system

Abstract

We provide the system. [Solution] A means of collecting corporate information and training a generative artificial intelligence model, A means of collecting and analyzing data on a designated market and conducting demand and competition analysis, In order to provide legal information for the target country, a means of referencing legal databases and generating checklists, Means of supporting translation and negotiation between different languages, A means of managing product distribution in conjunction with international e-commerce platforms and logistics systems, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is 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 as a 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] Small and medium-sized enterprises in Japan face multiple barriers such as legal compliance, market research, and difficulties in cross-cultural communication when entering overseas markets while having high technological capabilities. As a result, there is a problem of a delay in international expansion and the inability to fully utilize global competitiveness. The purpose of this invention is to provide a system that can autonomously overcome these barriers and enable enterprises to efficiently enter overseas markets.

Means for Solving the Problems

[0005] <( This invention provides means for collecting corporate information and learning it based on a generative artificial intelligence model. This enables the use of corporate business knowledge to formulate market entry strategies. It also includes means for collecting and analyzing data on specific markets to provide insights into demand and competition, and means for referencing legal databases and generating checklists to provide timely legal information for target markets. Furthermore, it incorporates means for cross-language translation and negotiation support, and means for managing product distribution in conjunction with international e-commerce platforms and logistics systems, comprehensively addressing these challenges.

[0006] "Company information" refers to information owned by small and medium-sized enterprises, including operational data, product information, and business objectives.

[0007] A "generative artificial intelligence model" is an artificial intelligence model that learns from collected company information and can imitate and apply specific business knowledge and market characteristics.

[0008] Market research is the process of collecting and analyzing information on demand, supply, competition, and consumer trends in a target market.

[0009] A "legal database" is a collection of information that comprehensively gathers and manages the latest laws, regulations, and procedures related to the target country of business.

[0010] A "checklist" is a list of items that enumerate the steps and considerations necessary to achieve a specific objective.

[0011] Translation is the process of converting information written in one language into another language, and it supports communication between languages.

[0012] "Negotiation support" refers to activities that help facilitate smooth business communication with parties from different cultures and linguistic backgrounds.

[0013] An "international e-commerce platform" is an online marketplace environment for buying and selling goods and providing services across national borders via the internet.

[0014] A "logistics system" is a system that includes means and processes for optimizing the movement, storage, and delivery of goods during the distribution process. [Brief explanation of the drawing]

[0015] [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. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Modes for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one 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), etc.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

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

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] 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.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] 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.

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

[0032] 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.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0036] In one embodiment of the present invention, a system is provided to solve various challenges that Japanese small and medium-sized enterprises face when entering the global market. This system utilizes a generative artificial intelligence model and performs learning and analysis based on company information to support smooth entry into overseas markets.

[0037] The server first receives business data and product information provided by small and medium-sized enterprises (SMEs) and constructs information based on the companies' business objectives. This information is used as training data for a generative artificial intelligence model, which learns company-specific knowledge and market characteristics. Through this process, the model acquires the ability to formulate market entry strategies tailored to the specific strategies of the companies.

[0038] Next, the user submits a request for market research via the terminal. The server references internet data sources and commercial databases to analyze demand and competitive landscape in the target market. The analysis results are processed into demand forecasts and competitive comparisons and provided to the user in a visual format via the terminal. This information allows companies to assess their specific market position and potential for entry.

[0039] Furthermore, to support compliance with laws and regulations in overseas markets, the server references legal databases of the target country and provides necessary legal procedure information. This includes export and import procedures and required permits and licenses. Users can then proceed with specific legal procedures based on the provided checklist.

[0040] Furthermore, to overcome language and cultural barriers, the server has a function to translate between different languages ​​and support cross-cultural business negotiations. This function allows users to communicate smoothly with overseas companies and lead negotiations to success.

[0041] Finally, to support international trade, the server integrates with existing cross-border e-commerce platforms and logistics systems, providing a means to optimize product shipment and distribution. Users can utilize this system to efficiently send goods and services to overseas markets.

[0042] For example, if a small or medium-sized Japanese manufacturing company is considering entering the European market, utilizing this system would allow them to gain a concrete understanding of local consumer needs and formulate a product strategy that differentiates them from competitors. Furthermore, receiving support for legal procedures and logistics would enable them to enter the market quickly and smoothly.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The server receives business data and product information from small and medium-sized enterprises. This includes specific information about the companies' business goals and industries. The received data is used to build training data for generative artificial intelligence models.

[0046] Step 2:

[0047] The server trains a generative artificial intelligence model based on the received data. By learning the company's unique business knowledge and market characteristics, the model can develop market entry strategies tailored to specific markets.

[0048] Step 3:

[0049] Users request market research for specific countries or regions through their devices. This includes demand forecasting and competitive analysis for the target market.

[0050] Step 4:

[0051] The server crawls publicly available data sources and commercial databases on the internet to collect necessary data for market research. This allows it to obtain the latest market information.

[0052] Step 5:

[0053] The server analyzes the collected data to assess demand, supply, and competition. The analysis results are compiled into demand forecasts and competitive comparisons.

[0054] Step 6:

[0055] The terminal visualizes the analysis results and displays them in an easy-to-understand manner for the user. Based on this information, the user can formulate an entry plan.

[0056] Step 7:

[0057] The server accesses legal databases to obtain the latest legal information for the target country. This includes information on import / export procedures and business license acquisition.

[0058] Step 8:

[0059] The server provides the user with a legal checklist. The user then proceeds with the necessary legal procedures based on this checklist.

[0060] Step 9:

[0061] Users use their devices to input or update details of negotiations with overseas companies. This includes communication history and negotiation progress.

[0062] Step 10:

[0063] The server utilizes translation capabilities to translate emails and documents between different languages. Furthermore, it automatically adjusts the content to take cultural context into consideration.

[0064] Step 11:

[0065] The device provides users with notifications regarding negotiation details and next steps, supporting smooth communication.

[0066] Step 12:

[0067] The server integrates with international e-commerce platforms and logistics systems to optimize product distribution and management. This includes inventory management and delivery route optimization.

[0068] Step 13:

[0069] The terminal notifies the user in real time of the delivery status of the product and the progress of the logistics process. This allows the user to respond quickly to unforeseen circumstances related to distribution.

[0070] (Example 1)

[0071] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0072] Traditionally, small and medium-sized enterprises (SMEs) have faced numerous challenges when entering global markets, including thorough market research, legal compliance, language barriers, and logistics management. A comprehensive system is needed to address these challenges and support overseas expansion efficiently and effectively.

[0073] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0074] In this invention, the server includes means for aggregating business information and training strategies using a generative AI model, means for collecting data related to a specific market and performing demand forecasting and competitive analysis, and means for obtaining legal information of the target market and generating procedural checklists. This enables companies to efficiently conduct market research, prepare for legal procedures, and smoothly enter overseas markets.

[0075] "Business information" refers to all data related to a company's operations, including sales, inventory, customer information, and product information.

[0076] A "generative AI model" is an artificial intelligence technology that learns from large amounts of data and formulates knowledge and strategies tailored to specific purposes.

[0077] "Data collection" refers to the process of systematically gathering necessary information, and involves obtaining information from the internet or databases.

[0078] "Demand forecasting" is a method of numerically predicting the future willingness to purchase a particular product or service.

[0079] "Competitive analysis" is the process of analyzing the activities and characteristics of competitors within the same market.

[0080] "Legal information" refers to information that provides details about the laws and regulations applicable in a specific region.

[0081] A "procedure checklist" is a comprehensive list that outlines the steps required for a specific task or legal procedure.

[0082] "Language translation" is the process of replacing a text written in one language with a text written in another language.

[0083] "Intercultural negotiation" refers to negotiations conducted between people with different cultural backgrounds.

[0084] An "international commercial trading platform" is an integrated system for conducting online international buying and selling transactions of goods and services.

[0085] A "logistics management system" is a general term for technologies and methods used to efficiently manage the distribution process of goods.

[0086] A "user interface" refers to the part of a system or application that provides the user interface and input methods for interacting with it.

[0087] "Visual information" refers to information presented in a visual format, including graphs, diagrams, and report formats.

[0088] The system implementing this invention utilizes generative AI models to provide comprehensive support for Japanese small and medium-sized enterprises to enter the global market. This system includes three entities: a server, a terminal, and a user, each playing a specific role.

[0089] The server first aggregates business information provided by companies. This information is collected via APIs from databases such as ERP and CRM systems. Based on this data, it trains a generative AI model and uses the learned knowledge to form a market entry strategy. Machine learning frameworks such as TENSORFLOW® and PyTorch are used for this training. The server also accesses online data sources and commercial databases to perform demand forecasting and competitive analysis for specified markets, and processes the results as visual information.

[0090] Through the terminal, the user enters a prompt about a specific market and requests research from the server. For example, the user might enter, "We are planning to enter the European market with our products. Please tell me about local market trends and competitive information." The server receives this input, retrieves the necessary information, and analyzes it.

[0091] The server organizes legal information for the target country and provides users with procedural checklists. This allows users to efficiently proceed with the necessary procedures. Furthermore, to facilitate cross-cultural communication, the server performs language translation and provides negotiation support.

[0092] Finally, the server integrates with logistics management systems and international trade platforms to optimize product distribution. This functionality enables users to efficiently deliver products and services to overseas markets.

[0093] Thus, the present invention aims to support small and medium-sized enterprises in entering the global market and to enable smooth business development through its diverse functions.

[0094] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0095] Step 1:

[0096] The server collects business information from companies. The input is ERP and CRM data provided by companies via APIs. The server collects this data and stores it in a database. Next, this data is preprocessed to serve as a training dataset for a generative AI model. The output is the training dataset for the generative AI model to learn from.

[0097] Step 2:

[0098] The server learns corporate strategies using a generative AI model. It uses the training dataset obtained in the previous step as input. The server trains the model using a machine learning framework (e.g., TensorFlow, PyTorch) to build a model with corporate-specific strategic planning capabilities. The output is the completed generative AI model.

[0099] Step 3:

[0100] The user uses a terminal to input a prompt message about a specific market. The input is a prompt message that clearly states the market to be investigated and the information to be obtained (e.g., "We are planning to enter the European market with our products. Please tell us about local market trends and competitor information."). The terminal sends this prompt message to the server. The output is a research request sent to the server.

[0101] Step 4:

[0102] The server conducts market research based on prompt messages. The input is the prompt message received from the user. The server collects data on the target market from the internet and commercial databases (e.g., Statista, Euromonitor) and performs demand forecasting and competitive analysis. It uses natural language processing and data mining techniques to perform the analysis and generates a visual report as output.

[0103] Step 5:

[0104] The server retrieves legal information for the target market and generates a procedural checklist. The input is access information to the legal database of the target market. Based on this information, the server collects the latest legal data and generates a list of procedures that the company must follow. The output is a procedural checklist available to the user.

[0105] Step 6:

[0106] The server performs language translation and supports cross-cultural communication. The input is the text that the user will use for communication. Using a translation API, the server translates it into the required language. The output is clearly translated text, which the user can use to communicate smoothly.

[0107] Step 7:

[0108] The server integrates with international trade platforms and logistics systems to optimize logistics management. Inputs include product delivery data and order information. The server utilizes APIs from shipping carriers to develop efficient inventory management and delivery plans. The output is an optimized logistics plan, which users can use to manage international product shipments.

[0109] (Application Example 1)

[0110] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0111] Currently, many small and medium-sized enterprises (SMEs) attempting to enter overseas markets face complex challenges such as market demand analysis, competitor research, and legal compliance. Furthermore, communication barriers due to language and cultural differences hinder business success. An effective support system is needed to comprehensively address these challenges.

[0112] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0113] In this invention, the server includes means for collecting corporate information and training a generative artificial intelligence model, means for collecting and analyzing data on a designated market and performing demand and competition analysis, and means for visually providing market analysis results and suggesting sales opportunities. This enables small and medium-sized enterprises to efficiently grasp the characteristics of their target market and formulate specific market entry strategies.

[0114] "Methods for collecting corporate information and training generative artificial intelligence models" refers to the process of receiving data provided by companies and feeding it to generative artificial intelligence models to learn company-specific knowledge and market characteristics.

[0115] "Means of collecting and analyzing data on a designated market and conducting demand and competition analysis" refers to a function for collecting various data on a target market and analyzing demand trends and the activities of competitors in that market.

[0116] "A means of generating checklists by referring to legal databases in order to provide legal information for the target country of entry" refers to a system for searching the legal database of the target country of entry and creating a checklist that lists the necessary legal procedures.

[0117] "Means of supporting translation and negotiation between different languages" refers to a function that translates texts between different languages ​​and provides support to facilitate negotiations while taking cultural backgrounds into consideration.

[0118] "Means of managing product distribution in conjunction with international e-commerce platforms and logistics systems" refers to management functions that enable products to be delivered to consumers efficiently and effectively by integrating with e-commerce sites and logistics networks.

[0119] "A means of visually providing market analysis results and suggesting sales opportunities" refers to a method of visually presenting analyzed market data to users and proposing specific sales opportunities and strategic actions.

[0120] The system for implementing this invention is primarily built around a server and terminals connected to it. The server first receives business information and product data provided by companies and learns from it using a generative artificial intelligence model. In this process, it accumulates company-specific knowledge and market characteristics, and gains the ability to formulate market entry strategies.

[0121] Users request information about their target market via their devices. The server analyzes the collected market data to assess demand trends and the competitive landscape. This allows companies to clearly understand their product's position in the market and visually grasp sales opportunities.

[0122] Furthermore, the server references legal information for the country or region where the company plans to expand and generates a checklist of necessary legal procedures. This checklist is provided to the user to support smooth compliance with the law.

[0123] The server also provides translation functionality between different languages, facilitating smooth intercultural communication. This allows users to conduct international business negotiations more effectively.

[0124] Finally, the integration of international e-commerce platforms, logistics systems, and servers enables efficient management of product distribution. This system allows companies to deliver products to their target markets quickly and effectively.

[0125] As a concrete example, when an Asian manufacturing company is exploring sales opportunities in the European market, it can send the following prompt to the server:

[0126] "Please analyze the sales opportunities for high-quality, handcrafted furniture in the European market."

[0127] Based on this prompt, the server conducts a detailed market analysis and presents the user with an effective market entry strategy.

[0128] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0129] Step 1:

[0130] Corporate information collection and AI model training

[0131] The server receives business information and product data provided by users. This data is input into a generative artificial intelligence model, which learns company-specific knowledge and market characteristics. As part of data processing, the business information is converted into a structured data format, and analysis is performed by the AI ​​model. As an output, the parameters of the AI ​​model are adjusted, accumulating knowledge useful for future analyses.

[0132] Step 2:

[0133] Market data collection and analysis

[0134] Through a terminal, the user requests an analysis of a specific market from the server. The server collects market data from internet data sources and commercial databases. It analyzes the input market data and calculates demand and competitor trends. In this process, data cleaning and statistical methods are used to derive the analysis results. As output, the server provides the user with a visual analytics report.

[0135] Step 3:

[0136] Reference to legal information and creation of checklists

[0137] The server accesses legal databases in the target country or region to retrieve necessary legal information. Specifically, it uses a database API to obtain the latest legal data. Based on the input legal data, it creates a checklist of legal procedures. As output, a list of specific procedures is generated and provided to the user.

[0138] Step 4:

[0139] Translation and negotiation support features

[0140] The user sends text in a different language as input to the server. The server performs text translation using a translation engine. Translation memory and statistical translation models are used for data processing to provide highly accurate translations. The output translation results support international communication by the user.

[0141] Step 5:

[0142] Integration of e-commerce and logistics management

[0143] The server interacts with international e-commerce platforms and logistics networks. Specifically, it manages product inventory information and shipping options via APIs. Based on the entered order information, it automatically calculates the optimal shipping strategy. As an output, users are provided with an efficient product distribution plan.

[0144] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0145] This invention provides a system to facilitate the entry of Japanese small and medium-sized enterprises (SMEs) into international markets, and further enhances the user experience by combining it with an emotion engine. This system is based on the collection of company information and learning and analysis using a generative artificial intelligence model, and provides a process for formulating entry strategies into specific markets. Furthermore, it supports appropriate market entry by referring to the laws and regulations of the target market and assisting with necessary legal procedures.

[0146] The emotion engine has the ability to analyze the user's emotional state in real time and dynamically adjusts the system interface and the information presented based on the analysis results. This is designed to allow users to use the system more comfortably.

[0147] In a specific implementation, the server receives business data and product information from small and medium-sized enterprises (SMEs) and uses a generative artificial intelligence model to extract key strategic insights from this data. Simultaneously, the server consults legal databases to list legal requirements in the target country. This information is provided to users via terminals to facilitate legal procedures.

[0148] When a user uses the system, the emotion engine analyzes their emotions through input devices such as camera and mouse movements. This data is used by the server to adjust the display content of the system's operation screen and interface according to instructions. For example, if signs of user confusion are detected, the system will immediately display helpful information and hints.

[0149] Furthermore, the server provides translation functionality to support cross-cultural business negotiations. In this process, it takes into account the analysis results of the sentiment engine to appropriately adjust translations and expressions, minimizing misunderstandings between cultures.

[0150] Furthermore, integration with international e-commerce platforms and logistics systems allows users to manage the effective distribution of their products and services. The system can also leverage feedback from an emotional engine to adjust logistics plans and customer service strategies.

[0151] As a concrete example, let's consider a Japanese small-to-medium-sized software company aiming to enter the North American market. This company uses a system to collect local needs and competitive information, supporting strategic planning while simultaneously deepening its understanding of local laws and regulations. Furthermore, by utilizing an emotional engine, it can manage project managers' stress and misunderstandings, supporting optimal decision-making. This enables Japanese companies to leverage their global competitiveness and build success in international markets.

[0152] The following describes the processing flow.

[0153] Step 1:

[0154] The server receives business data and product information provided by small and medium-sized businesses. This includes data sharing via cloud storage such as SkyDrive and Dropbox.

[0155] Step 2:

[0156] The server trains a generative artificial intelligence model based on the received company information. The model learns business knowledge and strategies tailored to the characteristics of each company.

[0157] Step 3:

[0158] Users request specific market research via their devices. The research request includes details such as the target country and research items.

[0159] Step 4:

[0160] The server uses the internet and commercial databases to collect data on the specified market. This is done using crawling technology.

[0161] Step 5:

[0162] The server analyzes market data and generates competitive information and demand forecasts. This helps to concretize the potential markets that companies should enter.

[0163] Step 6:

[0164] The device presents the analysis results to the user as a visual dashboard. Through graphs and charts, users can intuitively grasp the information.

[0165] Step 7:

[0166] The server references legal databases for the target market and generates up-to-date legal information and a checklist of necessary documents for the business.

[0167] Step 8:

[0168] The device displays the necessary legal procedures and their priorities to the user, along with their progress. The user then proceeds with the procedures based on this information.

[0169] Step 9:

[0170] The emotion engine performs real-time sentiment analysis based on data entered by the user through the device's camera and microphone.

[0171] Step 10:

[0172] The server adjusts the system interface based on the results of the sentiment analysis. For example, if the user is stressed, it will display the user guide.

[0173] Step 11:

[0174] The server provides translation support for cross-language communication, offering expressions that take cultural context into account. This facilitates smoother negotiations.

[0175] Step 12:

[0176] The device uses data from its emotion engine to receive user feedback and then suggests the next course of action. This includes the direction and strategy of negotiations.

[0177] Step 13:

[0178] The server integrates with e-commerce platforms and logistics systems to automate product distribution and inventory management.

[0179] Step 14:

[0180] The terminal provides users with real-time information on product delivery status and inventory. This allows companies to operate their supply chains more efficiently.

[0181] (Example 2)

[0182] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0183] These are the challenges faced by Japanese small and medium-sized enterprises (SMEs) when entering international markets: improving the efficiency of information gathering, formulating market strategies, understanding local laws and regulations, and overcoming communication gaps in cross-cultural business negotiations. Furthermore, there is the need to improve usability by dynamically adjusting the system to take into account the emotional state of the user.

[0184] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0185] In this invention, the server includes means for collecting corporate information and training it using a generative AI model, means for collecting information on a specified market and analyzing demand and competition, and means for referencing legal data sources and generating a list in order to provide regulatory information for the target market. This enables smooth entry of small and medium-sized enterprises into international markets and dynamic adjustment of the interface according to the emotional state of the user.

[0186] "Company information" refers to a collection of data and knowledge related to a company's activities, including business operations, product information, and sales data.

[0187] A "generative AI model" is an artificial intelligence system that uses machine learning algorithms to analyze data and generate patterns and insights.

[0188] A "designated market" refers to a specific geographical or industry-specific area in which a company aims to enter, and the market trends and needs within that area are the focus.

[0189] "Regulatory information" refers to data on laws and regulations enacted in a particular country or region, which indicate the requirements that companies must comply with when conducting their business activities.

[0190] "Intercultural translation" is the process of linguistic conversion that enables accurate communication between people with different languages ​​and cultures.

[0191] An "emotion engine" is a technology that analyzes a user's emotional state in real time, evaluating emotions such as stress and confusion by analyzing the user's facial expressions and behavior.

[0192] An "international trading platform" is an online service that supports cross-border commercial transactions and facilitates the sale and purchase of products and services.

[0193] A "logistics system" is a network and process for managing the distribution of products and services, with the aim of efficiently delivering goods to consumers.

[0194] This invention functions as a support system for companies to smoothly enter international markets. Specifically, it is a system whose main components are a server, terminals, and users, which cooperate to perform tasks such as information gathering, data analysis, legal compliance, and sentiment analysis.

[0195] The server receives information provided by companies and uses high-performance data processing servers as hardware. The software incorporates generative AI models built using Python, TensorFlow, and other technologies. This allows the server to learn the company's business knowledge and automatically generate strategies for specified markets. The server also has the ability to connect with online legal databases to retrieve and list the latest legal information.

[0196] The terminal functions as an interface device for the user to interact with the system, using a computer or smart device. A computer vision algorithm is installed as an emotion engine to analyze the user's facial expressions and movements from camera and mouse movements. The emotion data obtained by the terminal is sent to a server and used to dynamically adjust the interface and presented information.

[0197] Users access international market research and translation services through the system. Based on emotional states analyzed by an emotion engine, the terminal immediately provides additional instructions and hints if the user is confused. Furthermore, the server-based translation function enables effective cross-cultural business negotiations.

[0198] As a concrete example, consider the use of the system by a Japanese small-to-medium-sized software company aiming to enter the North American market. This company can efficiently perform the necessary analysis and strategy formulation by inputting the following prompt into the system's generating AI model: "We would like the generating AI model to provide the optimal strategy for a Japanese app development company to enter the American market, as well as the procedures for verifying local laws and regulations."

[0199] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0200] Step 1:

[0201] Users provide the system with information about their company and the requirements of their desired market through an input device. This input includes company product data, performance information, and market entry objectives. This information is sent to a server and stored in a database.

[0202] Step 2:

[0203] The server uses a generative AI model to analyze the input company information. The generative AI model uses the input data to forecast market demand and conduct competitive analysis, generating strategic insights as output. For example, it analyzes the trends of competing companies and proposes optimal pricing and marketing strategies.

[0204] Step 3:

[0205] The server retrieves legal information for the target region from an external database. It receives information about the country or region where the company plans to expand as input and references the relevant regional regulatory data. As output, it generates a list based on the law, providing an overview of the regulations the user must comply with.

[0206] Step 4:

[0207] The device analyzes the user's emotional state through input devices such as a camera and mouse. The input consists of the user's facial expressions and behavioral patterns, which are processed by an emotion engine to identify signs of stress or confusion. The output emotion data is then used by the server in real time to adjust the interface.

[0208] Step 5:

[0209] The server dynamically adjusts the system interface based on the analysis results of the emotion engine. If a specific emotional state is detected, for example, if the system determines that the user is confused, it immediately provides support by displaying additional guidance or explanations on the screen.

[0210] Step 6:

[0211] The server provides translation functionality to support cross-cultural communication. It receives business documents and conversations requiring translation as input, and generates appropriate translated expressions that reflect feedback from an emotion engine, providing them to the user as output.

[0212] (Application Example 2)

[0213] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0214] For businesses expanding into international markets, efficient and strategic decision-making is crucial. However, this presents challenges due to the need to consider diverse market information, legal regulations, and cross-cultural communication, which often requires significant time and effort. Furthermore, in logistics center operations, there is a need for process improvements that take into account the working conditions of the staff.

[0215] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0216] In this invention, the server includes means for collecting business entity information and training it using a generative artificial intelligence model; means for collecting and analyzing information on a designated market and analyzing demand and competition; means for referencing a legal database and generating a checklist to provide legal information for the target market; and means for analyzing the emotions of business personnel using an information presentation device and dynamically adjusting work instructions and information presentations. This enables strategic decision-making regarding entry into international markets and efficient execution of operations at logistics centers.

[0217] "Business entity information" refers to all information related to the operation of an organization that conducts business activities, and specifically includes financial data, product information, customer information, etc.

[0218] A "generative artificial intelligence model" refers to an AI algorithm that has the ability to analyze given data and learn patterns and rules, and is a technology that generates new insights and predictions.

[0219] "Market information" refers to data necessary for business strategy, such as economic trends in a specific industry or region, consumer demand, and the competitive landscape.

[0220] "Legal information" refers to data on laws and regulations necessary for business activities, and is information that clarifies legal requirements that differ from country to country and region to region.

[0221] An "information presentation device" refers to a device that provides information to a user visually or audibly, and includes output devices such as displays and speakers.

[0222] "The emotions of the person in charge of the work" refers to the psychological and emotional state of the personnel performing the work, including stress levels and motivation.

[0223] A "logistics procedures system" refers to an information management system equipped with planning, tracking, and optimization functions for managing the distribution of goods and services.

[0224] The system for implementing this invention consists of multiple hardware and software components. First, the server collects various information about the business entity and stores it in a database, and then uses a generative artificial intelligence model to learn and analyze that information. Specifically, it builds an AI model using Python and TensorFlow, and performs analysis by saving the data to MongoDB.

[0225] Smart glasses and head-mounted displays are used as information presentation devices, providing users with an environment where they can check information in real time while working. Specifically, this includes Google® Glass® and Microsoft® HoloLens®.

[0226] When a user operates the system, the server uses OpenCV to analyze video data from the camera and displays information such as inventory status and logistics routes. Furthermore, various sensors built into the information display device detect and analyze the user's emotional state, dynamically changing the display of work instructions and support information.

[0227] As a concrete example, imagine a scenario where the information presented to an operator at a logistics center during working hours is adjusted according to the operator's work condition. If the operator is detected to be under high stress, clearer explanations and notifications regarding appropriate break times will be displayed.

[0228] Examples of prompts for the generated AI model include: "Please suggest the optimal shelf arrangement to accommodate new product arrivals. Please calculate a picking route that takes into account the operator's physical condition." In this context, the system's role is to simultaneously provide efficient operational support and improve the user experience.

[0229] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0230] Step 1:

[0231] The server collects business and market information into a database and uses TensorFlow to train a generative artificial intelligence model. Inputs include financial data and market trends of the businesses, while outputs are analyzed demand forecasts and strategic insights. During this process, the data is preprocessed and supplied to the AI ​​model in an optimal format.

[0232] Step 2:

[0233] Users can view real-time information within the logistics center through smart glasses or head-mounted displays. Camera footage is captured by the terminal and sent to the server as input. The server analyzes this data using OpenCV and generates output such as inventory status and optimal logistics routes.

[0234] Step 3:

[0235] The server analyzes the user's emotional state using sensors built into the information display device. Inputs include the user's heart rate and movement data, while outputs include the user's stress level and motivation assessment. Based on this, the server generates appropriate work instructions and support information.

[0236] Step 4:

[0237] Based on the user's emotional state, the server dynamically adjusts the display content of the information presentation device. The input is the emotion analysis result obtained in step 3, and based on this, work instructions and support information are presented in a way that is easy for the user to understand. The output is information that has been adjusted visually or audibly.

[0238] Step 5:

[0239] The server utilizes data obtained from the generative AI model to present users with prompts that support the optimization and strategic planning of logistics centers. The input is the analysis results from the generative AI model, and the output is optimization suggestions in the form of prompts. This process aims to improve operational efficiency and enhance worker experience.

[0240] 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.

[0241] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0242] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0243] [Second Embodiment]

[0244] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0245] 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.

[0246] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0247] 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.

[0248] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0249] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0250] 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.

[0251] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0252] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0253] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0254] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0255] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0256] In one embodiment of the present invention, a system is provided to solve various challenges that Japanese small and medium-sized enterprises face when entering the global market. This system utilizes a generative artificial intelligence model and performs learning and analysis based on company information to support smooth entry into overseas markets.

[0257] The server first receives business data and product information provided by small and medium-sized enterprises (SMEs) and constructs information based on the companies' business objectives. This information is used as training data for a generative artificial intelligence model, which learns company-specific knowledge and market characteristics. Through this process, the model acquires the ability to formulate market entry strategies tailored to the specific strategies of the companies.

[0258] Next, the user submits a request for market research via the terminal. The server references internet data sources and commercial databases to analyze demand and competitive landscape in the target market. The analysis results are processed into demand forecasts and competitive comparisons and provided to the user in a visual format via the terminal. This information allows companies to assess their specific market position and potential for entry.

[0259] Furthermore, to support compliance with laws and regulations in overseas markets, the server references legal databases of the target country and provides necessary legal procedure information. This includes export and import procedures and required permits and licenses. Users can then proceed with specific legal procedures based on the provided checklist.

[0260] Furthermore, to overcome language and cultural barriers, the server has a function to translate between different languages ​​and support cross-cultural business negotiations. This function allows users to communicate smoothly with overseas companies and lead negotiations to success.

[0261] Finally, to support international trade, the server integrates with existing cross-border e-commerce platforms and logistics systems, providing a means to optimize product shipment and distribution. Users can utilize this system to efficiently send goods and services to overseas markets.

[0262] For example, if a small or medium-sized Japanese manufacturing company is considering entering the European market, utilizing this system would allow them to gain a concrete understanding of local consumer needs and formulate a product strategy that differentiates them from competitors. Furthermore, receiving support for legal procedures and logistics would enable them to enter the market quickly and smoothly.

[0263] The following describes the processing flow.

[0264] Step 1:

[0265] The server receives business data and product information from small and medium-sized enterprises. This includes specific information about the companies' business goals and industries. The received data is used to build training data for generative artificial intelligence models.

[0266] Step 2:

[0267] The server trains a generative artificial intelligence model based on the received data. By learning the company's unique business knowledge and market characteristics, the model can develop market entry strategies tailored to specific markets.

[0268] Step 3:

[0269] Users request market research for specific countries or regions through their devices. This includes demand forecasting and competitive analysis for the target market.

[0270] Step 4:

[0271] The server crawls publicly available data sources and commercial databases on the internet to collect necessary data for market research. This allows it to obtain the latest market information.

[0272] Step 5:

[0273] The server analyzes the collected data to assess demand, supply, and competition. The analysis results are compiled into demand forecasts and competitive comparisons.

[0274] Step 6:

[0275] The terminal visualizes the analysis results and presents them to the user in an understandable way. Based on this information, the user can formulate a progress plan.

[0276] Step 7:

[0277] The server refers to the legal database and obtains the latest legal information of the target country. This includes information on export procedures and business license acquisition.

[0278] Step 8:

[0279] The server provides the user with a legal checklist. Based on this checklist, the user proceeds with the necessary legal procedures.

[0280] Step 9:

[0281] The user uses the terminal to input or update the negotiation content with overseas companies. This includes communication history and negotiation progress.

[0282] Step 10:

[0283] The server utilizes the translation function to translate emails and documents between different languages. Furthermore, it automatically adjusts the content considering the cultural background.

[0284] Step 11:

[0285] The terminal provides the user with notifications regarding negotiation content and next steps, and offers support for smooth communication.

[0286] Step 12:

[0287] The server integrates with international e-commerce platforms and logistics systems to optimize product distribution and management. This includes inventory management and delivery route optimization.

[0288] Step 13:

[0289] The terminal notifies the user in real time of the delivery status of the product and the progress of the logistics process. This allows the user to respond quickly to unforeseen circumstances related to distribution.

[0290] (Example 1)

[0291] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0292] Traditionally, small and medium-sized enterprises (SMEs) have faced numerous challenges when entering global markets, including thorough market research, legal compliance, language barriers, and logistics management. A comprehensive system is needed to address these challenges and support overseas expansion efficiently and effectively.

[0293] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0294] In this invention, the server includes means for aggregating business information and training strategies using a generative AI model, means for collecting data related to a specific market and performing demand forecasting and competitive analysis, and means for obtaining legal information of the target market and generating procedural checklists. This enables companies to efficiently conduct market research, prepare for legal procedures, and smoothly enter overseas markets.

[0295] "Business information" refers to all data related to a company's operations, including sales, inventory, customer information, and product information.

[0296] A "generative AI model" is an artificial intelligence technology that learns from large amounts of data and formulates knowledge and strategies tailored to specific purposes.

[0297] "Data collection" refers to the process of systematically gathering necessary information, and involves obtaining information from the internet or databases.

[0298] "Demand forecasting" is a method of numerically predicting the future willingness to purchase a particular product or service.

[0299] "Competitive analysis" is the process of analyzing the activities and characteristics of competitors within the same market.

[0300] "Legal information" refers to information that provides details about the laws and regulations applicable in a specific region.

[0301] A "procedure checklist" is a comprehensive list that outlines the steps required for a specific task or legal procedure.

[0302] "Language translation" is the process of replacing a text written in one language with a text written in another language.

[0303] "Intercultural negotiation" refers to negotiations conducted between people with different cultural backgrounds.

[0304] An "international commercial trading platform" is an integrated system for conducting online international buying and selling transactions of goods and services.

[0305] A "logistics management system" is a general term for technologies and methods used to efficiently manage the distribution process of goods.

[0306] A "user interface" refers to the part of a system or application that provides the user interface and input methods for interacting with it.

[0307] "Visual information" refers to information provided in a visual form, including graphs, diagrams, report formats, etc.

[0308] The system for implementing this invention utilizes a generative AI model to provide comprehensive support for Japanese small and medium-sized enterprises to enter the global market. This system includes three entities: a server, a terminal, and a user, each playing a specific role.

[0309] First, the server aggregates the business information provided by enterprises. This information is collected through APIs from databases such as ERP systems and CRM systems. Based on this data, a generative AI model is trained, and the learned knowledge is used to formulate a market entry strategy. Machine learning frameworks such as TensorFlow and PyTorch are used for this training. In addition, the server accesses online data sources and commercial databases to conduct demand forecasting and competitive analysis for the designated market, and processes the results as visual information.

[0310] Through the terminal, the user inputs a prompt sentence about a specific market and requests an investigation from the server. For example, the user inputs "I am planning to enter the European market with my product. Please tell me the local market trends and competitive information." The server receives this input, obtains the necessary information, and analyzes it.

[0311] The server organizes the legal information of the target country and provides a procedure checklist to the user. This enables the user to efficiently proceed with the necessary procedures. Furthermore, to facilitate smooth cross-cultural communication, the server performs language translation and provides negotiation support.

[0312] Finally, the server integrates with the logistics management system and international trade platforms to optimize product distribution. This function enables the user to efficiently deliver products and services to overseas markets.

[0313] Thus, the present invention aims to support small and medium-sized enterprises in entering the global market and to enable smooth business development through its diverse functions.

[0314] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0315] Step 1:

[0316] The server collects business information from companies. The input is ERP and CRM data provided by companies via APIs. The server collects this data and stores it in a database. Next, this data is preprocessed to serve as a training dataset for a generative AI model. The output is the training dataset for the generative AI model to learn from.

[0317] Step 2:

[0318] The server learns corporate strategies using a generative AI model. It uses the training dataset obtained in the previous step as input. The server trains the model using a machine learning framework (e.g., TensorFlow, PyTorch) to build a model with corporate-specific strategic planning capabilities. The output is the completed generative AI model.

[0319] Step 3:

[0320] The user uses a terminal to input a prompt message about a specific market. The input is a prompt message that clearly states the market to be investigated and the information to be obtained (e.g., "We are planning to enter the European market with our products. Please tell us about local market trends and competitor information."). The terminal sends this prompt message to the server. The output is a research request sent to the server.

[0321] Step 4:

[0322] The server conducts market research based on prompt messages. The input is the prompt message received from the user. The server collects data on the target market from the internet and commercial databases (e.g., Statista, Euromonitor) and performs demand forecasting and competitive analysis. It uses natural language processing and data mining techniques to perform the analysis and generates a visual report as output.

[0323] Step 5:

[0324] The server retrieves legal information for the target market and generates a procedural checklist. The input is access information to the legal database of the target market. Based on this information, the server collects the latest legal data and generates a list of procedures that the company must follow. The output is a procedural checklist available to the user.

[0325] Step 6:

[0326] The server performs language translation and supports cross-cultural communication. The input is the text that the user will use for communication. Using a translation API, the server translates it into the required language. The output is clearly translated text, which the user can use to communicate smoothly.

[0327] Step 7:

[0328] The server integrates with international trade platforms and logistics systems to optimize logistics management. Inputs include product delivery data and order information. The server utilizes APIs from shipping carriers to develop efficient inventory management and delivery plans. The output is an optimized logistics plan, which users can use to manage international product shipments.

[0329] (Application Example 1)

[0330] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0331] Currently, many small and medium-sized enterprises (SMEs) attempting to enter overseas markets face complex challenges such as market demand analysis, competitor research, and legal compliance. Furthermore, communication barriers due to language and cultural differences hinder business success. An effective support system is needed to comprehensively address these challenges.

[0332] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0333] In this invention, the server includes means for collecting corporate information and training a generative artificial intelligence model, means for collecting and analyzing data on a designated market and performing demand and competition analysis, and means for visually providing market analysis results and suggesting sales opportunities. This enables small and medium-sized enterprises to efficiently grasp the characteristics of their target market and formulate specific market entry strategies.

[0334] "Methods for collecting corporate information and training generative artificial intelligence models" refers to the process of receiving data provided by companies and feeding it to generative artificial intelligence models to learn company-specific knowledge and market characteristics.

[0335] "Means of collecting and analyzing data on a designated market and conducting demand and competition analysis" refers to a function for collecting various data on a target market and analyzing demand trends and the activities of competitors in that market.

[0336] "A means of generating checklists by referring to legal databases in order to provide legal information for the target country of entry" refers to a system for searching the legal database of the target country of entry and creating a checklist that lists the necessary legal procedures.

[0337] "Means of supporting translation and negotiation between different languages" refers to a function that translates texts between different languages ​​and provides support to facilitate negotiations while taking cultural backgrounds into consideration.

[0338] "Means of managing product distribution in conjunction with international e-commerce platforms and logistics systems" refers to management functions that enable products to be delivered to consumers efficiently and effectively by integrating with e-commerce sites and logistics networks.

[0339] "A means of visually providing market analysis results and suggesting sales opportunities" refers to a method of visually presenting analyzed market data to users and proposing specific sales opportunities and strategic actions.

[0340] The system for implementing this invention is primarily built around a server and terminals connected to it. The server first receives business information and product data provided by companies and learns from it using a generative artificial intelligence model. In this process, it accumulates company-specific knowledge and market characteristics, and gains the ability to formulate market entry strategies.

[0341] Users request information about their target market via their devices. The server analyzes the collected market data to assess demand trends and the competitive landscape. This allows companies to clearly understand their product's position in the market and visually grasp sales opportunities.

[0342] Furthermore, the server references legal information for the country or region where the company plans to expand and generates a checklist of necessary legal procedures. This checklist is provided to the user to support smooth compliance with the law.

[0343] The server also provides translation functionality between different languages, facilitating smooth intercultural communication. This allows users to conduct international business negotiations more effectively.

[0344] Finally, the integration of international e-commerce platforms, logistics systems, and servers enables efficient management of product distribution. This system allows companies to deliver products to their target markets quickly and effectively.

[0345] As a concrete example, when an Asian manufacturing company is exploring sales opportunities in the European market, it can send the following prompt to the server:

[0346] "Please analyze the sales opportunities for high-quality, handcrafted furniture in the European market."

[0347] Based on this prompt, the server conducts a detailed market analysis and presents the user with an effective market entry strategy.

[0348] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0349] Step 1:

[0350] Corporate information collection and AI model training

[0351] The server receives business information and product data provided by users. This data is input into a generative artificial intelligence model, which learns company-specific knowledge and market characteristics. As part of data processing, the business information is converted into a structured data format, and analysis is performed by the AI ​​model. As an output, the parameters of the AI ​​model are adjusted, accumulating knowledge useful for future analyses.

[0352] Step 2:

[0353] Market data collection and analysis

[0354] Through a terminal, the user requests an analysis of a specific market from the server. The server collects market data from internet data sources and commercial databases. It analyzes the input market data and calculates demand and competitor trends. In this process, data cleaning and statistical methods are used to derive the analysis results. As output, the server provides the user with a visual analytics report.

[0355] Step 3:

[0356] Reference to legal information and creation of checklists

[0357] The server accesses legal databases in the target country or region to retrieve necessary legal information. Specifically, it uses a database API to obtain the latest legal data. Based on the input legal data, it creates a checklist of legal procedures. As output, a list of specific procedures is generated and provided to the user.

[0358] Step 4:

[0359] Translation and negotiation support features

[0360] The user sends text in a different language as input to the server. The server performs text translation using a translation engine. Translation memory and statistical translation models are used for data processing to provide highly accurate translations. The output translation results support international communication by the user.

[0361] Step 5:

[0362] Integration of e-commerce and logistics management

[0363] The server interacts with international e-commerce platforms and logistics networks. Specifically, it manages product inventory information and shipping options via APIs. Based on the entered order information, it automatically calculates the optimal shipping strategy. As an output, users are provided with an efficient product distribution plan.

[0364] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0365] This invention provides a system to facilitate the entry of Japanese small and medium-sized enterprises (SMEs) into international markets, and further enhances the user experience by combining it with an emotion engine. This system is based on the collection of company information and learning and analysis using a generative artificial intelligence model, and provides a process for formulating entry strategies into specific markets. Furthermore, it supports appropriate market entry by referring to the laws and regulations of the target market and assisting with necessary legal procedures.

[0366] The emotion engine has the ability to analyze the user's emotional state in real time and dynamically adjusts the system interface and the information presented based on the analysis results. This is designed to allow users to use the system more comfortably.

[0367] In a specific implementation, the server receives business data and product information from small and medium-sized enterprises (SMEs) and uses a generative artificial intelligence model to extract key strategic insights from this data. Simultaneously, the server consults legal databases to list legal requirements in the target country. This information is provided to users via terminals to facilitate legal procedures.

[0368] When a user uses the system, the emotion engine analyzes their emotions through input devices such as camera and mouse movements. This data is used by the server to adjust the display content of the system's operation screen and interface according to instructions. For example, if signs of user confusion are detected, the system will immediately display helpful information and hints.

[0369] Furthermore, the server provides translation functionality to support cross-cultural business negotiations. In this process, it takes into account the analysis results of the sentiment engine to appropriately adjust translations and expressions, minimizing misunderstandings between cultures.

[0370] Furthermore, integration with international e-commerce platforms and logistics systems allows users to manage the effective distribution of their products and services. The system can also leverage feedback from an emotional engine to adjust logistics plans and customer service strategies.

[0371] As a concrete example, let's consider a Japanese small-to-medium-sized software company aiming to enter the North American market. This company uses a system to collect local needs and competitive information, supporting strategic planning while simultaneously deepening its understanding of local laws and regulations. Furthermore, by utilizing an emotional engine, it can manage project managers' stress and misunderstandings, supporting optimal decision-making. This enables Japanese companies to leverage their global competitiveness and build success in international markets.

[0372] The following describes the processing flow.

[0373] Step 1:

[0374] The server receives business data and product information provided by small and medium-sized businesses. This includes data sharing via cloud storage such as SkyDrive and Dropbox.

[0375] Step 2:

[0376] The server trains a generative artificial intelligence model based on the received company information. The model learns business knowledge and strategies tailored to the characteristics of each company.

[0377] Step 3:

[0378] Users request specific market research via their devices. The research request includes details such as the target country and research items.

[0379] Step 4:

[0380] The server uses the internet and commercial databases to collect data on the specified market. This is done using crawling technology.

[0381] Step 5:

[0382] The server analyzes market data and generates competitive information and demand forecasts. This helps to concretize the potential markets that companies should enter.

[0383] Step 6:

[0384] The device presents the analysis results to the user as a visual dashboard. Through graphs and charts, users can intuitively grasp the information.

[0385] Step 7:

[0386] The server references legal databases for the target market and generates up-to-date legal information and a checklist of necessary documents for the business.

[0387] Step 8:

[0388] The device displays the necessary legal procedures and their priorities to the user, along with their progress. The user then proceeds with the procedures based on this information.

[0389] Step 9:

[0390] The emotion engine performs real-time sentiment analysis based on data entered by the user through the device's camera and microphone.

[0391] Step 10:

[0392] The server adjusts the system interface based on the results of the sentiment analysis. For example, if the user is stressed, it will display the user guide.

[0393] Step 11:

[0394] The server provides translation support for cross-language communication, offering expressions that take cultural context into account. This facilitates smoother negotiations.

[0395] Step 12:

[0396] The device uses data from its emotion engine to receive user feedback and then suggests the next course of action. This includes the direction and strategy of negotiations.

[0397] Step 13:

[0398] The server integrates with e-commerce platforms and logistics systems to automate product distribution and inventory management.

[0399] Step 14:

[0400] The terminal provides users with real-time information on product delivery status and inventory. This allows companies to operate their supply chains more efficiently.

[0401] (Example 2)

[0402] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0403] These are the challenges faced by Japanese small and medium-sized enterprises (SMEs) when entering international markets: improving the efficiency of information gathering, formulating market strategies, understanding local laws and regulations, and overcoming communication gaps in cross-cultural business negotiations. Furthermore, there is the need to improve usability by dynamically adjusting the system to take into account the emotional state of the user.

[0404] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0405] In this invention, the server includes means for collecting corporate information and training it using a generative AI model, means for collecting information on a specified market and analyzing demand and competition, and means for referencing legal data sources and generating a list in order to provide regulatory information for the target market. This enables smooth entry of small and medium-sized enterprises into international markets and dynamic adjustment of the interface according to the emotional state of the user.

[0406] "Company information" refers to a collection of data and knowledge related to a company's activities, including business operations, product information, and sales data.

[0407] A "generative AI model" is an artificial intelligence system that uses machine learning algorithms to analyze data and generate patterns and insights.

[0408] A "designated market" refers to a specific geographical or industry-specific area in which a company aims to enter, and the market trends and needs within that area are the focus.

[0409] "Regulatory information" refers to data on laws and regulations enacted in a particular country or region, which indicate the requirements that companies must comply with when conducting their business activities.

[0410] "Intercultural translation" is the process of linguistic conversion that enables accurate communication between people with different languages ​​and cultures.

[0411] An "emotion engine" is a technology that analyzes a user's emotional state in real time, evaluating emotions such as stress and confusion by analyzing the user's facial expressions and behavior.

[0412] An "international trading platform" is an online service that supports cross-border commercial transactions and facilitates the sale and purchase of products and services.

[0413] A "logistics system" is a network and process for managing the distribution of products and services, with the aim of efficiently delivering goods to consumers.

[0414] This invention functions as a support system for companies to smoothly enter international markets. Specifically, it is a system whose main components are a server, terminals, and users, which cooperate to perform tasks such as information gathering, data analysis, legal compliance, and sentiment analysis.

[0415] The server receives information provided by companies and uses high-performance data processing servers as hardware. The software incorporates generative AI models built using Python, TensorFlow, and other technologies. This allows the server to learn the company's business knowledge and automatically generate strategies for specified markets. The server also has the ability to connect with online legal databases to retrieve and list the latest legal information.

[0416] The terminal functions as an interface device for the user to interact with the system, using a computer or smart device. A computer vision algorithm is installed as an emotion engine to analyze the user's facial expressions and movements from camera and mouse movements. The emotion data obtained by the terminal is sent to a server and used to dynamically adjust the interface and presented information.

[0417] Users access international market research and translation services through the system. Based on emotional states analyzed by an emotion engine, the terminal immediately provides additional instructions and hints if the user is confused. Furthermore, the server-based translation function enables effective cross-cultural business negotiations.

[0418] As a concrete example, consider the use of the system by a Japanese small-to-medium-sized software company aiming to enter the North American market. This company can efficiently perform the necessary analysis and strategy formulation by inputting the following prompt into the system's generating AI model: "We would like the generating AI model to provide the optimal strategy for a Japanese app development company to enter the American market, as well as the procedures for verifying local laws and regulations."

[0419] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0420] Step 1:

[0421] Users provide the system with information about their company and the requirements of their desired market through an input device. This input includes company product data, performance information, and market entry objectives. This information is sent to a server and stored in a database.

[0422] Step 2:

[0423] The server uses a generative AI model to analyze the input company information. The generative AI model uses the input data to forecast market demand and conduct competitive analysis, generating strategic insights as output. For example, it analyzes the trends of competing companies and proposes optimal pricing and marketing strategies.

[0424] Step 3:

[0425] The server retrieves legal information for the target region from an external database. It receives information about the country or region where the company plans to expand as input and references the relevant regional regulatory data. As output, it generates a list based on the law, providing an overview of the regulations the user must comply with.

[0426] Step 4:

[0427] The device analyzes the user's emotional state through input devices such as a camera and mouse. The input consists of the user's facial expressions and behavioral patterns, which are processed by an emotion engine to identify signs of stress or confusion. The output emotion data is then used by the server in real time to adjust the interface.

[0428] Step 5:

[0429] The server dynamically adjusts the system interface based on the analysis results of the emotion engine. If a specific emotional state is detected, for example, if the system determines that the user is confused, it immediately provides support by displaying additional guidance or explanations on the screen.

[0430] Step 6:

[0431] The server provides translation functionality to support cross-cultural communication. It receives business documents and conversations requiring translation as input, and generates appropriate translated expressions that reflect feedback from an emotion engine, providing them to the user as output.

[0432] (Application Example 2)

[0433] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0434] For businesses expanding into international markets, efficient and strategic decision-making is crucial. However, this presents challenges due to the need to consider diverse market information, legal regulations, and cross-cultural communication, which often requires significant time and effort. Furthermore, in logistics center operations, there is a need for process improvements that take into account the working conditions of the staff.

[0435] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0436] In this invention, the server includes means for collecting business entity information and training it using a generative artificial intelligence model; means for collecting and analyzing information on a designated market and analyzing demand and competition; means for referencing a legal database and generating a checklist to provide legal information for the target market; and means for analyzing the emotions of business personnel using an information presentation device and dynamically adjusting work instructions and information presentations. This enables strategic decision-making regarding entry into international markets and efficient execution of operations at logistics centers.

[0437] "Business entity information" refers to all information related to the operation of an organization that conducts business activities, and specifically includes financial data, product information, customer information, etc.

[0438] A "generative artificial intelligence model" refers to an AI algorithm that has the ability to analyze given data and learn patterns and rules, and is a technology that generates new insights and predictions.

[0439] "Market information" refers to data necessary for business strategy, such as economic trends in a specific industry or region, consumer demand, and the competitive landscape.

[0440] "Legal information" refers to data on laws and regulations necessary for business activities, and is information that clarifies legal requirements that differ from country to country and region to region.

[0441] An "information presentation device" refers to a device that provides information to a user visually or audibly, and includes output devices such as displays and speakers.

[0442] "The emotions of the person in charge of the work" refers to the psychological and emotional state of the personnel performing the work, including stress levels and motivation.

[0443] A "logistics procedures system" refers to an information management system equipped with planning, tracking, and optimization functions for managing the distribution of goods and services.

[0444] The system for implementing this invention consists of multiple hardware and software components. First, the server collects various information about the business entity and stores it in a database, and then uses a generative artificial intelligence model to learn and analyze that information. Specifically, it builds an AI model using Python and TensorFlow, and performs analysis by saving the data to MongoDB.

[0445] Smart glasses and head-mounted displays are used as information presentation devices, providing users with an environment where they can check information in real time while working. Specifically, these include Google Glass and Microsoft HoloLens.

[0446] When a user operates the system, the server uses OpenCV to analyze video data from the camera and displays information such as inventory status and logistics routes. Furthermore, various sensors built into the information display device detect and analyze the user's emotional state, dynamically changing the display of work instructions and support information.

[0447] As a concrete example, imagine a scenario where the information presented to an operator at a logistics center during working hours is adjusted according to the operator's work condition. If the operator is detected to be under high stress, clearer explanations and notifications regarding appropriate break times will be displayed.

[0448] Examples of prompts for the generated AI model include: "Please suggest the optimal shelf arrangement to accommodate new product arrivals. Please calculate a picking route that takes into account the operator's physical condition." In this context, the system's role is to simultaneously provide efficient operational support and improve the user experience.

[0449] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0450] Step 1:

[0451] The server collects business and market information into a database and uses TensorFlow to train a generative artificial intelligence model. Inputs include financial data and market trends of the businesses, while outputs are analyzed demand forecasts and strategic insights. During this process, the data is preprocessed and supplied to the AI ​​model in an optimal format.

[0452] Step 2:

[0453] Users can view real-time information within the logistics center through smart glasses or head-mounted displays. Camera footage is captured by the terminal and sent to the server as input. The server analyzes this data using OpenCV and generates output such as inventory status and optimal logistics routes.

[0454] Step 3:

[0455] The server analyzes the user's emotional state using sensors built into the information display device. Inputs include the user's heart rate and movement data, while outputs include the user's stress level and motivation assessment. Based on this, the server generates appropriate work instructions and support information.

[0456] Step 4:

[0457] Based on the user's emotional state, the server dynamically adjusts the display content of the information presentation device. The input is the emotion analysis result obtained in step 3, and based on this, work instructions and support information are presented in a way that is easy for the user to understand. The output is information that has been adjusted visually or audibly.

[0458] Step 5:

[0459] The server utilizes data obtained from the generative AI model to present users with prompts that support the optimization and strategic planning of logistics centers. The input is the analysis results from the generative AI model, and the output is optimization suggestions in the form of prompts. This process aims to improve operational efficiency and enhance worker experience.

[0460] 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.

[0461] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0462] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0463] [Third Embodiment]

[0464] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0465] 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.

[0466] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0467] 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.

[0468] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0469] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0470] 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.

[0471] 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.

[0472] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0473] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0474] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0475] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0476] In one embodiment of the present invention, a system is provided to solve various challenges that Japanese small and medium-sized enterprises face when entering the global market. This system utilizes a generative artificial intelligence model and performs learning and analysis based on company information to support smooth entry into overseas markets.

[0477] The server first receives business data and product information provided by small and medium-sized enterprises (SMEs) and constructs information based on the companies' business objectives. This information is used as training data for a generative artificial intelligence model, which learns company-specific knowledge and market characteristics. Through this process, the model acquires the ability to formulate market entry strategies tailored to the specific strategies of the companies.

[0478] Next, the user submits a request for market research via the terminal. The server references internet data sources and commercial databases to analyze demand and competitive landscape in the target market. The analysis results are processed into demand forecasts and competitive comparisons and provided to the user in a visual format via the terminal. This information allows companies to assess their specific market position and potential for entry.

[0479] Furthermore, to support compliance with laws and regulations in overseas markets, the server references legal databases of the target country and provides necessary legal procedure information. This includes export and import procedures and required permits and licenses. Users can then proceed with specific legal procedures based on the provided checklist.

[0480] Furthermore, to overcome language and cultural barriers, the server has a function to translate between different languages ​​and support cross-cultural business negotiations. This function allows users to communicate smoothly with overseas companies and lead negotiations to success.

[0481] Finally, to support international trade, the server integrates with existing cross-border e-commerce platforms and logistics systems, providing a means to optimize product shipment and distribution. Users can utilize this system to efficiently send goods and services to overseas markets.

[0482] For example, if a small or medium-sized Japanese manufacturing company is considering entering the European market, utilizing this system would allow them to gain a concrete understanding of local consumer needs and formulate a product strategy that differentiates them from competitors. Furthermore, receiving support for legal procedures and logistics would enable them to enter the market quickly and smoothly.

[0483] The following describes the processing flow.

[0484] Step 1:

[0485] The server receives business data and product information from small and medium-sized enterprises. This includes specific information about the companies' business goals and industries. The received data is used to build training data for generative artificial intelligence models.

[0486] Step 2:

[0487] The server trains a generative artificial intelligence model based on the received data. By learning the company's unique business knowledge and market characteristics, the model can develop market entry strategies tailored to specific markets.

[0488] Step 3:

[0489] Users request market research for specific countries or regions through their devices. This includes demand forecasting and competitive analysis for the target market.

[0490] Step 4:

[0491] The server crawls publicly available data sources and commercial databases on the internet to collect necessary data for market research. This allows it to obtain the latest market information.

[0492] Step 5:

[0493] The server analyzes the collected data to assess demand, supply, and competition. The analysis results are compiled into demand forecasts and competitive comparisons.

[0494] Step 6:

[0495] The terminal visualizes the analysis results and displays them in an easy-to-understand manner for the user. Based on this information, the user can formulate an entry plan.

[0496] Step 7:

[0497] The server accesses legal databases to obtain the latest legal information for the target country. This includes information on import / export procedures and business license acquisition.

[0498] Step 8:

[0499] The server provides the user with a legal checklist. The user then proceeds with the necessary legal procedures based on this checklist.

[0500] Step 9:

[0501] Users use their devices to input or update details of negotiations with overseas companies. This includes communication history and negotiation progress.

[0502] Step 10:

[0503] The server utilizes translation capabilities to translate emails and documents between different languages. Furthermore, it automatically adjusts the content to take cultural context into consideration.

[0504] Step 11:

[0505] The device provides users with notifications regarding negotiation details and next steps, supporting smooth communication.

[0506] Step 12:

[0507] The server integrates with international e-commerce platforms and logistics systems to optimize product distribution and management. This includes inventory management and delivery route optimization.

[0508] Step 13:

[0509] The terminal notifies the user in real time of the delivery status of the product and the progress of the logistics process. This allows the user to respond quickly to unforeseen circumstances related to distribution.

[0510] (Example 1)

[0511] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0512] Traditionally, small and medium-sized enterprises (SMEs) have faced numerous challenges when entering global markets, including thorough market research, legal compliance, language barriers, and logistics management. A comprehensive system is needed to address these challenges and support overseas expansion efficiently and effectively.

[0513] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0514] In this invention, the server includes means for aggregating business information and training strategies using a generative AI model, means for collecting data related to a specific market and performing demand forecasting and competitive analysis, and means for obtaining legal information of the target market and generating procedural checklists. This enables companies to efficiently conduct market research, prepare for legal procedures, and smoothly enter overseas markets.

[0515] "Business information" refers to all data related to a company's operations, including sales, inventory, customer information, and product information.

[0516] A "generative AI model" is an artificial intelligence technology that learns from large amounts of data and formulates knowledge and strategies tailored to specific purposes.

[0517] "Data collection" refers to the process of systematically gathering necessary information, and involves obtaining information from the internet or databases.

[0518] "Demand forecasting" is a method of numerically predicting the future willingness to purchase a particular product or service.

[0519] "Competitive analysis" is the process of analyzing the activities and characteristics of competitors within the same market.

[0520] "Legal information" refers to information that provides details about the laws and regulations applicable in a specific region.

[0521] A "procedure checklist" is a comprehensive list that outlines the steps required for a specific task or legal procedure.

[0522] "Language translation" is the process of replacing a text written in one language with a text written in another language.

[0523] "Intercultural negotiation" refers to negotiations conducted between people with different cultural backgrounds.

[0524] An "international commercial trading platform" is an integrated system for conducting online international buying and selling transactions of goods and services.

[0525] A "logistics management system" is a general term for technologies and methods used to efficiently manage the distribution process of goods.

[0526] A "user interface" refers to the part of a system or application that provides the user interface and input methods for interacting with it.

[0527] "Visual information" refers to information presented in a visual format, including graphs, diagrams, and report formats.

[0528] The system implementing this invention utilizes generative AI models to provide comprehensive support for Japanese small and medium-sized enterprises to enter the global market. This system includes three entities: a server, a terminal, and a user, each playing a specific role.

[0529] The server first aggregates business information provided by companies. This information is collected via APIs from databases such as ERP and CRM systems. Based on this data, it trains a generative AI model and uses the learned knowledge to formulate market entry strategies. Machine learning frameworks such as TensorFlow and PyTorch are used for this training. The server also accesses online data sources and commercial databases to perform demand forecasting and competitive analysis for specified markets, and processes the results as visual information.

[0530] Through the terminal, the user enters a prompt about a specific market and requests research from the server. For example, the user might enter, "We are planning to enter the European market with our products. Please tell me about local market trends and competitive information." The server receives this input, retrieves the necessary information, and analyzes it.

[0531] The server organizes legal information for the target country and provides users with procedural checklists. This allows users to efficiently proceed with the necessary procedures. Furthermore, to facilitate cross-cultural communication, the server performs language translation and provides negotiation support.

[0532] Finally, the server integrates with logistics management systems and international trade platforms to optimize product distribution. This functionality enables users to efficiently deliver products and services to overseas markets.

[0533] Thus, the present invention aims to support small and medium-sized enterprises in entering the global market and to enable smooth business development through its diverse functions.

[0534] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0535] Step 1:

[0536] The server collects business information from companies. The input is ERP and CRM data provided by companies via APIs. The server collects this data and stores it in a database. Next, this data is preprocessed to serve as a training dataset for a generative AI model. The output is the training dataset for the generative AI model to learn from.

[0537] Step 2:

[0538] The server learns corporate strategies using a generative AI model. It uses the training dataset obtained in the previous step as input. The server trains the model using a machine learning framework (e.g., TensorFlow, PyTorch) to build a model with corporate-specific strategic planning capabilities. The output is the completed generative AI model.

[0539] Step 3:

[0540] The user uses a terminal to input a prompt message about a specific market. The input is a prompt message that clearly states the market to be investigated and the information to be obtained (e.g., "We are planning to enter the European market with our products. Please tell us about local market trends and competitor information."). The terminal sends this prompt message to the server. The output is a research request sent to the server.

[0541] Step 4:

[0542] The server conducts market research based on prompt messages. The input is the prompt message received from the user. The server collects data on the target market from the internet and commercial databases (e.g., Statista, Euromonitor) and performs demand forecasting and competitive analysis. It uses natural language processing and data mining techniques to perform the analysis and generates a visual report as output.

[0543] Step 5:

[0544] The server retrieves legal information for the target market and generates a procedural checklist. The input is access information to the legal database of the target market. Based on this information, the server collects the latest legal data and generates a list of procedures that the company must follow. The output is a procedural checklist available to the user.

[0545] Step 6:

[0546] The server performs language translation and supports cross-cultural communication. The input is the text that the user will use for communication. Using a translation API, the server translates it into the required language. The output is clearly translated text, which the user can use to communicate smoothly.

[0547] Step 7:

[0548] The server integrates with international trade platforms and logistics systems to optimize logistics management. Inputs include product delivery data and order information. The server utilizes APIs from shipping carriers to develop efficient inventory management and delivery plans. The output is an optimized logistics plan, which users can use to manage international product shipments.

[0549] (Application Example 1)

[0550] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0551] Currently, many small and medium-sized enterprises (SMEs) attempting to enter overseas markets face complex challenges such as market demand analysis, competitor research, and legal compliance. Furthermore, communication barriers due to language and cultural differences hinder business success. An effective support system is needed to comprehensively address these challenges.

[0552] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0553] In this invention, the server includes means for collecting corporate information and training a generative artificial intelligence model, means for collecting and analyzing data on a designated market and performing demand and competition analysis, and means for visually providing market analysis results and suggesting sales opportunities. This enables small and medium-sized enterprises to efficiently grasp the characteristics of their target market and formulate specific market entry strategies.

[0554] "Methods for collecting corporate information and training generative artificial intelligence models" refers to the process of receiving data provided by companies and feeding it to generative artificial intelligence models to learn company-specific knowledge and market characteristics.

[0555] "Means of collecting and analyzing data on a designated market and conducting demand and competition analysis" refers to a function for collecting various data on a target market and analyzing demand trends and the activities of competitors in that market.

[0556] "A means of generating checklists by referring to legal databases in order to provide legal information for the target country of entry" refers to a system for searching the legal database of the desired country of entry and creating a checklist that lists the necessary legal procedures.

[0557] "Means of supporting translation and negotiation between different languages" refers to a function that translates texts between different languages ​​and provides support to facilitate negotiations while taking cultural backgrounds into consideration.

[0558] "Means of managing product distribution in conjunction with international e-commerce platforms and logistics systems" refers to management functions that enable products to be delivered to consumers efficiently and effectively by integrating with e-commerce sites and logistics networks.

[0559] "A means of visually providing market analysis results and suggesting sales opportunities" refers to a method of visually presenting analyzed market data to users and proposing specific sales opportunities and strategic actions.

[0560] The system for implementing this invention is primarily built around a server and terminals connected to it. The server first receives business information and product data provided by companies and learns from it using a generative artificial intelligence model. In this process, it accumulates company-specific knowledge and market characteristics, and gains the ability to formulate market entry strategies.

[0561] Users request information about their target market via their devices. The server analyzes the collected market data to assess demand trends and the competitive landscape. This allows companies to clearly understand their product's position in the market and visually grasp sales opportunities.

[0562] Furthermore, the server references legal information for the country or region where the company plans to expand and generates a checklist of necessary legal procedures. This checklist is provided to the user to support smooth compliance with the law.

[0563] The server also provides translation functionality between different languages, facilitating smooth intercultural communication. This allows users to conduct international business negotiations more effectively.

[0564] Finally, the integration of international e-commerce platforms, logistics systems, and servers enables efficient management of product distribution. This system allows companies to deliver products to their target markets quickly and effectively.

[0565] As a concrete example, when an Asian manufacturing company is exploring sales opportunities in the European market, it can send the following prompt to the server:

[0566] "Please analyze the sales opportunities for high-quality, handcrafted furniture in the European market."

[0567] Based on this prompt, the server conducts a detailed market analysis and presents the user with an effective market entry strategy.

[0568] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0569] Step 1:

[0570] Corporate information collection and AI model training

[0571] The server receives business information and product data provided by users. This data is input into a generative artificial intelligence model, which learns company-specific knowledge and market characteristics. As part of data processing, the business information is converted into a structured data format, and analysis is performed by the AI ​​model. As an output, the parameters of the AI ​​model are adjusted, accumulating knowledge useful for future analyses.

[0572] Step 2:

[0573] Market data collection and analysis

[0574] Through a terminal, the user requests an analysis of a specific market from the server. The server collects market data from internet data sources and commercial databases. It analyzes the input market data and calculates demand and competitor trends. In this process, data cleaning and statistical methods are used to derive the analysis results. As output, the server provides the user with a visual analytics report.

[0575] Step 3:

[0576] Reference to legal information and creation of checklists

[0577] The server accesses legal databases in the target country or region to retrieve necessary legal information. Specifically, it uses a database API to obtain the latest legal data. Based on the input legal data, it creates a checklist of legal procedures. As output, a list of specific procedures is generated and provided to the user.

[0578] Step 4:

[0579] Translation and negotiation support features

[0580] The user sends text in a different language as input to the server. The server performs text translation using a translation engine. Translation memory and statistical translation models are used for data processing to provide highly accurate translations. The output translation results support international communication by the user.

[0581] Step 5:

[0582] Integration of e-commerce and logistics management

[0583] The server interacts with international e-commerce platforms and logistics networks. Specifically, it manages product inventory information and shipping options via APIs. Based on the entered order information, it automatically calculates the optimal shipping strategy. As an output, users are provided with an efficient product distribution plan.

[0584] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0585] This invention provides a system to facilitate the smooth entry of Japanese small and medium-sized enterprises (SMEs) into international markets, and further enhances the user experience by combining it with an emotion engine. This system is based on the collection of company information and learning and analysis using a generative artificial intelligence model, and provides a process for formulating entry strategies into specific markets. Furthermore, it supports appropriate market entry by referring to the laws and regulations of the target market and assisting with necessary legal procedures.

[0586] The emotion engine has the ability to analyze the user's emotional state in real time and dynamically adjusts the system interface and the information presented based on the analysis results. This is designed to allow users to use the system more comfortably.

[0587] In a specific implementation, the server receives business data and product information from small and medium-sized enterprises (SMEs) and uses a generative artificial intelligence model to extract key strategic insights from this data. Simultaneously, the server consults legal databases to list legal requirements in the target country. This information is provided to users via terminals to facilitate legal procedures.

[0588] When a user uses the system, the emotion engine analyzes their emotions through input devices such as camera and mouse movements. This data is used by the server to adjust the display content of the system's operation screen and interface according to instructions. For example, if signs of user confusion are detected, the system will immediately display helpful information and hints.

[0589] Furthermore, the server provides translation functionality to support cross-cultural business negotiations. In this process, it takes into account the analysis results of the sentiment engine to appropriately adjust translations and expressions, minimizing misunderstandings between cultures.

[0590] Furthermore, integration with international e-commerce platforms and logistics systems allows users to manage the effective distribution of their products and services. The system can also leverage feedback from an emotional engine to adjust logistics plans and customer service strategies.

[0591] As a concrete example, let's consider a Japanese small-to-medium-sized software company aiming to enter the North American market. This company uses a system to collect local needs and competitive information, supporting strategic planning while simultaneously deepening its understanding of local laws and regulations. Furthermore, by utilizing an emotional engine, it can manage project managers' stress and misunderstandings, supporting optimal decision-making. This enables Japanese companies to leverage their global competitiveness and build success in international markets.

[0592] The following describes the processing flow.

[0593] Step 1:

[0594] The server receives business data and product information provided by small and medium-sized businesses. This includes data sharing via cloud storage such as SkyDrive and Dropbox.

[0595] Step 2:

[0596] The server trains a generative artificial intelligence model based on the received company information. The model learns business knowledge and strategies tailored to the characteristics of each company.

[0597] Step 3:

[0598] Users request specific market research via their devices. The research request includes details such as the target country and research items.

[0599] Step 4:

[0600] The server uses the internet and commercial databases to collect data on the specified market. This is done using crawling technology.

[0601] Step 5:

[0602] The server analyzes market data and generates competitive information and demand forecasts. This helps to concretize the potential markets that companies should enter.

[0603] Step 6:

[0604] The device presents the analysis results to the user as a visual dashboard. Through graphs and charts, users can intuitively grasp the information.

[0605] Step 7:

[0606] The server references legal databases for the target market and generates up-to-date legal information and a checklist of necessary documents for the business.

[0607] Step 8:

[0608] The device displays the necessary legal procedures and their priorities to the user, along with their progress. The user then proceeds with the procedures based on this information.

[0609] Step 9:

[0610] The emotion engine performs real-time sentiment analysis based on data entered by the user through the device's camera and microphone.

[0611] Step 10:

[0612] The server adjusts the system interface based on the results of the sentiment analysis. For example, if the user is stressed, it will display the user guide.

[0613] Step 11:

[0614] The server provides translation support for cross-language communication, offering expressions that take cultural context into account. This facilitates smoother negotiations.

[0615] Step 12:

[0616] The device uses data from its emotion engine to receive user feedback and then suggests the next course of action. This includes the direction and strategy of negotiations.

[0617] Step 13:

[0618] The server integrates with e-commerce platforms and logistics systems to automate product distribution and inventory management.

[0619] Step 14:

[0620] The terminal provides users with real-time information on product delivery status and inventory. This allows companies to operate their supply chains more efficiently.

[0621] (Example 2)

[0622] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0623] These are the challenges faced by Japanese small and medium-sized enterprises (SMEs) when entering international markets: improving the efficiency of information gathering, formulating market strategies, understanding local laws and regulations, and overcoming communication gaps in cross-cultural business negotiations. Furthermore, there is the need to improve usability by dynamically adjusting the system to take into account the emotional state of the user.

[0624] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0625] In this invention, the server includes means for collecting corporate information and training it using a generative AI model, means for collecting information on a specified market and analyzing demand and competition, and means for referencing legal data sources and generating a list in order to provide regulatory information for the target market. This enables smooth entry of small and medium-sized enterprises into international markets and dynamic adjustment of the interface according to the emotional state of the user.

[0626] "Company information" refers to a collection of data and knowledge related to a company's activities, including business operations, product information, and sales data.

[0627] A "generative AI model" is an artificial intelligence system that uses machine learning algorithms to analyze data and generate patterns and insights.

[0628] A "designated market" refers to a specific geographical or industry-specific area in which a company aims to enter, and the market trends and needs within that area are the focus.

[0629] "Regulatory information" refers to data on laws and regulations enacted in a particular country or region, which indicate the requirements that companies must comply with when conducting their business activities.

[0630] "Intercultural translation" is the process of linguistic conversion that enables accurate communication between people with different languages ​​and cultures.

[0631] An "emotion engine" is a technology that analyzes a user's emotional state in real time, evaluating emotions such as stress and confusion by analyzing the user's facial expressions and behavior.

[0632] An "international trading platform" is an online service that supports cross-border commercial transactions and facilitates the sale and purchase of products and services.

[0633] A "logistics system" is a network and process for managing the distribution of products and services, with the aim of efficiently delivering goods to consumers.

[0634] This invention functions as a support system for companies to smoothly enter international markets. Specifically, it is a system whose main components are a server, terminals, and users, which cooperate to perform tasks such as information gathering, data analysis, legal compliance, and sentiment analysis.

[0635] The server receives information provided by companies and uses high-performance data processing servers as hardware. The software incorporates generative AI models built using Python, TensorFlow, and other technologies. This allows the server to learn the company's business knowledge and automatically generate strategies for specified markets. The server also has the ability to connect with online legal databases to retrieve and list the latest legal information.

[0636] The terminal functions as an interface device for the user to interact with the system, using a computer or smart device. A computer vision algorithm is installed as an emotion engine to analyze the user's facial expressions and movements from camera and mouse movements. The emotion data obtained by the terminal is sent to a server and used to dynamically adjust the interface and presented information.

[0637] Users access international market research and translation services through the system. Based on emotional states analyzed by an emotion engine, the terminal immediately provides additional instructions and hints if the user is confused. Furthermore, the server-based translation function enables effective cross-cultural business negotiations.

[0638] As a concrete example, consider the use of the system by a Japanese small-to-medium-sized software company aiming to enter the North American market. This company can efficiently perform the necessary analysis and strategy formulation by inputting the following prompt into the system's generating AI model: "We would like the generating AI model to provide the optimal strategy for a Japanese app development company to enter the American market, as well as the procedures for verifying local laws and regulations."

[0639] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0640] Step 1:

[0641] Users provide the system with information about their company and the requirements of their desired market through an input device. This input includes company product data, performance information, and market entry objectives. This information is sent to a server and stored in a database.

[0642] Step 2:

[0643] The server uses a generative AI model to analyze the input company information. The generative AI model uses the input data to forecast market demand and conduct competitive analysis, generating strategic insights as output. For example, it analyzes the trends of competing companies and proposes optimal pricing and marketing strategies.

[0644] Step 3:

[0645] The server retrieves legal information for the target region from an external database. It receives information about the country or region where the company plans to expand as input and references the relevant regional regulatory data. As output, it generates a list based on the law, providing an overview of the regulations the user must comply with.

[0646] Step 4:

[0647] The device analyzes the user's emotional state through input devices such as a camera and mouse. The input consists of the user's facial expressions and behavioral patterns, which are processed by an emotion engine to identify signs of stress or confusion. The output emotion data is then used by the server in real time to adjust the interface.

[0648] Step 5:

[0649] The server dynamically adjusts the system interface based on the analysis results of the emotion engine. If a specific emotional state is detected, for example, if the system determines that the user is confused, it immediately provides support by displaying additional guidance or explanations on the screen.

[0650] Step 6:

[0651] The server provides translation functionality to support cross-cultural communication. It receives business documents and conversations requiring translation as input, and generates appropriate translated expressions that reflect feedback from an emotion engine, providing them to the user as output.

[0652] (Application Example 2)

[0653] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0654] For businesses expanding into international markets, efficient and strategic decision-making is crucial. However, this presents challenges due to the need to consider diverse market information, legal regulations, and cross-cultural communication, which often requires significant time and effort. Furthermore, in logistics center operations, there is a need for process improvements that take into account the working conditions of the staff.

[0655] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0656] In this invention, the server includes means for collecting business entity information and training it using a generative artificial intelligence model; means for collecting and analyzing information on a designated market and analyzing demand and competition; means for referencing a legal database and generating a checklist to provide legal information for the target market; and means for analyzing the emotions of business personnel using an information presentation device and dynamically adjusting work instructions and information presentations. This enables strategic decision-making regarding entry into international markets and efficient execution of operations at logistics centers.

[0657] "Business entity information" refers to all information related to the operation of an organization that conducts business activities, and specifically includes financial data, product information, customer information, etc.

[0658] A "generative artificial intelligence model" refers to an AI algorithm that has the ability to analyze given data and learn patterns and rules, and is a technology that generates new insights and predictions.

[0659] "Market information" refers to data necessary for business strategy, such as economic trends in a specific industry or region, consumer demand, and the competitive landscape.

[0660] "Legal information" refers to data on laws and regulations necessary for business activities, and is information that clarifies legal requirements that differ from country to country and region to region.

[0661] An "information presentation device" refers to a device that provides information to a user visually or audibly, and includes output devices such as displays and speakers.

[0662] "The emotions of the person in charge of the work" refers to the psychological and emotional state of the personnel performing the work, including stress levels and motivation.

[0663] A "logistics procedures system" refers to an information management system equipped with planning, tracking, and optimization functions for managing the distribution of goods and services.

[0664] The system for implementing this invention consists of multiple hardware and software components. First, the server collects various information about the business entity and stores it in a database, and then uses a generative artificial intelligence model to learn and analyze that information. Specifically, it builds an AI model using Python and TensorFlow, and performs analysis by saving the data to MongoDB.

[0665] Smart glasses and head-mounted displays are used as information presentation devices, providing users with an environment where they can check information in real time while working. Specifically, these include Google Glass and Microsoft HoloLens.

[0666] When a user operates the system, the server uses OpenCV to analyze video data from the camera and displays information such as inventory status and logistics routes. Furthermore, various sensors built into the information display device detect and analyze the user's emotional state, dynamically changing the display of work instructions and support information.

[0667] As a concrete example, imagine a scenario where the information presented to an operator at a logistics center during working hours is adjusted according to the operator's work condition. If the operator is detected to be under high stress, clearer explanations and notifications regarding appropriate break times will be displayed.

[0668] Examples of prompts for the generated AI model include: "Please suggest the optimal shelf arrangement to accommodate new product arrivals. Please calculate a picking route that takes into account the operator's physical condition." In this context, the system's role is to simultaneously provide efficient operational support and improve the user experience.

[0669] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0670] Step 1:

[0671] The server collects business and market information into a database and uses TensorFlow to train a generative artificial intelligence model. Inputs include financial data and market trends of the businesses, while outputs are analyzed demand forecasts and strategic insights. During this process, the data is preprocessed and supplied to the AI ​​model in an optimal format.

[0672] Step 2:

[0673] Users can view real-time information within the logistics center through smart glasses or head-mounted displays. Camera footage is captured by the terminal and sent to the server as input. The server analyzes this data using OpenCV and generates output such as inventory status and optimal logistics routes.

[0674] Step 3:

[0675] The server analyzes the user's emotional state using sensors built into the information display device. Inputs include the user's heart rate and movement data, while outputs include the user's stress level and motivation assessment. Based on this, the server generates appropriate work instructions and support information.

[0676] Step 4:

[0677] Based on the user's emotional state, the server dynamically adjusts the display content of the information presentation device. The input is the emotion analysis result obtained in step 3, and based on this, work instructions and support information are presented in a way that is easy for the user to understand. The output is information that has been adjusted visually or audibly.

[0678] Step 5:

[0679] The server utilizes data obtained from the generative AI model to present users with prompts that support the optimization and strategic planning of logistics centers. The input is the analysis results from the generative AI model, and the output is optimization suggestions in the form of prompts. This process aims to improve operational efficiency and enhance worker experience.

[0680] 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.

[0681] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0682] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0683] [Fourth Embodiment]

[0684] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0685] 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.

[0686] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0687] 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.

[0688] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0689] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0690] 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.

[0691] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0692] 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.

[0693] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0694] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0695] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0696] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0697] In one embodiment of the present invention, a system is provided to solve various challenges that Japanese small and medium-sized enterprises face when entering the global market. This system utilizes a generative artificial intelligence model and performs learning and analysis based on company information to support smooth entry into overseas markets.

[0698] The server first receives business data and product information provided by small and medium-sized enterprises (SMEs) and constructs information based on the companies' business objectives. This information is used as training data for a generative artificial intelligence model, which learns company-specific knowledge and market characteristics. Through this process, the model acquires the ability to formulate market entry strategies tailored to the specific strategies of the companies.

[0699] Next, the user submits a request for market research via the terminal. The server references internet data sources and commercial databases to analyze demand and competitive landscape in the target market. The analysis results are processed into demand forecasts and competitive comparisons and provided to the user in a visual format via the terminal. This information allows companies to assess their specific market position and potential for entry.

[0700] Furthermore, to support compliance with laws and regulations in overseas markets, the server references legal databases of the target country and provides necessary legal procedure information. This includes export and import procedures and required permits and licenses. Users can then proceed with specific legal procedures based on the provided checklist.

[0701] Furthermore, to overcome language and cultural barriers, the server has a function to translate between different languages ​​and support cross-cultural business negotiations. This function allows users to communicate smoothly with overseas companies and lead negotiations to success.

[0702] Finally, to support international trade, the server integrates with existing cross-border e-commerce platforms and logistics systems, providing a means to optimize product shipment and distribution. Users can utilize this system to efficiently send goods and services to overseas markets.

[0703] For example, if a small or medium-sized Japanese manufacturing company is considering entering the European market, utilizing this system would allow them to gain a concrete understanding of local consumer needs and formulate a product strategy that differentiates them from competitors. Furthermore, receiving support for legal procedures and logistics would enable them to enter the market quickly and smoothly.

[0704] The following describes the processing flow.

[0705] Step 1:

[0706] The server receives business data and product information from small and medium-sized enterprises. This includes specific information about the companies' business goals and industries. The received data is used to build training data for generative artificial intelligence models.

[0707] Step 2:

[0708] The server trains a generative artificial intelligence model based on the received data. By learning the company's unique business knowledge and market characteristics, the model can develop market entry strategies tailored to specific markets.

[0709] Step 3:

[0710] Users request market research for specific countries or regions through their devices. This includes demand forecasting and competitive analysis for the target market.

[0711] Step 4:

[0712] The server crawls publicly available data sources and commercial databases on the internet to collect necessary data for market research. This allows it to obtain the latest market information.

[0713] Step 5:

[0714] The server analyzes the collected data to assess demand, supply, and competition. The analysis results are compiled into demand forecasts and competitive comparisons.

[0715] Step 6:

[0716] The terminal visualizes the analysis results and displays them in an easy-to-understand manner for the user. Based on this information, the user can formulate an entry plan.

[0717] Step 7:

[0718] The server accesses legal databases to obtain the latest legal information for the target country. This includes information on import / export procedures and business license acquisition.

[0719] Step 8:

[0720] The server provides the user with a legal checklist. The user then proceeds with the necessary legal procedures based on this checklist.

[0721] Step 9:

[0722] Users use their devices to input or update details of negotiations with overseas companies. This includes communication history and negotiation progress.

[0723] Step 10:

[0724] The server utilizes translation capabilities to translate emails and documents between different languages. Furthermore, it automatically adjusts the content to take cultural context into consideration.

[0725] Step 11:

[0726] The device provides users with notifications regarding negotiation details and next steps, supporting smooth communication.

[0727] Step 12:

[0728] The server integrates with international e-commerce platforms and logistics systems to optimize product distribution and management. This includes inventory management and delivery route optimization.

[0729] Step 13:

[0730] The terminal notifies the user in real time of the delivery status of the product and the progress of the logistics process. This allows the user to respond quickly to unforeseen circumstances related to distribution.

[0731] (Example 1)

[0732] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0733] Traditionally, small and medium-sized enterprises (SMEs) have faced numerous challenges when entering global markets, including thorough market research, legal compliance, language barriers, and logistics management. A comprehensive system is needed to address these challenges and support overseas expansion efficiently and effectively.

[0734] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0735] In this invention, the server includes means for aggregating business information and training strategies using a generative AI model, means for collecting data related to a specific market and performing demand forecasting and competitive analysis, and means for obtaining legal information of the target market and generating procedural checklists. This enables companies to efficiently conduct market research, prepare for legal procedures, and smoothly enter overseas markets.

[0736] "Business information" refers to all data related to a company's operations, including sales, inventory, customer information, and product information.

[0737] A "generative AI model" is an artificial intelligence technology that learns from large amounts of data and formulates knowledge and strategies tailored to specific purposes.

[0738] "Data collection" refers to the process of systematically gathering necessary information, and involves obtaining information from the internet or databases.

[0739] "Demand forecasting" is a method of numerically predicting the future willingness to purchase a particular product or service.

[0740] "Competitive analysis" is the process of analyzing the activities and characteristics of competitors within the same market.

[0741] "Legal information" refers to information that provides details about the laws and regulations applicable in a specific region.

[0742] A "procedure checklist" is a comprehensive list that outlines the steps required for a specific task or legal procedure.

[0743] "Language translation" is the process of replacing a text written in one language with a text written in another language.

[0744] "Intercultural negotiation" refers to negotiations conducted between people with different cultural backgrounds.

[0745] An "international commercial trading platform" is an integrated system for conducting online international buying and selling transactions of goods and services.

[0746] A "logistics management system" is a general term for technologies and methods used to efficiently manage the distribution process of goods.

[0747] A "user interface" refers to the part of a system or application that provides the user interface and input methods for interacting with it.

[0748] "Visual information" refers to information presented in a visual format, including graphs, diagrams, and report formats.

[0749] The system implementing this invention utilizes generative AI models to provide comprehensive support for Japanese small and medium-sized enterprises to enter the global market. This system includes three entities: a server, a terminal, and a user, each playing a specific role.

[0750] The server first aggregates business information provided by companies. This information is collected via APIs from databases such as ERP and CRM systems. Based on this data, it trains a generative AI model and uses the learned knowledge to formulate market entry strategies. Machine learning frameworks such as TensorFlow and PyTorch are used for this training. The server also accesses online data sources and commercial databases to perform demand forecasting and competitive analysis for specified markets, and processes the results as visual information.

[0751] Through the terminal, the user enters a prompt about a specific market and requests research from the server. For example, the user might enter, "We are planning to enter the European market with our products. Please tell me about local market trends and competitive information." The server receives this input, retrieves the necessary information, and analyzes it.

[0752] The server organizes legal information for the target country and provides users with procedural checklists. This allows users to efficiently proceed with the necessary procedures. Furthermore, to facilitate cross-cultural communication, the server performs language translation and provides negotiation support.

[0753] Finally, the server integrates with logistics management systems and international trade platforms to optimize product distribution. This functionality enables users to efficiently deliver products and services to overseas markets.

[0754] Thus, the present invention aims to support small and medium-sized enterprises in entering the global market and to enable smooth business development through its diverse functions.

[0755] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0756] Step 1:

[0757] The server collects business information from companies. The input is ERP and CRM data provided by companies via APIs. The server collects this data and stores it in a database. Next, this data is preprocessed to serve as a training dataset for a generative AI model. The output is the training dataset for the generative AI model to learn from.

[0758] Step 2:

[0759] The server learns corporate strategies using a generative AI model. It uses the training dataset obtained in the previous step as input. The server trains the model using a machine learning framework (e.g., TensorFlow, PyTorch) to build a model with corporate-specific strategic planning capabilities. The output is the completed generative AI model.

[0760] Step 3:

[0761] The user uses a terminal to input a prompt message about a specific market. The input is a prompt message that clearly states the market to be investigated and the information to be obtained (e.g., "We are planning to enter the European market with our products. Please tell us about local market trends and competitor information."). The terminal sends this prompt message to the server. The output is a research request sent to the server.

[0762] Step 4:

[0763] The server conducts market research based on prompt messages. The input is the prompt message received from the user. The server collects data on the target market from the internet and commercial databases (e.g., Statista, Euromonitor) and performs demand forecasting and competitive analysis. It uses natural language processing and data mining techniques to perform the analysis and generates a visual report as output.

[0764] Step 5:

[0765] The server retrieves legal information for the target market and generates a procedural checklist. The input is access information to the legal database of the target market. Based on this information, the server collects the latest legal data and generates a list of procedures that the company must follow. The output is a procedural checklist available to the user.

[0766] Step 6:

[0767] The server performs language translation and supports cross-cultural communication. The input is the text that the user will use for communication. Using a translation API, the server translates it into the required language. The output is clearly translated text, which the user can use to communicate smoothly.

[0768] Step 7:

[0769] The server integrates with international trade platforms and logistics systems to optimize logistics management. Inputs include product delivery data and order information. The server utilizes APIs from shipping carriers to develop efficient inventory management and delivery plans. The output is an optimized logistics plan, which users can use to manage international product shipments.

[0770] (Application Example 1)

[0771] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0772] Currently, many small and medium-sized enterprises (SMEs) attempting to enter overseas markets face complex challenges such as market demand analysis, competitor research, and legal compliance. Furthermore, communication barriers due to language and cultural differences hinder business success. An effective support system is needed to comprehensively address these challenges.

[0773] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0774] In this invention, the server includes means for collecting corporate information and training a generative artificial intelligence model, means for collecting and analyzing data on a designated market and performing demand and competition analysis, and means for visually providing market analysis results and suggesting sales opportunities. This enables small and medium-sized enterprises to efficiently grasp the characteristics of their target market and formulate specific market entry strategies.

[0775] "Methods for collecting corporate information and training generative artificial intelligence models" refers to the process of receiving data provided by companies and feeding it to generative artificial intelligence models to learn company-specific knowledge and market characteristics.

[0776] "Means of collecting and analyzing data on a designated market and conducting demand and competition analysis" refers to a function for collecting various data on a target market and analyzing demand trends and the activities of competitors in that market.

[0777] "A means of generating checklists by referring to legal databases in order to provide legal information for the target country of entry" refers to a system for searching the legal database of the desired country of entry and creating a checklist that lists the necessary legal procedures.

[0778] "Means of supporting translation and negotiation between different languages" refers to a function that translates texts between different languages ​​and provides support to facilitate negotiations while taking cultural backgrounds into consideration.

[0779] "Means of managing product distribution in conjunction with international e-commerce platforms and logistics systems" refers to management functions that enable products to be delivered to consumers efficiently and effectively by integrating with e-commerce sites and logistics networks.

[0780] "A means of visually providing market analysis results and suggesting sales opportunities" refers to a method of visually presenting analyzed market data to users and proposing specific sales opportunities and strategic actions.

[0781] The system for implementing this invention is primarily built around a server and terminals connected to it. The server first receives business information and product data provided by companies and learns from it using a generative artificial intelligence model. In this process, it accumulates company-specific knowledge and market characteristics, and gains the ability to formulate market entry strategies.

[0782] Users request information about their target market via their devices. The server analyzes the collected market data to assess demand trends and the competitive landscape. This allows companies to clearly understand their product's position in the market and visually grasp sales opportunities.

[0783] Furthermore, the server references legal information for the country or region where the company plans to expand and generates a checklist of necessary legal procedures. This checklist is provided to the user to support smooth compliance with the law.

[0784] The server also provides translation functionality between different languages, facilitating smooth intercultural communication. This allows users to conduct international business negotiations more effectively.

[0785] Finally, the integration of international e-commerce platforms, logistics systems, and servers enables efficient management of product distribution. This system allows companies to deliver products to their target markets quickly and effectively.

[0786] As a concrete example, when an Asian manufacturing company is exploring sales opportunities in the European market, it can send the following prompt to the server:

[0787] "Please analyze the sales opportunities for high-quality, handcrafted furniture in the European market."

[0788] Based on this prompt, the server conducts a detailed market analysis and presents the user with an effective market entry strategy.

[0789] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0790] Step 1:

[0791] Corporate information collection and AI model training

[0792] The server receives business information and product data provided by users. This data is input into a generative artificial intelligence model, which learns company-specific knowledge and market characteristics. As part of data processing, the business information is converted into a structured data format, and analysis is performed by the AI ​​model. As an output, the parameters of the AI ​​model are adjusted, accumulating knowledge useful for future analyses.

[0793] Step 2:

[0794] Market data collection and analysis

[0795] Through a terminal, the user requests an analysis of a specific market from the server. The server collects market data from internet data sources and commercial databases. It analyzes the input market data and calculates demand and competitor trends. In this process, data cleaning and statistical methods are used to derive the analysis results. As output, the server provides the user with a visual analytics report.

[0796] Step 3:

[0797] Reference to legal information and creation of checklists

[0798] The server accesses legal databases in the target country or region to retrieve necessary legal information. Specifically, it uses a database API to obtain the latest legal data. Based on the input legal data, it creates a checklist of legal procedures. As output, a list of specific procedures is generated and provided to the user.

[0799] Step 4:

[0800] Translation and negotiation support features

[0801] The user sends text in a different language as input to the server. The server performs text translation using a translation engine. Translation memory and statistical translation models are used for data processing to provide highly accurate translations. The output translation results support international communication by the user.

[0802] Step 5:

[0803] Integration of e-commerce and logistics management

[0804] The server interacts with international e-commerce platforms and logistics networks. Specifically, it manages product inventory information and shipping options via APIs. Based on the entered order information, it automatically calculates the optimal shipping strategy. As an output, users are provided with an efficient product distribution plan.

[0805] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0806] This invention provides a system to facilitate the smooth entry of Japanese small and medium-sized enterprises (SMEs) into international markets, and further enhances the user experience by combining it with an emotion engine. This system is based on the collection of company information and learning and analysis using a generative artificial intelligence model, and provides a process for formulating entry strategies into specific markets. Furthermore, it supports appropriate market entry by referring to the laws and regulations of the target market and assisting with necessary legal procedures.

[0807] The emotion engine has the ability to analyze the user's emotional state in real time and dynamically adjusts the system interface and the information presented based on the analysis results. This is designed to allow users to use the system more comfortably.

[0808] In a specific implementation, the server receives business data and product information from small and medium-sized enterprises (SMEs) and uses a generative artificial intelligence model to extract key strategic insights from this data. Simultaneously, the server consults legal databases to list legal requirements in the target country. This information is provided to users via terminals to facilitate legal procedures.

[0809] When a user uses the system, the emotion engine analyzes their emotions through input devices such as camera and mouse movements. This data is used by the server to adjust the display content of the system's operation screen and interface according to instructions. For example, if signs of user confusion are detected, the system will immediately display helpful information and hints.

[0810] Furthermore, the server provides translation functionality to support cross-cultural business negotiations. In this process, it takes into account the analysis results of the sentiment engine to appropriately adjust translations and expressions, minimizing misunderstandings between cultures.

[0811] Furthermore, integration with international e-commerce platforms and logistics systems allows users to manage the effective distribution of their products and services. The system can also leverage feedback from an emotional engine to adjust logistics plans and customer service strategies.

[0812] As a concrete example, let's consider a Japanese small-to-medium-sized software company aiming to enter the North American market. This company uses a system to collect local needs and competitive information, supporting strategic planning while simultaneously deepening its understanding of local laws and regulations. Furthermore, by utilizing an emotional engine, it can manage project managers' stress and misunderstandings, supporting optimal decision-making. This enables Japanese companies to leverage their global competitiveness and build success in international markets.

[0813] The following describes the processing flow.

[0814] Step 1:

[0815] The server receives business data and product information provided by small and medium-sized businesses. This includes data sharing via cloud storage such as SkyDrive and Dropbox.

[0816] Step 2:

[0817] The server trains a generative artificial intelligence model based on the received company information. The model learns business knowledge and strategies tailored to the characteristics of each company.

[0818] Step 3:

[0819] Users request specific market research via their devices. The research request includes details such as the target country and research items.

[0820] Step 4:

[0821] The server uses the internet and commercial databases to collect data on the specified market. This is done using crawling technology.

[0822] Step 5:

[0823] The server analyzes market data and generates competitive information and demand forecasts. This helps to concretize the potential markets that companies should enter.

[0824] Step 6:

[0825] The device presents the analysis results to the user as a visual dashboard. Through graphs and charts, users can intuitively grasp the information.

[0826] Step 7:

[0827] The server references legal databases for the target market and generates up-to-date legal information and a checklist of necessary documents for the business.

[0828] Step 8:

[0829] The device displays the necessary legal procedures and their priorities to the user, along with their progress. The user then proceeds with the procedures based on this information.

[0830] Step 9:

[0831] The emotion engine performs real-time sentiment analysis based on data entered by the user through the device's camera and microphone.

[0832] Step 10:

[0833] The server adjusts the system interface based on the results of the sentiment analysis. For example, if the user is stressed, it will display the user guide.

[0834] Step 11:

[0835] The server provides translation support for cross-language communication, offering expressions that take cultural context into account. This facilitates smoother negotiations.

[0836] Step 12:

[0837] The device uses data from its emotion engine to receive user feedback and then suggests the next course of action. This includes the direction and strategy of negotiations.

[0838] Step 13:

[0839] The server integrates with e-commerce platforms and logistics systems to automate product distribution and inventory management.

[0840] Step 14:

[0841] The terminal provides users with real-time information on product delivery status and inventory. This allows companies to operate their supply chains more efficiently.

[0842] (Example 2)

[0843] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0844] These are the challenges faced by Japanese small and medium-sized enterprises (SMEs) when entering international markets: improving the efficiency of information gathering, formulating market strategies, understanding local laws and regulations, and overcoming communication gaps in cross-cultural business negotiations. Furthermore, there is the need to improve usability by dynamically adjusting the system to take into account the emotional state of the user.

[0845] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0846] In this invention, the server includes means for collecting corporate information and training it using a generative AI model, means for collecting information on a specified market and analyzing demand and competition, and means for referencing legal data sources and generating a list in order to provide regulatory information for the target market. This enables smooth entry of small and medium-sized enterprises into international markets and dynamic adjustment of the interface according to the emotional state of the user.

[0847] "Company information" refers to a collection of data and knowledge related to a company's activities, including business operations, product information, and sales data.

[0848] A "generative AI model" is an artificial intelligence system that uses machine learning algorithms to analyze data and generate patterns and insights.

[0849] A "designated market" refers to a specific geographical or industry-specific area in which a company aims to enter, and the market trends and needs within that area are the focus.

[0850] "Regulatory information" refers to data on laws and regulations enacted in a particular country or region, which indicate the requirements that companies must comply with when conducting their business activities.

[0851] "Intercultural translation" is the process of linguistic conversion that enables accurate communication between people with different languages ​​and cultures.

[0852] An "emotion engine" is a technology that analyzes a user's emotional state in real time, evaluating emotions such as stress and confusion by analyzing the user's facial expressions and behavior.

[0853] An "international trading platform" is an online service that supports cross-border commercial transactions and facilitates the sale and purchase of products and services.

[0854] A "logistics system" is a network and process for managing the distribution of products and services, with the aim of efficiently delivering goods to consumers.

[0855] This invention functions as a support system for companies to smoothly enter international markets. Specifically, it is a system whose main components are a server, terminals, and users, which cooperate to perform tasks such as information gathering, data analysis, legal compliance, and sentiment analysis.

[0856] The server receives information provided by companies and uses high-performance data processing servers as hardware. The software incorporates generative AI models built using Python, TensorFlow, and other technologies. This allows the server to learn the company's business knowledge and automatically generate strategies for specified markets. The server also has the ability to connect with online legal databases to retrieve and list the latest legal information.

[0857] The terminal functions as an interface device for the user to interact with the system, using a computer or smart device. A computer vision algorithm is installed as an emotion engine to analyze the user's facial expressions and movements from camera and mouse movements. The emotion data obtained by the terminal is sent to a server and used to dynamically adjust the interface and presented information.

[0858] Users access international market research and translation services through the system. Based on emotional states analyzed by an emotion engine, the terminal immediately provides additional instructions and hints if the user is confused. Furthermore, the server-based translation function enables effective cross-cultural business negotiations.

[0859] As a concrete example, consider the use of the system by a Japanese small-to-medium-sized software company aiming to enter the North American market. This company can efficiently perform the necessary analysis and strategy formulation by inputting the following prompt into the system's generating AI model: "We would like the generating AI model to provide the optimal strategy for a Japanese app development company to enter the American market, as well as the procedures for verifying local laws and regulations."

[0860] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0861] Step 1:

[0862] Users provide the system with information about their company and the requirements of their desired market through an input device. This input includes company product data, performance information, and market entry objectives. This information is sent to a server and stored in a database.

[0863] Step 2:

[0864] The server uses a generative AI model to analyze the input company information. The generative AI model uses the input data to forecast market demand and conduct competitive analysis, generating strategic insights as output. For example, it analyzes the trends of competing companies and proposes optimal pricing and marketing strategies.

[0865] Step 3:

[0866] The server retrieves legal information for the target region from an external database. It receives information about the country or region where the company plans to expand as input and references the relevant regional regulatory data. As output, it generates a list based on the law, providing an overview of the regulations the user must comply with.

[0867] Step 4:

[0868] The device analyzes the user's emotional state through input devices such as a camera and mouse. The input consists of the user's facial expressions and behavioral patterns, which are processed by an emotion engine to identify signs of stress or confusion. The output emotion data is then used by the server in real time to adjust the interface.

[0869] Step 5:

[0870] The server dynamically adjusts the system interface based on the analysis results of the emotion engine. If a specific emotional state is detected, for example, if the system determines that the user is confused, it immediately provides support by displaying additional guidance or explanations on the screen.

[0871] Step 6:

[0872] The server provides translation functionality to support cross-cultural communication. It receives business documents and conversations requiring translation as input, and generates appropriate translated expressions that reflect feedback from an emotion engine, providing them to the user as output.

[0873] (Application Example 2)

[0874] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0875] For businesses expanding into international markets, efficient and strategic decision-making is crucial. However, this presents challenges due to the need to consider diverse market information, legal regulations, and cross-cultural communication, which often requires significant time and effort. Furthermore, in logistics center operations, there is a need for process improvements that take into account the working conditions of the staff.

[0876] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0877] In this invention, the server includes means for collecting business entity information and training it using a generative artificial intelligence model; means for collecting and analyzing information on a designated market and analyzing demand and competition; means for referencing a legal database and generating a checklist to provide legal information for the target market; and means for analyzing the emotions of business personnel using an information presentation device and dynamically adjusting work instructions and information presentations. This enables strategic decision-making regarding entry into international markets and efficient execution of operations at logistics centers.

[0878] "Business entity information" refers to all information related to the operation of an organization that conducts business activities, and specifically includes financial data, product information, customer information, etc.

[0879] A "generative artificial intelligence model" refers to an AI algorithm that has the ability to analyze given data and learn patterns and rules, and is a technology that generates new insights and predictions.

[0880] "Market information" refers to data necessary for business strategy, such as economic trends in a specific industry or region, consumer demand, and the competitive landscape.

[0881] "Legal information" refers to data on laws and regulations necessary for business activities, and is information that clarifies legal requirements that differ from country to country and region to region.

[0882] An "information presentation device" refers to a device that provides information to a user visually or audibly, and includes output devices such as displays and speakers.

[0883] "The emotions of the person in charge of the work" refers to the psychological and emotional state of the personnel performing the work, including stress levels and motivation.

[0884] A "logistics procedures system" refers to an information management system equipped with planning, tracking, and optimization functions for managing the distribution of goods and services.

[0885] The system for implementing this invention consists of multiple hardware and software components. First, the server collects various information about the business entity and stores it in a database, and then uses a generative artificial intelligence model to learn and analyze that information. Specifically, it builds an AI model using Python and TensorFlow, and performs analysis by saving the data to MongoDB.

[0886] Smart glasses and head-mounted displays are used as information presentation devices, providing users with an environment where they can check information in real time while working. Specifically, these include Google Glass and Microsoft HoloLens.

[0887] When a user operates the system, the server uses OpenCV to analyze video data from the camera and displays information such as inventory status and logistics routes. Furthermore, various sensors built into the information display device detect and analyze the user's emotional state, dynamically changing the display of work instructions and support information.

[0888] As a concrete example, imagine a scenario where the information presented to an operator at a logistics center during working hours is adjusted according to the operator's work condition. If the operator is detected to be under high stress, clearer explanations and notifications regarding appropriate break times will be displayed.

[0889] Examples of prompts for the generated AI model include: "Please suggest the optimal shelf arrangement to accommodate new product arrivals. Please calculate a picking route that takes into account the operator's physical condition." In this context, the system's role is to simultaneously provide efficient operational support and improve the user experience.

[0890] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0891] Step 1:

[0892] The server collects business and market information into a database and uses TensorFlow to train a generative artificial intelligence model. Inputs include financial data and market trends of the businesses, while outputs are analyzed demand forecasts and strategic insights. During this process, the data is preprocessed and supplied to the AI ​​model in an optimal format.

[0893] Step 2:

[0894] Users can view real-time information within the logistics center through smart glasses or head-mounted displays. Camera footage is captured by the terminal and sent to the server as input. The server analyzes this data using OpenCV and generates output such as inventory status and optimal logistics routes.

[0895] Step 3:

[0896] The server analyzes the user's emotional state using sensors built into the information display device. Inputs include the user's heart rate and movement data, while outputs include the user's stress level and motivation assessment. Based on this, the server generates appropriate work instructions and support information.

[0897] Step 4:

[0898] Based on the user's emotional state, the server dynamically adjusts the display content of the information presentation device. The input is the emotion analysis result obtained in step 3, and based on this, work instructions and support information are presented in a way that is easy for the user to understand. The output is information that has been adjusted visually or audibly.

[0899] Step 5:

[0900] The server utilizes data obtained from the generative AI model to present users with prompts that support the optimization and strategic planning of logistics centers. The input is the analysis results from the generative AI model, and the output is optimization suggestions in the form of prompts. This process aims to improve operational efficiency and enhance worker experience.

[0901] 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.

[0902] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0903] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0904] 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.

[0905] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0906] 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.

[0907] 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.

[0908] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0909] 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."

[0910] 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.

[0911] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0912] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0913] 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.

[0914] 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.

[0915] 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.

[0916] 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.

[0917] 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.

[0918] 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.

[0919] 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.

[0920] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0921] 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.

[0922] The following is further disclosed regarding the embodiments described above.

[0923] (Claim 1)

[0924] A means of collecting corporate information and training a generative artificial intelligence model,

[0925] A means of collecting and analyzing data on a designated market and conducting demand and competition analysis,

[0926] In order to provide legal information for the target country, a means of referencing legal databases and generating checklists,

[0927] Means of supporting translation and negotiation between different languages,

[0928] A means of managing product distribution in conjunction with international e-commerce platforms and logistics systems,

[0929] A system that includes this.

[0930] (Claim 2)

[0931] The system according to claim 1, which learns a company's business knowledge and formulates a strategy for entering a specific market using a generative artificial intelligence model.

[0932] (Claim 3)

[0933] The system described in claim 1, which regularly updates legal information and provides small and medium-sized enterprises with the latest legal procedure information.

[0934] "Example 1"

[0935] (Claim 1)

[0936] A means of aggregating business information and using a generative AI model to learn strategies,

[0937] A means of collecting data related to a specific market and performing demand forecasting and competitive analysis,

[0938] A means of obtaining legal information for the target country and generating a procedural checklist,

[0939] Means to support language translation and intercultural communication,

[0940] A means to optimize product distribution by integrating with international trade platforms and logistics management systems,

[0941] A means of providing visual information through a user interface,

[0942] A system that includes this.

[0943] (Claim 2)

[0944] The system according to claim 1, which uses a generative AI model to learn a company's expertise and provides research results for market entry in a visual format.

[0945] (Claim 3)

[0946] The system according to claim 1, which automatically updates legal information and periodically provides companies with the latest legal information.

[0947] "Application Example 1"

[0948] (Claim 1)

[0949] A means of collecting corporate information and training a generative artificial intelligence model,

[0950] A means of collecting and analyzing data on a designated market and conducting demand and competition analysis,

[0951] In order to provide legal information for the target country, a means of referencing legal databases and generating checklists,

[0952] Means of supporting translation and negotiation between different languages,

[0953] A means of managing product distribution in conjunction with international e-commerce platforms and logistics systems,

[0954] A means of visually presenting market analysis results and suggesting sales opportunities,

[0955] A system that includes this.

[0956] (Claim 2)

[0957] The system according to claim 1, which learns a company's business knowledge and formulates a strategy for entering a specific market using a generative artificial intelligence model.

[0958] (Claim 3)

[0959] The system according to claim 1, which regularly updates legal information, provides the latest legal procedure information to businesses, and makes visual market analysis results available.

[0960] "Example 2 of combining an emotion engine"

[0961] (Claim 1)

[0962] A means of collecting company information and training it using a generative AI model,

[0963] A means of collecting information on a specified market and analyzing demand and competition,

[0964] In order to provide regulatory information for the target country, a means of referencing legal data sources and generating a list,

[0965] Means to support cross-cultural translation and negotiation,

[0966] A means of analyzing the user's emotional state using an emotion engine and dynamically adjusting the user interface and presented information,

[0967] A means of managing product distribution by collaborating with international trading platforms and logistics systems,

[0968] A system that includes this.

[0969] (Claim 2)

[0970] The system according to claim 1, which uses a generative AI model to learn a company's business knowledge, formulates a strategy for entering a specific market, and manages user stress and confusion based on the analysis results of an emotion engine.

[0971] (Claim 3)

[0972] The system according to claim 1, which regularly updates regulatory information, provides companies with the latest legal procedure information in a timely manner, and adjusts customer service strategies based on feedback from an emotional engine.

[0973] "Application example 2 when combining with an emotional engine"

[0974] (Claim 1)

[0975] A means of collecting business entity information and training a generative artificial intelligence model,

[0976] A means of collecting and analyzing information about a designated market and conducting demand and competition analysis,

[0977] In order to provide legal information for the target country, a means of referencing legal databases and generating checklists,

[0978] Means of supporting translation and negotiation between different languages,

[0979] A means of managing product distribution in conjunction with international electronic trading platforms and logistics procedures systems,

[0980] A means of using an information presentation device to analyze the emotions of the person in charge of the work and dynamically adjust work instructions and information presentation,

[0981] A system that includes this.

[0982] (Claim 2)

[0983] The system according to claim 1, which learns the business knowledge of a business entity and formulates a strategy for entering a specific market using a generative artificial intelligence model.

[0984] (Claim 3)

[0985] The system described in claim 1, which regularly updates legal information, provides the business entity with the latest legal procedural information, and proposes breaks and work improvements in accordance with the working conditions of the person in charge of the work. [Explanation of Symbols]

[0986] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting corporate information and training a generative artificial intelligence model, A means of collecting and analyzing data on a designated market and conducting demand and competition analysis, In order to provide legal information for the target country, a means of referencing legal databases and generating checklists, Means of supporting translation and negotiation between different languages, A means of managing product distribution in conjunction with international e-commerce platforms and logistics systems, A system that includes this.

2. The system according to claim 1, which learns a company's business knowledge using a generative artificial intelligence model and formulates a strategy for entering a specific market.

3. The system described in claim 1, which regularly updates legal information and provides small and medium-sized enterprises with the latest legal procedural information.

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