on those estimated sentiments. The system described in Appendix 2, characterized by the features described herein. (Note 36) The aforementioned SNS collection unit, When collecting social media data, we prioritize the collection of highly relevant data by considering the geographical location information of foreign tourists. The system described in Appendix 2, characterized by the features described herein. (Note 37) The aforementioned needs analysis department, We estimate the emotions of foreign tourists and adjust the way we express needs analysis based on those estimated emotions. The system described in Appendix 3, characterized by the features described herein. (Note 38) The aforementioned needs analysis department, During needs analysis, adjust the level of detail of the analysis based on the importance of the collected social media data. The system described in Appendix 3, characterized by the features described herein. (Note 39) The aforementioned needs analysis department, Estimate the emotions of foreign tourists and adjust the length of the needs analysis based on the estimated emotions. The system described in Appendix 3, characterized by the features described herein. (Note 40) The aforementioned needs analysis department, When conducting needs analysis, prioritize the analysis based on when the social media data was collected. The system described in Appendix 3, characterized by the features described herein. (Note 41) The aforementioned country proposal departments We estimate the sentiments of foreign tourists and adjust the wording of country-specific proposals based on those estimated sentiments. The system described in Appendix 4, characterized by the features described herein. (Note 42) The aforementioned country proposal departments When creating country-specific proposals, adjust the level of detail based on the importance of travelers in each country. The system described in Appendix 4, characterized by the features described herein. (Note 43) The aforementioned country proposal departments Estimate the sentiments of foreign tourists and adjust the length of country-specific proposals based on those estimated sentiments. The system described in Appendix 4, characterized by the features described herein. (Note 44) The aforementioned country proposal departments When submitting proposals by country, the priority of proposals will be determined based on when travelers from each country submitted their proposals. The system described in Appendix 4, characterized by the features described herein. [Explanation of symbols]

[0205] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A collection department that gathers detailed information and material information from the target craftsmen, An analysis unit analyzes the information collected by the aforementioned collection unit, Based on the analysis results obtained by the aforementioned analysis unit, the proposal unit proposes an experiential tour. The system comprises a business development unit that commercializes the content proposed by the aforementioned proposal unit into a tourism business. A system characterized by the following features.

2. We have a needs analysis department that analyzes the needs of foreign tourists. The system according to feature 1.

3. The company has a country-specific proposal department that offers tours tailored to the national characteristics and preferences of each country. The system according to feature 1.

4. The aforementioned collection unit is Collect detailed information about the craftsman's skills, dedication, and historical background. The system according to feature 1.

5. The aforementioned analysis unit is Based on the collected information, we will understand the experiences that foreign tourists are looking for. The system according to feature 1.

6. The aforementioned proposal section is, We propose experiential tours that are perfect for travelers from all countries. The system according to feature 1.

7. The aforementioned commercialization department, Turning the proposed ideas into a tourism business The system according to feature 1.

8. The aforementioned collection unit is The system estimates the emotions of the craftsmen and adjusts the timing of information gathering based on those estimated emotions. The system according to feature 1.

9. The aforementioned collection unit is Analyze the craftsman's past works and activity history to select the most suitable information gathering method. The system according to feature 1.

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