System

Abstract

An object of a system according to an embodiment is to provide necessary information to a mountain climber in a timely manner while ensuring safety during mountain climbing.SOLUTION: A system according to an embodiment includes a navigation unit, a notification reception unit, an information transmission unit, and a notification unit. The navigation section navigates a mountain climbing route. The notification reception unit receives a notification from the management building. The information transmission unit transmits the position information of the climber to the management building. The notification unit performs weather notification, break timing notification, and health condition notification.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional techniques have had the problem of making it difficult to provide climbers with the necessary information in a timely manner while ensuring their safety during mountain climbing.

[0005] The system according to the embodiment aims to provide climbers with necessary information in a timely manner while ensuring safety during mountain climbing. [Means for solving the problem]

[0006] The system according to the embodiment includes a navigation unit, a message receiving unit, an information transmitting unit, and a notification unit. The navigation unit navigates the climbing route. The message receiving unit receives messages from the management building. The information transmitting unit transmits the climber's location information to the management building. The notification unit notifies the climber of weather, break times, and health status. [Effects of the Invention]

[0007] The system according to the embodiment can provide climbers with necessary information in a timely manner while ensuring safety during mountain climbing. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) A mountain climbing support system according to an embodiment of the present invention uses guide glasses and a watch to ensure the safety of climbers and provide them with an enjoyable mountain climbing experience. This mountain climbing support system uses a generation AI to navigate the mountain climbing route, preventing them from getting lost or entering dangerous areas. It also has a function to receive reports from the management building and notify climbers of disaster evacuation information, bear sightings, and other information. It also has a function to send information to the management building, including SOS location information. It also provides weather notifications, break timing notifications, and health status notifications (such as pulse rate), supporting climbers' health management. The generation AI also has a function to describe the scenery, flora, and fauna that catches the eye during a climb. For everyday use, it can also navigate while avoiding rain clouds. This allows the mountain climbing support system to ensure the safety of climbers and provide them with an enjoyable mountain climbing experience.

[0029] A mountain climbing support system according to an embodiment includes a navigation unit, a message receiving unit, an information transmitting unit, and a notification unit. The navigation unit navigates a mountain climbing route. For example, the generation AI calculates the optimal mountain climbing route based on the climber's current location and destination and issues specific instructions. The generation AI navigates based on prompts containing instructions the climber wants the generation AI to follow. The message receiving unit receives messages from the management building. For example, the message receiving unit receives disaster evacuation information and bear sighting information in real time and notifies the climber. The information transmitting unit transmits the climber's location information to the management building. For example, if the climber sends an SOS, the message transmitting unit transmits the location information to the management building. The notification unit notifies the climber of weather, break timing, and health status. For example, the generation AI transmits a notification such as "It will start raining soon, so please prepare rain gear" based on weather information. The generation AI also monitors the climber's health status, such as pulse rate, and notifies the climber of appropriate break times. This allows the mountain climbing support system according to an embodiment to ensure the climber's safety and provide an enjoyable mountain climbing experience.

[0030] The navigation unit can learn a climber's past climbing history and suggest the optimal route for the climber. For example, the generation AI stores the climber's past climbing history in a database and suggests the optimal route based on that data. For example, it selects a route that suits the climber's physical strength and experience, taking into account the difficulty of mountains and routes visited in the past. The navigation unit also analyzes data on routes used by climbers in the past, and the generation AI learns these trends. For example, it suggests a more enjoyable route by taking into account the climber's preferred scenery and rest points. The navigation unit also automatically excludes routes that the climber wants to avoid or dangerous areas based on the climber's past climbing history. For example, it suggests avoiding routes where there have been problems in the past. This allows the generation AI to suggest the optimal route based on the climber's past experience.

[0031] The navigation unit monitors the climber's physical condition in real time and can suggest route changes based on their physical condition. For example, the generation AI in the navigation unit monitors the climber's heart rate and oxygen saturation in real time and evaluates their physical condition based on that data. For example, if their physical condition is declining, the system will change to an easier route. The navigation unit also uses a smartwatch or heart rate monitor to monitor the climber's physical condition, and the generation AI analyzes the data. For example, if fatigue accumulates, the system will suggest taking a break. The navigation unit also monitors the climber's physical condition in real time and automatically suggests route changes based on their physical condition. For example, the system will select a route that avoids steep climbs. This allows the system to suggest the optimal route based on the climber's physical condition.

[0032] The notification receiving unit can automatically translate the contents of notifications, making it possible to accommodate foreign climbers as well. The notification receiving unit can automatically translate the contents of notifications from, for example, the management building, making it possible to accommodate foreign climbers as well. For example, disaster evacuation information can be translated into English or Chinese and notified. The notification receiving unit can also translate the contents of notifications in real time, creating a system that notifies foreign climbers in the appropriate language. For example, bear sighting information can be provided in multiple languages. The notification receiving unit can also use an automatic translation function to quickly convey the contents of notifications from the management building to foreign climbers. For example, emergency evacuation instructions can be displayed in multiple languages. This makes it possible to receive notifications that can accommodate foreign climbers as well.

[0033] The notification receiving unit can read out the contents of the notification aloud, making it accessible to visually impaired people. The notification receiving unit is equipped with a function to read out the contents of notifications from the management building, for example, making it accessible to visually impaired people. For example, disaster evacuation information is notified by voice. The notification receiving unit can also build a system that reads out the contents of notifications aloud, allowing visually impaired people to quickly grasp the information. For example, bear sighting information is provided by voice. The notification receiving unit also uses the voice reading function to convey the contents of notifications from the management building to visually impaired people. For example, emergency evacuation instructions are announced by voice. This makes it possible to receive notifications that are accessible to visually impaired people.

[0034] The information transmission unit can simultaneously transmit not only the climber's location information but also health condition and environmental information. For example, the information transmission unit constructs a system that simultaneously transmits not only the climber's location information but also health condition and environmental information. For example, it transmits heart rate and oxygen saturation. The information transmission unit also transmits health condition and environmental information to the management building in real time, enabling a quick response. For example, it transmits environmental information such as temperature and humidity. The information transmission unit also simultaneously transmits health condition and environmental information in addition to location information, allowing the management building to grasp more detailed information. For example, it transmits the climber's body temperature and blood pressure. This allows health condition and environmental information to be transmitted simultaneously in addition to the climber's location information.

[0035] The information transmission unit can add a function that allows climbers to send out an SOS by voice, enabling a response even in situations where they cannot use their hands. The information transmission unit can, for example, add a function that allows climbers to send out an SOS by voice, building a system that allows a response even in situations where they cannot use their hands. For example, using voice recognition technology, an SOS can be sent out simply by saying "help." The information transmission unit can also be equipped with a function to send out an SOS by voice, allowing climbers to notify of an emergency without using their hands. For example, location information can be sent via voice command. The information transmission unit can also develop a system that allows climbers to send out an SOS by voice, enabling a quick response even in situations where they cannot use their hands. For example, the system can explain the emergency situation and notify the management building. This allows an SOS to be sent out by voice even in situations where they cannot use their hands.

[0036] The notification unit uses the generation AI to learn the climber's past health data and can suggest the optimal rest timing for each individual climber. For example, the generation AI stores the climber's past health data in a database and suggests the optimal rest timing based on that data. For example, the notification unit makes suggestions taking into account past fatigue levels and rest patterns. The notification unit also analyzes the climber's past health data and the generation AI learns those trends. For example, it suggests rest times taking into account the times when climbers tend to get tired. The notification unit also automatically suggests the optimal rest timing for each individual climber based on the climber's past health data. For example, it selects rest points based on past data. This makes it possible to suggest the optimal rest timing based on the climber's past health data.

[0037] The notification unit uses the generation AI to monitor the climber's health condition in real time and can immediately notify if an abnormality is detected. For example, the notification unit builds a system in which the generation AI monitors the climber's heart rate and oxygen saturation in real time and immediately notifies if an abnormality is detected. For example, an alert is issued if the heart rate is abnormally high. The notification unit also monitors the climber's health condition in real time and immediately notifies if an abnormality is detected. For example, an alert is displayed if the oxygen saturation level drops. The notification unit also monitors the climber's health condition in real time and automatically notifies if an abnormality is detected. For example, an alert is issued if the body temperature is abnormally high. This allows the system to monitor the climber's health condition in real time and immediately notify if an abnormality is detected.

[0038] The notification unit can use the generation AI to suggest rest spots that suit the climber's preferences. For example, the generation AI learns the climber's past behavioral data and preferences and suggests rest spots. For example, it suggests places with good scenery that the climber likes. The notification unit also has the generation AI automatically select and suggest rest spots based on the climber's preferences. For example, it suggests quiet places or places with shade. The notification unit also has the generation AI analyze the climber's preferences in real time and suggest rest spots. For example, it selects places where the climber can relax. This makes it possible to suggest rest spots that suit the climber's preferences.

[0039] The notification unit can support group climbing by using the generation AI to share real-time health information with other climbers. For example, the notification unit can build a system in which the generation AI shares the health information of other climbers in real time to support group climbing. For example, it can monitor the health status of group members. Furthermore, by sharing health information, the notification unit allows the generation AI to optimize the health status of the entire group. For example, it can suggest times when it is convenient for everyone to take a break. Furthermore, the notification unit can support group climbing by using the generation AI to monitor the health information of other climbers in real time. For example, it can suggest appropriate measures to take for members who are feeling unwell. This allows real-time health information to be shared with other climbers to support group climbing.

[0040] The navigation unit uses the generation AI to learn the climber's past interests and can provide the most suitable explanations for each individual climber, including the scenery, flora, and fauna. For example, the navigation unit stores the climber's past interests in a database and provides the most suitable explanations based on that data. For example, it prioritizes providing information on the flora and fauna that the climber is interested in. The navigation unit also analyzes the climber's past interests and the generation AI learns these tendencies. For example, it provides information on the climber's favorite flowers and birds. The navigation unit also automatically provides the most suitable explanations for each individual climber, based on the climber's past interests and the generation AI. For example, it explains the historical background that the climber is interested in. This makes it possible to provide the most suitable explanations for the scenery, flora, and fauna based on the climber's past interests.

[0041] The navigation unit uses the generation AI to collect new information in real time and provide the latest explanations of the scenery, flora and fauna. For example, the navigation unit builds a system in which the generation AI collects new information in real time and provides the latest explanations. For example, it provides information on newly discovered flora and fauna. The navigation unit also collects new information in real time and the generation AI provides the latest explanations. For example, it updates the explanations based on the latest weather information and environmental data. The navigation unit also uses the generation AI to collect new information in real time and provide the latest explanations to climbers. For example, it provides explanations based on the latest research results and discoveries. This allows the system to collect new information in real time and provide the latest explanations of the scenery, flora and fauna.

[0042] The navigation unit can use the generation AI to provide descriptions of popular scenery, flora and fauna preferentially based on the ratings of other climbers. For example, the navigation unit constructs a system in which the generation AI collects rating data from other climbers and provides popular descriptions preferentially. For example, highly rated descriptions are displayed preferentially. The navigation unit also has the generation AI automatically select and provide popular descriptions based on the ratings of other climbers. For example, highly rated descriptions are provided preferentially. The navigation unit also has the generation AI analyze rating data from other climbers and provide popular descriptions preferentially. For example, the navigation unit recommends highly rated descriptions to climbers. This makes it possible to provide descriptions of popular scenery, flora and fauna preferentially based on the ratings of other climbers.

[0043] The navigation unit uses the generation AI to provide explanations of the scenery, flora and fauna in accordance with the climber's language, making it possible to accommodate foreign climbers as well. For example, the navigation unit creates a system in which the generation AI provides explanations in an appropriate language based on the climber's language setting. For example, explanations may be provided in English or Chinese. The navigation unit also has the generation AI automatically translate and provide explanations in accordance with the climber's language. For example, explanations may be provided in the climber's native language for foreign climbers. The navigation unit also has the generation AI analyze the climber's language setting in real time and provide explanations in an appropriate language. For example, explanations may be provided in the language selected by the climber. This makes it possible to provide explanations of the scenery, flora and fauna in accordance with the climber's language, making it possible to accommodate foreign climbers as well.

[0044] The navigation unit can use the generation AI to learn past weather data and suggest the optimal route. For example, the generation AI stores past weather data in a database and suggests the optimal route based on that data. For example, the navigation unit selects a route taking into account the past movement of rain clouds. The navigation unit also analyzes past weather data and the generation AI learns the trends. For example, it avoids routes that are prone to rain during certain seasons or times of the day. The navigation unit also uses the generation AI to automatically suggest the optimal route based on past weather data. For example, it selects a route that avoids rain clouds based on past data. This makes it possible to suggest the optimal route based on past weather data.

[0045] The navigation unit uses the generation AI to collect real-time weather information and can instantly suggest route changes. For example, the navigation unit builds a system in which the generation AI collects real-time weather information and instantly suggests route changes. For example, it will suggest an alternative route if rain clouds are approaching. The navigation unit also uses the generation AI to instantly suggest route changes based on real-time weather information. For example, it will suggest the optimal evacuation route if it starts to rain. The navigation unit also uses the generation AI to collect real-time weather information and instantly suggest route changes to climbers. For example, it will select a safe route if a thunderstorm is expected. This allows for instant route changes to be suggested based on real-time weather information.

[0046] The navigation unit can use the generation AI to share real-time location information of other climbers and support group route selection. For example, the navigation unit builds a system in which the generation AI shares the location information of other climbers in real time to support group route selection. For example, it can suggest a route that makes it easy for all members of the group to meet up. The navigation unit also shares the location information of other climbers, allowing the generation AI to optimize the route for the entire group. For example, it can select a route that allows everyone to travel safely. The navigation unit also monitors the location information of other climbers in real time to support group route selection. For example, it can suggest a route to quickly find a lost member. This allows the generation AI to share the real-time location information of other climbers and support group route selection.

[0047] The navigation unit can use the generation AI to incorporate tourist spots into the route based on the climber's preferences. For example, the generation AI learns the climber's past behavioral data and preferences and incorporates tourist spots into the route. For example, if the climber likes flowers, the generation AI will suggest a route with many flowers in bloom. The navigation unit also automatically selects tourist spots based on the climber's preferences and incorporates them into the route. For example, it will suggest a route that includes historical buildings and points where beautiful scenery can be seen. The navigation unit also analyzes the climber's preferences in real time using the generation AI to incorporate tourist spots into the route. For example, if the climber enjoys photography, it will suggest a route that includes photogenic spots. This makes it possible to incorporate tourist spots into the route based on the climber's preferences.

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

[0049] The navigation unit can learn a climber's past climbing history and suggest the optimal route for them. For example, the generation AI stores the climber's past climbing history in a database and suggests the optimal route based on that data. It selects a route that suits the climber's physical strength and experience, taking into account the difficulty of mountains and routes previously visited. The navigation unit also analyzes data on routes previously used by climbers, allowing the generation AI to learn these trends. It can also suggest more enjoyable routes by taking into account the climber's preferred scenery and rest points. Furthermore, the navigation unit automatically excludes routes and dangerous areas that the climber wants to avoid based on the climber's past climbing history. It can also suggest routes that avoid routes where there have been problems in the past. This allows the generation AI to suggest the optimal route based on the climber's past experience.

[0050] The navigation unit monitors the climber's physical condition in real time and can suggest route changes based on their physical strength. For example, the generation AI monitors the climber's heart rate and oxygen saturation in real time and evaluates their physical condition based on that data. If their physical strength is declining, it can change to an easier route. The navigation unit also uses a smartwatch or heart rate monitor to monitor the climber's physical condition, and the generation AI analyzes the data. It can also suggest taking a break if fatigue accumulates. Furthermore, the navigation unit's generation AI monitors the climber's physical condition in real time and automatically suggests route changes based on their physical strength. It can also select routes that avoid steep climbs. This allows it to suggest the optimal route based on the climber's physical condition.

[0051] The notification receiving unit can automatically translate the contents of notifications, making it possible to accommodate foreign climbers as well. For example, it can automatically translate the contents of notifications from the management building, making it possible to accommodate foreign climbers as well. Disaster evacuation information can be translated into English or Chinese and notified. The notification receiving unit can also translate the contents of notifications in real time, creating a system that notifies foreign climbers in the appropriate language. It can also provide bear sighting information in multiple languages. Furthermore, the notification receiving unit uses an automatic translation function to quickly convey the contents of notifications from the management building to foreign climbers. Emergency evacuation instructions can also be displayed in multiple languages. This makes it possible to receive notifications that can accommodate foreign climbers as well.

[0052] The notification receiving unit can read out the contents of the notification aloud, making it accessible to visually impaired people. For example, it can be equipped with a function that reads out the contents of notifications from the management building aloud, making it accessible to visually impaired people. Disaster evacuation information can be notified by voice. The notification receiving unit can also be built into a system that reads out the contents of notifications aloud, allowing visually impaired people to quickly grasp the information. It can also provide information on bear sightings by voice. Furthermore, the notification receiving unit uses the voice reading function to convey the contents of notifications from the management building to visually impaired people. Emergency evacuation instructions can also be announced by voice. This makes it possible to receive notifications that are accessible to visually impaired people.

[0053] The information transmission unit can simultaneously transmit not only the climber's location information but also health condition and environmental information. For example, a system can be constructed that simultaneously transmits not only the climber's location information but also health condition and environmental information. Heart rate and oxygen saturation can be transmitted. The information transmission unit also transmits health condition and environmental information to the management building in real time, enabling a quick response. Environmental information such as temperature and humidity can also be transmitted. Furthermore, by simultaneously transmitting health condition and environmental information in addition to location information, the information transmission unit allows the management building to obtain more detailed information. The climber's body temperature and blood pressure can also be transmitted. This makes it possible to simultaneously transmit health condition and environmental information in addition to the climber's location information.

[0054] The information transmission unit can add a function that allows climbers to send an SOS by voice, enabling them to respond even in situations where they cannot use their hands. For example, we will build a system that allows climbers to send an SOS by voice, enabling them to respond even in situations where they cannot use their hands. Using voice recognition technology, an SOS can be sent simply by saying "help." The information transmission unit will also be equipped with a function to send an SOS by voice, allowing climbers to notify of an emergency without using their hands. It will also be possible to send location information via voice command. Furthermore, by allowing climbers to send an SOS by voice, we will develop a system that allows for quick response even in situations where they cannot use their hands. It will also be possible to explain the emergency situation and notify the management building. This will allow climbers to send an SOS by voice even in situations where they cannot use their hands.

[0055] The notification unit uses the generation AI to learn the climber's past health data and can suggest the optimal rest timing for each individual climber. For example, the generation AI stores the climber's past health data in a database and suggests the optimal rest timing based on that data. Suggestions can be made taking into account past fatigue levels and rest patterns. The notification unit also analyzes the climber's past health data and the generation AI learns those trends. It is also possible to suggest rest times taking into account the times when climbers tend to get tired. Furthermore, the notification unit automatically suggests the optimal rest timing for each individual climber based on the climber's past health data using the generation AI. It is also possible to select rest points based on past data. This makes it possible to suggest the optimal rest timing based on the climber's past health data.

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

[0057] Step 1: The navigation unit navigates the climbing route. For example, the generation AI calculates the optimal climbing route based on the climber's current location and destination, and issues specific instructions. The generation AI navigates based on prompts that include instructions on what the climber wants the generation AI to do. Step 2: The notification receiving unit receives notifications from the management building. For example, disaster evacuation information and bear sighting information are received in real time and notified to climbers. Step 3: The information transmission unit transmits the climber's location information to the management building. For example, if the climber sends out an SOS, the information transmission unit transmits the location information to the management building. Step 4: The notification unit notifies the user of the weather, when to take a break, and their health condition. For example, the AI ​​generation unit may notify them of the weather, such as "It will soon start raining, so please prepare your rain gear," based on weather information. The AI ​​generation unit may also monitor the climber's health condition, such as their pulse rate, and notify them of appropriate times to take a break.

[0058] (Example 2) A mountain climbing support system according to an embodiment of the present invention uses guide glasses and a watch to ensure the safety of climbers and provide them with an enjoyable mountain climbing experience. This mountain climbing support system uses a generation AI to navigate the mountain climbing route, preventing them from getting lost or entering dangerous areas. It also has a function to receive reports from the management building and notify climbers of disaster evacuation information, bear sightings, and other information. It also has a function to send information to the management building, including SOS location information. It also provides weather notifications, break timing notifications, and health status notifications (such as pulse rate), supporting climbers' health management. The generation AI also has a function to describe the scenery, flora, and fauna that catches the eye during a climb. For everyday use, it can also navigate while avoiding rain clouds. This allows the mountain climbing support system to ensure the safety of climbers and provide them with an enjoyable mountain climbing experience.

[0059] A mountain climbing support system according to an embodiment includes a navigation unit, a message receiving unit, an information transmitting unit, and a notification unit. The navigation unit navigates a mountain climbing route. For example, the generation AI calculates the optimal mountain climbing route based on the climber's current location and destination and issues specific instructions. The generation AI navigates based on prompts containing instructions the climber wants the generation AI to follow. The message receiving unit receives messages from the management building. For example, the message receiving unit receives disaster evacuation information and bear sighting information in real time and notifies the climber. The information transmitting unit transmits the climber's location information to the management building. For example, if the climber sends an SOS, the message transmitting unit transmits the location information to the management building. The notification unit notifies the climber of weather, break timing, and health status. For example, the generation AI transmits a notification such as "It will start raining soon, so please prepare rain gear" based on weather information. The generation AI also monitors the climber's health status, such as pulse rate, and notifies the climber of appropriate break times. This allows the mountain climbing support system according to an embodiment to ensure the climber's safety and provide an enjoyable mountain climbing experience.

[0060] The navigation unit can learn a climber's past climbing history and suggest the optimal route for the climber. For example, the generation AI stores the climber's past climbing history in a database and suggests the optimal route based on that data. For example, it selects a route that suits the climber's physical strength and experience, taking into account the difficulty of mountains and routes visited in the past. The navigation unit also analyzes data on routes used by climbers in the past, and the generation AI learns these trends. For example, it suggests a more enjoyable route by taking into account the climber's preferred scenery and rest points. The navigation unit also automatically excludes routes that the climber wants to avoid or dangerous areas based on the climber's past climbing history. For example, it suggests avoiding routes where there have been problems in the past. This allows the generation AI to suggest the optimal route based on the climber's past experience.

[0061] The navigation unit monitors the climber's physical condition in real time and can suggest route changes based on their physical condition. For example, the generation AI in the navigation unit monitors the climber's heart rate and oxygen saturation in real time and evaluates their physical condition based on that data. For example, if their physical condition is declining, the system will change to an easier route. The navigation unit also uses a smartwatch or heart rate monitor to monitor the climber's physical condition, and the generation AI analyzes the data. For example, if fatigue accumulates, the system will suggest taking a break. The navigation unit also monitors the climber's physical condition in real time and automatically suggests route changes based on their physical condition. For example, the system will select a route that avoids steep climbs. This allows the system to suggest the optimal route based on the climber's physical condition.

[0062] The navigation unit can use the emotion estimation function to analyze the climber's emotional state and suggest routes to reduce stress. For example, the generation AI in the navigation unit analyzes the climber's facial expressions and voice to estimate their emotional state in real time. For example, if stress is high, it will suggest a route with a good view. The navigation unit also uses the emotion estimation function to analyze the climber's emotional state and select a relaxing route. For example, it will suggest a route that passes through a quiet forest. The navigation unit also monitors the climber's emotional state and automatically suggests routes to reduce stress. For example, it will determine whether the climber is enjoying themselves and select a route that will maximize their enjoyment. This makes it possible to suggest routes that reduce stress according to the climber's emotional state.

[0063] The notification receiving unit can automatically translate the contents of notifications, making it possible to accommodate foreign climbers as well. The notification receiving unit can automatically translate the contents of notifications from, for example, the management building, making it possible to accommodate foreign climbers as well. For example, disaster evacuation information can be translated into English or Chinese and notified. The notification receiving unit can also translate the contents of notifications in real time, creating a system that notifies foreign climbers in the appropriate language. For example, bear sighting information can be provided in multiple languages. The notification receiving unit can also use an automatic translation function to quickly convey the contents of notifications from the management building to foreign climbers. For example, emergency evacuation instructions can be displayed in multiple languages. This makes it possible to receive notifications that can accommodate foreign climbers as well.

[0064] The notification receiving unit can read out the contents of the notification aloud, making it accessible to visually impaired people. The notification receiving unit is equipped with a function to read out the contents of notifications from the management building, for example, making it accessible to visually impaired people. For example, disaster evacuation information is notified by voice. The notification receiving unit can also build a system that reads out the contents of notifications aloud, allowing visually impaired people to quickly grasp the information. For example, bear sighting information is provided by voice. The notification receiving unit also uses the voice reading function to convey the contents of notifications from the management building to visually impaired people. For example, emergency evacuation instructions are announced by voice. This makes it possible to receive notifications that are accessible to visually impaired people.

[0065] The report receiving unit can use the emotion estimation function to analyze the urgency of the report content and prioritize the notifications. The report receiving unit, for example, uses the emotion estimation function to build a system that analyzes the urgency of the report content and prioritizes the notifications. For example, reports with high urgency are notified first. The report receiving unit also performs emotion analysis of the report content, evaluates the urgency, and notifies the report. For example, it analyzes the urgency of disaster evacuation information or bear sighting information and prioritizes the notifications. The report receiving unit also uses the emotion estimation function to analyze the urgency of the report content in real time and prioritize the notifications. For example, it immediately notifies reports with high urgency. This allows the reports to be prioritized according to the urgency of the report content.

[0066] The information transmission unit can simultaneously transmit not only the climber's location information but also health condition and environmental information. For example, the information transmission unit constructs a system that simultaneously transmits not only the climber's location information but also health condition and environmental information. For example, it transmits heart rate and oxygen saturation. The information transmission unit also transmits health condition and environmental information to the management building in real time, enabling a quick response. For example, it transmits environmental information such as temperature and humidity. The information transmission unit also simultaneously transmits health condition and environmental information in addition to location information, allowing the management building to grasp more detailed information. For example, it transmits the climber's body temperature and blood pressure. This allows health condition and environmental information to be transmitted simultaneously in addition to the climber's location information.

[0067] The information transmission unit can add a function that allows climbers to send out an SOS by voice, enabling a response even in situations where they cannot use their hands. The information transmission unit can, for example, add a function that allows climbers to send out an SOS by voice, building a system that allows a response even in situations where they cannot use their hands. For example, using voice recognition technology, an SOS can be sent out simply by saying "help." The information transmission unit can also be equipped with a function to send out an SOS by voice, allowing climbers to notify of an emergency without using their hands. For example, location information can be sent via voice command. The information transmission unit can also develop a system that allows climbers to send out an SOS by voice, enabling a quick response even in situations where they cannot use their hands. For example, the system can explain the emergency situation and notify the management building. This allows an SOS to be sent out by voice even in situations where they cannot use their hands.

[0068] The information transmission unit can use the emotion estimation function to analyze the emotional state of the climber, determine the level of urgency, and notify the management building. The information transmission unit, for example, uses the emotion estimation function to build a system that analyzes the emotional state of the climber, determines the level of urgency, and notifies the management building. For example, the level of urgency is determined by evaluating the degree of stress or fear. The information transmission unit also analyzes the emotional state of the climber in real time, evaluates the level of urgency, and notifies the management building. For example, if the emotion score is high, the information transmission unit immediately notifies. The information transmission unit also uses the emotion estimation function to monitor the emotional state of the climber, automatically determine the level of urgency, and notify the management building. For example, the information transmission unit sets a priority for notifications according to the emotional state. This makes it possible to determine the level of urgency based on the emotional state of the climber and notify the management building.

[0069] The notification unit uses the generation AI to learn the climber's past health data and can suggest the optimal rest timing for each individual climber. For example, the generation AI stores the climber's past health data in a database and suggests the optimal rest timing based on that data. For example, the notification unit makes suggestions taking into account past fatigue levels and rest patterns. The notification unit also analyzes the climber's past health data and the generation AI learns those trends. For example, it suggests rest times taking into account the times when climbers tend to get tired. The notification unit also automatically suggests the optimal rest timing for each individual climber based on the climber's past health data. For example, it selects rest points based on past data. This makes it possible to suggest the optimal rest timing based on the climber's past health data.

[0070] The notification unit uses the generation AI to monitor the climber's health condition in real time and can immediately notify if an abnormality is detected. For example, the notification unit builds a system in which the generation AI monitors the climber's heart rate and oxygen saturation in real time and immediately notifies if an abnormality is detected. For example, an alert is issued if the heart rate is abnormally high. The notification unit also monitors the climber's health condition in real time and immediately notifies if an abnormality is detected. For example, an alert is displayed if the oxygen saturation level drops. The notification unit also monitors the climber's health condition in real time and automatically notifies if an abnormality is detected. For example, an alert is issued if the body temperature is abnormally high. This allows the system to monitor the climber's health condition in real time and immediately notify if an abnormality is detected.

[0071] The notification unit can use the emotion estimation function to analyze the emotional state of the climber and suggest timing for taking a break to reduce stress. For example, the notification unit can use the emotion estimation function to analyze the emotional state of the climber in real time and suggest timing for taking a break to reduce stress. For example, if stress is high, the notification unit can suggest taking an earlier break. The notification unit can also analyze the emotional state of the climber and automatically suggest timing for taking a break to reduce stress. For example, the notification unit can suggest taking a break in a relaxing place. The notification unit can also use the emotion estimation function to monitor the emotional state of the climber and suggest timing for taking a break to reduce stress. For example, the notification unit can select a rest point depending on the emotional state. This makes it possible to suggest timing for taking a break to reduce stress based on the emotional state of the climber.

[0072] The notification unit can use the generation AI to suggest rest spots that suit the climber's preferences. For example, the generation AI learns the climber's past behavioral data and preferences and suggests rest spots. For example, it suggests places with good scenery that the climber likes. The notification unit also has the generation AI automatically select and suggest rest spots based on the climber's preferences. For example, it suggests quiet places or places with shade. The notification unit also has the generation AI analyze the climber's preferences in real time and suggest rest spots. For example, it selects places where the climber can relax. This makes it possible to suggest rest spots that suit the climber's preferences.

[0073] The notification unit can support group climbing by using the generation AI to share real-time health information with other climbers. For example, the notification unit can build a system in which the generation AI shares the health information of other climbers in real time to support group climbing. For example, it can monitor the health status of group members. Furthermore, by sharing health information, the notification unit allows the generation AI to optimize the health status of the entire group. For example, it can suggest times when it is convenient for everyone to take a break. Furthermore, the notification unit can support group climbing by using the generation AI to monitor the health information of other climbers in real time. For example, it can suggest appropriate measures to take for members who are feeling unwell. This allows real-time health information to be shared with other climbers to support group climbing.

[0074] The notification unit can use the emotion estimation function to suggest notification content that will help the climber relax. For example, the notification unit uses the emotion estimation function to analyze the climber's emotional state in real time and suggest notification content that will help the climber relax. For example, relaxing music can be played. The notification unit can also analyze the climber's emotional state and automatically suggest notification content that will help the climber relax. For example, a message encouraging deep breathing can be displayed. The notification unit can also use the emotion estimation function to monitor the climber's emotional state and suggest notification content that will help the climber relax. For example, suggesting a break at a relaxing place. In this way, notification content that will help the climber relax can be suggested.

[0075] The navigation unit uses the generation AI to learn the climber's past interests and can provide the most suitable explanations for each individual climber, including the scenery, flora, and fauna. For example, the navigation unit stores the climber's past interests in a database and provides the most suitable explanations based on that data. For example, it prioritizes providing information on the flora and fauna that the climber is interested in. The navigation unit also analyzes the climber's past interests and the generation AI learns these tendencies. For example, it provides information on the climber's favorite flowers and birds. The navigation unit also automatically provides the most suitable explanations for each individual climber, based on the climber's past interests and the generation AI. For example, it explains the historical background that the climber is interested in. This makes it possible to provide the most suitable explanations for the scenery, flora, and fauna based on the climber's past interests.

[0076] The navigation unit uses the generation AI to collect new information in real time and provide the latest explanations of the scenery, flora and fauna. For example, the navigation unit builds a system in which the generation AI collects new information in real time and provides the latest explanations. For example, it provides information on newly discovered flora and fauna. The navigation unit also collects new information in real time and the generation AI provides the latest explanations. For example, it updates the explanations based on the latest weather information and environmental data. The navigation unit also uses the generation AI to collect new information in real time and provide the latest explanations to climbers. For example, it provides explanations based on the latest research results and discoveries. This allows the system to collect new information in real time and provide the latest explanations of the scenery, flora and fauna.

[0077] The navigation unit can use the emotion estimation function to analyze the emotional state of the climber and provide interesting explanations of the scenery, flora and fauna. For example, the navigation unit can use the emotion estimation function to analyze the emotional state of the climber in real time and provide interesting explanations. For example, if the climber is excited, a detailed explanation is provided. The navigation unit can also analyze the emotional state of the climber and automatically provide interesting explanations. For example, if the climber is relaxed, a concise explanation is provided. The navigation unit can also use the emotion estimation function to monitor the emotional state of the climber and provide interesting explanations. For example, the content and tone of the explanation can be adjusted depending on the emotional state. This makes it possible to provide interesting explanations of the scenery, flora and fauna based on the emotional state of the climber.

[0078] The navigation unit can use the generation AI to provide descriptions of popular scenery, flora and fauna preferentially based on the ratings of other climbers. For example, the navigation unit constructs a system in which the generation AI collects rating data from other climbers and provides popular descriptions preferentially. For example, highly rated descriptions are displayed preferentially. The navigation unit also has the generation AI automatically select and provide popular descriptions based on the ratings of other climbers. For example, highly rated descriptions are provided preferentially. The navigation unit also has the generation AI analyze rating data from other climbers and provide popular descriptions preferentially. For example, the navigation unit recommends highly rated descriptions to climbers. This makes it possible to provide descriptions of popular scenery, flora and fauna preferentially based on the ratings of other climbers.

[0079] The navigation unit uses the generation AI to provide explanations of the scenery, flora and fauna in accordance with the climber's language, making it possible to accommodate foreign climbers as well. For example, the navigation unit creates a system in which the generation AI provides explanations in an appropriate language based on the climber's language setting. For example, explanations may be provided in English or Chinese. The navigation unit also has the generation AI automatically translate and provide explanations in accordance with the climber's language. For example, explanations may be provided in the climber's native language for foreign climbers. The navigation unit also has the generation AI analyze the climber's language setting in real time and provide explanations in an appropriate language. For example, explanations may be provided in the language selected by the climber. This makes it possible to provide explanations of the scenery, flora and fauna in accordance with the climber's language, making it possible to accommodate foreign climbers as well.

[0080] The navigation unit can use the emotion estimation function to determine whether the climber is enjoying themselves and provide explanations of the scenery, flora, and fauna to maximize their enjoyment. The navigation unit, for example, uses the emotion estimation function to analyze the climber's emotional state in real time and provide explanations to maximize their enjoyment. For example, if the climber is enjoying themselves, it provides a detailed explanation. The navigation unit also analyzes the climber's emotional state and automatically provides explanations to maximize their enjoyment. For example, if the climber is relaxed, it provides a concise explanation. The navigation unit also uses the emotion estimation function to monitor the climber's emotional state and provide explanations to maximize their enjoyment. For example, it adjusts the content and tone of the explanation depending on the climber's emotional state. This makes it possible to determine whether the climber is enjoying themselves and provide explanations of the scenery, flora, and fauna to maximize their enjoyment.

[0081] The navigation unit can use the generation AI to learn past weather data and suggest the optimal route. For example, the generation AI stores past weather data in a database and suggests the optimal route based on that data. For example, the navigation unit selects a route taking into account the past movement of rain clouds. The navigation unit also analyzes past weather data and the generation AI learns the trends. For example, it avoids routes that are prone to rain during certain seasons or times of the day. The navigation unit also uses the generation AI to automatically suggest the optimal route based on past weather data. For example, it selects a route that avoids rain clouds based on past data. This makes it possible to suggest the optimal route based on past weather data.

[0082] The navigation unit uses the generation AI to collect real-time weather information and can instantly suggest route changes. For example, the navigation unit builds a system in which the generation AI collects real-time weather information and instantly suggests route changes. For example, it will suggest an alternative route if rain clouds are approaching. The navigation unit also uses the generation AI to instantly suggest route changes based on real-time weather information. For example, it will suggest the optimal evacuation route if it starts to rain. The navigation unit also uses the generation AI to collect real-time weather information and instantly suggest route changes to climbers. For example, it will select a safe route if a thunderstorm is expected. This allows for instant route changes to be suggested based on real-time weather information.

[0083] The navigation unit can use the emotion estimation function to analyze the emotional state of the climber and suggest a route to reduce stress. For example, the navigation unit uses the emotion estimation function to analyze the emotional state of the climber in real time and suggest a route to reduce stress. For example, if stress is high, the navigation unit suggests a route with a good view. The navigation unit also analyzes the emotional state of the climber and automatically suggests a route to reduce stress. For example, it selects a route that allows relaxation. The navigation unit also uses the emotion estimation function to monitor the emotional state of the climber and suggest a route to reduce stress. For example, it adjusts the route according to the emotional state. In this way, it is possible to suggest a route to reduce stress based on the emotional state of the climber.

[0084] The navigation unit can use the generation AI to share real-time location information of other climbers and support group route selection. For example, the navigation unit builds a system in which the generation AI shares the location information of other climbers in real time to support group route selection. For example, it can suggest a route that makes it easy for all members of the group to meet up. The navigation unit also shares the location information of other climbers, allowing the generation AI to optimize the route for the entire group. For example, it can select a route that allows everyone to travel safely. The navigation unit also monitors the location information of other climbers in real time to support group route selection. For example, it can suggest a route to quickly find a lost member. This allows the generation AI to share the real-time location information of other climbers and support group route selection.

[0085] The navigation unit can use the generation AI to incorporate tourist spots into the route based on the climber's preferences. For example, the generation AI learns the climber's past behavioral data and preferences and incorporates tourist spots into the route. For example, if the climber likes flowers, the generation AI will suggest a route with many flowers in bloom. The navigation unit also automatically selects tourist spots based on the climber's preferences and incorporates them into the route. For example, it will suggest a route that includes historical buildings and points where beautiful scenery can be seen. The navigation unit also analyzes the climber's preferences in real time using the generation AI to incorporate tourist spots into the route. For example, if the climber enjoys photography, it will suggest a route that includes photogenic spots. This makes it possible to incorporate tourist spots into the route based on the climber's preferences.

[0086] The navigation unit can use the emotion estimation function to determine whether the climber is enjoying themselves and suggest a route that will maximize their enjoyment. For example, the generation AI in the navigation unit analyzes the climber's emotional state in real time and suggests a route that will maximize their enjoyment. For example, if the climber is smiling, the navigation unit selects a route that includes even more enjoyable spots. The navigation unit also uses the emotion estimation function to determine whether the climber is enjoying themselves and suggest a route that will maximize their enjoyment. For example, if the climber is excited, the navigation unit suggests a route with an adventurous element. The navigation unit also monitors the climber's emotional state and automatically suggests a route that will maximize their enjoyment. For example, if the climber is relaxed, the navigation unit selects a quiet route. This allows the navigation unit to determine whether the climber is enjoying themselves and suggest a route that will maximize their enjoyment.

[0087] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0088] The navigation unit can learn a climber's past climbing history and suggest the optimal route for them. For example, the generation AI stores the climber's past climbing history in a database and suggests the optimal route based on that data. It selects a route that suits the climber's physical strength and experience, taking into account the difficulty of mountains and routes previously visited. The navigation unit also analyzes data on routes previously used by climbers, allowing the generation AI to learn these trends. It can also suggest more enjoyable routes by taking into account the climber's preferred scenery and rest points. Furthermore, the navigation unit automatically excludes routes and dangerous areas that the climber wants to avoid based on the climber's past climbing history. It can also suggest routes that avoid routes where there have been problems in the past. This allows the generation AI to suggest the optimal route based on the climber's past experience.

[0089] The navigation unit monitors the climber's physical condition in real time and can suggest route changes based on their physical strength. For example, the generation AI monitors the climber's heart rate and oxygen saturation in real time and evaluates their physical condition based on that data. If their physical strength is declining, it can change to an easier route. The navigation unit also uses a smartwatch or heart rate monitor to monitor the climber's physical condition, and the generation AI analyzes the data. It can also suggest taking a break if fatigue accumulates. Furthermore, the navigation unit's generation AI monitors the climber's physical condition in real time and automatically suggests route changes based on their physical strength. It can also select routes that avoid steep climbs. This allows it to suggest the optimal route based on the climber's physical condition.

[0090] The navigation unit can use the emotion estimation function to analyze the climber's emotional state and suggest routes to reduce stress. For example, the generation AI analyzes the climber's facial expressions and voice to estimate their emotional state in real time. If stress is high, it can suggest a route with a good view. The navigation unit also uses the emotion estimation function to analyze the climber's emotional state and select a relaxing route. It can also suggest a route that passes through a quiet forest. Furthermore, the navigation unit's generation AI monitors the climber's emotional state and automatically suggests routes to reduce stress. It can also determine whether the climber is enjoying themselves and select a route that maximizes enjoyment. This makes it possible to suggest routes that reduce stress according to the climber's emotional state.

[0091] The notification receiving unit can automatically translate the contents of notifications, making it possible to accommodate foreign climbers as well. For example, it can automatically translate the contents of notifications from the management building, making it possible to accommodate foreign climbers as well. Disaster evacuation information can be translated into English or Chinese and notified. The notification receiving unit can also translate the contents of notifications in real time, creating a system that notifies foreign climbers in the appropriate language. It can also provide bear sighting information in multiple languages. Furthermore, the notification receiving unit uses an automatic translation function to quickly convey the contents of notifications from the management building to foreign climbers. Emergency evacuation instructions can also be displayed in multiple languages. This makes it possible to receive notifications that can accommodate foreign climbers as well.

[0092] The notification receiving unit can read out the contents of the notification aloud, making it accessible to visually impaired people. For example, it can be equipped with a function that reads out the contents of notifications from the management building aloud, making it accessible to visually impaired people. Disaster evacuation information can be notified by voice. The notification receiving unit can also be built into a system that reads out the contents of notifications aloud, allowing visually impaired people to quickly grasp the information. It can also provide information on bear sightings by voice. Furthermore, the notification receiving unit uses the voice reading function to convey the contents of notifications from the management building to visually impaired people. Emergency evacuation instructions can also be announced by voice. This makes it possible to receive notifications that are accessible to visually impaired people.

[0093] The report receiving unit can use the emotion estimation function to analyze the urgency of the report content and prioritize notifications. For example, a system can be constructed that uses the emotion estimation function to analyze the urgency of the report content and prioritize notifications. Highly urgent reports can be given priority in notification. The report receiving unit also performs emotion analysis of the report content, evaluates the urgency, and notifies the report. It is also possible to analyze the urgency of disaster evacuation information and bear sighting information and prioritize them. Furthermore, the report receiving unit uses the emotion estimation function to analyze the urgency of the report content in real time and prioritize notifications. Highly urgent reports can also be notified immediately. This allows reports to be prioritized according to the urgency of the report content.

[0094] The information transmission unit can simultaneously transmit not only the climber's location information but also health condition and environmental information. For example, a system can be constructed that simultaneously transmits not only the climber's location information but also health condition and environmental information. Heart rate and oxygen saturation can be transmitted. The information transmission unit also transmits health condition and environmental information to the management building in real time, enabling a quick response. Environmental information such as temperature and humidity can also be transmitted. Furthermore, by simultaneously transmitting health condition and environmental information in addition to location information, the information transmission unit allows the management building to obtain more detailed information. The climber's body temperature and blood pressure can also be transmitted. This makes it possible to simultaneously transmit health condition and environmental information in addition to the climber's location information.

[0095] The information transmission unit can add a function that allows climbers to send an SOS by voice, enabling them to respond even in situations where they cannot use their hands. For example, we will build a system that allows climbers to send an SOS by voice, enabling them to respond even in situations where they cannot use their hands. Using voice recognition technology, an SOS can be sent simply by saying "help." The information transmission unit will also be equipped with a function to send an SOS by voice, allowing climbers to notify of an emergency without using their hands. It will also be possible to send location information via voice command. Furthermore, by allowing climbers to send an SOS by voice, we will develop a system that allows for quick response even in situations where they cannot use their hands. It will also be possible to explain the emergency situation and notify the management building. This will allow climbers to send an SOS by voice even in situations where they cannot use their hands.

[0096] The information transmission unit can use the emotion estimation function to analyze the emotional state of the climber, determine the level of urgency, and notify the management building. For example, a system can be constructed that uses the emotion estimation function to analyze the emotional state of the climber, determine the level of urgency, and notify the management building. The level of urgency can be determined by evaluating the level of stress and fear. The information transmission unit can also analyze the emotional state of the climber in real time, evaluate the level of urgency, and notify the management building. It is also possible to notify immediately if the emotion score is high. Furthermore, the information transmission unit can use the emotion estimation function to monitor the emotional state of the climber, automatically determine the level of urgency, and notify the management building. It is also possible to set the priority of notifications according to the emotional state. This makes it possible to determine the level of urgency based on the emotional state of the climber and notify the management building.

[0097] The notification unit uses the generation AI to learn the climber's past health data and can suggest the optimal rest timing for each individual climber. For example, the generation AI stores the climber's past health data in a database and suggests the optimal rest timing based on that data. Suggestions can be made taking into account past fatigue levels and rest patterns. The notification unit also analyzes the climber's past health data and the generation AI learns those trends. It is also possible to suggest rest times taking into account the times when climbers tend to get tired. Furthermore, the notification unit automatically suggests the optimal rest timing for each individual climber based on the climber's past health data using the generation AI. It is also possible to select rest points based on past data. This makes it possible to suggest the optimal rest timing based on the climber's past health data.

[0098] The processing flow of the second embodiment will be briefly explained below.

[0099] Step 1: The navigation unit navigates the climbing route. For example, the generation AI calculates the optimal climbing route based on the climber's current location and destination, and issues specific instructions. The generation AI navigates based on prompts that include instructions on what the climber wants the generation AI to do. Step 2: The notification receiving unit receives notifications from the management building. For example, disaster evacuation information and bear sighting information are received in real time and notified to climbers. Step 3: The information transmission unit transmits the climber's location information to the management building. For example, if the climber sends out an SOS, the information transmission unit transmits the location information to the management building. Step 4: The notification unit notifies the user of the weather, when to take a break, and their health condition. For example, the AI ​​generation unit may notify them of the weather, such as "It will soon start raining, so please prepare your rain gear," based on weather information. The AI ​​generation unit may also monitor the climber's health condition, such as their pulse rate, and notify them of appropriate times to take a break.

[0100] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0101] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0102] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0103] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0104] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0105] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0106] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0107] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0108] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0109] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0110] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0111] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0112] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0113] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0114] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0115] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0116] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0117] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0118] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0119] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0120] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0121] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0122] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0123] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0124] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0125] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0126] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0127] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0128] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0129] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0130] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0131] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0132] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0133] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0134] 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.

[0135] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0136] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0137] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0138] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0139] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0140] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0141] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0142] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0143] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0144] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0145] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0146] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0147] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0148] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0149] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0150] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0151] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0152] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0153] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0154] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0155] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0156] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0157] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0158] 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.

[0159] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0160] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0161] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0162] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0163] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0164] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0165] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0166] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0167] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A navigation section that navigates the mountain climbing route, a report receiving unit that receives reports from the management building; an information transmitting unit that transmits the climber's location information to the management building; A notification unit that notifies the user of weather, break timing, and health status. A system characterized by:

2. The navigation unit Learn the climber's past climbing history and suggest the best route for the climber 2. The system of claim 1.

3. The navigation unit Monitor the climber's physical condition in real time and suggest route changes according to their physical condition.

2. The system of claim 1.

4. The navigation unit Analyze the climber's emotional state and suggest routes to reduce stress 2. The system of claim 1.

5. The notification receiving unit Automatically translate reports to accommodate foreign climbers 2. The system of claim 1.

6. The notification receiving unit The contents of the report will be read out loud, making it accessible to visually impaired people.

2. The system of claim 1.

7. The notification receiving unit Analyze the urgency of the report and prioritize notifications 2. The system of claim 1.

8. The information transmission unit Not only the climber's location information, but also health and environmental information is transmitted at the same time.

2. The system of claim 1.

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