System

Abstract

An object of a system according to an embodiment is to collectively process a moving procedure and reduce a burden on an applicant and a business operator.SOLUTION: A system includes a moving procedure batch processing part, a business efficiency improvement part, a moving out report procedure part, a visit reservation part, and a sufferer request grasping part. A moving procedure batch processing part processes a moving procedure in a batch. The business efficiency improvement unit improves business efficiency of the business operator. A moving out report procedure part performs the procedure of the moving out report online. A visit reservation part reserves a visit schedule online. The victim's needs grasping unit grasps the needs of victims at the time of a natural disaster.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 has the problem that moving procedures are complicated and place a heavy burden on applicants and businesses.

[0005] The system according to the embodiment aims to process moving procedures all at once, thereby reducing the burden on applicants and businesses. [Means for solving the problem]

[0006] The system according to the embodiment comprises a bulk moving procedure processing unit, a business efficiency improvement unit, a moving-out notification processing unit, a visit reservation unit, and a disaster victim request understanding unit. The bulk moving procedure processing unit processes moving procedures in bulk. The business efficiency improvement unit improves the business efficiency of businesses. The moving-out notification processing unit processes moving-out notifications online. The visit reservation unit makes online reservations for visits to the office. The disaster victim request understanding unit understands the requests of disaster victims in the event of a natural disaster. [Effects of the Invention]

[0007] The system according to the embodiment can process moving procedures all at once, thereby reducing the burden on applicants and businesses. [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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[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 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[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) The system for streamlining relocation procedures according to an embodiment of the present invention uses a national smartphone app to streamline procedures for relocating. By consolidating the complicated relocation procedures that span both government and private sectors, this system reduces the burden on applicants, improves business efficiency, and improves resident services provided by local governments. It also includes functions for online procedures for moving-out notifications and appointments, and efficiently grasps the needs of disaster victims in the event of a natural disaster. This system reduces the procedural burden on applicants, streamlines business efficiency, and improves resident services provided by local governments.

[0029] The system for streamlining relocation procedures according to the embodiment includes a bulk moving procedure processing unit, a business efficiency improvement unit, a moving-out notification processing unit, a visit reservation unit, and a disaster victim request understanding unit. The bulk moving procedure processing unit processes moving procedures in bulk. For example, it can transfer residence registration, change electricity, gas, and water contracts, and process mail forwarding all at once. The business efficiency unit improves the business's business efficiency. For example, a generation AI manages the progress of various procedures in real time and automatically notifies relevant parties of necessary information. The moving-out notification processing unit processes moving-out notifications online. For example, when a user enters the address of the new address and the planned moving-out date on the app, the generation AI analyzes the information and automatically generates the necessary documents. The visit reservation unit schedules visits online. For example, when a user enters the desired date and time of visit on the app, the generation AI analyzes the information and confirms the reservation in cooperation with the local government's reservation system. The disaster victim request understanding unit understands the requests of disaster victims in the event of a natural disaster. For example, when a disaster victim enters information about the relief supplies and evacuation locations they need on the app, the AI ​​analyzes that information and automatically notifies local governments and aid organizations. This enables the residential relocation procedure efficiency system to streamline moving procedures, improve business efficiency, improve resident services, and enable rapid response in the event of a natural disaster.

[0030] The bulk moving procedure processing unit can analyze the user's past moving history and propose the optimal procedure order. For example, the bulk moving procedure processing unit uses a generation AI to analyze the user's past moving history and propose the optimal procedure order. For example, it automatically generates an efficient procedure order taking into account problems and procedural delays that occurred in past moves. This reduces the burden on the user by proposing the optimal procedure order based on past moving history.

[0031] The bulk moving procedure processing unit can provide individually customized procedures taking into account the user's lifestyle and family composition. For example, the generation AI can provide individually customized procedures taking into account the user's lifestyle and family composition. For example, school transfer procedures can be given priority for families with children. This allows for procedures customized to the user's lifestyle and family composition, thereby improving the efficiency of the procedures and increasing user satisfaction.

[0032] The bulk processing unit for moving procedures can include procedures for moving pets and procedures for transferring to a new school. The bulk processing unit for moving procedures can also include procedures for moving pets. For example, the bulk processing unit for moving procedures can automatically list the documents and procedures required for moving a pet. This reduces the burden of procedures on the user by including procedures for moving pets and procedures for transferring to a new school.

[0033] The bulk moving procedure processing unit can also handle overseas moves. The bulk moving procedure processing unit can also handle overseas moves. For example, it can automatically list the visas and customs procedures required for overseas moves. This allows it to handle overseas moves, reducing the procedural burden on users.

[0034] The business efficiency improvement unit can analyze a business operator's business processes, identify bottlenecks, and propose improvements. For example, the business efficiency improvement unit uses a generation AI to analyze a business operator's business processes, identify bottlenecks, and propose improvements. For example, it can detect delays and duplications in procedures and propose efficient processes. This allows the business operator's business processes to be analyzed, bottlenecks to be identified, and improvements to be proposed, thereby improving business efficiency.

[0035] The business efficiency improvement unit can analyze usage data for resident services and predict demand for services. For example, the business efficiency improvement unit uses a generation AI to analyze usage data for resident services and predict demand for services. For example, future demand is predicted based on past usage data. In this way, the quality of services is improved by analyzing usage data for resident services and predicting demand.

[0036] The business efficiency improvement unit can also include the business of logistics companies and moving companies. The business efficiency improvement unit, for example, also includes the business of logistics companies and moving companies. For example, it optimizes the delivery schedule of logistics companies. In this way, by including the business of logistics companies and moving companies, business efficiency is improved.

[0037] The Business Efficiency Improvement Department can also include services provided by medical institutions and educational institutions in improving resident services. For example, the Business Efficiency Improvement Department can automate the reservation systems of medical institutions and the admission procedures of educational institutions. By including the services of medical institutions and educational institutions, the quality of resident services can be improved.

[0038] The moving-out notification procedure section can automatically digitally sign the necessary documents. For example, when the generation AI processes a moving-out notification, the moving-out notification procedure section automatically digitally signs the necessary documents. For example, the digital signature is generated based on information entered by the user. This allows the necessary documents to be automatically digitally signed, speeding up the process.

[0039] The moving-out notification procedure section can simplify the procedure by referring to the user's past address change history. For example, when the generation AI processes a moving-out notification, the moving-out notification procedure section simplifies the procedure by referring to the user's past address change history. For example, it automatically inputs the necessary information based on past address change data. This simplifies the procedure by referring to the past address change history, allowing the procedure to proceed more quickly.

[0040] The moving-out notification processing unit can also handle the online moving-out notification procedure as a moving-in notification procedure. The moving-out notification processing unit can, for example, handle the online moving-out notification procedure as a moving-in notification procedure. For example, by simply entering the address of the moving-out destination, the moving-in notification procedure can also be automatically performed. In this way, by handling the moving-out notification procedure as a moving-in notification procedure, the procedures can be completed in one go.

[0041] The moving out notification procedure unit can also accommodate the online moving out notification procedure with the company's address change procedure. The moving out notification procedure unit, for example, can also accommodate the online moving out notification procedure with the company's address change procedure. For example, it can automatically generate the documents required for the company's address change. This allows the company to also accommodate the company's address change procedure, allowing the procedures to be completed in one go.

[0042] The visit reservation department can analyze the user's schedule and suggest the optimal visit date and time. For example, the visit reservation department uses a generation AI to analyze the user's schedule and suggest the optimal visit date and time. For example, it can automatically suggest available dates and times based on the user's calendar information. This allows the visit procedure to proceed smoothly by analyzing the user's schedule and suggesting the optimal visit date and time.

[0043] The visit reservation department can analyze the congestion situation in a local government in real time and suggest a visit date and time that will avoid congestion. For example, the generation AI can analyze the congestion situation in a local government in real time and suggest a visit date and time that will avoid congestion. For example, it can automatically suggest a time period when it is less crowded. This allows the visit procedure to proceed smoothly by analyzing the congestion situation in a local government in real time and suggesting a visit date and time that will avoid congestion.

[0044] The Visitor Reservation Department can also make online reservations for visits compatible with hospital and school reservation systems. For example, the Visitor Reservation Department can analyze hospital reservation status in real time and suggest the optimal reservation date and time. By making it compatible with hospital and school reservation systems, the visit procedure can be carried out smoothly.

[0045] The Visitor Reservation Department can also make online reservations for visits compatible with public transportation reservation systems. For example, the Visitor Reservation Department can analyze bus and train reservation status in real time and suggest the optimal reservation date and time. By making it compatible with public transportation reservation systems, the visit procedure can be carried out smoothly.

[0046] The victim request understanding unit can analyze the requests of disaster victims and prioritize the most urgent requests. For example, the generation AI can analyze the requests of disaster victims and prioritize the most urgent requests. For example, it can automatically list the most urgent requests and respond to them quickly. This makes it possible to provide prompt support by analyzing the requests of disaster victims and prioritizing the most urgent requests.

[0047] The victim request understanding unit can analyze the location information of the victim and suggest the nearest support base. For example, the generation AI can analyze the location information of the victim and suggest the nearest support base. For example, the unit can automatically suggest the nearest evacuation shelter or support base based on the current location of the victim. This makes it possible to provide prompt support by analyzing the location information of the victim and suggesting the nearest support base.

[0048] The disaster victim request ascertainment unit can also adapt the ascertainment of disaster victim requests in the event of a natural disaster to preventive measures before a disaster occurs. The disaster victim request ascertainment unit, for example, adapts the ascertainment of disaster victim requests in the event of a natural disaster to preventive measures before a disaster occurs. For example, the unit automatically proposes preparations and evacuation plans required before a disaster occurs. This allows the safety of disaster victims to be ensured in advance by adapting the system to preventive measures before a disaster occurs.

[0049] The disaster victim request ascertaining unit can also adapt the ascertainment of disaster victim requests during natural disasters to other emergency situations (e.g., pandemics). The disaster victim request ascertaining unit can, for example, adapt the ascertainment of disaster victim requests during natural disasters to other emergency situations (e.g., pandemics). For example, it automatically lists support requests during pandemics. This allows the unit to respond to other emergency situations, making it possible to provide rapid support.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The system for streamlining residential relocation procedures can also include a health management unit that monitors the user's health and identifies health risks that may affect the progress of the relocation process. For example, if the user has a chronic illness, the system can adjust the relocation schedule based on that information. It can also advise the user to get adequate rest if the stress of moving is likely to have a negative impact on their health. It can also provide information about medical institutions in the relocation destination and arrange for necessary medical services in advance. This allows the relocation process to be completed with peace of mind, taking the user's health into consideration.

[0052] The system for streamlining residential relocation procedures can also include a local information provider that takes into account the user's hobbies and interests and provides local information about the area where the user is moving. For example, if the user likes sports, information about sports facilities and clubs in the area can be provided. If the user is interested in cultural activities, information about local events and museums can be provided. Furthermore, information about nearby parks and playgrounds can be provided for families with children. This allows the user to quickly become accustomed to their new living environment by providing local information tailored to their hobbies and interests.

[0053] The system for streamlining residential relocation procedures can also be equipped with a lifestyle support unit to support the user's life in their new home. For example, it can provide information on how to use public transportation at the new home and the nearest supermarket. It can also provide information on how to dispose of garbage at the new home and local rules. It can also provide information on emergency contacts and medical institutions at the new home. This helps the user adapt quickly to their new living environment.

[0054] The system for streamlining residential relocation procedures can also be equipped with a chat support section to respond in real time to users' questions and concerns regarding the relocation procedures. For example, if a user has a question during the process, they can ask a specialized support staff member via chat. The system also has an automated response function for frequently asked questions, providing quick answers. Furthermore, it can also switch to telephone support as needed. This eliminates any anxieties or questions the user may have during the process, allowing the process to proceed smoothly.

[0055] The system for streamlining home relocation procedures can also have a sharing function that allows the user to share the progress of the moving procedures with family and friends. For example, the user can share the progress of the procedures with family and friends and receive support. The user can also receive encouraging messages from family and friends as the procedures progress. Furthermore, when the procedures are completed, the user can share a sense of accomplishment with family and friends. This allows the user to proceed with the moving procedures while receiving support from family and friends.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The bulk moving procedure processing unit processes all moving procedures in one go. For example, you can transfer your residence registration, change your electricity, gas, and water contracts, and forward your mail all at once. Step 2: The Business Efficiency Department aims to improve the business efficiency of the business. For example, the generation AI manages the progress of various procedures in real time and automatically notifies relevant parties of necessary information. Step 3: The moving-out notification processing unit processes the moving-out notification online. For example, when a user enters the address of the new address and the planned moving-out date on the app, the generation AI analyzes that information and automatically generates the necessary documents. Step 4: The Visitor Reservation Department makes online reservations for visits. For example, when a user enters the desired date and time of visit on the app, the generation AI analyzes the information and connects with the local government's reservation system to confirm the reservation. Step 5: The disaster victim needs understanding unit understands the needs of disaster victims in the event of a natural disaster. For example, when a disaster victim enters information about necessary relief supplies and evacuation locations into the app, the generation AI analyzes the information and automatically notifies local governments and relief organizations.

[0058] (Example 2) The system for streamlining relocation procedures according to an embodiment of the present invention uses a national smartphone app to streamline procedures for relocating. By consolidating the complicated relocation procedures that span both government and private sectors, this system reduces the burden on applicants, improves business efficiency, and improves resident services provided by local governments. It also includes functions for online procedures for moving-out notifications and appointments, and efficiently grasps the needs of disaster victims in the event of a natural disaster. This system reduces the procedural burden on applicants, streamlines business efficiency, and improves resident services provided by local governments.

[0059] The system for streamlining relocation procedures according to the embodiment includes a bulk moving procedure processing unit, a business efficiency improvement unit, a moving-out notification processing unit, a visit reservation unit, and a disaster victim request understanding unit. The bulk moving procedure processing unit processes moving procedures in bulk. For example, it can transfer residence registration, change electricity, gas, and water contracts, and process mail forwarding all at once. The business efficiency unit improves the business's business efficiency. For example, a generation AI manages the progress of various procedures in real time and automatically notifies relevant parties of necessary information. The moving-out notification processing unit processes moving-out notifications online. For example, when a user enters the address of the new address and the planned moving-out date on the app, the generation AI analyzes the information and automatically generates the necessary documents. The visit reservation unit schedules visits online. For example, when a user enters the desired date and time of visit on the app, the generation AI analyzes the information and confirms the reservation in cooperation with the local government's reservation system. The disaster victim request understanding unit understands the requests of disaster victims in the event of a natural disaster. For example, when a disaster victim enters information about the relief supplies and evacuation locations they need on the app, the AI ​​analyzes that information and automatically notifies local governments and aid organizations. This enables the residential relocation procedure efficiency system to streamline moving procedures, improve business efficiency, improve resident services, and enable rapid response in the event of a natural disaster.

[0060] The bulk moving procedure processing unit can analyze the user's past moving history and propose the optimal procedure order. For example, the bulk moving procedure processing unit uses a generation AI to analyze the user's past moving history and propose the optimal procedure order. For example, it automatically generates an efficient procedure order taking into account problems and procedural delays that occurred in past moves. This reduces the burden on the user by proposing the optimal procedure order based on past moving history.

[0061] The bulk moving procedure processing unit can provide individually customized procedures taking into account the user's lifestyle and family composition. For example, the generation AI can provide individually customized procedures taking into account the user's lifestyle and family composition. For example, school transfer procedures can be given priority for families with children. This allows for procedures customized to the user's lifestyle and family composition, thereby improving the efficiency of the procedures and increasing user satisfaction.

[0062] The moving procedure batch processing unit can use the emotion estimation function to analyze the user's stress level and propose a procedure order to reduce stress. The moving procedure batch processing unit, for example, uses the emotion estimation function to analyze the user's stress level and propose a procedure order to reduce stress. For example, it postpones procedures that cause high stress. In this way, by analyzing the user's stress level and proposing a procedure order to reduce stress, the burden on the user is reduced.

[0063] The bulk processing unit for moving procedures can include procedures for moving pets and procedures for transferring to a new school. The bulk processing unit for moving procedures can also include procedures for moving pets. For example, the bulk processing unit for moving procedures can automatically list the documents and procedures required for moving a pet. This reduces the burden of procedures on the user by including procedures for moving pets and procedures for transferring to a new school.

[0064] The bulk moving procedure processing unit can also handle overseas moves. The bulk moving procedure processing unit can also handle overseas moves. For example, it can automatically list the visas and customs procedures required for overseas moves. This allows it to handle overseas moves, reducing the procedural burden on users.

[0065] The moving procedure bulk processing unit can use the emotion estimation function to provide advice to increase the user's motivation as they proceed with the moving procedure. The moving procedure bulk processing unit, for example, uses the emotion estimation function to provide advice to increase the user's motivation as they proceed with the moving procedure. For example, it presents encouraging messages and success stories. By providing advice to increase the user's motivation, the progress of the procedure is made smoother.

[0066] The business efficiency improvement unit can analyze a business operator's business processes, identify bottlenecks, and propose improvements. For example, the business efficiency improvement unit uses a generation AI to analyze a business operator's business processes, identify bottlenecks, and propose improvements. For example, it can detect delays and duplications in procedures and propose efficient processes. This allows the business operator's business processes to be analyzed, bottlenecks to be identified, and improvements to be proposed, thereby improving business efficiency.

[0067] The business efficiency improvement unit can analyze usage data for resident services and predict demand for services. For example, the business efficiency improvement unit uses a generation AI to analyze usage data for resident services and predict demand for services. For example, future demand is predicted based on past usage data. In this way, the quality of services is improved by analyzing usage data for resident services and predicting demand.

[0068] The business efficiency improvement unit can use the emotion estimation function to monitor resident satisfaction in real time and use the information to improve services. The business efficiency improvement unit, for example, uses the emotion estimation function to monitor resident satisfaction in real time and use the information to improve services. For example, it analyzes the emotional state of residents and makes improvement suggestions if satisfaction is low. In this way, resident satisfaction can be monitored in real time and used to improve services, thereby improving the quality of services for residents.

[0069] The business efficiency improvement unit can also include the business of logistics companies and moving companies. The business efficiency improvement unit, for example, also includes the business of logistics companies and moving companies. For example, it optimizes the delivery schedule of logistics companies. In this way, by including the business of logistics companies and moving companies, business efficiency is improved.

[0070] The Business Efficiency Improvement Department can also include services provided by medical institutions and educational institutions in improving resident services. For example, the Business Efficiency Improvement Department can automate the reservation systems of medical institutions and the admission procedures of educational institutions. By including the services of medical institutions and educational institutions, the quality of resident services can be improved.

[0071] The business efficiency improvement unit can use the emotion estimation function to identify the timing of service provision that will most satisfy the resident. The business efficiency improvement unit, for example, uses the emotion estimation function to identify the timing of service provision that will most satisfy the resident. For example, it analyzes the emotional state of the resident and suggests the optimal timing of service provision. In this way, the quality of resident services can be improved by identifying the timing of service provision that will most satisfy the resident.

[0072] The moving-out notification procedure section can automatically digitally sign the necessary documents. For example, when the generation AI processes a moving-out notification, the moving-out notification procedure section automatically digitally signs the necessary documents. For example, the digital signature is generated based on information entered by the user. This allows the necessary documents to be automatically digitally signed, speeding up the process.

[0073] The moving-out notification procedure section can simplify the procedure by referring to the user's past address change history. For example, when the generation AI processes a moving-out notification, the moving-out notification procedure section simplifies the procedure by referring to the user's past address change history. For example, it automatically inputs the necessary information based on past address change data. This simplifies the procedure by referring to the past address change history, allowing the procedure to proceed more quickly.

[0074] The moving-out notification procedure unit can use the emotion estimation function to provide support to reduce anxiety when the user is completing the moving-out notification procedure. The moving-out notification procedure unit, for example, uses the emotion estimation function to provide support to reduce anxiety when the user is completing the moving-out notification procedure. For example, it analyzes the user's emotional state and provides appropriate advice. This provides support to reduce the user's anxiety, allowing the procedure to proceed smoothly.

[0075] The moving-out notification processing unit can also handle the online moving-out notification procedure as a moving-in notification procedure. The moving-out notification processing unit can, for example, handle the online moving-out notification procedure as a moving-in notification procedure. For example, by simply entering the address of the moving-out destination, the moving-in notification procedure can also be automatically performed. In this way, by handling the moving-out notification procedure as a moving-in notification procedure, the procedures can be completed in one go.

[0076] The moving out notification procedure unit can also accommodate the online moving out notification procedure with the company's address change procedure. The moving out notification procedure unit, for example, can also accommodate the online moving out notification procedure with the company's address change procedure. For example, it can automatically generate the documents required for the company's address change. This allows the company to also accommodate the company's address change procedure, allowing the procedures to be completed in one go.

[0077] The moving-out notification procedure unit can use the emotion estimation function to provide advice to increase the user's motivation when completing the moving-out notification procedure. The moving-out notification procedure unit, for example, uses the emotion estimation function to provide advice to increase the user's motivation when completing the moving-out notification procedure. For example, encouraging messages or success stories are presented. By providing advice to increase the user's motivation, the procedure can be smoothly carried out.

[0078] The visit reservation department can analyze the user's schedule and suggest the optimal visit date and time. For example, the visit reservation department uses a generation AI to analyze the user's schedule and suggest the optimal visit date and time. For example, it can automatically suggest available dates and times based on the user's calendar information. This allows the visit procedure to proceed smoothly by analyzing the user's schedule and suggesting the optimal visit date and time.

[0079] The visit reservation department can analyze the congestion situation in a local government in real time and suggest a visit date and time that will avoid congestion. For example, the generation AI can analyze the congestion situation in a local government in real time and suggest a visit date and time that will avoid congestion. For example, it can automatically suggest a time period when it is less crowded. This allows the visit procedure to proceed smoothly by analyzing the congestion situation in a local government in real time and suggesting a visit date and time that will avoid congestion.

[0080] The office visit reservation unit can use the emotion estimation function to analyze the user's stress level and suggest a visit date and time that will reduce stress. The office visit reservation unit, for example, uses the emotion estimation function to analyze the user's stress level and suggest a visit date and time that will reduce stress. For example, it automatically suggests a time period that is less stressful. In this way, by analyzing the user's stress level and suggesting a visit date and time that will reduce stress, the office visit procedure can be smoothly carried out.

[0081] The Visitor Reservation Department can also make online reservations for visits compatible with hospital and school reservation systems. For example, the Visitor Reservation Department can analyze hospital reservation status in real time and suggest the optimal reservation date and time. By making it compatible with hospital and school reservation systems, the visit procedure can be carried out smoothly.

[0082] The Visitor Reservation Department can also make online reservations for visits compatible with public transportation reservation systems. For example, the Visitor Reservation Department can analyze bus and train reservation status in real time and suggest the optimal reservation date and time. By making it compatible with public transportation reservation systems, the visit procedure can be carried out smoothly.

[0083] The office visit reservation unit can use the emotion estimation function to provide advice to increase the user's motivation when reserving an office visit. The office visit reservation unit, for example, uses the emotion estimation function to provide advice to increase the user's motivation when reserving an office visit. For example, it presents encouraging messages and success stories. By providing advice to increase the user's motivation, the office visit procedure can be smoothly carried out.

[0084] The victim request understanding unit can analyze the requests of disaster victims and prioritize the most urgent requests. For example, the generation AI can analyze the requests of disaster victims and prioritize the most urgent requests. For example, it can automatically list the most urgent requests and respond to them quickly. This makes it possible to provide prompt support by analyzing the requests of disaster victims and prioritizing the most urgent requests.

[0085] The victim request understanding unit can analyze the location information of the victim and suggest the nearest support base. For example, the generation AI can analyze the location information of the victim and suggest the nearest support base. For example, the unit can automatically suggest the nearest evacuation shelter or support base based on the current location of the victim. This makes it possible to provide prompt support by analyzing the location information of the victim and suggesting the nearest support base.

[0086] The victim request understanding unit can use the emotion estimation function to analyze the psychological state of the victim and provide appropriate support. The victim request understanding unit can, for example, use the emotion estimation function to analyze the psychological state of the victim and provide appropriate support. For example, it can analyze the emotional state of the victim and provide psychological support. In this way, by analyzing the psychological state of the victim and providing appropriate support, it is possible to increase the victim's sense of security.

[0087] The disaster victim request ascertainment unit can also adapt the ascertainment of disaster victim requests in the event of a natural disaster to preventive measures before a disaster occurs. The disaster victim request ascertainment unit, for example, adapts the ascertainment of disaster victim requests in the event of a natural disaster to preventive measures before a disaster occurs. For example, the unit automatically proposes preparations and evacuation plans required before a disaster occurs. This allows the safety of disaster victims to be ensured in advance by adapting the system to preventive measures before a disaster occurs.

[0088] The disaster victim request ascertaining unit can also adapt the ascertainment of disaster victim requests during natural disasters to other emergency situations (e.g., pandemics). The disaster victim request ascertaining unit can, for example, adapt the ascertainment of disaster victim requests during natural disasters to other emergency situations (e.g., pandemics). For example, it automatically lists support requests during pandemics. This allows the unit to respond to other emergency situations, making it possible to provide rapid support.

[0089] The disaster victim request understanding unit can use the emotion estimation function to identify the support method that will make the disaster victim feel most at ease. The disaster victim request understanding unit, for example, uses the emotion estimation function to identify the support method that will make the disaster victim feel most at ease. For example, it analyzes the emotional state of the disaster victim and proposes the optimal support method. In this way, by identifying the support method that will make the disaster victim feel most at ease, it is possible to increase the disaster victim's sense of security.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] The system for streamlining residential relocation procedures can also include a health management unit that monitors the user's health and identifies health risks that may affect the progress of the relocation process. For example, if the user has a chronic illness, the system can adjust the relocation schedule based on that information. It can also advise the user to get adequate rest if the stress of moving is likely to have a negative impact on their health. It can also provide information about medical institutions in the relocation destination and arrange for necessary medical services in advance. This allows the relocation process to be completed with peace of mind, taking the user's health into consideration.

[0092] The system for streamlining residential relocation procedures can also include a local information provider that takes into account the user's hobbies and interests and provides local information about the area where the user is moving. For example, if the user likes sports, information about sports facilities and clubs in the area can be provided. If the user is interested in cultural activities, information about local events and museums can be provided. Furthermore, information about nearby parks and playgrounds can be provided for families with children. This allows the user to quickly become accustomed to their new living environment by providing local information tailored to their hobbies and interests.

[0093] The system for streamlining the relocation process can also estimate the user's emotions and provide advice to support building new relationships in their new home. For example, if the user is feeling anxious about moving, it can provide information about local community activities and clubs to increase opportunities to make new friends. It can also provide advice on how to communicate with people they meet for the first time in their new home. It can also provide information about the culture and customs of the new home to support a smooth adaptation. This helps users build relationships in their new environment smoothly.

[0094] The system for streamlining residential relocation procedures can also estimate the user's emotions and suggest appropriate relaxation methods depending on the progress of the relocation process. For example, if the user is feeling stressed, it can suggest using relaxation music or a meditation app. It can also advise the user to take short breaks between moving tasks. It can also provide information on relaxation spots and services at the new location. This helps the user reduce stress during the relocation process and allows them to proceed with the process in a relaxed state.

[0095] The system for streamlining the home relocation process can also estimate the user's emotions and introduce a reward system to maintain motivation as the relocation process progresses. For example, points can be awarded for completing each step of the process, and those points can be used to purchase relocation-related services and products at discounted prices. It can also send encouraging messages according to the progress of the process. Furthermore, it can provide a reward that gives the user a sense of accomplishment when the process is completed. This helps the user to actively proceed with the relocation process.

[0096] The system for streamlining residential relocation procedures can also be equipped with a lifestyle support unit to support the user's life in their new home. For example, it can provide information on how to use public transportation at the new home and the nearest supermarket. It can also provide information on how to dispose of garbage at the new home and local rules. It can also provide information on emergency contacts and medical institutions at the new home. This helps the user adapt quickly to their new living environment.

[0097] The system for streamlining residential relocation procedures can also be equipped with a chat support section to respond in real time to users' questions and concerns regarding the relocation procedures. For example, if a user has a question during the process, they can ask a specialized support staff member via chat. The system also has an automated response function for frequently asked questions, providing quick answers. Furthermore, it can also switch to telephone support as needed. This eliminates any anxieties or questions the user may have during the process, allowing the process to proceed smoothly.

[0098] The system for streamlining the home relocation process can also estimate the user's emotions and provide appropriate feedback as the process progresses. For example, if the user is feeling anxious about the process, it can provide a detailed explanation of the progress and clarify the next steps. If the process is progressing smoothly, it can send an encouraging message. Furthermore, once the process is complete, it can provide feedback that gives the user a sense of accomplishment. This helps the user to proceed smoothly with the process.

[0099] The system for streamlining home relocation procedures can also have a sharing function that allows the user to share the progress of the moving procedures with family and friends. For example, the user can share the progress of the procedures with family and friends and receive support. The user can also receive encouraging messages from family and friends as the procedures progress. Furthermore, when the procedures are completed, the user can share a sense of accomplishment with family and friends. This allows the user to proceed with the moving procedures while receiving support from family and friends.

[0100] The system for streamlining residential relocation procedures can also estimate the user's emotions and suggest appropriate exercises and stretches as the moving process progresses. For example, if the user feels tired during the process, it can suggest simple exercises and stretches. It can also suggest exercises to refresh between procedures. It can also provide an exercise plan to maintain health at the new home. This allows the user to maintain their health as they move through the moving process.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The bulk moving procedure processing unit processes all moving procedures in one go. For example, you can transfer your residence registration, change your electricity, gas, and water contracts, and forward your mail all at once. Step 2: The Business Efficiency Department aims to improve the business efficiency of the business. For example, the generation AI manages the progress of various procedures in real time and automatically notifies relevant parties of necessary information. Step 3: The moving-out notification processing unit processes the moving-out notification online. For example, when a user enters the address of the new address and the planned moving-out date on the app, the generation AI analyzes that information and automatically generates the necessary documents. Step 4: The Visitor Reservation Department makes online reservations for visits. For example, when a user enters the desired date and time of visit on the app, the generation AI analyzes the information and connects with the local government's reservation system to confirm the reservation. Step 5: The disaster victim needs understanding unit understands the needs of disaster victims in the event of a natural disaster. For example, when a disaster victim enters information about necessary relief supplies and evacuation locations into the app, the generation AI analyzes the information and automatically notifies local governments and relief organizations.

[0103] 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.

[0104] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<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.

[0105] 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.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0116] 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. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0131] 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 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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).

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0147] In the robot 414, the processor 46 performs the identification process. 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. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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).

[0156] 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.

[0157] 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."

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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. [Explanation of symbols]

[0170] 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 bulk moving procedure processing unit that processes all moving procedures at once; The Business Efficiency Department aims to improve the business efficiency of businesses, The Moving Out Notification Processing Department handles the moving out notification process online, and The Visitor Reservation Department allows you to make online reservations for visits to the office, A disaster victim request ascertaining unit that ascertains the requests of disaster victims in the event of a natural disaster. A system characterized by:

2. The moving procedure bulk processing unit is Analyzes the user's past moving history and suggests the optimal procedure 2. The system of claim 1.

3. The business efficiency department Analyze the business process of the company, identify bottlenecks, and propose improvements 2. The system of claim 1.

4. The moving-out notification processing department Automatically e-sign required documents 2. The system of claim 1.

5. The visitor reservation department Analyzes the user's schedule and suggests the best time to visit the office 2. The system of claim 1.

6. The disaster victim request understanding unit Analyzing the requests of the victims and prioritizing the most urgent requests 2. The system of claim 1.

7. The moving procedure bulk processing unit is Analyzes the user's stress level and suggests a procedural sequence to reduce stress 2. The system of claim 1.

8. The business efficiency department Real-time monitoring of resident satisfaction to help improve services 2. The system of claim 1.

Images