System

Abstract

An object of a system according to an embodiment is to digitize and efficiently manage warranty certificate.SOLUTION: A system includes a digitalization part, an analysis part, a management part, a retrieval part, a notification part, and a sharing part. The digitizing section digitizes the warranty certificate. The analysis unit analyzes the warranty certificate digitized by the digitizing unit. The management unit manages the warranty certificate analyzed by the analysis unit. The retrieval unit retrieves the warranty certificate managed by the management unit. The notifying unit notifies the deadline of the warranty certificate. The shared unit shares a warranty certificate.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 had the problem that managing paper guarantees is cumbersome and it is difficult to grasp the guarantee contents and expiration date.

[0005] The system according to the embodiment aims to digitize and efficiently manage warranty certificates. [Means for solving the problem]

[0006] The system according to the embodiment includes a digitizing unit, an analyzing unit, a managing unit, a searching unit, a notifying unit, and a sharing unit. The digitizing unit digitizes the warranty. The analyzing unit analyzes the warranty digitized by the digitizing unit. The managing unit manages the warranty analyzed by the analyzing unit. The searching unit searches for the warranty managed by the managing unit. The notifying unit notifies the expiration date of the warranty. The sharing unit shares the warranty. [Effects of the Invention]

[0007] The system according to the embodiment can digitize the warranty and manage it efficiently. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

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

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

[0028] (Example 1) The warranty management system according to an embodiment of the present invention is a system that efficiently manages warranty certificates using a generation AI and allows the contents of the warranty and the expiration date to be easily confirmed. As a result, the warranty management system makes it easy to manage warranty certificates and allows the contents of the warranty and the expiration date to be easily confirmed.

[0029] A warranty management system according to an embodiment includes a digitization unit, an analysis unit, a management unit, a search unit, a notification unit, and a sharing unit. The digitization unit digitizes warranty cards. For example, it scans paper warranty cards and converts them into digital data. The digitization unit can also convert printed warranty cards into text data using OCR technology. For example, it analyzes image data scanned by a scanner using OCR technology and converts it into text data. The analysis unit analyzes warranty cards digitized by the digitization unit. For example, a generation AI analyzes the contents of the warranty card and classifies them into appropriate categories. The analysis unit also understands the contents of the warranty card and registers them in a database. For example, the generation AI analyzes the contents of the warranty card and classifies them into iPhone warranties, home appliance warranties, life insurance certificates, etc. The management unit manages the warranty cards analyzed by the analysis unit. For example, it manages the warranties registered in the database and performs access control. The management unit can also back up warranty cards. For example, it periodically backs up the database to ensure data integrity. The search unit searches for warranty cards managed by the management unit. For example, the generation AI searches for and displays a specific warranty based on user instructions. The search unit can also perform keyword searches and filtering. For example, if a user requests, "Show me the iPhone warranty," the generation AI searches the database for the relevant warranty and displays it. The notification unit notifies the user of the warranty expiration date. For example, if the warranty period expires in one month, the generation AI notifies the user, "The warranty period for this home appliance will expire in one month." The notification unit can also provide email and push notifications. For example, it can send an email to the user's email address notifying them of the expiration of the warranty period. The sharing unit shares the warranty. For example, the generation AI sends the digital data of the warranty to a specified user. The sharing unit can also share links and files. For example, if a warranty is shared with family or friends, the generation AI generates a shared link and sends it to the specified user. This allows the warranty management system to efficiently digitize, analyze, manage, search, notify, and share warranties. For example, users can easily manage their warranties and check the warranty details and expiration dates.

[0030] The digitization unit can automatically recognize handwritten notes or annotations and include them in the digital data. For example, the digitization unit automatically recognizes handwritten notes and annotations written on a warranty card and includes them in the digital data. For example, it analyzes information such as repair history and purchase date written in the margins of the warranty card and registers it in a database. The digitization unit also uses handwriting recognition technology to convert handwritten notes written on the warranty card into text data, and the generation AI analyzes the content. For example, it automatically extracts precautions and special notices written on the warranty card. The digitization unit also detects handwritten notes and annotations from scanned images of the warranty card and integrates them into the digital data. For example, it automatically recognizes notes written on the back of the warranty card and saves them in a database. This allows for complete management of warranty card information by including handwritten notes and annotations in the digital data.

[0031] The digitization department can automatically translate warranty cards written in different languages ​​and manage them in a unified format. For example, the digitization department automatically translates warranty cards written in different languages ​​and converts them into digital data in a unified format. For example, warranty cards in English and Chinese are translated into Japanese and registered in a database. The digitization department also automatically detects text in different languages ​​when the generation AI analyzes the contents of the warranty card and translates it using a translation engine. For example, a French warranty card is translated into English and managed in a unified format. The digitization department also extracts text in different languages ​​from scanned images of the warranty card and automatically translates it using a translation engine. For example, a Spanish warranty card is translated into Japanese and stored in a database. This allows warranty cards in different languages ​​to be managed in a unified format.

[0032] The digitization department can simultaneously digitize a warranty and import related product manuals or purchase histories for comprehensive management. For example, when digitizing a warranty, the digitization department also scans related product manuals and purchase histories, converts them into digital data, and registers them in a database. For example, a home appliance warranty and its product manual are managed together. Furthermore, when the generation AI analyzes the contents of a warranty, the digitization department automatically imports related product manuals and purchase histories for comprehensive management. For example, an iPhone warranty and purchase history are stored together in a database. The digitization department also converts related product manuals and purchase histories into digital data along with the scanned image of the warranty, and manages them in a unified format. For example, a life insurance certificate and its contract details are managed together. This allows warranties to be managed together with related product manuals and purchase histories.

[0033] The digitization unit can manage the digitized warranty card using blockchain technology to prevent tampering. For example, the digitization unit manages the digitized warranty card using blockchain technology to prevent tampering. For example, the digital data of the warranty card is registered on the blockchain, making it impossible to tamper with. The digitization unit also has a generation AI analyze the contents of the warranty card, convert it into digital data, and then register that data on the blockchain. For example, a warranty card for a home appliance is stored on the blockchain to prevent tampering. The digitization unit also builds a system that converts scanned images of the warranty card into digital data and manages that data using blockchain technology. For example, a life insurance certificate is registered on the blockchain to prevent tampering. This allows the digitized warranty card to be managed to prevent tampering.

[0034] The management department can predict future trends based on past warranty data and make suggestions to users. For example, the management department develops an algorithm in which the generation AI analyzes past warranty data and predicts future trends. For example, it predicts the failure rate of a specific product and the trend toward extending the warranty period, and makes suggestions to users. The management department also predicts future trends based on past warranty data and makes customized suggestions to users. For example, it predicts a trend toward shorter warranty periods for specific home appliances and suggests extended warranties to users. The management department also builds a system in which the generation AI learns from past data and predicts future trends. For example, it predicts the possibility of changes to the coverage of a specific insurance product and provides appropriate advice to users. This makes it possible to predict future trends and make suggestions to users.

[0035] The management unit can provide customized alerts based on the user's lifestyle or frequency of use. For example, the generation AI in the management unit analyzes the user's lifestyle and frequency of use and provides customized alerts based on that. For example, when the warranty expiration date of a frequently used home appliance is approaching, a special alert is displayed. The management unit also manages warranty details and expiration dates based on the user's frequency of use data and builds a system that provides customized alerts. For example, when the warranty expiration date of a frequently used product is approaching, notifications are given priority. The management unit also analyzes the user's lifestyle data and provides customized alerts using the generation AI. For example, if the warranty expiration date is due to expire while the user is traveling, a notification is sent in advance. This makes it possible to provide customized alerts based on the user's lifestyle and frequency of use.

[0036] The management unit can work in conjunction with smart home devices to provide real-time alerts according to the usage of home appliances. For example, the management unit constructs a system in which the generation AI works in conjunction with smart home devices to provide real-time alerts according to the usage of home appliances. For example, if a refrigerator is used frequently, it will notify the user when the warranty expiration date is approaching. The management unit also analyzes the usage of home appliances based on data obtained from smart home devices and provides real-time alerts. For example, if a washing machine is used frequently, it will display a special alert when the warranty expiration date is approaching. The management unit also works in conjunction with smart home devices to provide customized alerts according to the usage of home appliances. For example, if an air conditioner is used for a long time, it will prioritize notifications when the warranty expiration date is approaching. This makes it possible to provide real-time alerts according to the usage of home appliances.

[0037] The management unit can provide personalized services by linking with the user's health data or lifestyle data. For example, the management unit builds a system in which a generation AI links with the user's health data and lifestyle data to manage coverage details and expiration dates. For example, it provides customized alerts based on the user's health condition. The management unit also manages coverage details and expiration dates based on the user's lifestyle data to provide personalized services. For example, it notifies the user of coverage expiration dates based on the user's sleep patterns. The management unit also manages coverage details and expiration dates by linking with the user's health data through a generation AI. For example, it proposes customized coverage details based on the user's exercise habits. This makes it possible to provide personalized services based on the user's health data and lifestyle data.

[0038] The search unit can use voice recognition technology to enable searches via voice input. For example, the search unit will build a system in which the generation AI uses voice recognition technology to enable users to search for warranties via voice input. For example, simply by speaking, "Show me the iPhone warranty," the relevant warranty will be displayed. The search unit will also use voice recognition technology to enable users to search for warranties via voice. For example, in response to a voice command such as "Find the refrigerator warranty," the generation AI will search for and display the relevant warranty. The search unit will also develop a system in which the generation AI analyzes voice input and displays the search results for warranty certificates. For example, in response to a voice command such as "Show me the insurance certificate," the system will search for and display the relevant certificate. This will enable searches via voice input.

[0039] The search unit can provide optimized search results based on the user's past search history or usage history. For example, the search unit uses a generation AI to analyze the user's past search history or usage history and build a system that optimizes search results for warranty certificates based on that. For example, frequently searched warranty certificates are displayed with priority. The search unit also customizes search results for warranty certificates based on the user's past search history. For example, warranty certificates that have been searched for in the past are displayed with priority. The search unit also uses a generation AI to analyze the user's usage history and optimize search results for warranty certificates based on that. For example, recently used warranty certificates are displayed with priority. This makes it possible to provide optimized search results based on the user's past search history or usage history.

[0040] The search unit can work in conjunction with mobile devices such as smartphones or tablets, enabling searches to be performed anywhere. For example, the generation AI works in conjunction with smartphones or tablets to build a system that allows users to search for warranties anywhere. For example, they can search for warranties using a smartphone even when they are out and about. The search unit also works in conjunction with mobile devices to enable users to search for warranties anytime, anywhere. For example, it searches for and displays warranties using a tablet. The generation AI also works in conjunction with mobile devices to improve the convenience of users when searching for warranties. For example, it allows users to search for warranties using voice input using a smartphone. This makes searches possible anywhere.

[0041] The search unit can also simultaneously display product reviews or user feedback related to the warranty search results. For example, the search unit will build a system that simultaneously displays related product reviews and user feedback when the generation AI searches for warranty results. For example, when a home appliance warranty is searched, reviews of that product will also be displayed. The search unit will also display product reviews and user feedback related to the warranty search results. For example, when an iPhone warranty is searched, reviews and feedback from other users will be displayed. The search unit will also develop a system that automatically displays related product reviews and user feedback when the generation AI searches for a warranty. For example, when an insurance certificate is searched, feedback from other users will be displayed. This makes it possible to simultaneously display product reviews and user feedback related to the warranty search results.

[0042] The notification unit works in conjunction with the user's schedule and can provide notifications at the optimal timing. For example, the generation AI works in conjunction with the user's schedule to build a system in which the notification unit notifies the user of warranty expiration dates at the optimal timing. For example, it works in conjunction with the user's calendar to provide notifications when there are no important appointments. The notification unit also notifies the user of warranty expiration dates at the optimal timing based on the user's schedule data. For example, it notifies the user during times when the user is not busy. The notification unit also works in conjunction with the user's schedule and notifies the user of warranty expiration dates at the appropriate timing. For example, it notifies the user during times when the user is relaxing. This makes it possible to provide notifications at the optimal timing based on the user's schedule.

[0043] The notification unit can work in conjunction with a wearable device such as a smartwatch or fitness tracker to receive notifications in real time. For example, the generation AI works in conjunction with a smartwatch or fitness tracker to build a system in which the user receives notifications in real time. For example, the notification unit displays a warranty expiration notification on a smartwatch. The notification unit also works in conjunction with a wearable device to enable the user to receive notifications anytime, anywhere. For example, the notification unit displays a warranty expiration notification on a fitness tracker. The generation AI also works in conjunction with a wearable device to improve the convenience of the user receiving notifications in real time. For example, the notification unit displays a voice notification on a smartwatch. This allows the user to receive notifications in real time by working in conjunction with a wearable device.

[0044] The notification unit can simultaneously provide upgrade information or special offer information for related products when notifying the expiration of a warranty. For example, the notification unit builds a system that simultaneously provides upgrade information or special offer information for related products when the generation AI notifies the expiration of a warranty. For example, when the warranty expiration of a home appliance is approaching, it provides information on the latest model. The notification unit also displays upgrade information or special offer information for related products simultaneously with the warranty expiration notification. For example, when the warranty expiration of a smartphone is approaching, it provides information on special offers for the latest model. The notification unit also develops a system that automatically provides upgrade information or special offer information for related products when the generation AI notifies the expiration of a warranty. For example, when the expiration of an insurance certificate is approaching, it provides information on new insurance products. This makes it possible to simultaneously provide upgrade information or special offer information for related products.

[0045] The sharing unit can suggest the optimal sharing method based on the usage or needs of the sharing recipient. For example, the sharing unit builds a system in which the generation AI analyzes the usage and needs of the sharing recipient and suggests the optimal sharing method. For example, the sharing unit sends the warranty card to a device that the sharing recipient frequently uses. The sharing unit also customizes the warranty card sharing method based on the needs of the sharing recipient. For example, if the sharing recipient prefers email, the warranty card will be sent by email. The sharing unit also analyzes the usage of the sharing recipient through the generation AI and suggests the optimal sharing method. For example, if the sharing recipient mainly uses a smartphone, the warranty card will be sent to the smartphone. This makes it possible to suggest the optimal sharing method based on the usage and needs of the sharing recipient.

[0046] The sharing unit can provide a function that allows comments or feedback to be added to a shared warranty certificate in real time. The sharing unit, for example, builds a system that provides a function that allows the generation AI to add comments or feedback to a shared warranty certificate in real time. For example, the other party with whom it is shared can add comments to the warranty certificate. The sharing unit also provides a function that allows feedback to be added to a shared warranty certificate in real time. For example, the other party with whom it is shared can add questions or opinions to the warranty certificate. The sharing unit also provides a function that allows the generation AI to add comments or feedback to a shared warranty certificate in real time. For example, the other party with whom it is shared can add corrections or supplementary information to the warranty certificate. This allows comments or feedback to be added to the shared warranty certificate in real time.

[0047] The sharing unit can work with social media platforms to enable the warranty to be easily shared. For example, the generation AI works with social media platforms to build a system that enables users to easily share warranty cards. For example, the warranty card is shared on Facebook or Twitter. The sharing unit also works with social media platforms to enable users to easily share warranty cards. For example, an image of the warranty card is shared on Instagram. The generation AI also works with social media platforms to enable users to easily share warranty cards. For example, warranty card information is shared on LinkedIn. This makes it possible to easily share warranty cards by working with social media platforms.

[0048] The sharing unit can automatically translate a warranty into the language of the other party when it is shared, enabling international sharing. For example, the sharing unit builds a system in which, when the generating AI shares a warranty, it automatically translates it into the language of the other party, enabling international sharing. For example, it translates an English warranty into Japanese and shares it. The sharing unit also automatically translates it into the language of the other party, enabling the warranty to be shared internationally. For example, it translates a French warranty into English and shares it. The sharing unit also automatically translates a warranty into the language of the other party when it is shared, enabling international sharing. For example, it translates a Chinese warranty into Japanese and shares it. This allows the warranty to be automatically translated into the language of the other party when it is shared, enabling international sharing.

[0049] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0050] The warranty management system may further include a purchase history analysis unit that analyzes a user's purchase history and automatically registers related warranty certificates. For example, the purchase history analysis unit may automatically obtain warranty certificates for products purchased by a user on an online shopping site and register them in a database. The purchase history analysis unit may also analyze a user's credit card usage history and automatically register warranty certificates for purchased products. For example, the purchase history analysis unit may obtain information about purchased products from credit card statements and automatically digitize warranty certificates. The purchase history analysis unit may also analyze a user's email account and automatically obtain warranty certificates from purchase confirmation emails. For example, the warranty certificate attached to the email may be automatically digitized and registered in a database. This eliminates the need for users to manually register warranty certificates, allowing for more efficient management.

[0051] The warranty management system can further include an extended warranty suggestion unit that suggests extended warranty options to users when the warranty expiration date is approaching. For example, the system notifies users of extended warranty options one month before the warranty period for a home appliance expires. The extended warranty suggestion unit can also analyze the user's frequency of use and the condition of the product to suggest the most appropriate extended warranty plan. For example, it can suggest a long-term extended warranty for a frequently used product. The extended warranty suggestion unit can also make customized suggestions based on the user's past extended warranty usage history. For example, it can offer a special discount to users who have used an extended warranty in the past. This allows users to select an appropriate extended warranty before the warranty period expires.

[0052] The warranty management system may further include a maintenance schedule generation unit that analyzes the contents of the warranty and automatically generates a maintenance schedule for the related product. For example, a car warranty may be analyzed to automatically generate a schedule for periodic oil changes and inspections. The maintenance schedule generation unit may also analyze the user's usage status and suggest optimal maintenance times. For example, it may suggest more frequent maintenance for frequently used home appliances. The maintenance schedule generation unit may also link with the user's calendar and automatically add scheduled maintenance events. For example, maintenance events may be added during the user's free time. This allows the user to efficiently perform product maintenance.

[0053] The warranty management system can further include a recall notification unit that analyzes the contents of the warranty and automatically notifies the user of recall information for related products. For example, it can analyze a car warranty and notify the user when a recall occurs. The recall notification unit can also analyze the user's location and guide the user to the nearest recall facility. For example, it can guide the user to the nearest dealer or repair shop based on the user's address information. The recall notification unit can also update recall information in real time to provide the user with the latest information. For example, it can immediately notify the user when new recall information is released. This allows the user to quickly understand the recall information and take appropriate action.

[0054] The warranty management system may further include a usage instruction providing unit that analyzes the contents of the warranty and provides usage instructions and troubleshooting information for the related product. For example, the warranty for a home appliance may be analyzed and usage instructions and troubleshooting information may be provided to the user. The usage instruction providing unit may also analyze the user's usage status and suggest optimal usage methods. For example, it may suggest efficient usage methods for frequently used products. The usage instruction providing unit may also answer user questions in real time. For example, it may provide instant answers to questions about how to use the product. This allows the user to use the product correctly and prevent problems before they occur.

[0055] The processing flow of the first embodiment will be briefly explained below.

[0056] Step 1: The digitization unit digitizes the warranty. For example, a paper warranty is scanned and converted into digital data. The digitization unit can also convert a printed warranty into text data using OCR technology. For example, image data scanned with a scanner is analyzed using OCR technology and converted into text data. Step 2: The analysis unit analyzes the warranty card digitized by the digitization unit. For example, the generation AI analyzes the contents of the warranty card and classifies it into the appropriate category. The analysis unit also understands the contents of the warranty card and registers them in a database. For example, the generation AI analyzes the contents of the warranty card and classifies it into an iPhone warranty card, a home appliance warranty card, a life insurance certificate, etc. Step 3: The management unit manages the warranty certificates analyzed by the analysis unit. For example, it manages the warranty certificates registered in a database and performs access control. The management unit can also back up the warranty certificates. For example, it can periodically create backups of the database to ensure data integrity. Step 4: The search unit searches for warranty cards managed by the management unit. For example, the generation AI searches for and displays a specific warranty card based on the user's instructions. The search unit can also perform keyword searches and filtering. For example, if the user instructs, "Show me the iPhone warranty card," the generation AI searches the database for the relevant warranty card and displays it. Step 5: The notification unit notifies the user of the expiration date of the warranty. For example, if the warranty period expires in one month, the generation AI notifies the user, "The warranty period for this appliance will expire in one month." The notification unit can also send email notifications or push notifications. For example, it can send an email to the user's email address notifying them of the expiration of the warranty period. Step 6: The sharing unit shares the warranty. For example, the generation AI sends the digital data of the warranty to a designated user. The sharing unit can also share links and files. For example, when sharing a warranty with family or friends, the generation AI generates a sharing link and sends it to the designated user.

[0057] (Example 2) The warranty management system according to an embodiment of the present invention is a system that efficiently manages warranty certificates using a generation AI and allows the contents of the warranty and the expiration date to be easily confirmed. As a result, the warranty management system makes it easy to manage warranty certificates and allows the contents of the warranty and the expiration date to be easily confirmed.

[0058] A warranty management system according to an embodiment includes a digitization unit, an analysis unit, a management unit, a search unit, a notification unit, and a sharing unit. The digitization unit digitizes warranty cards. For example, it scans paper warranty cards and converts them into digital data. The digitization unit can also convert printed warranty cards into text data using OCR technology. For example, it analyzes image data scanned by a scanner using OCR technology and converts it into text data. The analysis unit analyzes warranty cards digitized by the digitization unit. For example, a generation AI analyzes the contents of the warranty card and classifies them into appropriate categories. The analysis unit also understands the contents of the warranty card and registers them in a database. For example, the generation AI analyzes the contents of the warranty card and classifies them into iPhone warranties, home appliance warranties, life insurance certificates, etc. The management unit manages the warranty cards analyzed by the analysis unit. For example, it manages the warranties registered in the database and performs access control. The management unit can also back up warranty cards. For example, it periodically backs up the database to ensure data integrity. The search unit searches for warranty cards managed by the management unit. For example, the generation AI searches for and displays a specific warranty based on user instructions. The search unit can also perform keyword searches and filtering. For example, if a user requests, "Show me the iPhone warranty," the generation AI searches the database for the relevant warranty and displays it. The notification unit notifies the user of the warranty expiration date. For example, if the warranty period expires in one month, the generation AI notifies the user, "The warranty period for this home appliance will expire in one month." The notification unit can also provide email and push notifications. For example, it can send an email to the user's email address notifying them of the expiration of the warranty period. The sharing unit shares the warranty. For example, the generation AI sends the digital data of the warranty to a specified user. The sharing unit can also share links and files. For example, if a warranty is shared with family or friends, the generation AI generates a shared link and sends it to the specified user. This allows the warranty management system to efficiently digitize, analyze, manage, search, notify, and share warranties. For example, users can easily manage their warranties and check the warranty details and expiration dates.

[0059] The digitization unit can automatically recognize handwritten notes or annotations and include them in the digital data. For example, the digitization unit automatically recognizes handwritten notes and annotations written on a warranty card and includes them in the digital data. For example, it analyzes information such as repair history and purchase date written in the margins of the warranty card and registers it in a database. The digitization unit also uses handwriting recognition technology to convert handwritten notes written on the warranty card into text data, and the generation AI analyzes the content. For example, it automatically extracts precautions and special notices written on the warranty card. The digitization unit also detects handwritten notes and annotations from scanned images of the warranty card and integrates them into the digital data. For example, it automatically recognizes notes written on the back of the warranty card and saves them in a database. This allows for complete management of warranty card information by including handwritten notes and annotations in the digital data.

[0060] The digitization department can automatically translate warranty cards written in different languages ​​and manage them in a unified format. For example, the digitization department automatically translates warranty cards written in different languages ​​and converts them into digital data in a unified format. For example, warranty cards in English and Chinese are translated into Japanese and registered in a database. The digitization department also automatically detects text in different languages ​​when the generation AI analyzes the contents of the warranty card and translates it using a translation engine. For example, a French warranty card is translated into English and managed in a unified format. The digitization department also extracts text in different languages ​​from scanned images of the warranty card and automatically translates it using a translation engine. For example, a Spanish warranty card is translated into Japanese and stored in a database. This allows warranty cards in different languages ​​to be managed in a unified format.

[0061] The digitization unit uses the emotion estimation function to analyze the user's emotion regarding the contents of the warranty and can prioritize digitization of warranty cards that are highly important. The digitization unit, for example, uses the emotion estimation function to analyze the emotion of the user when scanning the warranty and prioritize digitization of warranty cards that are highly important. For example, warranty cards that the user feels anxious or impatient about are processed preferentially. The digitization unit also analyzes the user's emotion regarding the contents of the warranty in real time and automatically determines warranty cards that are highly important. For example, warranty cards that the user feels joy or relief about are prioritized for digitization. The digitization unit also builds a system that prioritizes digitization of warranty cards that the user feels important based on the emotion estimation data. For example, warranty cards that the user feels strong emotions about are automatically detected and converted into digital data. This allows warranty cards that are highly important to be digitized preferentially based on the user's emotion.

[0062] The digitization department can simultaneously digitize a warranty and import related product manuals or purchase histories for comprehensive management. For example, when digitizing a warranty, the digitization department also scans related product manuals and purchase histories, converts them into digital data, and registers them in a database. For example, a home appliance warranty and its product manual are managed together. Furthermore, when the generation AI analyzes the contents of a warranty, the digitization department automatically imports related product manuals and purchase histories for comprehensive management. For example, an iPhone warranty and purchase history are stored together in a database. The digitization department also converts related product manuals and purchase histories into digital data along with the scanned image of the warranty, and manages them in a unified format. For example, a life insurance certificate and its contract details are managed together. This allows warranties to be managed together with related product manuals and purchase histories.

[0063] The digitization unit can manage the digitized warranty card using blockchain technology to prevent tampering. For example, the digitization unit manages the digitized warranty card using blockchain technology to prevent tampering. For example, the digital data of the warranty card is registered on the blockchain, making it impossible to tamper with. The digitization unit also has a generation AI analyze the contents of the warranty card, convert it into digital data, and then register that data on the blockchain. For example, a warranty card for a home appliance is stored on the blockchain to prevent tampering. The digitization unit also builds a system that converts scanned images of the warranty card into digital data and manages that data using blockchain technology. For example, a life insurance certificate is registered on the blockchain to prevent tampering. This allows the digitized warranty card to be managed to prevent tampering.

[0064] The digitization unit can use the emotion estimation function to analyze the emotion a user feels when scanning a warranty card and provide an interface for reducing stress. The digitization unit, for example, uses the emotion estimation function to analyze the emotion a user feels when scanning a warranty card in real time and provide an interface for reducing stress. For example, music or a message that helps the user relax is displayed. The digitization unit also analyzes the user's emotional state and automatically adjusts the interface for reducing stress. For example, if the user is feeling anxious, a message that gives a sense of security is displayed. The digitization unit also builds a system that provides an interface for reducing stress a user feels when scanning a warranty card based on the emotion estimation data. For example, visuals or audio that helps the user relax are displayed. This makes it possible to provide an interface for reducing stress for the user.

[0065] The management department can predict future trends based on past warranty data and make suggestions to users. For example, the management department develops an algorithm in which the generation AI analyzes past warranty data and predicts future trends. For example, it predicts the failure rate of a specific product and the trend toward extending the warranty period, and makes suggestions to users. The management department also predicts future trends based on past warranty data and makes customized suggestions to users. For example, it predicts a trend toward shorter warranty periods for specific home appliances and suggests extended warranties to users. The management department also builds a system in which the generation AI learns from past data and predicts future trends. For example, it predicts the possibility of changes to the coverage of a specific insurance product and provides appropriate advice to users. This makes it possible to predict future trends and make suggestions to users.

[0066] The management unit can provide customized alerts based on the user's lifestyle or frequency of use. For example, the generation AI in the management unit analyzes the user's lifestyle and frequency of use and provides customized alerts based on that. For example, when the warranty expiration date of a frequently used home appliance is approaching, a special alert is displayed. The management unit also manages warranty details and expiration dates based on the user's frequency of use data and builds a system that provides customized alerts. For example, when the warranty expiration date of a frequently used product is approaching, notifications are given priority. The management unit also analyzes the user's lifestyle data and provides customized alerts using the generation AI. For example, if the warranty expiration date is due to expire while the user is traveling, a notification is sent in advance. This makes it possible to provide customized alerts based on the user's lifestyle and frequency of use.

[0067] The management unit can use the emotion estimation function to analyze the emotions of the user when checking the coverage details or expiration date, and provide information to elicit positive emotions. For example, the management unit can use the emotion estimation function to analyze the emotions of the user when checking the coverage details or expiration date in real time, and provide information to elicit positive emotions. For example, the management unit displays a message that gives the user a sense of security. The management unit also builds a system that analyzes the user's emotional state and automatically provides information to elicit positive emotions. For example, the management unit displays details of the coverage details that make the user feel happy. The management unit also provides information to elicit positive emotions when the user checks the coverage details or expiration date, based on the emotion estimation data. For example, the management unit suggests an option to extend the coverage period that will give the user a sense of satisfaction. In this way, information to elicit positive emotions can be provided to the user.

[0068] The management unit can work in conjunction with smart home devices to provide real-time alerts according to the usage of home appliances. For example, the management unit constructs a system in which the generation AI works in conjunction with smart home devices to provide real-time alerts according to the usage of home appliances. For example, if a refrigerator is used frequently, it will notify the user when the warranty expiration date is approaching. The management unit also analyzes the usage of home appliances based on data obtained from smart home devices and provides real-time alerts. For example, if a washing machine is used frequently, it will display a special alert when the warranty expiration date is approaching. The management unit also works in conjunction with smart home devices to provide customized alerts according to the usage of home appliances. For example, if an air conditioner is used for a long time, it will prioritize notifications when the warranty expiration date is approaching. This makes it possible to provide real-time alerts according to the usage of home appliances.

[0069] The management unit can provide personalized services by linking with the user's health data or lifestyle data. For example, the management unit builds a system in which a generation AI links with the user's health data and lifestyle data to manage coverage details and expiration dates. For example, it provides customized alerts based on the user's health condition. The management unit also manages coverage details and expiration dates based on the user's lifestyle data to provide personalized services. For example, it notifies the user of coverage expiration dates based on the user's sleep patterns. The management unit also manages coverage details and expiration dates by linking with the user's health data through a generation AI. For example, it proposes customized coverage details based on the user's exercise habits. This makes it possible to provide personalized services based on the user's health data and lifestyle data.

[0070] The search unit can use voice recognition technology to enable searches via voice input. For example, the search unit will build a system in which the generation AI uses voice recognition technology to enable users to search for warranties via voice input. For example, simply by speaking, "Show me the iPhone warranty," the relevant warranty will be displayed. The search unit will also use voice recognition technology to enable users to search for warranties via voice. For example, in response to a voice command such as "Find the refrigerator warranty," the generation AI will search for and display the relevant warranty. The search unit will also develop a system in which the generation AI analyzes voice input and displays the search results for warranty certificates. For example, in response to a voice command such as "Show me the insurance certificate," the system will search for and display the relevant certificate. This will enable searches via voice input.

[0071] The search unit can provide optimized search results based on the user's past search history or usage history. For example, the search unit uses a generation AI to analyze the user's past search history or usage history and build a system that optimizes search results for warranty certificates based on that. For example, frequently searched warranty certificates are displayed with priority. The search unit also customizes search results for warranty certificates based on the user's past search history. For example, warranty certificates that have been searched for in the past are displayed with priority. The search unit also uses a generation AI to analyze the user's usage history and optimize search results for warranty certificates based on that. For example, recently used warranty certificates are displayed with priority. This makes it possible to provide optimized search results based on the user's past search history or usage history.

[0072] The search unit can use the emotion estimation function to analyze the emotion of a user when searching for a warranty and display search results to reduce stress. The search unit, for example, uses the emotion estimation function to analyze the emotion of a user when searching for a warranty in real time and display search results to reduce stress. For example, if the user is feeling impatient, the search unit quickly displays search results. The search unit also builds a system that analyzes the user's emotional state and automatically displays search results to reduce stress. For example, if the user is feeling anxious, the search unit displays search results that give a sense of security. The search unit also displays search results to reduce stress when the user searches for a warranty based on the emotion estimation data. For example, if the user is irritated, the search results are displayed in an easy-to-understand manner. This makes it possible to display search results to reduce stress for the user.

[0073] The search unit can work in conjunction with mobile devices such as smartphones or tablets, enabling searches to be performed anywhere. For example, the generation AI works in conjunction with smartphones or tablets to build a system that allows users to search for warranties anywhere. For example, they can search for warranties using a smartphone even when they are out and about. The search unit also works in conjunction with mobile devices to enable users to search for warranties anytime, anywhere. For example, it searches for and displays warranties using a tablet. The generation AI also works in conjunction with mobile devices to improve the convenience of users when searching for warranties. For example, it allows users to search for warranties using voice input using a smartphone. This makes searches possible anywhere.

[0074] The search unit can also simultaneously display product reviews or user feedback related to the warranty search results. For example, the search unit will build a system that simultaneously displays related product reviews and user feedback when the generation AI searches for warranty results. For example, when a home appliance warranty is searched, reviews of that product will also be displayed. The search unit will also display product reviews and user feedback related to the warranty search results. For example, when an iPhone warranty is searched, reviews and feedback from other users will be displayed. The search unit will also develop a system that automatically displays related product reviews and user feedback when the generation AI searches for a warranty. For example, when an insurance certificate is searched, feedback from other users will be displayed. This makes it possible to simultaneously display product reviews and user feedback related to the warranty search results.

[0075] The search unit can use the emotion estimation function to analyze the emotion a user has when searching for a warranty, and display search results that elicit positive emotions. The search unit, for example, uses the emotion estimation function to analyze the emotion a user has when searching for a warranty in real time, and display search results that elicit positive emotions. For example, it displays search results that make the user feel happy. The search unit also builds a system that analyzes the emotional state of the user and automatically displays search results that elicit positive emotions. For example, it displays warranty details that give the user a sense of satisfaction. The search unit also displays search results that elicit positive emotions when the user searches for a warranty, based on the emotion estimation data. For example, it displays warranty information that gives the user a sense of security. This makes it possible to display search results that elicit positive emotions from the user.

[0076] The notification unit works in conjunction with the user's schedule and can provide notifications at the optimal timing. For example, the generation AI works in conjunction with the user's schedule to build a system in which the notification unit notifies the user of warranty expiration dates at the optimal timing. For example, it works in conjunction with the user's calendar to provide notifications when there are no important appointments. The notification unit also notifies the user of warranty expiration dates at the optimal timing based on the user's schedule data. For example, it notifies the user during times when the user is not busy. The notification unit also works in conjunction with the user's schedule and notifies the user of warranty expiration dates at the appropriate timing. For example, it notifies the user during times when the user is relaxing. This makes it possible to provide notifications at the optimal timing based on the user's schedule.

[0077] The notification unit can use the emotion estimation function to analyze the user's emotion when receiving a notification and provide notification content that elicits positive emotions. The notification unit, for example, uses the emotion estimation function to analyze the user's emotion when receiving a notification in real time and provide notification content that elicits positive emotions. For example, it displays a message that makes the user feel happy. The notification unit also analyzes the user's emotional state and builds a system that automatically provides notification content that elicits positive emotions. For example, it displays notification content that gives the user a sense of security. The notification unit also provides notification content that elicits positive emotions when the user receives a notification based on the emotion estimation data. For example, it displays notification content that gives the user a sense of satisfaction. In this way, it is possible to provide notification content that elicits positive emotions from the user.

[0078] The notification unit can work in conjunction with a wearable device such as a smartwatch or fitness tracker to receive notifications in real time. For example, the generation AI works in conjunction with a smartwatch or fitness tracker to build a system in which the user receives notifications in real time. For example, the notification unit displays a warranty expiration notification on a smartwatch. The notification unit also works in conjunction with a wearable device to enable the user to receive notifications anytime, anywhere. For example, the notification unit displays a warranty expiration notification on a fitness tracker. The generation AI also works in conjunction with a wearable device to improve the convenience of the user receiving notifications in real time. For example, the notification unit displays a voice notification on a smartwatch. This allows the user to receive notifications in real time by working in conjunction with a wearable device.

[0079] The notification unit can simultaneously provide upgrade information or special offer information for related products when notifying the expiration of a warranty. For example, the notification unit builds a system that simultaneously provides upgrade information or special offer information for related products when the generation AI notifies the expiration of a warranty. For example, when the warranty expiration of a home appliance is approaching, it provides information on the latest model. The notification unit also displays upgrade information or special offer information for related products simultaneously with the warranty expiration notification. For example, when the warranty expiration of a smartphone is approaching, it provides information on special offers for the latest model. The notification unit also develops a system that automatically provides upgrade information or special offer information for related products when the generation AI notifies the expiration of a warranty. For example, when the expiration of an insurance certificate is approaching, it provides information on new insurance products. This makes it possible to simultaneously provide upgrade information or special offer information for related products.

[0080] The notification unit can use the emotion estimation function to analyze the user's emotion when receiving a notification and provide notification content to alleviate negative emotions. The notification unit, for example, uses the emotion estimation function to analyze the user's emotion when receiving a notification in real time and provide notification content to alleviate negative emotions. For example, if the user is feeling anxious, a message that gives a sense of security is displayed. The notification unit also builds a system that analyzes the user's emotional state and automatically provides notification content to alleviate negative emotions. For example, if the user is feeling stressed, a notification that helps the user relax is displayed. The notification unit also provides notification content to alleviate negative emotions when the user receives a notification based on the emotion estimation data. For example, if the user is feeling impatient, a message urging the user to stay calm is displayed. This makes it possible to provide notification content to alleviate negative emotions.

[0081] The sharing unit can suggest the optimal sharing method based on the usage or needs of the sharing recipient. For example, the sharing unit builds a system in which the generation AI analyzes the usage and needs of the sharing recipient and suggests the optimal sharing method. For example, the sharing unit sends the warranty card to a device that the sharing recipient frequently uses. The sharing unit also customizes the warranty card sharing method based on the needs of the sharing recipient. For example, if the sharing recipient prefers email, the warranty card will be sent by email. The sharing unit also analyzes the usage of the sharing recipient through the generation AI and suggests the optimal sharing method. For example, if the sharing recipient mainly uses a smartphone, the warranty card will be sent to the smartphone. This makes it possible to suggest the optimal sharing method based on the usage and needs of the sharing recipient.

[0082] The sharing unit can provide a function that allows comments or feedback to be added to a shared warranty certificate in real time. The sharing unit, for example, builds a system that provides a function that allows the generation AI to add comments or feedback to a shared warranty certificate in real time. For example, the other party with whom it is shared can add comments to the warranty certificate. The sharing unit also provides a function that allows feedback to be added to a shared warranty certificate in real time. For example, the other party with whom it is shared can add questions or opinions to the warranty certificate. The sharing unit also provides a function that allows the generation AI to add comments or feedback to a shared warranty certificate in real time. For example, the other party with whom it is shared can add corrections or supplementary information to the warranty certificate. This allows comments or feedback to be added to the shared warranty certificate in real time.

[0083] The sharing unit can work with social media platforms to enable the warranty to be easily shared. For example, the generation AI works with social media platforms to build a system that enables users to easily share warranty cards. For example, the warranty card is shared on Facebook or Twitter. The sharing unit also works with social media platforms to enable users to easily share warranty cards. For example, an image of the warranty card is shared on Instagram. The generation AI also works with social media platforms to enable users to easily share warranty cards. For example, warranty card information is shared on LinkedIn. This makes it possible to easily share warranty cards by working with social media platforms.

[0084] The sharing unit can automatically translate a warranty into the language of the other party when it is shared, enabling international sharing. For example, the sharing unit builds a system in which, when the generating AI shares a warranty, it automatically translates it into the language of the other party, enabling international sharing. For example, it translates an English warranty into Japanese and shares it. The sharing unit also automatically translates it into the language of the other party, enabling the warranty to be shared internationally. For example, it translates a French warranty into English and shares it. The sharing unit also automatically translates a warranty into the language of the other party when it is shared, enabling international sharing. For example, it translates a Chinese warranty into Japanese and shares it. This allows the warranty to be automatically translated into the language of the other party when it is shared, enabling international sharing.

[0085] The sharing unit can use the emotion estimation function to analyze the user's emotion toward the shared warranty and provide a sharing method for reducing negative emotions. The sharing unit, for example, uses the emotion estimation function to analyze the user's emotion toward the shared warranty in real time and provide a sharing method for reducing negative emotions. For example, if the user is feeling anxious, the sharing unit displays a shared message that gives a sense of security. The sharing unit also builds a system that analyzes the user's emotional state and automatically provides a sharing method for reducing negative emotions. For example, if the user is feeling stressed, the sharing unit suggests a sharing method that helps the user relax. The sharing unit also provides a sharing method for reducing negative emotions toward the shared warranty based on the emotion estimation data. For example, if the user is feeling impatient, the sharing unit suggests a sharing method that encourages the user to stay calm. This makes it possible to provide a sharing method for reducing negative emotions toward the shared warranty.

[0086] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0087] The warranty management system may further include a purchase history analysis unit that analyzes a user's purchase history and automatically registers related warranty certificates. For example, the purchase history analysis unit may automatically obtain warranty certificates for products purchased by a user on an online shopping site and register them in a database. The purchase history analysis unit may also analyze a user's credit card usage history and automatically register warranty certificates for purchased products. For example, the purchase history analysis unit may obtain information about purchased products from credit card statements and automatically digitize warranty certificates. The purchase history analysis unit may also analyze a user's email account and automatically obtain warranty certificates from purchase confirmation emails. For example, the warranty certificate attached to the email may be automatically digitized and registered in a database. This eliminates the need for users to manually register warranty certificates, allowing for more efficient management.

[0088] The warranty management system can further include an extended warranty suggestion unit that suggests extended warranty options to users when the warranty expiration date is approaching. For example, the system notifies users of extended warranty options one month before the warranty period for a home appliance expires. The extended warranty suggestion unit can also analyze the user's frequency of use and the condition of the product to suggest the most appropriate extended warranty plan. For example, it can suggest a long-term extended warranty for a frequently used product. The extended warranty suggestion unit can also make customized suggestions based on the user's past extended warranty usage history. For example, it can offer a special discount to users who have used an extended warranty in the past. This allows users to select an appropriate extended warranty before the warranty period expires.

[0089] The warranty management system may further include a maintenance schedule generation unit that analyzes the contents of the warranty and automatically generates a maintenance schedule for the related product. For example, a car warranty may be analyzed to automatically generate a schedule for periodic oil changes and inspections. The maintenance schedule generation unit may also analyze the user's usage status and suggest optimal maintenance times. For example, it may suggest more frequent maintenance for frequently used home appliances. The maintenance schedule generation unit may also link with the user's calendar and automatically add scheduled maintenance events. For example, maintenance events may be added during the user's free time. This allows the user to efficiently perform product maintenance.

[0090] The warranty management system can further include a recall notification unit that analyzes the contents of the warranty and automatically notifies the user of recall information for related products. For example, it can analyze a car warranty and notify the user when a recall occurs. The recall notification unit can also analyze the user's location and guide the user to the nearest recall facility. For example, it can guide the user to the nearest dealer or repair shop based on the user's address information. The recall notification unit can also update recall information in real time to provide the user with the latest information. For example, it can immediately notify the user when new recall information is released. This allows the user to quickly understand the recall information and take appropriate action.

[0091] The warranty management system may further include a usage instruction providing unit that analyzes the contents of the warranty and provides usage instructions and troubleshooting information for the related product. For example, the warranty for a home appliance may be analyzed and usage instructions and troubleshooting information may be provided to the user. The usage instruction providing unit may also analyze the user's usage status and suggest optimal usage methods. For example, it may suggest efficient usage methods for frequently used products. The usage instruction providing unit may also answer user questions in real time. For example, it may provide instant answers to questions about how to use the product. This allows the user to use the product correctly and prevent problems before they occur.

[0092] The warranty management system may further include an emotional support unit that analyzes the user's emotions and provides support to alleviate any anxieties or doubts about the contents of the warranty. For example, if the user feels anxious when checking the contents of the warranty, a message that gives a sense of security may be displayed. The emotional support unit may also analyze the user's emotional state in real time and provide appropriate support. For example, if the user has doubts, a detailed explanation may be provided. The emotional support unit may also provide customized support based on the user's emotional data. For example, special support may be provided to users who have felt anxious in the past. This allows the user to resolve any anxieties or doubts about the contents of the warranty and use the service with peace of mind.

[0093] The warranty management system may further include a positive emotion unit that analyzes the user's emotions and provides information to elicit positive emotions regarding the warranty contents. For example, a message that makes the user feel happy when checking the warranty contents may be displayed. The positive emotion unit may also analyze the user's emotional state in real time and provide information to elicit positive emotions. For example, details of the warranty contents that will give the user a sense of satisfaction may be displayed. The positive emotion unit may also provide customized information based on the user's emotional data. For example, special information may be provided to a user who has felt happy in the past. This allows the user to have positive emotions regarding the warranty contents.

[0094] The warranty management system may further include a negative emotion reduction unit that analyzes the user's emotions and provides information to reduce negative emotions regarding the contents of the warranty. For example, if the user feels anxious when checking the contents of the warranty, a message that gives a sense of security is displayed. The negative emotion reduction unit may also analyze the user's emotional state in real time and provide information to reduce negative emotions. For example, if the user feels anxious, a message urging the user to stay calm is displayed. The negative emotion reduction unit may also provide customized information based on the user's emotional data. For example, special support may be provided to users who have felt anxious in the past. This allows the user to reduce negative emotions regarding the contents of the warranty and use the service with peace of mind.

[0095] The warranty management system may further include an emotional stress reduction unit that analyzes the user's emotions and provides an interface for reducing stress caused by the contents of the warranty. For example, music or visuals that help the user relax when checking the warranty may be displayed. The emotional stress reduction unit may also analyze the user's emotional state in real time and provide an interface for reducing stress. For example, if the user is feeling anxious, a message that gives a sense of security may be displayed. The emotional stress reduction unit may also provide a customized interface based on the user's emotional data. For example, a special interface may be provided for users who have experienced stress in the past. This allows the user to reduce stress when checking the contents of the warranty.

[0096] The warranty management system may further include a positive emotion notification unit that analyzes the user's emotions and sends notifications to elicit positive emotions regarding the warranty contents. For example, a message that makes the user feel happy is displayed when the user checks the warranty expiration date. The positive emotion notification unit may also analyze the user's emotional state in real time and send notifications to elicit positive emotions. For example, it may notify the user of details about the warranty that will give the user a sense of satisfaction. The positive emotion notification unit may also send customized notifications based on the user's emotional data. For example, it may provide a special notification to a user who has felt happy in the past. This allows the user to have positive emotions regarding the warranty contents.

[0097] The processing flow of the second embodiment will be briefly explained below.

[0098] Step 1: The digitization unit digitizes the warranty. For example, a paper warranty is scanned and converted into digital data. The digitization unit can also convert a printed warranty into text data using OCR technology. For example, image data scanned with a scanner is analyzed using OCR technology and converted into text data. Step 2: The analysis unit analyzes the warranty card digitized by the digitization unit. For example, the generation AI analyzes the contents of the warranty card and classifies it into the appropriate category. The analysis unit also understands the contents of the warranty card and registers them in a database. For example, the generation AI analyzes the contents of the warranty card and classifies it into an iPhone warranty card, a home appliance warranty card, a life insurance certificate, etc. Step 3: The management unit manages the warranty certificates analyzed by the analysis unit. For example, it manages the warranty certificates registered in a database and performs access control. The management unit can also back up the warranty certificates. For example, it can periodically create backups of the database to ensure data integrity. Step 4: The search unit searches for warranty cards managed by the management unit. For example, the generation AI searches for and displays a specific warranty card based on the user's instructions. The search unit can also perform keyword searches and filtering. For example, if the user instructs, "Show me the iPhone warranty card," the generation AI searches the database for the relevant warranty card and displays it. Step 5: The notification unit notifies the user of the expiration date of the warranty. For example, if the warranty period expires in one month, the generation AI notifies the user, "The warranty period for this appliance will expire in one month." The notification unit can also send email notifications or push notifications. For example, it can send an email to the user's email address notifying them of the expiration of the warranty period. Step 6: The sharing unit shares the warranty. For example, the generation AI sends the digital data of the warranty to a designated user. The sharing unit can also share links and files. For example, when sharing a warranty with family or friends, the generation AI generates a sharing link and sends it to the designated user.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0103] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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).

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0118] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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).

[0123] 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.

[0124] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0133] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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).

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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).

[0152] 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.

[0153] 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."

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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]

[0166] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a digitization department that digitizes the warranty; an analysis unit that analyzes the warranty card digitized by the digitization unit; a management unit that manages the warranty analyzed by the analysis unit; a search unit that searches the guarantees managed by the management unit; a notification unit that notifies the expiration date of the warranty; a shared section that shares the warranty; A system characterized by:

2. The digitizing unit Analyze user sentiment regarding the contents of the warranty and prioritize digitizing warranty certificates that are of high importance.

2. The system of claim 1.

3. The management unit Predict future trends based on past warranty data and make suggestions to users 2. The system of claim 1.

4. The search unit Uses voice recognition technology to enable voice-input searches 2. The system of claim 1.

5. The notification unit Linking with the user's schedule, the notification is sent at the optimal time 2. The system of claim 1.

6. The common part is Suggest the best sharing method based on the recipient's usage or needs 2. The system of claim 1.

7. The management unit Analyze the user's emotions when checking the details of the warranty or the expiration date, and provide information to elicit positive emotions.

2. The system of claim 1.

8. The search unit Analyzing the user's feelings when searching for the warranty, and displaying search results to reduce stress.

2. The system of claim 1.

Images