system

Abstract

We provide the system. [Solution] A means for filtering information on construction companies based on the entered construction order conditions, A method for selecting the most suitable construction company from a filtered list of construction companies based on their track record and operational status, A means of providing a user interface that allows users to review order details and make modifications as needed, A means of generating purchase orders and placing orders with selected construction companies, A system that includes a means of evaluating and updating the construction company's historical data after the completion of construction work.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In the construction order business, it takes time and is not efficient to select a construction company considering a large number of conditions. Also, if the selection of the construction company is inappropriate, it may impose an excessive burden on subcontractors and may lead to construction delays and cost increases. Furthermore, long-distance movement and emergency response are difficult, and the risk of accidents is also likely to occur. It is required to solve these problems. 【Means for Solving the Problems】 【0005】 This invention provides a system that filters information on construction companies based on input construction order conditions and selects the most suitable construction company based on its construction track record and operational status. The system allows users to review and modify order details through a user interface, generate an order form, and place the order with the selected construction company. Furthermore, after construction is completed, the system evaluates and updates the construction company's historical data, calculates the company's travel distance to adjust its workload, and enables real-time tracking of operational status in emergencies for rapid response. In this way, the system aims to improve the efficiency and safety of construction ordering operations. 【0006】 "Construction order conditions" refer to the conditions considered when carrying out construction work, including information such as the type of work, scale, location, and required skills and qualifications. 【0007】 A "construction company" refers to a company or organization that possesses the ability and qualifications to carry out specific construction work and undertakes the execution of such work. 【0008】 "Filtering" refers to the process of selecting data or information based on specific conditions and extracting only the necessary items. 【0009】 "Construction track record" refers to records of construction projects that a construction company has carried out in the past, as well as data showing their performance. 【0010】 "Operating status" refers to information indicating the current and future workload and the state of available resources. 【0011】 A "user interface" refers to the means of providing screen displays and operating methods for users to interact with a computer system. 【0012】 A "purchase order" is an official document created to order specific services or goods, and it forms part of a contract. 【0013】 "Historical data" refers to records of a construction company's past work experience and its evaluation. 【0014】 "Moving distance" refers to the physical distance required for a construction company to reach the construction site. 【0015】 "Emergency" refers to a situation that requires sudden and rapid response different from normal operations. 【Brief Explanation of Drawings】 【0016】 [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] [[ID=四十一]] [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] ​It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined. 【Embodiments for Carrying Out the Invention】 【0017】 Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0018】 First, the terms used in the following description will be explained. 【0019】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc. 【0020】 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. 【0021】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc. 【0022】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0023】 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." 【0024】 [First Embodiment] 【0025】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0026】 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. 【0027】 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). 【0028】 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. 【0029】 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. 【0030】 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. 【0031】 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. 【0032】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0033】 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. 【0034】 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. 【0035】 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. 【0036】 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". 【0037】 This invention relates to a system for efficiently and effectively carrying out construction ordering operations. This system improves operational efficiency by automating everything from selecting construction companies and determining the optimal contractor to evaluating the completed work. 【0038】 The system's main operation unfolds as follows: First, the user inputs the construction order conditions via a terminal. These conditions include the type and scale of the construction, as well as the required qualifications and skills. Once the terminal receives this information, the server processes it and retrieves information about construction companies from the database. The construction company data includes past construction performance, current operational status, and types of construction they specialize in. 【0039】 The server analyzes this data and selects the construction company that best fits the project order conditions. One of the evaluation criteria is the similarity of past project experience. For example, priority is given to companies that have successfully completed similar projects in the past. The server also takes into account operational status and travel distance to select a construction company that can allocate resources efficiently. 【0040】 The selected construction company information is presented to the user via a terminal. The user can review the information and modify the order details as needed. Based on this information, the server automatically generates an order form and sends an order instruction to the designated construction company. 【0041】 Once construction is complete, the server collects feedback data from the construction company, evaluates the quality of the work and the company's response, and updates the database. This evaluation process is used to improve the accuracy of future procurement decisions and the selection of construction companies. 【0042】 For example, in a building renovation project requiring advanced equipment installation skills, a construction company with experience in similar projects is selected, and priority is given to construction teams that can be relocated from nearby existing sites. This shortens the construction period and reduces the risk of traffic accidents. In this way, the system of the present invention automates various processes related to ordering construction work, enabling precise decision-making. 【0043】 The following describes the processing flow. 【0044】 Step 1: 【0045】 The user enters the construction order requirements into the terminal. This includes information such as the type of construction, scale, required skills, and location. 【0046】 Step 2: 【0047】 The terminal sends the order conditions entered by the user to the server. The order conditions are converted into a format compatible with the server's processing. 【0048】 Step 3: 【0049】 Based on the order conditions received by the server, it retrieves information on all construction companies from the database. This information includes construction track record, skill sets, operational status, and qualifications. 【0050】 Step 4: 【0051】 Based on the construction company information acquired by the server, the system filters out construction companies that match the order conditions. Filtering criteria include matching types of construction work and skill sets. 【0052】 Step 5: 【0053】 The server then ranks and selects the most suitable construction company from the filtered list based on their track record and evaluation scores. 【0054】 Step 6: 【0055】 The server calculates the operational status and travel distance of the selected construction company and creates the optimal ordering plan. 【0056】 Step 7: 【0057】 The terminal presents the selection results and order plan received from the server to the user and requests their confirmation. 【0058】 Step 8: 【0059】 The user reviews the presented order plan and sends any requested modifications to the server via their device. 【0060】 Step 9: 【0061】 The server receives user confirmation and modifications, generates the final purchase order, and places the order with the designated construction company. 【0062】 Step 10: 【0063】 After the construction is completed, the server receives feedback data from the construction company, evaluates the construction, and updates the database. 【0064】 (Example 1) 【0065】 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." 【0066】 In construction procurement, there is a need to automate and optimize the selection of appropriate construction companies, efficient resource allocation, and post-completion evaluation. The challenge lies in improving efficiency, accuracy, and time efficiency through these processes. 【0067】 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. 【0068】 In this invention, the server includes means for filtering group information based on planning conditions, means for selecting the most suitable group from the filtered groups based on work history and work status, and means for supporting future planning decisions based on evaluation results. This streamlines the construction ordering process and enables a highly accurate selection and evaluation process for construction companies. 【0069】 "Planning conditions" refer to a set of basic requirements set when ordering construction work, such as the type and scale of the work, and the necessary qualifications and skills. 【0070】 "Organizational information" refers to data including past construction achievements, current operational status, and types of construction work that the construction company specializes in. 【0071】 "Filtering" is the process of selecting and applying data based on specific criteria. 【0072】 "Work history" refers to records of construction work previously carried out by a construction company, as well as the experience gained from its successes and failures. 【0073】 "Work status" refers to information indicating the projects currently underway by the construction company and their future operational readiness. 【0074】 "Configuration" refers to a part of a system that provides an interface and settings for users to review order details and make modifications as needed. 【0075】 "Evaluation results" refer to the feedback received from the construction company after the completion of their work, and the results of the analysis based on that feedback. 【0076】 "Means to support future planning decisions" refers to a function that supports appropriate decisions when placing new construction orders, based on past evaluation results. 【0077】 "Load balancing" is the process of optimizing the use of labor by taking into account the distance traveled and the operational status of the group. 【0078】 This invention constitutes a system for efficiently automating construction order ordering operations. The system is primarily operated by a server, terminals, and users. 【0079】 First, the user inputs planning conditions such as the type and scale of the construction work, and the necessary qualifications and skills, through a terminal. This forms the basic data for the work. The terminal receives this information and sends it to the server. 【0080】 The server retrieves information on construction companies from the database based on the planning conditions and performs filtering. This filtering process involves selecting data based on specific criteria to narrow down the most suitable companies. Specifically, it considers factors such as the company's work history, work status, and current operational status. The software used here is for performing data processing and analysis. A modern option is often to use a cloud-based data analytics platform. 【0081】 The selected organization information is presented to the user via a terminal. The user can review this information and modify the plan details as needed through an interface. This allows for fine-tuning of the order details. 【0082】 As a concrete example of the selection process, consider the case of "selecting a construction company with the technology to handle advanced weather conditions for the exterior wall construction of a high-rise building." In this case, a company with a track record of working under similar weather conditions in the past would be selected, and the optimal construction period would be presented. 【0083】 Furthermore, an example of a prompt message that utilizes a generative AI model could be a request such as, "List construction companies specializing in soundproofing for interior construction of urban hotels, and prioritize them based on their past performance." 【0084】 In this form, the present invention streamlines various judgments and procedures associated with ordering construction work and supports highly accurate decision-making. 【0085】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0086】 Step 1: 【0087】 The user enters the construction order conditions via a terminal. This input includes the type and scale of the construction, as well as the required qualifications and skills. This information is received by the terminal as planning conditions. The entered data is then prepared to be sent directly to the server. 【0088】 Step 2: 【0089】 The terminal sends the received planning conditions to the server. The server receives this data and starts the process of retrieving information about construction companies from the database. Specifically, it executes a database query and extracts information about organizations that match the conditions. As a result, a list of relevant construction companies is output. 【0090】 Step 3: 【0091】 The server filters the acquired organization information. Here, it performs analysis to select the most suitable organization based on work history and work status. Data processing includes checking past construction performance and comparing it with current operational status. The best candidates are listed and a prioritized list is output. 【0092】 Step 4: 【0093】 The terminal displays a list of candidates sent from the server to the user. The user can review the information and modify the order details as needed. Editing is possible directly on the interface, and the changes are immediately reflected on the server. 【0094】 Step 5: 【0095】 The server automatically generates a purchase order based on the information confirmed and corrected by the user. This process creates a document containing details of the work and payment terms. The generated purchase order is sent as an electronic message to the selected construction company. 【0096】 Step 6: 【0097】 After the construction is completed, the server collects feedback data from the construction company. This data includes the quality of the work, the construction period, and the construction company's response. The server analyzes this information and updates the database. This generates new evaluation information that can be used when selecting construction companies in the future. 【0098】 (Application Example 1) 【0099】 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." 【0100】 In the modern construction industry, the process of ordering construction work still relies heavily on manual work, and there are problems with the selection and ordering of contractors being carried out in an ineffective manner. In addition, there is a need for efficient resource allocation that takes into account information such as the travel distance and schedules of contractors. However, the lack of systems that integrate this information in real time and automatically recommend the most suitable contractors has prevented the achievement of operational efficiency. 【0101】 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. 【0102】 In this invention, the server includes means for filtering contractor information based on input construction order conditions, means for selecting the most suitable contractor from the filtered contractors based on construction history and usage status, and means for providing a human-machine interface that allows for confirmation of order information and modification as needed. This makes it possible to select contractors in real time and place construction orders efficiently. 【0103】 "Construction order conditions" refer to information that serves as a basis for selecting a construction contractor, including the type and scale of the construction work, and the necessary qualifications and skills. 【0104】 A "construction contractor" is a company or organization that actually undertakes and carries out construction work. 【0105】 "Filtering" is the process of narrowing down data based on specific conditions and selecting only the necessary information. 【0106】 "Construction history" refers to data that records the types and number of construction projects carried out in the past, as well as the degree of success. 【0107】 "Usage status" refers to operational information such as the current progress of tasks and the availability of schedules. 【0108】 The "human-machine interface" refers to the interface through which a user interacts with a system, and usually refers to a graphical user interface (GUI). 【0109】 A "procurement order" is a document used to formally request a contractor to perform a specific construction project. 【0110】 "Geographic information" refers to information used to identify the location and coordinates of a construction site. 【0111】 "Schedule" refers to the schedule information for tasks and construction work that the contractor plans to carry out in the future. 【0112】 To implement this system, a program is needed that allows users to input construction order conditions on their terminals and send that information to a server. Mobile devices such as smartphones can be used as terminals, and a basic UI (user interface) will be implemented. Through this UI, users will be able to input information such as the type and scale of the construction work, and the required skills. 【0113】 The server is built using server-side frameworks such as Node.js or Python and processes the input data. Based on the received construction order conditions, the server extracts data on construction companies from a database such as PostgreSQL and uses algorithms to filter and select them. Parameters such as construction history and usage status are used in this selection process. The geographical information and schedules of the construction companies are also taken into consideration to make the optimal selection. 【0114】 The selection results are again displayed on the terminal's UI for the user to review. The user can modify this information as needed, generate the final order form, and send it to the contractor. 【0115】 As a concrete example, when ordering construction work that requires advanced technology for a certain project, the user might say, "I would like renovation work done. Area: 300m²." 2The prompt reads, "Please limit the timeframe to two months or less. Please recommend a contractor with similar experience in the past." In response to this input, the server selects the contractor that best fits the criteria, enabling efficient project ordering. 【0116】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0117】 Step 1: 【0118】 The user enters the construction order conditions (type of construction, scale, required skills, etc.) using a terminal. The entered information is temporarily stored on the terminal and prepared for transmission to the server. 【0119】 Step 2: 【0120】 The terminal sends the entered construction order conditions to the server. The server receives the data and analyzes the information. Specifically, it parses the information sent in text format and extracts the elements necessary for filtering. 【0121】 Step 3: 【0122】 The server retrieves contractor data from the database based on the extracted elements. The database query used here is built with PostgreSQL and extracts contractors that match conditions such as the type of construction and usage status. 【0123】 Step 4: 【0124】 The server filters the acquired contractor data and executes an algorithm to select the best candidate based on construction history and usage status. It performs data calculations that include similarity of historical data, current operational status, and geographical information to narrow down the options. 【0125】 Step 5: 【0126】 The server sends information about the selected contractor to the terminal. The terminal displays this information and presents it to the user. The user can review the proposed contractors and modify the information if necessary. 【0127】 Step 6: 【0128】 Once the user confirms their selection, the terminal sends that information to the server, which automatically generates the final order. The server then creates the order and sends it to the designated contractor. 【0129】 Step 7: 【0130】 After construction is completed, the server collects feedback data from the contractor and evaluates the results of the construction and the contractor's response. This evaluation data is stored in a database and used in the contractor selection process for future projects. 【0131】 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. 【0132】 This invention relates to a system that recognizes user emotions and utilizes that information to optimize construction ordering operations. This system is based on the construction company selection process and combines it with an emotion engine that recognizes emotions during user operation to optimize the user interface and improve operational efficiency. 【0133】 Specifically, the system works as follows: First, the user inputs the construction order conditions via a terminal. At this point, the emotion engine analyzes the user's emotional state from their facial expressions and voice. This information is used to set the conditions for construction orders and to confirm the selection results. 【0134】 The terminal sends emotional information and construction order conditions to the server. Based on this data, the server uses a database of construction companies to select the most suitable construction company. By taking emotional information into consideration, for example, if the user is feeling stressed, the burden can be reduced by adding a more user-friendly interface or a detailed explanation of the selection reasoning. 【0135】 Information about the selected construction company is presented to the user via a terminal, and the interface dynamically adjusts according to the user's emotional state. For example, if the user shows interest or confidence, standard information is displayed, but if anxiety or stress is detected, additional support information or simplified options are provided. 【0136】 Ultimately, even in the process where the server generates purchase orders and places them with selected construction companies, feedback based on sentiment analysis is obtained and used to improve the ordering process in the future. 【0137】 For example, if a user feels anxious when using the system for the first time, the emotion engine recognizes this and provides guided instructions through the interface, allowing the user to proceed with the ordering process with confidence. In this way, the present invention improves the efficiency of construction ordering operations and enhances the user experience by incorporating the user's emotional information. 【0138】 The following describes the processing flow. 【0139】 Step 1: 【0140】 The user enters the construction order conditions via a terminal. These conditions include the type of construction, scale, required skills, and location. 【0141】 Step 2: 【0142】 The device activates an emotion engine that analyzes the user's emotions in real time from their facial expressions and voice to identify the user's emotional state. 【0143】 Step 3: 【0144】 The terminal sends the entered order conditions and sentiment information to the server. Sentiment information includes the user's current sentiment state and the corresponding recommended actions. 【0145】 Step 4: 【0146】 The server filters suitable construction companies from its database based on the order conditions received. During this process, it considers the user's emotional state and adjusts the selection process and information provision as needed. 【0147】 Step 5: 【0148】 The server selects the most suitable construction company from a filtered list of companies based on their track record and operational status, and adds user-generated content that responds to emotional information. 【0149】 Step 6: 【0150】 The device presents the selection results to the user. Depending on the user's emotional state, additional information and support options may be available. 【0151】 Step 7: 【0152】 The system reviews the information presented by the user and determines if there are any problems with the order. The user's emotions are then analyzed again and fed back into the interface. 【0153】 Step 8: 【0154】 If necessary, the user sends a correction request to the server via their device. 【0155】 Step 9: 【0156】 The server generates the final purchase order and places it with the selected construction company. Sentimental information is recorded as a result and used to improve the process in the future. 【0157】 Step 10: 【0158】 After the construction is completed, the server evaluates the feedback from the construction company and updates the database along with the user sentiment analysis results. 【0159】 (Example 2) 【0160】 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." 【0161】 In construction ordering operations, the challenge is to streamline the ordering process and improve the user experience by simplifying procedures and information processing that tend to cause stress for users, and by automating appropriate responses that respond to user emotions. In particular, conventional systems do not take user emotions into consideration, which leads to a problem of user dissatisfaction and stress accumulating. 【0162】 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. 【0163】 In this invention, the server includes emotion recognition means for analyzing the user's facial expressions and voice to identify their emotional state, means for providing a user interface that is dynamically adjusted according to the identified emotional state, and means for placing orders with selected construction organizations and evaluating and updating historical data after the completion of construction. This makes it possible to efficiently utilize the user's emotional information, select an appropriate construction company, and provide a user interface that reduces the burden on the user. 【0164】 "Construction order conditions" refer to the detailed requirements specified by the user when requesting construction work, and include information such as the type of work, desired schedule, budget, and location. 【0165】 A "construction company" refers to a business contracted to carry out construction work, and is a corporation or individual selected according to the specific details of the construction work. 【0166】 "Emotion recognition means" refers to technology or devices that can identify a user's emotional state by analyzing their facial expressions and voice. 【0167】 "User interface" refers to the operating environment in which the user directly interacts, including screen displays and operating methods for exchanging information between the system and the user. 【0168】 A "purchase order" is a document that formally records the details of a construction request from the user to the construction company, and clearly outlines the contract terms. 【0169】 "Historical data" refers to past performance and evaluation information of construction companies, and is used for selecting and evaluating construction companies. 【0170】 This invention is a system for improving user experience and the efficiency of construction ordering operations. This system utilizes emotion recognition technology and includes a process for selecting the most suitable construction company based on user input information. 【0171】 When a user uses the system, they first input construction order conditions through a terminal. The terminal sends the input conditions to the server, while simultaneously using a built-in emotion engine to capture the user's facial expressions and voice in real time and perform emotion recognition. For specific emotion recognition, a camera and microphone are used, along with image processing and voice analysis software such as OpenCV and TENSORFLOW®. 【0172】 The server integrates user input data and emotional information to filter information on construction companies and select the most suitable one. The selection process considers the construction company's historical data and operational status. Furthermore, it dynamically adjusts the user interface based on emotional information to provide appropriate information tailored to the user's psychological state. 【0173】 As a concrete example, if a user experiencing the system for the first time feels anxious, the system uses an emotion engine to recognize this anxiety and displays guided instructions through the interface. This allows the user to proceed with the process with confidence. 【0174】 An example of a prompt message to the system would be: "Please provide guidelines for selecting the most suitable construction company based on construction order conditions and user sentiment information, and designing an interface to propose it to the user." This prompt message is used as an instruction to the generating AI model. 【0175】 The system of the present invention considers user emotions as an important factor and provides appropriate feedback, thereby streamlining the ordering process and improving user satisfaction. 【0176】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0177】 Step 1: 【0178】 The user enters the construction order conditions using a terminal. Specifically, they enter information such as the type of construction, desired dates, budget, and location into a form displayed on the screen. The entered data is temporarily stored on the terminal and used for subsequent processing. 【0179】 Step 2: 【0180】 The terminal uses an emotion engine to capture the user's facial expressions and voice based on the order conditions entered by the user. Image data captured by the camera and audio data recorded by the microphone are passed to analysis software. OpenCV and TensorFlow are used to identify the user's emotions from this data. The input is image data and audio data, and the output is an emotional state (e.g., reassured, anxious, stressed). 【0181】 Step 3: 【0182】 The terminal collects the user's order conditions and sentiment information and sends it to the server. A secure protocol (e.g., HTTPS) is used for transmission. In this process, the input is the user's order conditions and sentiment information, and the output is the integrated data sent to the server. 【0183】 Step 4: 【0184】 The server analyzes the transmitted data and compares it against a database of construction companies. A filtering algorithm is then used to select candidate construction companies that meet the specified criteria. The input is the integrated data, and the output is a list of construction companies that meet the criteria. 【0185】 Step 5: 【0186】 The server dynamically adjusts the user interface based on the selection results, taking into account the user's emotional information. For example, if the user indicates anxiety, it generates an interface that includes detailed explanations and guide messages. The input is a list of construction companies and emotional information, and the output is the adjusted user interface. 【0187】 Step 6: 【0188】 The server ultimately generates the purchase order and places the order with the selected construction company. The purchase order is a formal document containing the details of the work, conditions, and information about the construction company, and is sent electronically to the construction company. The input is the construction company's information and the order conditions, and the output is the generated purchase order. 【0189】 (Application Example 2) 【0190】 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". 【0191】 In the process of ordering work, a system is needed that appropriately reflects the emotional state of users and improves their experience. Especially in fields where emotions are a crucial element, such as caregiving, it is essential to select the most suitable service provider while considering the user's feelings, ensuring that users can proceed with the process comfortably. Furthermore, efficient means are needed to reduce the anxiety and stress experienced by users and enable smoother work execution. 【0192】 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. 【0193】 In this invention, the server includes means for filtering information on performers based on input work order conditions, means for selecting the most suitable performer from the filtered performers based on work performance and operational status, and means for recognizing the user's emotions and applying dynamic adjustments based on that information to the user connection surface. This enables a work order process that reflects the user's emotional state, thereby improving the user experience. 【0194】 "Work order conditions" refer to the specific work content and conditions required of the person performing the work. 【0195】 "Implementer" refers to the individual or group that actually carries out the work, and is the entity that receives the order and performs the work. 【0196】 The "user interface" refers to the interface through which users interact with the system, and is a connection point designed to enhance usability. 【0197】 "Recognizing emotions" refers to the process of detecting and analyzing a user's emotional state from their facial expressions and voice. 【0198】 "Dynamic adjustment" refers to the automatic modification of a system's interface and behavior in response to conditions such as the user's emotional state. 【0199】 "Post-performance history documentation" refers to information such as the performer's past work performance and evaluations, which is recorded after the work is completed. 【0200】 In this invention, the user's terminal accepts the input work order conditions, filters the information of the person performing the work, and selects the most suitable person. In this process, the terminal analyzes the user's facial expressions and voice, and recognizes the user's emotional state using an emotion engine. The emotional information is transmitted to a server, which applies dynamic adjustments to the user connection surface according to the emotion. This reduces the user's anxiety and stress, providing a comfortable user experience. 【0201】 The server selects the most suitable service provider for the user, taking into account their work history and operational status. After selection, the order details are presented to the user via the user connection, and the details can be modified as needed. Furthermore, after the work is completed, the service provider's performance history is evaluated and used for future use. 【0202】 This system utilizes standard webcams and smartphones, and the emotion recognition algorithm employs existing image processing libraries such as OpenCV. Furthermore, suggestions based on emotion information are generated using a generative AI model on the server. 【0203】 As a concrete example, the system recognizes in real time the anxiety that residents show through their facial expressions within a nursing home and makes suggestions to the residents, such as, "How about this music when you want to relax?" Examples of prompts to be input into the generating AI model include, "What should be said to an elderly person whose facial expression indicates anxiety?" 【0204】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0205】 Step 1: 【0206】 The terminal receives the work order conditions from the user. The data entered here (e.g., work details, desired dates, budget, etc.) is prepared to be sent to the server for subsequent processes. 【0207】 Step 2: 【0208】 The device uses its camera to collect image and audio data from the user. This data is analyzed by an emotion engine to identify the user's emotional state. This process uses image processing libraries such as OpenCV to analyze the data, and emotional information is obtained as output. 【0209】 Step 3: 【0210】 The server filters the information of the performers based on the sentiment information and work order conditions received. Specifically, it extracts performers from the database who meet conditions such as work performance and operational status, and obtains that data as the filtered result. 【0211】 Step 4: 【0212】 The server selects the most suitable implementer from the filtering results. This process also considers an interface designed to reduce user stress by utilizing emotional information. Based on the selection results, detailed information about the chosen implementer is generated and output. 【0213】 Step 5: 【0214】 The server uses a generative AI model to create suggestions tailored to the user's emotional state. The system generates prompts, which are then input into the generative AI model to obtain interface information, including appropriate suggestions and guidance. 【0215】 Step 6: 【0216】 The terminal displays the obtained implementer information and proposed interface information to the user. The user reviews the order details based on this information and makes any necessary corrections. Finally, the finalized order information is sent to the server. 【0217】 Step 7: 【0218】 The server generates a purchase order and places it with the selected contractor. Simultaneously, after the work is completed, it updates the contractor's performance history to keep the system data up-to-date. 【0219】 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. 【0220】 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. 【0221】 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. 【0222】 [Second Embodiment] 【0223】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0224】 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. 【0225】 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). 【0226】 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. 【0227】 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. 【0228】 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). 【0229】 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. 【0230】 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. 【0231】 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. 【0232】 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. 【0233】 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. 【0234】 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". 【0235】 This invention relates to a system for efficiently and effectively carrying out construction ordering operations. This system improves operational efficiency by automating everything from selecting construction companies and determining the optimal contractor to evaluating the completed work. 【0236】 The system's main operation unfolds as follows: First, the user inputs the construction order conditions via a terminal. These conditions include the type and scale of the construction, as well as the required qualifications and skills. Once the terminal receives this information, the server processes it and retrieves information about construction companies from the database. The construction company data includes past construction performance, current operational status, and types of construction they specialize in. 【0237】 The server analyzes this data and selects the construction company that best fits the project order conditions. One of the evaluation criteria is the similarity of past project experience. For example, priority is given to companies that have successfully completed similar projects in the past. The server also takes into account operational status and travel distance to select a construction company that can allocate resources efficiently. 【0238】 The selected construction company information is presented to the user via a terminal. The user can review the information and modify the order details as needed. Based on this information, the server automatically generates an order form and sends an order instruction to the designated construction company. 【0239】 Once construction is complete, the server collects feedback data from the construction company, evaluates the quality of the work and the company's response, and updates the database. This evaluation process is used to improve the accuracy of future procurement decisions and the selection of construction companies. 【0240】 For example, in a building renovation project requiring advanced equipment installation skills, a construction company with experience in similar projects is selected, and priority is given to construction teams that can be relocated from nearby existing sites. This shortens the construction period and reduces the risk of traffic accidents. In this way, the system of the present invention automates various processes related to ordering construction work, enabling precise decision-making. 【0241】 The following describes the processing flow. 【0242】 Step 1: 【0243】 The user enters the construction order requirements into the terminal. This includes information such as the type of construction, scale, required skills, and location. 【0244】 Step 2: 【0245】 The terminal sends the order conditions entered by the user to the server. The order conditions are converted into a format compatible with the server's processing. 【0246】 Step 3: 【0247】 Based on the order conditions received by the server, it retrieves information on all construction companies from the database. This information includes construction track record, skill sets, operational status, and qualifications. 【0248】 Step 4: 【0249】 Based on the construction company information acquired by the server, the system filters out construction companies that match the order conditions. Filtering criteria include matching types of construction work and skill sets. 【0250】 Step 5: 【0251】 The server then ranks and selects the most suitable construction company from the filtered list based on their track record and evaluation scores. 【0252】 Step 6: 【0253】 The server calculates the operational status and travel distance of the selected construction company and creates the optimal ordering plan. 【0254】 Step 7: 【0255】 The terminal presents the selection results and order plan received from the server to the user and requests their confirmation. 【0256】 Step 8: 【0257】 The user reviews the presented order plan and sends any requested modifications to the server via their device. 【0258】 Step 9: 【0259】 The server receives user confirmation and modifications, generates the final purchase order, and places the order with the designated construction company. 【0260】 Step 10: 【0261】 After the construction is completed, the server receives feedback data from the construction company, evaluates the construction, and updates the database. 【0262】 (Example 1) 【0263】 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." 【0264】 In construction procurement, there is a need to automate and optimize the selection of appropriate construction companies, efficient resource allocation, and post-completion evaluation. The challenge lies in improving efficiency, accuracy, and time efficiency through these processes. 【0265】 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. 【0266】 In this invention, the server includes means for filtering group information based on planning conditions, means for selecting the most suitable group from the filtered groups based on work history and work status, and means for supporting future planning decisions based on evaluation results. This streamlines the construction ordering process and enables a highly accurate selection and evaluation process for construction companies. 【0267】 "Planning conditions" refer to a set of basic requirements set when ordering construction work, such as the type and scale of the work, and the necessary qualifications and skills. 【0268】 "Organizational information" refers to data including past construction achievements, current operational status, and types of construction work that the construction company specializes in. 【0269】 "Filtering" is the process of selecting and applying data based on specific criteria. 【0270】 "Work history" refers to records of construction work previously carried out by a construction company, as well as the experience gained from its successes and failures. 【0271】 "Work status" refers to information indicating the projects currently underway by the construction company and their future operational readiness. 【0272】 "Configuration" refers to a part of a system that provides an interface and settings for users to review order details and make modifications as needed. 【0273】 "Evaluation results" refer to the feedback received from the construction company after the completion of their work, and the results of the analysis based on that feedback. 【0274】 "Means to support future planning decisions" refers to a function that supports appropriate decisions when placing new construction orders, based on past evaluation results. 【0275】 "Load balancing" is the process of optimizing the use of labor by taking into account the distance traveled and the operational status of the group. 【0276】 This invention constitutes a system for efficiently automating construction order ordering operations. The system is primarily operated by a server, terminals, and users. 【0277】 First, the user inputs planning conditions such as the type and scale of the construction work, and the necessary qualifications and skills, through a terminal. This forms the basic data for the work. The terminal receives this information and sends it to the server. 【0278】 The server retrieves information on construction companies from the database based on the planning conditions and performs filtering. This filtering process involves selecting data based on specific criteria to narrow down the most suitable companies. Specifically, it considers factors such as the company's work history, work status, and current operational status. The software used here is for performing data processing and analysis. A modern option is often to use a cloud-based data analytics platform. 【0279】 The selected organization information is presented to the user through the terminal. The user can operate through an interface that can view this information and modify the plan content as needed. This makes it possible to adjust the details of the order content. 【0280】 As a specific example of the selection process, consider, for example, the case of "selecting a construction company with technology capable of handling advanced climate conditions for the exterior wall construction of a high-rise building". In this case, a company with past work performance under similar weather conditions will be selected, and an optimal construction period will be presented. 【0281】 Also, as an example of a prompt sentence utilizing a generative AI model, it is conceivable to input a requirement such as "listing construction companies specialized in soundproofing construction in the interior decoration work of an urban hotel and ranking them based on past performance". 【0282】 In this manner, the present invention streamlines various judgments and procedures associated with construction orders and supports high-precision decision-making. 【0283】 The flow of the specific process in Example 1 will be described using FIG. 11. 【0284】 Step 1: 【0285】 The user inputs the order conditions for the construction through the terminal. The input includes the type of construction, scale, required qualifications and skills. This information is received on the terminal as planning conditions. The input data is prepared to be transmitted to the server as it is. 【0286】 Step 2: 【0287】 The terminal sends the received planning conditions to the server. The server receives this data and starts the process of retrieving information about construction companies from the database. Specifically, it executes a database query and extracts information about organizations that match the conditions. As a result, a list of relevant construction companies is output. 【0288】 Step 3: 【0289】 The server filters the acquired organization information. Here, it performs analysis to select the most suitable organization based on work history and work status. Data processing includes checking past construction performance and comparing it with current operational status. The best candidates are listed and a prioritized list is output. 【0290】 Step 4: 【0291】 The terminal displays a list of candidates sent from the server to the user. The user can review the information and modify the order details as needed. Editing is possible directly on the interface, and the changes are immediately reflected on the server. 【0292】 Step 5: 【0293】 The server automatically generates a purchase order based on the information confirmed and corrected by the user. This process creates a document containing details of the work and payment terms. The generated purchase order is sent as an electronic message to the selected construction company. 【0294】 Step 6: 【0295】 After the construction is completed, the server collects feedback data from the construction company. This data includes the quality of the work, the construction period, and the construction company's response. The server analyzes this information and updates the database. This generates new evaluation information that can be used when selecting construction companies in the future. 【0296】 (Application Example 1) 【0297】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0298】 In the modern construction industry, the process of ordering construction work still relies heavily on manual work, and there are problems with the selection and ordering of contractors being carried out in an ineffective manner. In addition, there is a need for efficient resource allocation that takes into account information such as the travel distance and schedules of contractors. However, the lack of systems that integrate this information in real time and automatically recommend the most suitable contractors has prevented the achievement of operational efficiency. 【0299】 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. 【0300】 In this invention, the server includes means for filtering contractor information based on input construction order conditions, means for selecting the most suitable contractor from the filtered contractors based on construction history and usage status, and means for providing a human-machine interface that allows for confirmation of order information and modification as needed. This makes it possible to select contractors in real time and place construction orders efficiently. 【0301】 "Construction order conditions" refer to information that serves as a basis for selecting a construction contractor, including the type and scale of the construction work, and the necessary qualifications and skills. 【0302】 A "construction contractor" is a company or organization that actually undertakes and carries out construction work. 【0303】 "Filtering" is the process of narrowing down data based on specific conditions and selecting only the necessary information. 【0304】 "Construction history" refers to data that records the types and number of construction projects carried out in the past, as well as the degree of success. 【0305】 "Usage status" refers to operation information such as the current progress of work and the availability of schedules. 【0306】 "The interface between humans and machines" is the interface for users to interact with the system, usually referring to the graphical user interface (GUI). 【0307】 "The order instruction document" is a document for formally requesting a specific construction project from a construction contractor. 【0308】 "Geographical information" is information for specifying the location and coordinates of the construction site. 【0309】 "Schedule" refers to the schedule information of the work and construction projects that the construction contractor plans to carry out in the future. 【0310】 To implement this system, a program is required that allows the user to input construction order conditions on the terminal used and send that information to the server. Mobile devices such as smartphones can be used as the terminal, and a basic UI (user interface) is implemented. Through this UI, the user can input the type of construction, scale, required skills, etc. 【0311】 The server is built using server - side frameworks such as Node.js or Python to process the input data. Based on the received construction order conditions, the server extracts the data of construction contractors from a database such as PostgreSQL and performs filtering and selection using algorithms. Parameters such as construction history and usage status are used in this selection process. Also, the geographical information and schedule of the construction contractor are considered to make an optimal selection. 【0312】 The selection result is presented again on the UI of the terminal for the user to confirm. If necessary, the user can modify this information and generate a final order instruction document to send to the construction contractor. 【0313】 As a concrete example, when ordering construction work that requires advanced technology for a certain project, the user might say, "I would like renovation work done. Area: 300m²." 2 The prompt reads, "Please limit the timeframe to two months or less. Please recommend a contractor with similar experience in the past." In response to this input, the server selects the contractor that best fits the criteria, enabling efficient project ordering. 【0314】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0315】 Step 1: 【0316】 The user enters the construction order conditions (type of construction, scale, required skills, etc.) using a terminal. The entered information is temporarily stored on the terminal and prepared for transmission to the server. 【0317】 Step 2: 【0318】 The terminal sends the entered construction order conditions to the server. The server receives the data and analyzes the information. Specifically, it parses the information sent in text format and extracts the elements necessary for filtering. 【0319】 Step 3: 【0320】 The server retrieves contractor data from the database based on the extracted elements. The database query used here is built with PostgreSQL and extracts contractors that match conditions such as the type of construction and usage status. 【0321】 Step 4: 【0322】 The server filters the acquired contractor data and executes an algorithm to select the best candidate based on construction history and usage status. It performs data calculations that include similarity of historical data, current operational status, and geographical information to narrow down the options. 【0323】 Step 5: 【0324】 The server sends information about the selected contractor to the terminal. The terminal displays this information and presents it to the user. The user can review the proposed contractors and modify the information if necessary. 【0325】 Step 6: 【0326】 Once the user confirms their selection, the terminal sends that information to the server, which automatically generates the final order. The server then creates the order and sends it to the designated contractor. 【0327】 Step 7: 【0328】 After construction is completed, the server collects feedback data from the contractor and evaluates the results of the construction and the contractor's response. This evaluation data is stored in a database and used in the contractor selection process for future projects. 【0329】 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. 【0330】 This invention relates to a system that recognizes user emotions and utilizes that information to optimize construction ordering operations. This system is based on the construction company selection process and combines it with an emotion engine that recognizes emotions during user operation to optimize the user interface and improve operational efficiency. 【0331】 Specifically, the system works as follows: First, the user inputs the construction order conditions via a terminal. At this point, the emotion engine analyzes the user's emotional state from their facial expressions and voice. This information is used to set the conditions for construction orders and to confirm the selection results. 【0332】 The terminal sends emotional information and construction order conditions to the server. Based on this data, the server uses a database of construction companies to select the most suitable construction company. By taking emotional information into consideration, for example, if the user is feeling stressed, the burden can be reduced by adding a more user-friendly interface or a detailed explanation of the selection reasoning. 【0333】 Information about the selected construction company is presented to the user via a terminal, and the interface dynamically adjusts according to the user's emotional state. For example, if the user shows interest or confidence, standard information is displayed, but if anxiety or stress is detected, additional support information or simplified options are provided. 【0334】 Ultimately, even in the process where the server generates purchase orders and places them with selected construction companies, feedback based on sentiment analysis is obtained and used to improve the ordering process in the future. 【0335】 For example, if a user feels anxious when using the system for the first time, the emotion engine recognizes this and provides guided instructions through the interface, allowing the user to proceed with the ordering process with confidence. In this way, the present invention improves the efficiency of construction ordering operations and enhances the user experience by incorporating the user's emotional information. 【0336】 The following describes the processing flow. 【0337】 Step 1: 【0338】 The user enters the construction order conditions via a terminal. These conditions include the type of construction, scale, required skills, and location. 【0339】 Step 2: 【0340】 The device activates an emotion engine that analyzes the user's emotions in real time from their facial expressions and voice to identify the user's emotional state. 【0341】 Step 3: 【0342】 The terminal sends the entered order conditions and sentiment information to the server. Sentiment information includes the user's current sentiment state and the corresponding recommended actions. 【0343】 Step 4: 【0344】 The server filters suitable construction companies from its database based on the order conditions received. During this process, it considers the user's emotional state and adjusts the selection process and information provision as needed. 【0345】 Step 5: 【0346】 The server selects the most suitable construction company from a filtered list of companies based on their track record and operational status, and adds user-generated content that responds to emotional information. 【0347】 Step 6: 【0348】 The device presents the selection results to the user. Depending on the user's emotional state, additional information and support options may be available. 【0349】 Step 7: 【0350】 The system reviews the information presented by the user and determines if there are any problems with the order. The user's emotions are then analyzed again and fed back into the interface. 【0351】 Step 8: 【0352】 If necessary, the user sends a correction request to the server via their device. 【0353】 Step 9: 【0354】 The server generates the final purchase order and places it with the selected construction company. Sentimental information is recorded as a result and used to improve the process in the future. 【0355】 Step 10: 【0356】 After the construction is completed, the server evaluates the feedback from the construction company and updates the database along with the user sentiment analysis results. 【0357】 (Example 2) 【0358】 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". 【0359】 In construction ordering operations, the challenge is to streamline the ordering process and improve the user experience by simplifying procedures and information processing that tend to cause stress for users, and by automating appropriate responses that respond to user emotions. In particular, conventional systems do not take user emotions into consideration, which leads to a problem of user dissatisfaction and stress accumulating. 【0360】 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. 【0361】 In this invention, the server includes emotion recognition means for analyzing the user's facial expressions and voice to identify their emotional state, means for providing a user interface that is dynamically adjusted according to the identified emotional state, and means for placing orders with selected construction organizations and evaluating and updating historical data after the completion of construction. This makes it possible to efficiently utilize the user's emotional information, select an appropriate construction company, and provide a user interface that reduces the burden on the user. 【0362】 "Construction order conditions" refer to the detailed requirements specified by the user when requesting construction work, and include information such as the type of work, desired schedule, budget, and location. 【0363】 A "construction company" refers to a business contracted to carry out construction work, and is a corporation or individual selected according to the specific details of the construction work. 【0364】 "Emotion recognition means" refers to technology or devices that can identify a user's emotional state by analyzing their facial expressions and voice. 【0365】 "User interface" refers to the operating environment in which the user directly interacts, including screen displays and operating methods for exchanging information between the system and the user. 【0366】 A "purchase order" is a document that formally records the details of a construction request from the user to the construction company, and clearly outlines the contract terms. 【0367】 "Historical data" refers to past performance and evaluation information of construction companies, and is used for selecting and evaluating construction companies. 【0368】 This invention is a system for improving user experience and the efficiency of construction ordering operations. This system utilizes emotion recognition technology and includes a process for selecting the most suitable construction company based on user input information. 【0369】 When a user uses the system, they first input construction order conditions through a terminal. The terminal sends the input conditions to the server, while simultaneously using a built-in emotion engine to capture the user's facial expressions and voice in real time and perform emotion recognition. For specific emotion recognition, the system uses a camera and microphone, and utilizes image processing and speech analysis software such as OpenCV and TensorFlow. 【0370】 The server integrates user input data and emotional information to filter information on construction companies and select the most suitable one. The selection process considers the construction company's historical data and operational status. Furthermore, it dynamically adjusts the user interface based on emotional information to provide appropriate information tailored to the user's psychological state. 【0371】 As a concrete example, if a user experiencing the system for the first time feels anxious, the system uses an emotion engine to recognize this anxiety and displays guided instructions through the interface. This allows the user to proceed with the process with confidence. 【0372】 An example of a prompt message to the system would be: "Please provide guidelines for selecting the most suitable construction company based on construction order conditions and user sentiment information, and designing an interface to propose it to the user." This prompt message is used as an instruction to the generating AI model. 【0373】 The system of the present invention considers user emotions as an important factor and provides appropriate feedback, thereby streamlining the ordering process and improving user satisfaction. 【0374】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0375】 Step 1: 【0376】 The user enters the construction order conditions using a terminal. Specifically, they enter information such as the type of construction, desired dates, budget, and location into a form displayed on the screen. The entered data is temporarily stored on the terminal and used for subsequent processing. 【0377】 Step 2: 【0378】 The terminal uses an emotion engine to capture the user's facial expressions and voice based on the order conditions entered by the user. Image data captured by the camera and audio data recorded by the microphone are passed to analysis software. OpenCV and TensorFlow are used to identify the user's emotions from this data. The input is image data and audio data, and the output is an emotional state (e.g., reassured, anxious, stressed). 【0379】 Step 3: 【0380】 The terminal collects the user's order conditions and sentiment information and sends it to the server. A secure protocol (e.g., HTTPS) is used for transmission. In this process, the input is the user's order conditions and sentiment information, and the output is the integrated data sent to the server. 【0381】 Step 4: 【0382】 The server analyzes the transmitted data and compares it against a database of construction companies. A filtering algorithm is then used to select candidate construction companies that meet the specified criteria. The input is the integrated data, and the output is a list of construction companies that meet the criteria. 【0383】 Step 5: 【0384】 The server dynamically adjusts the user interface based on the selection results, taking into account the user's emotional information. For example, if the user indicates anxiety, it generates an interface that includes detailed explanations and guide messages. The input is a list of construction companies and emotional information, and the output is the adjusted user interface. 【0385】 Step 6: 【0386】 The server ultimately generates the purchase order and places the order with the selected construction company. The purchase order is a formal document containing the details of the work, conditions, and information about the construction company, and is sent electronically to the construction company. The input is the construction company's information and the order conditions, and the output is the generated purchase order. 【0387】 (Application Example 2) 【0388】 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." 【0389】 In the process of ordering work, a system is needed that appropriately reflects the emotional state of users and improves their experience. Especially in fields where emotions are a crucial element, such as caregiving, it is essential to select the most suitable service provider while considering the user's feelings, ensuring that users can proceed with the process comfortably. Furthermore, efficient means are needed to reduce the anxiety and stress experienced by users and enable smoother work execution. 【0390】 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. 【0391】 In this invention, the server includes means for filtering information on performers based on input work order conditions, means for selecting the most suitable performer from the filtered performers based on work performance and operational status, and means for recognizing the user's emotions and applying dynamic adjustments based on that information to the user connection surface. This enables a work order process that reflects the user's emotional state, thereby improving the user experience. 【0392】 "Work order conditions" refer to the specific work content and conditions required of the person performing the work. 【0393】 "Implementer" refers to the individual or group that actually carries out the work, and is the entity that receives the order and performs the work. 【0394】 The "user interface" refers to the interface through which users interact with the system, and is a connection point designed to enhance usability. 【0395】 "Recognizing emotions" refers to the process of detecting and analyzing a user's emotional state from their facial expressions and voice. 【0396】 "Dynamic adjustment" refers to the automatic modification of a system's interface and behavior in response to conditions such as the user's emotional state. 【0397】 "Post-performance history documentation" refers to information such as the performer's past work performance and evaluations, which is recorded after the work is completed. 【0398】 In this invention, the user's terminal accepts the input work order conditions, filters the information of the person performing the work, and selects the most suitable person. In this process, the terminal analyzes the user's facial expressions and voice, and recognizes the user's emotional state using an emotion engine. The emotional information is transmitted to a server, which applies dynamic adjustments to the user connection surface according to the emotion. This reduces the user's anxiety and stress, providing a comfortable user experience. 【0399】 The server selects the most suitable service provider for the user, taking into account their work history and operational status. After selection, the order details are presented to the user via the user connection, and the details can be modified as needed. Furthermore, after the work is completed, the service provider's performance history is evaluated and used for future use. 【0400】 This system utilizes standard webcams and smartphones, and the emotion recognition algorithm employs existing image processing libraries such as OpenCV. Furthermore, suggestions based on emotion information are generated using a generative AI model on the server. 【0401】 As a concrete example, the system recognizes in real time the anxiety that residents show through their facial expressions within a nursing home and makes suggestions to the residents, such as, "How about this music when you want to relax?" Examples of prompts to be input into the generating AI model include, "What should be said to an elderly person whose facial expression indicates anxiety?" 【0402】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0403】 Step 1: 【0404】 The terminal receives the work order conditions from the user. The data entered here (e.g., work details, desired dates, budget, etc.) is prepared to be sent to the server for subsequent processes. 【0405】 Step 2: 【0406】 The device uses its camera to collect image and audio data from the user. This data is analyzed by an emotion engine to identify the user's emotional state. This process uses image processing libraries such as OpenCV to analyze the data, and emotional information is obtained as output. 【0407】 Step 3: 【0408】 The server filters the information of the performers based on the sentiment information and work order conditions received. Specifically, it extracts performers from the database who meet conditions such as work performance and operational status, and obtains that data as the filtered result. 【0409】 Step 4: 【0410】 The server selects the most suitable implementer from the filtering results. This process also considers an interface designed to reduce user stress by utilizing emotional information. Based on the selection results, detailed information about the chosen implementer is generated and output. 【0411】 Step 5: 【0412】 The server uses a generative AI model to create suggestions tailored to the user's emotional state. The system generates prompts, which are then input into the generative AI model to obtain interface information, including appropriate suggestions and guidance. 【0413】 Step 6: 【0414】 The terminal displays the obtained implementer information and proposed interface information to the user. The user reviews the order details based on this information and makes any necessary corrections. Finally, the finalized order information is sent to the server. 【0415】 Step 7: 【0416】 The server generates a purchase order and places it with the selected contractor. Simultaneously, after the work is completed, it updates the contractor's performance history to keep the system data up-to-date. 【0417】 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. 【0418】 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. 【0419】 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. 【0420】 [Third Embodiment] 【0421】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0422】 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. 【0423】 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). 【0424】 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. 【0425】 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. 【0426】 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). 【0427】 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. 【0428】 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. 【0429】 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. 【0430】 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. 【0431】 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. 【0432】 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". 【0433】 This invention relates to a system for efficiently and effectively carrying out construction ordering operations. This system improves operational efficiency by automating everything from selecting construction companies and determining the optimal contractor to evaluating the completed work. 【0434】 The system's main operation unfolds as follows: First, the user inputs the construction order conditions via a terminal. These conditions include the type and scale of the construction, as well as the required qualifications and skills. Once the terminal receives this information, the server processes it and retrieves information about construction companies from the database. The construction company data includes past construction performance, current operational status, and types of construction they specialize in. 【0435】 The server analyzes this data and selects the construction company that best fits the project order conditions. One of the evaluation criteria is the similarity of past project experience. For example, priority is given to companies that have successfully completed similar projects in the past. The server also takes into account operational status and travel distance to select a construction company that can allocate resources efficiently. 【0436】 The selected construction company information is presented to the user via a terminal. The user can review the information and modify the order details as needed. Based on this information, the server automatically generates an order form and sends an order instruction to the designated construction company. 【0437】 Once construction is complete, the server collects feedback data from the construction company, evaluates the quality of the work and the company's response, and updates the database. This evaluation process is used to improve the accuracy of future procurement decisions and the selection of construction companies. 【0438】 For example, in a building renovation project requiring advanced equipment installation skills, a construction company with experience in similar projects is selected, and priority is given to construction teams that can be relocated from nearby existing sites. This shortens the construction period and reduces the risk of traffic accidents. In this way, the system of the present invention automates various processes related to ordering construction work, enabling precise decision-making. 【0439】 The following describes the processing flow. 【0440】 Step 1: 【0441】 The user enters the construction order requirements into the terminal. This includes information such as the type of construction, scale, required skills, and location. 【0442】 Step 2: 【0443】 The terminal sends the order conditions entered by the user to the server. The order conditions are converted into a format compatible with the server's processing. 【0444】 Step 3: 【0445】 Based on the order conditions received by the server, it retrieves information on all construction companies from the database. This information includes construction track record, skill sets, operational status, and qualifications. 【0446】 Step 4: 【0447】 Based on the construction company information acquired by the server, the system filters out construction companies that match the order conditions. Filtering criteria include matching types of construction work and skill sets. 【0448】 Step 5: 【0449】 The server then ranks and selects the most suitable construction company from the filtered list based on their track record and evaluation scores. 【0450】 Step 6: 【0451】 The server calculates the operational status and travel distance of the selected construction company and creates the optimal ordering plan. 【0452】 Step 7: 【0453】 The terminal presents the selection results and order plan received from the server to the user and requests their confirmation. 【0454】 Step 8: 【0455】 The user reviews the presented order plan and sends any requested modifications to the server via their device. 【0456】 Step 9: 【0457】 The server receives user confirmation and modifications, generates the final purchase order, and places the order with the designated construction company. 【0458】 Step 10: 【0459】 After the construction is completed, the server receives feedback data from the construction company, evaluates the construction, and updates the database. 【0460】 (Example 1) 【0461】 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." 【0462】 In construction procurement, there is a need to automate and optimize the selection of appropriate construction companies, efficient resource allocation, and post-completion evaluation. The challenge lies in improving efficiency, accuracy, and time efficiency through these processes. 【0463】 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. 【0464】 In this invention, the server includes means for filtering group information based on planning conditions, means for selecting the most suitable group from the filtered groups based on work history and work status, and means for supporting future planning decisions based on evaluation results. This streamlines the construction ordering process and enables a highly accurate selection and evaluation process for construction companies. 【0465】 "Planning conditions" refer to a set of basic requirements set when ordering construction work, such as the type and scale of the work, and the necessary qualifications and skills. 【0466】 "Organizational information" refers to data including past construction achievements, current operational status, and types of construction work that the construction company specializes in. 【0467】 "Filtering" is the process of selecting and applying data based on specific criteria. 【0468】 "Work history" refers to records of construction work previously carried out by a construction company, as well as the experience gained from its successes and failures. 【0469】 "Work status" refers to information indicating the projects currently underway by the construction company and their future operational readiness. 【0470】 "Configuration" refers to a part of a system that provides an interface and settings for users to review order details and make modifications as needed. 【0471】 "Evaluation results" refer to the feedback received from the construction company after the completion of their work, and the results of the analysis based on that feedback. 【0472】 "Means to support future planning decisions" refers to a function that supports appropriate decisions when placing new construction orders, based on past evaluation results. 【0473】 "Load balancing" is the process of optimizing the use of labor by taking into account the distance traveled and the operational status of the group. 【0474】 This invention constitutes a system for efficiently automating construction order ordering operations. The system is primarily operated by a server, terminals, and users. 【0475】 First, the user inputs planning conditions such as the type and scale of the construction work, and the necessary qualifications and skills, through a terminal. This forms the basic data for the work. The terminal receives this information and sends it to the server. 【0476】 The server retrieves information on construction companies from the database based on the planning conditions and performs filtering. This filtering process involves selecting data based on specific criteria to narrow down the most suitable companies. Specifically, it considers factors such as the company's work history, work status, and current operational status. The software used here is for performing data processing and analysis. A modern option is often to use a cloud-based data analytics platform. 【0477】 The selected organization information is presented to the user via a terminal. The user can review this information and modify the plan details as needed through an interface. This allows for fine-tuning of the order details. 【0478】 As a concrete example of the selection process, consider the case of "selecting a construction company with the technology to handle advanced weather conditions for the exterior wall construction of a high-rise building." In this case, a company with a track record of working under similar weather conditions in the past would be selected, and the optimal construction period would be presented. 【0479】 Furthermore, an example of a prompt message that utilizes a generative AI model could be a request such as, "List construction companies specializing in soundproofing for interior construction of urban hotels, and prioritize them based on their past performance." 【0480】 In this form, the present invention streamlines various judgments and procedures associated with ordering construction work and supports highly accurate decision-making. 【0481】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0482】 Step 1: 【0483】 The user enters the construction order conditions via a terminal. This input includes the type and scale of the construction, as well as the required qualifications and skills. This information is received by the terminal as planning conditions. The entered data is then prepared to be sent directly to the server. 【0484】 Step 2: 【0485】 The terminal sends the received planning conditions to the server. The server receives this data and starts the process of retrieving information about construction companies from the database. Specifically, it executes a database query and extracts information about organizations that match the conditions. As a result, a list of relevant construction companies is output. 【0486】 Step 3: 【0487】 The server filters the acquired organization information. Here, it performs analysis to select the most suitable organization based on work history and work status. Data processing includes checking past construction performance and comparing it with current operational status. The best candidates are listed and a prioritized list is output. 【0488】 Step 4: 【0489】 The terminal displays a list of candidates sent from the server to the user. The user can review the information and modify the order details as needed. Editing is possible directly on the interface, and the changes are immediately reflected on the server. 【0490】 Step 5: 【0491】 The server automatically generates a purchase order based on the information confirmed and corrected by the user. This process creates a document containing details of the work and payment terms. The generated purchase order is sent as an electronic message to the selected construction company. 【0492】 Step 6: 【0493】 After the construction is completed, the server collects feedback data from the construction company. This data includes the quality of the work, the construction period, and the construction company's response. The server analyzes this information and updates the database. This generates new evaluation information that can be used when selecting construction companies in the future. 【0494】 (Application Example 1) 【0495】 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." 【0496】 In the modern construction industry, the process of ordering construction work still relies heavily on manual work, and there are problems with the selection and ordering of contractors being carried out in an ineffective manner. In addition, there is a need for efficient resource allocation that takes into account information such as the travel distance and schedules of contractors. However, the lack of systems that integrate this information in real time and automatically recommend the most suitable contractors has prevented the achievement of operational efficiency. 【0497】 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. 【0498】 In this invention, the server includes means for filtering contractor information based on input construction order conditions, means for selecting the most suitable contractor from the filtered contractors based on construction history and usage status, and means for providing a human-machine interface that allows for confirmation of order information and modification as needed. This makes it possible to select contractors in real time and place construction orders efficiently. 【0499】 "Construction order conditions" refer to information that serves as a basis for selecting a construction contractor, including the type and scale of the construction work, and the necessary qualifications and skills. 【0500】 A "construction contractor" is a company or organization that actually undertakes and carries out construction work. 【0501】 "Filtering" is the process of narrowing down data based on specific conditions and selecting only the necessary information. 【0502】 "Construction history" refers to data that records the types and number of construction projects carried out in the past, as well as the degree of success. 【0503】 "Usage status" refers to operational information such as the current progress of tasks and the availability of schedules. 【0504】 The "human-machine interface" refers to the interface through which a user interacts with a system, and usually refers to a graphical user interface (GUI). 【0505】 A "procurement order" is a document used to formally request a contractor to perform a specific construction project. 【0506】 "Geographic information" refers to information used to identify the location and coordinates of a construction site. 【0507】 "Schedule" refers to the schedule information for tasks and construction work that the contractor plans to carry out in the future. 【0508】 To implement this system, a program is needed that allows users to input construction order conditions on their terminals and send that information to a server. Mobile devices such as smartphones can be used as terminals, and a basic UI (user interface) will be implemented. Through this UI, users will be able to input information such as the type and scale of the construction work, and the required skills. 【0509】 The server is built using server-side frameworks such as Node.js or Python and processes the input data. Based on the received construction order conditions, the server extracts data on construction companies from a database such as PostgreSQL and uses algorithms to filter and select them. Parameters such as construction history and usage status are used in this selection process. The geographical information and schedules of the construction companies are also taken into consideration to make the optimal selection. 【0510】 The selection results are again displayed on the terminal's UI for the user to review. The user can modify this information as needed, generate the final order form, and send it to the contractor. 【0511】 As a concrete example, when ordering construction work that requires advanced technology for a certain project, the user might say, "I would like renovation work done. Area: 300m²." 2 The prompt reads, "Please limit the timeframe to two months or less. Please recommend a contractor with similar experience in the past." In response to this input, the server selects the contractor that best fits the criteria, enabling efficient project ordering. 【0512】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0513】 Step 1: 【0514】 The user enters the construction order conditions (type of construction, scale, required skills, etc.) using a terminal. The entered information is temporarily stored on the terminal and prepared for transmission to the server. 【0515】 Step 2: 【0516】 The terminal sends the entered construction order conditions to the server. The server receives the data and analyzes the information. Specifically, it parses the information sent in text format and extracts the elements necessary for filtering. 【0517】 Step 3: 【0518】 The server retrieves contractor data from the database based on the extracted elements. The database query used here is built with PostgreSQL and extracts contractors that match conditions such as the type of construction and usage status. 【0519】 Step 4: 【0520】 The server filters the acquired contractor data and executes an algorithm to select the best candidate based on construction history and usage status. It performs data calculations that include similarity of historical data, current operational status, and geographical information to narrow down the options. 【0521】 Step 5: 【0522】 The server sends information about the selected contractor to the terminal. The terminal displays this information and presents it to the user. The user can review the proposed contractors and modify the information if necessary. 【0523】 Step 6: 【0524】 Once the user confirms their selection, the terminal sends that information to the server, which automatically generates the final order. The server then creates the order and sends it to the designated contractor. 【0525】 Step 7: 【0526】 After construction is completed, the server collects feedback data from the contractor and evaluates the results of the construction and the contractor's response. This evaluation data is stored in a database and used in the contractor selection process for future projects. 【0527】 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. 【0528】 This invention relates to a system that recognizes user emotions and utilizes that information to optimize construction ordering operations. This system is based on the construction company selection process and combines it with an emotion engine that recognizes emotions during user operation to optimize the user interface and improve operational efficiency. 【0529】 Specifically, the system works as follows: First, the user inputs the construction order conditions via a terminal. At this point, the emotion engine analyzes the user's emotional state from their facial expressions and voice. This information is used to set the conditions for construction orders and to confirm the selection results. 【0530】 The terminal sends emotional information and construction order conditions to the server. Based on this data, the server uses a database of construction companies to select the most suitable construction company. By taking emotional information into consideration, for example, if the user is feeling stressed, the burden can be reduced by adding a more user-friendly interface or a detailed explanation of the selection reasoning. 【0531】 Information about the selected construction company is presented to the user via a terminal, and the interface dynamically adjusts according to the user's emotional state. For example, if the user shows interest or confidence, standard information is displayed, but if anxiety or stress is detected, additional support information or simplified options are provided. 【0532】 Ultimately, even in the process where the server generates purchase orders and places them with selected construction companies, feedback based on sentiment analysis is obtained and used to improve the ordering process in the future. 【0533】 For example, if a user feels anxious when using the system for the first time, the emotion engine recognizes this and provides guided instructions through the interface, allowing the user to proceed with the ordering process with confidence. In this way, the present invention improves the efficiency of construction ordering operations and enhances the user experience by incorporating the user's emotional information. 【0534】 The following describes the processing flow. 【0535】 Step 1: 【0536】 The user enters the construction order conditions via a terminal. These conditions include the type of construction, scale, required skills, and location. 【0537】 Step 2: 【0538】 The device activates an emotion engine that analyzes the user's emotions in real time from their facial expressions and voice to identify the user's emotional state. 【0539】 Step 3: 【0540】 The terminal sends the entered order conditions and sentiment information to the server. Sentiment information includes the user's current sentiment state and the corresponding recommended actions. 【0541】 Step 4: 【0542】 The server filters suitable construction companies from its database based on the order conditions received. During this process, it considers the user's emotional state and adjusts the selection process and information provision as needed. 【0543】 Step 5: 【0544】 The server selects the most suitable construction company from a filtered list of companies based on their track record and operational status, and adds user-generated content that responds to emotional information. 【0545】 Step 6: 【0546】 The device presents the selection results to the user. Depending on the user's emotional state, additional information and support options may be available. 【0547】 Step 7: 【0548】 The system reviews the information presented by the user and determines if there are any problems with the order. The user's emotions are then analyzed again and fed back into the interface. 【0549】 Step 8: 【0550】 If necessary, the user sends a correction request to the server via their device. 【0551】 Step 9: 【0552】 The server generates the final purchase order and places it with the selected construction company. Sentimental information is recorded as a result and used to improve the process in the future. 【0553】 Step 10: 【0554】 After the construction is completed, the server evaluates the feedback from the construction company and updates the database along with the user sentiment analysis results. 【0555】 (Example 2) 【0556】 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." 【0557】 In construction ordering operations, the challenge is to streamline the ordering process and improve the user experience by simplifying procedures and information processing that tend to cause stress for users, and by automating appropriate responses that respond to user emotions. In particular, conventional systems do not take user emotions into consideration, which leads to a problem of user dissatisfaction and stress accumulating. 【0558】 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. 【0559】 In this invention, the server includes emotion recognition means for analyzing the user's facial expressions and voice to identify their emotional state, means for providing a user interface that is dynamically adjusted according to the identified emotional state, and means for placing orders with selected construction organizations and evaluating and updating historical data after the completion of construction. This makes it possible to efficiently utilize the user's emotional information, select an appropriate construction company, and provide a user interface that reduces the burden on the user. 【0560】 "Construction order conditions" refer to the detailed requirements specified by the user when requesting construction work, and include information such as the type of work, desired schedule, budget, and location. 【0561】 A "construction company" refers to a business contracted to carry out construction work, and is a corporation or individual selected according to the specific details of the construction work. 【0562】 "Emotion recognition means" refers to technology or devices that can identify a user's emotional state by analyzing their facial expressions and voice. 【0563】 "User interface" refers to the operating environment in which the user directly interacts, including screen displays and operating methods for exchanging information between the system and the user. 【0564】 A "purchase order" is a document that formally records the details of a construction request from the user to the construction company, and clearly outlines the contract terms. 【0565】 "Historical data" refers to past performance and evaluation information of construction companies, and is used for selecting and evaluating construction companies. 【0566】 This invention is a system for improving user experience and the efficiency of construction ordering operations. This system utilizes emotion recognition technology and includes a process for selecting the most suitable construction company based on user input information. 【0567】 When a user uses the system, they first input construction order conditions through a terminal. The terminal sends the input conditions to the server, while simultaneously using a built-in emotion engine to capture the user's facial expressions and voice in real time and perform emotion recognition. For specific emotion recognition, the system uses a camera and microphone, and utilizes image processing and speech analysis software such as OpenCV and TensorFlow. 【0568】 The server integrates user input data and emotional information to filter information on construction companies and select the most suitable one. The selection process considers the construction company's historical data and operational status. Furthermore, it dynamically adjusts the user interface based on emotional information to provide appropriate information tailored to the user's psychological state. 【0569】 As a concrete example, if a user experiencing the system for the first time feels anxious, the system uses an emotion engine to recognize this anxiety and displays guided instructions through the interface. This allows the user to proceed with the process with confidence. 【0570】 An example of a prompt message to the system would be: "Please provide guidelines for selecting the most suitable construction company based on construction order conditions and user sentiment information, and designing an interface to propose it to the user." This prompt message is used as an instruction to the generating AI model. 【0571】 The system of the present invention considers user emotions as an important factor and provides appropriate feedback, thereby streamlining the ordering process and improving user satisfaction. 【0572】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0573】 Step 1: 【0574】 The user enters the construction order conditions using a terminal. Specifically, they enter information such as the type of construction, desired dates, budget, and location into a form displayed on the screen. The entered data is temporarily stored on the terminal and used for subsequent processing. 【0575】 Step 2: 【0576】 The terminal uses an emotion engine to capture the user's facial expressions and voice based on the order conditions entered by the user. Image data captured by the camera and audio data recorded by the microphone are passed to analysis software. OpenCV and TensorFlow are used to identify the user's emotions from this data. The input is image data and audio data, and the output is an emotional state (e.g., reassured, anxious, stressed). 【0577】 Step 3: 【0578】 The terminal collects the user's order conditions and sentiment information and sends it to the server. A secure protocol (e.g., HTTPS) is used for transmission. In this process, the input is the user's order conditions and sentiment information, and the output is the integrated data sent to the server. 【0579】 Step 4: 【0580】 The server analyzes the transmitted data and compares it against a database of construction companies. A filtering algorithm is then used to select candidate construction companies that meet the specified criteria. The input is the integrated data, and the output is a list of construction companies that meet the criteria. 【0581】 Step 5: 【0582】 The server dynamically adjusts the user interface based on the selection results, taking into account the user's emotional information. For example, if the user indicates anxiety, it generates an interface that includes detailed explanations and guide messages. The input is a list of construction companies and emotional information, and the output is the adjusted user interface. 【0583】 Step 6: 【0584】 The server ultimately generates the purchase order and places the order with the selected construction company. The purchase order is a formal document containing the details of the work, conditions, and information about the construction company, and is sent electronically to the construction company. The input is the construction company's information and the order conditions, and the output is the generated purchase order. 【0585】 (Application Example 2) 【0586】 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." 【0587】 In the process of ordering work, a system is needed that appropriately reflects the emotional state of users and improves their experience. Especially in fields where emotions are a crucial element, such as caregiving, it is essential to select the most suitable service provider while considering the user's feelings, ensuring that users can proceed with the process comfortably. Furthermore, efficient means are needed to reduce the anxiety and stress experienced by users and enable smoother work execution. 【0588】 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. 【0589】 In this invention, the server includes means for filtering information on performers based on input work order conditions, means for selecting the most suitable performer from the filtered performers based on work performance and operational status, and means for recognizing the user's emotions and applying dynamic adjustments based on that information to the user connection surface. This enables a work order process that reflects the user's emotional state, thereby improving the user experience. 【0590】 "Work order conditions" refer to the specific work content and conditions required of the person performing the work. 【0591】 "Implementer" refers to the individual or group that actually carries out the work, and is the entity that receives the order and performs the work. 【0592】 The "user interface" refers to the interface through which users interact with the system, and is a connection point designed to enhance usability. 【0593】 "Recognizing emotions" refers to the process of detecting and analyzing a user's emotional state from their facial expressions and voice. 【0594】 "Dynamic adjustment" refers to the automatic modification of a system's interface and behavior in response to conditions such as the user's emotional state. 【0595】 "Post-performance history documentation" refers to information such as the performer's past work performance and evaluations, which is recorded after the work is completed. 【0596】 In this invention, the user's terminal accepts the input work order conditions, filters the information of the person performing the work, and selects the most suitable person. In this process, the terminal analyzes the user's facial expressions and voice, and recognizes the user's emotional state using an emotion engine. The emotional information is transmitted to a server, which applies dynamic adjustments to the user connection surface according to the emotion. This reduces the user's anxiety and stress, providing a comfortable user experience. 【0597】 The server selects the most suitable service provider for the user, taking into account their work history and operational status. After selection, the order details are presented to the user via the user connection, and the details can be modified as needed. Furthermore, after the work is completed, the service provider's performance history is evaluated and used for future use. 【0598】 This system utilizes standard webcams and smartphones, and the emotion recognition algorithm employs existing image processing libraries such as OpenCV. Furthermore, suggestions based on emotion information are generated using a generative AI model on the server. 【0599】 As a concrete example, the system recognizes in real time the anxiety that residents show through their facial expressions within a nursing home and makes suggestions to the residents, such as, "How about this music when you want to relax?" Examples of prompts to be input into the generating AI model include, "What should be said to an elderly person whose facial expression indicates anxiety?" 【0600】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0601】 Step 1: 【0602】 The terminal receives the work order conditions from the user. The data entered here (e.g., work details, desired dates, budget, etc.) is prepared to be sent to the server for subsequent processes. 【0603】 Step 2: 【0604】 The device uses its camera to collect image and audio data from the user. This data is analyzed by an emotion engine to identify the user's emotional state. This process uses image processing libraries such as OpenCV to analyze the data, and emotional information is obtained as output. 【0605】 Step 3: 【0606】 The server filters the information of the performers based on the sentiment information and work order conditions received. Specifically, it extracts performers from the database who meet conditions such as work performance and operational status, and obtains that data as the filtered result. 【0607】 Step 4: 【0608】 The server selects the most suitable implementer from the filtering results. This process also considers an interface designed to reduce user stress by utilizing emotional information. Based on the selection results, detailed information about the chosen implementer is generated and output. 【0609】 Step 5: 【0610】 The server uses a generative AI model to create suggestions tailored to the user's emotional state. The system generates prompts, which are then input into the generative AI model to obtain interface information, including appropriate suggestions and guidance. 【0611】 Step 6: 【0612】 The terminal displays the obtained implementer information and proposed interface information to the user. The user reviews the order details based on this information and makes any necessary corrections. Finally, the finalized order information is sent to the server. 【0613】 Step 7: 【0614】 The server generates a purchase order and places it with the selected contractor. Simultaneously, after the work is completed, it updates the contractor's performance history to keep the system data up-to-date. 【0615】 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. 【0616】 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. 【0617】 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. 【0618】 [Fourth Embodiment] 【0619】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0620】 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. 【0621】 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). 【0622】 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. 【0623】 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. 【0624】 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). 【0625】 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. 【0626】 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. 【0627】 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. 【0628】 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. 【0629】 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. 【0630】 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. 【0631】 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". 【0632】 This invention relates to a system for efficiently and effectively carrying out construction ordering operations. This system improves operational efficiency by automating everything from selecting construction companies and determining the optimal contractor to evaluating the completed work. 【0633】 The system's main operation unfolds as follows: First, the user inputs the construction order conditions via a terminal. These conditions include the type and scale of the construction, as well as the required qualifications and skills. Once the terminal receives this information, the server processes it and retrieves information about construction companies from the database. The construction company data includes past construction performance, current operational status, and types of construction they specialize in. 【0634】 The server analyzes this data and selects the construction company that best fits the project order conditions. One of the evaluation criteria is the similarity of past project experience. For example, priority is given to companies that have successfully completed similar projects in the past. The server also takes into account operational status and travel distance to select a construction company that can allocate resources efficiently. 【0635】 The selected construction company information is presented to the user via a terminal. The user can review the information and modify the order details as needed. Based on this information, the server automatically generates an order form and sends an order instruction to the designated construction company. 【0636】 Once construction is complete, the server collects feedback data from the construction company, evaluates the quality of the work and the company's response, and updates the database. This evaluation process is used to improve the accuracy of future procurement decisions and the selection of construction companies. 【0637】 For example, in a building renovation project requiring advanced equipment installation skills, a construction company with experience in similar projects is selected, and priority is given to construction teams that can be relocated from nearby existing sites. This shortens the construction period and reduces the risk of traffic accidents. In this way, the system of the present invention automates various processes related to ordering construction work, enabling precise decision-making. 【0638】 The following describes the processing flow. 【0639】 Step 1: 【0640】 The user enters the construction order requirements into the terminal. This includes information such as the type of construction, scale, required skills, and location. 【0641】 Step 2: 【0642】 The terminal sends the order conditions entered by the user to the server. The order conditions are converted into a format compatible with the server's processing. 【0643】 Step 3: 【0644】 Based on the order conditions received by the server, it retrieves information on all construction companies from the database. This information includes construction track record, skill sets, operational status, and qualifications. 【0645】 Step 4: 【0646】 Based on the construction company information acquired by the server, the system filters out construction companies that match the order conditions. Filtering criteria include matching types of construction work and skill sets. 【0647】 Step 5: 【0648】 The server then ranks and selects the most suitable construction company from the filtered list based on their track record and evaluation scores. 【0649】 Step 6: 【0650】 The server calculates the operational status and travel distance of the selected construction company and creates the optimal ordering plan. 【0651】 Step 7: 【0652】 The terminal presents the selection results and order plan received from the server to the user and requests their confirmation. 【0653】 Step 8: 【0654】 The user reviews the presented order plan and sends any requested modifications to the server via their device. 【0655】 Step 9: 【0656】 The server receives user confirmation and modifications, generates the final purchase order, and places the order with the designated construction company. 【0657】 Step 10: 【0658】 After the construction is completed, the server receives feedback data from the construction company, evaluates the construction, and updates the database. 【0659】 (Example 1) 【0660】 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". 【0661】 In construction procurement, there is a need to automate and optimize the selection of appropriate construction companies, efficient resource allocation, and post-completion evaluation. The challenge lies in improving efficiency, accuracy, and time efficiency through these processes. 【0662】 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. 【0663】 In this invention, the server includes means for filtering group information based on planning conditions, means for selecting the most suitable group from the filtered groups based on work history and work status, and means for supporting future planning decisions based on evaluation results. This streamlines the construction ordering process and enables a highly accurate selection and evaluation process for construction companies. 【0664】 "Planning conditions" refer to a set of basic requirements set when ordering construction work, such as the type and scale of the work, and the necessary qualifications and skills. 【0665】 "Organizational information" refers to data including past construction achievements, current operational status, and types of construction work that the construction company specializes in. 【0666】 "Filtering" is the process of selecting and applying data based on specific criteria. 【0667】 "Work history" refers to records of construction work previously carried out by a construction company, as well as the experience gained from its successes and failures. 【0668】 "Work status" refers to information indicating the projects currently underway by the construction company and their future operational readiness. 【0669】 "Configuration" refers to a part of a system that provides an interface and settings for users to review order details and make modifications as needed. 【0670】 "Evaluation results" refer to the feedback received from the construction company after the completion of their work, and the results of the analysis based on that feedback. 【0671】 "Means to support future planning decisions" refers to a function that supports appropriate decisions when placing new construction orders, based on past evaluation results. 【0672】 "Load balancing" is the process of optimizing the use of labor by taking into account the distance traveled and the operational status of the group. 【0673】 This invention constitutes a system for efficiently automating construction order ordering operations. The system is primarily operated by a server, terminals, and users. 【0674】 First, the user inputs planning conditions such as the type and scale of the construction work, and the necessary qualifications and skills, through a terminal. This forms the basic data for the work. The terminal receives this information and sends it to the server. 【0675】 The server retrieves information on construction companies from the database based on the planning conditions and performs filtering. This filtering process involves selecting data based on specific criteria to narrow down the most suitable companies. Specifically, it considers factors such as the company's work history, work status, and current operational status. The software used here is for performing data processing and analysis. A modern option is often to use a cloud-based data analytics platform. 【0676】 The selected organization information is presented to the user via a terminal. The user can review this information and modify the plan details as needed through an interface. This allows for fine-tuning of the order details. 【0677】 As a concrete example of the selection process, consider the case of "selecting a construction company with the technology to handle advanced weather conditions for the exterior wall construction of a high-rise building." In this case, a company with a track record of working under similar weather conditions in the past would be selected, and the optimal construction period would be presented. 【0678】 Furthermore, an example of a prompt message that utilizes a generative AI model could be a request such as, "List construction companies specializing in soundproofing for interior construction of urban hotels, and prioritize them based on their past performance." 【0679】 In this form, the present invention streamlines various judgments and procedures associated with ordering construction work and supports highly accurate decision-making. 【0680】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0681】 Step 1: 【0682】 The user enters the construction order conditions via a terminal. This input includes the type and scale of the construction, as well as the required qualifications and skills. This information is received by the terminal as planning conditions. The entered data is then prepared to be sent directly to the server. 【0683】 Step 2: 【0684】 The terminal sends the received planning conditions to the server. The server receives this data and starts the process of retrieving information about construction companies from the database. Specifically, it executes a database query and extracts information about organizations that match the conditions. As a result, a list of relevant construction companies is output. 【0685】 Step 3: 【0686】 The server filters the acquired organization information. Here, it performs analysis to select the most suitable organization based on work history and work status. Data processing includes checking past construction performance and comparing it with current operational status. The best candidates are listed and a prioritized list is output. 【0687】 Step 4: 【0688】 The terminal displays a list of candidates sent from the server to the user. The user can review the information and modify the order details as needed. Editing is possible directly on the interface, and the changes are immediately reflected on the server. 【0689】 Step 5: 【0690】 The server automatically generates a purchase order based on the information confirmed and corrected by the user. This process creates a document containing details of the work and payment terms. The generated purchase order is sent as an electronic message to the selected construction company. 【0691】 Step 6: 【0692】 After the construction is completed, the server collects feedback data from the construction company. This data includes the quality of the work, the construction period, and the construction company's response. The server analyzes this information and updates the database. This generates new evaluation information that can be used when selecting construction companies in the future. 【0693】 (Application Example 1) 【0694】 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". 【0695】 In the modern construction industry, the process of ordering construction work still relies heavily on manual work, and there are problems with the selection and ordering of contractors being carried out in an ineffective manner. In addition, there is a need for efficient resource allocation that takes into account information such as the travel distance and schedules of contractors. However, the lack of systems that integrate this information in real time and automatically recommend the most suitable contractors has prevented the achievement of operational efficiency. 【0696】 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. 【0697】 In this invention, the server includes means for filtering contractor information based on input construction order conditions, means for selecting the most suitable contractor from the filtered contractors based on construction history and usage status, and means for providing a human-machine interface that allows for confirmation of order information and modification as needed. This makes it possible to select contractors in real time and place construction orders efficiently. 【0698】 "Construction order conditions" refer to information that serves as a basis for selecting a construction contractor, including the type and scale of the construction work, and the necessary qualifications and skills. 【0699】 A "construction contractor" is a company or organization that actually undertakes and carries out construction work. 【0700】 "Filtering" is the process of narrowing down data based on specific conditions and selecting only the necessary information. 【0701】 "Construction history" refers to data that records the types and number of construction projects carried out in the past, as well as the degree of success. 【0702】 "Usage status" refers to operational information such as the current progress of tasks and the availability of schedules. 【0703】 The "human-machine interface" refers to the interface through which a user interacts with a system, and usually refers to a graphical user interface (GUI). 【0704】 A "procurement order" is a document used to formally request a contractor to perform a specific construction project. 【0705】 "Geographic information" refers to information used to identify the location and coordinates of a construction site. 【0706】 "Schedule" refers to the schedule information for tasks and construction work that the contractor plans to carry out in the future. 【0707】 To implement this system, a program is needed that allows users to input construction order conditions on their terminals and send that information to a server. Mobile devices such as smartphones can be used as terminals, and a basic UI (user interface) will be implemented. Through this UI, users will be able to input information such as the type and scale of the construction work, and the required skills. 【0708】 The server is built using server-side frameworks such as Node.js or Python and processes the input data. Based on the received construction order conditions, the server extracts data on construction companies from a database such as PostgreSQL and uses algorithms to filter and select them. Parameters such as construction history and usage status are used in this selection process. The geographical information and schedules of the construction companies are also taken into consideration to make the optimal selection. 【0709】 The selection results are again displayed on the terminal's UI for the user to review. The user can modify this information as needed, generate the final order form, and send it to the contractor. 【0710】 As a concrete example, when ordering construction work that requires advanced technology for a certain project, the user might say, "I would like renovation work done. Area: 300m²." 2 The prompt reads, "Please limit the timeframe to two months or less. Please recommend a contractor with similar experience in the past." In response to this input, the server selects the contractor that best fits the criteria, enabling efficient project ordering. 【0711】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0712】 Step 1: 【0713】 The user enters the construction order conditions (type of construction, scale, required skills, etc.) using a terminal. The entered information is temporarily stored on the terminal and prepared for transmission to the server. 【0714】 Step 2: 【0715】 The terminal sends the entered construction order conditions to the server. The server receives the data and analyzes the information. Specifically, it parses the information sent in text format and extracts the elements necessary for filtering. 【0716】 Step 3: 【0717】 The server retrieves contractor data from the database based on the extracted elements. The database query used here is built with PostgreSQL and extracts contractors that match conditions such as the type of construction and usage status. 【0718】 Step 4: 【0719】 The server filters the acquired contractor data and executes an algorithm to select the best candidate based on construction history and usage status. It performs data calculations that include similarity of historical data, current operational status, and geographical information to narrow down the options. 【0720】 Step 5: 【0721】 The server sends information about the selected contractor to the terminal. The terminal displays this information and presents it to the user. The user can review the proposed contractors and modify the information if necessary. 【0722】 Step 6: 【0723】 Once the user confirms their selection, the terminal sends that information to the server, which automatically generates the final order. The server then creates the order and sends it to the designated contractor. 【0724】 Step 7: 【0725】 After construction is completed, the server collects feedback data from the contractor and evaluates the results of the construction and the contractor's response. This evaluation data is stored in a database and used in the contractor selection process for future projects. 【0726】 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. 【0727】 This invention relates to a system that recognizes user emotions and utilizes that information to optimize construction ordering operations. This system is based on the construction company selection process and combines it with an emotion engine that recognizes emotions during user operation to optimize the user interface and improve operational efficiency. 【0728】 Specifically, the system works as follows: First, the user inputs the construction order conditions via a terminal. At this point, the emotion engine analyzes the user's emotional state from their facial expressions and voice. This information is used to set the conditions for construction orders and to confirm the selection results. 【0729】 The terminal sends emotional information and construction order conditions to the server. Based on this data, the server uses a database of construction companies to select the most suitable construction company. By taking emotional information into consideration, for example, if the user is feeling stressed, the burden can be reduced by adding a more user-friendly interface or a detailed explanation of the selection reasoning. 【0730】 Information about the selected construction company is presented to the user via a terminal, and the interface dynamically adjusts according to the user's emotional state. For example, if the user shows interest or confidence, standard information is displayed, but if anxiety or stress is detected, additional support information or simplified options are provided. 【0731】 Ultimately, even in the process where the server generates purchase orders and places them with selected construction companies, feedback based on sentiment analysis is obtained and used to improve the ordering process in the future. 【0732】 For example, if a user feels anxious when using the system for the first time, the emotion engine recognizes this and provides guided instructions through the interface, allowing the user to proceed with the ordering process with confidence. In this way, the present invention improves the efficiency of construction ordering operations and enhances the user experience by incorporating the user's emotional information. 【0733】 The following describes the processing flow. 【0734】 Step 1: 【0735】 The user enters the construction order conditions via a terminal. These conditions include the type of construction, scale, required skills, and location. 【0736】 Step 2: 【0737】 The device activates an emotion engine that analyzes the user's emotions in real time from their facial expressions and voice to identify the user's emotional state. 【0738】 Step 3: 【0739】 The terminal sends the entered order conditions and sentiment information to the server. Sentiment information includes the user's current sentiment state and the corresponding recommended actions. 【0740】 Step 4: 【0741】 The server filters suitable construction companies from its database based on the order conditions received. During this process, it considers the user's emotional state and adjusts the selection process and information provision as needed. 【0742】 Step 5: 【0743】 The server selects the most suitable construction company from a filtered list of companies based on their track record and operational status, and adds user-generated content that responds to emotional information. 【0744】 Step 6: 【0745】 The device presents the selection results to the user. Depending on the user's emotional state, additional information and support options may be available. 【0746】 Step 7: 【0747】 The system reviews the information presented by the user and determines if there are any problems with the order. The user's emotions are then analyzed again and fed back into the interface. 【0748】 Step 8: 【0749】 If necessary, the user sends a correction request to the server via their device. 【0750】 Step 9: 【0751】 The server generates the final purchase order and places it with the selected construction company. Sentimental information is recorded as a result and used to improve the process in the future. 【0752】 Step 10: 【0753】 After the construction is completed, the server evaluates the feedback from the construction company and updates the database along with the user sentiment analysis results. 【0754】 (Example 2) 【0755】 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". 【0756】 In construction ordering operations, the challenge is to streamline the ordering process and improve the user experience by simplifying procedures and information processing that tend to cause stress for users, and by automating appropriate responses that respond to user emotions. In particular, conventional systems do not take user emotions into consideration, which leads to a problem of user dissatisfaction and stress accumulating. 【0757】 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. 【0758】 In this invention, the server includes emotion recognition means for analyzing the user's facial expressions and voice to identify their emotional state, means for providing a user interface that is dynamically adjusted according to the identified emotional state, and means for placing orders with selected construction organizations and evaluating and updating historical data after the completion of construction. This makes it possible to efficiently utilize the user's emotional information, select an appropriate construction company, and provide a user interface that reduces the burden on the user. 【0759】 "Construction order conditions" refer to the detailed requirements specified by the user when requesting construction work, and include information such as the type of work, desired schedule, budget, and location. 【0760】 A "construction company" refers to a business contracted to carry out construction work, and is a corporation or individual selected according to the specific details of the construction work. 【0761】 "Emotion recognition means" refers to technology or devices that can identify a user's emotional state by analyzing their facial expressions and voice. 【0762】 "User interface" refers to the operating environment in which the user directly interacts, including screen displays and operating methods for exchanging information between the system and the user. 【0763】 A "purchase order" is a document that formally records the details of a construction request from the user to the construction company, and clearly outlines the contract terms. 【0764】 "Historical data" refers to past performance and evaluation information of construction companies, and is used for selecting and evaluating construction companies. 【0765】 This invention is a system for improving user experience and the efficiency of construction ordering operations. This system utilizes emotion recognition technology and includes a process for selecting the most suitable construction company based on user input information. 【0766】 When a user uses the system, they first input construction order conditions through a terminal. The terminal sends the input conditions to the server, while simultaneously using a built-in emotion engine to capture the user's facial expressions and voice in real time and perform emotion recognition. For specific emotion recognition, the system uses a camera and microphone, and utilizes image processing and speech analysis software such as OpenCV and TensorFlow. 【0767】 The server integrates user input data and emotional information to filter information on construction companies and select the most suitable one. The selection process considers the construction company's historical data and operational status. Furthermore, it dynamically adjusts the user interface based on emotional information to provide appropriate information tailored to the user's psychological state. 【0768】 As a concrete example, if a user experiencing the system for the first time feels anxious, the system uses an emotion engine to recognize this anxiety and displays guided instructions through the interface. This allows the user to proceed with the process with confidence. 【0769】 An example of a prompt message to the system would be: "Please provide guidelines for selecting the most suitable construction company based on construction order conditions and user sentiment information, and designing an interface to propose it to the user." This prompt message is used as an instruction to the generating AI model. 【0770】 The system of the present invention considers user emotions as an important factor and provides appropriate feedback, thereby streamlining the ordering process and improving user satisfaction. 【0771】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0772】 Step 1: 【0773】 The user enters the construction order conditions using a terminal. Specifically, they enter information such as the type of construction, desired dates, budget, and location into a form displayed on the screen. The entered data is temporarily stored on the terminal and used for subsequent processing. 【0774】 Step 2: 【0775】 The terminal uses an emotion engine to capture the user's facial expressions and voice based on the order conditions entered by the user. Image data captured by the camera and audio data recorded by the microphone are passed to analysis software. OpenCV and TensorFlow are used to identify the user's emotions from this data. The input is image data and audio data, and the output is an emotional state (e.g., reassured, anxious, stressed). 【0776】 Step 3: 【0777】 The terminal collects the user's order conditions and sentiment information and sends it to the server. A secure protocol (e.g., HTTPS) is used for transmission. In this process, the input is the user's order conditions and sentiment information, and the output is the integrated data sent to the server. 【0778】 Step 4: 【0779】 The server analyzes the transmitted data and compares it against a database of construction companies. A filtering algorithm is then used to select candidate construction companies that meet the specified criteria. The input is the integrated data, and the output is a list of construction companies that meet the criteria. 【0780】 Step 5: 【0781】 The server dynamically adjusts the user interface based on the selection results, taking into account the user's emotional information. For example, if the user indicates anxiety, it generates an interface that includes detailed explanations and guide messages. The input is a list of construction companies and emotional information, and the output is the adjusted user interface. 【0782】 Step 6: 【0783】 The server ultimately generates the purchase order and places the order with the selected construction company. The purchase order is a formal document containing the details of the work, conditions, and information about the construction company, and is sent electronically to the construction company. The input is the construction company's information and the order conditions, and the output is the generated purchase order. 【0784】 (Application Example 2) 【0785】 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". 【0786】 In the process of ordering work, a system is needed that appropriately reflects the emotional state of users and improves their experience. Especially in fields where emotions are a crucial element, such as caregiving, it is essential to select the most suitable service provider while considering the user's feelings, ensuring that users can proceed with the process comfortably. Furthermore, efficient means are needed to reduce the anxiety and stress experienced by users and enable smoother work execution. 【0787】 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. 【0788】 In this invention, the server includes means for filtering information on performers based on input work order conditions, means for selecting the most suitable performer from the filtered performers based on work performance and operational status, and means for recognizing the user's emotions and applying dynamic adjustments based on that information to the user connection surface. This enables a work order process that reflects the user's emotional state, thereby improving the user experience. 【0789】 "Work order conditions" refer to the specific work content and conditions required of the person performing the work. 【0790】 "Implementer" refers to the individual or group that actually carries out the work, and is the entity that receives the order and performs the work. 【0791】 The "user interface" refers to the interface through which users interact with the system, and is a connection point designed to enhance usability. 【0792】 "Recognizing emotions" refers to the process of detecting and analyzing a user's emotional state from their facial expressions and voice. 【0793】 "Dynamic adjustment" refers to the automatic modification of a system's interface and behavior in response to conditions such as the user's emotional state. 【0794】 "Post-performance history documentation" refers to information such as the performer's past work performance and evaluations, which is recorded after the work is completed. 【0795】 In this invention, the user's terminal accepts the input work order conditions, filters the information of the person performing the work, and selects the most suitable person. In this process, the terminal analyzes the user's facial expressions and voice, and recognizes the user's emotional state using an emotion engine. The emotional information is transmitted to a server, which applies dynamic adjustments to the user connection surface according to the emotion. This reduces the user's anxiety and stress, providing a comfortable user experience. 【0796】 The server selects the most suitable service provider for the user, taking into account their work history and operational status. After selection, the order details are presented to the user via the user connection, and the details can be modified as needed. Furthermore, after the work is completed, the service provider's performance history is evaluated and used for future use. 【0797】 This system utilizes standard webcams and smartphones, and the emotion recognition algorithm employs existing image processing libraries such as OpenCV. Furthermore, suggestions based on emotion information are generated using a generative AI model on the server. 【0798】 As a concrete example, the system recognizes in real time the anxiety that residents show through their facial expressions within a nursing home and makes suggestions to the residents, such as, "How about this music when you want to relax?" Examples of prompts to be input into the generating AI model include, "What should be said to an elderly person whose facial expression indicates anxiety?" 【0799】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0800】 Step 1: 【0801】 The terminal receives the work order conditions from the user. The data entered here (e.g., work details, desired dates, budget, etc.) is prepared to be sent to the server for subsequent processes. 【0802】 Step 2: 【0803】 The device uses its camera to collect image and audio data from the user. This data is analyzed by an emotion engine to identify the user's emotional state. This process uses image processing libraries such as OpenCV to analyze the data, and emotional information is obtained as output. 【0804】 Step 3: 【0805】 The server filters the information of the performers based on the sentiment information and work order conditions received. Specifically, it extracts performers from the database who meet conditions such as work performance and operational status, and obtains that data as the filtered result. 【0806】 Step 4: 【0807】 The server selects the most suitable implementer from the filtering results. This process also considers an interface designed to reduce user stress by utilizing emotional information. Based on the selection results, detailed information about the chosen implementer is generated and output. 【0808】 Step 5: 【0809】 The server uses a generative AI model to create suggestions tailored to the user's emotional state. The system generates prompts, which are then input into the generative AI model to obtain interface information, including appropriate suggestions and guidance. 【0810】 Step 6: 【0811】 The terminal displays the obtained implementer information and proposed interface information to the user. The user reviews the order details based on this information and makes any necessary corrections. Finally, the finalized order information is sent to the server. 【0812】 Step 7: 【0813】 The server generates a purchase order and places it with the selected contractor. Simultaneously, after the work is completed, it updates the contractor's performance history to keep the system data up-to-date. 【0814】 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. 【0815】 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. 【0816】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0817】 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. 【0818】 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. 【0819】 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. 【0820】 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. 【0821】 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. 【0822】 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." 【0823】 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. 【0824】 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. 【0825】 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. 【0826】 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. 【0827】 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. 【0828】 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. 【0829】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0830】 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. 【0831】 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. 【0832】 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. 【0833】 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. 【0834】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0835】 The following is further disclosed regarding the embodiments described above. 【0836】 (Claim 1) 【0837】 A means for filtering information on construction companies based on the entered construction order conditions, 【0838】 A method for selecting the most suitable construction company from a filtered list of construction companies based on their track record and operational status, 【0839】 A means of providing a user interface that allows users to review order details and make modifications as needed, 【0840】 A means of generating purchase orders and placing orders with selected construction companies, 【0841】 A system that includes a means of evaluating and updating the construction company's historical data after the completion of construction work. 【0842】 (Claim 2) 【0843】 The system according to claim 1, which calculates the travel distance of the construction company and adjusts the load accordingly. 【0844】 (Claim 3) 【0845】 The system according to claim 1, which tracks the operational status of construction companies in real time during an emergency and automatically selects a construction company that can respond quickly. 【0846】 "Example 1" 【0847】 (Claim 1) 【0848】 A means for filtering group information based on the entered plan conditions, 【0849】 A method for selecting the most suitable organization from the filtered organizations based on their work history and work status, 【0850】 A means to provide a configuration that allows for reviewing the plan and making modifications as needed, 【0851】 A means of generating purchase orders and executing orders to selected organizations, 【0852】 A means of evaluating and updating the organization's historical data after the work is completed, 【0853】 A means to support planning decisions for the next time based on the evaluation results, 【0854】 A means of appropriately allocating groups with specific skills and qualifications, 【0855】 A system that includes this. 【0856】 (Claim 2) 【0857】 The system according to claim 1, which calculates the distance traveled by a group and adjusts the load accordingly. 【0858】 (Claim 3) 【0859】 The system according to claim 1, which tracks the work status of organizations in real time and automatically selects an organization that can respond quickly. 【0860】 "Application Example 1" 【0861】 (Claim 1) 【0862】 A means for filtering contractor information based on the entered construction order conditions, 【0863】 A method for selecting the most suitable contractor from a filtered list of contractors based on their construction history and usage status, 【0864】 A means of providing a human-machine interface that allows for the confirmation and modification of order information as needed, 【0865】 A means of generating order instructions and placing orders with selected construction companies, 【0866】 A means of evaluating and updating the construction company's history information after the completion of construction, 【0867】 A method for recommending construction companies to human operators, taking into account geographical information and the construction companies' schedules, 【0868】 A means to enable users to easily complete the ordering process, 【0869】 A system that includes this. 【0870】 (Claim 2) 【0871】 The system according to claim 1, which calculates the travel distance of the construction workers and adjusts their workload accordingly. 【0872】 (Claim 3) 【0873】 The system according to claim 1, which tracks the availability of contractors in real time during an emergency and automatically selects a contractor capable of responding quickly. 【0874】 "Example 2 of combining an emotion engine" 【0875】 (Claim 1) 【0876】 A means for filtering information on construction companies based on the entered construction order conditions, 【0877】 A means of selecting the optimal construction organization from filtered construction information based on historical data and operational status, 【0878】 An emotion recognition means that analyzes the user's facial expressions and voice to identify their emotional state, 【0879】 A means for providing a user interface that is dynamically adjusted according to the identified emotional state, 【0880】 A means of providing a user interface that allows users to review order details and make modifications as needed, 【0881】 A means of generating purchase orders and issuing orders to selected construction organizations, 【0882】 A system that includes a means of evaluating and updating the construction company's historical data after the completion of construction work. 【0883】 (Claim 2) 【0884】 The system according to claim 1, which provides a more user-friendly interface based on identified emotional states and reduces the burden on the user. 【0885】 (Claim 3) 【0886】 The system according to claim 1, which takes into account the user's emotional state and improves the ordering process based on real-time feedback. 【0887】 "Application example 2 when combining with an emotional engine" 【0888】 (Claim 1) 【0889】 A means for filtering the information of the person performing the work based on the entered work order conditions, 【0890】 A means of selecting the most suitable implementer from a filtered pool of implementers based on their work performance and operational status, 【0891】 A means of providing a user interface that allows users to check order details and make modifications as needed, 【0892】 A means of generating purchase orders and placing orders with selected implementers, 【0893】 A means for recognizing user emotions and applying dynamic adjustments based on that information to the user connection surface, 【0894】 A system that provides optimal suggestions based on user sentiment information and includes a means to evaluate and update the provider's historical data after the work is completed. 【0895】 (Claim 2) 【0896】 The system according to claim 1, which calculates the distance traveled by the operator and adjusts the load accordingly. 【0897】 (Claim 3) 【0898】 The system according to claim 1, which tracks the operational status of implementers in real time during an emergency and automatically selects implementers who can respond quickly. [Explanation of symbols] 【0899】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means for filtering information on construction companies based on the entered construction order conditions, A method for selecting the most suitable construction company from a filtered list of construction companies based on their track record and operational status, A means of providing a user interface that allows users to review order details and make modifications as needed, A means of generating purchase orders and placing orders with selected construction companies, A system that includes a means of evaluating and updating the construction company's historical data after the completion of construction work. [Claim 2] The system according to claim 1, which calculates the travel distance of the construction company and adjusts the load accordingly. [Claim 3] The system according to claim 1, which tracks the operational status of construction companies in real time during an emergency and automatically selects a construction company that can respond quickly.

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