system

Abstract

The system according to this embodiment aims to provide a centralized source of information necessary when going out with children. [Solution] The system according to the embodiment comprises an information provision unit, a route search unit, a route proposal unit, and a route optimization unit. The information provision unit provides information according to the desired destination. The route search unit searches for a route from the user's current location to the destination. The route proposal unit proposes a route that takes into account the elevator's location based on the route search unit. The route optimization unit provides the optimal route based on the route proposed by the route proposal unit.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, there is no system that provides necessary information in a unified manner when going out with children, and there is a problem that prior preparation is very difficult.

[0005] The system according to the embodiment aims to provide necessary information in a unified manner when going out with children.

Means for Solving the Problems

[0006] The system according to this embodiment comprises an information provision unit, a route search unit, a route proposal unit, and a route optimization unit. The information provision unit provides information according to the desired destination. The route search unit searches for a route from the user's current location to the destination. The route proposal unit proposes a route that takes into account the location of elevators based on the route search unit. The route optimization unit provides the optimal route based on the route proposed by the route proposal unit. [Effects of the Invention]

[0007] The system according to this embodiment can provide all the necessary information when going out with children in a centralized manner. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

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

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

[0017] As shown in FIG. 1, the 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, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0024] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The outing support system according to an embodiment of the present invention is a system designed to simplify the preparations parents make when going out with children. This outing support system provides the following information depending on the destination. First, it tells the user the location of restrooms. For example, it can tell the user the location of restrooms in advance at places they will go with their children, such as shopping malls and parks. Next, it tells the user the location of places where they can prepare formula milk. For example, it can tell the user the location of places with facilities for preparing formula milk, such as cafes and restaurants. Furthermore, it tells the user the location of places where they can change clothes. For example, it can tell the user the location of places where they can change their child's clothes, such as baby changing rooms and dressing rooms. It also tells the user the location of restaurants that are easy to go to with children. For example, it can tell the user the location of restaurants with children's menus or restaurants that have high chairs available. Furthermore, it tells the user the location of routes that are easy to navigate even with a large stroller. For example, it can tell the user the location of routes that are easy to navigate with a stroller, such as routes with few steps or routes with wide sidewalks. It also tells the user the location of elevators. For example, it can tell the user the location of elevators in places such as train stations and shopping malls. Using this outing support system makes going out with children much easier. Parents can obtain necessary information in advance, allowing them to go out with peace of mind. For example, when going to a shopping mall, knowing the location of restrooms, places to prepare milk, and elevators beforehand allows for a smoother outing. Also, knowing in advance about child-friendly restaurants and routes that are easy to navigate with a stroller allows for a stress-free outing. This outing support system targets families with young children, such as infants and elementary school children. It solves problems such as limited places to go when wanting to go out, the difficulty of prior research, and the fact that they have never been able to arrive on time due to detours using elevators. By alleviating parental anxiety and suggesting child-friendly places and routes, it allows parents to go out with peace of mind. In this way, the outing support system provides parents with information to make outings with children smoother and more worry-free.

[0029] The outing support system according to this embodiment comprises an information provision unit, a route search unit, a route suggestion unit, and a route optimization unit. The information provision unit provides information according to the destination. For example, the information provision unit provides information such as the location of toilets, places where milk can be prepared, places where clothes can be changed, restaurants that are easy to go to with children, routes that are easy to navigate even with a large stroller, and the location of elevators. For example, the information provision unit displays the locations of toilets in shopping malls and parks on a map. The information provision unit can also provide text information about places where milk can be prepared, such as cafes and restaurants. Furthermore, the information provision unit can also display places where clothes can be changed, such as baby rest rooms and changing rooms, on a map. For example, the information provision unit lists restaurants with children's menus and restaurants that have baby chairs and provides this information to the user. The information provision unit can also display routes on a map that have few steps or wide sidewalks. Furthermore, the information provision unit can also display the locations of elevators in stations and shopping malls on a map. The route search unit searches for a route from the user's current location to their destination. The route search unit searches for a route based on the departure and destination points entered by the user. For example, the route search unit allows users to input the departure and destination points by methods such as entering an address or specifying a pin on a map. The route search unit searches for the optimal route based on the entered information. The route suggestion unit proposes a route that takes elevator locations into account, based on the route search unit's search results. For example, the route suggestion unit proposes a route that makes travel with a stroller easier by taking elevator locations into account. For example, the route suggestion unit displays elevator locations on a map and proposes a route that takes these locations into account. The route optimization unit provides the optimal route based on the route suggested by the route suggestion unit. For example, the route optimization unit provides the optimal route based on user input, according to criteria such as time reduction, distance reduction, and consideration of traffic conditions. For example, the route optimization unit provides the optimal route by taking real-time traffic information into account.As a result, the outing support system according to this embodiment provides information that allows parents to go out with their children smoothly, enabling them to go out with peace of mind.

[0030] The information service provides information tailored to the user's desired destination. For example, it can provide information such as the locations of restrooms, places to prepare formula, changing facilities, child-friendly restaurants, routes easily accessible with large strollers, and elevator locations. Specifically, the service displays the locations of restrooms in shopping malls and parks on a map, allowing users to quickly find the nearest restroom. It can also provide text information about places to prepare formula, such as cafes and restaurants. For instance, it might indicate whether a particular cafe offers hot water or has a dedicated space for preparing formula. Furthermore, the service can display changing facilities, such as baby changing rooms and restrooms, on a map, enabling users to quickly find the nearest facility even in urgent situations. For example, the service can list restaurants with children's menus or high chairs, making dining out with children more comfortable. Finally, the service can display routes with minimal steps and wide sidewalks on a map. This allows users to choose routes that allow for smooth movement even with large strollers. Furthermore, the information service can display the locations of elevators in places like train stations and shopping malls on the map. This allows users to avoid stairs and escalators. The information service centrally manages this information, enabling users to quickly obtain the information they need. For example, when a user searches for a specific facility or location, relevant information will be automatically displayed. The information service can also provide individually customized information based on the user's past search and usage history. This allows users to receive more personalized information, improving convenience when going out.

[0031] The route search unit searches for a route from the user's current location to their destination. For example, it searches for a route based on the user's entered starting point and destination. Specifically, the route search unit allows users to input the starting point and destination using methods such as address input or pin selection on a map. Once the user enters the starting point and destination, the route search unit accesses map databases and traffic information databases to find the optimal route. This allows the user to obtain a route that takes into account real-time traffic conditions and road congestion. For example, the route search unit calculates the fastest route to the destination based on current traffic conditions. The route search unit can also provide routes that consider specific conditions according to the user's preferences. For example, if the user is using a stroller, it can prioritize routes with fewer steps or routes with elevators. Furthermore, the route search unit can handle cases where the user sets multiple destinations. For example, if the user wants to stop by a park before going to a shopping mall, the route search unit provides the optimal route to visit these destinations in order. This allows the user to travel efficiently. The route search unit displays the search results on a map, allowing the user to visually confirm the route. Furthermore, the route search unit provides voice and text guidance, making it easier for users to check their route while traveling. In this way, the route search unit helps users reach their destination smoothly.

[0032] The route suggestion unit proposes routes that take elevator locations into consideration, based on the routes found by the route search unit. Specifically, the route suggestion unit proposes routes that are easy to navigate with a stroller, taking elevator locations into account. For example, the route suggestion unit displays elevator locations on the map and proposes routes that take these locations into consideration. This allows users to avoid stairs and escalators. In addition to elevator locations, the route suggestion unit also considers routes with fewer steps and wider sidewalks. This makes travel more comfortable for users with strollers or wheelchairs. Furthermore, the route suggestion unit can also propose individually customized routes based on the user's past travel history and preferences. For example, it proposes the optimal route considering routes the user has used in the past and places they like to visit. This allows users to enjoy a more personalized travel experience. The route suggestion unit displays the proposed route on the map, allowing users to visually confirm the route. The route suggestion unit also provides voice and text guidance to make it easier for users to check the route while traveling. In this way, the route suggestion unit helps users reach their destination smoothly. Furthermore, the route suggestion system can continuously update suggested routes by taking real-time traffic and weather information into account. This ensures that users always have access to the optimal route based on the latest information.

[0033] The route optimization unit provides the optimal route based on the route proposed by the route suggestion unit. Specifically, the route optimization unit provides the optimal route based on information entered by the user, according to criteria such as time reduction, distance reduction, and consideration of traffic conditions. For example, the route optimization unit provides the optimal route considering real-time traffic information. This allows the user to avoid congestion and travel smoothly. The route optimization unit also considers not only traffic information but also weather information and road construction information. This allows the user to travel while avoiding unexpected delays and obstacles. Furthermore, the route optimization unit can also provide individually customized routes based on the user's travel history and preferences. For example, it provides the optimal route considering routes the user has used in the past and places they like to visit. This allows the user to enjoy a more personalized travel experience. The route optimization unit displays the proposed route on a map, allowing the user to visually confirm the route. In addition, the route optimization unit provides voice guidance and text guidance to make it easier for the user to check the route while traveling. In this way, the route optimization unit helps the user reach their destination smoothly. Furthermore, the route optimization unit can continuously update the proposed route by taking real-time traffic and weather information into account. This ensures that users can always utilize the optimal route based on the latest information.

[0034] The information service can provide information such as the locations of restrooms, places where milk can be prepared, places where clothes can be changed, restaurants that are easy to visit with children, routes that are easy to navigate with large strollers, and elevator locations. For example, the information service can display the locations of restrooms on a map. For example, it can display the locations of restrooms in shopping malls and parks on a map. The information service can also provide text information about places where milk can be prepared, such as cafes and restaurants. For example, it can provide text information about the opening hours and availability of facilities for cafes and restaurants. Furthermore, the information service can display places where clothes can be changed, such as baby rest rooms and changing rooms, on a map. For example, it can display information about the privacy and facilities of baby rest rooms and changing rooms on a map. In addition, the information service can list and provide users with restaurants that have children's menus or restaurants that have baby chairs. For example, it can list and provide information about restaurants that have children's menus or the availability of baby chairs. Furthermore, the information service can display routes on a map that have few steps or wide sidewalks. For example, the information provision unit displays the presence or absence of steps and road width on a map. The information provision unit can also display the locations of elevators in places like train stations and shopping malls on a map. For instance, the information provision unit displays elevator locations on a map and provides this information to the user. This allows the user to obtain necessary information in advance, enabling them to go out with peace of mind. Some or all of the above-described processing in the information provision unit may be performed using AI, or not. For example, the information provision unit can input information about the locations of toilets or places where milk can be prepared into the AI, which can then provide the most appropriate information.

[0035] The route search unit can search for a route based on the departure point and destination entered by the user. For example, the route search unit can input the departure point and destination by methods such as entering an address or specifying a pin on a map. The route search unit searches for the optimal route based on the entered information. For example, the route search unit searches for the optimal route based on the departure point and destination entered by the user. The route search unit can also suggest the optimal route based on the departure point and destination information entered by the user. This allows the user to find the optimal route simply by entering the departure point and destination. Some or all of the above processing in the route search unit may be performed using AI, for example, or without AI. For example, the route search unit can input the departure point and destination information entered by the user into the AI, and the AI ​​can search for the optimal route.

[0036] The route suggestion unit can propose a route that takes the location of the elevator into consideration. For example, the route suggestion unit can propose a route that makes it easier to travel with a stroller by taking the location of the elevator into consideration. For example, the route suggestion unit can display the location of the elevator on a map and propose a route that takes that location into consideration. In this way, by proposing a route that takes the location of the elevator into consideration, it makes it easier to travel with a stroller. Some or all of the above processing in the route suggestion unit may be performed using AI, for example, or not using AI. For example, the route suggestion unit can input the location of the elevator into the AI, and the AI ​​can propose the optimal route.

[0037] The route optimization unit can provide the optimal route based on the information entered by the user. For example, the route optimization unit provides the optimal route based on the information entered by the user, according to criteria such as time reduction, distance reduction, and consideration of traffic conditions. For example, the route optimization unit provides the optimal route by considering real-time traffic information. This enables efficient travel by providing the optimal route based on the information entered by the user. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input the information entered by the user into the AI, and the AI ​​can provide the optimal route.

[0038] The review sharing section allows users to share reviews and ratings of places they have visited. For example, the review sharing section can share reviews and ratings of places visited by users. For example, the review sharing section can share reviews and ratings in methods such as star ratings and comments. The review sharing section provides reviews and ratings of places visited by users so that other users can refer to them. For example, the review sharing section displays reviews of places visited by users using star ratings, allowing other users to refer to those ratings. The review sharing section also displays detailed comments about places visited by users, allowing other users to refer to those comments. This allows other users to refer to reviews and ratings of places visited by users by sharing them. Some or all of the above processing in the review sharing section may be performed using AI, or not. For example, the review sharing section can input user-entered reviews and ratings into AI, which can then provide optimal reviews and ratings.

[0039] The information storage unit can store information about places the user has visited. For example, the information storage unit can store information in the form of text information or photographs. The information storage unit stores information about places the user has visited so that it can be used to help with future outings. For example, the information storage unit can store text information about places the user has visited so that it can be referenced on future outings. The information storage unit can also store photographs of places the user has visited so that it can be referenced on future outings. In this way, by saving information about places the user has visited, it can be used to help with future outings. Some or all of the above processing in the information storage unit may be performed using AI, for example, or without AI. For example, the information storage unit can input information entered by the user into the AI, and the AI ​​can store the most appropriate information.

[0040] The Outing Suggestion Department uses AI to suggest destinations for your next outing. For example, the Outing Suggestion Department can analyze the user's past behavior history and preferences to suggest destinations for their next outing. The Outing Suggestion Department helps users discover new places. For example, it can suggest related new places based on information about places the user has visited in the past. It can also suggest new destinations based on the user's preferences and interests. In this way, the AI ​​suggests destinations for the next outing, allowing users to discover new places. Some or all of the above processes in the Outing Suggestion Department are performed using generative AI. For example, the Outing Suggestion Department inputs the user's past behavior history and preferences into the generative AI, which can then suggest the most suitable destination.

[0041] The information provision unit can analyze a user's past search history and provide customized, optimal information. For example, the information provision unit can prioritize displaying restroom locations that the user has frequently searched for in the past. The information provision unit can also suggest similar restaurants based on reviews of restaurants the user has visited in the past. For example, the information provision unit can suggest relevant restaurants based on reviews of restaurants the user has visited in the past. The information provision unit can also suggest the optimal route based on the location of elevators the user has used in the past. For example, the information provision unit can suggest the optimal route based on the location of elevators the user has used in the past. By analyzing the user's past search history, more relevant information can be provided. Some or all of the above processing in the information provision unit may be performed using AI, for example, or not. For example, the information provision unit can input the user's past search history into AI, which can then customize and provide optimal information.

[0042] The information provision unit can filter the information it provides based on the user's child's age and characteristics. For example, the information provision unit can prioritize providing information on places to prepare formula and change diapers to parents with infants. The information provision unit can also suggest playgrounds and restaurants with children's menus to parents with toddlers. The information provision unit can also suggest learning facilities and experiential facilities to parents with elementary school children. The information provision unit can prioritize displaying learning facilities and experiential facilities to parents with elementary school children. By providing information based on the user's child's age and characteristics, more appropriate information can be provided. Some or all of the above processing in the information provision unit may be performed using AI, for example, or not. For example, the information provision unit can input information on the user's child's age and characteristics into the AI, which can then filter and provide the most suitable information.

[0043] The information provision unit can prioritize displaying information that is highly relevant to the user, taking into account the user's geographical location. For example, the information provision unit can prioritize displaying the locations of toilets close to the user's current location. The information provision unit can also prioritize displaying the locations of milk preparation facilities close to the user's current location. The information provision unit can also prioritize displaying the locations of elevators close to the user's current location. By considering the user's geographical location, more relevant information can be provided. Some or all of the above processing in the information provision unit may be performed using AI, for example, or without AI. For example, the information provision unit can input the user's geographical location information into AI, which can then prioritize displaying the most relevant information.

[0044] The information provision unit can analyze the user's social media activity and display relevant information in the information it provides. For example, the information provision unit can suggest relevant locations based on information about places the user has shared on social media. For example, the information provision unit can suggest relevant locations based on information about accounts the user follows on social media. For example, the information provision unit can suggest relevant locations based on information about places the user has checked into on social media. For example, the information provision unit can suggest relevant locations based on information about places the user has checked into on social media. By analyzing the user's social media activity, it is possible to provide more relevant information. Some or all of the above processing in the information provision unit may be performed using AI, for example, or not. For example, the information provision unit can input data on the user's social media activity into AI, which can then display the most relevant information.

[0045] The route search unit can analyze the user's past travel history and select the optimal route search method. For example, the route search unit can search for the optimal route based on routes the user has used in the past. The route search unit can also search for routes that avoid congestion based on the user's past travel history. The route search unit can also analyze the user's past travel history and search for the most efficient route. By analyzing the user's past travel history, a more efficient route can be provided. Some or all of the above processing in the route search unit may be performed using AI, for example, or without AI. For example, the route search unit can input the user's past travel history into AI, which can then select the optimal route search method.

[0046] The route search unit can provide search results while considering the user's current traffic conditions and weather information. For example, the route search unit can search for the optimal route based on real-time traffic congestion information. The route search unit can also search for the optimal route while considering the real-time operation status of public transportation. For example, the route search unit can search for the optimal route while considering the real-time operation status of public transportation. The route search unit can also search for the optimal route based on real-time weather information. For example, the route search unit can search for the optimal route while considering the user's current traffic conditions and weather information. This allows the system to provide a more appropriate route by considering the user's current traffic conditions and weather information. Some or all of the above processing in the route search unit may be performed using AI, or not. For example, the route search unit can input real-time traffic conditions and weather information into the AI, which can then search for the optimal route.

[0047] The route search unit can prioritize displaying routes that are more relevant to the user, taking into account the user's geographical location information during a route search. For example, the route search unit can prioritize displaying routes that are close to the user's current location. The route search unit can also prioritize displaying routes that are close to the user's destination. For example, the route search unit can prioritize displaying routes that are close to the user's destination. The route search unit can also prioritize displaying the shortest route from the user's current location to their destination. For example, the route search unit can prioritize displaying the shortest route from the user's current location to their destination. By considering the user's geographical location information, the system can provide more relevant routes. Some or all of the above processing in the route search unit may be performed using AI, or not. For example, the route search unit can input the user's geographical location information into AI, which can then prioritize displaying the optimal route.

[0048] The route search unit can analyze the user's social media activity during route searching and display relevant routes. For example, the route search unit can suggest relevant routes based on information about locations the user has shared on social media. The route search unit can also suggest relevant routes based on information about accounts the user follows on social media. The route search unit can also suggest relevant routes based on information about locations the user has checked into on social media. By analyzing the user's social media activity, it is possible to provide more relevant routes. Some or all of the above processing in the route search unit may be performed using AI, for example, or without AI. For example, the route search unit can input data on the user's social media activity into AI, which can then display the optimal route.

[0049] The route suggestion unit can propose the optimal route by analyzing the user's past travel history. For example, the route suggestion unit can propose the optimal route based on routes the user has used in the past. The route suggestion unit can also propose routes that avoid congestion based on the user's past travel history. The route suggestion unit can also analyze the user's past travel history and propose the most efficient route. By analyzing the user's past travel history, a more efficient route can be provided. Some or all of the above processing in the route suggestion unit may be performed using AI, or not. For example, the route suggestion unit can input the user's past travel history into the AI, which can then propose the optimal route.

[0050] The route suggestion unit can provide route suggestions by considering the user's current traffic conditions and weather information. For example, the route suggestion unit can suggest the optimal route based on real-time traffic congestion information. The route suggestion unit can also suggest the optimal route by considering the real-time operation status of public transportation. The route suggestion unit can also suggest the optimal route by considering the real-time operation status of public transportation. The route suggestion unit can also suggest the optimal route based on real-time weather information. This allows for the provision of more appropriate routes by considering the user's current traffic conditions and weather information. Some or all of the above processing in the route suggestion unit may be performed using AI, or not. For example, the route suggestion unit can input real-time traffic conditions and weather information into AI, which can then suggest the optimal route.

[0051] The route suggestion unit can prioritize displaying the most relevant routes by considering the user's geographical location information when suggesting routes. For example, the route suggestion unit can prioritize displaying routes that are close to the user's current location. The route suggestion unit can also prioritize displaying routes that are close to the user's destination. The route suggestion unit can also prioritize displaying the shortest route from the user's current location to their destination. By considering the user's geographical location information, the system can provide more relevant routes. Some or all of the above processing in the route suggestion unit may be performed using AI, for example, or without AI. For example, the route suggestion unit can input the user's geographical location information into AI, which can then prioritize displaying the most suitable route.

[0052] The route suggestion unit can analyze the user's social media activity and display relevant routes when suggesting routes. For example, the route suggestion unit can suggest relevant routes based on information about places the user has shared on social media. The route suggestion unit can also suggest relevant routes based on information about accounts the user follows on social media. The route suggestion unit can also suggest relevant routes based on information about places the user has checked in to on social media. By analyzing the user's social media activity, it is possible to provide more relevant routes. Some or all of the above processing in the route suggestion unit may be performed using AI, or not. For example, the route suggestion unit can input data on the user's social media activity into AI, which can then display the optimal route.

[0053] The route optimization unit can provide the optimal route by analyzing the user's past travel history during route optimization. For example, the route optimization unit can provide the optimal route based on routes the user has used in the past. The route optimization unit can also provide routes that avoid congestion based on the user's past travel history. The route optimization unit can also analyze the user's past travel history and provide the most efficient route. By analyzing the user's past travel history, a more efficient route can be provided. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input the user's past travel history into AI, which can then provide the optimal route.

[0054] The route optimization unit can provide optimization results by considering the user's current traffic conditions and weather information during route optimization. For example, the route optimization unit can provide the optimal route based on real-time traffic congestion information. The route optimization unit can also provide the optimal route by considering the real-time operation status of public transportation. The route optimization unit can also provide the optimal route by considering the real-time operation status of public transportation. The route optimization unit can also provide the optimal route based on real-time weather information. This allows for the provision of a more appropriate route by considering the user's current traffic conditions and weather information. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input real-time traffic conditions and weather information into AI, which can then provide the optimal route.

[0055] The route optimization unit can prioritize displaying the most relevant routes by considering the user's geographical location information during route optimization. For example, the route optimization unit can prioritize displaying routes that are close to the user's current location. The route optimization unit can also prioritize displaying routes that are close to the user's destination. The route optimization unit can also prioritize displaying the shortest route from the user's current location to their destination. By considering the user's geographical location information, it is possible to provide more relevant routes. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input the user's geographical location information into AI, which can then prioritize displaying the optimal route.

[0056] The route optimization unit can analyze the user's social media activity and display relevant routes during route optimization. For example, the route optimization unit can suggest relevant routes based on information about locations shared by the user on social media. The route optimization unit can also suggest relevant routes based on information about accounts followed by the user on social media. The route optimization unit can also suggest relevant routes based on information about locations checked in by the user on social media. By analyzing the user's social media activity, it is possible to provide more relevant routes. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input data on the user's social media activity into AI, which can then display the optimal route.

[0057] The review sharing section can analyze a user's past review history to provide the most relevant reviews when a review is shared. For example, the review sharing section can prioritize displaying reviews of places the user has previously given high ratings to. The review sharing section can also prioritize displaying reviews of places the user has previously visited. The review sharing section can also analyze a user's past review history to provide relevant reviews. By analyzing a user's past review history, it can provide more relevant reviews. Some or all of the above processing in the review sharing section may be performed using AI, or not. For example, the review sharing section can input a user's past review history into an AI, which can then provide the most relevant reviews.

[0058] The review sharing section can prioritize displaying highly relevant reviews by considering the user's geographical location when a review is shared. For example, the review sharing section can prioritize displaying reviews from locations close to the user's current location. The review sharing section can also prioritize displaying reviews from locations close to the user's destination. For example, the review sharing section can prioritize displaying reviews from locations along the route from the user's current location to their destination. This allows for the provision of more relevant reviews by considering the user's geographical location. Some or all of the above processing in the review sharing section may be performed using AI, or not. For example, the review sharing section can input the user's geographical location information into AI, which can then prioritize displaying the most relevant reviews.

[0059] The information storage unit can analyze the user's past saving history and save the most relevant information when saving information. For example, the information storage unit can prioritize saving relevant information based on information the user has previously saved. The information storage unit can also prioritize saving frequently used information from the user's past saving history. The information storage unit can also analyze the user's past saving history and save the most relevant information. This allows for the saving of more relevant information by analyzing the user's past saving history. Some or all of the above processing in the information storage unit may be performed using AI, for example, or without AI. For example, the information storage unit can input the user's past saving history into AI, which can then save the most relevant information.

[0060] The information storage unit can prioritize saving highly relevant information by considering the user's geographical location when saving information. For example, the information storage unit can prioritize saving information that is close to the user's current location. The information storage unit can also prioritize saving information that is close to the user's destination. The information storage unit can also prioritize saving information that is along the route from the user's current location to their destination. By considering the user's geographical location, more relevant information can be saved. Some or all of the above processing in the information storage unit may be performed using AI, for example, or without AI. For example, the information storage unit can input the user's geographical location information into AI, and the AI ​​can save the most relevant information.

[0061] The outing suggestion function can analyze the user's past outing history to suggest the most suitable destination. For example, the outing suggestion function can suggest related destinations based on places the user has visited in the past. The outing suggestion function can also suggest similar places based on the user's past outing history. The outing suggestion function can also analyze the user's past outing history to suggest the most relevant destination. By analyzing the user's past outing history, it can provide more relevant destinations. Some or all of the above processing in the outing suggestion function may be performed using AI, for example, or without AI. For example, the outing suggestion function can input a user's past outing history into an AI, which can then suggest the most suitable destination.

[0062] The outing suggestion unit can provide suggestions by considering the user's current lifestyle and areas of interest when suggesting outings. For example, the outing suggestion unit can suggest appropriate destinations based on the user's current lifestyle. For example, the outing suggestion unit can suggest appropriate destinations based on the user's current lifestyle. The outing suggestion unit can also suggest relevant destinations based on the user's areas of interest. For example, the outing suggestion unit can suggest relevant destinations based on the user's areas of interest. The outing suggestion unit can also analyze the user's current lifestyle and areas of interest and suggest the most relevant destination. For example, the outing suggestion unit can analyze the user's current lifestyle and areas of interest and suggest the most relevant destination. By considering the user's current lifestyle and areas of interest, it can provide more relevant destinations. Some or all of the above processing in the outing suggestion unit may be performed using AI, for example, or without AI. For example, the outing suggestion function can input information about the user's current lifestyle and areas of interest into the AI, which can then suggest the most suitable outing destination.

[0063] The outing suggestion function can prioritize displaying highly relevant destinations by considering the user's geographical location when suggesting outings. For example, the outing suggestion function can prioritize displaying destinations close to the user's current location. For example, the outing suggestion function can prioritize displaying destinations close to the user's destination. For example, the outing suggestion function can prioritize displaying destinations close to the user's destination. For example, the outing suggestion function can prioritize displaying destinations that are on the route from the user's current location to their destination. For example, the outing suggestion function can prioritize displaying destinations that are on the route from the user's current location to their destination. By considering the user's geographical location, it is possible to provide more relevant destinations. Some or all of the above processing in the outing suggestion function may be performed using AI, for example, or without using AI. For example, the outing suggestion function can input the user's geographical location information into the AI, which can then prioritize displaying the most suitable outing destinations.

[0064] The outing suggestion function can analyze the user's social media activity and display relevant destinations when suggesting outings. For example, the outing suggestion function can suggest relevant destinations based on information about places the user has shared on social media. For example, the outing suggestion function can suggest relevant destinations based on information about accounts the user follows on social media. For example, the outing suggestion function can suggest relevant destinations based on information about places the user has checked into on social media. For example, the outing suggestion function can suggest relevant destinations based on information about places the user has checked into on social media. By analyzing the user's social media activity, it is possible to provide more relevant destinations. Some or all of the above processing in the outing suggestion function may be performed using AI, for example, or without AI. For example, the outing suggestion function can input data from the user's social media activity into an AI, which can then display the most suitable destination.

[0065] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0066] The outing support system can also include a health management unit that monitors the user's health status. The health management unit acquires vital data such as the user's heart rate and body temperature, and monitors the user's health status in real time. For example, if the user's heart rate is abnormally high, the health management unit can send a notification prompting them to take a break. It can also provide information on nearby medical facilities if the user's body temperature is high. Furthermore, the health management unit can suggest appropriate routes and destinations based on the user's health status. For example, if the user is tired, the health management unit can suggest a relaxing place that can be reached in a short time. This provides support tailored to the user's health condition, allowing them to go out with peace of mind.

[0067] The outing support system can also include a plan creation unit that creates customized outing plans based on the user's preferences. The plan creation unit analyzes the user's past activity history and preferences to propose the optimal outing plan. For example, it can create a plan that includes similar places based on places the user has visited and their ratings. It can also suggest new places based on the user's preferences and interests. Furthermore, it can create an efficient outing plan that fits the user's schedule. This allows for the provision of customized outing plans tailored to the user's preferences, supporting more fulfilling outings.

[0068] The outing support system can also include an activity suggestion unit that proposes appropriate activities based on the age and characteristics of the user's child. For example, the activity suggestion unit can suggest places where parents with infants can prepare formula and change diapers. It can also suggest playgrounds and restaurants with children's menus to parents with toddlers. Furthermore, it can suggest learning facilities and experiential facilities to parents with elementary school children. This allows the system to propose activities tailored to the age and characteristics of the user's child, supporting more fulfilling outings.

[0069] The outing support system can also include a search history analysis unit that analyzes the user's past search history and provides customized, optimal information. For example, the search history analysis unit can prioritize displaying locations of restrooms that the user has frequently searched for in the past. It can also suggest similar restaurants based on reviews of restaurants the user has visited in the past. Furthermore, it can suggest the optimal route based on the locations of elevators the user has used in the past. This allows for the provision of more relevant information by analyzing the user's past search history.

[0070] The outing support system can also include a geographic information provision unit that prioritizes displaying highly relevant information by considering the user's geographic location. The geographic information provision unit provides optimal information based on the user's current location. For example, the geographic information provision unit can prioritize displaying the locations of toilets near the user's current location. It can also prioritize displaying the locations of milk-making facilities near the user's current location. Furthermore, it can prioritize displaying the locations of elevators near the user's current location. In this way, more relevant information can be provided by considering the user's geographic location.

[0071] The outing support system can also include a social media analysis unit that analyzes the user's social media activity and displays relevant information. The social media analysis unit analyzes the user's social media activity and provides relevant information. For example, it can suggest relevant locations based on information about places the user has shared on social media. It can also suggest relevant locations based on information about accounts the user follows on social media. Furthermore, it can suggest relevant locations based on information about places the user has checked into on social media. This allows for the provision of more relevant information by analyzing the user's social media activity.

[0072] The following briefly describes the processing flow for example form 1.

[0073] Step 1: The information department provides information according to the destination. For example, it provides information such as the location of restrooms, places where you can prepare formula, places where you can change clothes, restaurants that are easy to go to with children, routes that are easy to navigate with large strollers, and the location of elevators. Specifically, it displays the locations of restrooms in shopping malls and parks on a map, and provides text information on places where you can prepare formula in cafes and restaurants. It also displays places where you can change clothes, such as baby rest rooms and changing rooms, on a map, and lists restaurants that have children's menus or restaurants that have baby chairs. Furthermore, it displays routes with few steps or wide sidewalks, and the locations of elevators in stations and shopping malls on a map. Step 2: The route search unit searches for a route from the user's current location to their destination. For example, it searches for a route based on the starting point and destination entered by the user. The user enters the starting point and destination using methods such as address input or specifying a pin on a map, and the unit searches for the optimal route based on the entered information. Step 3: The route suggestion unit proposes a route that takes the elevator's location into account, based on the route search unit's search results. For example, it proposes a route that allows for smooth travel with a stroller, taking the elevator's location into consideration. The elevator's location is displayed on the map, and a route that takes its location into account is proposed. Step 4: The route optimization unit provides the optimal route based on the route proposed by the route proposal unit. For example, it provides the optimal route based on information entered by the user, according to criteria such as time reduction, distance reduction, and consideration of traffic conditions. It provides the optimal route while considering real-time traffic information.

[0074] (Example of form 2) The outing support system according to an embodiment of the present invention is a system designed to simplify the preparations parents make when going out with children. This outing support system provides the following information depending on the destination. First, it tells the user the location of restrooms. For example, it can tell the user the location of restrooms in advance at places they will go with their children, such as shopping malls and parks. Next, it tells the user the location of places where they can prepare formula milk. For example, it can tell the user the location of places with facilities for preparing formula milk, such as cafes and restaurants. Furthermore, it tells the user the location of places where they can change clothes. For example, it can tell the user the location of places where they can change their child's clothes, such as baby changing rooms and dressing rooms. It also tells the user the location of restaurants that are easy to go to with children. For example, it can tell the user the location of restaurants with children's menus or restaurants that have high chairs available. Furthermore, it tells the user the location of routes that are easy to navigate even with a large stroller. For example, it can tell the user the location of routes that are easy to navigate with a stroller, such as routes with few steps or routes with wide sidewalks. It also tells the user the location of elevators. For example, it can tell the user the location of elevators in places such as train stations and shopping malls. Using this outing support system makes going out with children much easier. Parents can obtain necessary information in advance, allowing them to go out with peace of mind. For example, when going to a shopping mall, knowing the location of restrooms, places to prepare milk, and elevators beforehand allows for a smoother outing. Also, knowing in advance about child-friendly restaurants and routes that are easy to navigate with a stroller allows for a stress-free outing. This outing support system targets families with young children, such as infants and elementary school children. It solves problems such as limited places to go when wanting to go out, the difficulty of prior research, and the fact that they have never been able to arrive on time due to detours using elevators. By alleviating parental anxiety and suggesting child-friendly places and routes, it allows parents to go out with peace of mind. In this way, the outing support system provides parents with information to make outings with children smoother and more worry-free.

[0075] The outing support system according to this embodiment comprises an information provision unit, a route search unit, a route suggestion unit, and a route optimization unit. The information provision unit provides information according to the destination. For example, the information provision unit provides information such as the location of toilets, places where milk can be prepared, places where clothes can be changed, restaurants that are easy to go to with children, routes that are easy to navigate even with a large stroller, and the location of elevators. For example, the information provision unit displays the locations of toilets in shopping malls and parks on a map. The information provision unit can also provide text information about places where milk can be prepared, such as cafes and restaurants. Furthermore, the information provision unit can also display places where clothes can be changed, such as baby rest rooms and changing rooms, on a map. For example, the information provision unit lists restaurants with children's menus and restaurants that have baby chairs and provides this information to the user. The information provision unit can also display routes on a map that have few steps or wide sidewalks. Furthermore, the information provision unit can also display the locations of elevators in stations and shopping malls on a map. The route search unit searches for a route from the user's current location to their destination. The route search unit searches for a route based on the departure and destination points entered by the user. For example, the route search unit allows users to input the departure and destination points by methods such as entering an address or specifying a pin on a map. The route search unit searches for the optimal route based on the entered information. The route suggestion unit proposes a route that takes elevator locations into account, based on the route search unit's search results. For example, the route suggestion unit proposes a route that makes travel with a stroller easier by taking elevator locations into account. For example, the route suggestion unit displays elevator locations on a map and proposes a route that takes these locations into account. The route optimization unit provides the optimal route based on the route suggested by the route suggestion unit. For example, the route optimization unit provides the optimal route based on user input, according to criteria such as time reduction, distance reduction, and consideration of traffic conditions. For example, the route optimization unit provides the optimal route by taking real-time traffic information into account.As a result, the outing support system according to this embodiment provides information that allows parents to go out with their children smoothly, enabling them to go out with peace of mind.

[0076] The information service provides information tailored to the user's desired destination. For example, it can provide information such as the locations of restrooms, places to prepare formula, changing facilities, child-friendly restaurants, routes easily accessible with large strollers, and elevator locations. Specifically, the service displays the locations of restrooms in shopping malls and parks on a map, allowing users to quickly find the nearest restroom. It can also provide text information about places to prepare formula, such as cafes and restaurants. For instance, it might indicate whether a particular cafe offers hot water or has a dedicated space for preparing formula. Furthermore, the service can display changing facilities, such as baby changing rooms and restrooms, on a map, enabling users to quickly find the nearest facility even in urgent situations. For example, the service can list restaurants with children's menus or high chairs, making dining out with children more comfortable. Finally, the service can display routes with minimal steps and wide sidewalks on a map. This allows users to choose routes that allow for smooth movement even with large strollers. Furthermore, the information service can display the locations of elevators in places like train stations and shopping malls on the map. This allows users to avoid stairs and escalators. The information service centrally manages this information, enabling users to quickly obtain the information they need. For example, when a user searches for a specific facility or location, relevant information will be automatically displayed. The information service can also provide individually customized information based on the user's past search and usage history. This allows users to receive more personalized information, improving convenience when going out.

[0077] The route search unit searches for a route from the user's current location to their destination. For example, it searches for a route based on the user's entered starting point and destination. Specifically, the route search unit allows users to input the starting point and destination using methods such as address input or pin selection on a map. Once the user enters the starting point and destination, the route search unit accesses map databases and traffic information databases to find the optimal route. This allows the user to obtain a route that takes into account real-time traffic conditions and road congestion. For example, the route search unit calculates the fastest route to the destination based on current traffic conditions. The route search unit can also provide routes that consider specific conditions according to the user's preferences. For example, if the user is using a stroller, it can prioritize routes with fewer steps or routes with elevators. Furthermore, the route search unit can handle cases where the user sets multiple destinations. For example, if the user wants to stop by a park before going to a shopping mall, the route search unit provides the optimal route to visit these destinations in order. This allows the user to travel efficiently. The route search unit displays the search results on a map, allowing the user to visually confirm the route. Furthermore, the route search unit provides voice and text guidance, making it easier for users to check their route while traveling. In this way, the route search unit helps users reach their destination smoothly.

[0078] The route suggestion unit proposes routes that take elevator locations into consideration, based on the routes found by the route search unit. Specifically, the route suggestion unit proposes routes that are easy to navigate with a stroller, taking elevator locations into account. For example, the route suggestion unit displays elevator locations on the map and proposes routes that take these locations into consideration. This allows users to avoid stairs and escalators. In addition to elevator locations, the route suggestion unit also considers routes with fewer steps and wider sidewalks. This makes travel more comfortable for users with strollers or wheelchairs. Furthermore, the route suggestion unit can also propose individually customized routes based on the user's past travel history and preferences. For example, it proposes the optimal route considering routes the user has used in the past and places they like to visit. This allows users to enjoy a more personalized travel experience. The route suggestion unit displays the proposed route on the map, allowing users to visually confirm the route. The route suggestion unit also provides voice and text guidance to make it easier for users to check the route while traveling. In this way, the route suggestion unit helps users reach their destination smoothly. Furthermore, the route suggestion system can continuously update suggested routes by taking real-time traffic and weather information into account. This ensures that users always have access to the optimal route based on the latest information.

[0079] The route optimization unit provides the optimal route based on the route proposed by the route suggestion unit. Specifically, the route optimization unit provides the optimal route based on information entered by the user, according to criteria such as time reduction, distance reduction, and consideration of traffic conditions. For example, the route optimization unit provides the optimal route considering real-time traffic information. This allows the user to avoid congestion and travel smoothly. The route optimization unit also considers not only traffic information but also weather information and road construction information. This allows the user to travel while avoiding unexpected delays and obstacles. Furthermore, the route optimization unit can also provide individually customized routes based on the user's travel history and preferences. For example, it provides the optimal route considering routes the user has used in the past and places they like to visit. This allows the user to enjoy a more personalized travel experience. The route optimization unit displays the proposed route on a map, allowing the user to visually confirm the route. In addition, the route optimization unit provides voice guidance and text guidance to make it easier for the user to check the route while traveling. In this way, the route optimization unit helps the user reach their destination smoothly. Furthermore, the route optimization unit can continuously update the proposed route by taking real-time traffic and weather information into account. This ensures that users can always utilize the optimal route based on the latest information.

[0080] The information service can provide information such as the locations of restrooms, places where milk can be prepared, places where clothes can be changed, restaurants that are easy to visit with children, routes that are easy to navigate with large strollers, and elevator locations. For example, the information service can display the locations of restrooms on a map. For example, it can display the locations of restrooms in shopping malls and parks on a map. The information service can also provide text information about places where milk can be prepared, such as cafes and restaurants. For example, it can provide text information about the opening hours and availability of facilities for cafes and restaurants. Furthermore, the information service can display places where clothes can be changed, such as baby rest rooms and changing rooms, on a map. For example, it can display information about the privacy and facilities of baby rest rooms and changing rooms on a map. In addition, the information service can list and provide users with restaurants that have children's menus or restaurants that have baby chairs. For example, it can list and provide information about restaurants that have children's menus or the availability of baby chairs. Furthermore, the information service can display routes on a map that have few steps or wide sidewalks. For example, the information provision unit displays the presence or absence of steps and road width on a map. The information provision unit can also display the locations of elevators in places like train stations and shopping malls on a map. For instance, the information provision unit displays elevator locations on a map and provides this information to the user. This allows the user to obtain necessary information in advance, enabling them to go out with peace of mind. Some or all of the above-described processing in the information provision unit may be performed using AI, or not. For example, the information provision unit can input information about the locations of toilets or places where milk can be prepared into the AI, which can then provide the most appropriate information.

[0081] The route search unit can search for a route based on the departure point and destination entered by the user. For example, the route search unit can input the departure point and destination by methods such as entering an address or specifying a pin on a map. The route search unit searches for the optimal route based on the entered information. For example, the route search unit searches for the optimal route based on the departure point and destination entered by the user. The route search unit can also suggest the optimal route based on the departure point and destination information entered by the user. This allows the user to find the optimal route simply by entering the departure point and destination. Some or all of the above processing in the route search unit may be performed using AI, for example, or without AI. For example, the route search unit can input the departure point and destination information entered by the user into the AI, and the AI ​​can search for the optimal route.

[0082] The route suggestion unit can propose a route that takes the location of the elevator into consideration. For example, the route suggestion unit can propose a route that makes it easier to travel with a stroller by taking the location of the elevator into consideration. For example, the route suggestion unit can display the location of the elevator on a map and propose a route that takes that location into consideration. In this way, by proposing a route that takes the location of the elevator into consideration, it makes it easier to travel with a stroller. Some or all of the above processing in the route suggestion unit may be performed using AI, for example, or not using AI. For example, the route suggestion unit can input the location of the elevator into the AI, and the AI ​​can propose the optimal route.

[0083] The route optimization unit can provide the optimal route based on the information entered by the user. For example, the route optimization unit provides the optimal route based on the information entered by the user, according to criteria such as time reduction, distance reduction, and consideration of traffic conditions. For example, the route optimization unit provides the optimal route by considering real-time traffic information. This enables efficient travel by providing the optimal route based on the information entered by the user. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input the information entered by the user into the AI, and the AI ​​can provide the optimal route.

[0084] The review sharing section allows users to share reviews and ratings of places they have visited. For example, the review sharing section can share reviews and ratings of places visited by users. For example, the review sharing section can share reviews and ratings in methods such as star ratings and comments. The review sharing section provides reviews and ratings of places visited by users so that other users can refer to them. For example, the review sharing section displays reviews of places visited by users using star ratings, allowing other users to refer to those ratings. The review sharing section also displays detailed comments about places visited by users, allowing other users to refer to those comments. This allows other users to refer to reviews and ratings of places visited by users by sharing them. Some or all of the above processing in the review sharing section may be performed using AI, or not. For example, the review sharing section can input user-entered reviews and ratings into AI, which can then provide optimal reviews and ratings.

[0085] The information storage unit can store information about places the user has visited. For example, the information storage unit can store information in the form of text information or photographs. The information storage unit stores information about places the user has visited so that it can be used to help with future outings. For example, the information storage unit can store text information about places the user has visited so that it can be referenced on future outings. The information storage unit can also store photographs of places the user has visited so that it can be referenced on future outings. In this way, by saving information about places the user has visited, it can be used to help with future outings. Some or all of the above processing in the information storage unit may be performed using AI, for example, or without AI. For example, the information storage unit can input information entered by the user into the AI, and the AI ​​can store the most appropriate information.

[0086] The Outing Suggestion Department uses AI to suggest destinations for your next outing. For example, the Outing Suggestion Department can analyze the user's past behavior history and preferences to suggest destinations for their next outing. The Outing Suggestion Department helps users discover new places. For example, it can suggest related new places based on information about places the user has visited in the past. It can also suggest new destinations based on the user's preferences and interests. In this way, the AI ​​suggests destinations for the next outing, allowing users to discover new places. Some or all of the above processes in the Outing Suggestion Department are performed using generative AI. For example, the Outing Suggestion Department inputs the user's past behavior history and preferences into the generative AI, which can then suggest the most suitable destination.

[0087] The information provision unit can estimate the user's emotions and adjust the priority of the information provided based on those emotions. For example, if the user is stressed, the information provision unit will prioritize providing urgent information such as restrooms or places to prepare baby formula. If the user is relaxed, the information provision unit can also prioritize providing comfort-oriented information such as restaurants that are child-friendly or routes that are easy to navigate with a stroller. If the user is in a hurry, the information provision unit can prioritize providing information that allows for quick movement, such as elevator locations or the shortest routes. In this way, by adjusting the priority of information according to the user's emotions, more appropriate information can be provided. Emotion estimation is achieved using an emotion estimation function that utilizes an emotion engine or generative AI. The generation AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the processing described above in the information provision unit may be performed using AI, or not using AI. For example, the information provision unit can input user sentiment data into the generation AI, which can then adjust the priority of the information to be optimal.

[0088] The information provision unit can analyze a user's past search history and provide customized, optimal information. For example, the information provision unit can prioritize displaying restroom locations that the user has frequently searched for in the past. The information provision unit can also suggest similar restaurants based on reviews of restaurants the user has visited in the past. For example, the information provision unit can suggest relevant restaurants based on reviews of restaurants the user has visited in the past. The information provision unit can also suggest the optimal route based on the location of elevators the user has used in the past. For example, the information provision unit can suggest the optimal route based on the location of elevators the user has used in the past. By analyzing the user's past search history, more relevant information can be provided. Some or all of the above processing in the information provision unit may be performed using AI, for example, or not. For example, the information provision unit can input the user's past search history into AI, which can then customize and provide optimal information.

[0089] The information provision unit can filter the information it provides based on the user's child's age and characteristics. For example, the information provision unit can prioritize providing information on places to prepare formula and change diapers to parents with infants. The information provision unit can also suggest playgrounds and restaurants with children's menus to parents with toddlers. The information provision unit can also suggest learning facilities and experiential facilities to parents with elementary school children. The information provision unit can prioritize displaying learning facilities and experiential facilities to parents with elementary school children. By providing information based on the user's child's age and characteristics, more appropriate information can be provided. Some or all of the above processing in the information provision unit may be performed using AI, for example, or not. For example, the information provision unit can input information on the user's child's age and characteristics into the AI, which can then filter and provide the most suitable information.

[0090] The information provider can estimate the user's emotions and adjust the way information is displayed based on the estimated emotions. For example, if the user is nervous, the information provider can provide a simple and highly visible display method. For example, if the user is nervous, the information provider can provide a simple and highly visible display method. The information provider can also provide a display method that includes detailed information if the user is relaxed. For example, if the user is relaxed, the information provider can provide a display method that includes detailed information. The information provider can also provide a display method that gets to the point if the user is in a hurry. For example, if the information provider can provide a display method that gets to the point if the user is in a hurry. By adjusting the way information is displayed according to the user's emotions, more visually appealing information can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generative AI. The generative AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to these examples. Some or all of the above processing in the information provider may be performed using AI, for example, or without AI. For example, the information provision unit can input user emotion data into a generating AI, which can then adjust the optimal way to display the information.

[0091] The information provision unit can prioritize displaying information that is highly relevant to the user, taking into account the user's geographical location. For example, the information provision unit can prioritize displaying the locations of toilets close to the user's current location. The information provision unit can also prioritize displaying the locations of milk preparation facilities close to the user's current location. The information provision unit can also prioritize displaying the locations of elevators close to the user's current location. By considering the user's geographical location, more relevant information can be provided. Some or all of the above processing in the information provision unit may be performed using AI, for example, or without AI. For example, the information provision unit can input the user's geographical location information into AI, which can then prioritize displaying the most relevant information.

[0092] The information provision unit can analyze the user's social media activity and display relevant information in the information it provides. For example, the information provision unit can suggest relevant locations based on information about places the user has shared on social media. For example, the information provision unit can suggest relevant locations based on information about accounts the user follows on social media. For example, the information provision unit can suggest relevant locations based on information about places the user has checked into on social media. For example, the information provision unit can suggest relevant locations based on information about places the user has checked into on social media. By analyzing the user's social media activity, it is possible to provide more relevant information. Some or all of the above processing in the information provision unit may be performed using AI, for example, or not. For example, the information provision unit can input data on the user's social media activity into AI, which can then display the most relevant information.

[0093] The route search unit can estimate the user's emotions and adjust the priority of the route search based on the estimated emotions. For example, if the user is stressed, the route search unit will prioritize finding the shortest route. For example, if the user is relaxed, the route search unit will prioritize finding a route with good scenery. For example, if the user is relaxed, the route search unit will prioritize finding a route with good scenery. For example, if the user is in a hurry, the route search unit will prioritize finding a route that avoids traffic congestion. For example, if the user is in a hurry, the route search unit will prioritize finding a route that avoids traffic congestion. In this way, by adjusting the priority of the route search according to the user's emotions, a more appropriate route can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the route search unit may be performed using AI, for example, or without AI. For example, the route search unit can input user emotion data into a generating AI, which can then adjust the priority of the optimal route search.

[0094] The route search unit can analyze the user's past travel history and select the optimal route search method. For example, the route search unit can search for the optimal route based on routes the user has used in the past. The route search unit can also search for routes that avoid congestion based on the user's past travel history. The route search unit can also analyze the user's past travel history and search for the most efficient route. By analyzing the user's past travel history, a more efficient route can be provided. Some or all of the above processing in the route search unit may be performed using AI, for example, or without AI. For example, the route search unit can input the user's past travel history into AI, which can then select the optimal route search method.

[0095] The route search unit can provide search results while considering the user's current traffic conditions and weather information. For example, the route search unit can search for the optimal route based on real-time traffic congestion information. The route search unit can also search for the optimal route while considering the real-time operation status of public transportation. For example, the route search unit can search for the optimal route while considering the real-time operation status of public transportation. The route search unit can also search for the optimal route based on real-time weather information. For example, the route search unit can search for the optimal route while considering the user's current traffic conditions and weather information. This allows the system to provide a more appropriate route by considering the user's current traffic conditions and weather information. Some or all of the above processing in the route search unit may be performed using AI, or not. For example, the route search unit can input real-time traffic conditions and weather information into the AI, which can then search for the optimal route.

[0096] The route search unit can estimate the user's emotions and adjust the display method of the route search based on the estimated emotions. For example, if the user is nervous, the route search unit can provide a simple and highly visible display method. For example, if the user is nervous, the route search unit can provide a simple and highly visible display method. Also, if the user is relaxed, the route search unit can provide a display method that includes detailed information. Also, if the user is in a hurry, the route search unit can provide a display method that gets straight to the point. For example, if the user is in a hurry, the route search unit can provide a display method that gets straight to the point. By adjusting the display method of the route search according to the user's emotions, more visually appealing information can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the route search unit may be performed using AI, for example, or without AI. For example, the route search unit can input user emotion data into a generating AI, which can then adjust the optimal route search display method.

[0097] The route search unit can prioritize displaying routes that are more relevant to the user, taking into account the user's geographical location information during a route search. For example, the route search unit can prioritize displaying routes that are close to the user's current location. The route search unit can also prioritize displaying routes that are close to the user's destination. For example, the route search unit can prioritize displaying routes that are close to the user's destination. The route search unit can also prioritize displaying the shortest route from the user's current location to their destination. For example, the route search unit can prioritize displaying the shortest route from the user's current location to their destination. By considering the user's geographical location information, the system can provide more relevant routes. Some or all of the above processing in the route search unit may be performed using AI, or not. For example, the route search unit can input the user's geographical location information into AI, which can then prioritize displaying the optimal route.

[0098] The route search unit can analyze the user's social media activity during route searching and display relevant routes. For example, the route search unit can suggest relevant routes based on information about locations the user has shared on social media. The route search unit can also suggest relevant routes based on information about accounts the user follows on social media. The route search unit can also suggest relevant routes based on information about locations the user has checked into on social media. By analyzing the user's social media activity, it is possible to provide more relevant routes. Some or all of the above processing in the route search unit may be performed using AI, for example, or without AI. For example, the route search unit can input data on the user's social media activity into AI, which can then display the optimal route.

[0099] The route suggestion unit can estimate the user's emotions and adjust the priority of suggested routes based on the estimated emotions. For example, if the user is stressed, the route suggestion unit will prioritize suggesting the shortest route. For example, if the user is relaxed, the route suggestion unit will prioritize suggesting a route with good scenery. For example, if the user is relaxed, the route suggestion unit will prioritize suggesting a route with good scenery. For example, if the user is in a hurry, the route suggestion unit will prioritize suggesting a route that avoids traffic congestion. For example, if the user is in a hurry, the route suggestion unit will prioritize suggesting a route that avoids traffic congestion. In this way, by adjusting the priority of routes according to the user's emotions, a more appropriate route can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the route suggestion unit may be performed using AI, for example, or without AI. For example, the route suggestion unit can input user emotion data into a generating AI, which can then adjust the priority of the optimal route.

[0100] The route suggestion unit can propose the optimal route by analyzing the user's past travel history. For example, the route suggestion unit can propose the optimal route based on routes the user has used in the past. The route suggestion unit can also propose routes that avoid congestion based on the user's past travel history. The route suggestion unit can also analyze the user's past travel history and propose the most efficient route. By analyzing the user's past travel history, a more efficient route can be provided. Some or all of the above processing in the route suggestion unit may be performed using AI, or not. For example, the route suggestion unit can input the user's past travel history into the AI, which can then propose the optimal route.

[0101] The route suggestion unit can provide route suggestions by considering the user's current traffic conditions and weather information. For example, the route suggestion unit can suggest the optimal route based on real-time traffic congestion information. The route suggestion unit can also suggest the optimal route by considering the real-time operation status of public transportation. The route suggestion unit can also suggest the optimal route by considering the real-time operation status of public transportation. The route suggestion unit can also suggest the optimal route based on real-time weather information. This allows for the provision of more appropriate routes by considering the user's current traffic conditions and weather information. Some or all of the above processing in the route suggestion unit may be performed using AI, or not. For example, the route suggestion unit can input real-time traffic conditions and weather information into AI, which can then suggest the optimal route.

[0102] The route suggestion unit can estimate the user's emotions and adjust the way it displays the suggested route based on the estimated emotions. For example, if the user is nervous, the route suggestion unit can provide a simple and highly visible display method. For example, if the user is nervous, the route suggestion unit can provide a simple and highly visible display method. Also, if the user is relaxed, the route suggestion unit can provide a display method that includes detailed information. For example, if the user is relaxed, the route suggestion unit can provide a display method that includes detailed information. Also, if the user is in a hurry, the route suggestion unit can provide a display method that gets straight to the point. For example, if the user is in a hurry, the route suggestion unit can provide a display method that gets straight to the point. By adjusting the way the route is displayed according to the user's emotions, more visually appealing information can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processing in the route suggestion unit may be performed using AI, for example, or without AI. For example, the route suggestion unit can input user emotion data into a generating AI, which can then adjust the optimal route display method.

[0103] The route suggestion unit can prioritize displaying the most relevant routes by considering the user's geographical location information when suggesting routes. For example, the route suggestion unit can prioritize displaying routes that are close to the user's current location. The route suggestion unit can also prioritize displaying routes that are close to the user's destination. The route suggestion unit can also prioritize displaying the shortest route from the user's current location to their destination. By considering the user's geographical location information, the system can provide more relevant routes. Some or all of the above processing in the route suggestion unit may be performed using AI, for example, or without AI. For example, the route suggestion unit can input the user's geographical location information into AI, which can then prioritize displaying the most suitable route.

[0104] The route suggestion unit can analyze the user's social media activity and display relevant routes when suggesting routes. For example, the route suggestion unit can suggest relevant routes based on information about places the user has shared on social media. The route suggestion unit can also suggest relevant routes based on information about accounts the user follows on social media. The route suggestion unit can also suggest relevant routes based on information about places the user has checked in to on social media. By analyzing the user's social media activity, it is possible to provide more relevant routes. Some or all of the above processing in the route suggestion unit may be performed using AI, or not. For example, the route suggestion unit can input data on the user's social media activity into AI, which can then display the optimal route.

[0105] The route optimization unit can estimate the user's emotions and adjust the priority of the route to be optimized based on the estimated emotions. For example, if the user is stressed, the route optimization unit will prioritize optimizing the shortest route. For example, if the user is relaxed, the route optimization unit will prioritize optimizing the shortest route. For example, if the user is relaxed, the route optimization unit will prioritize optimizing the scenic route. For example, if the user is in a hurry, the route optimization unit will prioritize optimizing the route to avoid traffic congestion. For example, if the user is in a hurry, the route optimization unit will prioritize optimizing the route to avoid traffic congestion. In this way, by adjusting the route priority according to the user's emotions, a more appropriate route can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input user emotion data into a generating AI, which can then adjust the priority of the optimal route.

[0106] The route optimization unit can provide the optimal route by analyzing the user's past travel history during route optimization. For example, the route optimization unit can provide the optimal route based on routes the user has used in the past. The route optimization unit can also provide routes that avoid congestion based on the user's past travel history. The route optimization unit can also analyze the user's past travel history and provide the most efficient route. By analyzing the user's past travel history, a more efficient route can be provided. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input the user's past travel history into AI, which can then provide the optimal route.

[0107] The route optimization unit can provide optimization results by considering the user's current traffic conditions and weather information during route optimization. For example, the route optimization unit can provide the optimal route based on real-time traffic congestion information. The route optimization unit can also provide the optimal route by considering the real-time operation status of public transportation. The route optimization unit can also provide the optimal route by considering the real-time operation status of public transportation. The route optimization unit can also provide the optimal route based on real-time weather information. This allows for the provision of a more appropriate route by considering the user's current traffic conditions and weather information. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input real-time traffic conditions and weather information into AI, which can then provide the optimal route.

[0108] The route optimization unit can estimate the user's emotions and adjust the display method of the optimized route based on the estimated user emotions. For example, if the user is nervous, the route optimization unit can provide a simple and highly visible display method. For example, if the user is nervous, the route optimization unit can provide a simple and highly visible display method. The route optimization unit can also provide a display method that includes detailed information if the user is relaxed. For example, if the user is relaxed, the route optimization unit can provide a display method that includes detailed information. The route optimization unit can also provide a display method that gets to the point if the user is in a hurry. For example, if the user is in a hurry, the route optimization unit can provide a display method that gets to the point. By adjusting the route display method according to the user's emotions, more visually appealing information can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generative AI. The generative AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input user emotion data into a generating AI, which can then adjust the optimal route display method.

[0109] The route optimization unit can prioritize displaying the most relevant routes by considering the user's geographical location information during route optimization. For example, the route optimization unit can prioritize displaying routes that are close to the user's current location. The route optimization unit can also prioritize displaying routes that are close to the user's destination. The route optimization unit can also prioritize displaying the shortest route from the user's current location to their destination. By considering the user's geographical location information, it is possible to provide more relevant routes. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input the user's geographical location information into AI, which can then prioritize displaying the optimal route.

[0110] The route optimization unit can analyze the user's social media activity and display relevant routes during route optimization. For example, the route optimization unit can suggest relevant routes based on information about locations shared by the user on social media. The route optimization unit can also suggest relevant routes based on information about accounts followed by the user on social media. The route optimization unit can also suggest relevant routes based on information about locations checked in by the user on social media. By analyzing the user's social media activity, it is possible to provide more relevant routes. Some or all of the above processing in the route optimization unit may be performed using AI, for example, or without AI. For example, the route optimization unit can input data on the user's social media activity into AI, which can then display the optimal route.

[0111] The review sharing section can estimate the user's emotions and adjust how reviews are displayed based on the estimated emotions. For example, if the user is nervous, the review sharing section can provide a simple and highly visible display method. For example, if the user is nervous, the review sharing section can provide a simple and highly visible display method. For example, if the user is relaxed, the review sharing section can provide a display method that includes detailed information. For example, if the user is relaxed, the review sharing section can provide a display method that includes detailed information. For example, if the user is in a hurry, the review sharing section can provide a display method that gets to the point. For example, if the user is in a hurry, the review sharing section can provide a display method that gets to the point. By adjusting how reviews are displayed according to the user's emotions, more highly visible information can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the review sharing section may be performed using AI, for example, or without AI. For example, the review sharing section can input user sentiment data into a generating AI, which can then adjust the optimal way to display the reviews.

[0112] The review sharing section can analyze a user's past review history to provide the most relevant reviews when a review is shared. For example, the review sharing section can prioritize displaying reviews of places the user has previously given high ratings to. The review sharing section can also prioritize displaying reviews of places the user has previously visited. The review sharing section can also analyze a user's past review history to provide relevant reviews. By analyzing a user's past review history, it can provide more relevant reviews. Some or all of the above processing in the review sharing section may be performed using AI, or not. For example, the review sharing section can input a user's past review history into an AI, which can then provide the most relevant reviews.

[0113] The review sharing section can estimate the user's emotions and prioritize reviews based on those emotions. For example, if the user is stressed, the review sharing section will prioritize displaying positive reviews. For example, if the user is relaxed, the review sharing section will prioritize displaying detailed reviews. For example, if the user is relaxed, the review sharing section will prioritize displaying detailed reviews. For example, if the user is in a hurry, the review sharing section will prioritize displaying concise reviews. For example, if the user is in a hurry, the review sharing section will prioritize displaying concise reviews. By prioritizing reviews according to the user's emotions, more appropriate reviews can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the review sharing section may be performed using AI, for example, or without AI. For example, the review sharing section can input user sentiment data into a generating AI, which can then determine the optimal review priorities.

[0114] The review sharing section can prioritize displaying highly relevant reviews by considering the user's geographical location when a review is shared. For example, the review sharing section can prioritize displaying reviews from locations close to the user's current location. The review sharing section can also prioritize displaying reviews from locations close to the user's destination. For example, the review sharing section can prioritize displaying reviews from locations along the route from the user's current location to their destination. This allows for the provision of more relevant reviews by considering the user's geographical location. Some or all of the above processing in the review sharing section may be performed using AI, or not. For example, the review sharing section can input the user's geographical location information into AI, which can then prioritize displaying the most relevant reviews.

[0115] The information storage unit can estimate the user's emotions and adjust the priority of information to be stored based on the estimated emotions. For example, if the user is stressed, the information storage unit will prioritize storing information of high urgency. For example, if the user is relaxed, the information storage unit will prioritize storing information of high urgency. For example, if the user is relaxed, the information storage unit will prioritize storing information of detail. For example, if the user is in a hurry, the information storage unit will prioritize storing information that gets straight to the point. For example, if the user is in a hurry, the information storage unit will prioritize storing information that gets straight to the point. In this way, by adjusting the priority of information according to the user's emotions, more appropriate information can be stored. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the information storage unit may be performed using AI, for example, or without AI. For example, the information storage unit can input user emotion data into a generating AI, which can then adjust the priority of the information to be optimal.

[0116] The information storage unit can analyze the user's past saving history and save the most relevant information when saving information. For example, the information storage unit can prioritize saving relevant information based on information the user has previously saved. The information storage unit can also prioritize saving frequently used information from the user's past saving history. The information storage unit can also analyze the user's past saving history and save the most relevant information. This allows for the saving of more relevant information by analyzing the user's past saving history. Some or all of the above processing in the information storage unit may be performed using AI, for example, or without AI. For example, the information storage unit can input the user's past saving history into AI, which can then save the most relevant information.

[0117] The information storage unit can estimate the user's emotions and adjust the display method of the stored information based on the estimated user emotions. For example, if the user is nervous, the information storage unit can provide a simple and highly visible display method. For example, if the user is nervous, the information storage unit can provide a simple and highly visible display method. The information storage unit can also provide a display method that includes detailed information if the user is relaxed. For example, if the user is relaxed, the information storage unit can provide a display method that includes detailed information. The information storage unit can also provide a display method that gets to the point if the user is in a hurry. For example, if the user is in a hurry, the information storage unit can provide a display method that gets to the point. By adjusting the display method of information according to the user's emotions, more highly visible information can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the information storage unit may be performed using AI, for example, or without AI. For example, the information storage unit can input user emotion data into a generating AI, which can then adjust the optimal way to display the information.

[0118] The information storage unit can prioritize saving highly relevant information by considering the user's geographical location when saving information. For example, the information storage unit can prioritize saving information that is close to the user's current location. The information storage unit can also prioritize saving information that is close to the user's destination. The information storage unit can also prioritize saving information that is along the route from the user's current location to their destination. By considering the user's geographical location, more relevant information can be saved. Some or all of the above processing in the information storage unit may be performed using AI, for example, or without AI. For example, the information storage unit can input the user's geographical location information into AI, and the AI ​​can save the most relevant information.

[0119] The outing suggestion function can estimate the user's emotions and adjust the priority of suggested outing destinations based on those emotions. For example, if the user is feeling stressed, the outing suggestion function will prioritize suggesting places where the user can relax. It can also prioritize suggesting active places if the user is relaxed. Furthermore, if the user is in a hurry, the outing suggestion function can prioritize suggesting nearby destinations. By adjusting the priority of outing destinations according to the user's emotions, it can provide more appropriate destinations. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the outing suggestion unit may be performed using AI, for example, or without AI. For example, the outing suggestion unit can input user emotion data into a generating AI, which can then adjust the priority of the optimal outing destinations.

[0120] The outing suggestion function can analyze the user's past outing history to suggest the most suitable destination. For example, the outing suggestion function can suggest related destinations based on places the user has visited in the past. The outing suggestion function can also suggest similar places based on the user's past outing history. The outing suggestion function can also analyze the user's past outing history to suggest the most relevant destination. By analyzing the user's past outing history, it can provide more relevant destinations. Some or all of the above processing in the outing suggestion function may be performed using AI, for example, or without AI. For example, the outing suggestion function can input a user's past outing history into an AI, which can then suggest the most suitable destination.

[0121] The outing suggestion unit can provide suggestions by considering the user's current lifestyle and areas of interest when suggesting outings. For example, the outing suggestion unit can suggest appropriate destinations based on the user's current lifestyle. For example, the outing suggestion unit can suggest appropriate destinations based on the user's current lifestyle. The outing suggestion unit can also suggest relevant destinations based on the user's areas of interest. For example, the outing suggestion unit can suggest relevant destinations based on the user's areas of interest. The outing suggestion unit can also analyze the user's current lifestyle and areas of interest and suggest the most relevant destination. For example, the outing suggestion unit can analyze the user's current lifestyle and areas of interest and suggest the most relevant destination. By considering the user's current lifestyle and areas of interest, it can provide more relevant destinations. Some or all of the above processing in the outing suggestion unit may be performed using AI, for example, or without AI. For example, the outing suggestion function can input information about the user's current lifestyle and areas of interest into the AI, which can then suggest the most suitable outing destination.

[0122] The outing suggestion section can estimate the user's emotions and adjust the display method of suggested outings based on the estimated emotions. For example, if the user is feeling anxious, the outing suggestion section can provide a simple and highly visible display method. For example, if the user is feeling anxious, the outing suggestion section can provide a simple and highly visible display method. For example, if the user is feeling relaxed, the outing suggestion section can provide a display method that includes detailed information. For example, if the user is feeling relaxed, the outing suggestion section can provide a display method that includes detailed information. For example, if the user is in a hurry, the outing suggestion section can provide a display method that gets straight to the point. For example, if the user is in a hurry, the outing suggestion section can provide a display method that gets straight to the point. By adjusting the display method of outings according to the user's emotions, more highly visible information can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to these examples. Some or all of the above-described processes in the outing suggestion unit may be performed using AI, for example, or without AI. For example, the outing suggestion unit can input user emotion data into a generating AI, which can then adjust the optimal way to display outing destinations.

[0123] The outing suggestion function can prioritize displaying highly relevant destinations by considering the user's geographical location when suggesting outings. For example, the outing suggestion function can prioritize displaying destinations close to the user's current location. For example, the outing suggestion function can prioritize displaying destinations close to the user's destination. For example, the outing suggestion function can prioritize displaying destinations close to the user's destination. For example, the outing suggestion function can prioritize displaying destinations that are on the route from the user's current location to their destination. For example, the outing suggestion function can prioritize displaying destinations that are on the route from the user's current location to their destination. By considering the user's geographical location, it is possible to provide more relevant destinations. Some or all of the above processing in the outing suggestion function may be performed using AI, for example, or without using AI. For example, the outing suggestion function can input the user's geographical location information into the AI, which can then prioritize displaying the most suitable outing destinations.

[0124] The outing suggestion function can analyze the user's social media activity and display relevant destinations when suggesting outings. For example, the outing suggestion function can suggest relevant destinations based on information about places the user has shared on social media. For example, the outing suggestion function can suggest relevant destinations based on information about accounts the user follows on social media. For example, the outing suggestion function can suggest relevant destinations based on information about places the user has checked into on social media. For example, the outing suggestion function can suggest relevant destinations based on information about places the user has checked into on social media. By analyzing the user's social media activity, it is possible to provide more relevant destinations. Some or all of the above processing in the outing suggestion function may be performed using AI, for example, or without AI. For example, the outing suggestion function can input data from the user's social media activity into an AI, which can then display the most suitable destination.

[0125] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0126] The outing support system can also include a health management unit that monitors the user's health status. The health management unit acquires vital data such as the user's heart rate and body temperature, and monitors the user's health status in real time. For example, if the user's heart rate is abnormally high, the health management unit can send a notification prompting them to take a break. It can also provide information on nearby medical facilities if the user's body temperature is high. Furthermore, the health management unit can suggest appropriate routes and destinations based on the user's health status. For example, if the user is tired, the health management unit can suggest a relaxing place that can be reached in a short time. This provides support tailored to the user's health condition, allowing them to go out with peace of mind.

[0127] The outing support system can also include a music provider that estimates the user's emotions and provides music based on those emotions. The music provider estimates the user's emotions and provides relaxing music when the user wants to relax, and energetic music when the user wants to feel energized. For example, if the user is feeling stressed, the music provider can play relaxing music. It can also play cheerful music when the user is relaxed. Furthermore, if the user is in a hurry, the music provider can play fast-paced music. This allows the system to provide music tailored to the user's emotions, supporting a more comfortable outing.

[0128] The outing support system can also include a plan creation unit that creates customized outing plans based on the user's preferences. The plan creation unit analyzes the user's past activity history and preferences to propose the optimal outing plan. For example, it can create a plan that includes similar places based on places the user has visited and their ratings. It can also suggest new places based on the user's preferences and interests. Furthermore, it can create an efficient outing plan that fits the user's schedule. This allows for the provision of customized outing plans tailored to the user's preferences, supporting more fulfilling outings.

[0129] The outing support system can also include a crowd avoidance unit that estimates the user's emotions and makes suggestions considering the crowd situation at the destination based on those estimated emotions. The crowd avoidance unit estimates the user's emotions and, if the user is feeling stressed, suggests routes and destinations that avoid crowds. For example, if the user is feeling stressed, the crowd avoidance unit can suggest less crowded times and places. If the user is relaxed, the crowd avoidance unit can also suggest popular places that are crowded. Furthermore, if the user is in a hurry, the crowd avoidance unit can suggest the shortest route that avoids crowds. In this way, the system can provide crowd avoidance suggestions tailored to the user's emotions, supporting a more comfortable outing.

[0130] The outing support system can also include an activity suggestion unit that proposes appropriate activities based on the age and characteristics of the user's child. For example, the activity suggestion unit can suggest places where parents with infants can prepare formula and change diapers. It can also suggest playgrounds and restaurants with children's menus to parents with toddlers. Furthermore, it can suggest learning facilities and experiential facilities to parents with elementary school children. This allows the system to propose activities tailored to the age and characteristics of the user's child, supporting more fulfilling outings.

[0131] The outing support system can also include a safety information provision unit that estimates the user's emotions and provides safety information about the destination based on those emotions. The safety information provision unit estimates the user's emotions and prioritizes providing safe locations if the user is feeling stressed. For example, if the user is feeling stressed, the safety information provision unit can provide safe locations and evacuation routes. Also, if the user is relaxed, the safety information provision unit can provide detailed safety information. Furthermore, if the user is in a hurry, the safety information provision unit can provide concise safety information. This allows the system to provide safety information tailored to the user's emotions, enabling them to go out with peace of mind.

[0132] The outing support system can also include a search history analysis unit that analyzes the user's past search history and provides customized, optimal information. For example, the search history analysis unit can prioritize displaying locations of restrooms that the user has frequently searched for in the past. It can also suggest similar restaurants based on reviews of restaurants the user has visited in the past. Furthermore, it can suggest the optimal route based on the locations of elevators the user has used in the past. This allows for the provision of more relevant information by analyzing the user's past search history.

[0133] The outing support system can also include a review provision unit that estimates the user's emotions and provides reviews of outing destinations based on those emotions. The review provision unit estimates the user's emotions and prioritizes providing positive reviews if the user is feeling stressed. For example, if the user is feeling stressed, the review provision unit can prioritize displaying positive reviews. Furthermore, if the user is relaxed, the review provision unit can provide detailed reviews. Additionally, if the user is in a hurry, the review provision unit can provide concise reviews. This allows the system to provide reviews tailored to the user's emotions, supporting them in making more appropriate choices for outing destinations.

[0134] The outing support system can also include a geographic information provision unit that prioritizes displaying highly relevant information by considering the user's geographic location. The geographic information provision unit provides optimal information based on the user's current location. For example, the geographic information provision unit can prioritize displaying the locations of toilets near the user's current location. It can also prioritize displaying the locations of milk-making facilities near the user's current location. Furthermore, it can prioritize displaying the locations of elevators near the user's current location. In this way, more relevant information can be provided by considering the user's geographic location.

[0135] The outing support system can also include a social media analysis unit that analyzes the user's social media activity and displays relevant information. The social media analysis unit analyzes the user's social media activity and provides relevant information. For example, it can suggest relevant locations based on information about places the user has shared on social media. It can also suggest relevant locations based on information about accounts the user follows on social media. Furthermore, it can suggest relevant locations based on information about places the user has checked into on social media. This allows for the provision of more relevant information by analyzing the user's social media activity.

[0136] The following briefly describes the processing flow for example form 2.

[0137] Step 1: The information department provides information according to the destination. For example, it provides information such as the location of restrooms, places where you can prepare formula, places where you can change clothes, restaurants that are easy to go to with children, routes that are easy to navigate with large strollers, and the location of elevators. Specifically, it displays the locations of restrooms in shopping malls and parks on a map, and provides text information on places where you can prepare formula in cafes and restaurants. It also displays places where you can change clothes, such as baby rest rooms and changing rooms, on a map, and lists restaurants that have children's menus or restaurants that have baby chairs. Furthermore, it displays routes with few steps or wide sidewalks, and the locations of elevators in stations and shopping malls on a map. Step 2: The route search unit searches for a route from the user's current location to their destination. For example, it searches for a route based on the starting point and destination entered by the user. The user enters the starting point and destination using methods such as address input or specifying a pin on a map, and the unit searches for the optimal route based on the entered information. Step 3: The route suggestion unit proposes a route that takes the elevator's location into account, based on the route search unit's search results. For example, it proposes a route that allows for smooth travel with a stroller, taking the elevator's location into consideration. The elevator's location is displayed on the map, and a route that takes its location into account is proposed. Step 4: The route optimization unit provides the optimal route based on the route proposed by the route proposal unit. For example, it provides the optimal route based on information entered by the user, according to criteria such as time reduction, distance reduction, and consideration of traffic conditions. It provides the optimal route while considering real-time traffic information.

[0138] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0139] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0140] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0141] Each of the multiple elements mentioned above, including the information provision unit, route search unit, route suggestion unit, route optimization unit, review sharing unit, information storage unit, and outing suggestion unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the information provision unit is implemented by the control unit 46A of the smart device 14 and provides information such as the location of toilets and places where milk can be prepared. The route search unit is implemented by the specific processing unit 290 of the data processing unit 12 and searches for a route from the user's current location to the destination. The route suggestion unit is implemented by the specific processing unit 290 of the data processing unit 12 and proposes a route that takes into account the location of elevators. The route optimization unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides the optimal route. The review sharing unit is implemented by the control unit 46A of the smart device 14 and shares reviews and ratings of places visited by the user. The information storage unit is implemented by the control unit 46A of the smart device 14 and stores information about places visited by the user. The outing suggestion function is implemented by the specific processing unit 290 of the data processing device 12, and the AI ​​suggests the next outing destination. The correspondence between each part and the device or control unit is not limited to the example described above and can be modified in various ways.

[0142] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0143] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0144] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0145] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0146] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0147] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0148] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0149] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0150] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0151] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0152] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. 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 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0153] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0154] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0155] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0156] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0157] Each of the multiple elements mentioned above, including the information provision unit, route search unit, route suggestion unit, route optimization unit, review sharing unit, information storage unit, and outing suggestion unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the information provision unit is implemented by the control unit 46A of the smart glasses 214 and provides information such as the location of toilets and places where milk can be made. The route search unit is implemented by the identification processing unit 290 of the data processing unit 12 and searches for a route from the user's current location to the destination. The route suggestion unit is implemented by the identification processing unit 290 of the data processing unit 12 and suggests a route that takes into account the location of elevators. The route optimization unit is implemented by the identification processing unit 290 of the data processing unit 12 and provides the optimal route. The review sharing unit is implemented by the control unit 46A of the smart glasses 214 and shares reviews and ratings of places visited by the user. The information storage unit is implemented by the control unit 46A of the smart glasses 214 and stores information about places visited by the user. The outing suggestion function is implemented by the specific processing unit 290 of the data processing device 12, and the AI ​​suggests the next outing destination. The correspondence between each part and the device or control unit is not limited to the example described above and can be modified in various ways.

[0158] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0159] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0160] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0161] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0162] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0163] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0164] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0165] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0166] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0167] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0168] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0169] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0170] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0171] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0172] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0173] Each of the multiple elements described above, including the information provision unit, route search unit, route suggestion unit, route optimization unit, review sharing unit, information storage unit, and outing suggestion unit, is implemented by at least one of the headset terminal 314 and the data processing unit 12. For example, the information provision unit is implemented by the control unit 46A of the headset terminal 314 and provides information such as the location of toilets and places where milk can be prepared. The route search unit is implemented by the specific processing unit 290 of the data processing unit 12 and searches for a route from the user's current location to the destination. The route suggestion unit is implemented by the specific processing unit 290 of the data processing unit 12 and proposes a route that takes into account the location of elevators. The route optimization unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides the optimal route. The review sharing unit is implemented by the control unit 46A of the headset terminal 314 and shares reviews and ratings of places visited by the user. The information storage unit is implemented by the control unit 46A of the headset terminal 314 and stores information about places visited by the user. The outing suggestion function is implemented by the specific processing unit 290 of the data processing device 12, and the AI ​​suggests the next outing destination. The correspondence between each part and the device or control unit is not limited to the example described above and can be modified in various ways.

[0174] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0175] As shown in Figure 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.

[0176] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0177] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0178] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0179] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0180] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0181] The controlled 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 robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0182] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0183] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0184] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0185] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0186] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0187] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0188] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0189] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0190] Each of the multiple elements mentioned above, including the information provision unit, route search unit, route suggestion unit, route optimization unit, review sharing unit, information storage unit, and outing suggestion unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the information provision unit is implemented by the control unit 46A of the robot 414 and provides information such as the location of toilets and places where milk can be made. The route search unit is implemented by the specific processing unit 290 of the data processing unit 12 and searches for a route from the user's current location to the destination. The route suggestion unit is implemented by the specific processing unit 290 of the data processing unit 12 and proposes a route that takes into account the location of elevators. The route optimization unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides the optimal route. The review sharing unit is implemented by the control unit 46A of the robot 414 and shares reviews and evaluations of places visited by the user. The information storage unit is implemented by the control unit 46A of the robot 414 and stores information about places visited by the user. The outing suggestion function is implemented by the specific processing unit 290 of the data processing device 12, and the AI ​​suggests the next outing destination. The correspondence between each part and the device or control unit is not limited to the example described above and can be modified in various ways.

[0191] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0192] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0193] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0194] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0195] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0196] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0197] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0198] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0199] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0200] 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.

[0201] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0202] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0203] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0204] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0205] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0206] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0207] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0208] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0209] (Note 1) The information department provides information according to the place you want to go, A route search unit that allows the user to search for a route from their current location to their destination, A route proposal unit proposes a route that takes into account the location of the elevator based on the route searched by the aforementioned route search unit, The system includes a route optimization unit that provides an optimal route based on the route proposed by the route proposal unit. A system characterized by the following features. (Note 2) The aforementioned information provision unit, We provide information such as the location of restrooms, places to prepare formula, places to change clothes, child-friendly restaurants, routes that are easy to navigate with large strollers, and the locations of elevators. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned route search unit, Search for a route based on the departure and destination points entered by the user. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned route proposal unit, Route proposal that takes elevator locations into consideration. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned route optimization unit, Provides the optimal route based on the information entered by the user. The system described in Appendix 1, characterized by the features described herein. (Note 6) It features a review sharing section where users can share reviews and ratings of places they have visited. The system described in Appendix 1, characterized by the features described herein. (Note 7) It has an information storage unit that stores information about places the user has visited. The system described in Appendix 1, characterized by the features described herein. (Note 8) Equipped with an AI-powered outing suggestion system that proposes your next destination. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned information provision unit, It estimates the user's emotions and adjusts the priority of the information provided based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned information provision unit, We analyze the user's past search history and customize and provide the most relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned information provision unit, The information provided is filtered based on the user's child's age and characteristics. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned information provision unit, It estimates the user's emotions and adjusts how information is displayed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned information provision unit, The information provided will prioritize displaying the most relevant information, taking into account the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned information provision unit, The information provided includes an analysis of users' social media activity and displays relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned route search unit, It estimates the user's emotions and adjusts the route search priority based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned route search unit, Analyze the user's past travel history and select the optimal route search method. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned route search unit, When searching for a route, the system provides search results that take into account the user's current traffic conditions and weather information. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned route search unit, It estimates the user's emotions and adjusts how route search results are displayed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned route search unit, When searching for a route, the system prioritizes displaying the most relevant routes by considering the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned route search unit, When searching for a route, the system analyzes the user's social media activity and displays relevant routes. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned route proposal unit, It estimates the user's emotions and adjusts the priority of suggested routes based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned route proposal unit, When suggesting a route, the system analyzes the user's past travel history to propose the optimal route. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned route proposal unit, When suggesting routes, the system takes into account the user's current traffic conditions and weather information to provide suggested routes. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned route proposal unit, It estimates the user's emotions and adjusts how suggested routes are displayed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned route proposal unit, When suggesting routes, the system prioritizes displaying the most relevant routes, taking into account the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned route proposal unit, When suggesting routes, the system analyzes the user's social media activity and displays relevant routes. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned route optimization unit, It estimates the user's emotions and adjusts the priority of routes to optimize them based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned route optimization unit, During route optimization, the system analyzes the user's past travel history to provide the optimal route. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned route optimization unit, When optimizing routes, the system provides optimization results that take into account the user's current traffic conditions and weather information. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned route optimization unit, It estimates the user's emotions and adjusts how routes are displayed to optimize them based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned route optimization unit, During route optimization, the system prioritizes displaying the most relevant routes by considering the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned route optimization unit, During route optimization, the system analyzes the user's social media activity and displays relevant routes. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned review sharing section is, It estimates user sentiment and adjusts how reviews are displayed based on that estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 34) The aforementioned review sharing section is, When sharing reviews, the system analyzes the user's past review history to provide the most relevant reviews. The system described in Appendix 1, characterized by the features described herein. (Note 35) The aforementioned review sharing section is, It estimates user sentiment and prioritizes reviews based on the estimated user sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 36) The aforementioned review sharing section is, When sharing reviews, the system prioritizes displaying reviews that are more relevant, taking into account the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 37) The aforementioned information storage unit is It estimates the user's emotions and adjusts the priority of information to store based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 38) The aforementioned information storage unit is When saving information, the system analyzes the user's past saving history to save the most relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 39) The aforementioned information storage unit is It estimates the user's emotions and adjusts how stored information is displayed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 40) The aforementioned information storage unit is When saving information, the system prioritizes saving highly relevant information, taking into account the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 41) The aforementioned outing proposal department, It estimates the user's emotions and adjusts the priority of suggested outing destinations based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 42) The aforementioned outing proposal department, When suggesting outings, the system analyzes the user's past outing history to propose the most suitable destination. The system described in Appendix 1, characterized by the features described herein. (Note 43) The aforementioned outing proposal department, When suggesting outings, the system provides suggestions that take into account the user's current lifestyle and areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 44) The aforementioned outing proposal department, We estimate the user's emotions and adjust how suggested destinations are displayed based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 45) The aforementioned outing proposal department, When suggesting outings, the system prioritizes displaying highly relevant destinations based on the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 46) The aforementioned outing proposal department, When suggesting outings, the system analyzes the user's social media activity and displays relevant destinations. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0210] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The information department provides information according to the place you want to go, A route search unit that allows the user to search for a route from their current location to their destination, A route proposal unit proposes a route that takes into account the location of the elevator based on the route searched by the aforementioned route search unit, The system includes a route optimization unit that provides an optimal route based on the route proposed by the route proposal unit. A system characterized by the following features.

2. The aforementioned information provision unit, We provide information such as the location of restrooms, places to prepare formula, places to change clothes, child-friendly restaurants, routes that are easy to navigate with large strollers, and the locations of elevators. The system according to feature 1.

3. The aforementioned route search unit, Search for a route based on the departure and destination points entered by the user. The system according to feature 1.

4. The aforementioned route proposal unit, Route proposal that takes elevator locations into consideration. The system according to feature 1.

5. The aforementioned route optimization unit, Provides the optimal route based on the information entered by the user. The system according to feature 1.

6. It features a review sharing section where users can share reviews and ratings of places they have visited. The system according to feature 1.

7. It has an information storage unit that stores information about places the user has visited. The system according to feature 1.

8. It features an outing suggestion department where AI proposes destinations for your next outing. The system according to feature 1.

9. The aforementioned information provision unit, It estimates the user's emotions and adjusts the priority of the information provided based on those estimated emotions. The system according to feature 1.

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