System

Abstract

An object of the system according to the embodiment is to improve the efficiency of the cremation procedure and reduce the burden on the bereaved family.SOLUTION: A system according to an embodiment includes an online procedure unit, a priority optimization unit, an operation status grasping unit, and a waiting time minimization unit. In the online procedure part, the bereaved family completes the procedure online. A priority optimization part optimizes the priority of the procedure based on the procedure information from the bereaved family. The operation status grasping unit grasps an operation status of the cremation facility in real time. The waiting time minimizing unit minimizes the waiting time based on the operating status.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 not made cremation procedures sufficiently efficient, which has resulted in a heavy burden on the bereaved family.

[0005] The system of the embodiment aims to streamline cremation procedures and reduce the burden on bereaved families. [Means for solving the problem]

[0006] The system according to the embodiment comprises an online procedure unit, a priority optimization unit, an operation status understanding unit, and a waiting time minimization unit. The online procedure unit allows the bereaved family to complete procedures online. The priority optimization unit optimizes the priority of procedures based on procedure information from the bereaved family. The operation status understanding unit understands the operation status of the cremation facility in real time. The waiting time minimization unit minimizes waiting time based on the operation status. [Effects of the Invention]

[0007] The system according to the embodiment can streamline cremation procedures and reduce the burden on the bereaved. [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 nonvolatile storage devices that store various programs, various parameters, etc. Examples of nonvolatile 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 Reliefire system according to an embodiment of the present invention allows bereaved families to complete procedures online, and the AI ​​optimizes the priority of procedures, monitors the operating status of crematoriums in real time, and minimizes waiting times. This reduces stress for bereaved families and enables sudden funerals to be carried out smoothly.

[0029] The reliefire system according to the embodiment includes an online procedure unit, a priority optimization unit, an operation status assessment unit, and a wait time minimization unit. The online procedure unit allows bereaved family members to complete procedures online. For example, the bereaved family members can complete the procedures by entering the desired date, time, and location of the cremation and uploading the necessary documents. Furthermore, because the online procedure unit completes procedures via the internet, the bereaved family members can complete the procedures from home. The priority optimization unit optimizes the priority of procedures based on the procedure information provided by the bereaved family members. For example, the priority is set according to the bereaved family members' circumstances, such as when an urgent funeral is required or when they wish to have the cremation performed on a specific date and time. The generation AI optimizes the priority based on prompts containing the procedures desired by the bereaved family members. The operation status assessment unit assesses the operation status of crematoriums in real time. For example, it retrieves the reservation status and operation status of crematoriums from a database and checks the current availability. This allows immediate determination of whether cremation is possible on the date and time desired by the bereaved family members. The wait time minimization unit creates a schedule to minimize waiting time based on the operation status. For example, it compares the availability of multiple crematoriums and selects the facility that can accommodate the request most quickly. This reduces the waiting time for the bereaved family and enables a prompt response. As a result, the relief fire system according to the embodiment can streamline the procedures for the bereaved family and reduce their stress.

[0030] The online procedure section uses AI to automatically generate the necessary documents based on the information entered by the bereaved family, allowing them to complete the signatures online. For example, when the bereaved family enters the desired date, time, and location of the cremation, the AI ​​automatically generates the necessary documents and allows them to complete the signatures online. For example, documents such as a death certificate and cremation permit are automatically generated, and the bereaved family then electronically sign them. This allows the bereaved family to complete the procedures quickly and efficiently.

[0031] In the online procedure section, AI can provide real-time guidance to bereaved family members as they go through the procedures, explaining each step in an easy-to-understand manner. For example, in the online procedure section, AI can provide real-time guidance to bereaved family members as they go through the online procedures, explaining each step in an easy-to-understand manner. For example, it can display the progress of the procedure and guide them to the next step to take. This allows bereaved family members to go through the procedures smoothly.

[0032] The online procedure unit can incorporate a video call function during online procedures, allowing bereaved family members to consult directly with experts. The online procedure unit can, for example, incorporate a video call function during online procedures, allowing bereaved family members to consult directly with experts. For example, if a bereaved family member has a question for an expert during the procedure, the question can be immediately asked via video call. This allows bereaved family members to consult directly with an expert, thereby reducing anxiety about the procedure.

[0033] After the online procedure is completed, AI can automatically suggest related services. For example, after a cremation reservation is completed, AI can display options for arranging flowers and booking a venue. This allows bereaved families to smoothly use the services they need after the procedure is completed.

[0034] The priority optimization unit can analyze the past procedure history of the bereaved family and set optimal priorities. For example, AI can analyze the past procedure history of the bereaved family and set optimal priorities. For example, if a sudden funeral was required in the past, priorities can be set based on that information. This makes it possible to set optimal priorities based on past procedure history.

[0035] The priority optimization unit allows the AI ​​to take into account the social background and cultural factors of the bereaved when setting the priority of procedures. For example, the priority optimization unit sets priorities by taking into account the importance of funerals in a particular culture or religion. This makes it possible to set priorities by taking into account the social background and cultural factors of the bereaved.

[0036] In the priority optimization section, AI can coordinate with other related organizations (for example, government offices and hospitals) to centralize procedures when optimizing priorities. For example, in the priority optimization section, AI can coordinate with other related organizations (for example, government offices and hospitals) to centralize procedures when optimizing priorities. For example, submitting a death notification at the same time as cremation procedures. This allows procedures to be centralized by coordinating with related organizations.

[0037] When setting the priority of procedures, the priority optimization unit uses AI to automatically adjust the schedule of the bereaved family and suggest the optimal date and time.When setting the priority of procedures, the priority optimization unit uses AI to automatically adjust the schedule of the bereaved family and suggest the optimal date and time.For example, it analyzes the calendar of the bereaved family and suggests the optimal date and time.This makes it possible to suggest the optimal date and time based on the schedule of the bereaved family.

[0038] The operation status grasping unit uses AI to monitor the operation status of the crematorium in real time and immediately notify if an abnormality occurs.The operation status grasping unit uses AI to monitor the operation status of the crematorium in real time and immediately notify if an abnormality occurs.For example, it notifies if there is an equipment failure or a reservation overlap.This allows for immediate notification of any abnormality at the crematorium.

[0039] The operation status understanding unit uses AI to propose the optimal route based on the operation status of the crematorium, allowing the bereaved family to arrive at the facility smoothly.The operation status understanding unit uses AI to propose the optimal route based on the operation status of the crematorium, for example, allowing the bereaved family to arrive at the facility smoothly.For example, it proposes the optimal route taking into consideration traffic conditions and the location of the facility.This allows the bereaved family to arrive at the crematorium smoothly.

[0040] The operation status grasping unit allows the AI ​​to grasp the availability of other related facilities (for example, funeral halls and accommodation facilities) in real time based on the operation status of the crematorium. The operation status grasping unit allows the AI ​​to grasp the availability of other related facilities (for example, funeral halls and accommodation facilities) in real time based on the operation status of the crematorium. For example, it checks the reservation status of funeral halls and accommodation facilities. This makes it possible to grasp the availability of related facilities in real time.

[0041] The operation status grasping unit uses AI to suggest the optimal time slot based on the operation status of the crematorium, allowing bereaved families to avoid congestion.The operation status grasping unit uses AI to suggest the optimal time slot based on the operation status of the crematorium, allowing bereaved families to avoid congestion.For example, it suggests a time slot when it is less crowded.This allows bereaved families to use the crematorium without overcrowding.

[0042] The waiting time minimization unit uses AI to predict waiting times in real time based on the operating status of the crematorium and notify the bereaved.The waiting time minimization unit uses AI to predict waiting times in real time based on the operating status of the crematorium and notify the bereaved.For example, it predicts waiting times based on the current reservation status and notifies the bereaved.This makes it possible to predict waiting times in real time and notify the bereaved.

[0043] The waiting time minimization unit uses AI to automatically adjust the schedules of multiple crematoriums in order to minimize waiting times. The waiting time minimization unit uses AI to automatically adjust the schedules of multiple crematoriums in order to minimize waiting times, for example, by comparing the availability of multiple facilities and selecting the facility that can respond most quickly. This makes it possible to adjust the schedules of multiple crematoriums and minimize waiting times.

[0044] The waiting time minimization unit allows the AI ​​to simultaneously make reservations for other related services (e.g., transportation and accommodation) in order to minimize waiting times. The waiting time minimization unit allows the AI ​​to simultaneously make reservations for other related services (e.g., transportation and accommodation) in order to minimize waiting times. For example, the waiting time minimization unit makes reservations for transportation and accommodation at the same time as reserving a crematorium. In this way, reservations for related services can be made simultaneously, minimizing waiting times.

[0045] The waiting time minimization unit uses AI to suggest activities where the bereaved can relax (for example, cafes or parks) based on the waiting time.The waiting time minimization unit uses AI to suggest activities where the bereaved can relax (for example, cafes or parks) based on the waiting time.For example, if the waiting time is long, it will suggest a nearby cafe or park.This allows the bereaved to make effective use of their waiting time by suggesting activities where they can relax.

[0046] The waiting time minimization unit uses AI to automatically adjust the schedules of the bereaved family members and propose an optimal schedule to reduce stress. The waiting time minimization unit uses AI to automatically adjust the schedules of the bereaved family members and propose an optimal schedule to reduce stress. For example, it analyzes the calendars of the bereaved family members and proposes an optimal schedule. This makes it possible to automatically adjust the schedules of the bereaved family members and propose an optimal schedule to reduce stress.

[0047] The waiting time minimization unit can use AI to suggest booking other related services (e.g., counseling or relaxation) to reduce stress for the bereaved. The waiting time minimization unit can use AI to suggest booking other related services (e.g., counseling or relaxation) to reduce stress for the bereaved. For example, after the cremation procedures are completed, options for counseling or relaxation are displayed. This can suggest booking related services to reduce stress for the bereaved.

[0048] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0049] The Reliefire system can also include a cultural adaptation department that provides customized procedures based on the cultural background of the bereaved. For example, it takes into account funeral rituals and procedures in specific religions and cultures and provides appropriate guidelines and support. The cultural adaptation department can also respect the specific rituals and traditions desired by the bereaved and suggest procedures based on those. This allows bereaved families to smoothly hold funerals in accordance with their own culture and religion.

[0050] The Reliefire system can also include a health management unit that monitors the health of bereaved family members and provides medical support as needed. For example, if a bereaved family member is elderly or has a chronic illness, the health management unit can regularly check their health and arrange for the necessary medical support. The health management unit can also suggest relaxation and counseling options if the bereaved family member feels stressed or tired. This allows the process to proceed while protecting the health of the bereaved family.

[0051] The Reliefire system can also be equipped with a multilingual support department that uses AI to provide real-time translations as bereaved families go through the process. For example, if a bereaved family member speaks a foreign language, the multilingual support department can translate each step of the process into their native language, ensuring a smooth process. The multilingual support department can also provide expert interpretation services as needed, allowing the process to be completed without language barriers.

[0052] The processing flow of the first embodiment will be briefly explained below.

[0053] Step 1: In the online procedure section, the bereaved family completes the procedure online. For example, the bereaved family completes the procedure by entering the desired date, time, and location of the cremation and uploading the necessary documents. In addition, since the online procedure section is carried out via the Internet, the bereaved family can complete the procedure from home. Step 2: The priority optimization unit optimizes the priority of procedures based on procedural information from the bereaved family. For example, it sets priorities according to the bereaved family's circumstances, such as if an urgent funeral is required or if they wish to have the body cremated on a specific date and time. The generation AI optimizes the priority based on prompts containing the procedures desired by the bereaved family. Step 3: The operation status monitoring unit monitors the operation status of the crematorium in real time. For example, it retrieves the reservation status and operation status of the crematorium from a database and checks the current availability. This makes it possible to immediately determine whether cremation is possible on the date and time desired by the bereaved family. Step 4: The waiting time minimization unit creates a schedule to minimize waiting times based on the operating status. For example, it compares the availability of multiple crematoriums and selects the facility that can respond most quickly. This reduces waiting times for bereaved families and enables prompt responses.

[0054] (Example 2) The Reliefire system according to an embodiment of the present invention allows bereaved families to complete procedures online, and the AI ​​optimizes the priority of procedures, monitors the operating status of crematoriums in real time, and minimizes waiting times. This reduces stress for bereaved families and enables sudden funerals to be carried out smoothly.

[0055] The reliefire system according to the embodiment includes an online procedure unit, a priority optimization unit, an operation status assessment unit, and a wait time minimization unit. The online procedure unit allows bereaved family members to complete procedures online. For example, the bereaved family members can complete the procedures by entering the desired date, time, and location of the cremation and uploading the necessary documents. Furthermore, because the online procedure unit completes procedures via the internet, the bereaved family members can complete the procedures from home. The priority optimization unit optimizes the priority of procedures based on the procedure information provided by the bereaved family members. For example, the priority is set according to the bereaved family members' circumstances, such as when an urgent funeral is required or when they wish to have the cremation performed on a specific date and time. The generation AI optimizes the priority based on prompts containing the procedures desired by the bereaved family members. The operation status assessment unit assesses the operation status of crematoriums in real time. For example, it retrieves the reservation status and operation status of crematoriums from a database and checks the current availability. This allows immediate determination of whether cremation is possible on the date and time desired by the bereaved family members. The wait time minimization unit creates a schedule to minimize waiting time based on the operation status. For example, it compares the availability of multiple crematoriums and selects the facility that can accommodate the request most quickly. This reduces the waiting time for the bereaved family and enables a prompt response. As a result, the relief fire system according to the embodiment can streamline the procedures for the bereaved family and reduce their stress.

[0056] The online procedure section uses AI to automatically generate the necessary documents based on the information entered by the bereaved family, allowing them to complete the signatures online. For example, when the bereaved family enters the desired date, time, and location of the cremation, the AI ​​automatically generates the necessary documents and allows them to complete the signatures online. For example, documents such as a death certificate and cremation permit are automatically generated, and the bereaved family then electronically sign them. This allows the bereaved family to complete the procedures quickly and efficiently.

[0057] In the online procedure section, AI can provide real-time guidance to bereaved family members as they go through the procedures, explaining each step in an easy-to-understand manner. For example, in the online procedure section, AI can provide real-time guidance to bereaved family members as they go through the online procedures, explaining each step in an easy-to-understand manner. For example, it can display the progress of the procedure and guide them to the next step to take. This allows bereaved family members to go through the procedures smoothly.

[0058] The online procedure unit can use the emotion estimation function to analyze the emotional state of the bereaved family, and if stress is high, make suggestions to simplify the procedures. For example, the online procedure unit can use the emotion estimation function to analyze the emotional state of the bereaved family in real time, and if stress is high, make suggestions to simplify the procedures. For example, it can suggest omitting some procedures or postponing them to a later date. This can reduce stress for the bereaved family and simplify the procedures.

[0059] The online procedure unit can incorporate a video call function during online procedures, allowing bereaved family members to consult directly with experts. The online procedure unit can, for example, incorporate a video call function during online procedures, allowing bereaved family members to consult directly with experts. For example, if a bereaved family member has a question for an expert during the procedure, the question can be immediately asked via video call. This allows bereaved family members to consult directly with an expert, thereby reducing anxiety about the procedure.

[0060] After the online procedure is completed, AI can automatically suggest related services. For example, after a cremation reservation is completed, AI can display options for arranging flowers and booking a venue. This allows bereaved families to smoothly use the services they need after the procedure is completed.

[0061] The online procedure unit can use the emotion estimation function to monitor in real time the emotions of the bereaved family as they go through the procedures and display messages to elicit positive emotions. For example, the online procedure unit can use the emotion estimation function to monitor in real time the emotions of the bereaved family as they go through the procedures and display messages to elicit positive emotions. For example, messages of encouragement or words of gratitude can be displayed. This can keep the emotions of the bereaved family positive.

[0062] The priority optimization unit can analyze the past procedure history of the bereaved family and set optimal priorities. For example, AI can analyze the past procedure history of the bereaved family and set optimal priorities. For example, if a sudden funeral was required in the past, priorities can be set based on that information. This makes it possible to set optimal priorities based on past procedure history.

[0063] The priority optimization unit allows the AI ​​to take into account the social background and cultural factors of the bereaved when setting the priority of procedures. For example, the priority optimization unit sets priorities by taking into account the importance of funerals in a particular culture or religion. This makes it possible to set priorities by taking into account the social background and cultural factors of the bereaved.

[0064] The priority optimization unit uses the emotion estimation function to adjust the priority based on the emotional state of the bereaved family, and can raise the priority if stress is high. The priority optimization unit, for example, uses the emotion estimation function to analyze the emotional state of the bereaved family in real time, and raises the priority of the procedure if stress is high. For example, if the emotion score is high, the priority is raised. This makes it possible to adjust the priority according to the emotional state of the bereaved family.

[0065] In the priority optimization section, AI can coordinate with other related organizations (for example, government offices and hospitals) to centralize procedures when optimizing priorities. For example, in the priority optimization section, AI can coordinate with other related organizations (for example, government offices and hospitals) to centralize procedures when optimizing priorities. For example, submitting a death notification at the same time as cremation procedures. This allows procedures to be centralized by coordinating with related organizations.

[0066] When setting the priority of procedures, the priority optimization unit uses AI to automatically adjust the schedule of the bereaved family and suggest the optimal date and time.When setting the priority of procedures, the priority optimization unit uses AI to automatically adjust the schedule of the bereaved family and suggest the optimal date and time.For example, it analyzes the calendar of the bereaved family and suggests the optimal date and time.This makes it possible to suggest the optimal date and time based on the schedule of the bereaved family.

[0067] The priority optimization unit can use the emotion estimation function to set priorities based on the emotional state of the bereaved family members and make suggestions to elicit positive emotions. For example, the priority optimization unit uses the emotion estimation function to analyze the emotional state of the bereaved family members in real time and make suggestions to elicit positive emotions. For example, if the emotion score is high, the priority is increased. This allows priorities to be set based on the emotional state of the bereaved family members and suggestions to elicit positive emotions.

[0068] The operation status grasping unit uses AI to monitor the operation status of the crematorium in real time and immediately notify if an abnormality occurs.The operation status grasping unit uses AI to monitor the operation status of the crematorium in real time and immediately notify if an abnormality occurs.For example, it notifies if there is an equipment failure or a reservation overlap.This allows for immediate notification of any abnormality at the crematorium.

[0069] The operation status understanding unit uses AI to propose the optimal route based on the operation status of the crematorium, allowing the bereaved family to arrive at the facility smoothly.The operation status understanding unit uses AI to propose the optimal route based on the operation status of the crematorium, for example, allowing the bereaved family to arrive at the facility smoothly.For example, it proposes the optimal route taking into consideration traffic conditions and the location of the facility.This allows the bereaved family to arrive at the crematorium smoothly.

[0070] The operation status grasping unit allows the AI ​​to grasp the availability of other related facilities (for example, funeral halls and accommodation facilities) in real time based on the operation status of the crematorium. The operation status grasping unit allows the AI ​​to grasp the availability of other related facilities (for example, funeral halls and accommodation facilities) in real time based on the operation status of the crematorium. For example, it checks the reservation status of funeral halls and accommodation facilities. This makes it possible to grasp the availability of related facilities in real time.

[0071] The operation status grasping unit uses AI to suggest the optimal time slot based on the operation status of the crematorium, allowing bereaved families to avoid congestion.The operation status grasping unit uses AI to suggest the optimal time slot based on the operation status of the crematorium, allowing bereaved families to avoid congestion.For example, it suggests a time slot when it is less crowded.This allows bereaved families to use the crematorium without overcrowding.

[0072] The operation status understanding unit can use the emotion estimation function to suggest the most suitable facility based on the emotional state of the bereaved family and make suggestions to bring out positive emotions. The operation status understanding unit, for example, uses the emotion estimation function to analyze the emotional state of the bereaved family in real time and make suggestions to bring out positive emotions. For example, if the emotion score is high, the operation status understanding unit can suggest the most suitable facility. This makes it possible to suggest the most suitable facility based on the emotional state of the bereaved family and make suggestions to bring out positive emotions.

[0073] The waiting time minimization unit uses AI to predict waiting times in real time based on the operating status of the crematorium and notify the bereaved.The waiting time minimization unit uses AI to predict waiting times in real time based on the operating status of the crematorium and notify the bereaved.For example, it predicts waiting times based on the current reservation status and notifies the bereaved.This makes it possible to predict waiting times in real time and notify the bereaved.

[0074] The waiting time minimization unit uses AI to automatically adjust the schedules of multiple crematoriums in order to minimize waiting times. The waiting time minimization unit uses AI to automatically adjust the schedules of multiple crematoriums in order to minimize waiting times, for example, by comparing the availability of multiple facilities and selecting the facility that can respond most quickly. This makes it possible to adjust the schedules of multiple crematoriums and minimize waiting times.

[0075] The waiting time minimization unit can use the emotion estimation function to analyze the emotional state of the bereaved family members, and if stress is high, make a suggestion to further shorten the waiting time. The waiting time minimization unit can, for example, use the emotion estimation function to analyze the emotional state of the bereaved family members in real time, and if stress is high, make a suggestion to further shorten the waiting time. For example, if the emotion score is high, the waiting time is shortened. This makes it possible to make a suggestion to further shorten the waiting time according to the emotional state of the bereaved family members.

[0076] The waiting time minimization unit allows the AI ​​to simultaneously make reservations for other related services (e.g., transportation and accommodation) in order to minimize waiting times. The waiting time minimization unit allows the AI ​​to simultaneously make reservations for other related services (e.g., transportation and accommodation) in order to minimize waiting times. For example, the waiting time minimization unit makes reservations for transportation and accommodation at the same time as reserving a crematorium. In this way, reservations for related services can be made simultaneously, minimizing waiting times.

[0077] The waiting time minimization unit uses AI to suggest activities where the bereaved can relax (for example, cafes or parks) based on the waiting time.The waiting time minimization unit uses AI to suggest activities where the bereaved can relax (for example, cafes or parks) based on the waiting time.For example, if the waiting time is long, it will suggest a nearby cafe or park.This allows the bereaved to make effective use of their waiting time by suggesting activities where they can relax.

[0078] The waiting time minimization unit can use the emotion estimation function to adjust the waiting time based on the emotional state of the bereaved family and make suggestions to elicit positive emotions. For example, the waiting time minimization unit uses the emotion estimation function to analyze the emotional state of the bereaved family in real time and make suggestions to elicit positive emotions. For example, if the emotion score is high, the waiting time is shortened. This allows the waiting time to be adjusted based on the emotional state of the bereaved family and makes suggestions to elicit positive emotions.

[0079] The waiting time minimization unit uses AI to monitor the emotional state of the bereaved in real time and make suggestions to help them relax if stress levels are high.The waiting time minimization unit, for example, uses AI to monitor the emotional state of the bereaved in real time and make suggestions to help them relax if stress levels are high.For example, if the emotional score is high, it will suggest a relaxing activity.This allows the AI ​​to monitor the emotional state of the bereaved in real time and make suggestions to help them relax.

[0080] The waiting time minimization unit uses an emotion estimation function by AI to display messages that draw out positive emotions as the bereaved family members go through the procedures. For example, the waiting time minimization unit uses an emotion estimation function by AI to display messages that draw out positive emotions as the bereaved family members go through the procedures. For example, it displays messages of encouragement or words of gratitude. This makes it possible to display messages that draw out positive emotions as the bereaved family members go through the procedures.

[0081] The waiting time minimization unit uses AI to automatically adjust the schedules of the bereaved family members and propose an optimal schedule to reduce stress. The waiting time minimization unit uses AI to automatically adjust the schedules of the bereaved family members and propose an optimal schedule to reduce stress. For example, it analyzes the calendars of the bereaved family members and proposes an optimal schedule. This makes it possible to automatically adjust the schedules of the bereaved family members and propose an optimal schedule to reduce stress.

[0082] The waiting time minimization unit can use AI to suggest booking other related services (e.g., counseling or relaxation) to reduce stress for the bereaved. The waiting time minimization unit can use AI to suggest booking other related services (e.g., counseling or relaxation) to reduce stress for the bereaved. For example, after the cremation procedures are completed, options for counseling or relaxation are displayed. This can suggest booking related services to reduce stress for the bereaved.

[0083] The waiting time minimization unit uses AI to suggest activities to reduce stress (for example, walking or meditation) based on the emotional state of the bereaved. For example, the waiting time minimization unit uses AI to analyze the emotional state of the bereaved in real time and suggest activities to reduce stress (for example, walking or meditation). For example, if the emotional score is high, it will suggest a relaxing activity. This makes it possible to suggest activities to reduce stress based on the emotional state of the bereaved.

[0084] The waiting time minimization unit can use the emotion estimation function to make suggestions for reducing stress based on the emotional state of the bereaved family members and provide support for drawing out positive emotions. For example, the waiting time minimization unit can use the emotion estimation function to analyze the emotional state of the bereaved family members in real time and make suggestions for drawing out positive emotions. For example, if the emotion score is high, the waiting time minimization unit can suggest a relaxing activity. This makes it possible to make suggestions for reducing stress based on the emotional state of the bereaved family members and provide support for drawing out positive emotions.

[0085] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0086] The Reliefire system can also include a cultural adaptation department that provides customized procedures based on the cultural background of the bereaved. For example, it takes into account funeral rituals and procedures in specific religions and cultures and provides appropriate guidelines and support. The cultural adaptation department can also respect the specific rituals and traditions desired by the bereaved and suggest procedures based on those. This allows bereaved families to smoothly hold funerals in accordance with their own culture and religion.

[0087] The Reliefire system can also include a health management unit that monitors the health of bereaved family members and provides medical support as needed. For example, if a bereaved family member is elderly or has a chronic illness, the health management unit can regularly check their health and arrange for the necessary medical support. The health management unit can also suggest relaxation and counseling options if the bereaved family member feels stressed or tired. This allows the process to proceed while protecting the health of the bereaved family.

[0088] The Reliefire system can also be equipped with a multilingual support department that uses AI to provide real-time translations as bereaved families go through the process. For example, if a bereaved family member speaks a foreign language, the multilingual support department can translate each step of the process into their native language, ensuring a smooth process. The multilingual support department can also provide expert interpretation services as needed, allowing the process to be completed without language barriers.

[0089] The Reliefire system also uses AI to monitor the emotional state of bereaved family members in real time as they go through the procedures, and can offer relaxation suggestions if stress levels are high. For example, it uses emotion estimation to analyze the emotional state of bereaved family members, and if stress levels are high, it can offer deep breathing or meditation guidance. It can also play music or nature sounds for relaxation. This helps reduce stress for bereaved family members and allows the procedures to proceed smoothly.

[0090] The Reliefire system also uses AI's emotion estimation function to display messages designed to elicit positive emotions as the bereaved family members go through the procedures. For example, the emotion estimation function can analyze the emotional state of the bereaved family members in real time and display encouraging messages or words of gratitude. In addition, when the bereaved family members complete the procedures, messages of gratitude or words of encouragement can be displayed to elicit positive emotions. This allows the bereaved family members to maintain positive emotions as they go through the procedures.

[0091] Furthermore, as bereaved family members go through the procedures, the Reliefire system uses its AI's emotion estimation function to make suggestions to simplify the process if they are under high stress. For example, the emotion estimation function can analyze the emotional state of the bereaved family in real time, and if they are under high stress, it can suggest skipping some procedures or postponing them to a later date. The system also displays the progress of the procedures and guides them to the next step, allowing the bereaved family to proceed smoothly through the process. This reduces stress for the bereaved and simplifies the process.

[0092] The Reliefire system also uses AI's emotion estimation function to display messages designed to elicit positive emotions as the bereaved family members go through the procedures. For example, the emotion estimation function can analyze the emotional state of the bereaved family members in real time and display encouraging messages or words of gratitude. In addition, when the bereaved family members complete the procedures, messages of gratitude or words of encouragement can be displayed to elicit positive emotions. This allows the bereaved family members to maintain positive emotions as they go through the procedures.

[0093] Furthermore, as bereaved family members go through the procedures, the Reliefire system uses its AI's emotion estimation function to make suggestions to simplify the process if they are under high stress. For example, the emotion estimation function can analyze the emotional state of the bereaved family in real time, and if they are under high stress, it can suggest skipping some procedures or postponing them to a later date. The system also displays the progress of the procedures and guides them to the next step, allowing the bereaved family to proceed smoothly through the process. This reduces stress for the bereaved and simplifies the process.

[0094] The Reliefire system also uses AI's emotion estimation function to display messages designed to elicit positive emotions as the bereaved family members go through the procedures. For example, the emotion estimation function can analyze the emotional state of the bereaved family members in real time and display encouraging messages or words of gratitude. In addition, when the bereaved family members complete the procedures, messages of gratitude or words of encouragement can be displayed to elicit positive emotions. This allows the bereaved family members to maintain positive emotions as they go through the procedures.

[0095] Furthermore, as bereaved family members go through the procedures, the Reliefire system uses its AI's emotion estimation function to make suggestions to simplify the process if they are under high stress. For example, the emotion estimation function can analyze the emotional state of the bereaved family in real time, and if they are under high stress, it can suggest skipping some procedures or postponing them to a later date. The system also displays the progress of the procedures and guides them to the next step, allowing the bereaved family to proceed smoothly through the process. This reduces stress for the bereaved and simplifies the process.

[0096] The processing flow of the second embodiment will be briefly explained below.

[0097] Step 1: In the online procedure section, the bereaved family completes the procedure online. For example, the bereaved family completes the procedure by entering the desired date, time, and location of the cremation and uploading the necessary documents. In addition, since the online procedure section is carried out via the Internet, the bereaved family can complete the procedure from home. Step 2: The priority optimization unit optimizes the priority of procedures based on procedural information from the bereaved family. For example, it sets priorities according to the bereaved family's circumstances, such as if an urgent funeral is required or if they wish to have the body cremated on a specific date and time. The generation AI optimizes the priority based on prompts containing the procedures desired by the bereaved family. Step 3: The operation status monitoring unit monitors the operation status of the crematorium in real time. For example, it retrieves the reservation status and operation status of the crematorium from a database and checks the current availability. This makes it possible to immediately determine whether cremation is possible on the date and time desired by the bereaved family. Step 4: The waiting time minimization unit creates a schedule to minimize waiting times based on the operating status. For example, it compares the availability of multiple crematoriums and selects the facility that can respond most quickly. This reduces waiting times for bereaved families and enables prompt responses.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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).

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0117] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0132] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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).

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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).

[0151] 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.

[0152] 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."

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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]

[0165] 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. An online procedure section where family members can complete procedures online; a priority optimization unit that optimizes the priority of procedures based on procedure information from the bereaved family; An operation status monitoring unit that monitors the operation status of the crematorium in real time; a waiting time minimizing unit that minimizes the waiting time based on the operating status. A system characterized by:

2. The online procedure unit Using an emotion estimation function, the emotional state of the bereaved family is analyzed, and if stress levels are high, suggestions are made to simplify the procedure. The system of claim 1 .

3. The priority optimization unit Analyze the past procedure history of the bereaved family and set the optimal priority The system of claim 1 .

4. The operation status grasping unit The AI ​​monitors the operation status of the crematorium in real time and immediately notifies the operator if any abnormalities occur. The system of claim 1 .

5. The latency minimization unit The AI ​​predicts the waiting time in real time based on the operating status of the crematorium and notifies the bereaved family. The system of claim 1 .

6. The priority optimization unit Using an emotion estimation function, the priority is adjusted based on the emotional state of the bereaved family, and if stress is high, the priority is increased. The system of claim 1 .

7. The operation status grasping unit Using an emotion estimation function, the emotional state of the bereaved family is analyzed, and if stress levels are high, the system preferentially suggests the most suitable facility. The system of claim 1 .

8. The latency minimization unit Using an emotion estimation function, the emotional state of the bereaved family is analyzed, and if stress levels are high, a proposal is made to further shorten the waiting time. The system of claim 1 .

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