System

Abstract

An object of a system according to an embodiment is to quickly and accurately provide the location and facility information of an optimum toilet at a place where a user has gone.SOLUTION: A system includes a toilet information acquisition part, an analysis part, and a provision part. The toilet information acquisition unit acquires the location and facility information of the toilet. The analysis part analyzes the information acquired by the toilet information acquisition part. The providing unit provides the user with the information analyzed by the analysis unit.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 of making it difficult to quickly and accurately obtain information on the location and facilities of the most suitable toilets when out and about.

[0005] The system according to the embodiment aims to quickly and accurately provide information on the location and facilities of the most suitable toilets when you are out and about. [Means for solving the problem]

[0006] The system according to the embodiment includes a toilet information acquisition unit, an analysis unit, and a provision unit. The toilet information acquisition unit acquires information about toilet locations and facilities. The analysis unit analyzes the information acquired by the toilet information acquisition unit. The provision unit provides the information analyzed by the analysis unit to a user. [Effects of the Invention]

[0007] The system according to the embodiment can quickly and accurately provide information on the location and facilities of the most suitable toilets when you are out and about. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The toilet recommendation system according to an embodiment of the present invention is a system that suggests the best toilet for people through a smartphone app or website. This system uses generative AI to easily provide information on the location and facilities of nearby toilets in a chat format. This allows users to easily find the best toilet at any time.

[0029] A toilet recommendation system according to an embodiment includes a toilet information acquisition unit, an analysis unit, and a provision unit. The toilet information acquisition unit acquires information about toilet locations and facilities. For example, the toilet information acquisition unit identifies a user's current location using GPS data and acquires location information about nearby toilets. The toilet information acquisition unit can also acquire toilet facility information (such as the number of toilet seats, cleanliness, congestion forecast, and whether a diaper changing station is available). For example, the toilet information acquisition unit acquires facility information in real time from a toilet management system. The analysis unit analyzes the information acquired by the toilet information acquisition unit. For example, the analysis unit can analyze a user's prompts using a generation AI to suggest the optimal toilet. The analysis unit can also analyze a user's past toilet usage history and suggest a personalized toilet that is optimal for each individual user. For example, the analysis unit learns the characteristics of toilets that the user has used in the past and makes a next suggestion based on that information. The provision unit provides the user with the information analyzed by the analysis unit. For example, the provision unit can provide the user with toilet location and facility information in a chat format. The providing unit can also provide the toilet usage fee and payment method (free, paid, electronic money, etc.). For example, the providing unit displays details of the toilet usage fee and payment method. This allows the toilet suggestion system according to the embodiment to allow the user to easily find the best toilet at any time. For example, when the user inputs a prompt such as "Tell me about a clean toilet nearby," the generation AI analyzes the prompt and suggests the best toilet based on the user's current location and information about nearby toilets.

[0030] The analysis unit analyzes a user's past toilet usage history and can recommend personalized toilets that are optimal for each individual user. For example, the generation AI analyzes a user's past toilet usage history and learns the characteristics of frequently used toilets. For example, if a user prefers clean toilets, the analysis unit will prioritize clean toilets based on that information. The analysis unit also analyzes toilet usage patterns at specific times and locations based on the user's past toilet usage history. For example, if a user tends to use toilets in specific areas at specific times, the analysis unit will prioritize toilets in those areas. The analysis unit also analyzes a user's past toilet usage history and learns how frequently specific facilities (diaper changing stations, nursing rooms, etc.) are used. For example, if a user frequently uses diaper changing stations, the analysis unit will prioritize toilets with diaper changing stations based on that information. This allows the analysis unit to recommend toilets that meet the user's preferences.

[0031] The provision unit can simultaneously provide information on surrounding facilities in addition to information on toilet facilities. For example, the generation AI of the provision unit provides information on nearby cafes and restaurants in addition to information on toilet facilities. For example, it may suggest cafes where you can relax or restaurants where you can eat after using the toilet. When providing information on the location and facilities of the toilet, the provision unit also simultaneously provides information on nearby tourist spots and shopping areas. For example, it may suggest places where you can enjoy sightseeing or shopping after using the toilet. In addition to information on toilet facilities, the generation AI of the provision unit provides information on nearby public transportation. For example, it may provide information on the nearest bus stops and stations after using the toilet to support travel. This can support activities after using the toilet.

[0032] The provision unit can provide the toilet usage fee and payment method in addition to the toilet facility information. For example, the generation AI provides the toilet usage fee and payment method in addition to the toilet location and facility information. For example, it preferentially suggests free toilets and toilets that accept electronic money. When providing the toilet location and facility information, the provision unit also provides details of the usage fee and payment method at the same time. For example, it displays the fee and payment method (cash, credit card, electronic money, etc.) for paid toilets. The generation AI also provides the toilet location and facility information, along with the usage fee and payment method. For example, if the user wants to use electronic money, it preferentially suggests toilets that accept electronic money. This makes it possible to provide the toilet usage fee and payment method.

[0033] The providing unit can display information about toilet facilities on a visually easy-to-understand map or 3D model. For example, the generating AI in the providing unit displays the location of the toilet and facility information on a visually easy-to-understand map. For example, the location of the toilet is marked on a map and facility information is displayed in a pop-up. The providing unit also displays the location of the toilet and facility information in a 3D model to enable the user to intuitively understand. For example, the internal structure of the toilet and the layout of the facilities are displayed in a 3D model. The providing unit also displays the location of the toilet and facility information on a visually easy-to-understand map or 3D model by the generating AI. For example, the user can operate the map or 3D model to check detailed information about the toilet. This allows the user to intuitively understand the location of the toilet and facility information.

[0034] The toilet information acquisition unit acquires the cleaning status and cleaning schedule of the toilet in real time, and can preferentially suggest toilets that have just been cleaned. For example, the generation AI in the toilet information acquisition unit acquires the cleaning status and cleaning schedule of the toilet in real time, and preferentially suggests toilets that have just been cleaned. For example, it notifies the user of toilets that have just been cleaned. The toilet information acquisition unit also acquires the toilet cleaning schedule in real time, and preferentially suggests toilets that have just been cleaned. For example, it provides information about toilets that are scheduled to be cleaned and suggests using them after they are cleaned. The toilet information acquisition unit also acquires the cleaning status of the toilet in real time, and preferentially suggests toilets that have just been cleaned. For example, it evaluates the cleanliness of toilets that have been cleaned and suggests them to the user. This makes it possible to preferentially suggest clean toilets that have just been cleaned.

[0035] The toilet information acquisition unit can count the number of toilet users in real time and predict and provide the degree of congestion. In the toilet information acquisition unit, for example, a generation AI counts the number of toilet users in real time and predicts and provides the degree of congestion. For example, a sensor is used to measure the number of toilet users and display the degree of congestion. The toilet information acquisition unit also counts the number of toilet users in real time and predicts and provides the degree of congestion. For example, the congestion degree is predicted based on past usage data and provided to the user. In the toilet information acquisition unit, a generation AI counts the number of toilet users in real time and predicts and provides the degree of congestion. For example, the generation AI predicts time periods with a high number of toilet users and makes suggestions to avoid congestion. In this way, the degree of congestion of the toilet can be predicted and provided.

[0036] The toilet information acquisition unit can provide information on surrounding traffic conditions and weather in addition to real-time toilet information. For example, the generation AI of the toilet information acquisition unit provides information on surrounding traffic conditions in addition to real-time toilet information. For example, it displays information on the nearest bus stop or station to support the user's travel. The toilet information acquisition unit also provides weather information in addition to real-time toilet information. For example, if it is raining, it will preferentially suggest indoor toilets. The generation AI of the toilet information acquisition unit also provides information on surrounding traffic conditions and weather in addition to real-time toilet information. For example, if there is traffic congestion, it will suggest a route that avoids the congestion. This can support the user's travel.

[0037] The providing unit can provide real-time information about toilets through a voice assistant, enabling hands-free use. In the providing unit, for example, the generation AI provides the real-time information about toilets through the voice assistant. For example, when a user verbally commands, "Tell me where the nearest toilet is," the voice assistant reads out the toilet information. The providing unit also provides real-time information about toilets through the voice assistant, enabling hands-free use. For example, it allows a user who is driving to obtain toilet information by voice. The providing unit also allows the generation AI to provide real-time information about toilets through the voice assistant. For example, it allows a user to check the cleanliness and congestion status of a toilet by voice. This allows hands-free obtaining of toilet information.

[0038] The provision unit can learn the user's past dialogue history and provide more natural and personalized dialogue. For example, the provision unit uses a generation AI to learn the user's past dialogue history and provide more natural and personalized dialogue. For example, the provision unit makes a next suggestion based on the characteristics of toilets that the user has preferred to use in the past. The provision unit also uses a chatbot to learn the user's past dialogue history and provide dialogue that meets the user's preferences and needs. For example, if the user prefers clean toilets, the provision unit suggests clean toilets based on that information. The provision unit also uses a generation AI to learn the user's past dialogue history and provide personalized dialogue based on the user's usage patterns. For example, if the user tends to use the toilet at a specific time of day, the provision unit suggests the best toilet for that time of day. This makes it possible to provide the user with a natural and personalized dialogue.

[0039] The providing unit can provide reviews and ratings of related restrooms in real time in response to a user's question. For example, the generating AI in the providing unit provides reviews and ratings of related restrooms in real time in response to a user's question. For example, the latest reviews and ratings are displayed in response to a question such as "What is the rating of this restroom?" The providing unit also provides reviews and ratings of related restrooms in response to a user's question by a chatbot. For example, a question such as "Is this restroom clean?" is answered based on the ratings of other users. The providing unit also provides reviews and ratings of related restrooms in real time in response to a user's question by the generating AI. For example, the latest user feedback is displayed in response to a question such as "Is this restroom crowded?" This allows reviews and ratings to be provided in real time in response to a user's question.

[0040] The provision unit supports multiple languages ​​and can provide optimal toilet information to foreign users as well. For example, the generation AI in the provision unit supports multiple languages ​​and provides optimal toilet information to foreign users as well. For example, it provides information on toilet locations and facilities in languages ​​such as English, Chinese, and Spanish. The provision unit also supports multiple languages ​​through a chatbot, providing optimal toilet information to foreign users as well. For example, it prioritizes suggesting toilets that are easy for foreign tourists to use. The provision unit also supports multiple languages ​​through the generation AI, providing optimal toilet information to foreign users as well. For example, it answers questions in a foreign language in the appropriate language. This makes it possible to provide optimal toilet information to foreign users as well.

[0041] The providing unit can provide optimal route guidance based on the user's location information and support the user's journey to the restroom. In the providing unit, for example, the generation AI provides optimal route guidance based on the user's location information. For example, it displays directions from the current location to the nearest restroom. In addition, the providing unit provides optimal route guidance through a chatbot based on the user's location information. For example, if the user is walking, it suggests a route for pedestrians. In addition, the providing unit provides optimal route guidance through the generation AI based on the user's location information. For example, if using public transportation, it displays a route from the nearest bus stop or station. This makes it possible to provide optimal route guidance based on the user's location information.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The toilet recommendation system can further include a health monitoring unit that monitors the user's health condition and recommends an appropriate toilet. For example, it can measure the user's heart rate and blood pressure and recommend a toilet that suits their health condition. If the user's heart rate is high, it can recommend a toilet that is relaxing. The health monitoring unit can also record the user's number of steps and amount of exercise, and recommend toilets that are easy to use after exercise. Furthermore, the health monitoring unit can record the user's water intake and recommend toilets at appropriate times. This makes it possible to recommend toilets that suit the user's health condition.

[0044] The toilet suggestion system can further include a design suggestion unit that can suggest toilet designs that suit the user's preferences. For example, if the user prefers modern designs, a modern-design toilet can be suggested. If the user prefers classic designs, a classic-design toilet can be suggested. Furthermore, if the user prefers designs that evoke a sense of nature, a nature-themed toilet can be suggested. This makes it possible to suggest toilet designs that suit the user's preferences.

[0045] The toilet recommendation system can further include a transportation suggestion unit that can suggest toilets according to the user's transportation means. For example, if the user is traveling by car, toilets with parking facilities can be suggested. If the user is traveling by bicycle, toilets with bicycle parking spaces can be suggested. Furthermore, if the user is traveling on foot, toilets with pedestrian-friendly access can be suggested. This makes it possible to suggest toilets according to the user's transportation means.

[0046] The toilet recommendation system can further include a usage frequency analysis unit that analyzes the user's toilet usage frequency and can suggest toilets at appropriate times. For example, if the user tends to use the toilet at regular intervals, toilets can be suggested based on those times. Also, if the user tends to use the toilet after consuming a specific drink, toilets can be suggested after the user has consumed that drink. Furthermore, if the user tends to use the toilet after performing a specific activity, toilets can be suggested after that activity. This makes it possible to suggest toilets based on the user's toilet usage frequency.

[0047] The toilet recommendation system can further include a usage history analysis unit that can analyze the user's toilet usage history and learn the toilet usage patterns. For example, if a user tends to use a specific toilet at a specific time of day, it can suggest toilets that fit that time of day. Also, if a user tends to use the toilet in a specific location, it can suggest toilets close to that location. Furthermore, if a user tends to prefer using a specific facility, it can suggest toilets that have that facility. This makes it possible to suggest toilets based on the user's toilet usage patterns.

[0048] The processing flow of the first embodiment will be briefly explained below.

[0049] Step 1: The toilet information acquisition unit acquires information about the location and facilities of the toilets. For example, the toilet information acquisition unit identifies the user's current location using GPS data and acquires location information about nearby toilets. The toilet information acquisition unit can also acquire information about the facilities of the toilets (such as the number of toilet seats, cleanliness, predicted congestion, and the presence or absence of a diaper changing station). For example, the toilet information acquisition unit acquires facility information in real time from a toilet management system. Step 2: The analysis unit analyzes the information acquired by the toilet information acquisition unit. For example, the analysis unit uses a generation AI to analyze the user's prompts and suggest the most suitable toilet. The analysis unit can also analyze the user's past toilet usage history and suggest personalized toilets that are best suited to each individual user. For example, the analysis unit learns the characteristics of toilets that the user has used in the past and makes suggestions for the next time based on that information. Step 3: The providing unit provides the user with the information analyzed by the analyzing unit. For example, the providing unit provides the user with information about the location and facilities of the restroom in a chat format. The providing unit can also provide the restroom usage fee and payment method (free, paid, electronic money, etc.). For example, the providing unit displays details of the restroom usage fee and payment method.

[0050] (Example 2) The toilet recommendation system according to an embodiment of the present invention is a system that suggests the best toilet for people through a smartphone app or website. This system uses generative AI to easily provide information on the location and facilities of nearby toilets in a chat format. This allows users to easily find the best toilet at any time.

[0051] A toilet recommendation system according to an embodiment includes a toilet information acquisition unit, an analysis unit, and a provision unit. The toilet information acquisition unit acquires information about toilet locations and facilities. For example, the toilet information acquisition unit identifies a user's current location using GPS data and acquires location information about nearby toilets. The toilet information acquisition unit can also acquire toilet facility information (such as the number of toilet seats, cleanliness, congestion forecast, and whether a diaper changing station is available). For example, the toilet information acquisition unit acquires facility information in real time from a toilet management system. The analysis unit analyzes the information acquired by the toilet information acquisition unit. For example, the analysis unit can analyze a user's prompts using a generation AI to suggest the optimal toilet. The analysis unit can also analyze a user's past toilet usage history and suggest a personalized toilet that is optimal for each individual user. For example, the analysis unit learns the characteristics of toilets that the user has used in the past and makes a next suggestion based on that information. The provision unit provides the user with the information analyzed by the analysis unit. For example, the provision unit can provide the user with toilet location and facility information in a chat format. The providing unit can also provide the toilet usage fee and payment method (free, paid, electronic money, etc.). For example, the providing unit displays details of the toilet usage fee and payment method. This allows the toilet suggestion system according to the embodiment to allow the user to easily find the best toilet at any time. For example, when the user inputs a prompt such as "Tell me about a clean toilet nearby," the generation AI analyzes the prompt and suggests the best toilet based on the user's current location and information about nearby toilets.

[0052] The analysis unit analyzes a user's past toilet usage history and can recommend personalized toilets that are optimal for each individual user. For example, the generation AI analyzes a user's past toilet usage history and learns the characteristics of frequently used toilets. For example, if a user prefers clean toilets, the analysis unit will prioritize clean toilets based on that information. The analysis unit also analyzes toilet usage patterns at specific times and locations based on the user's past toilet usage history. For example, if a user tends to use toilets in specific areas at specific times, the analysis unit will prioritize toilets in those areas. The analysis unit also analyzes a user's past toilet usage history and learns how frequently specific facilities (diaper changing stations, nursing rooms, etc.) are used. For example, if a user frequently uses diaper changing stations, the analysis unit will prioritize toilets with diaper changing stations based on that information. This allows the analysis unit to recommend toilets that meet the user's preferences.

[0053] The provision unit can simultaneously provide information on surrounding facilities in addition to information on toilet facilities. For example, the generation AI of the provision unit provides information on nearby cafes and restaurants in addition to information on toilet facilities. For example, it may suggest cafes where you can relax or restaurants where you can eat after using the toilet. When providing information on the location and facilities of the toilet, the provision unit also simultaneously provides information on nearby tourist spots and shopping areas. For example, it may suggest places where you can enjoy sightseeing or shopping after using the toilet. In addition to information on toilet facilities, the generation AI of the provision unit provides information on nearby public transportation. For example, it may provide information on the nearest bus stops and stations after using the toilet to support travel. This can support activities after using the toilet.

[0054] The analysis unit can analyze the user's current emotional state and suggest a relaxing restroom environment. For example, the generation AI in the analysis unit analyzes the user's current emotional state and suggests a relaxing restroom environment. For example, if the user is feeling stressed, a quiet and clean restroom is suggested. The analysis unit also uses an emotion estimation function to suggest a restroom environment in which the user can relax. For example, if the user is tired, a spacious restroom or a restroom that plays relaxing music is suggested. The analysis unit also uses the generation AI in the analysis unit to analyze the user's emotional state and suggest a relaxing restroom environment. For example, if the user is tense, a restroom with an aroma diffuser is suggested. This makes it possible to suggest a restroom environment that suits the user's emotional state.

[0055] The provision unit can provide the toilet usage fee and payment method in addition to the toilet facility information. For example, the generation AI provides the toilet usage fee and payment method in addition to the toilet location and facility information. For example, it preferentially suggests free toilets and toilets that accept electronic money. When providing the toilet location and facility information, the provision unit also provides details of the usage fee and payment method at the same time. For example, it displays the fee and payment method (cash, credit card, electronic money, etc.) for paid toilets. The generation AI also provides the toilet location and facility information, along with the usage fee and payment method. For example, if the user wants to use electronic money, it preferentially suggests toilets that accept electronic money. This makes it possible to provide the toilet usage fee and payment method.

[0056] The providing unit can display information about toilet facilities on a visually easy-to-understand map or 3D model. For example, the generating AI in the providing unit displays the location of the toilet and facility information on a visually easy-to-understand map. For example, the location of the toilet is marked on a map and facility information is displayed in a pop-up. The providing unit also displays the location of the toilet and facility information in a 3D model to enable the user to intuitively understand. For example, the internal structure of the toilet and the layout of the facilities are displayed in a 3D model. The providing unit also displays the location of the toilet and facility information on a visually easy-to-understand map or 3D model by the generating AI. For example, the user can operate the map or 3D model to check detailed information about the toilet. This allows the user to intuitively understand the location of the toilet and facility information.

[0057] The analysis unit can analyze the user's emotional state and provide advice to reduce anxiety and stress when using the restroom. For example, the generation AI analyzes the user's emotional state and provides advice to reduce anxiety and stress when using the restroom. For example, it suggests breathing techniques or stretching methods to help the user relax. The analysis unit also uses the emotion estimation function to provide advice to help the user reduce anxiety and stress when using the restroom. For example, it suggests listening to relaxing music before using the restroom. The analysis unit also uses the generation AI to analyze the user's emotional state and provides advice to reduce anxiety and stress when using the restroom. For example, it suggests taking a deep breath before using the restroom. This can reduce the user's anxiety and stress.

[0058] The toilet information acquisition unit acquires the cleaning status and cleaning schedule of the toilet in real time, and can preferentially suggest toilets that have just been cleaned. For example, the generation AI in the toilet information acquisition unit acquires the cleaning status and cleaning schedule of the toilet in real time, and preferentially suggests toilets that have just been cleaned. For example, it notifies the user of toilets that have just been cleaned. The toilet information acquisition unit also acquires the toilet cleaning schedule in real time, and preferentially suggests toilets that have just been cleaned. For example, it provides information about toilets that are scheduled to be cleaned and suggests using them after they are cleaned. The toilet information acquisition unit also acquires the cleaning status of the toilet in real time, and preferentially suggests toilets that have just been cleaned. For example, it evaluates the cleanliness of toilets that have been cleaned and suggests them to the user. This makes it possible to preferentially suggest clean toilets that have just been cleaned.

[0059] The toilet information acquisition unit can count the number of toilet users in real time and predict and provide the degree of congestion. In the toilet information acquisition unit, for example, a generation AI counts the number of toilet users in real time and predicts and provides the degree of congestion. For example, a sensor is used to measure the number of toilet users and display the degree of congestion. The toilet information acquisition unit also counts the number of toilet users in real time and predicts and provides the degree of congestion. For example, the congestion degree is predicted based on past usage data and provided to the user. In the toilet information acquisition unit, a generation AI counts the number of toilet users in real time and predicts and provides the degree of congestion. For example, the generation AI predicts time periods with a high number of toilet users and makes suggestions to avoid congestion. In this way, the degree of congestion of the toilet can be predicted and provided.

[0060] The analysis unit can analyze the user's emotional state and provide information about the congestion level of the restroom according to the emotional state. For example, the generation AI in the analysis unit analyzes the user's emotional state and provides information about the congestion level of the restroom according to the emotional state. For example, if the user is feeling stressed, it preferentially suggests restrooms that are not crowded. The analysis unit also uses an emotion estimation function to provide information about the congestion level of the restroom according to the user's emotional state. For example, if the user wants to relax, it suggests an empty restroom. The analysis unit also uses the generation AI in the analysis unit analyzes the user's emotional state and provides information about the congestion level of the restroom according to the emotional state. For example, if the user is in a hurry, it suggests a restroom that is not crowded. This makes it possible to provide information about the congestion level of the restroom according to the user's emotional state.

[0061] The toilet information acquisition unit can provide information on surrounding traffic conditions and weather in addition to real-time toilet information. For example, the generation AI of the toilet information acquisition unit provides information on surrounding traffic conditions in addition to real-time toilet information. For example, it displays information on the nearest bus stop or station to support the user's travel. The toilet information acquisition unit also provides weather information in addition to real-time toilet information. For example, if it is raining, it will preferentially suggest indoor toilets. The generation AI of the toilet information acquisition unit also provides information on surrounding traffic conditions and weather in addition to real-time toilet information. For example, if there is traffic congestion, it will suggest a route that avoids the congestion. This can support the user's travel.

[0062] The providing unit can provide real-time information about toilets through a voice assistant, enabling hands-free use. In the providing unit, for example, the generation AI provides the real-time information about toilets through the voice assistant. For example, when a user verbally commands, "Tell me where the nearest toilet is," the voice assistant reads out the toilet information. The providing unit also provides real-time information about toilets through the voice assistant, enabling hands-free use. For example, it allows a user who is driving to obtain toilet information by voice. The providing unit also allows the generation AI to provide real-time information about toilets through the voice assistant. For example, it allows a user to check the cleanliness and congestion status of a toilet by voice. This allows hands-free obtaining of toilet information.

[0063] The analysis unit can analyze the user's emotional state and provide real-time information to increase the sense of security. For example, the generation AI analyzes the user's emotional state and provides real-time information to increase the sense of security. For example, it prioritizes suggesting clean restrooms and restrooms that are vacant. The analysis unit also uses an emotion estimation function to provide real-time information to increase the sense of security when the user uses the restroom. For example, it displays the number of restroom users and the cleaning status in real time. The analysis unit also uses the generation AI to analyze the user's emotional state and provides real-time information to increase the sense of security. For example, it provides information about the restroom's facilities and surrounding safety information. This makes it possible to provide information to increase the user's sense of security.

[0064] The provision unit can learn the user's past dialogue history and provide more natural and personalized dialogue. For example, the provision unit uses a generation AI to learn the user's past dialogue history and provide more natural and personalized dialogue. For example, the provision unit makes a next suggestion based on the characteristics of toilets that the user has preferred to use in the past. The provision unit also uses a chatbot to learn the user's past dialogue history and provide dialogue that meets the user's preferences and needs. For example, if the user prefers clean toilets, the provision unit suggests clean toilets based on that information. The provision unit also uses a generation AI to learn the user's past dialogue history and provide personalized dialogue based on the user's usage patterns. For example, if the user tends to use the toilet at a specific time of day, the provision unit suggests the best toilet for that time of day. This makes it possible to provide the user with a natural and personalized dialogue.

[0065] The providing unit can provide reviews and ratings of related restrooms in real time in response to a user's question. For example, the generating AI in the providing unit provides reviews and ratings of related restrooms in real time in response to a user's question. For example, the latest reviews and ratings are displayed in response to a question such as "What is the rating of this restroom?" The providing unit also provides reviews and ratings of related restrooms in response to a user's question by a chatbot. For example, a question such as "Is this restroom clean?" is answered based on the ratings of other users. The providing unit also provides reviews and ratings of related restrooms in real time in response to a user's question by the generating AI. For example, the latest user feedback is displayed in response to a question such as "Is this restroom crowded?" This allows reviews and ratings to be provided in real time in response to a user's question.

[0066] The analysis unit can analyze the user's emotional state, select a dialogue style according to that emotional state, and provide a relaxing dialogue. For example, the generation AI in the analysis unit analyzes the user's emotional state and selects a dialogue style according to that emotional state. For example, if the user is feeling stressed, the dialogue will be conducted in a gentle, relaxing tone. The analysis unit also uses an emotion estimation function to select a dialogue style according to the user's emotional state. For example, if the user is tense, the generation AI will provide relaxing advice or words of encouragement. The analysis unit can also analyze the user's emotional state and provide a relaxing dialogue. For example, if the user is tired, the generation AI will suggest relaxing music or ways to refresh themselves. This makes it possible to provide a relaxing dialogue according to the user's emotional state.

[0067] The provision unit supports multiple languages ​​and can provide optimal toilet information to foreign users as well. For example, the generation AI in the provision unit supports multiple languages ​​and provides optimal toilet information to foreign users as well. For example, it provides information on toilet locations and facilities in languages ​​such as English, Chinese, and Spanish. The provision unit also supports multiple languages ​​through a chatbot, providing optimal toilet information to foreign users as well. For example, it prioritizes suggesting toilets that are easy for foreign tourists to use. The provision unit also supports multiple languages ​​through the generation AI, providing optimal toilet information to foreign users as well. For example, it answers questions in a foreign language in the appropriate language. This makes it possible to provide optimal toilet information to foreign users as well.

[0068] The providing unit can provide optimal route guidance based on the user's location information and support the user's journey to the restroom. In the providing unit, for example, the generation AI provides optimal route guidance based on the user's location information. For example, it displays directions from the current location to the nearest restroom. In addition, the providing unit provides optimal route guidance through a chatbot based on the user's location information. For example, if the user is walking, it suggests a route for pedestrians. In addition, the providing unit provides optimal route guidance through the generation AI based on the user's location information. For example, if using public transportation, it displays a route from the nearest bus stop or station. This makes it possible to provide optimal route guidance based on the user's location information.

[0069] The analysis unit can analyze the user's emotional state and provide a dialogue to reduce anxiety when using the restroom. For example, the generation AI in the analysis unit analyzes the user's emotional state and provides a dialogue to reduce anxiety when using the restroom. For example, if the user is feeling anxious, it provides reassuring information. The analysis unit also uses an emotion estimation function to provide a dialogue to reduce anxiety when using the restroom. For example, if the user is feeling nervous, it provides advice to help them relax. The analysis unit also uses the generation AI in the analysis unit analyzes the user's emotional state and provides a dialogue to reduce anxiety when using the restroom. For example, if the user is feeling anxious, it provides information about the cleanliness and safety of the restroom. This makes it possible to provide a dialogue to reduce the user's anxiety.

[0070] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0071] The toilet recommendation system can further include a health monitoring unit that monitors the user's health condition and recommends an appropriate toilet. For example, it can measure the user's heart rate and blood pressure and recommend a toilet that suits their health condition. If the user's heart rate is high, it can recommend a toilet that is relaxing. The health monitoring unit can also record the user's number of steps and amount of exercise, and recommend toilets that are easy to use after exercise. Furthermore, the health monitoring unit can record the user's water intake and recommend toilets at appropriate times. This makes it possible to recommend toilets that suit the user's health condition.

[0072] The toilet recommendation system can also analyze the user's emotional state and suggest toilet scents that correspond to the user's emotional state. For example, if the user is feeling stressed, a toilet with a relaxing lavender scent can be suggested. If the user is tired, a toilet with a refreshing mint scent can be suggested. Furthermore, if the user is nervous, a toilet with a chamomile scent can be suggested. This makes it possible to suggest toilet scents that correspond to the user's emotional state.

[0073] The toilet suggestion system can further include a design suggestion unit that can suggest toilet designs that suit the user's preferences. For example, if the user prefers modern designs, a modern-design toilet can be suggested. If the user prefers classic designs, a classic-design toilet can be suggested. Furthermore, if the user prefers designs that evoke a sense of nature, a nature-themed toilet can be suggested. This makes it possible to suggest toilet designs that suit the user's preferences.

[0074] The toilet recommendation system can further analyze the user's emotional state and suggest toilet lighting that matches the user's emotional state. For example, if the user wants to relax, a toilet with soft, warm lighting can be suggested. If the user wants to concentrate, a toilet with bright white lighting can be suggested. Furthermore, if the user wants to refresh, a toilet with lighting similar to natural light can be suggested. This makes it possible to suggest toilet lighting that matches the user's emotional state.

[0075] The toilet recommendation system can further include a transportation suggestion unit that can suggest toilets according to the user's transportation means. For example, if the user is traveling by car, toilets with parking facilities can be suggested. If the user is traveling by bicycle, toilets with bicycle parking spaces can be suggested. Furthermore, if the user is traveling on foot, toilets with pedestrian-friendly access can be suggested. This makes it possible to suggest toilets according to the user's transportation means.

[0076] The toilet suggestion system can further analyze the user's emotional state and suggest toilet music that matches the user's emotional state. For example, if the user wants to relax, a toilet that plays classical music can be suggested. If the user wants to cheer up, a toilet that plays pop music can be suggested. Furthermore, if the user wants to concentrate, a toilet that plays ambient sounds can be suggested. This makes it possible to suggest toilet music that matches the user's emotional state.

[0077] The toilet recommendation system can further include a usage frequency analysis unit that analyzes the user's toilet usage frequency and can suggest toilets at appropriate times. For example, if the user tends to use the toilet at regular intervals, toilets can be suggested based on those times. Also, if the user tends to use the toilet after consuming a specific drink, toilets can be suggested after the user has consumed that drink. Furthermore, if the user tends to use the toilet after performing a specific activity, toilets can be suggested after that activity. This makes it possible to suggest toilets based on the user's toilet usage frequency.

[0078] The toilet recommendation system can further analyze the user's emotional state and suggest a toilet temperature that matches the emotional state. For example, if the user wants to relax, a toilet with a moderate temperature can be suggested. If the user feels cold, a warm toilet can be suggested. If the user feels hot, a cool toilet can be suggested. This makes it possible to suggest a toilet temperature that matches the user's emotional state.

[0079] The toilet recommendation system can further include a usage history analysis unit that can analyze the user's toilet usage history and learn the toilet usage patterns. For example, if a user tends to use a specific toilet at a specific time of day, it can suggest toilets that fit that time of day. Also, if a user tends to use the toilet in a specific location, it can suggest toilets close to that location. Furthermore, if a user tends to prefer using a specific facility, it can suggest toilets that have that facility. This makes it possible to suggest toilets based on the user's toilet usage patterns.

[0080] The restroom suggestion system can further analyze the user's emotional state and provide information about the degree of congestion of restrooms according to the user's emotional state. For example, if the user is feeling stressed, it can preferentially suggest uncrowded restrooms. If the user wants to relax, it can suggest vacant restrooms. Furthermore, if the user is in a hurry, it can suggest uncrowded restrooms. This makes it possible to provide information about the degree of congestion of restrooms according to the user's emotional state.

[0081] The processing flow of the second embodiment will be briefly explained below.

[0082] Step 1: The toilet information acquisition unit acquires information about the location and facilities of the toilets. For example, the toilet information acquisition unit identifies the user's current location using GPS data and acquires location information about nearby toilets. The toilet information acquisition unit can also acquire information about the facilities of the toilets (such as the number of toilet seats, cleanliness, predicted congestion, and the presence or absence of a diaper changing station). For example, the toilet information acquisition unit acquires facility information in real time from a toilet management system. Step 2: The analysis unit analyzes the information acquired by the toilet information acquisition unit. For example, the analysis unit uses a generation AI to analyze the user's prompts and suggest the most suitable toilet. The analysis unit can also analyze the user's past toilet usage history and suggest personalized toilets that are best suited to each individual user. For example, the analysis unit learns the characteristics of toilets that the user has used in the past and makes suggestions for the next time based on that information. Step 3: The providing unit provides the user with the information analyzed by the analyzing unit. For example, the providing unit provides the user with information about the location and facilities of the restroom in a chat format. The providing unit can also provide the restroom usage fee and payment method (free, paid, electronic money, etc.). For example, the providing unit displays details of the restroom usage fee and payment method.

[0083] 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.

[0084] 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.

[0085] 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.

[0086] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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).

[0092] 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.

[0093] 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.

[0094] 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.

[0095] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0096] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0102] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0103] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0104] The 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.

[0105] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0106] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0107] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0108] Fig. 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.

[0109] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0110] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0111] In the headset type terminal 314, 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 headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0112] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0113] The specific processing unit 290 transmits the result of the specific processing to the 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.

[0114] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0115] The data processing system 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.

[0116] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0117] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0118] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0119] The 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.

[0120] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0121] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS 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).

[0122] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0123] 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.

[0124] 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.

[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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0127] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[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 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.

[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 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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).

[0136] 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.

[0137] 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."

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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]

[0150] 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 toilet information acquisition unit that acquires information about toilet locations and facilities; an analysis unit that analyzes the information acquired by the toilet information acquisition unit; a providing unit that provides the information analyzed by the analyzing unit to a user. A system characterized by:

2. The analysis unit Analyze the user's past toilet usage history and personalize and suggest the best toilet for each individual user.

2. The system of claim 1.

3. The providing unit In addition to the toilet facility information, information on surrounding facilities is also provided at the same time.

2. The system of claim 1.

4. The analysis unit Analyze the user's current emotional state and propose a relaxing toilet environment 2. The system of claim 1.

5. The providing unit In addition to the toilet facility information, the service also provides toilet usage fees and payment methods.

2. The system of claim 1.

6. The providing unit Displaying the toilet facility information in a visually easy-to-understand map or 3D model 2. The system of claim 1.

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