system

Abstract

We provide the system. [Solution] An information processing device for users to input business data, A data server checks the integrity of the input data and stores it, An analytical means that analyzes real-time data during customer service and generates feedback, A generation means for generating educational modules optimized for individual users, An optimization method that automatically assigns work schedules based on business demand, An analytical tool that provides insights by analyzing customer interaction data, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including 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 in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Unexamined Patent Application Publication No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 The management of a large number of personnel engaged in sales operations has become complicated and inefficient because unified business data and efficient resource allocation are not carried out. In addition, the lack of specific feedback for improving the quality of customer service and an educational program suitable for individuals is also cited as a problem. Furthermore, it is difficult to create an appropriate work schedule considering customer demand and staff capabilities, and there is also a lack of specific strategic planning based on analysis of customer insights. 【Means for Solving the Problems】 【0005】 This invention achieves centralized information by using a data server that checks the consistency of user-entered business data and efficiently stores it. It also includes an analysis mechanism that analyzes real-time data during customer service and provides feedback, thereby improving crew capabilities by generating optimal training modules for individual users. Furthermore, it implements a mechanism that automatically optimizes dynamic work schedules based on business demands, and by acquiring and analyzing customer insights, it provides a foundation for concretizing future business strategies. These mechanisms enable increased efficiency in sales operations and improved crew performance. 【0006】 "User" refers to a person engaged in business operations who inputs business data or receives feedback through an information processing device. 【0007】 An "information processing device" refers to a terminal used by users to input business data and receive feedback. 【0008】 A "data server" refers to a centrally managed computer device that has the function of checking the integrity of data sent by users and storing it. 【0009】 "Analysis method" refers to a system that evaluates user behavior and generates feedback based on real-time data from customer service interactions. 【0010】 "Generation method" refers to a system that automatically creates educational modules while taking user performance into consideration. 【0011】 "Optimization method" refers to a system that dynamically determines a user's work schedule based on work-related information. 【0012】 "Analysis tools" refer to components that have the function of analyzing customer interaction data and extracting useful insights. [Brief explanation of the drawing] 【0013】 [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] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0014】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0017】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0019】 In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applicable to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc. 【0020】 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." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 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. 【0024】 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). 【0025】 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. 【0026】 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. 【0027】 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. 【0028】 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. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 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. 【0031】 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. 【0032】 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. 【0033】 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". 【0034】 The system of this invention provides comprehensive management and support functions to enable users engaged in sales operations to perform their duties efficiently. This system mainly consists of three elements: a server, a terminal, and a user, and each element works in cooperation with the others. 【0035】 Users input their daily work data into a terminal. The terminal checks the format of the input data and sends it to the server. The server checks the integrity of the received data and stores it securely. The stored data includes a wide range of information, such as crew sales information, customer service performance, and shift information. 【0036】 During customer service activities, the user's device collects voice and location data. The server uses this data to perform real-time analysis, and an AI model evaluates the user's customer service attitude and the customer's emotions. The evaluation results are immediately sent to the user's device as feedback, and areas for improvement are notified. 【0037】 The server also analyzes accumulated user performance data and automatically generates individually optimized educational programs. The generated programs are delivered to the user's device, and the course schedule and other information are presented. 【0038】 Shift optimization based on business demand is also performed on the server. The server dynamically calculates work schedules, taking into account customer demand at each store and the capabilities of the users. These calculation results are sent to the users' terminals to ensure smooth workflow. 【0039】 Furthermore, extracting customer insights is also a crucial element. The server uses accumulated customer data to analyze new insights and suggest service improvements. Based on this, it provides users with concrete strategic proposals and notifies them of feasible improvement measures. 【0040】 As a concrete example, for users who provide highly-rated customer service during peak hours at a retail store, a training program is generated that allows them to reflect on their behavioral characteristics. The program is presented as a set of skills applicable to similar situations, helping to promote further growth for the user. 【0041】 Through this series of processes, the present invention enables the efficient management and training of personnel engaged in sales operations, contributing to improved operational productivity and enhanced customer satisfaction. 【0042】 The following describes the processing flow. 【0043】 Step 1: 【0044】 The user enters sales data and the start and end times of their work into the terminal. The terminal formats the entered data and sends it to the server according to a security protocol. 【0045】 Step 2: 【0046】 The server receives data sent from the terminal and verifies its integrity. If the data is correct, it is saved to the centralized management database. 【0047】 Step 3: 【0048】 When a user interacts with a customer, the device collects voice and motion data in real time. This data is immediately sent to a server for analysis. 【0049】 Step 4: 【0050】 The server analyzes the received audio data and uses an AI model to evaluate customer satisfaction and user service attitude. The evaluation results are generated as feedback. 【0051】 Step 5: 【0052】 The terminal receives feedback from the server and displays it to the user. The user can then consider improvement measures based on the feedback. 【0053】 Step 6: 【0054】 The server analyzes accumulated user performance data and generates educational programs that focus on areas where specific skill improvements are needed. 【0055】 Step 7: 【0056】 The terminal receives educational programs distributed from the server and notifies the user of the course schedule and details. 【0057】 Step 8: 【0058】 The server analyzes customer demand data and crew performance data to dynamically calculate optimized shifts. 【0059】 Step 9: 【0060】 The terminal receives new shift information from the server and displays it to the user. The user then performs their duties based on this shift information. 【0061】 Step 10: 【0062】 The server analyzes customer data and extracts insights and potential trends. Based on this, it creates specific suggestions for service improvement. 【0063】 Step 11: 【0064】 The terminal receives suggestions from the server and notifies the user of the improvement measures. The user can then improve the quality of their customer service by implementing the suggestions. 【0065】 (Example 1) 【0066】 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." 【0067】 In modern sales operations, efficient data management, real-time analytics, personalized training, and dynamic shift adjustments based on demand are crucial. However, the lack of a system that centrally manages and integrates these processes leads to a decline in overall operational efficiency and customer satisfaction. 【0068】 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. 【0069】 In this invention, the server includes a storage means for checking the integrity of input information and storing it, an analysis means for analyzing real-time information acquired during customer service and generating feedback, and an education means for generating education programs tailored to each user. This enables more efficient data management in sales operations, rapid improvement of users' customer service attitudes, and the provision of individually optimized education. 【0070】 A "terminal device" is a device used by a user to input information and has a function to check the integrity of the input data. 【0071】 A "memory device" is a part of a system that has the function of securely storing input information and keeping it in a state that can be accessed as needed. 【0072】 The "analysis means" refers to a function that analyzes information acquired in real time and executes a process to provide feedback to the user. 【0073】 The "educational tool" has the function of automatically generating and providing individually optimized educational programs based on the user's performance data. 【0074】 "Adjustment mechanisms" are functions that dynamically allocate work time based on the demands of the business, thereby supporting efficient business operations. 【0075】 "Analytical tools" are those that analyze information based on customer interactions, provide new insights, and propose concrete strategies. 【0076】 This system is designed to enable users engaged in sales operations to perform their duties efficiently. Its main components include a server, terminals, and users, and each element works in conjunction with the others. 【0077】 Users begin by entering daily work information using a terminal. The terminal checks the integrity of the information entered by the user and sends it to the server if the format is correct. This terminal device is involved in input via touchscreen or keyboard, and data buffering. 【0078】 The server receives information transmitted from the terminal and stores it in a database using secure storage methods. This data includes sales information and customer service history. Furthermore, the server analyzes real-time information acquired during customer service and generates feedback based on a generated AI model. This analysis step utilizes speech recognition software and location services. 【0079】 While a user is interacting with an employee, the device automatically collects voice and location data and sends it to a server. The server's analysis system evaluates the user's behavior based on this data and provides real-time feedback. This feedback is intended to encourage improvements in customer service practices. 【0080】 Furthermore, the server utilizes educational tools to generate personalized training programs based on past performance data. These programs are delivered to the user's device and presented along with the training schedule. For example, if a salesperson receives high ratings for customer service during peak hours, a training program is created based on their specific behavioral characteristics. 【0081】 The system also optimizes shifts based on business demand, specifically by adjusting work hours based on trends in customer numbers and staff skill set data. 【0082】 The system also includes analytical tools that analyze customer interaction data to provide new insights. Based on this, the server generates strategic recommendations and notifies the user. 【0083】 An example of a prompt message is: "Analyze recent customer service data from peak hours, extract the specific skills of staff members who provided particularly high customer satisfaction, and create a training program based on that that can be applied to other staff members." 【0084】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0085】 Step 1: 【0086】 Users input work-related information using a terminal. Specifically, they input sales data, customer service history, shift information, etc., and store the data correctly according to the format. The entered data is temporarily stored on the terminal. 【0087】 Step 2: 【0088】 The terminal performs an integrity check on the input data. It verifies that the data format and required fields are entered correctly. Once the check is complete, it prepares to send the data to the server. If there are no integrity issues, the terminal is triggered to send the data to the server. 【0089】 Step 3: 【0090】 The server receives the data sent from the terminal and performs another integrity check. After confirming that there is no duplicate data or invalid entries, it stores the data in a secure database. The moment the data integrity is confirmed, the write operation to the database is executed. 【0091】 Step 4: 【0092】 When a user interacts with a customer, the device begins collecting voice and location data. This information is acquired using the built-in microphone and GPS module and transmitted to the server in real time. This step starts automatically each time a user action occurs. 【0093】 Step 5: 【0094】 The server processes the received audio and location data through an AI model to analyze the user's customer service attitude and the customer's emotions. Data processing includes converting audio to text and calculating distance and time to the customer using location information. The analysis results are immediately sent to the user's device as feedback. 【0095】 Step 6: 【0096】 The server analyzes accumulated user performance data and generates personalized training programs. This involves analyzing historical data to identify areas where specific skills or knowledge need strengthening. The training programs are then delivered to the user's device, and the user learns based on them. 【0097】 Step 7: 【0098】 The server optimizes work shifts using customer trend data and user skill profiles. Predictive algorithms are used in the calculations to ensure optimal staffing at all times. The adjustment results are sent to terminals, where users can check the new shift information. 【0099】 Step 8: 【0100】 The server analyzes customer data using advanced analytical algorithms to extract new customer insights and suggestions for service improvements. Based on these results, it generates prompt messages to notify the user, allowing them to use them as a reference for implementing their strategies. 【0101】 (Application Example 1) 【0102】 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." 【0103】 In modern brick-and-mortar retail operations, there is a demand for improved staff customer service skills and increased customer satisfaction. However, there is a lack of systems that effectively provide real-time feedback and personalized training programs, resulting in insufficient efficiency and optimization of operations. Furthermore, because methods for analyzing and immediately evaluating sales staff behavior and conversation data are underdeveloped, staff do not have the opportunity to immediately improve their customer service style. 【0104】 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. 【0105】 In this invention, the server includes means for checking the integrity of input data and storing it, means for analyzing real-time data during customer service and generating feedback, and means for analyzing and evaluating the salesperson's behavior and conversation data in real time and notifying them of areas for improvement. This enables immediate improvement of staff customer service skills in sales operations, leading to increased operational fluidity and customer satisfaction. 【0106】 An "information processing device" is an electronic device used by users to input sales data. 【0107】 A "data server" is a computer system that performs integrity checks and stores data sent by users. 【0108】 "Analysis means" refers to a function that analyzes real-time data collected during customer service and generates feedback. 【0109】 The "generation method" refers to a function that automatically creates training modules optimized for each sales staff member. 【0110】 An "optimization method" is an algorithm that automatically adjusts work schedules according to the demands of the work. 【0111】 "Analysis tools" refer to functions that analyze customer interaction data and provide insights useful for sales strategies. 【0112】 The "evaluation method" is a function that analyzes the seller's behavior and conversation data, evaluates it in real time, and notifies them of areas for improvement. 【0113】 The system for implementing this invention consists of a user, a terminal for sending and receiving data, and a server for processing. The user inputs daily work data using a terminal such as a smartphone or tablet. The terminal checks the integrity of the input data and transmits it to the data server via the internet. The server securely stores the data and operates analysis means as needed. 【0114】 The server's analysis method uses voice and location data to evaluate the user's customer service activities in real time and generates feedback using an AI model. The feedback is immediately delivered to the user's device, allowing the user to see specific areas for improvement. The server also generates individually optimized training modules based on the evaluation results and accumulated data. The generated training modules are delivered to the user's device, and a learning schedule is presented. 【0115】 To ensure operational fluidity, the server has a function to optimize work schedules based on business demand. It dynamically calculates shift assignments, taking into account customer demand data for each store and user capacity data. This result is also delivered to the user's terminal. Furthermore, the server analyzes customer interaction data to extract new insights, which are used to improve sales strategies. 【0116】 As a concrete example, a training program is generated for sales staff who provide highly-rated customer service during peak hours, allowing them to reflect on their actions. This program is presented to users as a set of skills applicable to similar situations, supporting their growth. For instance, prompts such as, "What feedback did you receive from your recent customer service experience? What actions will you take to improve?" are used. This leads to immediate improvement in customer service skills and increased customer satisfaction. 【0117】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0118】 Step 1: 【0119】 The user enters business data into a terminal. The terminal checks the integrity of the entered business data and sends it to the server. The entered data includes customer information, sales performance, customer service details, etc. Data whose integrity has been confirmed is used as the basis for the next processing step. 【0120】 Step 2: 【0121】 The server securely stores the received data and activates the analysis tools. The stored data includes sales data, customer service details, and customer feedback. The server uses the stored data to run an AI model and prepares to evaluate the user's customer service activities. 【0122】 Step 3: 【0123】 The server receives voice and location data transmitted from the terminal and performs real-time analysis. Voice data is converted to text using speech recognition software and analyzed by an AI model. Location data is used to calculate user movement patterns and dwell time. This results in output that evaluates the user's customer service style and customer reactions. 【0124】 Step 4: 【0125】 The server generates feedback on the user's customer service activities based on the analysis results from the AI ​​model. The feedback includes areas for improvement and points of good behavior, along with specific methods for improvement. The generated feedback is sent to the user's device as a push notification. 【0126】 Step 5: 【0127】 The server adds the user's evaluation results to the stored data and activates the means for generating educational programs. The server analyzes the evaluation data and assembles educational modules optimized for each individual user. This educational program is sent to the user's terminal, and the schedule is displayed. 【0128】 Step 6: 【0129】 The server uses optimization techniques to calculate a dynamic work schedule based on business demand. Flexible shift assignments are created based on business-related information and user capability data. The optimized shift information is then sent to the user's terminal. 【0130】 Step 7: 【0131】 The server activates analytical tools to extract new customer insights based on accumulated customer interaction data. It analyzes customer conversations and purchase history to generate information that can lead to improvements in sales strategies. The analysis results are provided to the user as strategic recommendations and notifications. 【0132】 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. 【0133】 The present invention provides an integrated platform for improving users' work efficiency and interpersonal skills in sales operations. This system includes an information processing device for user input of work data, a data server for data integrity checks and storage, an analysis means for analyzing real-time data during customer service, a generation means for generating optimized training modules, an optimization means for automatically assigning work schedules based on business needs, and an analysis means for analyzing customer interaction data. Furthermore, by incorporating an emotion engine that recognizes user emotions, it becomes possible to understand the user's emotional state and provide more accurate feedback and training content. 【0134】 Users input sales and shift information into a terminal at the start and end of their workday. This terminal sends the input data to a server. The server checks the received data and stores it in a database. This data is used as basic information for analyzing the user's work performance. 【0135】 During customer service, the user's device collects voice and motion data. The emotion engine analyzes this data to recognize the user's emotions in real time. The emotion recognition results are sent to a server and used as reference information to generate feedback. Based on the user's emotions, the analysis system determines appropriate feedback and notifies the user through the device. 【0136】 The generation method creates personalized educational modules based on the user's past performance data and emotion recognition results. These modules are tailored to the user's characteristics and challenges and are delivered via the device. This allows users to receive education suited to their emotional state, leading to expected skill improvement. 【0137】 Furthermore, the optimization mechanism dynamically assigns work schedules based on information obtained from multiple data sources. This optimizes each user's work style and enables efficient resource allocation. 【0138】 For example, if the emotion engine detects that a user is experiencing stress during customer interactions, the analysis means generates feedback that takes that emotion into account and provides an educational module on stress management. In this way, the system of the present invention helps to improve the user's work efficiency and satisfaction by utilizing emotion recognition. 【0139】 The following describes the processing flow. 【0140】 Step 1: 【0141】 At the start of their workday, users use a terminal to enter their login information and begin inputting work data. The terminal formats this data and sends it to the server in real time. 【0142】 Step 2: 【0143】 The server receives business data sent from terminals and automatically checks its integrity. If the data is correct, it is saved to a database and managed as a daily work record. 【0144】 Step 3: 【0145】 When a user begins interacting with a customer, the device collects voice and gesture data in real time and sends it to the server. 【0146】 Step 4: 【0147】 The server uses an emotion engine to analyze the user's emotional state in real time from received voice and behavioral data. Based on the analysis results, it identifies the user's psychological state. 【0148】 Step 5: 【0149】 The analysis tool uses data provided by the emotion engine to generate feedback. This feedback, tailored to the user's emotional state, is delivered to the user via the device. 【0150】 Step 6: 【0151】 Users will be able to immediately work on improving their customer service methods based on the feedback they receive from their devices. 【0152】 Step 7: 【0153】 The server integrates and analyzes historical performance data and sentiment recognition results to generate user-optimized educational modules. These generated modules are then delivered to the user via their terminal. 【0154】 Step 8: 【0155】 The terminal manages information from the educational modules provided to the user and helps prepare them for application to subsequent tasks. 【0156】 Step 9: 【0157】 The server dynamically optimizes users' work schedules by utilizing information from multiple data sources. This optimization helps to facilitate smooth staffing in business operations. 【0158】 Step 10: 【0159】 The terminal receives optimized shift information sent from the server and displays it visually to the user. This allows the user to understand the new shift and perform their work efficiently. 【0160】 (Example 2) 【0161】 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." 【0162】 In sales operations, a system is needed that comprehensively utilizes diverse data to provide real-time feedback and personalized training in order to support the improvement of users' work efficiency and interpersonal skills. However, current systems are insufficient in recognizing users' emotional states and dynamically adjusting work schedules based on work data, limiting the optimization of the entire operation. This leads to increased burden on users and difficulties in improving customer satisfaction. 【0163】 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. 【0164】 In this invention, the server includes an information processing device for users to input work data, a data storage device for checking the integrity of the input data and storing it, and an analysis device for analyzing dynamic data during face-to-face customer service and generating responses. This makes it possible to recognize the user's emotional state in real time and provide a dynamically optimized work schedule. As a result, users can receive feedback and training based on their emotional state, which is expected to improve work efficiency and skills. 【0165】 An "information processing device" is a device used by users to input data related to their work. 【0166】 A "data storage device" is a system for verifying the integrity of received data and storing it. 【0167】 An "analysis device" is a device that analyzes real-time dynamic data obtained during customer service and generates feedback and responses. 【0168】 A "generation device" is a means of creating personalized educational programs for users. 【0169】 An "optimization device" is a means of automatically optimizing and allocating users' work time based on business needs. 【0170】 An "analytical device" is a means of analyzing customer and user interaction data to provide insights. 【0171】 An "emotion recognition device" is a means of recognizing a user's emotional state and providing appropriate feedback based on that information. 【0172】 This invention provides an integrated platform for improving the work efficiency and interpersonal skills of users in sales operations. This system mainly includes information processing devices, data storage servers, real-time analysis devices, generation devices, optimization functions, and emotion recognition functions. 【0173】 Information processing device 【0174】 The terminal is used by users to input work data at the start and end of their workday. Specifically, sales information and shift information are recorded on the terminal using the keyboard or touch input and treated as entry data. 【0175】 Data storage device 【0176】 The server checks the integrity of the data and stores it in the database using a secure communication protocol. The stored data serves as basic information for evaluating the user's work performance. 【0177】 Real-time analysis device and emotion recognition 【0178】 During customer service, the terminal collects voice and motion data. The emotion recognition device analyzes this data to identify the user's emotional state in real time. Based on the recognition results, the server generates appropriate feedback and notifies the user. 【0179】 Provision of educational programs using generation equipment 【0180】 The server generates personalized training programs based on the user's past work data and current emotional state. This allows users to receive training optimized for them, leading to improved skills. 【0181】 Optimization function 【0182】 The server analyzes data obtained from various sources and optimizes the user's work schedule. This enables efficient allocation of work time and reduces the user's burden. 【0183】 For example, if a user exhibits high stress levels during customer service, the emotion recognition device detects this and generates feedback on relaxation techniques. Furthermore, a personalized stress management education program is provided on the device. This gives users the opportunity to quickly improve their stress management skills. By inputting a prompt sentence such as, "What relaxation techniques should be recommended if the user exhibits high stress levels?" into the AI ​​model, the optimal feedback content is created. 【0184】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0185】 Step 1: 【0186】 Users input sales and shift information using a terminal at the start of their workday. The entered data is sent to the database server by the terminal. The input here consists of numerical and text data, which the terminal sends to the server using HTTP communication. 【0187】 Step 2: 【0188】 The server checks the integrity of the received data. This integrity check verifies that sales information is numerical and that shift information is in the correct format. The server then saves the verified data to the database. This saving operation makes the data available for future analysis and reporting. 【0189】 Step 3: 【0190】 While the user is interacting with customers, the terminal collects voice and motion data. The terminal transmits this data to an emotion recognition device in real time. The input here is audio files and video frames, which the emotion recognition device analyzes to identify the user's emotional state. The identified emotion data is sent to a server to serve as the basis for generating feedback. 【0191】 Step 4: 【0192】 The server generates feedback based on the emotion recognition results. It inputs prompts into a generation AI model to construct appropriate feedback. The generated feedback is sent to the terminal and notified to the user. This feedback output can be a text message or voice instruction. 【0193】 Step 5: 【0194】 The server generates a personalized training program based on past work data and current emotional state. This program includes training content tailored to the user's characteristics. The generated program is delivered on the terminal to support the user's skill improvement. The program's output is displayed in the form of video tutorials and online learning materials. 【0195】 Step 6: 【0196】 The server executes an algorithm to optimize work schedules based on data collected from various sources. Using past work history and data on business demand, it dynamically adjusts user shifts to achieve efficient work allocation. The optimized schedule is displayed on the terminal, allowing users to check their schedules. 【0197】 (Application Example 2) 【0198】 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". 【0199】 Smooth communication with customers during on-site service delivery, and improving staff work efficiency and interpersonal skills, are crucial challenges in brick-and-mortar store management. Furthermore, it is essential for on-site staff to recognize their own emotional states and respond appropriately, thereby improving their skills, in order to enhance customer satisfaction. However, conventional systems have struggled to provide real-time emotional recognition, appropriate feedback, and training modules, making it difficult to efficiently address these challenges. 【0200】 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. 【0201】 In this invention, the server includes a data processing device for users to input work information, a data management device for checking the integrity of the input information and storing it, an analysis device for analyzing real-time information during service provision and generating feedback, and an educational support device for providing personalized training modules based on emotional states. This allows staff to grasp their own and the customer's emotional states in real time during interactions with customers, enabling appropriate and timely responses and skill development. Furthermore, by providing efficient work allocation, it is possible to improve the overall productivity of operations. 【0202】 A "data processing device" is a device that takes user input of work information and converts it into a format usable within the system. 【0203】 A "data management device" is a device used to verify the integrity of input data and to store it appropriately. 【0204】 An "analysis device" is a device that analyzes real-time data collected during service provision and generates appropriate feedback. 【0205】 A "configuration device" is a device that has the function of creating learning modules optimized for individual users. 【0206】 An "optimization scheduling device" is a device that automatically determines an efficient work schedule based on collected work-related information. 【0207】 An "analytical device" is a device that analyzes customer interaction data and provides useful insights. 【0208】 An "emotion recognition device" is a device that has the function of identifying the emotional state of users and customers in real time. 【0209】 An "educational support device" is a device that provides individualized training modules tailored to the user's emotional state. 【0210】 The system implementing this invention is an integrated platform including a data processing device, a data management device, an analysis device, a configuration device, an optimization placement device, an analysis device, an emotion recognition device, and an educational support device. The system is realized through the cooperation of the user's smart glasses or smartphone with a server. 【0211】 The server receives business information entered by the user, checks its integrity using a data processing device, and then stores it in storage. This data is fundamental information for analyzing the user's work efficiency. During real-time work, the user's terminal collects conversation and behavioral data with customers and sends it to the server. The server's analysis device uses this data to recognize customer emotions and generate appropriate feedback for the user. 【0212】 Furthermore, the emotion recognition device evaluates the user's emotional state in real time, and the analysis device provides insights based on that information. This allows the server to provide feedback tailored to each user's individual state. In addition, the system analyzes the user's past performance data and current emotional state to generate a customized learning module. This module is displayed on the user's smart glasses or smartphone to support individual skill improvement. 【0213】 The optimization placement device acquires business-related information from multiple data sources and efficiently adjusts work schedules. Furthermore, by analyzing this data and considering the emotional state of users, it is possible to improve the quality of work. 【0214】 As a concrete example, a florist wearing smart glasses can monitor their own and the customer's emotional state in real time during interactions, enabling them to provide more appropriate service. An example of a prompt to the generated AI model is, "Analyze the customer's facial expressions and vocal characteristics when they choose flowers, and determine their emotional state." This system allows users to improve work efficiency and customer satisfaction. 【0215】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0216】 Step 1: 【0217】 Users input work information into a terminal. Users use smart glasses or smartphones to input sales and shift information at the start of their workday. This data is sent to the server as input data and processed as initial data. 【0218】 Step 2: 【0219】 The server checks the integrity of the input data and stores it through the data management device. After receiving business information, the server performs an integrity check and stores the data in a database. This becomes the foundational data used for later analysis. 【0220】 Step 3: 【0221】 The device collects customer interaction data in real time. Using the device's camera and microphone, it records the customer's facial expressions and voice in real time. This serves as the input for customer data. 【0222】 Step 4: 【0223】 The server uses an analysis device to analyze the collected data and perform emotion recognition. The server inputs the customer's facial expressions and voice characteristics into emotion recognition software to determine their emotional state. This is the output of the information analysis. 【0224】 Step 5: 【0225】 The server generates feedback based on the analysis results and sends it to the terminal. The server generates appropriate feedback from the output of the analysis device and sends it to the user's terminal. This allows the user to optimize the interaction in real time. 【0226】 Step 6: 【0227】 The server generates customized learning modules using educational support devices. Based on historical work data and real-time sentiment data, the server creates an individualized training plan and sends it to the user's terminal. 【0228】 Step 7: 【0229】 The server dynamically allocates work schedules using an optimization placement device. The server references multiple data sources and considers work demands and emotional states to efficiently optimize user work time. 【0230】 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. 【0231】 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. 【0232】 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. 【0233】 [Second Embodiment] 【0234】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0235】 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. 【0236】 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). 【0237】 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. 【0238】 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. 【0239】 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). 【0240】 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. 【0241】 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. 【0242】 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. 【0243】 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. 【0244】 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. 【0245】 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". 【0246】 The system of this invention provides comprehensive management and support functions to enable users engaged in sales operations to perform their duties efficiently. This system mainly consists of three elements: a server, a terminal, and a user, and each element works in cooperation with the others. 【0247】 Users input their daily work data into a terminal. The terminal checks the format of the input data and sends it to the server. The server checks the integrity of the received data and stores it securely. The stored data includes a wide range of information, such as crew sales information, customer service performance, and shift information. 【0248】 During customer service activities, the user's device collects voice and location data. The server uses this data to perform real-time analysis, and an AI model evaluates the user's customer service attitude and the customer's emotions. The evaluation results are immediately sent to the user's device as feedback, and areas for improvement are notified. 【0249】 The server also analyzes accumulated user performance data and automatically generates individually optimized educational programs. The generated programs are delivered to the user's device, and the course schedule and other information are presented. 【0250】 Shift optimization based on business demand is also performed on the server. The server dynamically calculates work schedules, taking into account customer demand at each store and the capabilities of the users. These calculation results are sent to the users' terminals to ensure smooth workflow. 【0251】 Furthermore, extracting customer insights is also a crucial element. The server uses accumulated customer data to analyze new insights and suggest service improvements. Based on this, it provides users with concrete strategic proposals and notifies them of feasible improvement measures. 【0252】 As a concrete example, for users who provide highly-rated customer service during peak hours at a retail store, a training program is generated that allows them to reflect on their behavioral characteristics. The program is presented as a set of skills applicable to similar situations, helping to promote further growth for the user. 【0253】 Through this series of processes, the present invention enables the efficient management and training of personnel engaged in sales operations, contributing to improved operational productivity and enhanced customer satisfaction. 【0254】 The following describes the processing flow. 【0255】 Step 1: 【0256】 The user enters sales data and the start and end times of their work into the terminal. The terminal formats the entered data and sends it to the server according to a security protocol. 【0257】 Step 2: 【0258】 The server receives data sent from the terminal and verifies its integrity. If the data is correct, it is saved to the centralized management database. 【0259】 Step 3: 【0260】 When a user interacts with a customer, the device collects voice and motion data in real time. This data is immediately sent to a server for analysis. 【0261】 Step 4: 【0262】 The server analyzes the received audio data and uses an AI model to evaluate customer satisfaction and user service attitude. The evaluation results are generated as feedback. 【0263】 Step 5: 【0264】 The terminal receives feedback from the server and displays it to the user. The user can then consider improvement measures based on the feedback. 【0265】 Step 6: 【0266】 The server analyzes accumulated user performance data and generates educational programs that focus on areas where specific skill improvements are needed. 【0267】 Step 7: 【0268】 The terminal receives educational programs distributed from the server and notifies the user of the course schedule and details. 【0269】 Step 8: 【0270】 The server analyzes customer demand data and crew performance data to dynamically calculate optimized shifts. 【0271】 Step 9: 【0272】 The terminal receives new shift information from the server and displays it to the user. The user then performs their duties based on this shift information. 【0273】 Step 10: 【0274】 The server analyzes customer data and extracts insights and potential trends. Based on this, it creates specific suggestions for service improvement. 【0275】 Step 11: 【0276】 The terminal receives suggestions from the server and notifies the user of the improvement measures. The user can then improve the quality of their customer service by implementing the suggestions. 【0277】 (Example 1) 【0278】 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." 【0279】 In modern sales operations, efficient data management, real-time analytics, personalized training, and dynamic shift adjustments based on demand are crucial. However, the lack of a system that centrally manages and integrates these processes leads to a decline in overall operational efficiency and customer satisfaction. 【0280】 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. 【0281】 In this invention, the server includes a storage means for checking the integrity of the input information and storing it, an analysis means for analyzing the real-time information obtained during customer service and generating feedback, and an education means for generating an education program specialized for each user. As a result, it becomes possible to improve the efficiency of data management in sales operations, quickly improve the customer service attitude of users, and provide individually optimized education. 【0282】 The "terminal device" is a device used by a user to input information and has a function for checking the integrity of the input data. 【0283】 The "storage means" is a part of a system that has a function for safely storing the input information and storing it in an accessible state as needed. 【0284】 The "analysis means" has a function for analyzing the information obtained in real time and executing a process for providing feedback to the user. 【0285】 The "education means" has a function for automatically generating and providing an individually optimized education program based on the performance data of the user. 【0286】 The "adjustment means" has a function for dynamically allocating working hours based on the demand of the business and supporting efficient business operations. 【0287】 The "analysis means" has a function for analyzing information based on communication with customers, providing new insights, and proposing specific strategies. 【0288】 This system is designed so that users engaged in sales operations can efficiently perform their work. The main components include a server, a terminal, and a user, and each component functions in cooperation. 【0289】 Users begin by entering daily work information using a terminal. The terminal checks the integrity of the information entered by the user and sends it to the server if the format is correct. This terminal device is involved in input via touchscreen or keyboard, and data buffering. 【0290】 The server receives information transmitted from the terminal and stores it in a database using secure storage methods. This data includes sales information and customer service history. Furthermore, the server analyzes real-time information acquired during customer service and generates feedback based on a generated AI model. This analysis step utilizes speech recognition software and location services. 【0291】 While a user is interacting with an employee, the device automatically collects voice and location data and sends it to a server. The server's analysis system evaluates the user's behavior based on this data and provides real-time feedback. This feedback is intended to encourage improvements in customer service practices. 【0292】 Furthermore, the server utilizes educational tools to generate personalized training programs based on past performance data. These programs are delivered to the user's device and presented along with the training schedule. For example, if a salesperson receives high ratings for customer service during peak hours, a training program is created based on their specific behavioral characteristics. 【0293】 The system also optimizes shifts based on business demand, specifically by adjusting work hours based on trends in customer numbers and staff skill set data. 【0294】 The system also includes analytical tools that analyze customer interaction data to provide new insights. Based on this, the server generates strategic recommendations and notifies the user. 【0295】 An example of a prompt message is: "Analyze recent customer service data from peak hours, extract the specific skills of staff members who provided particularly high customer satisfaction, and create a training program based on that that can be applied to other staff members." 【0296】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0297】 Step 1: 【0298】 Users input work-related information using a terminal. Specifically, they input sales data, customer service history, shift information, etc., and store the data correctly according to the format. The entered data is temporarily stored on the terminal. 【0299】 Step 2: 【0300】 The terminal performs an integrity check on the input data. It verifies that the data format and required fields are entered correctly. Once the check is complete, it prepares to send the data to the server. If there are no integrity issues, the terminal is triggered to send the data to the server. 【0301】 Step 3: 【0302】 The server receives the data sent from the terminal and performs another integrity check. After confirming that there is no duplicate data or invalid entries, it stores the data in a secure database. The moment the data integrity is confirmed, the write operation to the database is executed. 【0303】 Step 4: 【0304】 When a user interacts with a customer, the device begins collecting voice and location data. This information is acquired using the built-in microphone and GPS module and transmitted to the server in real time. This step starts automatically each time a user action occurs. 【0305】 Step 5: 【0306】 The server applies the received voice and location data to the generative AI model to analyze the user's customer service attitude and the customer's emotions. As data processing, the voice is converted into text, and the distance and time from the customer are calculated using the location information. The analysis results are immediately sent as feedback to the user's terminal. 【0307】 Step 6: 【0308】 The server analyzes the accumulated user performance data and generates an individual education program. For the generation, the past data is analyzed to identify areas where specific skills and knowledge need to be strengthened. The education program is distributed to the user's terminal, and the user learns based on it. 【0309】 Step 7: 【0310】 The server optimizes the business shift using the customer movement data and the user's skill profile. Prediction algorithms are used for the calculation to always achieve the optimal staff allocation. The results of this adjustment are sent to the terminal, and the user checks the new shift information. 【0311】 Step 8: 【0312】 The server analyzes the customer data using advanced analysis algorithms to extract new customer insights and service improvement plans. Based on this result, a prompt sentence is generated and notified to the user for reference in implementing the strategy. 【0313】 (Application Example 1) 【0314】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0315】 In modern brick-and-mortar retail operations, there is a demand for improved staff customer service skills and increased customer satisfaction. However, there is a lack of systems that effectively provide real-time feedback and personalized training programs, resulting in insufficient efficiency and optimization of operations. Furthermore, because methods for analyzing and immediately evaluating sales staff behavior and conversation data are underdeveloped, staff do not have the opportunity to immediately improve their customer service style. 【0316】 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. 【0317】 In this invention, the server includes means for checking the integrity of input data and storing it, means for analyzing real-time data during customer service and generating feedback, and means for analyzing and evaluating the salesperson's behavior and conversation data in real time and notifying them of areas for improvement. This enables immediate improvement of staff customer service skills in sales operations, leading to increased operational fluidity and customer satisfaction. 【0318】 An "information processing device" is an electronic device used by users to input sales data. 【0319】 A "data server" is a computer system that performs integrity checks and stores data sent by users. 【0320】 "Analysis means" refers to a function that analyzes real-time data collected during customer service and generates feedback. 【0321】 The "generation method" refers to a function that automatically creates training modules optimized for each sales staff member. 【0322】 An "optimization method" is an algorithm that automatically adjusts work schedules according to the demands of the work. 【0323】 "Analysis tools" refer to functions that analyze customer interaction data and provide insights useful for sales strategies. 【0324】 The "evaluation method" is a function that analyzes the seller's behavior and conversation data, evaluates it in real time, and notifies them of areas for improvement. 【0325】 The system for implementing this invention consists of a user, a terminal for sending and receiving data, and a server for processing. The user inputs daily work data using a terminal such as a smartphone or tablet. The terminal checks the integrity of the input data and transmits it to the data server via the internet. The server securely stores the data and operates analysis means as needed. 【0326】 The server's analysis method uses voice and location data to evaluate the user's customer service activities in real time and generates feedback using an AI model. The feedback is immediately delivered to the user's device, allowing the user to see specific areas for improvement. The server also generates individually optimized training modules based on the evaluation results and accumulated data. The generated training modules are delivered to the user's device, and a learning schedule is presented. 【0327】 To ensure operational fluidity, the server has a function to optimize work schedules based on business demand. It dynamically calculates shift assignments, taking into account customer demand data for each store and user capacity data. This result is also delivered to the user's terminal. Furthermore, the server analyzes customer interaction data to extract new insights, which are used to improve sales strategies. 【0328】 As a concrete example, a training program is generated for sales staff who provide highly-rated customer service during peak hours, allowing them to reflect on their actions. This program is presented to users as a set of skills applicable to similar situations, supporting their growth. For instance, prompts such as, "What feedback did you receive from your recent customer service experience? What actions will you take to improve?" are used. This leads to immediate improvement in customer service skills and increased customer satisfaction. 【0329】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0330】 Step 1: 【0331】 The user enters business data into a terminal. The terminal checks the integrity of the entered business data and sends it to the server. The entered data includes customer information, sales performance, customer service details, etc. Data whose integrity has been confirmed is used as the basis for the next processing step. 【0332】 Step 2: 【0333】 The server securely stores the received data and activates the analysis tools. The stored data includes sales data, customer service details, and customer feedback. The server uses the stored data to run an AI model and prepares to evaluate the user's customer service activities. 【0334】 Step 3: 【0335】 The server receives voice and location data transmitted from the terminal and performs real-time analysis. Voice data is converted to text using speech recognition software and analyzed by an AI model. Location data is used to calculate user movement patterns and dwell time. This results in output that evaluates the user's customer service style and customer reactions. 【0336】 Step 4: 【0337】 The server generates feedback on the user's customer service activities based on the analysis results from the AI ​​model. The feedback includes areas for improvement and points of good behavior, along with specific methods for improvement. The generated feedback is sent to the user's device as a push notification. 【0338】 Step 5: 【0339】 The server adds the user's evaluation results to the stored data and activates the means for generating educational programs. The server analyzes the evaluation data and assembles educational modules optimized for each individual user. This educational program is sent to the user's terminal, and the schedule is displayed. 【0340】 Step 6: 【0341】 The server uses optimization techniques to calculate a dynamic work schedule based on business demand. Flexible shift assignments are created based on business-related information and user capability data. The optimized shift information is then sent to the user's terminal. 【0342】 Step 7: 【0343】 The server activates analytical tools to extract new customer insights based on accumulated customer interaction data. It analyzes customer conversations and purchase history to generate information that can lead to improvements in sales strategies. The analysis results are provided to the user as strategic recommendations and notifications. 【0344】 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. 【0345】 The present invention provides an integrated platform for improving users' work efficiency and interpersonal skills in sales operations. This system includes an information processing device for user input of work data, a data server for data integrity checks and storage, an analysis means for analyzing real-time data during customer service, a generation means for generating optimized training modules, an optimization means for automatically assigning work schedules based on business needs, and an analysis means for analyzing customer interaction data. Furthermore, by incorporating an emotion engine that recognizes user emotions, it becomes possible to understand the user's emotional state and provide more accurate feedback and training content. 【0346】 Users input sales and shift information into a terminal at the start and end of their workday. This terminal sends the input data to a server. The server checks the received data and stores it in a database. This data is used as basic information for analyzing the user's work performance. 【0347】 During customer service, the user's device collects voice and motion data. The emotion engine analyzes this data to recognize the user's emotions in real time. The emotion recognition results are sent to a server and used as reference information to generate feedback. Based on the user's emotions, the analysis system determines appropriate feedback and notifies the user through the device. 【0348】 The generation method creates personalized educational modules based on the user's past performance data and emotion recognition results. These modules are tailored to the user's characteristics and challenges and are delivered via the device. This allows users to receive education suited to their emotional state, leading to expected skill improvement. 【0349】 Furthermore, the optimization mechanism dynamically assigns work schedules based on information obtained from multiple data sources. This optimizes each user's work style and enables efficient resource allocation. 【0350】 For example, if the emotion engine detects that a user is experiencing stress during customer interactions, the analysis means generates feedback that takes that emotion into account and provides an educational module on stress management. In this way, the system of the present invention helps to improve the user's work efficiency and satisfaction by utilizing emotion recognition. 【0351】 The following describes the processing flow. 【0352】 Step 1: 【0353】 At the start of their workday, users use a terminal to enter their login information and begin inputting work data. The terminal formats this data and sends it to the server in real time. 【0354】 Step 2: 【0355】 The server receives business data sent from terminals and automatically checks its integrity. If the data is correct, it is saved to a database and managed as a daily work record. 【0356】 Step 3: 【0357】 When a user begins interacting with a customer, the device collects voice and gesture data in real time and sends it to the server. 【0358】 Step 4: 【0359】 The server uses an emotion engine to analyze the user's emotional state in real time from received voice and behavioral data. Based on the analysis results, it identifies the user's psychological state. 【0360】 Step 5: 【0361】 The analysis tool uses data provided by the emotion engine to generate feedback. This feedback, tailored to the user's emotional state, is delivered to the user via the device. 【0362】 Step 6: 【0363】 Users will be able to immediately work on improving their customer service methods based on the feedback they receive from their devices. 【0364】 Step 7: 【0365】 The server integrates and analyzes historical performance data and sentiment recognition results to generate user-optimized educational modules. These generated modules are then delivered to the user via their terminal. 【0366】 Step 8: 【0367】 The terminal manages information from the educational modules provided to the user and helps prepare them for application to subsequent tasks. 【0368】 Step 9: 【0369】 The server dynamically optimizes users' work schedules by utilizing information from multiple data sources. This optimization helps to facilitate smooth staffing in business operations. 【0370】 Step 10: 【0371】 The terminal receives optimized shift information sent from the server and displays it visually to the user. This allows the user to understand the new shift and perform their work efficiently. 【0372】 (Example 2) 【0373】 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". 【0374】 In sales operations, a system is needed that comprehensively utilizes diverse data to provide real-time feedback and personalized training in order to support the improvement of users' work efficiency and interpersonal skills. However, current systems are insufficient in recognizing users' emotional states and dynamically adjusting work schedules based on work data, limiting the optimization of the entire operation. This leads to increased burden on users and difficulties in improving customer satisfaction. 【0375】 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. 【0376】 In this invention, the server includes an information processing device for users to input work data, a data storage device for checking the integrity of the input data and storing it, and an analysis device for analyzing dynamic data during face-to-face customer service and generating responses. This makes it possible to recognize the user's emotional state in real time and provide a dynamically optimized work schedule. As a result, users can receive feedback and training based on their emotional state, which is expected to improve work efficiency and skills. 【0377】 An "information processing device" is a device used by users to input data related to their work. 【0378】 A "data storage device" is a system for verifying the integrity of received data and storing it. 【0379】 An "analysis device" is a device that analyzes real-time dynamic data obtained during customer service and generates feedback and responses. 【0380】 A "generation device" is a means of creating personalized educational programs for users. 【0381】 An "optimization device" is a means of automatically optimizing and allocating users' work time based on business needs. 【0382】 An "analytical device" is a means of analyzing customer and user interaction data to provide insights. 【0383】 An "emotion recognition device" is a means of recognizing a user's emotional state and providing appropriate feedback based on that information. 【0384】 This invention provides an integrated platform for improving the work efficiency and interpersonal skills of users in sales operations. This system mainly includes information processing devices, data storage servers, real-time analysis devices, generation devices, optimization functions, and emotion recognition functions. 【0385】 Information processing device 【0386】 The terminal is used by users to input work data at the start and end of their workday. Specifically, sales information and shift information are recorded on the terminal using the keyboard or touch input and treated as entry data. 【0387】 Data storage device 【0388】 The server checks the integrity of the data and stores it in the database using a secure communication protocol. The stored data serves as basic information for evaluating the user's work performance. 【0389】 Real-time analysis device and emotion recognition 【0390】 During customer service, the terminal collects voice and motion data. The emotion recognition device analyzes this data to identify the user's emotional state in real time. Based on the recognition results, the server generates appropriate feedback and notifies the user. 【0391】 Provision of educational programs using generation equipment 【0392】 The server generates personalized training programs based on the user's past work data and current emotional state. This allows users to receive training optimized for them, leading to improved skills. 【0393】 Optimization function 【0394】 The server analyzes data obtained from various sources and optimizes the user's work schedule. This enables efficient allocation of work time and reduces the user's burden. 【0395】 For example, if a user exhibits high stress levels during customer service, the emotion recognition device detects this and generates feedback on relaxation techniques. Furthermore, a personalized stress management education program is provided on the device. This gives users the opportunity to quickly improve their stress management skills. By inputting a prompt sentence such as, "What relaxation techniques should be recommended if the user exhibits high stress levels?" into the AI ​​model, the optimal feedback content is created. 【0396】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0397】 Step 1: 【0398】 Users input sales and shift information using a terminal at the start of their workday. The entered data is sent to the database server by the terminal. The input here consists of numerical and text data, which the terminal sends to the server using HTTP communication. 【0399】 Step 2: 【0400】 The server checks the integrity of the received data. This integrity check verifies that sales information is numerical and that shift information is in the correct format. The server then saves the verified data to the database. This saving operation makes the data available for future analysis and reporting. 【0401】 Step 3: 【0402】 While the user is interacting with customers, the terminal collects voice and motion data. The terminal transmits this data to an emotion recognition device in real time. The input here is audio files and video frames, which the emotion recognition device analyzes to identify the user's emotional state. The identified emotion data is sent to a server to serve as the basis for generating feedback. 【0403】 Step 4: 【0404】 The server generates feedback based on the emotion recognition results. It inputs prompts into a generation AI model to construct appropriate feedback. The generated feedback is sent to the terminal and notified to the user. This feedback output can be a text message or voice instruction. 【0405】 Step 5: 【0406】 The server generates a personalized training program based on past work data and current emotional state. This program includes training content tailored to the user's characteristics. The generated program is delivered on the terminal to support the user's skill improvement. The program's output is displayed in the form of video tutorials and online learning materials. 【0407】 Step 6: 【0408】 The server executes an algorithm to optimize work schedules based on data collected from various sources. Using past work history and data on business demand, it dynamically adjusts user shifts to achieve efficient work allocation. The optimized schedule is displayed on the terminal, allowing users to check their schedules. 【0409】 (Application Example 2) 【0410】 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." 【0411】 Smooth communication with customers during on-site service delivery, and improving staff work efficiency and interpersonal skills, are crucial challenges in brick-and-mortar store management. Furthermore, it is essential for on-site staff to recognize their own emotional states and respond appropriately, thereby improving their skills, in order to enhance customer satisfaction. However, conventional systems have struggled to provide real-time emotional recognition, appropriate feedback, and training modules, making it difficult to efficiently address these challenges. 【0412】 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. 【0413】 In this invention, the server includes a data processing device for users to input work information, a data management device for checking the integrity of the input information and storing it, an analysis device for analyzing real-time information during service provision and generating feedback, and an educational support device for providing personalized training modules based on emotional states. This allows staff to grasp their own and the customer's emotional states in real time during interactions with customers, enabling appropriate and timely responses and skill development. Furthermore, by providing efficient work allocation, it is possible to improve the overall productivity of operations. 【0414】 A "data processing device" is a device that takes user input of work information and converts it into a format usable within the system. 【0415】 A "data management device" is a device used to verify the integrity of input data and to store it appropriately. 【0416】 An "analysis device" is a device that analyzes real-time data collected during service provision and generates appropriate feedback. 【0417】 A "configuration device" is a device that has the function of creating learning modules optimized for individual users. 【0418】 An "optimization scheduling device" is a device that automatically determines an efficient work schedule based on collected work-related information. 【0419】 An "analytical device" is a device that analyzes customer interaction data and provides useful insights. 【0420】 An "emotion recognition device" is a device that has the function of identifying the emotional state of users and customers in real time. 【0421】 An "educational support device" is a device that provides individualized training modules tailored to the user's emotional state. 【0422】 The system implementing this invention is an integrated platform including a data processing device, a data management device, an analysis device, a configuration device, an optimization placement device, an analysis device, an emotion recognition device, and an educational support device. The system is realized through the cooperation of the user's smart glasses or smartphone with a server. 【0423】 The server receives business information entered by the user, checks its integrity using a data processing device, and then stores it in storage. This data is fundamental information for analyzing the user's work efficiency. During real-time work, the user's terminal collects conversation and behavioral data with customers and sends it to the server. The server's analysis device uses this data to recognize customer emotions and generate appropriate feedback for the user. 【0424】 Furthermore, the emotion recognition device evaluates the user's emotional state in real time, and the analysis device provides insights based on that information. This allows the server to provide feedback tailored to each user's individual state. In addition, the system analyzes the user's past performance data and current emotional state to generate a customized learning module. This module is displayed on the user's smart glasses or smartphone to support individual skill improvement. 【0425】 The optimization placement device acquires business-related information from multiple data sources and efficiently adjusts work schedules. Furthermore, by analyzing this data and considering the emotional state of users, it is possible to improve the quality of work. 【0426】 As a concrete example, a florist wearing smart glasses can monitor their own and the customer's emotional state in real time during interactions, enabling them to provide more appropriate service. An example of a prompt to the generated AI model is, "Analyze the customer's facial expressions and vocal characteristics when they choose flowers, and determine their emotional state." This system allows users to improve work efficiency and customer satisfaction. 【0427】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0428】 Step 1: 【0429】 Users input work information into a terminal. Users use smart glasses or smartphones to input sales and shift information at the start of their workday. This data is sent to the server as input data and processed as initial data. 【0430】 Step 2: 【0431】 The server checks the integrity of the input data and stores it through the data management device. After receiving business information, the server performs an integrity check and stores the data in a database. This becomes the foundational data used for later analysis. 【0432】 Step 3: 【0433】 The device collects customer interaction data in real time. Using the device's camera and microphone, it records the customer's facial expressions and voice in real time. This serves as the input for customer data. 【0434】 Step 4: 【0435】 The server uses an analysis device to analyze the collected data and perform emotion recognition. The server inputs the customer's facial expressions and voice characteristics into emotion recognition software to determine their emotional state. This is the output of the information analysis. 【0436】 Step 5: 【0437】 The server generates feedback based on the analysis results and sends it to the terminal. The server generates appropriate feedback from the output of the analysis device and sends it to the user's terminal. This allows the user to optimize the interaction in real time. 【0438】 Step 6: 【0439】 The server generates customized learning modules using educational support devices. Based on historical work data and real-time sentiment data, the server creates an individualized training plan and sends it to the user's terminal. 【0440】 Step 7: 【0441】 The server dynamically allocates work schedules using an optimization placement device. The server references multiple data sources and considers work demands and emotional states to efficiently optimize user work time. 【0442】 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. 【0443】 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. 【0444】 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. 【0445】 [Third Embodiment] 【0446】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0447】 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. 【0448】 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). 【0449】 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. 【0450】 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. 【0451】 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). 【0452】 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. 【0453】 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. 【0454】 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. 【0455】 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. 【0456】 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. 【0457】 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". 【0458】 The system of this invention provides comprehensive management and support functions to enable users engaged in sales operations to perform their duties efficiently. This system mainly consists of three elements: a server, a terminal, and a user, and each element works in cooperation with the others. 【0459】 Users input their daily work data into a terminal. The terminal checks the format of the input data and sends it to the server. The server checks the integrity of the received data and stores it securely. The stored data includes a wide range of information, such as crew sales information, customer service performance, and shift information. 【0460】 During customer service activities, the user's device collects voice and location data. The server uses this data to perform real-time analysis, and an AI model evaluates the user's customer service attitude and the customer's emotions. The evaluation results are immediately sent to the user's device as feedback, and areas for improvement are notified. 【0461】 The server also analyzes accumulated user performance data and automatically generates individually optimized educational programs. The generated programs are delivered to the user's device, and the course schedule and other information are presented. 【0462】 Shift optimization based on business demand is also performed on the server. The server dynamically calculates work schedules, taking into account customer demand at each store and the capabilities of the users. These calculation results are sent to the users' terminals to ensure smooth workflow. 【0463】 Furthermore, extracting customer insights is also a crucial element. The server uses accumulated customer data to analyze new insights and suggest service improvements. Based on this, it provides users with concrete strategic proposals and notifies them of feasible improvement measures. 【0464】 As a concrete example, for users who provide highly-rated customer service during peak hours at a retail store, a training program is generated that allows them to reflect on their behavioral characteristics. The program is presented as a set of skills applicable to similar situations, helping to promote further growth for the user. 【0465】 Through this series of processes, the present invention enables the efficient management and training of personnel engaged in sales operations, contributing to improved operational productivity and enhanced customer satisfaction. 【0466】 The following describes the processing flow. 【0467】 Step 1: 【0468】 The user enters sales data and the start and end times of their work into the terminal. The terminal formats the entered data and sends it to the server according to a security protocol. 【0469】 Step 2: 【0470】 The server receives data sent from the terminal and verifies its integrity. If the data is correct, it is saved to the centralized management database. 【0471】 Step 3: 【0472】 When a user interacts with a customer, the device collects voice and motion data in real time. This data is immediately sent to a server for analysis. 【0473】 Step 4: 【0474】 The server analyzes the received audio data and uses an AI model to evaluate customer satisfaction and user service attitude. The evaluation results are generated as feedback. 【0475】 Step 5: 【0476】 The terminal receives feedback from the server and displays it to the user. The user can then consider improvement measures based on the feedback. 【0477】 Step 6: 【0478】 The server analyzes accumulated user performance data and generates educational programs that focus on areas where specific skill improvements are needed. 【0479】 Step 7: 【0480】 The terminal receives educational programs distributed from the server and notifies the user of the course schedule and details. 【0481】 Step 8: 【0482】 The server analyzes customer demand data and crew performance data to dynamically calculate optimized shifts. 【0483】 Step 9: 【0484】 The terminal receives new shift information from the server and displays it to the user. The user then performs their duties based on this shift information. 【0485】 Step 10: 【0486】 The server analyzes customer data and extracts insights and potential trends. Based on this, it creates specific suggestions for service improvement. 【0487】 Step 11: 【0488】 The terminal receives suggestions from the server and notifies the user of the improvement measures. The user can then improve the quality of their customer service by implementing the suggestions. 【0489】 (Example 1) 【0490】 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." 【0491】 In modern sales operations, efficient data management, real-time analytics, personalized training, and dynamic shift adjustments based on demand are crucial. However, the lack of a system that centrally manages and integrates these processes leads to a decline in overall operational efficiency and customer satisfaction. 【0492】 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. 【0493】 In this invention, the server includes a storage means for checking the integrity of input information and storing it, an analysis means for analyzing real-time information acquired during customer service and generating feedback, and an education means for generating education programs tailored to each user. This enables more efficient data management in sales operations, rapid improvement of users' customer service attitudes, and the provision of individually optimized education. 【0494】 A "terminal device" is a device used by a user to input information and has a function to check the integrity of the input data. 【0495】 A "memory device" is a part of a system that has the function of securely storing input information and keeping it in a state that can be accessed as needed. 【0496】 The "analysis means" refers to a function that analyzes information acquired in real time and executes a process to provide feedback to the user. 【0497】 The "educational tool" has the function of automatically generating and providing individually optimized educational programs based on the user's performance data. 【0498】 "Adjustment mechanisms" are functions that dynamically allocate work time based on the demands of the business, thereby supporting efficient business operations. 【0499】 "Analytical tools" are those that analyze information based on customer interactions, provide new insights, and propose concrete strategies. 【0500】 This system is designed to enable users engaged in sales operations to perform their duties efficiently. Its main components include a server, terminals, and users, and each element works in conjunction with the others. 【0501】 Users begin by entering daily work information using a terminal. The terminal checks the integrity of the information entered by the user and sends it to the server if the format is correct. This terminal device is involved in input via touchscreen or keyboard, and data buffering. 【0502】 The server receives information transmitted from the terminal and stores it in a database using secure storage methods. This data includes sales information and customer service history. Furthermore, the server analyzes real-time information acquired during customer service and generates feedback based on a generated AI model. This analysis step utilizes speech recognition software and location services. 【0503】 While a user is interacting with an employee, the device automatically collects voice and location data and sends it to a server. The server's analysis system evaluates the user's behavior based on this data and provides real-time feedback. This feedback is intended to encourage improvements in customer service practices. 【0504】 Furthermore, the server utilizes educational tools to generate personalized training programs based on past performance data. These programs are delivered to the user's device and presented along with the training schedule. For example, if a salesperson receives high ratings for customer service during peak hours, a training program is created based on their specific behavioral characteristics. 【0505】 The system also optimizes shifts based on business demand, specifically by adjusting work hours based on trends in customer numbers and staff skill set data. 【0506】 The system also includes analytical tools that analyze customer interaction data to provide new insights. Based on this, the server generates strategic recommendations and notifies the user. 【0507】 An example of a prompt message is: "Analyze recent customer service data from peak hours, extract the specific skills of staff members who provided particularly high customer satisfaction, and create a training program based on that that can be applied to other staff members." 【0508】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0509】 Step 1: 【0510】 Users input work-related information using a terminal. Specifically, they input sales data, customer service history, shift information, etc., and store the data correctly according to the format. The entered data is temporarily stored on the terminal. 【0511】 Step 2: 【0512】 The terminal performs an integrity check on the input data. It verifies that the data format and required fields are entered correctly. Once the check is complete, it prepares to send the data to the server. If there are no integrity issues, the terminal is triggered to send the data to the server. 【0513】 Step 3: 【0514】 The server receives the data sent from the terminal and performs another integrity check. After confirming that there is no duplicate data or invalid entries, it stores the data in a secure database. The moment the data integrity is confirmed, the write operation to the database is executed. 【0515】 Step 4: 【0516】 When a user interacts with a customer, the device begins collecting voice and location data. This information is acquired using the built-in microphone and GPS module and transmitted to the server in real time. This step starts automatically each time a user action occurs. 【0517】 Step 5: 【0518】 The server processes the received audio and location data through an AI model to analyze the user's customer service attitude and the customer's emotions. Data processing includes converting audio to text and calculating distance and time to the customer using location information. The analysis results are immediately sent to the user's device as feedback. 【0519】 Step 6: 【0520】 The server analyzes accumulated user performance data and generates personalized training programs. This involves analyzing historical data to identify areas where specific skills or knowledge need strengthening. The training programs are then delivered to the user's device, and the user learns based on them. 【0521】 Step 7: 【0522】 The server optimizes work shifts using customer trend data and user skill profiles. Predictive algorithms are used in the calculations to ensure optimal staffing at all times. The adjustment results are sent to terminals, where users can check the new shift information. 【0523】 Step 8: 【0524】 The server analyzes customer data using advanced analytical algorithms to extract new customer insights and suggestions for service improvements. Based on these results, it generates prompt messages to notify the user, allowing them to use them as a reference for implementing their strategies. 【0525】 (Application Example 1) 【0526】 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." 【0527】 In modern brick-and-mortar retail operations, there is a demand for improved staff customer service skills and increased customer satisfaction. However, there is a lack of systems that effectively provide real-time feedback and personalized training programs, resulting in insufficient efficiency and optimization of operations. Furthermore, because methods for analyzing and immediately evaluating sales staff behavior and conversation data are underdeveloped, staff do not have the opportunity to immediately improve their customer service style. 【0528】 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. 【0529】 In this invention, the server includes means for checking the integrity of input data and storing it, means for analyzing real-time data during customer service and generating feedback, and means for analyzing and evaluating the salesperson's behavior and conversation data in real time and notifying them of areas for improvement. This enables immediate improvement of staff customer service skills in sales operations, leading to increased operational fluidity and customer satisfaction. 【0530】 An "information processing device" is an electronic device used by users to input sales data. 【0531】 A "data server" is a computer system that performs integrity checks and stores data sent by users. 【0532】 "Analysis means" refers to a function that analyzes real-time data collected during customer service and generates feedback. 【0533】 The "generation method" refers to a function that automatically creates training modules optimized for each sales staff member. 【0534】 An "optimization method" is an algorithm that automatically adjusts work schedules according to the demands of the work. 【0535】 "Analysis tools" refer to functions that analyze customer interaction data and provide insights useful for sales strategies. 【0536】 The "evaluation method" is a function that analyzes the seller's behavior and conversation data, evaluates it in real time, and notifies them of areas for improvement. 【0537】 The system for implementing this invention consists of a user, a terminal for sending and receiving data, and a server for processing. The user inputs daily work data using a terminal such as a smartphone or tablet. The terminal checks the integrity of the input data and transmits it to the data server via the internet. The server securely stores the data and operates analysis means as needed. 【0538】 The server's analysis method uses voice and location data to evaluate the user's customer service activities in real time and generates feedback using an AI model. The feedback is immediately delivered to the user's device, allowing the user to see specific areas for improvement. The server also generates individually optimized training modules based on the evaluation results and accumulated data. The generated training modules are delivered to the user's device, and a learning schedule is presented. 【0539】 To ensure operational fluidity, the server has a function to optimize work schedules based on business demand. It dynamically calculates shift assignments, taking into account customer demand data for each store and user capacity data. This result is also delivered to the user's terminal. Furthermore, the server analyzes customer interaction data to extract new insights, which are used to improve sales strategies. 【0540】 As a concrete example, a training program is generated for sales staff who provide highly-rated customer service during peak hours, allowing them to reflect on their actions. This program is presented to users as a set of skills applicable to similar situations, supporting their growth. For instance, prompts such as, "What feedback did you receive from your recent customer service experience? What actions will you take to improve?" are used. This leads to immediate improvement in customer service skills and increased customer satisfaction. 【0541】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0542】 Step 1: 【0543】 The user enters business data into a terminal. The terminal checks the integrity of the entered business data and sends it to the server. The entered data includes customer information, sales performance, customer service details, etc. Data whose integrity has been confirmed is used as the basis for the next processing step. 【0544】 Step 2: 【0545】 The server securely stores the received data and activates the analysis tools. The stored data includes sales data, customer service details, and customer feedback. The server uses the stored data to run an AI model and prepares to evaluate the user's customer service activities. 【0546】 Step 3: 【0547】 The server receives voice and location data transmitted from the terminal and performs real-time analysis. Voice data is converted to text using speech recognition software and analyzed by an AI model. Location data is used to calculate user movement patterns and dwell time. This results in output that evaluates the user's customer service style and customer reactions. 【0548】 Step 4: 【0549】 The server generates feedback on the user's customer service activities based on the analysis results from the AI ​​model. The feedback includes areas for improvement and points of good behavior, along with specific methods for improvement. The generated feedback is sent to the user's device as a push notification. 【0550】 Step 5: 【0551】 The server adds the user's evaluation results to the stored data and activates the means for generating educational programs. The server analyzes the evaluation data and assembles educational modules optimized for each individual user. This educational program is sent to the user's terminal, and the schedule is displayed. 【0552】 Step 6: 【0553】 The server uses optimization techniques to calculate a dynamic work schedule based on business demand. Flexible shift assignments are created based on business-related information and user capability data. The optimized shift information is then sent to the user's terminal. 【0554】 Step 7: 【0555】 The server activates analytical tools to extract new customer insights based on accumulated customer interaction data. It analyzes customer conversations and purchase history to generate information that can lead to improvements in sales strategies. The analysis results are provided to the user as strategic recommendations and notifications. 【0556】 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. 【0557】 The present invention provides an integrated platform for improving users' work efficiency and interpersonal skills in sales operations. This system includes an information processing device for user input of work data, a data server for data integrity checks and storage, an analysis means for analyzing real-time data during customer service, a generation means for generating optimized training modules, an optimization means for automatically assigning work schedules based on business needs, and an analysis means for analyzing customer interaction data. Furthermore, by incorporating an emotion engine that recognizes user emotions, it becomes possible to understand the user's emotional state and provide more accurate feedback and training content. 【0558】 Users input sales and shift information into a terminal at the start and end of their workday. This terminal sends the input data to a server. The server checks the received data and stores it in a database. This data is used as basic information for analyzing the user's work performance. 【0559】 During customer service, the user's device collects voice and motion data. The emotion engine analyzes this data to recognize the user's emotions in real time. The emotion recognition results are sent to a server and used as reference information to generate feedback. Based on the user's emotions, the analysis system determines appropriate feedback and notifies the user through the device. 【0560】 The generation method creates personalized educational modules based on the user's past performance data and emotion recognition results. These modules are tailored to the user's characteristics and challenges and are delivered via the device. This allows users to receive education suited to their emotional state, leading to expected skill improvement. 【0561】 Furthermore, the optimization mechanism dynamically assigns work schedules based on information obtained from multiple data sources. This optimizes each user's work style and enables efficient resource allocation. 【0562】 For example, if the emotion engine detects that a user is experiencing stress during customer interactions, the analysis means generates feedback that takes that emotion into account and provides an educational module on stress management. In this way, the system of the present invention helps to improve the user's work efficiency and satisfaction by utilizing emotion recognition. 【0563】 The following describes the processing flow. 【0564】 Step 1: 【0565】 At the start of their workday, users use a terminal to enter their login information and begin inputting work data. The terminal formats this data and sends it to the server in real time. 【0566】 Step 2: 【0567】 The server receives business data sent from terminals and automatically checks its integrity. If the data is correct, it is saved to a database and managed as a daily work record. 【0568】 Step 3: 【0569】 When a user begins interacting with a customer, the device collects voice and gesture data in real time and sends it to the server. 【0570】 Step 4: 【0571】 The server uses an emotion engine to analyze the user's emotional state in real time from received voice and behavioral data. Based on the analysis results, it identifies the user's psychological state. 【0572】 Step 5: 【0573】 The analysis tool uses data provided by the emotion engine to generate feedback. This feedback, tailored to the user's emotional state, is delivered to the user via the device. 【0574】 Step 6: 【0575】 Users will be able to immediately work on improving their customer service methods based on the feedback they receive from their devices. 【0576】 Step 7: 【0577】 The server integrates and analyzes historical performance data and sentiment recognition results to generate user-optimized educational modules. These generated modules are then delivered to the user via their terminal. 【0578】 Step 8: 【0579】 The terminal manages information from the educational modules provided to the user and helps prepare them for application to subsequent tasks. 【0580】 Step 9: 【0581】 The server dynamically optimizes users' work schedules by utilizing information from multiple data sources. This optimization helps to facilitate smooth staffing in business operations. 【0582】 Step 10: 【0583】 The terminal receives optimized shift information sent from the server and displays it visually to the user. This allows the user to understand the new shift and perform their work efficiently. 【0584】 (Example 2) 【0585】 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." 【0586】 In sales operations, a system is needed that comprehensively utilizes diverse data to provide real-time feedback and personalized training in order to support the improvement of users' work efficiency and interpersonal skills. However, current systems are insufficient in recognizing users' emotional states and dynamically adjusting work schedules based on work data, limiting the optimization of the entire operation. This leads to increased burden on users and difficulties in improving customer satisfaction. 【0587】 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. 【0588】 In this invention, the server includes an information processing device for users to input work data, a data storage device for checking the integrity of the input data and storing it, and an analysis device for analyzing dynamic data during face-to-face customer service and generating responses. This makes it possible to recognize the user's emotional state in real time and provide a dynamically optimized work schedule. As a result, users can receive feedback and training based on their emotional state, which is expected to improve work efficiency and skills. 【0589】 An "information processing device" is a device used by users to input data related to their work. 【0590】 A "data storage device" is a system for verifying the integrity of received data and storing it. 【0591】 An "analysis device" is a device that analyzes real-time dynamic data obtained during customer service and generates feedback and responses. 【0592】 A "generation device" is a means of creating personalized educational programs for users. 【0593】 An "optimization device" is a means of automatically optimizing and allocating users' work time based on business needs. 【0594】 An "analytical device" is a means of analyzing customer and user interaction data to provide insights. 【0595】 An "emotion recognition device" is a means of recognizing a user's emotional state and providing appropriate feedback based on that information. 【0596】 This invention provides an integrated platform for improving the work efficiency and interpersonal skills of users in sales operations. This system mainly includes information processing devices, data storage servers, real-time analysis devices, generation devices, optimization functions, and emotion recognition functions. 【0597】 Information processing device 【0598】 The terminal is used by users to input work data at the start and end of their workday. Specifically, sales information and shift information are recorded on the terminal using the keyboard or touch input and treated as entry data. 【0599】 Data storage device 【0600】 The server checks the integrity of the data and stores it in the database using a secure communication protocol. The stored data serves as basic information for evaluating the user's work performance. 【0601】 Real-time analysis device and emotion recognition 【0602】 During customer service, the terminal collects voice and motion data. The emotion recognition device analyzes this data to identify the user's emotional state in real time. Based on the recognition results, the server generates appropriate feedback and notifies the user. 【0603】 Provision of educational programs using generation equipment 【0604】 The server generates personalized training programs based on the user's past work data and current emotional state. This allows users to receive training optimized for them, leading to improved skills. 【0605】 Optimization function 【0606】 The server analyzes data obtained from various sources and optimizes the user's work schedule. This enables efficient allocation of work time and reduces the user's burden. 【0607】 For example, if a user exhibits high stress levels during customer service, the emotion recognition device detects this and generates feedback on relaxation techniques. Furthermore, a personalized stress management education program is provided on the device. This gives users the opportunity to quickly improve their stress management skills. By inputting a prompt sentence such as, "What relaxation techniques should be recommended if the user exhibits high stress levels?" into the AI ​​model, the optimal feedback content is created. 【0608】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0609】 Step 1: 【0610】 Users input sales and shift information using a terminal at the start of their workday. The entered data is sent to the database server by the terminal. The input here consists of numerical and text data, which the terminal sends to the server using HTTP communication. 【0611】 Step 2: 【0612】 The server checks the integrity of the received data. This integrity check verifies that sales information is numerical and that shift information is in the correct format. The server then saves the verified data to the database. This saving operation makes the data available for future analysis and reporting. 【0613】 Step 3: 【0614】 While the user is interacting with customers, the terminal collects voice and motion data. The terminal transmits this data to an emotion recognition device in real time. The input here is audio files and video frames, which the emotion recognition device analyzes to identify the user's emotional state. The identified emotion data is sent to a server to serve as the basis for generating feedback. 【0615】 Step 4: 【0616】 The server generates feedback based on the emotion recognition results. It inputs prompts into a generation AI model to construct appropriate feedback. The generated feedback is sent to the terminal and notified to the user. This feedback output can be a text message or voice instruction. 【0617】 Step 5: 【0618】 The server generates a personalized training program based on past work data and current emotional state. This program includes training content tailored to the user's characteristics. The generated program is delivered on the terminal to support the user's skill improvement. The program's output is displayed in the form of video tutorials and online learning materials. 【0619】 Step 6: 【0620】 The server executes an algorithm to optimize work schedules based on data collected from various sources. Using past work history and data on business demand, it dynamically adjusts user shifts to achieve efficient work allocation. The optimized schedule is displayed on the terminal, allowing users to check their schedules. 【0621】 (Application Example 2) 【0622】 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." 【0623】 Smooth communication with customers during on-site service delivery, and improving staff work efficiency and interpersonal skills, are crucial challenges in brick-and-mortar store management. Furthermore, it is essential for on-site staff to recognize their own emotional states and respond appropriately, thereby improving their skills, in order to enhance customer satisfaction. However, conventional systems have struggled to provide real-time emotional recognition, appropriate feedback, and training modules, making it difficult to efficiently address these challenges. 【0624】 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. 【0625】 In this invention, the server includes a data processing device for users to input work information, a data management device for checking the integrity of the input information and storing it, an analysis device for analyzing real-time information during service provision and generating feedback, and an educational support device for providing personalized training modules based on emotional states. This allows staff to grasp their own and the customer's emotional states in real time during interactions with customers, enabling appropriate and timely responses and skill development. Furthermore, by providing efficient work allocation, it is possible to improve the overall productivity of operations. 【0626】 A "data processing device" is a device that takes user input of work information and converts it into a format usable within the system. 【0627】 A "data management device" is a device used to verify the integrity of input data and to store it appropriately. 【0628】 An "analysis device" is a device that analyzes real-time data collected during service provision and generates appropriate feedback. 【0629】 A "configuration device" is a device that has the function of creating learning modules optimized for individual users. 【0630】 An "optimization scheduling device" is a device that automatically determines an efficient work schedule based on collected work-related information. 【0631】 An "analytical device" is a device that analyzes customer interaction data and provides useful insights. 【0632】 An "emotion recognition device" is a device that has the function of identifying the emotional state of users and customers in real time. 【0633】 An "educational support device" is a device that provides individualized training modules tailored to the user's emotional state. 【0634】 The system implementing this invention is an integrated platform including a data processing device, a data management device, an analysis device, a configuration device, an optimization placement device, an analysis device, an emotion recognition device, and an educational support device. The system is realized through the cooperation of the user's smart glasses or smartphone with a server. 【0635】 The server receives business information entered by the user, checks its integrity using a data processing device, and then stores it in storage. This data is fundamental information for analyzing the user's work efficiency. During real-time work, the user's terminal collects conversation and behavioral data with customers and sends it to the server. The server's analysis device uses this data to recognize customer emotions and generate appropriate feedback for the user. 【0636】 Furthermore, the emotion recognition device evaluates the user's emotional state in real time, and the analysis device provides insights based on that information. This allows the server to provide feedback tailored to each user's individual state. In addition, the system analyzes the user's past performance data and current emotional state to generate a customized learning module. This module is displayed on the user's smart glasses or smartphone to support individual skill improvement. 【0637】 The optimization placement device acquires business-related information from multiple data sources and efficiently adjusts work schedules. Furthermore, by analyzing this data and considering the emotional state of users, it is possible to improve the quality of work. 【0638】 As a concrete example, a florist wearing smart glasses can monitor their own and the customer's emotional state in real time during interactions, enabling them to provide more appropriate service. An example of a prompt to the generated AI model is, "Analyze the customer's facial expressions and vocal characteristics when they choose flowers, and determine their emotional state." This system allows users to improve work efficiency and customer satisfaction. 【0639】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0640】 Step 1: 【0641】 Users input work information into a terminal. Users use smart glasses or smartphones to input sales and shift information at the start of their workday. This data is sent to the server as input data and processed as initial data. 【0642】 Step 2: 【0643】 The server checks the integrity of the input data and stores it through the data management device. After receiving business information, the server performs an integrity check and stores the data in a database. This becomes the foundational data used for later analysis. 【0644】 Step 3: 【0645】 The device collects customer interaction data in real time. Using the device's camera and microphone, it records the customer's facial expressions and voice in real time. This serves as the input for customer data. 【0646】 Step 4: 【0647】 The server uses an analysis device to analyze the collected data and perform emotion recognition. The server inputs the customer's facial expressions and voice characteristics into emotion recognition software to determine their emotional state. This is the output of the information analysis. 【0648】 Step 5: 【0649】 The server generates feedback based on the analysis results and sends it to the terminal. The server generates appropriate feedback from the output of the analysis device and sends it to the user's terminal. This allows the user to optimize the interaction in real time. 【0650】 Step 6: 【0651】 The server generates customized learning modules using educational support devices. Based on historical work data and real-time sentiment data, the server creates an individualized training plan and sends it to the user's terminal. 【0652】 Step 7: 【0653】 The server dynamically allocates work schedules using an optimization placement device. The server references multiple data sources and considers work demands and emotional states to efficiently optimize user work time. 【0654】 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. 【0655】 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. 【0656】 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. 【0657】 [Fourth Embodiment] 【0658】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0659】 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. 【0660】 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). 【0661】 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. 【0662】 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. 【0663】 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). 【0664】 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. 【0665】 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. 【0666】 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. 【0667】 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. 【0668】 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. 【0669】 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. 【0670】 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". 【0671】 The system of this invention provides comprehensive management and support functions to enable users engaged in sales operations to perform their duties efficiently. This system mainly consists of three elements: a server, a terminal, and a user, and each element works in cooperation with the others. 【0672】 Users input their daily work data into a terminal. The terminal checks the format of the input data and sends it to the server. The server checks the integrity of the received data and stores it securely. The stored data includes a wide range of information, such as crew sales information, customer service performance, and shift information. 【0673】 During customer service activities, the user's device collects voice and location data. The server uses this data to perform real-time analysis, and an AI model evaluates the user's customer service attitude and the customer's emotions. The evaluation results are immediately sent to the user's device as feedback, and areas for improvement are notified. 【0674】 The server also analyzes accumulated user performance data and automatically generates individually optimized educational programs. The generated programs are delivered to the user's device, and the course schedule and other information are presented. 【0675】 Shift optimization based on business demand is also performed on the server. The server dynamically calculates work schedules, taking into account customer demand at each store and the capabilities of the users. These calculation results are sent to the users' terminals to ensure smooth workflow. 【0676】 Furthermore, extracting customer insights is also a crucial element. The server uses accumulated customer data to analyze new insights and suggest service improvements. Based on this, it provides users with concrete strategic proposals and notifies them of feasible improvement measures. 【0677】 As a concrete example, for users who provide highly-rated customer service during peak hours at a retail store, a training program is generated that allows them to reflect on their behavioral characteristics. The program is presented as a set of skills applicable to similar situations, helping to promote further growth for the user. 【0678】 Through this series of processes, the present invention enables the efficient management and training of personnel engaged in sales operations, contributing to improved operational productivity and enhanced customer satisfaction. 【0679】 The following describes the processing flow. 【0680】 Step 1: 【0681】 The user enters sales data and the start and end times of their work into the terminal. The terminal formats the entered data and sends it to the server according to a security protocol. 【0682】 Step 2: 【0683】 The server receives data sent from the terminal and verifies its integrity. If the data is correct, it is saved to the centralized management database. 【0684】 Step 3: 【0685】 When a user interacts with a customer, the device collects voice and motion data in real time. This data is immediately sent to a server for analysis. 【0686】 Step 4: 【0687】 The server analyzes the received audio data and uses an AI model to evaluate customer satisfaction and the user's service attitude. The evaluation results are generated as feedback. 【0688】 Step 5: 【0689】 The terminal receives feedback from the server and displays it to the user. The user can then consider improvement measures based on the feedback. 【0690】 Step 6: 【0691】 The server analyzes accumulated user performance data and generates educational programs that focus on areas where specific skill improvements are needed. 【0692】 Step 7: 【0693】 The terminal receives educational programs distributed from the server and notifies the user of the course schedule and details. 【0694】 Step 8: 【0695】 The server analyzes customer demand data and crew performance data to dynamically calculate optimized shifts. 【0696】 Step 9: 【0697】 The terminal receives new shift information from the server and displays it to the user. The user then performs their duties based on this shift information. 【0698】 Step 10: 【0699】 The server analyzes customer data and extracts insights and potential trends. Based on this, it creates specific suggestions for service improvement. 【0700】 Step 11: 【0701】 The terminal receives suggestions from the server and notifies the user of the improvement measures. The user can then improve the quality of their customer service by implementing the suggestions. 【0702】 (Example 1) 【0703】 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". 【0704】 In modern sales operations, efficient data management, real-time analytics, personalized training, and dynamic shift adjustments based on demand are crucial. However, the lack of a system that centrally manages and integrates these processes leads to a decline in overall operational efficiency and customer satisfaction. 【0705】 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. 【0706】 In this invention, the server includes a storage means for checking the integrity of input information and storing it, an analysis means for analyzing real-time information acquired during customer service and generating feedback, and an education means for generating education programs tailored to each user. This enables more efficient data management in sales operations, rapid improvement of users' customer service attitudes, and the provision of individually optimized education. 【0707】 A "terminal device" is a device used by a user to input information and has a function to check the integrity of the input data. 【0708】 A "memory device" is a part of a system that has the function of securely storing input information and keeping it in a state that can be accessed as needed. 【0709】 The "analysis means" refers to a function that analyzes information acquired in real time and executes a process to provide feedback to the user. 【0710】 The "educational tool" has the function of automatically generating and providing individually optimized educational programs based on the user's performance data. 【0711】 "Adjustment mechanisms" are functions that dynamically allocate work time based on the demands of the business, thereby supporting efficient business operations. 【0712】 "Analytical tools" are those that analyze information based on customer interactions, provide new insights, and propose concrete strategies. 【0713】 This system is designed to enable users engaged in sales operations to perform their duties efficiently. Its main components include a server, terminals, and users, and each element works in conjunction with the others. 【0714】 Users begin by entering daily work information using a terminal. The terminal checks the integrity of the information entered by the user and sends it to the server if the format is correct. This terminal device is involved in input via touchscreen or keyboard, and data buffering. 【0715】 The server receives information transmitted from the terminal and stores it in a database using secure storage methods. This data includes sales information and customer service history. Furthermore, the server analyzes real-time information acquired during customer service and generates feedback based on a generated AI model. This analysis step utilizes speech recognition software and location services. 【0716】 While a user is interacting with an employee, the device automatically collects voice and location data and sends it to a server. The server's analysis system evaluates the user's behavior based on this data and provides real-time feedback. This feedback is intended to encourage improvements in customer service practices. 【0717】 Furthermore, the server utilizes educational tools to generate personalized training programs based on past performance data. These programs are delivered to the user's device and presented along with the training schedule. For example, if a salesperson receives high ratings for customer service during peak hours, a training program is created based on their specific behavioral characteristics. 【0718】 The system also optimizes shifts based on business demand, specifically by adjusting work hours based on trends in customer numbers and staff skill set data. 【0719】 The system also includes analytical tools that analyze customer interaction data to provide new insights. Based on this, the server generates strategic recommendations and notifies the user. 【0720】 An example of a prompt message is: "Analyze recent customer service data from peak hours, extract the specific skills of staff members who provided particularly high customer satisfaction, and create a training program based on that that can be applied to other staff members." 【0721】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0722】 Step 1: 【0723】 Users input work-related information using a terminal. Specifically, they input sales data, customer service history, shift information, etc., and store the data correctly according to the format. The entered data is temporarily stored on the terminal. 【0724】 Step 2: 【0725】 The terminal performs an integrity check on the input data. It verifies that the data format and required fields are entered correctly. Once the check is complete, it prepares to send the data to the server. If there are no integrity issues, the terminal is triggered to send the data to the server. 【0726】 Step 3: 【0727】 The server receives the data sent from the terminal and performs another integrity check. After confirming that there is no duplicate data or invalid entries, it stores the data in a secure database. The moment the data integrity is confirmed, the write operation to the database is executed. 【0728】 Step 4: 【0729】 When a user interacts with a customer, the device begins collecting voice and location data. This information is acquired using the built-in microphone and GPS module and transmitted to the server in real time. This step starts automatically each time a user action occurs. 【0730】 Step 5: 【0731】 The server processes the received audio and location data through an AI model to analyze the user's customer service attitude and the customer's emotions. Data processing includes converting audio to text and calculating distance and time to the customer using location information. The analysis results are immediately sent to the user's device as feedback. 【0732】 Step 6: 【0733】 The server analyzes accumulated user performance data and generates personalized training programs. This involves analyzing historical data to identify areas where specific skills or knowledge need strengthening. The training programs are then delivered to the user's device, and the user learns based on them. 【0734】 Step 7: 【0735】 The server optimizes work shifts using customer trend data and user skill profiles. Predictive algorithms are used in the calculations to ensure optimal staffing at all times. The adjustment results are sent to terminals, where users can check the new shift information. 【0736】 Step 8: 【0737】 The server analyzes customer data using advanced analytical algorithms to extract new customer insights and suggestions for service improvements. Based on these results, it generates prompt messages to notify the user, allowing them to use them as a reference for implementing their strategies. 【0738】 (Application Example 1) 【0739】 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". 【0740】 In modern brick-and-mortar retail operations, there is a demand for improved staff customer service skills and increased customer satisfaction. However, there is a lack of systems that effectively provide real-time feedback and personalized training programs, resulting in insufficient efficiency and optimization of operations. Furthermore, because methods for analyzing and immediately evaluating sales staff behavior and conversation data are underdeveloped, staff do not have the opportunity to immediately improve their customer service style. 【0741】 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. 【0742】 In this invention, the server includes means for checking the integrity of input data and storing it, means for analyzing real-time data during customer service and generating feedback, and means for analyzing and evaluating the salesperson's behavior and conversation data in real time and notifying them of areas for improvement. This enables immediate improvement of staff customer service skills in sales operations, leading to increased operational fluidity and customer satisfaction. 【0743】 An "information processing device" is an electronic device used by users to input sales data. 【0744】 A "data server" is a computer system that performs integrity checks and stores data sent by users. 【0745】 "Analysis means" refers to a function that analyzes real-time data collected during customer service and generates feedback. 【0746】 The "generation method" refers to a function that automatically creates training modules optimized for each sales staff member. 【0747】 An "optimization method" is an algorithm that automatically adjusts work schedules according to the demands of the work. 【0748】 "Analysis tools" refer to functions that analyze customer interaction data and provide insights useful for sales strategies. 【0749】 The "evaluation method" is a function that analyzes the seller's behavior and conversation data, evaluates it in real time, and notifies them of areas for improvement. 【0750】 The system for implementing this invention consists of a user, a terminal for sending and receiving data, and a server for processing. The user inputs daily work data using a terminal such as a smartphone or tablet. The terminal checks the integrity of the input data and transmits it to the data server via the internet. The server securely stores the data and operates analysis means as needed. 【0751】 The server's analysis method uses voice and location data to evaluate the user's customer service activities in real time and generates feedback using an AI model. The feedback is immediately delivered to the user's device, allowing the user to see specific areas for improvement. The server also generates individually optimized training modules based on the evaluation results and accumulated data. The generated training modules are delivered to the user's device, and a learning schedule is presented. 【0752】 To ensure operational fluidity, the server has a function to optimize work schedules based on business demand. It dynamically calculates shift assignments, taking into account customer demand data for each store and user capacity data. This result is also delivered to the user's terminal. Furthermore, the server analyzes customer interaction data to extract new insights, which are used to improve sales strategies. 【0753】 As a concrete example, a training program is generated for sales staff who provide highly-rated customer service during peak hours, allowing them to reflect on their actions. This program is presented to users as a set of skills applicable to similar situations, supporting their growth. For instance, prompts such as, "What feedback did you receive from your recent customer service experience? What actions will you take to improve?" are used. This leads to immediate improvement in customer service skills and increased customer satisfaction. 【0754】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0755】 Step 1: 【0756】 The user enters business data into a terminal. The terminal checks the integrity of the entered business data and sends it to the server. The entered data includes customer information, sales performance, customer service details, etc. Data whose integrity has been confirmed is used as the basis for the next processing step. 【0757】 Step 2: 【0758】 The server securely stores the received data and activates the analysis tools. The stored data includes sales data, customer service details, and customer feedback. The server uses the stored data to run an AI model and prepares to evaluate the user's customer service activities. 【0759】 Step 3: 【0760】 The server receives voice and location data transmitted from the terminal and performs real-time analysis. Voice data is converted to text using speech recognition software and analyzed by an AI model. Location data is used to calculate user movement patterns and dwell time. This results in output that evaluates the user's customer service style and customer reactions. 【0761】 Step 4: 【0762】 The server generates feedback on the user's customer service activities based on the analysis results from the AI ​​model. The feedback includes areas for improvement and points of good behavior, along with specific methods for improvement. The generated feedback is sent to the user's device as a push notification. 【0763】 Step 5: 【0764】 The server adds the user's evaluation results to the stored data and activates the means for generating educational programs. The server analyzes the evaluation data and assembles educational modules optimized for each individual user. This educational program is sent to the user's terminal, and the schedule is displayed. 【0765】 Step 6: 【0766】 The server uses optimization techniques to calculate a dynamic work schedule based on business demand. Flexible shift assignments are created based on business-related information and user capability data. The optimized shift information is then sent to the user's terminal. 【0767】 Step 7: 【0768】 The server activates analytical tools to extract new customer insights based on accumulated customer interaction data. It analyzes customer conversations and purchase history to generate information that can lead to improvements in sales strategies. The analysis results are provided to the user as strategic recommendations and notifications. 【0769】 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. 【0770】 The present invention provides an integrated platform for improving users' work efficiency and interpersonal skills in sales operations. This system includes an information processing device for user input of work data, a data server for data integrity checks and storage, an analysis means for analyzing real-time data during customer service, a generation means for generating optimized training modules, an optimization means for automatically assigning work schedules based on business needs, and an analysis means for analyzing customer interaction data. Furthermore, by incorporating an emotion engine that recognizes user emotions, it becomes possible to understand the user's emotional state and provide more accurate feedback and training content. 【0771】 Users input sales and shift information into a terminal at the start and end of their workday. This terminal sends the input data to a server. The server checks the received data and stores it in a database. This data is used as basic information for analyzing the user's work performance. 【0772】 During customer service, the user's device collects voice and motion data. The emotion engine analyzes this data to recognize the user's emotions in real time. The emotion recognition results are sent to a server and used as reference information to generate feedback. Based on the user's emotions, the analysis system determines appropriate feedback and notifies the user through the device. 【0773】 The generation method creates personalized educational modules based on the user's past performance data and emotion recognition results. These modules are tailored to the user's characteristics and challenges and are delivered via the device. This allows users to receive education suited to their emotional state, leading to expected skill improvement. 【0774】 Furthermore, the optimization mechanism dynamically assigns work schedules based on information obtained from multiple data sources. This optimizes each user's work style and enables efficient resource allocation. 【0775】 For example, if the emotion engine detects that a user is experiencing stress during customer interactions, the analysis means generates feedback that takes that emotion into account and provides an educational module on stress management. In this way, the system of the present invention helps to improve the user's work efficiency and satisfaction by utilizing emotion recognition. 【0776】 The following describes the processing flow. 【0777】 Step 1: 【0778】 At the start of their workday, users use a terminal to enter their login information and begin entering work data. The terminal formats this data and sends it to the server in real time. 【0779】 Step 2: 【0780】 The server receives business data sent from terminals and automatically checks its integrity. If the data is correct, it is saved to a database and managed as a daily work record. 【0781】 Step 3: 【0782】 When a user begins interacting with a customer, the device collects voice and gesture data in real time and sends it to the server. 【0783】 Step 4: 【0784】 The server uses an emotion engine to analyze the user's emotional state in real time from received voice and behavioral data. Based on the analysis results, it identifies the user's psychological state. 【0785】 Step 5: 【0786】 The analysis tool uses data provided by the emotion engine to generate feedback. This feedback, tailored to the user's emotional state, is delivered to the user via the device. 【0787】 Step 6: 【0788】 Users will be able to immediately work on improving their customer service methods based on the feedback they receive from their devices. 【0789】 Step 7: 【0790】 The server integrates and analyzes historical performance data and sentiment recognition results to generate user-optimized educational modules. These generated modules are then delivered to the user via their terminal. 【0791】 Step 8: 【0792】 The terminal manages information from the educational modules provided to the user and helps prepare them for application to the next task. 【0793】 Step 9: 【0794】 The server dynamically optimizes users' work schedules by utilizing information from multiple data sources. This optimization helps to facilitate smooth staffing in business operations. 【0795】 Step 10: 【0796】 The terminal receives optimized shift information sent from the server and displays it visually to the user. This allows the user to understand the new shift and perform their work efficiently. 【0797】 (Example 2) 【0798】 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". 【0799】 In sales operations, a system is needed that comprehensively utilizes diverse data to provide real-time feedback and personalized training in order to support the improvement of users' work efficiency and interpersonal skills. However, current systems are insufficient in recognizing users' emotional states and dynamically adjusting work schedules based on work data, limiting the optimization of the entire operation. This leads to increased burden on users and difficulties in improving customer satisfaction. 【0800】 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. 【0801】 In this invention, the server includes an information processing device for users to input work data, a data storage device for checking the integrity of the input data and storing it, and an analysis device for analyzing dynamic data during face-to-face customer service and generating responses. This makes it possible to recognize the user's emotional state in real time and provide a dynamically optimized work schedule. As a result, users can receive feedback and training based on their emotional state, which is expected to improve work efficiency and skills. 【0802】 An "information processing device" is a device used by users to input data related to their work. 【0803】 A "data storage device" is a system for verifying the integrity of received data and storing it. 【0804】 An "analysis device" is a device that analyzes real-time dynamic data obtained during customer service and generates feedback and responses. 【0805】 A "generation device" is a means of creating personalized educational programs for users. 【0806】 An "optimization device" is a means of automatically optimizing and allocating users' work time based on business needs. 【0807】 An "analytical device" is a means of analyzing customer and user interaction data and providing insights. 【0808】 An "emotion recognition device" is a means of recognizing a user's emotional state and providing appropriate feedback based on that information. 【0809】 This invention provides an integrated platform for improving the work efficiency and interpersonal skills of users in sales operations. This system mainly includes information processing devices, data storage servers, real-time analysis devices, generation devices, optimization functions, and emotion recognition functions. 【0810】 Information processing device 【0811】 The terminal is used by users to input work data at the start and end of their workday. Specifically, sales information and shift information are recorded on the terminal using the keyboard or touch input and treated as entry data. 【0812】 Data storage device 【0813】 The server checks the integrity of the data and stores it in the database using a secure communication protocol. The stored data serves as foundational information for evaluating the user's work performance. 【0814】 Real-time analysis device and emotion recognition 【0815】 During customer service, the terminal collects voice and motion data. The emotion recognition device analyzes this data to identify the user's emotional state in real time. Based on the recognition results, the server generates appropriate feedback and notifies the user. 【0816】 Provision of educational programs using generation equipment 【0817】 The server generates personalized training programs based on the user's past work data and current emotional state. This allows users to receive training optimized for them, leading to improved skills. 【0818】 Optimization function 【0819】 The server analyzes data obtained from various sources and optimizes the user's work schedule. This enables efficient allocation of work time and reduces the user's burden. 【0820】 For example, if a user exhibits high stress levels during customer service, the emotion recognition device detects this and generates feedback on relaxation techniques. Furthermore, a personalized stress management education program is provided on the device. This gives users the opportunity to quickly improve their stress management skills. By inputting a prompt sentence such as, "What relaxation techniques should be recommended if the user exhibits high stress levels?" into the AI ​​model, the optimal feedback content is created. 【0821】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0822】 Step 1: 【0823】 Users input sales and shift information using a terminal at the start of their workday. The entered data is sent to the database server by the terminal. The input here consists of numerical and text data, which the terminal sends to the server using HTTP communication. 【0824】 Step 2: 【0825】 The server checks the integrity of the received data. This integrity check verifies that sales information is numerical and that shift information is in the correct format. The server then saves the verified data to the database. This saving operation makes the data available for future analysis and reporting. 【0826】 Step 3: 【0827】 While the user is interacting with customers, the terminal collects voice and motion data. The terminal transmits this data to an emotion recognition device in real time. The input here is audio files and video frames, which the emotion recognition device analyzes to identify the user's emotional state. The identified emotion data is sent to a server to serve as the basis for generating feedback. 【0828】 Step 4: 【0829】 The server generates feedback based on the emotion recognition results. It inputs prompts into a generation AI model to construct appropriate feedback. The generated feedback is sent to the terminal and notified to the user. This feedback output can be a text message or voice instruction. 【0830】 Step 5: 【0831】 The server generates a personalized training program based on past work data and current emotional state. This program includes training content tailored to the user's characteristics. The generated program is delivered on the terminal to support the user's skill improvement. The program's output is displayed in the form of video tutorials and online learning materials. 【0832】 Step 6: 【0833】 The server executes an algorithm to optimize work schedules based on data collected from various sources. Using past work history and data on business demand, it dynamically adjusts user shifts to achieve efficient work allocation. The optimized schedule is displayed on the terminal, allowing users to check their schedules. 【0834】 (Application Example 2) 【0835】 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". 【0836】 Smooth communication with customers during on-site service delivery, and improving staff work efficiency and interpersonal skills, are crucial challenges in brick-and-mortar store management. Furthermore, it is essential for on-site staff to recognize their own emotional states and respond appropriately, thereby improving their skills, in order to enhance customer satisfaction. However, conventional systems have struggled to provide real-time emotional recognition, appropriate feedback, and training modules, making it difficult to efficiently address these challenges. 【0837】 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. 【0838】 In this invention, the server includes a data processing device for users to input work information, a data management device for checking the integrity of the input information and storing it, an analysis device for analyzing real-time information during service provision and generating feedback, and an educational support device for providing personalized training modules based on emotional states. This allows staff to grasp their own and the customer's emotional states in real time during interactions with customers, enabling appropriate and timely responses and skill development. Furthermore, by providing efficient work allocation, it is possible to improve the overall productivity of operations. 【0839】 A "data processing device" is a device that takes user input of work information and converts it into a format usable within the system. 【0840】 A "data management device" is a device used to verify the integrity of input data and to store it appropriately. 【0841】 An "analysis device" is a device that analyzes real-time data collected during service provision and generates appropriate feedback. 【0842】 A "configuration device" is a device that has the function of creating learning modules optimized for individual users. 【0843】 An "optimization scheduling device" is a device that automatically determines an efficient work schedule based on collected work-related information. 【0844】 An "analytical device" is a device that analyzes customer interaction data and provides useful insights. 【0845】 An "emotion recognition device" is a device that has the function of identifying the emotional state of users and customers in real time. 【0846】 An "educational support device" is a device that provides individualized training modules tailored to the user's emotional state. 【0847】 The system implementing this invention is an integrated platform including a data processing device, a data management device, an analysis device, a configuration device, an optimization placement device, an analysis device, an emotion recognition device, and an educational support device. The system is realized through the cooperation of the user's smart glasses or smartphone with a server. 【0848】 The server receives business information entered by the user, checks its integrity using a data processing device, and then stores it in storage. This data is fundamental information for analyzing the user's work efficiency. During real-time work, the user's terminal collects conversation and behavioral data with customers and sends it to the server. The server's analysis device uses this data to recognize customer emotions and generate appropriate feedback for the user. 【0849】 Furthermore, the emotion recognition device evaluates the user's emotional state in real time, and the analysis device provides insights based on that information. This allows the server to provide feedback tailored to each user's individual state. In addition, the system analyzes the user's past performance data and current emotional state to generate a customized learning module. This module is displayed on the user's smart glasses or smartphone to support individual skill improvement. 【0850】 The optimization placement device acquires business-related information from multiple data sources and efficiently adjusts work schedules. Furthermore, by analyzing this data and considering the emotional state of users, it is possible to improve the quality of work. 【0851】 As a concrete example, a florist wearing smart glasses can monitor their own and the customer's emotional state in real time during interactions, enabling them to provide more appropriate service. An example of a prompt to the generated AI model is, "Analyze the customer's facial expressions and vocal characteristics when they choose flowers, and determine their emotional state." This system allows users to improve work efficiency and customer satisfaction. 【0852】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0853】 Step 1: 【0854】 Users input work information into a terminal. Users use smart glasses or smartphones to input sales and shift information at the start of their workday. This data is sent to the server as input data and processed as initial data. 【0855】 Step 2: 【0856】 The server checks the integrity of the input data and stores it through the data management device. After receiving business information, the server performs an integrity check and stores the data in a database. This becomes the foundational data used for later analysis. 【0857】 Step 3: 【0858】 The device collects customer interaction data in real time. Using the device's camera and microphone, it records the customer's facial expressions and voice in real time. This serves as the input for customer data. 【0859】 Step 4: 【0860】 The server uses an analysis device to analyze the collected data and perform emotion recognition. The server inputs the customer's facial expressions and voice characteristics into emotion recognition software to determine their emotional state. This is the output of the information analysis. 【0861】 Step 5: 【0862】 The server generates feedback based on the analysis results and sends it to the terminal. The server generates appropriate feedback from the output of the analysis device and sends it to the user's terminal. This allows the user to optimize the interaction in real time. 【0863】 Step 6: 【0864】 The server generates customized learning modules using educational support devices. Based on historical work data and real-time sentiment data, the server creates an individualized training plan and sends it to the user's terminal. 【0865】 Step 7: 【0866】 The server dynamically allocates work schedules using an optimization placement device. The server references multiple data sources and considers work demands and emotional states to efficiently optimize user work time. 【0867】 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. 【0868】 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. 【0869】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0870】 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. 【0871】 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. 【0872】 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. 【0873】 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. 【0874】 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. 【0875】 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." 【0876】 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. 【0877】 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. 【0878】 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. 【0879】 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. 【0880】 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. 【0881】 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. 【0882】 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 this memory. 【0883】 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. 【0884】 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. 【0885】 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. 【0886】 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. 【0887】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. 【0888】 The following is further disclosed regarding the embodiments described above. 【0889】 (Claim 1) 【0890】 An information processing device for users to input business data, 【0891】 A data server checks the integrity of the input data and stores it, 【0892】 An analytical means that analyzes real-time data during customer service and generates feedback, 【0893】 A generation means for generating educational modules optimized for individual users, 【0894】 An optimization method that automatically assigns work schedules based on business demand, 【0895】 An analytical tool that provides insights by analyzing customer interaction data, 【0896】 A system that includes this. 【0897】 (Claim 2) 【0898】 The system according to claim 1, wherein the analysis means evaluates the user's activity using voice or motion data. 【0899】 (Claim 3) 【0900】 The system according to claim 1, wherein the optimization means dynamically adjusts the work schedule using work-related information obtained from multiple data sources. 【0901】 "Example 1" 【0902】 (Claim 1) 【0903】 A terminal device for the user to input information related to the operation, 【0904】 A storage means that checks the integrity of the input information and stores it, 【0905】 An analytical means that analyzes real-time information acquired during customer service and generates feedback, 【0906】 An educational tool that generates educational programs tailored to each user, 【0907】 An adjustment mechanism for dynamically allocating work time based on business requirements, 【0908】 Analytical tools that provide insights based on customer interactions and propose strategies, 【0909】 A system that includes this. 【0910】 (Claim 2) 【0911】 The system according to claim 1, wherein the analysis means evaluates the user's behavior using information about voice or location. 【0912】 (Claim 3) 【0913】 The system according to claim 1, wherein the adjustment means dynamically adjusts the work time using information about the work collected from multiple sources. 【0914】 "Application Example 1" 【0915】 (Claim 1) 【0916】 An information processing device for users to input business data, 【0917】 A data server checks the integrity of the input data and stores it, 【0918】 An analytical means that analyzes real-time data during customer service and generates feedback, 【0919】 A generation means for generating educational modules optimized for individual users, 【0920】 An optimization method that automatically assigns work schedules based on business demand, 【0921】 An analytical tool that provides insights by analyzing customer interaction data, 【0922】 An evaluation method that analyzes seller behavior and conversation data, evaluates it in real time, and notifies the user of areas for improvement, 【0923】 A system that includes this. 【0924】 (Claim 2) 【0925】 The system according to claim 1, wherein the analysis means evaluates the user's activity using voice or location data. 【0926】 (Claim 3) 【0927】 The system according to claim 1, wherein the optimization means dynamically adjusts the work schedule using work-related information obtained from multiple sources. 【0928】 "Example 2 of combining an emotion engine" 【0929】 (Claim 1) 【0930】 An information processing device for users to input work data, 【0931】 A data storage device that checks the integrity of the input data and stores it, 【0932】 An analysis device that analyzes dynamic data during face-to-face customer service and generates responses, 【0933】 A generation device that generates educational programs tailored to individual users, 【0934】 An optimization device that automatically allocates work time based on business demand, 【0935】 An analytical device that analyzes customer and user interaction data to provide insights, 【0936】 An emotion recognition device that recognizes the emotional state of the user, 【0937】 An integrated work efficiency improvement system that includes [specific features / features]. 【0938】 (Claim 2) 【0939】 The system according to claim 1, wherein the analysis device evaluates the user's activity status using voice information or physical movement information. 【0940】 (Claim 3) 【0941】 The system according to claim 1, wherein the optimization device dynamically adjusts the work time using work-related information obtained from multiple data sources. 【0942】 "Application example 2 when combining with an emotional engine" 【0943】 (Claim 1) 【0944】 A data processing device for users to input work information, 【0945】 A data management device that checks the integrity of the input information and stores it, 【0946】 An analysis device that analyzes real-time information during service provision and generates feedback, 【0947】 A configuration device that generates learning modules optimized for individual users, 【0948】 An optimization scheduling device that automatically allocates work time based on business demand, 【0949】 An analytical device that analyzes customer interaction data to provide insights, 【0950】 An emotion recognition device that recognizes the emotional state of users and customers and provides appropriate feedback in real time, 【0951】 An educational support device that provides personalized training modules based on the user's emotional state, 【0952】 A system that includes this. 【0953】 (Claim 2) 【0954】 The system according to claim 1, wherein the analysis device evaluates the user's activity using voice and motion data and determines the emotional state in real time. 【0955】 (Claim 3) 【0956】 The system according to claim 1, wherein the optimization placement device dynamically adjusts work time using work-related information acquired from multiple information sources, and provides efficient work placement that takes into account the emotional state of the users. [Explanation of symbols] 【0957】 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] An information processing device for users to input business data, A data server checks the integrity of the input data and stores it, An analytical means that analyzes real-time data during customer service and generates feedback, A generation means for generating educational modules optimized for individual users, An optimization method that automatically assigns work schedules based on business demand, An analytical tool that provides insights by analyzing customer interaction data, A system that includes this. [Claim 2] The system according to claim 1, wherein the analysis means evaluates the user's activity using voice or motion data. [Claim 3] The system according to claim 1, wherein the optimization means dynamically adjusts the work schedule using work-related information obtained from multiple data sources.

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