system

Abstract

We provide the system. [Solution] A means of accumulating past decision data of sales leaders, A means for receiving data from a portable device for acquiring biometric information, A means for combining and analyzing the aforementioned judgment data and biometric information to generate advice regarding business conditions, Means for notifying the aforementioned advice, 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, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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】 [[ID=​​​​​​​​​​​​​​​​​​This invention solves the above problems by providing a system that accumulates past decision data of sales instructors and analyzes it in combination with biometric information obtained from a portable device. This system generates advice appropriate to the sales situation in real time and notifies sales representatives, thereby compensating for unstable performance due to lack of experience. In addition, by tracking changes in biometric information during sales negotiations and adjusting advice based on that information, it also reduces health risks. Furthermore, by collecting feedback from the results of implementing the advice and utilizing it to generate advice for the next time, it is possible to always provide optimal support. 【0006】 A "sales coach" refers to a person who guides sales representatives in their sales activities and provides strategic judgment and feedback. 【0007】 "Past decision data" refers to a collection of information that records past sales decisions and feedback made by sales instructors. 【0008】 "Biometric information" refers to data related to the sales representative's physical condition, such as heart rate and stress level. 【0009】 "Portable devices" refer to electronic devices, such as wearable devices, that can be carried by sales representatives and that can acquire biometric information in real time. 【0010】 "Analysis" refers to the information processing process that involves processing collected data to generate useful insights and advice regarding business conditions. 【0011】 "Advice" refers to specific suggestions for improvement and solutions provided to sales representatives in response to situations they encounter during business negotiations. 【0012】 "Notification" refers to promptly communicating the generated advice to the sales representative. 【0013】 "Feedback" refers to the opinions and results reports that sales representatives provide regarding the outcome of implementing advice. 【0014】 "Learning methods" refer to the methods and processes by which a system improves its analytical accuracy based on feedback. [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] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined. 【Embodiments for Carrying Out the Invention】 【0016】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0017】 First, the terms used in the following description will be explained. 【0018】 In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0019】 In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0020】 In the following embodiments, a storage with a reference numeral is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【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】 This invention realizes a system that provides real-time sales support using the judgment data of sales managers and the biometric information of sales representatives. A specific embodiment of this system is shown below. 【0037】 First, past decision-making data of sales instructors is stored in a database. A server manages this data and prepares it as a resource for later analysis. Specifically, this includes past decisions made by sales instructors, successful sales strategies, and feedback received. 【0038】 Next, sales representatives wear portable devices such as wearable devices to continuously collect biometric information. The devices periodically measure heart rate, stress levels, and other parameters, and transmit this data to a server. This makes it possible to monitor the physical condition of sales representatives in real time during business negotiations. 【0039】 Next, the server combines the collected biometric information with past decision data and performs analysis. Using AI algorithms, it generates appropriate advice for specific sales situations. In this process, the most effective course of action is devised based on the sales coach's past success patterns and the salesperson's current state. 【0040】 The generated advice is immediately notified to the sales representative via the device. It is displayed visually on the screen and can also be provided via voice guidance. This allows the sales representative to respond calmly and effectively during sales negotiations. 【0041】 For example, when a salesperson is about to meet with a new client, the server analyzes past successful deals with similar clients and, based on current biometric data, advises the salesperson to "ask more questions and focus on active listening." If the salesperson's heart rate starts to increase during the meeting, the server suggests "taking a deep breath to calm down." 【0042】 After a sales negotiation concludes, the sales representative inputs their experience and results as feedback. The server uses this data to improve the quality of AI advice for future sales activities and to further enhance the system. 【0043】 In this way, the present invention aims to help sales representatives maintain peak performance in individual business negotiations and improve the overall sales capabilities of the company. 【0044】 The following describes the processing flow. 【0045】 Step 1: 【0046】 The server retrieves past decision-making data from sales coaches from a database and prepares it for analysis. This data includes details of past sales strategies and specific advice given. 【0047】 Step 2: 【0048】 The terminal receives biometric information from wearable devices carried by sales representatives. This information includes heart rate, stress levels, and other data, and is continuously monitored in real time. 【0049】 Step 3: 【0050】 The server combines biometric information transmitted from the terminal with past decision data acquired in Step 1 and performs analysis using an AI algorithm. This analysis is a process that generates advice tailored to the current business situation. 【0051】 Step 4: 【0052】 The server sends advice generated based on the analysis to the terminal. The advice is notified to the sales representative in a visual or audio manner. 【0053】 Step 5: 【0054】 The user (sales representative) reviews the advice displayed on the terminal and takes specific actions based on it. By making adjustments according to the situation during the sales negotiation, they can conduct effective sales activities. 【0055】 Step 6: 【0056】 After the business negotiation concludes, the user enters feedback on the negotiation results and the effectiveness of the advice into their device. This feedback will be used for future information analysis and advice generation. 【0057】 Step 7: 【0058】 The server receives feedback data and stores it in a database to help improve the accuracy of the AI ​​algorithm and generate future advice. This enables continuous improvement of the system. 【0059】 (Example 1) 【0060】 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." 【0061】 Making optimal decisions in real time during sales negotiations is often difficult for sales representatives. Furthermore, while providing accurate advice tailored to the negotiation situation and the individual representative's condition is crucial, traditional methods have failed to fully utilize the representative's physical condition or past success stories. This hinders the maximization of sales effectiveness. 【0062】 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. 【0063】 In this invention, the server includes means for an information processing device to store past decision data, means for receiving biometric data from an information acquisition device, and means for integrating and analyzing the decision data and biometric data to generate operational guidelines regarding sales status. This enables sales representatives to receive appropriate advice in real time for each business negotiation, thereby improving sales performance. 【0064】 An "information processing device" is a device used to store and analyze past decision data. 【0065】 "Information acquisition device" refers to various sensors and devices that collect biometric data from sales representatives. 【0066】 "Biometric data" refers to data that indicates the physical condition of sales representatives, such as their heart rate and stress index. 【0067】 "Action guidelines" refer to specific action plans and advice generated in response to business conditions. 【0068】 A "generative AI model" refers to an artificial intelligence system that analyzes a situation based on past success stories and real-time biometric data to generate appropriate advice. 【0069】 A "communication device" is an electronic device used to notify sales representatives of the generated operational guidelines. 【0070】 "Observation" refers to the act of monitoring changes in the biometric data of a sales representative in real time during a business negotiation. 【0071】 "Feedback" refers to evaluations and information based on the results of implementing the action guidelines provided by the sales representative. 【0072】 A "learning tool" is a system that utilizes collected feedback to improve the quality of future action guidelines. 【0073】 This invention is based on a system in which an information processing device (server) stores past decision data of sales instructors in a database. The stored data includes past successful sales strategies and feedback. 【0074】 Next, the terminal acquires biometric data from the information acquisition device (wearable device) worn by the sales representative. Specifically, it collects data such as heart rate and stress index, and transfers this data to the information processing device. Since the transfer is done using wireless communication technology, the sales representative's biometric data is continuously updated in real time even during business negotiations. 【0075】 The information processing device analyzes received biometric data and accumulated decision data using a generating AI model. This analysis generates action guidelines tailored to the business situation. The generating AI model evaluates the situation based on past success stories and real-time biometric data, and formulates the optimal course of action. 【0076】 The generated operational guidelines are notified to the sales representative via their device. The notification is delivered via voice guidance and display, allowing the sales representative to respond quickly during sales negotiations. 【0077】 For example, the server analyzes past success data from negotiations with new customers and generates suggestions such as "ask more questions to capture the customer's interest," and immediately provides advice such as "take a deep breath to relax" when your heart rate is elevated. 【0078】 After a business negotiation is completed, feedback on the results of the actions the user took is entered into the server. This feedback is analyzed and used as foundational data to improve the quality of future action guidelines. This allows for continuous improvement of the overall system's effectiveness. 【0079】 (Example of a prompt message) 【0080】 "Generate sales advice based on past success stories and real-time biometric data." 【0081】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0082】 Step 1: 【0083】 The server stores past decision-making data from sales leaders. This data includes past successful sales strategies and feedback. Past decision-making data is used as input, and this data is organized and stored in a database as output. During this process, the data is filtered and classified, and prepared in a format that can be used for later analysis. 【0084】 Step 2: 【0085】 The terminal acquires biometric data from the information acquisition device worn by the sales representative. Inputs include heart rate and stress index, which are measured in real time and transmitted wirelessly to the server as output. This process involves signal conversion and data standardization, allowing the server to receive the data in a format suitable for analysis. 【0086】 Step 3: 【0087】 The server integrates received biometric data with accumulated decision data and performs analysis using an AI algorithm. Inputs include historical decision data and real-time biometric data, and output is the generation of action guidelines tailored to specific business situations. This analysis process utilizes a generative AI model, performing pattern matching and predictive analysis based on past success stories. 【0088】 Step 4: 【0089】 The server notifies sales representatives of the generated operational guidelines via their terminals. The operational guidelines are taken as input, and are output in text or audio format, transmitted through the terminal's display or speaker. Through user interface control, the guidelines are visually verifiable, and audio guidance is provided as needed. 【0090】 Step 5: 【0091】 Sales representatives, as users, input feedback into the server after a sales meeting. This feedback includes the results of the actions taken, and the feedback data is used as input. The server analyzes this data and updates the database for future action guideline generation. The feedback analysis involves pattern recognition and text analysis, which are used to improve the accuracy of future guidelines. 【0092】 (Application Example 1) 【0093】 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." 【0094】 Sales representatives need to make immediate decisions about appropriate actions during negotiations, but it is difficult for them to receive real-time advice tailored to the specific negotiation situation and the sales representative's physical condition. Furthermore, while there is a need to leverage past success patterns to provide optimal advice during negotiations, there is a lack of effective systems for this purpose. 【0095】 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. 【0096】 In this invention, the server includes means for storing past decision information of sales instructors, means for receiving information from a portable device for acquiring physical information, means for analyzing the combination of the decision information and physical information to generate advice regarding the sales situation, and means for operating a robot to support sales activities. This enables real-time advice based on the physical condition of sales representatives during business negotiations, allowing sales representatives to take appropriate action immediately. 【0097】 A "sales leader" is a person or organization responsible for formulating policies and strategies in sales activities and providing guidance and advice to sales representatives. 【0098】 "Judgment information" refers to data obtained from the knowledge and experience of sales activities, such as the history of decisions made by sales instructors in the past, successful strategies, and the content of their guidance. 【0099】 "Physiological information" refers to data indicating physiological states, such as heart rate and stress level, obtained by sales representatives from wearable devices, etc. 【0100】 A "portable device" is a highly mobile device that can be worn by sales representatives to collect personal information. 【0101】 "Advice" refers to instructions or suggestions regarding appropriate actions or responses provided to sales representatives in response to the circumstances during their sales activities. 【0102】 "Means of supporting sales activities by operating robots" refers to robot systems that have the function of providing appropriate advice to sales representatives during business negotiations via voice or display. 【0103】 This invention is designed as a system to effectively support sales activities. The system operates with a server, a portable device, and a robot working together. The server is responsible for storing and managing past decision-making information of sales leaders in a database. This includes past successful strategies and decision-making history. 【0104】 A portable device, specifically a wearable device, continuously measures the physical information of sales representatives and transmits the acquired physiological data to a server. This device detects heart rate, stress levels, and other parameters, and transmits the data via Bluetooth or Wi-Fi. 【0105】 The server combines received physical information with accumulated judgment information for analysis. This analysis utilizes AI algorithms to generate appropriate advice tailored to specific business situations. Generative AI models enable iterative learning and analysis of data. For example, machine learning libraries such as TENSORFLOW® and PyTorch are used. 【0106】 The generated advice is communicated to the sales representative via the robot, either verbally or visually on a display. The robot accompanies the sales representative to the sales meeting, supporting them in receiving real-time advice based on their physical information. It can also prompt specific actions. 【0107】 For example, when a sales representative is about to meet with a new client, the system might offer advice such as, "We previously found the following approach effective with this company. Please increase the number of questions to capture the client's interest." If tension rises, it might also suggest, "Take a deep breath to relax." 【0108】 An example of a prompt would be, "Based on the sales representative's biometric information and past success data, please provide the optimal strategy to help during the sales negotiation." This prompt is presented to the AI ​​generation model, enabling the generation of specific advice tailored to the sales situation. 【0109】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0110】 Step 1: 【0111】 The user wears a wearable device. The device continuously measures the user's physical information, such as heart rate and stress level. This information is acquired by the device in real time. 【0112】 Step 2: 【0113】 The device transmits physical information collected from wearable devices to a server via Bluetooth or Wi-Fi. The input data includes heart rate and stress level, and the server receives this data and logs it. 【0114】 Step 3: 【0115】 The server begins analysis by combining accumulated past judgment data of sales instructors with received physical information. Using an AI algorithm, it performs pattern recognition and data mining based on this data to generate optimal advice tailored to the sales situation. The output is specific advice for sales representatives. 【0116】 Step 4: 【0117】 The server sends the generated advice to the robot. The robot provides advice to the user during the sales negotiation via a voice assistant or display. The output is expressed as a voice message or display message. 【0118】 Step 5: 【0119】 After a business negotiation concludes, the user enters feedback about the negotiation into their device. The device sends this feedback to the server, which then uses the feedback to retrain the AI ​​model for future advice generation. This feedback is crucial data for improving the AI's accuracy. 【0120】 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. 【0121】 This invention realizes a system that more effectively supports sales activities by using past judgment data of sales coaches, biometric information of sales representatives, and emotional data recognized by an emotion engine. This system integrates multiple data sources and generates optimal advice in real time. 【0122】 Specifically, the server first retrieves past decision-making data from sales instructors from a pre-established database and uses it for analysis as needed. This data includes successful sales techniques and customer response strategies. 【0123】 Next, the terminal acquires biometric information from the wearable device worn by the sales representative. Simultaneously, software equipped with an emotion engine analyzes emotional data from the sales representative's facial expressions and tone of voice. This combined data makes it possible to monitor the sales representative's biological and emotional state in real time and in detail. 【0124】 Next, the server comprehensively analyzes this data and uses AI algorithms to generate optimal advice for the sales situation. This advice helps provide the most appropriate course of action, taking into account the sales representative's current emotions and mental state. 【0125】 The generated advice is immediately communicated to the sales representative via their device, either visually or audibly. This supports the representative in making informed decisions during sales negotiations, allowing them to confidently interact with customers. 【0126】 For example, if the emotion engine detects signs of tension in a sales representative during a business negotiation, the server can use that information to generate specific advice such as "take a short break to help them relax." Similarly, if positive emotions are detected from the customer's reactions, the system can generate advice encouraging positive actions, such as "develop a proactive approach to closing the deal." 【0127】 After a sales meeting concludes, users input feedback into their terminals, and this information is analyzed on a server. This feedback is used to improve the accuracy of advice for future meetings and to fine-tune the emotional engine. Through this process, we support sales representatives in achieving their best performance in individual sales meetings and aim to improve the overall sales capabilities of the company. 【0128】 The following describes the processing flow. 【0129】 Step 1: 【0130】 The server retrieves past decision-making data from the sales coaches' database and prepares it for analysis. This data includes records of previous sales negotiations and summaries of successful sales techniques. 【0131】 Step 2: 【0132】 The terminal receives biometric information such as the salesperson's heart rate and stress level in real time from a wearable device. At the same time, the emotion engine analyzes emotional data from the salesperson's facial expressions and voice and transmits it to the terminal. 【0133】 Step 3: 【0134】 The server combines emotional data and biometric information, and uses AI algorithms to generate advice best suited to the current sales situation. Here, appropriate action guidelines are determined after comprehensively considering the emotional and physical state of the sales representative. 【0135】 Step 4: 【0136】 The server sends the generated advice to the terminal. The terminal displays the notification directly to the sales representative and provides immediate feedback through voice guidance. In this step, the sales representative can instantly know what appropriate action to take during the sales negotiation. 【0137】 Step 5: 【0138】 The user (sales representative) reviews the advice provided on the device and acts upon it in accordance with the flow of the sales negotiation. For example, if the emotion engine detects that the user is feeling nervous, they will try relaxation techniques such as taking deep breaths. 【0139】 Step 6: 【0140】 After the business negotiation concludes, the user enters feedback on the negotiation results and the effectiveness of the advice received into their terminal. This feedback information will be used to improve the accuracy of future advice provided. 【0141】 Step 7: 【0142】 The server records feedback data in a database and uses it to generate advice for the next time and analyze the emotion engine. This leads to an improvement in the overall system performance. 【0143】 (Example 2) 【0144】 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 will be referred to as the "terminal." 【0145】 In sales activities, providing real-time advice based on the physical and emotional state of the salesperson is difficult, resulting in sales performance being dependent on the salesperson's condition. Furthermore, the lack of a system to effectively utilize feedback from sales negotiations and incorporate it into future negotiations leads to insufficient accumulation of sales experience. 【0146】 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. 【0147】 In this invention, the server includes means for storing information based on the past judgments of sales leaders, means for receiving information from a portable device for collecting information on physical condition, and means for analyzing a combination of the information based on the judgments, information on physical condition, and information on emotions to generate optimal advice for sales activities. This enables the provision of real-time advice tailored to the biological and emotional state of sales representatives, and continuous improvement of sales techniques through the use of feedback. 【0148】 "Information based on past decisions of sales leaders" refers to data and information related to decisions and choices made by leaders in past sales activities. 【0149】 "Information regarding physical condition" refers to data that quantifies the sales representative's physical condition, such as heart rate, body temperature, and stress level. 【0150】 A "portable device" is a device that a sales representative can wear and that is used to acquire biometric information. 【0151】 "Emotional information" refers to data on the mental state and emotions extracted from the sales representative's facial expressions and tone of voice. 【0152】 "Means for analysis and generating optimal advice for sales activities" refers to the process of using AI algorithms and generative AI models to analyze collected data and generate appropriate instructions and suggestions for sales activities. 【0153】 "Real-time advice" refers to advice and instructions provided to sales representatives immediately on the spot. 【0154】 "Feedback" refers to evaluations and opinions regarding the results of business negotiations and the implementation of advice, and is information used to improve future interactions. 【0155】 This invention provides a system that effectively supports sales representatives in their sales activities by collecting data from multiple sources and analyzing it using an AI algorithm to generate optimal advice. 【0156】 First, the server retrieves information from a database built on the past decisions of sales leaders. This information includes past success stories and customer service strategies. A database management system is used to securely and efficiently access and retrieve the data. 【0157】 Next, the terminal collects biometric information in real time from a wearable device worn by the sales representative. This device has the function of measuring physical conditions such as heart rate and body temperature, and transmits the information to the terminal via Bluetooth or Wi-Fi. In addition, information about emotions is obtained by analyzing the sales representative's facial expressions and voice using the camera and microphone built into the terminal. 【0158】 The server integrates this information and performs analysis using a generative AI model. Specifically, the AI ​​algorithm creates optimal advice based on biometric data, emotional data, and information derived from past decisions, tailored to the sales situation. This advice is adapted to the salesperson's mental state and the customer's response. 【0159】 Advice is immediately communicated to sales representatives via their devices. Visual displays and audio output are used to provide effective feedback to sales representatives. After a sales meeting, users input feedback on the meeting results into their devices, and this information is sent back to the server. The server analyzes this feedback and uses it to train its generative AI model, thereby improving the accuracy of advice for future sales meetings. 【0160】 For example, when inputting prompt messages into an AI model, you can instruct it to "consider the sales coach's past data, current biometric information, and emotional data, and provide the most effective sales strategy." This allows the system to provide specific, situation-specific advice in real time. 【0161】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0162】 Step 1: 【0163】 The server retrieves information from a database based on the past decisions of sales managers. The input is the decision information stored in the database, and the output is the result of extracting this information. SQL queries are used to retrieve the necessary datasets from the database and prepare the data in memory for the next analysis. 【0164】 Step 2: 【0165】 The terminal receives biometric information from wearable devices worn by sales representatives. Input is biometric data such as heart rate and body temperature generated by the wearable device, while output is organized biometric data stored on the terminal. Data is received in real time using Bluetooth or Wi-Fi connections and stored in a local database. 【0166】 Step 3: 【0167】 The device uses its built-in camera and microphone to collect information about the sales representative's emotions. Inputs are camera footage and audio signals, while output is analyzed emotion data. Image processing and audio analysis algorithms are applied to determine emotions from facial expressions and voice tone, quantifying them and storing them in a database. 【0168】 Step 4: 【0169】 The server integrates acquired judgment information, biometric information, and emotional information, and begins analysis using a generative AI model. The input is all the integrated data, and the output is optimal advice for the sales representative. The AI ​​algorithm analyzes this data and generates actionable guidelines best suited to the sales scenario. 【0170】 Step 5: 【0171】 The terminal notifies sales representatives of advice received from the server. Input is advice data sent from the server, and output is visual or audio notification. The terminal displays text on its screen or uses an audio output device to convey the advice. 【0172】 Step 6: 【0173】 After a sales meeting, the user enters feedback into the terminal. The input consists of the results and opinions of the meeting based on the advice given by the sales representative, and the output is information sent to the server as feedback data. The terminal provides a feedback input interface and sends the entered information to the server. 【0174】 Step 7: 【0175】 The server analyzes the collected feedback data and updates the learning model to reflect the changes in future advice generation. The input is the feedback data received from the user, and the output is the updated AI model. Data analysis and machine learning techniques are used to improve the model's accuracy and prepare for the next business negotiation. 【0176】 (Application Example 2) 【0177】 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". 【0178】 Conventional sales support systems are often limited to sales situations, making it difficult to capture users' emotions and biometric information in real time in various aspects of their daily lives and provide appropriate advice. Furthermore, these systems struggle with natural human interaction, requiring flexible responses in home life support. Therefore, there is a need for a system that can provide appropriate advice in various aspects of daily life based on users' emotions and biometric information. 【0179】 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. 【0180】 In this invention, the server includes means for accumulating past decision data of sales instructors, means for receiving data from a portable device for acquiring biometric information, and means for analyzing the decision data, biometric information, and emotional information in combination to generate advice related to daily life situations. This makes it possible to capture the user's emotions and biological state in real time and automatically provide selective advice related to daily life situations. 【0181】 "Past decision data of sales instructors" refers to accumulated data recording the decisions and actions that sales instructors have taken to date, including successful sales methods and customer service strategies. 【0182】 "Biometric information" refers to information that indicates the user's physical condition, and includes data such as physiological indicators like heart rate, skin temperature, and respiratory rate. 【0183】 "Portable devices" refer to devices that can be worn by users and are easy to carry, and include devices such as wearable devices and smartphones. 【0184】 "Emotional information" refers to information that indicates the user's emotional state, and is data on emotional responses obtained through facial expression analysis and vocal information. 【0185】 A "means for generating advice" refers to a system that analyzes accumulated data and real-time received information to create specific action plans and recommendations for users. 【0186】 "Means of notification via robot" refers to notification methods using robots to deliver generated advice to users through functions such as voice or display. 【0187】 "Feedback" refers to information in which users provide evaluations and opinions on the advice they receive, and this information is used to improve the system in the future. 【0188】 In the system for implementing this invention, the server stores past decision data of sales instructors and extracts necessary information from the stored database. This includes successful sales methods and customer service strategies, which are used for data analysis. In addition, the terminal acquires the user's biometric information through a portable device (e.g., a wearable device). This is combined with software equipped with an emotion engine, which has the function of analyzing emotional information from facial expressions and voice. 【0189】 The server comprehensively analyzes this biometric and emotional information and uses a generative AI model to generate appropriate advice for various life situations. This advice takes into account the user's current emotions and physical state in real time and is communicated to the user via the robot. This communication is provided through voice feedback and visual displays to support the user's actions. 【0190】 For example, if the robot determines that the user is feeling stressed, it might offer specific advice such as, "Why not try listening to your favorite music to relax?" An example of a prompt might be, "Based on the user's current emotions and biometric information, please advise on ways to relax." 【0191】 Furthermore, by allowing users to input feedback after business negotiations and on a daily basis into their devices, this data is further analyzed on the server and used to improve the accuracy of advice generation in the future. In this way, a support system that improves the quality of life is realized. 【0192】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0193】 Step 1: 【0194】 By having the user wear a portable device, the terminal receives biometric information from the wearable device. Data such as heart rate, skin temperature, and respiratory rate are acquired as input and temporarily stored within the terminal. 【0195】 Step 2: 【0196】 The device uses an emotion engine to analyze emotional information from the user's facial expressions and voice. The input is real-time facial and voice data from the user, and the output is data on emotional state and stress levels. This allows for real-time monitoring of the user's mental state. 【0197】 Step 3: 【0198】 The server receives biometric and emotional information acquired from the terminal. Based on the input data, it compares it with a database of past judgments and generates appropriate advice using a generative AI model. The output is specific advice tailored to the user's situation. 【0199】 Step 4: 【0200】 The server sends generated advice to the terminal, which then notifies the user via a robot. Notifications are delivered via voice or display. The input is the generated advice, and the output is the specific action plan presented to the user. 【0201】 Step 5: 【0202】 After a business meeting or during daily life, users input feedback into their device. This input consists of evaluations and opinions on the advice, and the server receives this data to update it for future advice generation. The feedback data is used as training material for the AI ​​model, leading to the generation of more accurate advice. 【0203】 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. 【0204】 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. 【0205】 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. 【0206】 [Second Embodiment] 【0207】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0208】 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. 【0209】 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). 【0210】 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. 【0211】 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. 【0212】 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). 【0213】 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. 【0214】 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. 【0215】 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. 【0216】 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. 【0217】 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. 【0218】 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". 【0219】 This invention realizes a system that provides real-time sales support using the judgment data of sales managers and the biometric information of sales representatives. A specific embodiment of this system is shown below. 【0220】 First, past decision-making data of sales instructors is stored in a database. A server manages this data and prepares it as a resource for later analysis. Specifically, this includes past decisions made by sales instructors, successful sales strategies, and feedback received. 【0221】 Next, sales representatives wear portable devices such as wearable devices to continuously collect biometric information. The devices periodically measure heart rate, stress levels, and other parameters, and transmit this data to a server. This makes it possible to monitor the physical condition of sales representatives in real time during business negotiations. 【0222】 Next, the server combines the collected biometric information with past decision data and performs analysis. Using AI algorithms, it generates appropriate advice for specific sales situations. In this process, the most effective course of action is devised based on the sales coach's past success patterns and the salesperson's current state. 【0223】 The generated advice is immediately notified to the sales representative via the device. It is displayed visually on the screen and can also be provided via voice guidance. This allows the sales representative to respond calmly and effectively during sales negotiations. 【0224】 For example, when a salesperson is about to meet with a new client, the server analyzes past successful deals with similar clients and, based on current biometric data, advises the salesperson to "ask more questions and focus on active listening." If the salesperson's heart rate starts to increase during the meeting, the server suggests "taking a deep breath to calm down." 【0225】 After a sales negotiation concludes, the sales representative inputs their experience and results as feedback. The server uses this data to improve the quality of AI advice for future sales activities and to further enhance the system. 【0226】 In this way, the present invention aims to help sales representatives maintain peak performance in individual business negotiations and improve the overall sales capabilities of the company. 【0227】 The following describes the processing flow. 【0228】 Step 1: 【0229】 The server retrieves past decision-making data from sales coaches from a database and prepares it for analysis. This data includes details of past sales strategies and specific advice given. 【0230】 Step 2: 【0231】 The terminal receives biometric information from wearable devices carried by sales representatives. This information includes heart rate, stress levels, and other data, and is continuously monitored in real time. 【0232】 Step 3: 【0233】 The server combines biometric information transmitted from the terminal with past decision data acquired in Step 1 and performs analysis using an AI algorithm. This analysis is a process that generates advice tailored to the current business situation. 【0234】 Step 4: 【0235】 The server sends advice generated based on the analysis to the terminal. The advice is notified to the sales representative in a visual or audio manner. 【0236】 Step 5: 【0237】 The user (sales representative) reviews the advice displayed on the terminal and takes specific actions based on it. By making adjustments according to the situation during the sales negotiation, they can conduct effective sales activities. 【0238】 Step 6: 【0239】 After the business negotiation concludes, the user enters feedback on the negotiation results and the effectiveness of the advice into their device. This feedback will be used for future information analysis and advice generation. 【0240】 Step 7: 【0241】 The server receives feedback data and stores it in a database to help improve the accuracy of the AI ​​algorithm and generate future advice. This enables continuous improvement of the system. 【0242】 (Example 1) 【0243】 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." 【0244】 Making optimal decisions in real time during sales negotiations is often difficult for sales representatives. Furthermore, while providing accurate advice tailored to the negotiation situation and the individual representative's condition is crucial, traditional methods have failed to fully utilize the representative's physical condition or past success stories. This hinders the maximization of sales effectiveness. 【0245】 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. 【0246】 In this invention, the server includes means for an information processing device to store past decision data, means for receiving biometric data from an information acquisition device, and means for integrating and analyzing the decision data and biometric data to generate operational guidelines regarding sales status. This enables sales representatives to receive appropriate advice in real time for each business negotiation, thereby improving sales performance. 【0247】 An "information processing device" is a device used to store and analyze past decision data. 【0248】 "Information acquisition device" refers to various sensors and devices that collect biometric data from sales representatives. 【0249】 "Biometric data" refers to data that indicates the physical condition of sales representatives, such as their heart rate and stress index. 【0250】 "Action guidelines" refer to specific action plans and advice generated in response to business conditions. 【0251】 A "generative AI model" refers to an artificial intelligence system that analyzes a situation based on past success stories and real-time biometric data to generate appropriate advice. 【0252】 A "communication device" is an electronic device used to notify sales representatives of the generated operational guidelines. 【0253】 "Observation" refers to the act of monitoring changes in the biometric data of a sales representative in real time during a business negotiation. 【0254】 "Feedback" refers to evaluations and information based on the results of implementing the action guidelines provided by the sales representative. 【0255】 A "learning tool" is a system that utilizes collected feedback to improve the quality of future action guidelines. 【0256】 This invention is based on a system in which an information processing device (server) stores past decision data of sales instructors in a database. The stored data includes past successful sales strategies and feedback. 【0257】 Next, the terminal acquires biometric data from the information acquisition device (wearable device) worn by the sales representative. Specifically, it collects data such as heart rate and stress index, and transfers this data to the information processing device. Since the transfer is done using wireless communication technology, the sales representative's biometric data is continuously updated in real time even during business negotiations. 【0258】 The information processing device analyzes received biometric data and accumulated decision data using a generating AI model. This analysis generates action guidelines tailored to the business situation. The generating AI model evaluates the situation based on past success stories and real-time biometric data, and formulates the optimal course of action. 【0259】 The generated operational guidelines are notified to the sales representative via their device. The notification is delivered via voice guidance and display, allowing the sales representative to respond quickly during sales negotiations. 【0260】 For example, the server analyzes past success data from negotiations with new customers and generates suggestions such as "ask more questions to capture the customer's interest," and immediately provides advice such as "take a deep breath to relax" when your heart rate is elevated. 【0261】 After a business negotiation is completed, feedback on the results of the actions the user took is entered into the server. This feedback is analyzed and used as foundational data to improve the quality of future action guidelines. This allows for continuous improvement of the overall system's effectiveness. 【0262】 (Example of a prompt message) 【0263】 "Generate sales advice based on past success stories and real-time biometric data." 【0264】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0265】 Step 1: 【0266】 The server stores past decision-making data from sales leaders. This data includes past successful sales strategies and feedback. Past decision-making data is used as input, and this data is organized and stored in a database as output. During this process, the data is filtered and classified, and prepared in a format that can be used for later analysis. 【0267】 Step 2: 【0268】 The terminal acquires biometric data from the information acquisition device worn by the sales representative. Inputs include heart rate and stress index, which are measured in real time and transmitted wirelessly to the server as output. This process involves signal conversion and data standardization, allowing the server to receive the data in a format suitable for analysis. 【0269】 Step 3: 【0270】 The server integrates received biometric data with accumulated decision data and performs analysis using an AI algorithm. Inputs include historical decision data and real-time biometric data, and output is the generation of action guidelines tailored to specific business situations. This analysis process utilizes a generative AI model, performing pattern matching and predictive analysis based on past success stories. 【0271】 Step 4: 【0272】 The server notifies sales representatives of the generated operational guidelines via their terminals. The operational guidelines are taken as input, and are output in text or audio format, transmitted through the terminal's display or speaker. Through user interface control, the guidelines are visually verifiable, and audio guidance is provided as needed. 【0273】 Step 5: 【0274】 Sales representatives, as users, input feedback into the server after a sales meeting. This feedback includes the results of the actions taken, and the feedback data is used as input. The server analyzes this data and updates the database for future action guideline generation. The feedback analysis involves pattern recognition and text analysis, which are used to improve the accuracy of future guidelines. 【0275】 (Application Example 1) 【0276】 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." 【0277】 Sales representatives need to make immediate decisions about appropriate actions during negotiations, but it is difficult for them to receive real-time advice tailored to the specific negotiation situation and the sales representative's physical condition. Furthermore, while there is a need to leverage past success patterns to provide optimal advice during negotiations, there is a lack of effective systems for this purpose. 【0278】 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. 【0279】 In this invention, the server includes means for storing past decision information of sales instructors, means for receiving information from a portable device for acquiring physical information, means for analyzing the combination of the decision information and physical information to generate advice regarding the sales situation, and means for operating a robot to support sales activities. This enables real-time advice based on the physical condition of sales representatives during business negotiations, allowing sales representatives to take appropriate action immediately. 【0280】 A "sales leader" is a person or organization responsible for formulating policies and strategies in sales activities and providing guidance and advice to sales representatives. 【0281】 "Judgment information" refers to data obtained from the knowledge and experience of sales activities, such as the history of decisions made by sales instructors in the past, successful strategies, and the content of their guidance. 【0282】 "Physiological information" refers to data indicating physiological states, such as heart rate and stress level, obtained by sales representatives from wearable devices, etc. 【0283】 A "portable device" is a highly mobile device that can be worn by sales representatives to collect personal information. 【0284】 "Advice" refers to instructions or proposals regarding appropriate actions or responses provided to sales representatives according to the situation during business activities. 【0285】 "Means of operating a robot to support business activities" refers to a robot system that has the function of presenting appropriate advice to sales representatives during negotiations in the form of voice or display. 【0286】 This invention is designed as a system for effectively supporting business activities. The system operates in cooperation with a server, a portable device, and a robot. The server plays a role in accumulating and managing the past judgment information of business instructors in a database. This includes past successful strategies and judgment histories. 【0287】 A portable device, specifically a wearable device, continuously measures the physical information of sales representatives and transmits the acquired physiological data to the server. This device detects heart rate, stress level, etc. and transmits data via Bluetooth or Wi-Fi. 【0288】 The server combines and analyzes the received physical information and the accumulated judgment information. An AI algorithm is used in this analysis to generate appropriate advice according to specific business situations. By using a generated AI model, iterative learning and analysis of data become possible. For example, machine learning libraries such as TensorFlow and PyTorch are used. 【0289】 The generated advice is notified to sales representatives in a visible form via voice or display through the robot. The robot accompanies the negotiation site and provides support for sales representatives to receive real-time advice based on physical information. It can also prompt specific actions. 【0290】 For example, when a sales representative is about to meet with a new client, the system might offer advice such as, "We previously found the following approach effective with this company. Please increase the number of questions to capture the client's interest." If tension rises, it might also suggest, "Take a deep breath to relax." 【0291】 An example of a prompt would be, "Based on the sales representative's biometric information and past success data, please provide the optimal strategy to help during the sales negotiation." This prompt is presented to the AI ​​generation model, enabling the generation of specific advice tailored to the sales situation. 【0292】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0293】 Step 1: 【0294】 The user wears a wearable device. The device continuously measures the user's physical information, such as heart rate and stress level. This information is acquired by the device in real time. 【0295】 Step 2: 【0296】 The device transmits physical information collected from wearable devices to a server via Bluetooth or Wi-Fi. The input data includes heart rate and stress level, and the server receives this data and logs it. 【0297】 Step 3: 【0298】 The server begins analysis by combining accumulated past judgment data of sales instructors with received physical information. Using an AI algorithm, it performs pattern recognition and data mining based on this data to generate optimal advice tailored to the sales situation. The output is specific advice for sales representatives. 【0299】 Step 4: 【0300】 The server sends the generated advice to the robot. The robot provides advice to the user during the sales negotiation via a voice assistant or display. The output is expressed as a voice message or display message. 【0301】 Step 5: 【0302】 After a business negotiation concludes, the user enters feedback about the negotiation into their device. The device sends this feedback to the server, which then uses the feedback to retrain the AI ​​model for future advice generation. This feedback is crucial data for improving the AI's accuracy. 【0303】 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. 【0304】 This invention realizes a system that more effectively supports sales activities by using past judgment data of sales coaches, biometric information of sales representatives, and emotional data recognized by an emotion engine. This system integrates multiple data sources and generates optimal advice in real time. 【0305】 Specifically, the server first retrieves past decision-making data from sales instructors from a pre-established database and uses it for analysis as needed. This data includes successful sales techniques and customer response strategies. 【0306】 Next, the terminal acquires biometric information from the wearable device worn by the sales representative. Simultaneously, software equipped with an emotion engine analyzes emotional data from the sales representative's facial expressions and tone of voice. This combined data makes it possible to monitor the sales representative's biological and emotional state in real time and in detail. 【0307】 Subsequently, the server comprehensively analyzes these data and uses AI algorithms to generate advice that is optimal for the business situation. This advice takes into account the current emotions and mental states of the sales staff and helps provide the most suitable action guidelines. 【0308】 The generated advice is immediately notified visually or audibly to the sales staff through the terminal. This enables the staff to be supported in making appropriate decisions during negotiations and to interact with customers with confidence. 【0309】 For example, if the emotion engine detects signs that the sales staff is nervous during a negotiation, the server can generate specific advice such as "Insert a short break to relax" based on that information. Also, when positive emotions are detected from the customer's reaction, it is possible to generate advice that encourages positive actions such as "Develop an approach towards a positive conclusion." 【0310】 After the negotiation ends, the user inputs feedback into the terminal, and that information is analyzed by the server. This feedback is utilized to improve the accuracy of advice for the next negotiation and to tune the emotion engine. Through such processes, it supports the sales staff in performing at their best in individual negotiations and aims to improve the overall sales ability of the company. 【0311】 The following explains the process flow. 【0312】 Step 1: 【0313】 The server fetches the past judgment data of the sales instructor from the database and prepares it for analysis. This data includes previous negotiation records and outlines of successful sales techniques. 【0314】 Step 2: 【0315】 The terminal receives biometric information such as the salesperson's heart rate and stress level in real time from a wearable device. At the same time, the emotion engine analyzes emotional data from the salesperson's facial expressions and voice and transmits it to the terminal. 【0316】 Step 3: 【0317】 The server combines emotional data and biometric information, and uses AI algorithms to generate advice best suited to the current sales situation. Here, appropriate action guidelines are determined after comprehensively considering the emotional and physical state of the sales representative. 【0318】 Step 4: 【0319】 The server sends the generated advice to the terminal. The terminal displays the notification directly to the sales representative and provides immediate feedback through voice guidance. In this step, the sales representative can instantly know what appropriate action to take during the sales negotiation. 【0320】 Step 5: 【0321】 The user (sales representative) reviews the advice provided on the device and acts upon it in accordance with the flow of the sales negotiation. For example, if the emotion engine detects that the user is feeling nervous, they will try relaxation techniques such as taking deep breaths. 【0322】 Step 6: 【0323】 After the business negotiation concludes, the user enters feedback on the negotiation results and the effectiveness of the advice received into their terminal. This feedback information will be used to improve the accuracy of future advice provided. 【0324】 Step 7: 【0325】 The server records feedback data in a database and uses it to generate advice for the next time and analyze the emotion engine. This leads to an improvement in the overall system performance. 【0326】 (Example 2) 【0327】 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". 【0328】 In sales activities, providing real-time advice based on the physical and emotional state of the salesperson is difficult, resulting in sales performance being dependent on the salesperson's condition. Furthermore, the lack of a system to effectively utilize feedback from sales negotiations and incorporate it into future negotiations leads to insufficient accumulation of sales experience. 【0329】 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. 【0330】 In this invention, the server includes means for storing information based on the past judgments of sales leaders, means for receiving information from a portable device for collecting information on physical condition, and means for analyzing a combination of the information based on the judgments, information on physical condition, and information on emotions to generate optimal advice for sales activities. This enables the provision of real-time advice tailored to the biological and emotional state of sales representatives, and continuous improvement of sales techniques through the use of feedback. 【0331】 "Information based on past decisions of sales leaders" refers to data and information related to decisions and choices made by leaders in past sales activities. 【0332】 "Information regarding physical condition" refers to data that quantifies the sales representative's physical condition, such as heart rate, body temperature, and stress level. 【0333】 A "portable device" is a device that a sales representative can wear and that is used to acquire biometric information. 【0334】 "Emotional information" refers to data on the mental state and emotions extracted from the sales representative's facial expressions and tone of voice. 【0335】 "Means for analysis and generating optimal advice for sales activities" refers to the process of using AI algorithms and generative AI models to analyze collected data and generate appropriate instructions and suggestions for sales activities. 【0336】 "Real-time advice" refers to advice and instructions provided to sales representatives immediately on the spot. 【0337】 "Feedback" refers to evaluations and opinions regarding the results of business negotiations and the implementation of advice, and is information used to improve future interactions. 【0338】 This invention provides a system that effectively supports sales representatives in their sales activities by collecting data from multiple sources and analyzing it using an AI algorithm to generate optimal advice. 【0339】 First, the server retrieves information from a database built on the past decisions of sales leaders. This information includes past success stories and customer service strategies. A database management system is used to securely and efficiently access and retrieve the data. 【0340】 Next, the terminal collects biometric information in real time from a wearable device worn by the sales representative. This device has the function of measuring physical conditions such as heart rate and body temperature, and transmits the information to the terminal via Bluetooth or Wi-Fi. In addition, information about emotions is obtained by analyzing the sales representative's facial expressions and voice using the camera and microphone built into the terminal. 【0341】 The server integrates this information and performs analysis using a generative AI model. Specifically, the AI ​​algorithm creates optimal advice based on biometric data, emotional data, and information derived from past decisions, tailored to the sales situation. This advice is adapted to the salesperson's mental state and the customer's response. 【0342】 Advice is immediately communicated to sales representatives via their devices. Visual displays and audio output are used to provide effective feedback to sales representatives. After a sales meeting, users input feedback on the meeting results into their devices, and this information is sent back to the server. The server analyzes this feedback and uses it to train its generative AI model, thereby improving the accuracy of advice for future sales meetings. 【0343】 For example, when inputting prompt messages into an AI model, you can instruct it to "consider the sales coach's past data, current biometric information, and emotional data, and provide the most effective sales strategy." This allows the system to provide specific, situation-specific advice in real time. 【0344】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0345】 Step 1: 【0346】 The server retrieves information from a database based on the past decisions of sales managers. The input is the decision information stored in the database, and the output is the result of extracting this information. SQL queries are used to retrieve the necessary datasets from the database and prepare the data in memory for the next analysis. 【0347】 Step 2: 【0348】 The terminal receives biometric information from wearable devices worn by sales representatives. Input is biometric data such as heart rate and body temperature generated by the wearable device, while output is organized biometric data stored on the terminal. Data is received in real time using Bluetooth or Wi-Fi connections and stored in a local database. 【0349】 Step 3: 【0350】 The device uses its built-in camera and microphone to collect information about the sales representative's emotions. Inputs are camera footage and audio signals, while output is analyzed emotion data. Image processing and audio analysis algorithms are applied to determine emotions from facial expressions and voice tone, quantifying them and storing them in a database. 【0351】 Step 4: 【0352】 The server integrates acquired judgment information, biometric information, and emotional information, and begins analysis using a generative AI model. The input is all the integrated data, and the output is optimal advice for the sales representative. The AI ​​algorithm analyzes this data and generates actionable guidelines best suited to the sales scenario. 【0353】 Step 5: 【0354】 The terminal notifies sales representatives of advice received from the server. Input is advice data sent from the server, and output is visual or audio notification. The terminal displays text on its screen or uses an audio output device to convey the advice. 【0355】 Step 6: 【0356】 After a sales meeting, the user enters feedback into the terminal. The input consists of the results and opinions of the meeting based on the advice given by the sales representative, and the output is information sent to the server as feedback data. The terminal provides a feedback input interface and sends the entered information to the server. 【0357】 Step 7: 【0358】 The server analyzes the collected feedback data and updates the learning model to reflect the changes in future advice generation. The input is the feedback data received from the user, and the output is the updated AI model. Data analysis and machine learning techniques are used to improve the model's accuracy and prepare for the next business negotiation. 【0359】 (Application Example 2) 【0360】 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." 【0361】 Conventional sales support systems are often limited to sales situations, making it difficult to capture users' emotions and biometric information in real time in various aspects of their daily lives and provide appropriate advice. Furthermore, these systems struggle with natural human interaction, requiring flexible responses in home life support. Therefore, there is a need for a system that can provide appropriate advice in various aspects of daily life based on users' emotions and biometric information. 【0362】 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. 【0363】 In this invention, the server includes means for accumulating past decision data of sales instructors, means for receiving data from a portable device for acquiring biometric information, and means for analyzing the decision data, biometric information, and emotional information in combination to generate advice related to daily life situations. This makes it possible to capture the user's emotions and biological state in real time and automatically provide selective advice related to daily life situations. 【0364】 "Past decision data of sales instructors" refers to accumulated data recording the decisions and actions that sales instructors have taken to date, including successful sales methods and customer service strategies. 【0365】 "Biometric information" refers to information that indicates the user's physical condition, and includes data such as physiological indicators like heart rate, skin temperature, and respiratory rate. 【0366】 "Portable devices" refer to devices that can be worn by users and are easy to carry, and include devices such as wearable devices and smartphones. 【0367】 "Emotional information" refers to information that indicates the user's emotional state, and is data on emotional responses obtained through facial expression analysis and vocal information. 【0368】 A "means for generating advice" refers to a system that analyzes accumulated data and real-time received information to create specific action plans and recommendations for users. 【0369】 "Means of notification via robot" refers to notification methods using robots to deliver generated advice to users through functions such as voice or display. 【0370】 "Feedback" refers to information in which users provide evaluations and opinions on the advice they receive, and this information is used to improve the system in the future. 【0371】 In the system for implementing this invention, the server stores past decision data of sales instructors and extracts necessary information from the stored database. This includes successful sales methods and customer service strategies, which are used for data analysis. In addition, the terminal acquires the user's biometric information through a portable device (e.g., a wearable device). This is combined with software equipped with an emotion engine, which has the function of analyzing emotional information from facial expressions and voice. 【0372】 The server comprehensively analyzes this biometric and emotional information and uses a generative AI model to generate appropriate advice for various life situations. This advice takes into account the user's current emotions and physical state in real time and is communicated to the user via the robot. This communication is provided through voice feedback and visual displays to support the user's actions. 【0373】 For example, if the robot determines that the user is feeling stressed, it might offer specific advice such as, "Why not try listening to your favorite music to relax?" An example of a prompt might be, "Based on the user's current emotions and biometric information, please advise on ways to relax." 【0374】 Furthermore, by allowing users to input feedback after business negotiations and on a daily basis into their devices, this data is further analyzed on the server and used to improve the accuracy of advice generation in the future. In this way, a support system that improves the quality of life is realized. 【0375】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0376】 Step 1: 【0377】 By having the user wear a portable device, the terminal receives biometric information from the wearable device. Data such as heart rate, skin temperature, and respiratory rate are acquired as input and temporarily stored within the terminal. 【0378】 Step 2: 【0379】 The device uses an emotion engine to analyze emotional information from the user's facial expressions and voice. The input is real-time facial and voice data from the user, and the output is data on emotional state and stress levels. This allows for real-time monitoring of the user's mental state. 【0380】 Step 3: 【0381】 The server receives biometric and emotional information acquired from the terminal. Based on the input data, it compares it with a database of past judgments and generates appropriate advice using a generative AI model. The output is specific advice tailored to the user's situation. 【0382】 Step 4: 【0383】 The server sends generated advice to the terminal, which then notifies the user via a robot. Notifications are delivered via voice or display. The input is the generated advice, and the output is the specific action plan presented to the user. 【0384】 Step 5: 【0385】 After a business meeting or during daily life, users input feedback into their device. This input consists of evaluations and opinions on the advice, and the server receives this data to update it for future advice generation. The feedback data is used as training material for the AI ​​model, leading to the generation of more accurate advice. 【0386】 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. 【0387】 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. 【0388】 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. 【0389】 [Third Embodiment] 【0390】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0391】 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. 【0392】 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). 【0393】 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. 【0394】 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. 【0395】 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). 【0396】 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. 【0397】 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. 【0398】 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. 【0399】 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. 【0400】 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. 【0401】 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". 【0402】 This invention realizes a system that provides real-time sales support using the judgment data of sales managers and the biometric information of sales representatives. A specific embodiment of this system is shown below. 【0403】 First, past decision-making data of sales instructors is stored in a database. A server manages this data and prepares it as a resource for later analysis. Specifically, this includes past decisions made by sales instructors, successful sales strategies, and feedback received. 【0404】 Next, sales representatives wear portable devices such as wearable devices to continuously collect biometric information. The devices periodically measure heart rate, stress levels, and other parameters, and transmit this data to a server. This makes it possible to monitor the physical condition of sales representatives in real time during business negotiations. 【0405】 Next, the server combines the collected biometric information with past decision data and performs analysis. Using AI algorithms, it generates appropriate advice for specific sales situations. In this process, the most effective course of action is devised based on the sales coach's past success patterns and the salesperson's current state. 【0406】 The generated advice is immediately notified to the sales representative via the device. It is displayed visually on the screen and can also be provided via voice guidance. This allows the sales representative to respond calmly and effectively during sales negotiations. 【0407】 For example, when a salesperson is about to meet with a new client, the server analyzes past successful deals with similar clients and, based on current biometric data, advises the salesperson to "ask more questions and focus on active listening." If the salesperson's heart rate starts to increase during the meeting, the server suggests "taking a deep breath to calm down." 【0408】 After a sales negotiation concludes, the sales representative inputs their experience and results as feedback. The server uses this data to improve the quality of AI advice for future sales activities and to further enhance the system. 【0409】 In this way, the present invention aims to help sales representatives maintain peak performance in individual business negotiations and improve the overall sales capabilities of the company. 【0410】 The following describes the processing flow. 【0411】 Step 1: 【0412】 The server retrieves past decision-making data from sales coaches from a database and prepares it for analysis. This data includes details of past sales strategies and specific advice given. 【0413】 Step 2: 【0414】 The terminal receives biometric information from wearable devices carried by sales representatives. This information includes heart rate, stress levels, and other data, and is continuously monitored in real time. 【0415】 Step 3: 【0416】 The server combines biometric information transmitted from the terminal with past decision data acquired in Step 1 and performs analysis using an AI algorithm. This analysis is a process that generates advice tailored to the current business situation. 【0417】 Step 4: 【0418】 The server sends advice generated based on the analysis to the terminal. The advice is notified to the sales representative in a visual or audio manner. 【0419】 Step 5: 【0420】 The user (sales representative) reviews the advice displayed on the terminal and takes specific actions based on it. By making adjustments according to the situation during the sales negotiation, they can conduct effective sales activities. 【0421】 Step 6: 【0422】 After the business negotiation concludes, the user enters feedback on the negotiation results and the effectiveness of the advice into their device. This feedback will be used for future information analysis and advice generation. 【0423】 Step 7: 【0424】 The server receives feedback data and stores it in a database to help improve the accuracy of the AI ​​algorithm and generate future advice. This enables continuous improvement of the system. 【0425】 (Example 1) 【0426】 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." 【0427】 Making optimal decisions in real time during sales negotiations is often difficult for sales representatives. Furthermore, while providing accurate advice tailored to the negotiation situation and the individual representative's condition is crucial, traditional methods have failed to fully utilize the representative's physical condition or past success stories. This hinders the maximization of sales effectiveness. 【0428】 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. 【0429】 In this invention, the server includes means for an information processing device to store past decision data, means for receiving biometric data from an information acquisition device, and means for integrating and analyzing the decision data and biometric data to generate operational guidelines regarding sales status. This enables sales representatives to receive appropriate advice in real time for each business negotiation, thereby improving sales performance. 【0430】 An "information processing device" is a device used to store and analyze past decision data. 【0431】 "Information acquisition device" refers to various sensors and devices that collect biometric data from sales representatives. 【0432】 "Biometric data" refers to data that indicates the physical condition of sales representatives, such as their heart rate and stress index. 【0433】 "Action guidelines" refer to specific action plans and advice generated in response to business conditions. 【0434】 A "generative AI model" refers to an artificial intelligence system that analyzes a situation based on past success stories and real-time biometric data to generate appropriate advice. 【0435】 A "communication device" is an electronic device used to notify sales representatives of the generated operational guidelines. 【0436】 "Observation" refers to the act of monitoring changes in the biometric data of a sales representative in real time during a business negotiation. 【0437】 "Feedback" refers to evaluations and information based on the results of implementing the action guidelines provided by the sales representative. 【0438】 A "learning tool" is a system that utilizes collected feedback to improve the quality of future action guidelines. 【0439】 This invention is based on a system in which an information processing device (server) stores past decision data of sales instructors in a database. The stored data includes past successful sales strategies and feedback. 【0440】 Next, the terminal acquires biometric data from the information acquisition device (wearable device) worn by the sales representative. Specifically, it collects data such as heart rate and stress index, and transfers this data to the information processing device. Since the transfer is done using wireless communication technology, the sales representative's biometric data is continuously updated in real time even during business negotiations. 【0441】 The information processing device analyzes received biometric data and accumulated decision data using a generating AI model. This analysis generates action guidelines tailored to the business situation. The generating AI model evaluates the situation based on past success stories and real-time biometric data, and formulates the optimal course of action. 【0442】 The generated operational guidelines are notified to the sales representative via their device. The notification is delivered via voice guidance and display, allowing the sales representative to respond quickly during sales negotiations. 【0443】 For example, the server analyzes past success data from negotiations with new customers and generates suggestions such as "ask more questions to capture the customer's interest," and immediately provides advice such as "take a deep breath to relax" when your heart rate is elevated. 【0444】 After a business negotiation is completed, feedback on the results of the actions the user took is entered into the server. This feedback is analyzed and used as foundational data to improve the quality of future action guidelines. This allows for continuous improvement of the overall system's effectiveness. 【0445】 (Example of a prompt message) 【0446】 "Generate sales advice based on past success stories and real-time biometric data." 【0447】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0448】 Step 1: 【0449】 The server stores past decision-making data from sales leaders. This data includes past successful sales strategies and feedback. Past decision-making data is used as input, and this data is organized and stored in a database as output. During this process, the data is filtered and classified, and prepared in a format that can be used for later analysis. 【0450】 Step 2: 【0451】 The terminal acquires biometric data from the information acquisition device worn by the sales representative. Inputs include heart rate and stress index, which are measured in real time and transmitted wirelessly to the server as output. This process involves signal conversion and data standardization, allowing the server to receive the data in a format suitable for analysis. 【0452】 Step 3: 【0453】 The server integrates received biometric data with accumulated decision data and performs analysis using an AI algorithm. Inputs include historical decision data and real-time biometric data, and output is the generation of action guidelines tailored to specific business situations. This analysis process utilizes a generative AI model, performing pattern matching and predictive analysis based on past success stories. 【0454】 Step 4: 【0455】 The server notifies sales representatives of the generated operational guidelines via their terminals. The operational guidelines are taken as input, and are output in text or audio format, transmitted through the terminal's display or speaker. Through user interface control, the guidelines are visually verifiable, and audio guidance is provided as needed. 【0456】 Step 5: 【0457】 Sales representatives, as users, input feedback into the server after a sales meeting. This feedback includes the results of the actions taken, and the feedback data is used as input. The server analyzes this data and updates the database for future action guideline generation. The feedback analysis involves pattern recognition and text analysis, which are used to improve the accuracy of future guidelines. 【0458】 (Application Example 1) 【0459】 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." 【0460】 Sales representatives need to make immediate decisions about appropriate actions during negotiations, but it is difficult for them to receive real-time advice tailored to the specific negotiation situation and the sales representative's physical condition. Furthermore, while there is a need to leverage past success patterns to provide optimal advice during negotiations, there is a lack of effective systems for this purpose. 【0461】 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. 【0462】 In this invention, the server includes means for storing past decision information of sales instructors, means for receiving information from a portable device for acquiring physical information, means for analyzing the combination of the decision information and physical information to generate advice regarding the sales situation, and means for operating a robot to support sales activities. This enables real-time advice based on the physical condition of sales representatives during business negotiations, allowing sales representatives to take appropriate action immediately. 【0463】 A "sales leader" is a person or organization responsible for formulating policies and strategies in sales activities and providing guidance and advice to sales representatives. 【0464】 "Judgment information" refers to data obtained from the knowledge and experience of sales activities, such as the history of decisions made by sales instructors in the past, successful strategies, and the content of their guidance. 【0465】 "Physiological information" refers to data indicating physiological states, such as heart rate and stress level, obtained by sales representatives from wearable devices, etc. 【0466】 A "portable device" is a highly mobile device that can be worn by sales representatives to collect personal information. 【0467】 "Advice" refers to instructions or suggestions regarding appropriate actions or responses provided to sales representatives in response to the circumstances during their sales activities. 【0468】 "Means of supporting sales activities by operating robots" refers to robot systems that have the function of providing appropriate advice to sales representatives during business negotiations via voice or display. 【0469】 This invention is designed as a system to effectively support sales activities. The system operates with a server, a portable device, and a robot working together. The server is responsible for storing and managing past decision-making information of sales leaders in a database. This includes past successful strategies and decision-making history. 【0470】 A portable device, specifically a wearable device, continuously measures the physical information of sales representatives and transmits the acquired physiological data to a server. This device detects heart rate, stress levels, and other parameters, and transmits the data via Bluetooth or Wi-Fi. 【0471】 The server combines and analyzes the received physical information with the accumulated judgment information. This analysis uses AI algorithms to generate appropriate advice tailored to specific business situations. Generative AI models enable iterative learning and analysis of data. For example, machine learning libraries such as TensorFlow and PyTorch are used. 【0472】 The generated advice is communicated to the sales representative via the robot, either verbally or visually on a display. The robot accompanies the sales representative to the sales meeting, supporting them in receiving real-time advice based on their physical information. It can also prompt specific actions. 【0473】 For example, when a sales representative is about to meet with a new client, the system might offer advice such as, "We previously found the following approach effective with this company. Please increase the number of questions to capture the client's interest." If tension rises, it might also suggest, "Take a deep breath to relax." 【0474】 An example of a prompt would be, "Based on the sales representative's biometric information and past success data, please provide the optimal strategy to help during the sales negotiation." This prompt is presented to the AI ​​generation model, enabling the generation of specific advice tailored to the sales situation. 【0475】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0476】 Step 1: 【0477】 The user wears a wearable device. The device continuously measures the user's physical information, such as heart rate and stress level. This information is acquired by the device in real time. 【0478】 Step 2: 【0479】 The device transmits physical information collected from wearable devices to a server via Bluetooth or Wi-Fi. The input data includes heart rate and stress level, and the server receives this data and logs it. 【0480】 Step 3: 【0481】 The server begins analysis by combining accumulated past judgment data of sales instructors with received physical information. Using an AI algorithm, it performs pattern recognition and data mining based on this data to generate optimal advice tailored to the sales situation. The output is specific advice for sales representatives. 【0482】 Step 4: 【0483】 The server sends the generated advice to the robot. The robot provides advice to the user during the sales negotiation via a voice assistant or display. The output is expressed as a voice message or display message. 【0484】 Step 5: 【0485】 After a business negotiation concludes, the user enters feedback about the negotiation into their device. The device sends this feedback to the server, which then uses the feedback to retrain the AI ​​model for future advice generation. This feedback is crucial data for improving the AI's accuracy. 【0486】 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. 【0487】 This invention realizes a system that more effectively supports sales activities by using past judgment data of sales coaches, biometric information of sales representatives, and emotional data recognized by an emotion engine. This system integrates multiple data sources and generates optimal advice in real time. 【0488】 Specifically, the server first retrieves past decision-making data from sales instructors from a pre-established database and uses it for analysis as needed. This data includes successful sales techniques and customer response strategies. 【0489】 Next, the terminal acquires biometric information from the wearable device worn by the sales representative. Simultaneously, software equipped with an emotion engine analyzes emotional data from the sales representative's facial expressions and tone of voice. This combined data makes it possible to monitor the sales representative's biological and emotional state in real time and in detail. 【0490】 Next, the server comprehensively analyzes this data and uses AI algorithms to generate optimal advice for the sales situation. This advice helps provide the most appropriate course of action, taking into account the sales representative's current emotions and mental state. 【0491】 The generated advice is immediately communicated to the sales representative via their device, either visually or audibly. This supports the representative in making informed decisions during sales negotiations, allowing them to confidently interact with customers. 【0492】 For example, if the emotion engine detects signs of tension in a sales representative during a business negotiation, the server can use that information to generate specific advice such as "take a short break to help them relax." Similarly, if positive emotions are detected from the customer's reactions, the system can generate advice encouraging positive actions, such as "develop a proactive approach to closing the deal." 【0493】 After a sales meeting concludes, users input feedback into their terminals, and this information is analyzed on a server. This feedback is used to improve the accuracy of advice for future meetings and to fine-tune the emotional engine. Through this process, we support sales representatives in achieving their best performance in individual sales meetings and aim to improve the overall sales capabilities of the company. 【0494】 The following describes the processing flow. 【0495】 Step 1: 【0496】 The server retrieves past decision-making data from the sales coaches' database and prepares it for analysis. This data includes records of previous sales negotiations and summaries of successful sales techniques. 【0497】 Step 2: 【0498】 The terminal receives biometric information such as the salesperson's heart rate and stress level in real time from a wearable device. At the same time, the emotion engine analyzes emotional data from the salesperson's facial expressions and voice and transmits it to the terminal. 【0499】 Step 3: 【0500】 The server combines emotional data and biometric information, and uses AI algorithms to generate advice best suited to the current sales situation. Here, appropriate action guidelines are determined after comprehensively considering the emotional and physical state of the sales representative. 【0501】 Step 4: 【0502】 The server sends the generated advice to the terminal. The terminal displays the notification directly to the sales representative and provides immediate feedback through voice guidance. In this step, the sales representative can instantly know what appropriate action to take during the sales negotiation. 【0503】 Step 5: 【0504】 The user (sales representative) reviews the advice provided on the device and acts upon it in accordance with the flow of the sales negotiation. For example, if the emotion engine detects that the user is feeling nervous, they will try relaxation techniques such as taking deep breaths. 【0505】 Step 6: 【0506】 After the business negotiation concludes, the user enters feedback on the negotiation results and the effectiveness of the advice received into their terminal. This feedback information will be used to improve the accuracy of future advice provided. 【0507】 Step 7: 【0508】 The server records feedback data in a database and uses it to generate advice for the next time and analyze the emotion engine. This leads to an improvement in the overall system performance. 【0509】 (Example 2) 【0510】 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." 【0511】 In sales activities, providing real-time advice based on the physical and emotional state of the salesperson is difficult, resulting in sales performance being dependent on the salesperson's condition. Furthermore, the lack of a system to effectively utilize feedback from sales negotiations and incorporate it into future negotiations leads to insufficient accumulation of sales experience. 【0512】 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. 【0513】 In this invention, the server includes means for storing information based on the past judgments of sales leaders, means for receiving information from a portable device for collecting information on physical condition, and means for analyzing a combination of the information based on the judgments, information on physical condition, and information on emotions to generate optimal advice for sales activities. This enables the provision of real-time advice tailored to the biological and emotional state of sales representatives, and continuous improvement of sales techniques through the use of feedback. 【0514】 "Information based on past decisions of sales leaders" refers to data and information related to decisions and choices made by leaders in past sales activities. 【0515】 "Information regarding physical condition" refers to data that quantifies the sales representative's physical condition, such as heart rate, body temperature, and stress level. 【0516】 A "portable device" is a device that a sales representative can wear and that is used to acquire biometric information. 【0517】 "Emotional information" refers to data on the mental state and emotions extracted from the sales representative's facial expressions and tone of voice. 【0518】 "Means for analysis and generating optimal advice for sales activities" refers to the process of using AI algorithms and generative AI models to analyze collected data and generate appropriate instructions and suggestions for sales activities. 【0519】 "Real-time advice" refers to advice and instructions provided to sales representatives immediately on the spot. 【0520】 "Feedback" refers to evaluations and opinions regarding the results of business negotiations and the implementation of advice, and is information used to improve future interactions. 【0521】 This invention provides a system that effectively supports sales representatives in their sales activities by collecting data from multiple sources and analyzing it using an AI algorithm to generate optimal advice. 【0522】 First, the server retrieves information from a database built on the past decisions of sales leaders. This information includes past success stories and customer service strategies. A database management system is used to securely and efficiently access and retrieve the data. 【0523】 Next, the terminal collects biometric information in real time from a wearable device worn by the sales representative. This device has the function of measuring physical conditions such as heart rate and body temperature, and transmits the information to the terminal via Bluetooth or Wi-Fi. In addition, information about emotions is obtained by analyzing the sales representative's facial expressions and voice using the camera and microphone built into the terminal. 【0524】 The server integrates this information and performs analysis using a generative AI model. Specifically, the AI ​​algorithm creates optimal advice based on biometric data, emotional data, and information derived from past decisions, tailored to the sales situation. This advice is adapted to the salesperson's mental state and the customer's response. 【0525】 Advice is immediately communicated to sales representatives via their devices. Visual displays and audio output are used to provide effective feedback to sales representatives. After a sales meeting, users input feedback on the meeting results into their devices, and this information is sent back to the server. The server analyzes this feedback and uses it to train its generative AI model, thereby improving the accuracy of advice for future sales meetings. 【0526】 For example, when inputting prompt messages into an AI model, you can instruct it to "consider the sales coach's past data, current biometric information, and emotional data, and provide the most effective sales strategy." This allows the system to provide specific, situation-specific advice in real time. 【0527】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0528】 Step 1: 【0529】 The server retrieves information from a database based on the past decisions of sales managers. The input is the decision information stored in the database, and the output is the result of extracting this information. SQL queries are used to retrieve the necessary datasets from the database and prepare the data in memory for the next analysis. 【0530】 Step 2: 【0531】 The terminal receives biometric information from wearable devices worn by sales representatives. Input is biometric data such as heart rate and body temperature generated by the wearable device, while output is organized biometric data stored on the terminal. Data is received in real time using Bluetooth or Wi-Fi connections and stored in a local database. 【0532】 Step 3: 【0533】 The device uses its built-in camera and microphone to collect information about the sales representative's emotions. Inputs are camera footage and audio signals, while output is analyzed emotion data. Image processing and audio analysis algorithms are applied to determine emotions from facial expressions and voice tone, quantifying them and storing them in a database. 【0534】 Step 4: 【0535】 The server integrates acquired judgment information, biometric information, and emotional information, and begins analysis using a generative AI model. The input is all the integrated data, and the output is optimal advice for the sales representative. The AI ​​algorithm analyzes this data and generates actionable guidelines best suited to the sales scenario. 【0536】 Step 5: 【0537】 The terminal notifies sales representatives of advice received from the server. Input is advice data sent from the server, and output is visual or audio notification. The terminal displays text on its screen or uses an audio output device to convey the advice. 【0538】 Step 6: 【0539】 After a sales meeting, the user enters feedback into the terminal. The input consists of the results and opinions of the meeting based on the advice given by the sales representative, and the output is information sent to the server as feedback data. The terminal provides a feedback input interface and sends the entered information to the server. 【0540】 Step 7: 【0541】 The server analyzes the collected feedback data and updates the learning model to reflect the changes in future advice generation. The input is the feedback data received from the user, and the output is the updated AI model. Data analysis and machine learning techniques are used to improve the model's accuracy and prepare for the next business negotiation. 【0542】 (Application Example 2) 【0543】 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." 【0544】 Conventional sales support systems are often limited to sales situations, making it difficult to capture users' emotions and biometric information in real time in various aspects of their daily lives and provide appropriate advice. Furthermore, these systems struggle with natural human interaction, requiring flexible responses in home life support. Therefore, there is a need for a system that can provide appropriate advice in various aspects of daily life based on users' emotions and biometric information. 【0545】 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. 【0546】 In this invention, the server includes means for accumulating past decision data of sales instructors, means for receiving data from a portable device for acquiring biometric information, and means for analyzing the decision data, biometric information, and emotional information in combination to generate advice related to daily life situations. This makes it possible to capture the user's emotions and biological state in real time and automatically provide selective advice related to daily life situations. 【0547】 "Past decision data of sales instructors" refers to accumulated data recording the decisions and actions that sales instructors have taken to date, including successful sales methods and customer service strategies. 【0548】 "Biometric information" refers to information that indicates the user's physical condition, and includes data such as physiological indicators like heart rate, skin temperature, and respiratory rate. 【0549】 "Portable devices" refer to devices that can be worn by users and are easy to carry, and include devices such as wearable devices and smartphones. 【0550】 "Emotional information" refers to information that indicates the user's emotional state, and is data on emotional responses obtained through facial expression analysis and vocal information. 【0551】 A "means for generating advice" refers to a system that analyzes accumulated data and real-time received information to create specific action plans and recommendations for users. 【0552】 "Means of notification via robot" refers to notification methods using robots to deliver generated advice to users through functions such as voice or display. 【0553】 "Feedback" refers to information in which users provide evaluations and opinions on the advice they receive, and this information is used to improve the system in the future. 【0554】 In the system for implementing this invention, the server stores past decision data of sales instructors and extracts necessary information from the stored database. This includes successful sales methods and customer service strategies, which are used for data analysis. In addition, the terminal acquires the user's biometric information through a portable device (e.g., a wearable device). This is combined with software equipped with an emotion engine, which has the function of analyzing emotional information from facial expressions and voice. 【0555】 The server comprehensively analyzes this biometric and emotional information and uses a generative AI model to generate appropriate advice for various life situations. This advice takes into account the user's current emotions and physical state in real time and is communicated to the user via the robot. This communication is provided through voice feedback and visual displays to support the user's actions. 【0556】 For example, if the robot determines that the user is feeling stressed, it might offer specific advice such as, "Why not try listening to your favorite music to relax?" An example of a prompt might be, "Based on the user's current emotions and biometric information, please advise on ways to relax." 【0557】 Furthermore, by allowing users to input feedback after business negotiations and on a daily basis into their devices, this data is further analyzed on the server and used to improve the accuracy of advice generation in the future. In this way, a support system that improves the quality of life is realized. 【0558】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0559】 Step 1: 【0560】 By having the user wear a portable device, the terminal receives biometric information from the wearable device. Data such as heart rate, skin temperature, and respiratory rate are acquired as input and temporarily stored within the terminal. 【0561】 Step 2: 【0562】 The device uses an emotion engine to analyze emotional information from the user's facial expressions and voice. The input is real-time facial and voice data from the user, and the output is data on emotional state and stress levels. This allows for real-time monitoring of the user's mental state. 【0563】 Step 3: 【0564】 The server receives biometric and emotional information acquired from the terminal. Based on the input data, it compares it with a database of past judgments and generates appropriate advice using a generative AI model. The output is specific advice tailored to the user's situation. 【0565】 Step 4: 【0566】 The server sends generated advice to the terminal, which then notifies the user via a robot. Notifications are delivered via voice or display. The input is the generated advice, and the output is the specific action plan presented to the user. 【0567】 Step 5: 【0568】 After a business meeting or during daily life, users input feedback into their device. This input consists of evaluations and opinions on the advice, and the server receives this data to update it for future advice generation. The feedback data is used as training material for the AI ​​model, leading to the generation of more accurate advice. 【0569】 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. 【0570】 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. 【0571】 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. 【0572】 [Fourth Embodiment] 【0573】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0574】 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. 【0575】 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). 【0576】 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. 【0577】 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. 【0578】 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). 【0579】 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. 【0580】 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. 【0581】 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. 【0582】 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. 【0583】 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. 【0584】 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. 【0585】 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". 【0586】 This invention realizes a system that provides real-time sales support using the judgment data of sales managers and the biometric information of sales representatives. A specific embodiment of this system is shown below. 【0587】 First, past decision-making data of sales instructors is stored in a database. A server manages this data and prepares it as a resource for later analysis. Specifically, this includes past decisions made by sales instructors, successful sales strategies, and feedback received. 【0588】 Next, sales representatives wear portable devices such as wearable devices to continuously collect biometric information. The devices periodically measure heart rate, stress levels, and other parameters, and transmit this data to a server. This makes it possible to monitor the physical condition of sales representatives in real time during business negotiations. 【0589】 Next, the server combines the collected biometric information with past decision data and performs analysis. Using AI algorithms, it generates appropriate advice for specific sales situations. In this process, the most effective course of action is devised based on the sales coach's past success patterns and the salesperson's current state. 【0590】 The generated advice is immediately notified to the sales representative via the device. It is displayed visually on the screen and can also be provided via voice guidance. This allows the sales representative to respond calmly and effectively during sales negotiations. 【0591】 For example, when a salesperson is about to meet with a new client, the server analyzes past successful deals with similar clients and, based on current biometric data, advises the salesperson to "ask more questions and focus on active listening." If the salesperson's heart rate starts to increase during the meeting, the server suggests "taking a deep breath to calm down." 【0592】 After a sales negotiation concludes, the sales representative inputs their experience and results as feedback. The server uses this data to improve the quality of AI advice for future sales activities and to further enhance the system. 【0593】 In this way, the present invention aims to help sales representatives maintain peak performance in individual business negotiations and improve the overall sales capabilities of the company. 【0594】 The following describes the processing flow. 【0595】 Step 1: 【0596】 The server retrieves past decision-making data from sales coaches from a database and prepares it for analysis. This data includes details of past sales strategies and specific advice given. 【0597】 Step 2: 【0598】 The terminal receives biometric information from wearable devices carried by sales representatives. This information includes heart rate, stress levels, and other data, and is continuously monitored in real time. 【0599】 Step 3: 【0600】 The server combines biometric information transmitted from the terminal with past decision data acquired in Step 1 and performs analysis using an AI algorithm. This analysis is a process that generates advice tailored to the current business situation. 【0601】 Step 4: 【0602】 The server sends advice generated based on the analysis to the terminal. The advice is notified to the sales representative in a visual or audio manner. 【0603】 Step 5: 【0604】 The user (sales representative) reviews the advice displayed on the terminal and takes specific actions based on it. By making adjustments according to the situation during the sales negotiation, they can conduct effective sales activities. 【0605】 Step 6: 【0606】 After the business negotiation concludes, the user enters feedback on the negotiation results and the effectiveness of the advice into their device. This feedback will be used for future information analysis and advice generation. 【0607】 Step 7: 【0608】 The server receives feedback data and stores it in a database to help improve the accuracy of the AI ​​algorithm and generate future advice. This enables continuous improvement of the system. 【0609】 (Example 1) 【0610】 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". 【0611】 Making optimal decisions in real time during sales negotiations is often difficult for sales representatives. Furthermore, while providing accurate advice tailored to the negotiation situation and the individual representative's condition is crucial, traditional methods have failed to fully utilize the representative's physical condition or past success stories. This hinders the maximization of sales effectiveness. 【0612】 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. 【0613】 In this invention, the server includes means for an information processing device to store past decision data, means for receiving biometric data from an information acquisition device, and means for integrating and analyzing the decision data and biometric data to generate operational guidelines regarding sales status. This enables sales representatives to receive appropriate advice in real time for each business negotiation, thereby improving sales performance. 【0614】 An "information processing device" is a device used to store and analyze past decision data. 【0615】 "Information acquisition device" refers to various sensors and devices that collect biometric data from sales representatives. 【0616】 "Biometric data" refers to data that indicates the physical condition of sales representatives, such as their heart rate and stress index. 【0617】 "Action guidelines" refer to specific action plans and advice generated in response to business conditions. 【0618】 A "generative AI model" refers to an artificial intelligence system that analyzes a situation based on past success stories and real-time biometric data to generate appropriate advice. 【0619】 A "communication device" is an electronic device used to notify sales representatives of the generated operational guidelines. 【0620】 "Observation" refers to the act of monitoring changes in the biometric data of a sales representative in real time during a business negotiation. 【0621】 "Feedback" refers to evaluations and information based on the results of implementing the action guidelines provided by the sales representative. 【0622】 A "learning tool" is a system that utilizes collected feedback to improve the quality of future action guidelines. 【0623】 This invention is based on a system in which an information processing device (server) stores past decision data of sales instructors in a database. The stored data includes past successful sales strategies and feedback. 【0624】 Next, the terminal acquires biometric data from the information acquisition device (wearable device) worn by the sales representative. Specifically, it collects data such as heart rate and stress index, and transfers this data to the information processing device. Since the transfer is done using wireless communication technology, the sales representative's biometric data is continuously updated in real time even during business negotiations. 【0625】 The information processing device analyzes received biometric data and accumulated decision data using a generating AI model. This analysis generates action guidelines tailored to the business situation. The generating AI model evaluates the situation based on past success stories and real-time biometric data, and formulates the optimal course of action. 【0626】 The generated operational guidelines are notified to the sales representative via their device. The notification is delivered via voice guidance and display, allowing the sales representative to respond quickly during sales negotiations. 【0627】 For example, the server analyzes past success data from negotiations with new customers and generates suggestions such as "ask more questions to capture the customer's interest," and immediately provides advice such as "take a deep breath to relax" when your heart rate is elevated. 【0628】 After a business negotiation is completed, feedback on the results of the actions the user took is entered into the server. This feedback is analyzed and used as foundational data to improve the quality of future action guidelines. This allows for continuous improvement of the overall system's effectiveness. 【0629】 (Example of a prompt message) 【0630】 "Generate sales advice based on past success stories and real-time biometric data." 【0631】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0632】 Step 1: 【0633】 The server stores past decision-making data from sales leaders. This data includes past successful sales strategies and feedback. Past decision-making data is used as input, and this data is organized and stored in a database as output. During this process, the data is filtered and classified, and prepared in a format that can be used for later analysis. 【0634】 Step 2: 【0635】 The terminal acquires biometric data from the information acquisition device worn by the sales representative. Inputs include heart rate and stress index, which are measured in real time and transmitted wirelessly to the server as output. This process involves signal conversion and data standardization, allowing the server to receive the data in a format suitable for analysis. 【0636】 Step 3: 【0637】 The server integrates received biometric data with accumulated decision data and performs analysis using an AI algorithm. Inputs include historical decision data and real-time biometric data, and output is the generation of action guidelines tailored to specific business situations. This analysis process utilizes a generative AI model, performing pattern matching and predictive analysis based on past success stories. 【0638】 Step 4: 【0639】 The server notifies sales representatives of the generated operational guidelines via their terminals. The operational guidelines are taken as input, and are output in text or audio format, transmitted through the terminal's display or speaker. Through user interface control, the guidelines are visually verifiable, and audio guidance is provided as needed. 【0640】 Step 5: 【0641】 Sales representatives, as users, input feedback into the server after a sales meeting. This feedback includes the results of the actions taken, and the feedback data is used as input. The server analyzes this data and updates the database for future action guideline generation. The feedback analysis involves pattern recognition and text analysis, which are used to improve the accuracy of future guidelines. 【0642】 (Application Example 1) 【0643】 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". 【0644】 Sales representatives need to make immediate decisions about appropriate actions during negotiations, but it is difficult for them to receive real-time advice tailored to the specific negotiation situation and the sales representative's physical condition. Furthermore, while there is a need to leverage past success patterns to provide optimal advice during negotiations, there is a lack of effective systems for this purpose. 【0645】 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. 【0646】 In this invention, the server includes means for storing past decision information of sales instructors, means for receiving information from a portable device for acquiring physical information, means for analyzing the combination of the decision information and physical information to generate advice regarding the sales situation, and means for operating a robot to support sales activities. This enables real-time advice based on the physical condition of sales representatives during business negotiations, allowing sales representatives to take appropriate action immediately. 【0647】 A "sales leader" is a person or organization responsible for formulating policies and strategies in sales activities and providing guidance and advice to sales representatives. 【0648】 "Judgment information" refers to data obtained from the knowledge and experience of sales activities, such as the history of decisions made by sales instructors in the past, successful strategies, and the content of their guidance. 【0649】 "Physiological information" refers to data indicating physiological states, such as heart rate and stress level, obtained by sales representatives from wearable devices, etc. 【0650】 A "portable device" is a highly mobile device that can be worn by sales representatives to collect personal information. 【0651】 "Advice" refers to instructions or suggestions regarding appropriate actions or responses provided to sales representatives in response to the circumstances during their sales activities. 【0652】 "Means of supporting sales activities by operating robots" refers to robot systems that have the function of providing appropriate advice to sales representatives during business negotiations via voice or display. 【0653】 This invention is designed as a system to effectively support sales activities. The system operates with a server, a portable device, and a robot working together. The server is responsible for storing and managing past decision-making information of sales leaders in a database. This includes past successful strategies and decision-making history. 【0654】 A portable device, specifically a wearable device, continuously measures the physical information of sales representatives and transmits the acquired physiological data to a server. This device detects heart rate, stress levels, and other parameters, and transmits the data via Bluetooth or Wi-Fi. 【0655】 The server combines and analyzes the received physical information with the accumulated judgment information. This analysis uses AI algorithms to generate appropriate advice tailored to specific business situations. Generative AI models enable iterative learning and analysis of data. For example, machine learning libraries such as TensorFlow and PyTorch are used. 【0656】 The generated advice is communicated to the sales representative via the robot, either verbally or visually on a display. The robot accompanies the sales representative to the sales meeting, supporting them in receiving real-time advice based on their physical information. It can also prompt specific actions. 【0657】 For example, when a sales representative is about to meet with a new client, the system might offer advice such as, "We previously found the following approach effective with this company. Please increase the number of questions to capture the client's interest." If tension rises, it might also suggest, "Take a deep breath to relax." 【0658】 An example of a prompt would be, "Based on the sales representative's biometric information and past success data, please provide the optimal strategy to help during the sales negotiation." This prompt is presented to the AI ​​generation model, enabling the generation of specific advice tailored to the sales situation. 【0659】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0660】 Step 1: 【0661】 The user wears a wearable device. The device continuously measures the user's physical information, such as heart rate and stress level. This information is acquired by the device in real time. 【0662】 Step 2: 【0663】 The device transmits physical information collected from wearable devices to a server via Bluetooth or Wi-Fi. The input data includes heart rate and stress level, and the server receives this data and logs it. 【0664】 Step 3: 【0665】 The server begins analysis by combining accumulated past judgment data of sales instructors with received physical information. Using an AI algorithm, it performs pattern recognition and data mining based on this data to generate optimal advice tailored to the sales situation. The output is specific advice for sales representatives. 【0666】 Step 4: 【0667】 The server sends the generated advice to the robot. The robot provides advice to the user during the sales negotiation via a voice assistant or display. The output is expressed as a voice message or display message. 【0668】 Step 5: 【0669】 After a business negotiation concludes, the user enters feedback about the negotiation into their device. The device sends this feedback to the server, which then uses the feedback to retrain the AI ​​model for future advice generation. This feedback is crucial data for improving the AI's accuracy. 【0670】 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. 【0671】 This invention realizes a system that more effectively supports sales activities by using past judgment data of sales coaches, biometric information of sales representatives, and emotional data recognized by an emotion engine. This system integrates multiple data sources and generates optimal advice in real time. 【0672】 Specifically, the server first retrieves past decision-making data from sales instructors from a pre-established database and uses it for analysis as needed. This data includes successful sales techniques and customer response strategies. 【0673】 Next, the terminal acquires biometric information from the wearable device worn by the sales representative. Simultaneously, software equipped with an emotion engine analyzes emotional data from the sales representative's facial expressions and tone of voice. This combined data makes it possible to monitor the sales representative's biological and emotional state in real time and in detail. 【0674】 Next, the server comprehensively analyzes this data and uses AI algorithms to generate optimal advice for the sales situation. This advice helps provide the most appropriate course of action, taking into account the sales representative's current emotions and mental state. 【0675】 The generated advice is immediately communicated to the sales representative via their device, either visually or audibly. This supports the representative in making informed decisions during sales negotiations, allowing them to confidently interact with customers. 【0676】 For example, if the emotion engine detects signs of tension in a sales representative during a business negotiation, the server can use that information to generate specific advice such as "take a short break to help them relax." Similarly, if positive emotions are detected from the customer's reactions, the system can generate advice encouraging positive actions, such as "develop a proactive approach to closing the deal." 【0677】 After a sales meeting concludes, users input feedback into their terminals, and this information is analyzed on a server. This feedback is used to improve the accuracy of advice for future meetings and to fine-tune the emotional engine. Through this process, we support sales representatives in achieving their best performance in individual sales meetings and aim to improve the overall sales capabilities of the company. 【0678】 The following describes the processing flow. 【0679】 Step 1: 【0680】 The server retrieves past decision-making data from the sales coaches' database and prepares it for analysis. This data includes records of previous sales negotiations and summaries of successful sales techniques. 【0681】 Step 2: 【0682】 The terminal receives biometric information such as the salesperson's heart rate and stress level in real time from a wearable device. At the same time, the emotion engine analyzes emotional data from the salesperson's facial expressions and voice and transmits it to the terminal. 【0683】 Step 3: 【0684】 The server combines emotional data and biometric information, and uses AI algorithms to generate advice best suited to the current sales situation. Here, appropriate action guidelines are determined after comprehensively considering the emotional and physical state of the sales representative. 【0685】 Step 4: 【0686】 The server sends the generated advice to the terminal. The terminal displays the notification directly to the sales representative and provides immediate feedback through voice guidance. In this step, the sales representative can instantly know what appropriate action to take during the sales negotiation. 【0687】 Step 5: 【0688】 The user (sales representative) reviews the advice provided on the device and acts upon it in accordance with the flow of the sales negotiation. For example, if the emotion engine detects that the user is feeling nervous, they will try relaxation techniques such as taking deep breaths. 【0689】 Step 6: 【0690】 After the business negotiation concludes, the user enters feedback on the negotiation results and the effectiveness of the advice received into their terminal. This feedback information will be used to improve the accuracy of future advice provided. 【0691】 Step 7: 【0692】 The server records feedback data in a database and uses it to generate advice for the next time and analyze the emotion engine. This leads to an improvement in the overall system performance. 【0693】 (Example 2) 【0694】 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". 【0695】 In sales activities, providing real-time advice based on the physical and emotional state of the salesperson is difficult, resulting in sales performance being dependent on the salesperson's condition. Furthermore, the lack of a system to effectively utilize feedback from sales negotiations and incorporate it into future negotiations leads to insufficient accumulation of sales experience. 【0696】 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. 【0697】 In this invention, the server includes means for storing information based on the past judgments of sales leaders, means for receiving information from a portable device for collecting information on physical condition, and means for analyzing a combination of the information based on the judgments, information on physical condition, and information on emotions to generate optimal advice for sales activities. This enables the provision of real-time advice tailored to the biological and emotional state of sales representatives, and continuous improvement of sales techniques through the use of feedback. 【0698】 "Information based on past decisions of sales leaders" refers to data and information related to decisions and choices made by leaders in past sales activities. 【0699】 "Information regarding physical condition" refers to data that quantifies the sales representative's physical condition, such as heart rate, body temperature, and stress level. 【0700】 A "portable device" is a device that a sales representative can wear and that is used to acquire biometric information. 【0701】 "Emotional information" refers to data on the mental state and emotions extracted from the sales representative's facial expressions and tone of voice. 【0702】 "Means for analysis and generating optimal advice for sales activities" refers to the process of using AI algorithms and generative AI models to analyze collected data and generate appropriate instructions and suggestions for sales activities. 【0703】 "Real-time advice" refers to advice and instructions provided to sales representatives immediately on the spot. 【0704】 "Feedback" refers to evaluations and opinions regarding the results of business negotiations and the implementation of advice, and is information used to improve future interactions. 【0705】 This invention provides a system that effectively supports sales representatives in their sales activities by collecting data from multiple sources and analyzing it using an AI algorithm to generate optimal advice. 【0706】 First, the server retrieves information from a database built on the past decisions of sales leaders. This information includes past success stories and customer service strategies. A database management system is used to securely and efficiently access and retrieve the data. 【0707】 Next, the terminal collects biometric information in real time from a wearable device worn by the sales representative. This device has the function of measuring physical conditions such as heart rate and body temperature, and transmits the information to the terminal via Bluetooth or Wi-Fi. In addition, information about emotions is obtained by analyzing the sales representative's facial expressions and voice using the camera and microphone built into the terminal. 【0708】 The server integrates this information and performs analysis using a generative AI model. Specifically, the AI ​​algorithm creates optimal advice based on biometric data, emotional data, and information derived from past decisions, tailored to the sales situation. This advice is adapted to the salesperson's mental state and the customer's response. 【0709】 Advice is immediately communicated to sales representatives via their devices. Visual displays and audio output are used to provide effective feedback to sales representatives. After a sales meeting, users input feedback on the meeting results into their devices, and this information is sent back to the server. The server analyzes this feedback and uses it to train its generative AI model, thereby improving the accuracy of advice for future sales meetings. 【0710】 For example, when inputting prompt messages into an AI model, you can instruct it to "consider the sales coach's past data, current biometric information, and emotional data, and provide the most effective sales strategy." This allows the system to provide specific, situation-specific advice in real time. 【0711】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0712】 Step 1: 【0713】 The server retrieves information from a database based on the past decisions of sales managers. The input is the decision information stored in the database, and the output is the result of extracting this information. SQL queries are used to retrieve the necessary datasets from the database and prepare the data in memory for the next analysis. 【0714】 Step 2: 【0715】 The terminal receives biometric information from wearable devices worn by sales representatives. Input is biometric data such as heart rate and body temperature generated by the wearable device, while output is organized biometric data stored on the terminal. Data is received in real time using Bluetooth or Wi-Fi connections and stored in a local database. 【0716】 Step 3: 【0717】 The device uses its built-in camera and microphone to collect information about the sales representative's emotions. Inputs are camera footage and audio signals, while output is analyzed emotion data. Image processing and audio analysis algorithms are applied to determine emotions from facial expressions and voice tone, quantifying them and storing them in a database. 【0718】 Step 4: 【0719】 The server integrates acquired judgment information, biometric information, and emotional information, and begins analysis using a generative AI model. The input is all the integrated data, and the output is optimal advice for the sales representative. The AI ​​algorithm analyzes this data and generates actionable guidelines best suited to the sales scenario. 【0720】 Step 5: 【0721】 The terminal notifies sales representatives of advice received from the server. Input is advice data sent from the server, and output is visual or audio notification. The terminal displays text on its screen or uses an audio output device to convey the advice. 【0722】 Step 6: 【0723】 After a sales meeting, the user enters feedback into the terminal. The input consists of the results and opinions of the meeting based on the advice given by the sales representative, and the output is information sent to the server as feedback data. The terminal provides a feedback input interface and sends the entered information to the server. 【0724】 Step 7: 【0725】 The server analyzes the collected feedback data and updates the learning model to reflect the changes in future advice generation. The input is the feedback data received from the user, and the output is the updated AI model. Data analysis and machine learning techniques are used to improve the model's accuracy and prepare for the next business negotiation. 【0726】 (Application Example 2) 【0727】 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". 【0728】 Conventional sales support systems are often limited to sales situations, making it difficult to capture users' emotions and biometric information in real time in various aspects of their daily lives and provide appropriate advice. Furthermore, these systems struggle with natural human interaction, requiring flexible responses in home life support. Therefore, there is a need for a system that can provide appropriate advice in various aspects of daily life based on users' emotions and biometric information. 【0729】 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. 【0730】 In this invention, the server includes means for accumulating past decision data of sales instructors, means for receiving data from a portable device for acquiring biometric information, and means for analyzing the decision data, biometric information, and emotional information in combination to generate advice related to daily life situations. This makes it possible to capture the user's emotions and biological state in real time and automatically provide selective advice related to daily life situations. 【0731】 "Past decision data of sales instructors" refers to accumulated data recording the decisions and actions that sales instructors have taken to date, including successful sales methods and customer service strategies. 【0732】 "Biometric information" refers to information that indicates the user's physical condition, and includes data such as physiological indicators like heart rate, skin temperature, and respiratory rate. 【0733】 "Portable devices" refer to devices that can be worn by users and are easy to carry, and include devices such as wearable devices and smartphones. 【0734】 "Emotional information" refers to information that indicates the user's emotional state, and is data on emotional responses obtained through facial expression analysis and vocal information. 【0735】 A "means for generating advice" refers to a system that analyzes accumulated data and real-time received information to create specific action plans and recommendations for users. 【0736】 "Means of notification via robot" refers to notification methods using robots to deliver generated advice to users through functions such as voice or display. 【0737】 "Feedback" refers to information in which users provide evaluations and opinions on the advice they receive, and this information is used to improve the system in the future. 【0738】 In the system for implementing this invention, the server stores past decision data of sales instructors and extracts necessary information from the stored database. This includes successful sales methods and customer service strategies, which are used for data analysis. In addition, the terminal acquires the user's biometric information through a portable device (e.g., a wearable device). This is combined with software equipped with an emotion engine, which has the function of analyzing emotional information from facial expressions and voice. 【0739】 The server comprehensively analyzes this biometric and emotional information and uses a generative AI model to generate appropriate advice for various life situations. This advice takes into account the user's current emotions and physical state in real time and is communicated to the user via the robot. This communication is provided through voice feedback and visual displays to support the user's actions. 【0740】 For example, if the robot determines that the user is feeling stressed, it might offer specific advice such as, "Why not try listening to your favorite music to relax?" An example of a prompt might be, "Based on the user's current emotions and biometric information, please advise on ways to relax." 【0741】 Furthermore, by allowing users to input feedback after business negotiations and on a daily basis into their devices, this data is further analyzed on the server and used to improve the accuracy of advice generation in the future. In this way, a support system that improves the quality of life is realized. 【0742】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0743】 Step 1: 【0744】 By having the user wear a portable device, the terminal receives biometric information from the wearable device. Data such as heart rate, skin temperature, and respiratory rate are acquired as input and temporarily stored within the terminal. 【0745】 Step 2: 【0746】 The device uses an emotion engine to analyze emotional information from the user's facial expressions and voice. The input is real-time facial and voice data from the user, and the output is data on emotional state and stress levels. This allows for real-time monitoring of the user's mental state. 【0747】 Step 3: 【0748】 The server receives biometric and emotional information acquired from the terminal. Based on the input data, it compares it with a database of past judgments and generates appropriate advice using a generative AI model. The output is specific advice tailored to the user's situation. 【0749】 Step 4: 【0750】 The server sends generated advice to the terminal, which then notifies the user via a robot. Notifications are delivered via voice or display. The input is the generated advice, and the output is the specific action plan presented to the user. 【0751】 Step 5: 【0752】 After a business meeting or during daily life, users input feedback into their device. This input consists of evaluations and opinions on the advice, and the server receives this data to update it for future advice generation. The feedback data is used as training material for the AI ​​model, leading to the generation of more accurate advice. 【0753】 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. 【0754】 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. 【0755】 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. 【0756】 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. 【0757】 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. 【0758】 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. 【0759】 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. 【0760】 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. 【0761】 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." 【0762】 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. 【0763】 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. 【0764】 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. 【0765】 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. 【0766】 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. 【0767】 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. 【0768】 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. 【0769】 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. 【0770】 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. 【0771】 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. 【0772】 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. 【0773】 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 as being incorporated by reference. 【0774】 The following is further disclosed regarding the embodiments described above. 【0775】 (Claim 1) 【0776】 A means of accumulating past decision data of sales leaders, 【0777】 A means for receiving data from a portable device for acquiring biometric information, 【0778】 A means for combining and analyzing the aforementioned judgment data and biometric information to generate advice regarding business conditions, 【0779】 Means for notifying the aforementioned advice, 【0780】 A system that includes this. 【0781】 (Claim 2) 【0782】 The system according to claim 1, further comprising means for monitoring the biometric information of a sales representative during a business negotiation and adjusting the advice in real time based on changes therein. 【0783】 (Claim 3) 【0784】 The system according to claim 1, comprising a learning means for collecting feedback based on the results of implementing advice and utilizing it for generating advice in the future. 【0785】 "Example 1" 【0786】 (Claim 1) 【0787】 A means for an information processing device to store past decision data, 【0788】 A means for receiving biological data from an information acquisition device, 【0789】 A means for integrating and analyzing the aforementioned judgment data and biometric data to generate operational guidelines regarding business conditions, 【0790】 Means for notifying the aforementioned operating guidelines through a communication device, 【0791】 An information processing device uses an AI model to perform situational analysis based on success stories and biometric data of sales instructors, 【0792】 A system that includes this. 【0793】 (Claim 2) 【0794】 The system according to claim 1, further comprising means for observing the biometric data of the person in charge during a business negotiation and adjusting the operational guidelines in real time based on changes therein. 【0795】 (Claim 3) 【0796】 The system according to claim 1, comprising a learning means for collecting user feedback based on the results of executing the action guidelines and utilizing it for generating future action guidelines. 【0797】 "Application Example 1" 【0798】 (Claim 1) 【0799】 A means of accumulating past decision-making information of sales leaders, 【0800】 A means for receiving information from a portable device for acquiring physical information, 【0801】 A means for combining and analyzing the aforementioned judgment information and physical information to generate advice regarding business conditions, 【0802】 Means for notifying the aforementioned advice, 【0803】 A means of supporting sales activities by operating robots, 【0804】 A system that includes this. 【0805】 (Claim 2) 【0806】 The system according to claim 1, further comprising means for monitoring the physical information of a sales representative during a business negotiation and adjusting the advice in real time based on changes therein, and means for providing the advice to the sales representative via voice and display. 【0807】 (Claim 3) 【0808】 The system according to claim 1, comprising a learning means for collecting feedback based on the results of implementing advice and utilizing it for generating advice in the future. 【0809】 "Example 2 of combining an emotion engine" 【0810】 (Claim 1) 【0811】 A means of accumulating information based on the past judgments of sales leaders, 【0812】 A means of receiving information from a portable device for collecting information about the physical condition, 【0813】 A means for generating optimal advice for sales activities by combining and analyzing information based on the aforementioned judgment, information on physical condition, and information on emotions, 【0814】 Means for visually or audibly notifying the aforementioned advice, 【0815】 A system that includes this. 【0816】 (Claim 2) 【0817】 The system according to claim 1, further comprising means for monitoring information regarding the physical condition of a sales representative during a business negotiation and adjusting the advice in real time in response to changes therein. 【0818】 (Claim 3) 【0819】 The system according to claim 1, comprising means having a learning function for collecting opinions based on the results of providing advice and utilizing them for generating advice in the future. 【0820】 "Application example 2 when combining with an emotional engine" 【0821】 (Claim 1) 【0822】 A means of accumulating past decision data of sales leaders, 【0823】 A means for receiving data from a portable device for acquiring biometric information, 【0824】 A means for analyzing the aforementioned judgment data, biometric information, and emotional information to generate advice regarding living situations, 【0825】 Means for notifying the aforementioned advice via a robot, 【0826】 A system that includes this. 【0827】 (Claim 2) 【0828】 The system according to claim 1, further comprising means for monitoring the user's biometric and emotional information and adjusting the advice in real time based on changes therein. 【0829】 (Claim 3) 【0830】 The system according to claim 1, comprising a learning means for collecting feedback based on the results of implementing advice and utilizing it for generating advice in the future. [Explanation of symbols] 【0831】 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

[Claim 1] A means of accumulating past decision data of sales leaders, A means for receiving data from a portable device for acquiring biometric information, A means for combining and analyzing the aforementioned judgment data and biometric information to generate advice regarding business conditions, Means for notifying the aforementioned advice, A system that includes this. [Claim 2] The system according to claim 1, further comprising means for monitoring the biometric information of a sales representative during a business negotiation and adjusting the advice in real time based on changes therein. [Claim 3] The system according to claim 1, further comprising a learning means for collecting feedback based on the results of implementing advice and utilizing it for generating advice in the future.

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