System

Abstract

An object of a system according to an embodiment is to effectively perform mental care and support of a crew.SOLUTION: A system includes a registration part, a support part, a care part, and a chat part. The registration unit registers personal information of a crew. The support unit provides support and advice based on the registration information of the crew based on the information registered by the registration unit. The care unit performs the mental care of the crew based on the support and advice provided by the support unit. The chat part provides the crew with the result of the mental care performed by the care part.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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 Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology does not provide sufficient mental care and support for crew members, and there is room for improvement in preventing them from leaving the company and becoming isolated.

[0005] The system according to the embodiment aims to effectively provide mental care and support to crew members. [Means for solving the problem]

[0006] The system according to the embodiment includes a registration unit, a support unit, a care unit, and a chat unit. The registration unit registers personal information of the crew. The support unit provides support and advice based on the information registered by the registration unit and the crew's registered information. The care unit provides mental care to the crew based on the support and advice provided by the support unit. The chat unit provides the crew with the results of the mental care provided by the care unit. [Effects of the Invention]

[0007] The system according to the embodiment can effectively provide mental care and support to crew members. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

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

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0024] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

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

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

[0028] (Example 1) A crew management system according to an embodiment of the present invention registers personal information of crew members, provides support and advice tailored to their individual circumstances, and provides the results of mental care to crew members. The crew management system aims to support crew members experiencing anxiety and isolation, ultimately preventing them from leaving the company or becoming isolated. For example, in the crew management system, crew members register their personal information in an AI system and assign it to them exclusively. This allows the AI ​​to provide an effective approach to crew mental care and support. The AI ​​is implanted in each individual's work terminal and can be set to be available only during working hours, rather than 24 hours a day. Crew members can communicate with the AI ​​through conversational chat. This conversational chat is also expected to develop crew members' communication skills, allowing them to develop skills essential in today's world. This allows the crew management system to promote crew mental care and growth, improving overall team performance and teamwork. This allows crew members to work with peace of mind and achieve individual growth. For example, crew members can confide in the AI ​​about worries and anxieties that they cannot discuss with their superiors or colleagues. The AI ​​provides support and advice tailored to each individual's situation, supporting the crew's mental care. Through mental care and follow-up for growth, we can prevent employee turnover and isolation and improve overall team performance and teamwork.

[0029] A crew management system according to an embodiment includes a registration unit, a support unit, a care unit, and a chat unit. The registration unit registers personal information of crew members. The personal information of crew members includes, but is not limited to, names, addresses, contact information, and work history. For example, the registration unit stores the personal information entered by the crew members in a database. The registration unit can also update the personal information of crew members. For example, when a crew member registers new contact information, the registration unit updates the existing information. The support unit provides support and advice tailored to the crew members' individual situations based on the information registered by the registration unit. Examples of support and advice include, but are not limited to, technical support and psychological advice. For example, the support unit provides technical support tailored to the crew members' work duties. The support unit can also provide advice tailored to the crew members' psychological states. The care unit provides mental care to the crew members based on the support and advice provided by the support unit. Examples of mental care include, but are not limited to, counseling and stress management. For example, the care unit evaluates the crew members' stress levels and provides appropriate mental care. The care unit can also monitor the psychological state of the crew and adjust mental care as necessary. The chat unit provides the crew with the results of the mental care provided by the care unit. The chat unit communicates with the crew in the form of, for example, text chat, voice chat, video chat, or the like. For example, the chat unit notifies the crew of the results of the mental care by text message. The chat unit can also follow up on the mental care through video chat with the crew. As a result, the crew management system according to the embodiment can register the personal information of the crew, provide support and advice according to the individual situation, provide mental care, and provide the results to the crew.

[0030] The support department can provide support and advice tailored to the crew's individual circumstances. Examples of individual circumstances include, but are not limited to, the crew's work content, psychological state, and living environment. The support department can provide, for example, technical support tailored to the crew's work content. For example, when a crew member uses new software, the support department explains how to operate it. The support department can also provide advice tailored to the crew member's psychological state. For example, if a crew member is feeling stressed, the support department can advise them on how to manage their stress. The support department can also provide support tailored to the crew member's living environment. For example, if a crew member is working from home, the support department can provide advice on how to improve the efficiency of working from home. This allows the support department to provide more appropriate support by providing support and advice tailored to the crew member's individual circumstances.

[0031] The care department can provide mental care for crew members. Examples of mental care include, but are not limited to, counseling and stress management. For example, the care department can assess the stress level of crew members and provide appropriate mental care. For example, if a crew member is experiencing high stress, the care department can suggest ways to help them relax. The care department can also monitor the crew member's psychological state and adjust mental care as needed. For example, if the crew member's psychological state does not improve, the care department can increase the frequency of counseling. The care department can also record the results of the crew member's mental care and use the results for future care. For example, the care department can store the crew member's mental care history in a database and select the optimal care method based on the past care results. In this way, the care department can support the crew member's mental health by providing mental care.

[0032] The chat department can communicate with the crew through conversational chat. The chat department communicates with the crew in the form of, for example, text chat, voice chat, video chat, or the like. For example, the chat department notifies the crew of the results of mental care via a text message. The chat department can also follow up on the mental care through video chat with the crew. For example, if the crew has any questions about the results of mental care, the chat department can answer them in real time. The chat department can also support the development of the crew's communication skills. For example, the chat department provides training for the crew to learn effective communication skills. As a result, the chat department can improve the crew's communication skills by communicating with the crew through conversational chat.

[0033] The registration unit can analyze the crew's past behavior history and select the optimal registration method. Past behavior history includes, for example, work history, chat history, feedback history, etc., but is not limited to these examples. For example, if the crew preferred voice input in the past, the registration unit recommends voice input. For example, if the crew frequently used text input in the past, the registration unit recommends text input. Furthermore, if the crew used image input in the past, the registration unit can also recommend image input. For example, the registration unit selects the optimal registration method based on the crew's past behavior history. In this way, the registration unit can provide the optimal registration method by analyzing the crew's past behavior history.

[0034] When registering personal information, the registration unit can filter the information based on the crew member's current work situation and areas of interest. Examples of work situation include, but are not limited to, current projects, task progress, etc. Examples of areas of interest include, but are not limited to, past research themes, hobbies, and topics of interest. For example, the registration unit prioritizes registering only information necessary for the crew member's current work. For example, the registration unit prioritizes registering information related to the crew member's areas of interest. The registration unit can also filter and register unnecessary information according to the crew member's work situation. For example, the registration unit registers only necessary information taking into account the crew member's work schedule. In this way, the registration unit can register only necessary information by filtering information according to the crew member's work situation and areas of interest.

[0035] When registering personal information, the registration unit can select the optimal registration means depending on the crew's input method. Input methods include, but are not limited to, voice input, text input, and image input. For example, if the crew desires voice input, the registration unit provides voice input preferentially. For example, if the crew desires text input, the registration unit can provide text input preferentially. Furthermore, if the crew desires image input, the registration unit can also provide image input preferentially. For example, the registration unit selects the optimal registration means depending on the crew's input method. As a result, the registration unit provides the optimal registration means depending on the crew's input method, thereby making information registration more efficient.

[0036] When registering personal information, the registration unit can prioritize registering relevant information taking into account the crew's geographical location information. Geographical location information includes, but is not limited to, GPS data, IP addresses, etc. For example, if the crew is in a specific area, the registration unit prioritizes registering information related to that area. For example, if the crew is on a business trip, the registration unit prioritizes registering information related to the business trip destination. Furthermore, if the crew is at home, the registration unit can also prioritize registering information related to the crew's home. For example, the registration unit prioritizes registering highly relevant information taking into account the crew's geographical location information. As a result, the registration unit can provide more appropriate information by prioritizing registering highly relevant information based on the crew's geographical location information.

[0037] When registering personal information, the registration unit can analyze the crew's social media activity and register related information. Social media activity includes, but is not limited to, for example, posted content, like history, follower information, etc. The registration unit registers related personal information based on information shared by the crew on social media. For example, the registration unit analyzes the crew's social media activity and registers related information. The registration unit can also register related information with reference to the activities of the crew's friends on social media. For example, the registration unit analyzes the crew's social media activity and efficiently registers related information. In this way, the registration unit can efficiently register related information by analyzing the crew's social media activity.

[0038] When registering personal information, the registration unit can customize the registration method by reflecting the crew's past feedback. Feedback includes, but is not limited to, for example, survey results, comments, and ratings. The registration unit, for example, suggests the optimal registration method based on feedback provided by the crew in the past. For example, the registration unit simplifies the registration procedure by reflecting the crew's past feedback. The registration unit can also customize the registration interface by referring to the crew's past feedback. For example, the registration unit provides the optimal registration method based on the crew's feedback. In this way, the registration unit can provide the optimal registration method by reflecting the crew's past feedback.

[0039] When providing support, the support department can adjust the level of detail of the support based on the importance of the crew. The importance level includes, but is not limited to, the priority of the work and the urgency of the work. For example, the support department provides detailed support when the crew is in charge of an important work. For example, the support department provides basic support when the crew is performing daily work. The support department can also provide quick and concise support when the crew is responding to an emergency. For example, the support department adjusts the level of detail of the support based on the importance of the crew. This allows the support department to provide more appropriate support by adjusting the level of detail of the support according to the importance of the crew.

[0040] When providing support, the support department can apply different support algorithms depending on the crew category. Examples of categories include, but are not limited to, business categories, technical categories, and psychological categories. For example, the support department applies a basic support algorithm to new employees. For example, the support department applies an applied support algorithm to mid-level employees. The support department can also apply a strategic support algorithm to managers. For example, the support department applies different support algorithms depending on the crew category. This allows the support department to provide more appropriate support by applying different support algorithms depending on the crew category.

[0041] When providing support, the support unit can improve the accuracy of the support by referring to the crew's past support results. Past support results include, but are not limited to, support history, feedback results, etc. For example, the support unit analyzes the results of support the crew has received in the past and provides optimal support. For example, the support unit customizes the support content based on the crew's past support results. The support unit can also improve the support algorithm by referring to the crew's past support results. For example, the support unit improves the accuracy of support based on the crew's past support results. In this way, the support unit improves the accuracy of support by referring to the crew's past support results.

[0042] When providing support, the support department can determine the priority of support based on the time of submission by the crew. The submission time includes, but is not limited to, for example, the submission date, submission time, and submission deadline. For example, the support department responds with priority when the crew needs urgent support. For example, the support department responds with normal priority when the crew needs regular support. In addition, the support department can also respond in a planned manner when the crew needs long-term support. For example, the support department determines the priority of support based on the time of submission by the crew. In this way, the support department can provide more appropriate support by determining the priority of support based on the time of submission by the crew.

[0043] When providing support, the support department can adjust the order of support based on the relevance of the crew. Relevance includes, but is not limited to, for example, job relevance, technical relevance, etc. For example, the support department prioritizes providing support related to the crew's current job. For example, the support department plans to provide support that the crew will need in the future. The support department can also adjust the order taking into account the relevance of support that the crew has received in the past. For example, the support department adjusts the order of support based on the relevance of the crew. This allows the support department to provide more appropriate support by adjusting the order of support based on the relevance of the crew.

[0044] When providing support, the support department can adjust the use of support terminology according to the crew's level of expertise. Examples of expertise level include, but are not limited to, qualifications, years of experience, and past work history. For example, if the crew is a beginner, the support department can provide support by avoiding technical terms. For example, if the crew is an intermediate level crew member, the support department can provide support using basic technical terms. Furthermore, if the crew is an advanced level crew member, the support department can provide support using detailed technical terms. For example, the support department can adjust the use of support terminology according to the crew's level of expertise. This allows the support department to provide more appropriate support by adjusting the use of support terminology according to the crew's level of expertise.

[0045] When providing mental care, the care department can analyze the crew's past behavior and select the optimal care method. Past behavior includes, but is not limited to, work history, chat history, and feedback history. The care department selects the optimal care method, for example, based on the results of mental care that the crew received in the past. For example, the care department analyzes the crew's past behavior patterns and selects the optimal care method. The care department can also select the optimal care method by referring to the crew's past feedback. For example, the care department analyzes the crew's past behavior and provides the optimal care method. In this way, the care department can provide the optimal care method by analyzing the crew's past behavior.

[0046] When providing mental care, the care department can customize the care measures based on the crew member's current living situation. Examples of living situations include, but are not limited to, the crew member's home environment, health condition, and lifestyle. For example, if the crew member is busy, the care department can provide effective mental care in a short amount of time. For example, if the crew member is relaxed, the care department can provide detailed mental care. Furthermore, if the crew member is feeling stressed, the care department can provide mental care to reduce stress. For example, the care department customizes the care measures based on the crew member's living situation. This allows the care department to provide more appropriate mental care by customizing the care measures based on the crew member's current living situation.

[0047] The care department can improve the care method by reflecting crew feedback during mental care. Feedback includes, but is not limited to, for example, survey results, comments, and evaluations. The care department improves the mental care method, for example, based on the feedback provided by the crew. For example, the care department customizes the care method by reflecting the crew feedback. The care department can also improve the care algorithm by referring to the crew feedback. For example, the care department provides the optimal care method based on the crew feedback. In this way, the care department can improve the care method by reflecting the crew feedback.

[0048] When providing mental care, the care department can select the optimal care method by taking into account the crew's geographical location information. Geographical location information includes, but is not limited to, GPS data, IP address, etc. For example, if the crew is in an office, the care department provides a care method appropriate for the office environment. For example, if the crew is at home, the care department provides a care method appropriate for the home environment. Furthermore, if the crew is on a business trip, the care department can also provide a care method appropriate for the environment of the business trip destination. For example, the care department selects the optimal care method by taking into account the crew's geographical location information. As a result, the care department can provide more appropriate mental care by providing the optimal care method based on the crew's geographical location information.

[0049] During mental care, the care department can analyze the crew's social media activity and suggest care methods. Social media activity includes, but is not limited to, for example, post content, like history, follower information, etc. The care department can suggest optimal care methods based on information shared by the crew on social media. For example, the care department can analyze the crew's social media activity and suggest related care methods. The care department can also suggest optimal care methods based on the activity of the crew's friends on social media. For example, the care department can analyze the crew's social media activity and suggest optimal care methods. In this way, the care department can provide optimal care methods by analyzing the crew's social media activity.

[0050] During mental care, the care department can customize the care method by reflecting the crew's past feedback. Feedback includes, but is not limited to, for example, survey results, comments, and evaluations. The care department, for example, proposes the optimal care method based on the crew's past feedback. For example, the care department customizes the care method by reflecting the crew's past feedback. The care department can also improve the care algorithm by referring to the crew's past feedback. For example, the care department provides the optimal care method based on the crew's feedback. In this way, the care department can provide the optimal care method by reflecting the crew's past feedback.

[0051] When displaying chat, the chat unit can select the optimal display method by referring to the crew member's past operation history. The operation history includes, but is not limited to, for example, click history, operation time, and operation sequence. The chat unit provides the optimal display method based on, for example, a display method that the crew member has preferred in the past. For example, the chat unit analyzes the crew member's past operation history and suggests the optimal display method. The chat unit can also customize the display interface by referring to the crew member's past operation history. For example, the chat unit provides the optimal display method based on the crew member's operation history. In this way, the chat unit can provide the optimal display method by referring to the crew member's past operation history.

[0052] When displaying chat, the chat section can customize the display content according to the crew's current task. Examples of tasks include, but are not limited to, project tasks, daily work tasks, etc. The chat section, for example, prioritizes displaying information related to the crew's current task. For example, the chat section filters and displays unnecessary information according to the crew's current task. The chat section can also provide optimal display content based on the crew's current task. For example, the chat section displays only necessary information according to the crew's task. In this way, the chat section can provide more appropriate information by customizing the display content according to the crew's current task.

[0053] The chat unit can improve the display method by reflecting crew feedback when displaying chat. Examples of feedback include, but are not limited to, survey results, comments, and ratings. The chat unit improves the display method based on, for example, the feedback provided by the crew. For example, the chat unit customizes the display interface by reflecting the crew feedback. The chat unit can also improve the display algorithm by referring to the crew feedback. For example, the chat unit provides the optimal display method based on the crew feedback. In this way, the chat unit can improve the display method by reflecting the crew feedback.

[0054] When displaying chat, the chat unit can select the optimal display method by taking into consideration the crew member's device information. Device information includes, but is not limited to, the device type, OS, browser information, etc. For example, if the crew member is using a smartphone, the chat unit provides a display method that matches the screen size. For example, if the crew member is using a tablet, the chat unit provides a display method optimized for a large screen. Furthermore, if the crew member is using a smartwatch, the chat unit can provide a simple and highly visible display method. For example, the chat unit selects the optimal display method by taking into consideration the crew member's device information. As a result, the chat unit can provide a more appropriate display by providing the optimal display method based on the crew member's device information.

[0055] When displaying chat, the chat unit can make the display content multilingual according to the crew's language setting. Language settings include, but are not limited to, the language used and regional settings. For example, the chat unit automatically sets the chat language based on the language setting of the crew's device. For example, the chat unit provides a language switching function when the crew uses multiple languages. Furthermore, if the crew selects a specific language, the chat unit can provide chat in that language. For example, the chat unit makes the display content multilingual according to the crew's language setting. This allows the chat unit to display more appropriately by making the display content multilingual according to the crew's language setting.

[0056] When displaying chat, the chat unit can customize the display method by reflecting the crew's past feedback. Feedback includes, but is not limited to, for example, survey results, comments, and ratings. The chat unit improves the display method, for example, based on the feedback provided by the crew. For example, the chat unit customizes the display interface by reflecting the crew's feedback. The chat unit can also improve the display algorithm by referring to the crew's feedback. For example, the chat unit provides the optimal display method based on the crew's feedback. This allows the chat unit to customize the display method by reflecting the crew's past feedback.

[0057] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0058] The crew management system can further include a "feedback unit." The feedback unit collects feedback from the crew and uses it to improve the system as a whole. For example, the feedback unit analyzes survey results and comments provided by the crew and improves the system's functions and interface. The feedback unit can also improve the quality of services provided by the support unit and care unit based on the crew's feedback. Furthermore, the feedback unit can reflect the crew's feedback in real time and immediately implement improvements. In this way, the feedback unit can improve the usability of the system as a whole by reflecting the crew's opinions.

[0059] The care department can utilize crew lifestyle data when providing mental care to crew members. For example, the care department can analyze crew members' sleep patterns and meal records to provide appropriate mental care. The care department can also suggest stress management methods taking into account the crew members' exercise habits. Furthermore, the care department can create long-term mental care plans based on the crew members' lifestyle data. This allows the care department to provide more personalized mental care by utilizing the crew members' lifestyle data.

[0060] The crew management system can further include a "notification unit." The notification unit provides important information and reminders to crew members. For example, the notification unit can send meeting reminders based on the crew's schedule. The notification unit can also notify task deadlines based on the crew's work progress. Furthermore, the notification unit can notify crew members of regular check-ins as a follow-up for their mental health care. In this way, the notification unit can support work efficiency and continued mental health care by providing important information and reminders to crew members.

[0061] The registration unit can analyze the crew's past behavioral history and suggest the optimal timing for registration. For example, if the crew has tended to register information at night in the past, the registration unit can send a notification encouraging them to register at night. Also, if the crew often registers information on weekends, the registration unit can also send a notification encouraging them to register on weekends. Furthermore, if the crew registers information concentratedly during a specific time period, the registration unit can also send a notification encouraging them to register during that time period. In this way, the registration unit can suggest the optimal timing for registration based on the crew's past behavioral history, thereby making information registration more efficient.

[0062] When providing mental care to crew members, the care department can propose care methods that take into account the crew member's hobbies and interests. For example, if a crew member likes music, the care department can suggest relaxing music. If a crew member likes exercise, the care department can also suggest exercise to relieve stress. Furthermore, if a crew member likes reading, the care department can also suggest relaxing reading time. In this way, the care department can provide more individualized mental care by proposing care methods that take into account the crew member's hobbies and interests.

[0063] The processing flow of the first embodiment will be briefly explained below.

[0064] Step 1: The registration unit registers the crew member's personal information. The crew member's personal information includes, for example, name, address, contact information, and work history. The registration unit saves the personal information entered by the crew member in a database and can update it as needed. For example, if a crew member registers new contact information, the registration unit updates the existing information. Step 2: The Support Department provides support and advice tailored to the crew's individual circumstances based on the information registered by the Registration Department. Support and advice includes technical support and psychological advice. For example, technical support tailored to the crew's duties and advice tailored to their psychological state are provided. Step 3: The Care Department provides mental care for the crew based on the support and advice provided by the Support Department. Mental care includes counseling and stress management. For example, it assesses the crew's stress level and provides appropriate mental care. It also monitors the crew's psychological state and adjusts mental care as needed. Step 4: The chat department provides the crew with the results of the mental care provided by the care department. The chat department communicates with the crew in the form of text chat, voice chat, video chat, etc. For example, the chat department notifies the crew of the results of the mental care by text message or follows up via video chat.

[0065] (Example 2) A crew management system according to an embodiment of the present invention registers personal information of crew members, provides support and advice tailored to their individual circumstances, and provides the results of mental care to crew members. The crew management system aims to support crew members experiencing anxiety and isolation, ultimately preventing them from leaving the company or becoming isolated. For example, in the crew management system, crew members register their personal information in an AI system and assign it to them exclusively. This allows the AI ​​to provide an effective approach to crew mental care and support. The AI ​​is implanted in each individual's work terminal and can be set to be available only during working hours, rather than 24 hours a day. Crew members can communicate with the AI ​​through conversational chat. This conversational chat is also expected to develop crew members' communication skills, allowing them to develop skills essential in today's world. This allows the crew management system to promote crew mental care and growth, improving overall team performance and teamwork. This allows crew members to work with peace of mind and achieve individual growth. For example, crew members can confide in the AI ​​about worries and anxieties that they cannot discuss with their superiors or colleagues. The AI ​​provides support and advice tailored to each individual's situation, supporting the crew's mental care. Through mental care and follow-up for growth, we can prevent employee turnover and isolation and improve overall team performance and teamwork.

[0066] A crew management system according to an embodiment includes a registration unit, a support unit, a care unit, and a chat unit. The registration unit registers personal information of crew members. The personal information of crew members includes, but is not limited to, names, addresses, contact information, and work history. For example, the registration unit stores the personal information entered by the crew members in a database. The registration unit can also update the personal information of crew members. For example, when a crew member registers new contact information, the registration unit updates the existing information. The support unit provides support and advice tailored to the crew members' individual situations based on the information registered by the registration unit. Examples of support and advice include, but are not limited to, technical support and psychological advice. For example, the support unit provides technical support tailored to the crew members' work duties. The support unit can also provide advice tailored to the crew members' psychological states. The care unit provides mental care to the crew members based on the support and advice provided by the support unit. Examples of mental care include, but are not limited to, counseling and stress management. For example, the care unit evaluates the crew members' stress levels and provides appropriate mental care. The care unit can also monitor the psychological state of the crew and adjust mental care as necessary. The chat unit provides the crew with the results of the mental care provided by the care unit. The chat unit communicates with the crew in the form of, for example, text chat, voice chat, video chat, or the like. For example, the chat unit notifies the crew of the results of the mental care by text message. The chat unit can also follow up on the mental care through video chat with the crew. As a result, the crew management system according to the embodiment can register the personal information of the crew, provide support and advice according to the individual situation, provide mental care, and provide the results to the crew.

[0067] The support department can provide support and advice tailored to the crew's individual circumstances. Examples of individual circumstances include, but are not limited to, the crew's work content, psychological state, and living environment. The support department can provide, for example, technical support tailored to the crew's work content. For example, when a crew member uses new software, the support department explains how to operate it. The support department can also provide advice tailored to the crew member's psychological state. For example, if a crew member is feeling stressed, the support department can advise them on how to manage their stress. The support department can also provide support tailored to the crew member's living environment. For example, if a crew member is working from home, the support department can provide advice on how to improve the efficiency of working from home. This allows the support department to provide more appropriate support by providing support and advice tailored to the crew member's individual circumstances.

[0068] The care department can provide mental care for crew members. Examples of mental care include, but are not limited to, counseling and stress management. For example, the care department can assess the stress level of crew members and provide appropriate mental care. For example, if a crew member is experiencing high stress, the care department can suggest ways to help them relax. The care department can also monitor the crew member's psychological state and adjust mental care as needed. For example, if the crew member's psychological state does not improve, the care department can increase the frequency of counseling. The care department can also record the results of the crew member's mental care and use the results for future care. For example, the care department can store the crew member's mental care history in a database and select the optimal care method based on the past care results. In this way, the care department can support the crew member's mental health by providing mental care.

[0069] The chat department can communicate with the crew through conversational chat. The chat department communicates with the crew in the form of, for example, text chat, voice chat, video chat, or the like. For example, the chat department notifies the crew of the results of mental care via a text message. The chat department can also follow up on the mental care through video chat with the crew. For example, if the crew has any questions about the results of mental care, the chat department can answer them in real time. The chat department can also support the development of the crew's communication skills. For example, the chat department provides training for the crew to learn effective communication skills. As a result, the chat department can improve the crew's communication skills by communicating with the crew through conversational chat.

[0070] The registration unit can estimate the crew member's emotions and adjust the timing of registering personal information based on the estimated crew member's emotions. Emotion estimation is achieved, for example, by using an emotion estimation function using an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if a crew member is feeling stressed, the registration unit prompts the crew member to register personal information during a time when they can relax. For example, if a crew member is relaxed, the registration unit prompts the crew member to register personal information immediately. Furthermore, if a crew member is busy, the registration unit can prompt the crew member to register personal information when work has calmed down. For example, the registration unit prompts the crew member to register personal information at the optimal timing, taking into account the crew member's work schedule. In this way, the registration unit can adjust the timing of registering personal information according to the crew member's emotions, thereby registering information at a more appropriate time.

[0071] The registration unit can analyze the crew's past behavior history and select the optimal registration method. Past behavior history includes, for example, work history, chat history, feedback history, etc., but is not limited to these examples. For example, if the crew preferred voice input in the past, the registration unit recommends voice input. For example, if the crew frequently used text input in the past, the registration unit recommends text input. Furthermore, if the crew used image input in the past, the registration unit can also recommend image input. For example, the registration unit selects the optimal registration method based on the crew's past behavior history. In this way, the registration unit can provide the optimal registration method by analyzing the crew's past behavior history.

[0072] When registering personal information, the registration unit can filter the information based on the crew member's current work situation and areas of interest. Examples of work situation include, but are not limited to, current projects, task progress, etc. Examples of areas of interest include, but are not limited to, past research themes, hobbies, and topics of interest. For example, the registration unit prioritizes registering only information necessary for the crew member's current work. For example, the registration unit prioritizes registering information related to the crew member's areas of interest. The registration unit can also filter and register unnecessary information according to the crew member's work situation. For example, the registration unit registers only necessary information taking into account the crew member's work schedule. In this way, the registration unit can register only necessary information by filtering information according to the crew member's work situation and areas of interest.

[0073] When registering personal information, the registration unit can select the optimal registration means depending on the crew's input method. Input methods include, but are not limited to, voice input, text input, and image input. For example, if the crew desires voice input, the registration unit provides voice input preferentially. For example, if the crew desires text input, the registration unit can provide text input preferentially. Furthermore, if the crew desires image input, the registration unit can also provide image input preferentially. For example, the registration unit selects the optimal registration means depending on the crew's input method. As a result, the registration unit provides the optimal registration means depending on the crew's input method, thereby making information registration more efficient.

[0074] The registration unit can estimate the crew's emotions and determine the priority of information to be registered based on the estimated crew's emotions. Emotion estimation is achieved, for example, by using an emotion estimation function using an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the crew is feeling stressed, the registration unit prioritizes registering only important information. For example, if the crew is relaxed, the registration unit prioritizes registering detailed information. Furthermore, if the crew is busy, the registration unit can prioritize registering the minimum necessary information. For example, the registration unit prioritizes information according to the crew's emotions. As a result, the registration unit can prioritize registering important information by determining the priority of information according to the crew's emotions.

[0075] When registering personal information, the registration unit can prioritize registering relevant information taking into account the crew's geographical location information. Geographical location information includes, but is not limited to, GPS data, IP addresses, etc. For example, if the crew is in a specific area, the registration unit prioritizes registering information related to that area. For example, if the crew is on a business trip, the registration unit prioritizes registering information related to the business trip destination. Furthermore, if the crew is at home, the registration unit can also prioritize registering information related to the crew's home. For example, the registration unit prioritizes registering highly relevant information taking into account the crew's geographical location information. As a result, the registration unit can provide more appropriate information by prioritizing registering highly relevant information based on the crew's geographical location information.

[0076] When registering personal information, the registration unit can analyze the crew's social media activity and register related information. Social media activity includes, but is not limited to, for example, posted content, like history, follower information, etc. The registration unit registers related personal information based on information shared by the crew on social media. For example, the registration unit analyzes the crew's social media activity and registers related information. The registration unit can also register related information with reference to the activities of the crew's friends on social media. For example, the registration unit analyzes the crew's social media activity and efficiently registers related information. In this way, the registration unit can efficiently register related information by analyzing the crew's social media activity.

[0077] When registering personal information, the registration unit can customize the registration method by reflecting the crew's past feedback. Feedback includes, but is not limited to, for example, survey results, comments, and ratings. The registration unit, for example, suggests the optimal registration method based on feedback provided by the crew in the past. For example, the registration unit simplifies the registration procedure by reflecting the crew's past feedback. The registration unit can also customize the registration interface by referring to the crew's past feedback. For example, the registration unit provides the optimal registration method based on the crew's feedback. In this way, the registration unit can provide the optimal registration method by reflecting the crew's past feedback.

[0078] The support unit can estimate the crew member's emotions and adjust the way in which support is expressed based on the estimated crew member's emotions. Emotion estimation is achieved, for example, using an emotion estimation function using an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the crew member is nervous, the support unit provides support in a calm tone. For example, if the crew member is relaxed, the support unit provides support in a bright tone. Furthermore, if the crew member is feeling stressed, the support unit can provide simple and easy-to-understand support. For example, the support unit adjusts the way in which support is expressed depending on the crew member's emotions. This allows the support unit to provide more appropriate support by adjusting the way in which support is expressed depending on the crew member's emotions.

[0079] When providing support, the support department can adjust the level of detail of the support based on the importance of the crew. The importance level includes, but is not limited to, the priority of the work and the urgency of the work. For example, the support department provides detailed support when the crew is in charge of an important work. For example, the support department provides basic support when the crew is performing daily work. The support department can also provide quick and concise support when the crew is responding to an emergency. For example, the support department adjusts the level of detail of the support based on the importance of the crew. This allows the support department to provide more appropriate support by adjusting the level of detail of the support according to the importance of the crew.

[0080] When providing support, the support department can apply different support algorithms depending on the crew category. Examples of categories include, but are not limited to, business categories, technical categories, and psychological categories. For example, the support department applies a basic support algorithm to new employees. For example, the support department applies an applied support algorithm to mid-level employees. The support department can also apply a strategic support algorithm to managers. For example, the support department applies different support algorithms depending on the crew category. This allows the support department to provide more appropriate support by applying different support algorithms depending on the crew category.

[0081] When providing support, the support unit can improve the accuracy of the support by referring to the crew's past support results. Past support results include, but are not limited to, support history, feedback results, etc. For example, the support unit analyzes the results of support the crew has received in the past and provides optimal support. For example, the support unit customizes the support content based on the crew's past support results. The support unit can also improve the support algorithm by referring to the crew's past support results. For example, the support unit improves the accuracy of support based on the crew's past support results. In this way, the support unit improves the accuracy of support by referring to the crew's past support results.

[0082] The support unit can estimate the crew member's emotions and adjust the length of support based on the estimated crew member's emotions. Emotion estimation is achieved, for example, using an emotion estimation function using an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the crew member is nervous, the support unit can provide short, to-the-point support. For example, if the crew member is relaxed, the support unit can provide detailed support. Furthermore, if the crew member is feeling stressed, the support unit can provide simple, easy-to-understand support. For example, the support unit can adjust the length of support according to the crew member's emotions. This allows the support unit to provide more appropriate support by adjusting the length of support according to the crew member's emotions.

[0083] When providing support, the support department can determine the priority of support based on the time of submission by the crew. The submission time includes, but is not limited to, for example, the submission date, submission time, and submission deadline. For example, the support department responds with priority when the crew needs urgent support. For example, the support department responds with normal priority when the crew needs regular support. In addition, the support department can also respond in a planned manner when the crew needs long-term support. For example, the support department determines the priority of support based on the time of submission by the crew. In this way, the support department can provide more appropriate support by determining the priority of support based on the time of submission by the crew.

[0084] When providing support, the support department can adjust the order of support based on the relevance of the crew. Relevance includes, but is not limited to, for example, job relevance, technical relevance, etc. For example, the support department prioritizes providing support related to the crew's current job. For example, the support department plans to provide support that the crew will need in the future. The support department can also adjust the order taking into account the relevance of support that the crew has received in the past. For example, the support department adjusts the order of support based on the relevance of the crew. This allows the support department to provide more appropriate support by adjusting the order of support based on the relevance of the crew.

[0085] When providing support, the support department can adjust the use of support terminology according to the crew's level of expertise. Examples of expertise level include, but are not limited to, qualifications, years of experience, and past work history. For example, if the crew is a beginner, the support department can provide support by avoiding technical terms. For example, if the crew is an intermediate level crew member, the support department can provide support using basic technical terms. Furthermore, if the crew is an advanced level crew member, the support department can provide support using detailed technical terms. For example, the support department can adjust the use of support terminology according to the crew's level of expertise. This allows the support department to provide more appropriate support by adjusting the use of support terminology according to the crew's level of expertise.

[0086] The care department can estimate the crew's emotions and adjust the mental care method based on the estimated crew's emotions. Emotion estimation is achieved, for example, using an emotion estimation function using an emotion engine or generative AI. The generative AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the crew is tense, the care department provides mental care that helps them relax. For example, if the crew is relaxed, the care department provides proactive mental care. Furthermore, if the crew is feeling stressed, the care department can also provide mental care to reduce stress. For example, the care department adjusts the mental care method according to the crew's emotions. This allows the care department to provide more appropriate mental care by adjusting the mental care method according to the crew's emotions.

[0087] When providing mental care, the care department can analyze the crew's past behavior and select the optimal care method. Past behavior includes, but is not limited to, work history, chat history, and feedback history. The care department selects the optimal care method, for example, based on the results of mental care that the crew received in the past. For example, the care department analyzes the crew's past behavior patterns and selects the optimal care method. The care department can also select the optimal care method by referring to the crew's past feedback. For example, the care department analyzes the crew's past behavior and provides the optimal care method. In this way, the care department can provide the optimal care method by analyzing the crew's past behavior.

[0088] When providing mental care, the care department can customize the care measures based on the crew member's current living situation. Examples of living situations include, but are not limited to, the crew member's home environment, health condition, and lifestyle. For example, if the crew member is busy, the care department can provide effective mental care in a short amount of time. For example, if the crew member is relaxed, the care department can provide detailed mental care. Furthermore, if the crew member is feeling stressed, the care department can provide mental care to reduce stress. For example, the care department customizes the care measures based on the crew member's living situation. This allows the care department to provide more appropriate mental care by customizing the care measures based on the crew member's current living situation.

[0089] The care department can improve the care method by reflecting crew feedback during mental care. Feedback includes, but is not limited to, for example, survey results, comments, and evaluations. The care department improves the mental care method, for example, based on the feedback provided by the crew. For example, the care department customizes the care method by reflecting the crew feedback. The care department can also improve the care algorithm by referring to the crew feedback. For example, the care department provides the optimal care method based on the crew feedback. In this way, the care department can improve the care method by reflecting the crew feedback.

[0090] The care department can estimate the crew's emotions and determine care priorities based on the estimated crew's emotions. Emotion estimation is achieved, for example, by using an emotion estimation function using an emotion engine or generative AI. The generative AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, the care department provides care with priority when the crew is feeling highly stressed. For example, the care department provides care with normal priority when the crew is feeling mildly stressed. The care department can also provide regular care when the crew is relaxed. For example, the care department determines care priorities according to the crew's emotions. This allows the care department to provide more appropriate care by determining care priorities according to the crew's emotions.

[0091] When providing mental care, the care department can select the optimal care method by taking into account the crew's geographical location information. Geographical location information includes, but is not limited to, GPS data, IP address, etc. For example, if the crew is in an office, the care department provides a care method appropriate for the office environment. For example, if the crew is at home, the care department provides a care method appropriate for the home environment. Furthermore, if the crew is on a business trip, the care department can also provide a care method appropriate for the environment of the business trip destination. For example, the care department selects the optimal care method by taking into account the crew's geographical location information. As a result, the care department can provide more appropriate mental care by providing the optimal care method based on the crew's geographical location information.

[0092] During mental care, the care department can analyze the crew's social media activity and suggest care methods. Social media activity includes, but is not limited to, for example, post content, like history, follower information, etc. The care department can suggest optimal care methods based on information shared by the crew on social media. For example, the care department can analyze the crew's social media activity and suggest related care methods. The care department can also suggest optimal care methods based on the activity of the crew's friends on social media. For example, the care department can analyze the crew's social media activity and suggest optimal care methods. In this way, the care department can provide optimal care methods by analyzing the crew's social media activity.

[0093] During mental care, the care department can customize the care method by reflecting the crew's past feedback. Feedback includes, but is not limited to, for example, survey results, comments, and evaluations. The care department, for example, proposes the optimal care method based on the crew's past feedback. For example, the care department customizes the care method by reflecting the crew's past feedback. The care department can also improve the care algorithm by referring to the crew's past feedback. For example, the care department provides the optimal care method based on the crew's feedback. In this way, the care department can provide the optimal care method by reflecting the crew's past feedback.

[0094] The chat unit can estimate the crew member's emotions and adjust the chat display method based on the estimated crew member's emotions. Emotion estimation is achieved, for example, by using an emotion estimation function using an emotion engine or generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the crew member is nervous, the chat unit provides a simple, highly visible display method. For example, if the crew member is relaxed, the chat unit provides a display method including detailed information. Furthermore, if the crew member is feeling stressed, the chat unit can also provide a display method for stress reduction. For example, the chat unit adjusts the chat display method according to the crew member's emotions. As a result, the chat unit can adjust the chat display method according to the crew member's emotions, thereby enabling a more appropriate display.

[0095] When displaying chat, the chat unit can select the optimal display method by referring to the crew member's past operation history. The operation history includes, but is not limited to, for example, click history, operation time, and operation sequence. The chat unit provides the optimal display method based on, for example, a display method that the crew member has preferred in the past. For example, the chat unit analyzes the crew member's past operation history and suggests the optimal display method. The chat unit can also customize the display interface by referring to the crew member's past operation history. For example, the chat unit provides the optimal display method based on the crew member's operation history. In this way, the chat unit can provide the optimal display method by referring to the crew member's past operation history.

[0096] When displaying chat, the chat section can customize the display content according to the crew's current task. Examples of tasks include, but are not limited to, project tasks, daily work tasks, etc. The chat section, for example, prioritizes displaying information related to the crew's current task. For example, the chat section filters and displays unnecessary information according to the crew's current task. The chat section can also provide optimal display content based on the crew's current task. For example, the chat section displays only necessary information according to the crew's task. In this way, the chat section can provide more appropriate information by customizing the display content according to the crew's current task.

[0097] The chat unit can improve the display method by reflecting crew feedback when displaying chat. Examples of feedback include, but are not limited to, survey results, comments, and ratings. The chat unit improves the display method based on, for example, the feedback provided by the crew. For example, the chat unit customizes the display interface by reflecting the crew feedback. The chat unit can also improve the display algorithm by referring to the crew feedback. For example, the chat unit provides the optimal display method based on the crew feedback. In this way, the chat unit can improve the display method by reflecting the crew feedback.

[0098] The chat unit can estimate the crew member's emotions and adjust chat operation procedures based on the estimated crew member's emotions. Emotion estimation is achieved, for example, by using an emotion estimation function using an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. For example, if the crew member is nervous, the chat unit can provide simple and intuitive operation procedures. For example, if the crew member is relaxed, the chat unit can provide detailed operation procedures. Furthermore, if the crew member is feeling stressed, the chat unit can provide operation procedures for stress reduction. For example, the chat unit can adjust the chat operation procedures according to the crew member's emotions. This allows the chat unit to adjust the chat operation procedures according to the crew member's emotions, enabling more appropriate operation.

[0099] When displaying chat, the chat unit can select the optimal display method by taking into consideration the crew member's device information. Device information includes, but is not limited to, the device type, OS, browser information, etc. For example, if the crew member is using a smartphone, the chat unit provides a display method that matches the screen size. For example, if the crew member is using a tablet, the chat unit provides a display method optimized for a large screen. Furthermore, if the crew member is using a smartwatch, the chat unit can provide a simple and highly visible display method. For example, the chat unit selects the optimal display method by taking into consideration the crew member's device information. As a result, the chat unit can provide a more appropriate display by providing the optimal display method based on the crew member's device information.

[0100] When displaying chat, the chat unit can make the display content multilingual according to the crew's language setting. Language settings include, but are not limited to, the language used and regional settings. For example, the chat unit automatically sets the chat language based on the language setting of the crew's device. For example, the chat unit provides a language switching function when the crew uses multiple languages. Furthermore, if the crew selects a specific language, the chat unit can provide chat in that language. For example, the chat unit makes the display content multilingual according to the crew's language setting. This allows the chat unit to display more appropriately by making the display content multilingual according to the crew's language setting.

[0101] When displaying chat, the chat unit can customize the display method by reflecting the crew's past feedback. Feedback includes, but is not limited to, for example, survey results, comments, and ratings. The chat unit improves the display method, for example, based on the feedback provided by the crew. For example, the chat unit customizes the display interface by reflecting the crew's feedback. The chat unit can also improve the display algorithm by referring to the crew's feedback. For example, the chat unit provides the optimal display method based on the crew's feedback. This allows the chat unit to customize the display method by reflecting the crew's past feedback. === Hard Collateral 1-1 === Each of the multiple elements including the registration unit, support unit, care unit, and chat unit described above is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the registration unit is realized by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing device 12. For example, the crew's personal information is input through the reception device 38 of the smart device 14 and stored in the database 24 of the data processing device 12. The support unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides support and advice according to the crew's individual situation. The care unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides mental care for the crew. The chat unit is realized, for example, by the control unit 46A of the smart device 14 and communicates with the crew. === Hard Collateral 1-2 === Each of the multiple elements including the registration unit, support unit, care unit, and chat unit described above is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the registration unit is realized by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing device 12. For example, the crew member's personal information is input through the microphone 238 of the smart glasses 214 and stored in the database 24 of the data processing device 12. The support unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides support and advice according to the crew member's individual situation. The care unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides mental care for the crew member. The chat unit is realized, for example, by the control unit 46A of the smart glasses 214 and communicates with the crew member. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned registration unit, support unit, care unit, and chat unit is realized, for example, by at least one of the headset-type terminal 314 and the data processing device 12. For example, the registration unit is realized by the control unit 46A of the headset-type terminal 314 or the specific processing unit 290 of the data processing device 12. For example, the crew's personal information is input through the microphone 238 of the headset-type terminal 314 and stored in the database 24 of the data processing device 12. The support unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and provides support and advice according to the crew's individual situation. The care unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and provides mental care for the crew. The chat unit is realized, for example, by the control unit 46A of the headset-type terminal 314, and communicates with the crew. === Hard Collateral 1-4 === Each of the multiple elements including the registration unit, support unit, care unit, and chat unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the registration unit is realized by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing device 12. For example, the crew member's personal information is input through the microphone 238 of the robot 414 and stored in the database 24 of the data processing device 12. The support unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and provides support and advice according to the crew member's individual situation. The care unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and provides mental care for the crew member. The chat unit is realized, for example, by the control unit 46A of the robot 414, and communicates with the crew member.

[0102] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0103] The crew management system can further include a "feedback unit." The feedback unit collects feedback from the crew and uses it to improve the system as a whole. For example, the feedback unit analyzes survey results and comments provided by the crew and improves the system's functions and interface. The feedback unit can also improve the quality of services provided by the support unit and care unit based on the crew's feedback. Furthermore, the feedback unit can reflect the crew's feedback in real time and immediately implement improvements. In this way, the feedback unit can improve the usability of the system as a whole by reflecting the crew's opinions.

[0104] The support department can estimate the crew's emotions and customize the content of support based on the estimated crew's emotions. For example, if the crew is feeling anxious, the support department can provide support that gives them a sense of security. If the crew wants to increase their motivation, the support department can also provide encouragement and goal-setting support. Furthermore, if the crew is tired, the support department can also provide support that helps them relax. This allows the support department to provide more effective support by customizing the content of support according to the crew's emotions.

[0105] The care department can utilize crew lifestyle data when providing mental care to crew members. For example, the care department can analyze crew members' sleep patterns and meal records to provide appropriate mental care. The care department can also suggest stress management methods taking into account the crew members' exercise habits. Furthermore, the care department can create long-term mental care plans based on the crew members' lifestyle data. This allows the care department to provide more personalized mental care by utilizing the crew members' lifestyle data.

[0106] The chat unit can estimate the crew member's emotions and adjust the tone of the chat based on the estimated crew member's emotions. For example, if the crew member is nervous, the chat unit can send a message in a calm tone. If the crew member is relaxed, the chat unit can also send a message in a bright tone. Furthermore, if the crew member is feeling stressed, the chat unit can also send a simple, easy-to-understand message. In this way, the chat unit can achieve more appropriate communication by adjusting the tone of the chat according to the crew member's emotions.

[0107] The registration unit can estimate the crew member's emotions and suggest a method for registering personal information based on the estimated crew member's emotions. For example, if the crew member is feeling stressed, the registration unit can suggest an easy and intuitive registration method. Also, if the crew member is relaxed, the registration unit can suggest a method for entering detailed information. Furthermore, if the crew member is busy, the registration unit can suggest a simplified registration method that allows the crew member to add information later. In this way, the registration unit can realize a smoother registration process by suggesting a method for registering personal information according to the crew member's emotions.

[0108] The crew management system can further include a "notification unit." The notification unit provides important information and reminders to crew members. For example, the notification unit can send meeting reminders based on the crew's schedule. The notification unit can also notify task deadlines based on the crew's work progress. Furthermore, the notification unit can notify crew members of regular check-ins as a follow-up for their mental health care. In this way, the notification unit can support work efficiency and continued mental health care by providing important information and reminders to crew members.

[0109] The registration unit can analyze the crew's past behavioral history and suggest the optimal timing for registration. For example, if the crew has tended to register information at night in the past, the registration unit can send a notification encouraging them to register at night. Also, if the crew often registers information on weekends, the registration unit can also send a notification encouraging them to register on weekends. Furthermore, if the crew registers information concentratedly during a specific time period, the registration unit can also send a notification encouraging them to register during that time period. In this way, the registration unit can suggest the optimal timing for registration based on the crew's past behavioral history, thereby making information registration more efficient.

[0110] The support department can estimate the crew's emotions and adjust the frequency of support based on the estimated crew's emotions. For example, if the crew is feeling high stress, the support department can provide support frequently. Also, if the crew is relaxed, the support department can provide support as needed. Furthermore, if the crew wants to increase their motivation, the support department can periodically send encouraging messages. This allows the support department to provide more effective support by adjusting the frequency of support according to the crew's emotions.

[0111] When providing mental care to crew members, the care department can propose care methods that take into account the crew member's hobbies and interests. For example, if a crew member likes music, the care department can suggest relaxing music. If a crew member likes exercise, the care department can also suggest exercise to relieve stress. Furthermore, if a crew member likes reading, the care department can also suggest relaxing reading time. In this way, the care department can provide more individualized mental care by proposing care methods that take into account the crew member's hobbies and interests.

[0112] The chat unit can estimate the crew's emotions and adjust the content of the chat based on the estimated crew's emotions. For example, if the crew is feeling anxious, the chat unit can send a message that gives them a sense of security. Also, if the crew wants to increase their motivation, the chat unit can send an encouraging message. Furthermore, if the crew is tired, the chat unit can send a message that helps them relax. In this way, the chat unit can achieve more appropriate communication by adjusting the content of the chat according to the crew's emotions.

[0113] The processing flow of the second embodiment will be briefly explained below.

[0114] Step 1: The registration unit registers the crew member's personal information. The crew member's personal information includes, for example, name, address, contact information, and work history. The registration unit saves the personal information entered by the crew member in a database and can update it as needed. For example, if a crew member registers new contact information, the registration unit updates the existing information. Step 2: The Support Department provides support and advice tailored to the crew's individual circumstances based on the information registered by the Registration Department. Support and advice includes technical support and psychological advice. For example, technical support tailored to the crew's duties and advice tailored to their psychological state are provided. Step 3: The Care Department provides mental care for the crew based on the support and advice provided by the Support Department. Mental care includes counseling and stress management. For example, it assesses the crew's stress level and provides appropriate mental care. It also monitors the crew's psychological state and adjusts mental care as needed. Step 4: The chat department provides the crew with the results of the mental care provided by the care department. The chat department communicates with the crew in the form of text chat, voice chat, video chat, etc. For example, the chat department notifies the crew of the results of the mental care by text message or follows up via video chat.

[0115] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0116] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0117] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0118] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0119] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0120] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0121] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0122] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0123] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0124] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0125] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0126] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0127] 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.

[0128] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0129] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0130] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0131] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0132] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0133] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0134] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0135] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0136] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0137] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0138] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0139] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0140] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0141] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0142] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0143] 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.

[0144] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0145] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0146] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0147] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0148] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0149] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0150] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0151] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0152] 7, a 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.

[0153] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0154] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0155] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0156] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0157] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0158] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0159] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0160] 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.

[0161] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0162] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0163] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0164] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0165] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0166] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0167] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0168] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0169] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0170] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0171] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0172] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0173] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0174] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0175] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0176] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0177] 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.

[0178] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0179] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0180] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific process may be a single processor.

[0181] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0182] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0183] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0184] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0185] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0186] [Explanation of symbols]

[0187] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a registration section for registering personal information of crew members; a support unit that provides support and advice based on the crew's registered information based on the information registered by the registration unit; a care department that provides mental care to crew members based on the support and advice provided by the support department; a chat unit that provides the crew with the results of the mental care provided by the care unit. A system characterized by:

2. The support portion is Providing support and advice tailored to each crew member's individual situation 2. The system of claim 1.

3. The care unit includes: Providing mental care for crew members 2. The system of claim 1.

4. The chat section Communicate with crew members through conversational chat 2. The system of claim 1.

5. The registration unit Estimate the crew's emotions and adjust the timing of registering personal information based on the estimated crew's emotions 2. The system of claim 1.

6. The registration unit Analyze the crew's past behavior history and select the appropriate registration method 2. The system of claim 1.

7. The registration unit When registering personal information, filter based on the crew's current work status and interests 2. The system of claim 1.

8. The registration unit When registering personal information, select the most appropriate registration method depending on the crew's input method.

2. The system of claim 1.

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