System

Abstract

An object of the system according to the embodiment is to automate submission of a Iriyama request by a mountain climber and safety confirmation at the time of mountain descent and provide information to family members and friends.SOLUTION: In general, according to one embodiment, a system includes a AI camera, a face authenticating unit, a Iriyama request submitting unit, a mountain checking unit, and an information providing unit. The AI camera recognizes the face of the mountain climber. The face recognition unit performs face recognition based on a face image acquired by the AI camera. The Iriyama request submitting unit automatically submits a Iriyama request based on the information of the mountaineer authenticated by the face authenticating unit. The mountain descent confirmation unit confirms a mountain descent based on the information of the mountaineer authenticated by the face authentication unit. The information providing unit provides information acquired by the Iriyama request submitting unit and the mountain descent checking unit to family members and friends.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology requires climbers to submit mountain entry notifications and does not adequately check for safety when descending the mountain, so there is room for improvement.

[0005] The system of the embodiment aims to automate the submission of mountain climbing registrations and safety checks when descending the mountain by climbers, and to provide information to family and friends. [Means for solving the problem]

[0006] The system according to the embodiment comprises an AI camera, a face authentication unit, a mountain entry notification submission unit, a descent confirmation unit, and an information provision unit. The AI ​​camera recognizes the face of the climber. The face authentication unit performs face authentication based on the facial image acquired by the AI ​​camera. The mountain entry notification submission unit automatically submits a mountain entry notification based on the information of the climber authenticated by the face authentication unit. The descent confirmation unit confirms the descent based on the information of the climber authenticated by the face authentication unit. The information provision unit provides the information acquired by the mountain entry notification submission unit and the descent confirmation unit to family and friends. [Effects of the Invention]

[0007] The system according to the embodiment automates the submission of mountain climbing registrations and safety checks when descending the mountain, and can provide information to family and friends. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The climber safety assurance system according to an embodiment of the present invention automates the confirmation of climbers' entry and descent to ensure their safety. This system uses AI cameras to perform facial recognition, automatically submitting a mountain climbing notification when climbing, and also performing facial recognition when descending. This allows the climber safety assurance system to automatically send information about climbers' entry and descent, along with photos, to family and friends. Convenience can also be improved by installing AI cameras at mountain huts and major access points. Furthermore, by cooperating with local governments and linking the system to existing apps, it is possible to further ensure the safety of climbers' lives and prevent rescue costs and secondary damage to those in distress.

[0029] A climber safety assurance system according to an embodiment includes an AI camera, a face recognition unit, a mountain entry notification submission unit, a descent confirmation unit, and an information provision unit. The AI ​​camera recognizes the face of a climber. For example, when a climber stands in front of the camera, the AI ​​camera performs face recognition and recognizes the climber's face. The face recognition unit performs face recognition based on the facial image acquired by the AI ​​camera. For example, the face recognition unit authenticates the climber's face using a face recognition algorithm that uses deep learning. The mountain entry notification submission unit automatically submits a mountain entry notification based on the climber's information authenticated by the face recognition unit. For example, the mountain entry notification submission unit submits the mountain entry notification by automatically submitting an online form. The descent confirmation unit confirms the climber's descent based on the climber's information authenticated by the face recognition unit. For example, the descent confirmation unit performs face recognition when the climber arrives at the descent entrance and confirms the descent. The information provision unit provides the information acquired by the mountain entry notification submission unit and the descent confirmation unit to family and friends. For example, the information providing unit transmits a message saying "Mr. / Ms. XX has entered the mountain" along with a photo of the climber when he / she enters the mountain. Also, when the climber descends the mountain, the information providing unit transmits a message saying "Mr. / Ms. XX has safely descended the mountain." In this way, the climber safety ensuring system according to the embodiment can automate the confirmation of climbers entering and descending the mountain, thereby ensuring safety.

[0030] The facial recognition unit simultaneously recognizes the climber's face and measures their heart rate and body temperature without contact, issuing a warning if any abnormalities are detected. For example, when a climber stands in front of the AI ​​camera, the facial recognition unit activates a sensor that simultaneously measures their heart rate and body temperature without contact, and displays a warning message if an abnormality is detected. The facial recognition unit also uses a sensor built into the AI ​​camera to simultaneously measure the climber's vital signs and issue an audio warning if any abnormalities are detected. For example, if the body temperature is too high, the unit displays a message such as "Your body temperature is high. Please take care of your health." When the climber performs facial recognition, the facial recognition unit also activates a sensor that simultaneously measures their heart rate and body temperature without contact, and if any abnormalities are detected, it sends a warning notification to the smartphone. This allows the climber's health to be monitored in real time and a warning to be issued if any abnormalities are detected.

[0031] The facial recognition unit checks the climber's equipment and notifies them if any equipment is missing. For example, when a climber stands in front of the AI ​​camera, the facial recognition unit simultaneously checks their equipment and notifies them via voice if any equipment is missing. For example, it displays a message such as, "Your helmet is missing. Please check your equipment." The facial recognition unit's built-in equipment check function scans the climber's equipment simultaneously with facial recognition and sends a notification to their smartphone if any equipment is missing. Furthermore, when the climber performs facial recognition, the facial recognition unit activates the equipment check function, and if any equipment is detected, it displays a warning message on a display installed at the trailhead. This notifies climbers in advance of any missing equipment, improving safety.

[0032] The facial recognition unit provides an AI guide function to help climbers select a climbing route and can suggest the optimal route for them. For example, when a climber stands in front of the AI ​​camera, the AI ​​guide function activates upon facial recognition and suggests the optimal climbing route based on the climber's physical strength and experience. For example, it displays a message such as, "We recommend a route for beginners." The AI ​​guide function built into the AI ​​camera also references the climber's past climbing history upon facial recognition and suggests the optimal route. For example, it displays a message such as, "We recommend the same route as your previous climbing route." When a climber performs facial recognition, the AI ​​guide function activates and suggests the optimal route based on the climber's current physical condition and weather information. For example, it displays a message such as, "We recommend a route suitable for the current weather." This allows for the system to suggest the optimal route for climbers and improve safety.

[0033] The facial recognition unit can display the climber's past climbing history and provide advice based on past experience. For example, when a climber stands in front of the AI ​​camera, the facial recognition unit simultaneously displays the climber's past climbing history and provides advice based on past experience. For example, it displays a message such as, "You took few breaks on your last climb, so we recommend taking frequent breaks this time." In addition, the facial recognition unit's built-in history display function references the climber's past climbing history and provides appropriate advice at the same time as facial recognition. For example, it displays a message such as, "We recommend bringing the equipment you used on your last climb." In addition, when the climber performs facial recognition, the facial recognition unit displays the climber's past climbing history and provides advice based on past experience. For example, it displays a message such as, "Be careful of the points where you became ill on your last climb." This allows for advice based on the climber's past experience, improving safety.

[0034] The descent confirmation unit can evaluate the climber's fatigue level while simultaneously recognizing their face as they descend and display a message encouraging them to take a break if necessary. For example, when the climber arrives at the trailhead, the descent confirmation unit uses an AI camera to simultaneously evaluate their fatigue level while simultaneously recognizing their face, and provide an audio message encouraging them to take a break if necessary. For example, a message such as "Thank you for your hard work. Please take a short break" is displayed. The descent confirmation unit also uses a fatigue evaluation function built into the AI ​​camera to simultaneously analyze the climber's facial expressions and movements while simultaneously recognizing their face, evaluate their fatigue level, and send a message encouraging them to take a break to their smartphone. When the climber performs facial recognition at the trailhead, the descent confirmation unit also activates the fatigue evaluation function and displays a message encouraging them to take a break if necessary on a display installed at the trailhead. This improves safety by evaluating the climber's fatigue level and encouraging them to take a break if necessary.

[0035] The descent confirmation unit can check the condition of the climber's equipment during facial recognition and notify the climber if any damage or loss occurs. For example, when a climber arrives at the trailhead, the descent confirmation unit uses an AI camera to simultaneously check the condition of the equipment during facial recognition and notify the climber via voice if any damage or loss occurs. For example, the descent confirmation unit displays a message such as, "Part of your equipment is damaged. Please check it." The descent confirmation unit also uses an equipment check function built into the AI ​​camera to scan the climber's equipment during facial recognition and sends a notification to the smartphone if any damage or loss occurs. Furthermore, when the climber performs facial recognition at the trailhead, the equipment check function is activated, and if any damage or loss is detected, a warning message is displayed on a display installed at the trailhead. This improves safety by checking the condition of the climber's equipment and notifying the climber if any damage or loss occurs.

[0036] The descent confirmation unit records the climber's descent route in conjunction with facial recognition during descent, and can provide data useful for planning the next climb. For example, when the climber arrives at the trailhead, the descent confirmation unit records the climber's descent route simultaneously with facial recognition using an AI camera, and sends the data to a smartphone to be used for planning the next climb. For example, the descent confirmation unit displays a message such as, "This descent route has been recorded. Please use this data for planning your next climb." The descent confirmation unit also uses a route recording function built into the AI ​​camera to record the climber's descent route simultaneously with facial recognition, and stores the data in the cloud to be used for planning the next climb. Furthermore, when the climber performs facial recognition at the trailhead, the descent confirmation unit activates the route recording function, recording the descent route and displaying data to be used for planning the next climb on a display installed at the trailhead. This allows the climber's descent route to be recorded and provides data useful for planning the next climb.

[0037] The descent confirmation unit works in conjunction with facial recognition to provide the climber with a recovery plan for after their descent and advice on stretching and nutrition. For example, when a climber arrives at the trailhead, the descent confirmation unit uses an AI camera to simultaneously perform facial recognition and provide a recovery plan and audio advice on stretching and nutrition. For example, it displays a message such as, "Thank you for your hard work. Please stretch and replenish your nutrients." The descent confirmation unit's built-in recovery plan function analyzes the climber's physical condition simultaneously with facial recognition and sends appropriate stretching and nutrition advice to the climber's smartphone. When the climber performs facial recognition at the trailhead, the descent confirmation unit activates the recovery plan function and displays advice on stretching and nutrition on a display installed at the trailhead. This allows the climber to receive a recovery plan for after their descent and advice on stretching and nutrition.

[0038] The information providing unit can provide family and friends with real-time location information of the climber during their climb, in addition to information about their ascent and descent. For example, when a climber enters the mountain, the AI ​​camera simultaneously performs facial recognition and provides real-time location information to family and friends. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." The information providing unit also uses a location information providing function built into the AI ​​camera to simultaneously perform facial recognition and track the climber's location in real time, notifying family and friends. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." The information providing unit also activates a function to provide real-time location information to family and friends when the climber enters and descends the mountain, and periodically updates and notifies them of the location information during the climb. This increases the climber's sense of security by providing real-time location information of the climber during their climb.

[0039] The information provider can also report the climber's health condition and the condition of their equipment, providing more detailed information. For example, when a climber enters the mountain, the AI ​​camera performs facial recognition and simultaneously checks their health condition and the condition of their equipment, and provides this information to family and friends. For example, it sends a message such as, "Mr. / Ms. XX has entered the mountain. He / she is in good health." The AI ​​camera's built-in health and equipment check function also analyzes the climber's health condition and the condition of their equipment, simultaneously with facial recognition, and notifies family and friends. For example, it sends a message such as, "Mr. / Ms. XX has entered the mountain. His / her equipment is perfect." The information provider also activates a function to report the climber's health condition and the condition of their equipment to family and friends when the climber enters and descends the mountain, providing more detailed information. This allows the climber's health condition and the condition of their equipment to be reported, providing more detailed information.

[0040] The information providing unit automatically attaches photos and videos taken by the climber to the information provided to family and friends, allowing them to share their climb. For example, when a climber enters the mountain, the information providing unit automatically sends the photos and videos taken by the climber to family and friends at the same time as facial recognition using the AI ​​camera. For example, it sends a message such as, "Mr. / Ms. XX has entered the mountain. Please see the photo below." In addition, the information providing unit automatically sends the photos and videos taken by the climber to family and friends at the same time as facial recognition using the photo and video sharing function built into the AI ​​camera. For example, it sends a message such as, "Mr. / Ms. XX has entered the mountain. Please see the video below." In addition, when the climber enters and descends the mountain, the information providing unit activates a function to automatically share the photos and videos taken with family and friends, allowing them to share their climb in real time. This allows the photos and videos taken by the climber to be automatically attached and the climb to be shared.

[0041] The information providing unit can automatically post information about climbers' entry and descent to social media in cooperation with social media platforms, allowing it to be widely shared. For example, when a climber enters the mountain, the AI ​​camera automatically posts the entry information to social media platforms upon facial recognition. For example, a message such as "Mr. / Ms. XX has entered the mountain" is posted to social media. In addition, the information providing unit automatically posts information about climbers' entry and descent to social media platforms upon facial recognition using a social media integration function built into the AI ​​camera. For example, a message such as "Mr. / Ms. XX has safely descended the mountain" is posted to social media. In addition, when climbers enter and descend the mountain, the information providing unit activates a function that automatically posts information to social media platforms, allowing it to be widely shared. For example, a message such as "Mr. / Ms. XX has entered the mountain. Please see the photo below" is posted to social media. In this way, information about climbers' entry and descent to social media platforms can be automatically posted and widely shared in cooperation with social media platforms.

[0042] AI cameras are installed at mountain huts and major access points and can regularly check the health of climbers and notify them if any abnormalities are detected. For example, when a climber arrives at a mountain hut, the AI ​​camera performs facial recognition and simultaneously checks their health status, and if any abnormalities are detected, it notifies them via voice. For example, it displays a message such as, "Your temperature is high. Please take care of your health." In addition, the AI ​​camera's built-in health check function periodically checks the climber's health status at the same time as facial recognition, and sends a notification to their smartphone if any abnormalities are detected. In addition, when a climber arrives at a mountain hut, the health check function is activated, and if any abnormalities are detected, a warning message is displayed on a display installed in the hut. This allows the climber's health to be regularly checked and any abnormalities to be notified.

[0043] AI cameras can periodically check the condition of climbers' equipment and prompt them for necessary maintenance. For example, when a climber arrives at a mountain hut, the AI ​​camera performs facial recognition and simultaneously checks the condition of their equipment, and provides a voice message urging them to perform necessary maintenance. For example, it displays a message such as, "Part of your equipment is damaged. Please perform maintenance." In addition, the AI ​​camera's built-in equipment check function periodically checks the climber's equipment and simultaneously performs facial recognition and sends a message to their smartphone urging them to perform necessary maintenance. In addition, when a climber arrives at a mountain hut, the AI ​​camera's equipment check function is activated and a message urging them to perform necessary maintenance is displayed on a display installed in the hut. This allows the condition of climbers' equipment to be periodically checked and prompts them to perform necessary maintenance.

[0044] AI cameras are installed at mountain huts and major access points to track climbers' movements in real time, enabling rapid response in emergencies. For example, when a climber arrives at a mountain hut, the AI ​​camera simultaneously tracks the climber's movements in real time using facial recognition, enabling rapid response in emergencies. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." In addition, the AI ​​camera's built-in tracking function simultaneously tracks the climber's movements in real time using facial recognition, enabling rapid response in emergencies. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." In addition, when a climber arrives at a mountain hut, the tracking function is activated, tracking the climber's movements in real time, enabling rapid response in emergencies. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." This allows the AI ​​camera to track the climber's movements in real time, enabling rapid response in emergencies.

[0045] AI cameras can analyze climbers' behavior patterns and suggest optimal rest points and routes. For example, when a climber arrives at a mountain hut, the AI ​​camera performs facial recognition and simultaneously analyzes their behavior patterns to suggest optimal rest points and routes. For example, it displays a message such as, "The next rest point is point XX." The AI ​​camera's built-in behavior pattern analysis function also analyzes the climber's behavior patterns and suggests optimal rest points and routes. For example, it sends a message such as, "The next rest point is point XX" to a smartphone. When a climber arrives at a mountain hut, the AI ​​camera's behavior pattern analysis function is activated and suggests optimal rest points and routes. For example, it displays a message such as, "The next rest point is point XX" on a display installed in the hut. This allows the AI ​​camera to analyze climbers' behavior patterns and suggest optimal rest points and routes.

[0046] The information providing unit cooperates with local governments to build a database that centrally manages information about climbers, enabling a rapid response. The information providing unit, for example, cooperates with local governments to build a database that centrally manages information about climbers, enabling a rapid response in emergencies. For example, the information providing unit updates climbers' climbing and descending information in real time. The information providing unit also cooperates with local governments to build a database that centrally manages information about climbers, ensuring the safety of climbers. For example, the information providing unit registers the health status and equipment status of climbers in the database. The information providing unit also cooperates with local governments to build a database that centrally manages information about climbers, enabling a rapid response. For example, the information providing unit tracks the location information of climbers in real time. This allows the building of a database that centrally manages information about climbers, enabling a rapid response.

[0047] The information providing unit can work with existing apps to monitor the climber's health condition and equipment status in real time and notify the climber if any abnormalities are found. For example, the information providing unit can work with existing apps to monitor the climber's health condition and equipment status in real time and notify the climber if any abnormalities are found. For example, the information providing unit can send a message such as, "Your body temperature is high. Please take care of your health." The information providing unit can also work with existing apps to monitor the climber's health condition and equipment status in real time and notify the climber's smartphone if any abnormalities are found. The information providing unit can also work with existing apps to monitor the climber's health condition and equipment status in real time and notify the local government if any abnormalities are found. This allows the climber's health condition and equipment status to be monitored in real time and notified the climber if any abnormalities are found.

[0048] The information providing unit, in cooperation with local governments, creates statistical data based on information about climbers, which can be used to improve mountain climbing safety. The information providing unit, for example, in cooperation with local governments, creates statistical data based on information about climbers, which can be used to improve mountain climbing safety. For example, the information providing unit compiles information about climbers' ascent and descent to create statistical data. The information providing unit also works with local governments to create statistical data based on information about climbers, which can be used to improve mountain climbing safety. For example, the information providing unit compiles information about the climbers' health and the condition of their equipment to create statistical data. The information providing unit also works with local governments to create statistical data based on information about climbers, which can be used to improve mountain climbing safety. For example, the information providing unit compiles information about the climbers' location to create statistical data. In this way, statistical data based on information about climbers can be created, which can be used to improve mountain climbing safety.

[0049] The information providing unit can work in conjunction with an existing app to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan. The information providing unit, for example, works in conjunction with an existing app to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan. For example, it sends a message such as, "For your next mountain climbing plan, we recommend the XX route." The information providing unit can also work in conjunction with an existing app to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan. For example, it sends a message such as, "For your next mountain climbing plan, we recommend the XX route." to a smartphone. The information providing unit can also work in conjunction with an existing app to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan. For example, it sends a message such as, "For your next mountain climbing plan, we recommend the XX route." to a local government. In this way, it is possible to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The climber safety system can further include a weather information acquisition unit. The weather information acquisition unit can acquire current weather information when a climber enters the mountain and provide it to the climber. For example, when a climber arrives at the mountain entrance, the weather information acquisition unit acquires current weather information and displays a message such as, "The current weather is sunny. The temperature is 20 degrees." The weather information acquisition unit can also send a warning message if the weather suddenly changes while the climber is climbing. For example, it can display a message such as, "The weather is worsening. Please evacuate to a safe place." Furthermore, the weather information acquisition unit can also provide weather information when the climber descends the mountain, improving the safety of the descent. This allows climbers to obtain weather information in real time and climb safely.

[0052] The climber safety assurance system can further include an emergency communication unit. The emergency communication unit can quickly request rescue if a climber gets into an emergency. For example, if a climber gets lost, the emergency communication unit can automatically obtain location information and notify a rescue team. The emergency communication unit can also request rescue by having the climber manually press an emergency button. For example, it can send a message such as, "An emergency has occurred. Rescue is requested." Furthermore, the emergency communication unit can monitor the climber's health condition and automatically request rescue if an abnormality is detected. This allows climbers to respond quickly to emergencies and climb safely.

[0053] The climber safety assurance system can further include an energy management unit. The energy management unit can monitor the climber's energy consumption in real time and encourage appropriate energy replenishment. For example, after the climber has walked a certain distance, the energy management unit can display a message such as, "You need to replenish your energy. Please take a break." The energy management unit can also suggest the optimal timing for energy replenishment based on the climber's energy consumption. For example, it can display a message such as, "Please replenish your energy at the next rest point." Furthermore, the energy management unit can record the climber's energy consumption and use the information to plan the next climb. This allows the climber to replenish their energy appropriately and climb safely.

[0054] The climber safety system can further include a communication unit. The communication unit can support communication between climbers and promote information sharing. For example, when a climber arrives at a mountain hut, the communication unit can provide a chat function with other climbers to exchange information. In addition, if a climber becomes lost, the communication unit can request rescue from other climbers. For example, the communication unit can send a message such as, "I'm lost at location XX. Please help me." Furthermore, when a climber descends the mountain, the communication unit can share information about the descent with other climbers, improving safety. This supports communication between climbers and allows for safe climbing.

[0055] The climber safety system can further include an environmental monitoring unit. The environmental monitoring unit monitors the environmental conditions of the climbing route in real time and can issue a warning if an abnormality occurs. For example, if a climber experiences a sudden change in weather or a risk of a landslide while climbing, the environmental monitoring unit displays a message such as, "The weather is changing suddenly. Please evacuate to a safe location." The environmental monitoring unit can also record environmental data of the climbing route and use it to plan the next climb. For example, it can display a message such as, "A landslide occurred at point XX during the previous climb. Please be careful." Furthermore, the environmental monitoring unit can check the environmental conditions when the climber descends the mountain and support them in descending safely. This allows climbers to understand the environmental conditions in real time and climb safely.

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

[0057] Step 1: The AI ​​camera recognizes the climber's face. For example, when a climber stands in front of the camera, the AI ​​camera performs facial recognition and recognizes the climber's face. Step 2: The facial recognition unit performs facial recognition based on the facial image captured by the AI ​​camera. For example, the facial recognition unit uses a deep learning-based facial recognition algorithm to recognize the climber's face. Step 3: The mountain entry notification submission unit automatically submits a mountain entry notification based on the climber's information authenticated by the face recognition unit. For example, the mountain entry notification submission unit submits the mountain entry notification by automatically submitting an online form. Step 4: The descending confirmation unit confirms the climber's descent based on the information of the climber authenticated by the face authentication unit. For example, the descending confirmation unit performs face authentication when the climber arrives at the descending entrance and confirms that the climber has descended. Step 5: The information providing unit provides the information acquired by the mountain entry notification submission unit and the mountain descent confirmation unit to family and friends. For example, the information providing unit sends a message saying "Mr. / Ms. XX has entered the mountain" along with a photo of the climber when he / she enters the mountain. Also, when he / she descends the mountain, the information providing unit sends a message saying "Mr. / Ms. XX has descended the mountain safely."

[0058] (Example 2) The climber safety assurance system according to an embodiment of the present invention automates the confirmation of climbers' entry and descent to ensure their safety. This system uses AI cameras to perform facial recognition, automatically submitting a mountain climbing notification when climbing, and also performing facial recognition when descending. This allows the climber safety assurance system to automatically send information about climbers' entry and descent, along with photos, to family and friends. Convenience can also be improved by installing AI cameras at mountain huts and major access points. Furthermore, by cooperating with local governments and linking the system to existing apps, it is possible to further ensure the safety of climbers' lives and prevent rescue costs and secondary damage to those in distress.

[0059] A climber safety assurance system according to an embodiment includes an AI camera, a face recognition unit, a mountain entry notification submission unit, a descent confirmation unit, and an information provision unit. The AI ​​camera recognizes the face of a climber. For example, when a climber stands in front of the camera, the AI ​​camera performs face recognition and recognizes the climber's face. The face recognition unit performs face recognition based on the facial image acquired by the AI ​​camera. For example, the face recognition unit authenticates the climber's face using a face recognition algorithm that uses deep learning. The mountain entry notification submission unit automatically submits a mountain entry notification based on the climber's information authenticated by the face recognition unit. For example, the mountain entry notification submission unit submits the mountain entry notification by automatically submitting an online form. The descent confirmation unit confirms the climber's descent based on the climber's information authenticated by the face recognition unit. For example, the descent confirmation unit performs face recognition when the climber arrives at the descent entrance and confirms the descent. The information provision unit provides the information acquired by the mountain entry notification submission unit and the descent confirmation unit to family and friends. For example, the information providing unit transmits a message saying "Mr. / Ms. XX has entered the mountain" along with a photo of the climber when he / she enters the mountain. Also, when the climber descends the mountain, the information providing unit transmits a message saying "Mr. / Ms. XX has safely descended the mountain." In this way, the climber safety ensuring system according to the embodiment can automate the confirmation of climbers entering and descending the mountain, thereby ensuring safety.

[0060] The facial recognition unit simultaneously recognizes the climber's face and measures their heart rate and body temperature without contact, issuing a warning if any abnormalities are detected. For example, when a climber stands in front of the AI ​​camera, the facial recognition unit activates a sensor that simultaneously measures their heart rate and body temperature without contact, and displays a warning message if an abnormality is detected. The facial recognition unit also uses a sensor built into the AI ​​camera to simultaneously measure the climber's vital signs and issue an audio warning if any abnormalities are detected. For example, if the body temperature is too high, the unit displays a message such as "Your body temperature is high. Please take care of your health." When the climber performs facial recognition, the facial recognition unit also activates a sensor that simultaneously measures their heart rate and body temperature without contact, and if any abnormalities are detected, it sends a warning notification to the smartphone. This allows the climber's health to be monitored in real time and a warning to be issued if any abnormalities are detected.

[0061] The facial recognition unit checks the climber's equipment and notifies them if any equipment is missing. For example, when a climber stands in front of the AI ​​camera, the facial recognition unit simultaneously checks their equipment and notifies them via voice if any equipment is missing. For example, it displays a message such as, "Your helmet is missing. Please check your equipment." The facial recognition unit's built-in equipment check function scans the climber's equipment simultaneously with facial recognition and sends a notification to their smartphone if any equipment is missing. Furthermore, when the climber performs facial recognition, the facial recognition unit activates the equipment check function, and if any equipment is detected, it displays a warning message on a display installed at the trailhead. This notifies climbers in advance of any missing equipment, improving safety.

[0062] The facial recognition unit can use its emotion estimation function to detect a climber's tension or anxiety and provide them with advice to relax. For example, when a climber stands in front of the AI ​​camera, the emotion estimation function is activated simultaneously with facial recognition, and if tension or anxiety is detected, audio advice to relax is provided. For example, a message such as "Take a deep breath and relax" is displayed. The emotion estimation function built into the AI ​​camera also analyzes the climber's facial expression simultaneously with facial recognition, and if tension or anxiety is detected, advice to relax is sent to the smartphone. Furthermore, when the climber performs facial recognition, the emotion estimation function is activated, and if tension or anxiety is detected, advice to relax is displayed on a display installed at the trailhead. This makes it possible to detect a climber's tension or anxiety and provide them with advice to relax.

[0063] The facial recognition unit provides an AI guide function to help climbers select a climbing route and can suggest the optimal route for them. For example, when a climber stands in front of the AI ​​camera, the AI ​​guide function activates upon facial recognition and suggests the optimal climbing route based on the climber's physical strength and experience. For example, it displays a message such as, "We recommend a route for beginners." The AI ​​guide function built into the AI ​​camera also references the climber's past climbing history upon facial recognition and suggests the optimal route. For example, it displays a message such as, "We recommend the same route as your previous climbing route." When a climber performs facial recognition, the AI ​​guide function activates and suggests the optimal route based on the climber's current physical condition and weather information. For example, it displays a message such as, "We recommend a route suitable for the current weather." This allows for the system to suggest the optimal route for climbers and improve safety.

[0064] The facial recognition unit can display the climber's past climbing history and provide advice based on past experience. For example, when a climber stands in front of the AI ​​camera, the facial recognition unit simultaneously displays the climber's past climbing history and provides advice based on past experience. For example, it displays a message such as, "You took few breaks on your last climb, so we recommend taking frequent breaks this time." In addition, the facial recognition unit's built-in history display function references the climber's past climbing history and provides appropriate advice at the same time as facial recognition. For example, it displays a message such as, "We recommend bringing the equipment you used on your last climb." In addition, when the climber performs facial recognition, the facial recognition unit displays the climber's past climbing history and provides advice based on past experience. For example, it displays a message such as, "Be careful of the points where you became ill on your last climb." This allows for advice based on the climber's past experience, improving safety.

[0065] The facial recognition unit can use its emotion estimation function to display encouraging messages to motivate climbers. For example, when a climber stands in front of the AI ​​camera, the facial recognition unit simultaneously activates its emotion estimation function to provide an encouraging voice message to motivate them. For example, it displays a message such as, "Do your best! You can do it!" The facial recognition unit's built-in emotion estimation function also analyzes the climber's facial expression simultaneously with facial recognition and sends a motivational message to the smartphone. When the climber performs facial recognition, the facial recognition unit also activates its emotion estimation function to display a motivational message on a display installed at the trailhead. This makes it possible to provide encouraging messages to motivate climbers.

[0066] The descent confirmation unit can evaluate the climber's fatigue level while simultaneously recognizing their face as they descend and display a message encouraging them to take a break if necessary. For example, when the climber arrives at the trailhead, the descent confirmation unit uses an AI camera to simultaneously evaluate their fatigue level while simultaneously recognizing their face, and provide an audio message encouraging them to take a break if necessary. For example, a message such as "Thank you for your hard work. Please take a short break" is displayed. The descent confirmation unit also uses a fatigue evaluation function built into the AI ​​camera to simultaneously analyze the climber's facial expressions and movements while simultaneously recognizing their face, evaluate their fatigue level, and send a message encouraging them to take a break to their smartphone. When the climber performs facial recognition at the trailhead, the descent confirmation unit also activates the fatigue evaluation function and displays a message encouraging them to take a break if necessary on a display installed at the trailhead. This improves safety by evaluating the climber's fatigue level and encouraging them to take a break if necessary.

[0067] The descent confirmation unit can check the condition of the climber's equipment during facial recognition and notify the climber if any damage or loss occurs. For example, when a climber arrives at the trailhead, the descent confirmation unit uses an AI camera to simultaneously check the condition of the equipment during facial recognition and notify the climber via voice if any damage or loss occurs. For example, the descent confirmation unit displays a message such as, "Part of your equipment is damaged. Please check it." The descent confirmation unit also uses an equipment check function built into the AI ​​camera to scan the climber's equipment during facial recognition and sends a notification to the smartphone if any damage or loss occurs. Furthermore, when the climber performs facial recognition at the trailhead, the equipment check function is activated, and if any damage or loss is detected, a warning message is displayed on a display installed at the trailhead. This improves safety by checking the condition of the climber's equipment and notifying the climber if any damage or loss occurs.

[0068] The descent confirmation unit can use the emotion estimation function to evaluate the climber's sense of accomplishment and satisfaction and provide positive feedback. For example, when the climber arrives at the trailhead, the emotion estimation function activates at the same time as the AI ​​camera performs facial recognition, evaluating the climber's sense of accomplishment and satisfaction and providing positive feedback via voice. For example, a message such as "Thank you for your hard work! It was a great climb!" is displayed. The descent confirmation unit also uses the emotion estimation function built into the AI ​​camera to analyze the climber's facial expression at the same time as facial recognition, evaluating the climber's sense of accomplishment and satisfaction, and sending positive feedback to the smartphone. When the climber performs facial recognition at the trailhead, the emotion estimation function activates, evaluating the climber's sense of accomplishment and satisfaction, and displaying positive feedback on a display installed at the trailhead. This makes it possible to evaluate the climber's sense of accomplishment and satisfaction and provide positive feedback.

[0069] The descent confirmation unit records the climber's descent route in conjunction with facial recognition during descent, and can provide data useful for planning the next climb. For example, when the climber arrives at the trailhead, the descent confirmation unit records the climber's descent route simultaneously with facial recognition using an AI camera, and sends the data to a smartphone to be used for planning the next climb. For example, the descent confirmation unit displays a message such as, "This descent route has been recorded. Please use this data for planning your next climb." The descent confirmation unit also uses a route recording function built into the AI ​​camera to record the climber's descent route simultaneously with facial recognition, and stores the data in the cloud to be used for planning the next climb. Furthermore, when the climber performs facial recognition at the trailhead, the descent confirmation unit activates the route recording function, recording the descent route and displaying data to be used for planning the next climb on a display installed at the trailhead. This allows the climber's descent route to be recorded and provides data useful for planning the next climb.

[0070] The descent confirmation unit works in conjunction with facial recognition to provide the climber with a recovery plan for after their descent and advice on stretching and nutrition. For example, when a climber arrives at the trailhead, the descent confirmation unit uses an AI camera to simultaneously perform facial recognition and provide a recovery plan and audio advice on stretching and nutrition. For example, it displays a message such as, "Thank you for your hard work. Please stretch and replenish your nutrients." The descent confirmation unit's built-in recovery plan function analyzes the climber's physical condition simultaneously with facial recognition and sends appropriate stretching and nutrition advice to the climber's smartphone. When the climber performs facial recognition at the trailhead, the descent confirmation unit activates the recovery plan function and displays advice on stretching and nutrition on a display installed at the trailhead. This allows the climber to receive a recovery plan for after their descent and advice on stretching and nutrition.

[0071] The descent confirmation unit uses the emotion estimation function to encourage the climber to reflect on their descent and suggest areas for improvement for their next climb. For example, when the climber arrives at the trailhead, the emotion estimation function activates simultaneously with facial recognition by the AI ​​camera, providing an audio message encouraging them to reflect on their descent. For example, a message such as, "Reflect on this climb and think about what you can improve on next time" is displayed. The descent confirmation unit also uses the emotion estimation function built into the AI ​​camera to analyze the climber's facial expressions simultaneously with facial recognition and send questions and advice to the smartphone to encourage reflection. When the climber performs facial recognition at the trailhead, the emotion estimation function activates and displays a message encouraging reflection on a display installed at the trailhead, suggesting areas for improvement for the next climb. This encourages the climber to reflect on their descent and suggests areas for improvement for the next climb.

[0072] The information providing unit can provide family and friends with real-time location information of the climber during their climb, in addition to information about their ascent and descent. For example, when a climber enters the mountain, the AI ​​camera simultaneously performs facial recognition and provides real-time location information to family and friends. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." The information providing unit also uses a location information providing function built into the AI ​​camera to simultaneously perform facial recognition and track the climber's location in real time, notifying family and friends. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." The information providing unit also activates a function to provide real-time location information to family and friends when the climber enters and descends the mountain, and periodically updates and notifies them of the location information during the climb. This increases the climber's sense of security by providing real-time location information of the climber during their climb.

[0073] The information provider can also report the climber's health condition and the condition of their equipment, providing more detailed information. For example, when a climber enters the mountain, the AI ​​camera performs facial recognition and simultaneously checks their health condition and the condition of their equipment, and provides this information to family and friends. For example, it sends a message such as, "Mr. / Ms. XX has entered the mountain. He / she is in good health." The AI ​​camera's built-in health and equipment check function also analyzes the climber's health condition and the condition of their equipment, simultaneously with facial recognition, and notifies family and friends. For example, it sends a message such as, "Mr. / Ms. XX has entered the mountain. His / her equipment is perfect." The information provider also activates a function to report the climber's health condition and the condition of their equipment to family and friends when the climber enters and descends the mountain, providing more detailed information. This allows the climber's health condition and the condition of their equipment to be reported, providing more detailed information.

[0074] The information providing unit uses the emotion estimation function to report the climber's emotional state to family and friends and can send encouraging messages as needed. For example, when a climber enters the mountain, the AI ​​camera performs facial recognition and simultaneously activates the emotion estimation function to report the climber's emotional state to family and friends. For example, the information providing unit sends a message such as, "Mr. / Ms. XX has entered the mountain. He / she seems a little nervous." The emotion estimation function built into the AI ​​camera also analyzes the climber's facial expressions as it performs facial recognition and notifies family and friends of the climber's emotional state. For example, the information providing unit sends a message such as, "Mr. / Ms. XX has entered the mountain. He / she looks like he / she is having a lot of fun." The emotion estimation function also activates when the climber enters and descends the mountain, reporting the climber's emotional state to family and friends and sending encouraging messages as needed. This allows the information providing unit to report the climber's emotional state to family and friends and sending encouraging messages as needed.

[0075] The information providing unit automatically attaches photos and videos taken by the climber to the information provided to family and friends, allowing them to share their climb. For example, when a climber enters the mountain, the information providing unit automatically sends the photos and videos taken by the climber to family and friends at the same time as facial recognition using the AI ​​camera. For example, it sends a message such as, "Mr. / Ms. XX has entered the mountain. Please see the photo below." In addition, the information providing unit automatically sends the photos and videos taken by the climber to family and friends at the same time as facial recognition using the photo and video sharing function built into the AI ​​camera. For example, it sends a message such as, "Mr. / Ms. XX has entered the mountain. Please see the video below." In addition, when the climber enters and descends the mountain, the information providing unit activates a function to automatically share the photos and videos taken with family and friends, allowing them to share their climb in real time. This allows the photos and videos taken by the climber to be automatically attached and the climb to be shared.

[0076] The information providing unit can automatically post information about climbers' entry and descent to social media in cooperation with social media platforms, allowing it to be widely shared. For example, when a climber enters the mountain, the AI ​​camera automatically posts the entry information to social media platforms upon facial recognition. For example, a message such as "Mr. / Ms. XX has entered the mountain" is posted to social media. In addition, the information providing unit automatically posts information about climbers' entry and descent to social media platforms upon facial recognition using a social media integration function built into the AI ​​camera. For example, a message such as "Mr. / Ms. XX has safely descended the mountain" is posted to social media. In addition, when climbers enter and descend the mountain, the information providing unit activates a function that automatically posts information to social media platforms, allowing it to be widely shared. For example, a message such as "Mr. / Ms. XX has entered the mountain. Please see the photo below" is posted to social media. In this way, information about climbers' entry and descent to social media platforms can be automatically posted and widely shared in cooperation with social media platforms.

[0077] The information provision unit uses the emotion estimation function to optimize the content of messages sent by family and friends to the climber, thereby exerting a positive influence. For example, when a climber enters the mountain, the AI ​​camera performs facial recognition and simultaneously activates the emotion estimation function to optimize the content of messages sent by family and friends. For example, a message such as "Mr. / Ms. XX has entered the mountain. Please send a message of encouragement" is sent to family and friends. In addition, the emotion estimation function built into the AI ​​camera analyzes the climber's facial expressions during facial recognition and optimizes the content of messages sent by family and friends. For example, a message such as "Mr. / Ms. XX has entered the mountain. Please send a positive message" is sent to family and friends. In addition, when the climber enters and descends the mountain, the emotion estimation function is activated to optimize the content of messages sent by family and friends, thereby exerting a positive influence. For example, a message such as "Mr. / Ms. XX has entered the mountain. Please send a message of support" is sent to family and friends. In this way, the content of messages sent by family and friends to the climber is optimized, thereby exerting a positive influence.

[0078] AI cameras are installed at mountain huts and major access points and can regularly check the health of climbers and notify them if any abnormalities are detected. For example, when a climber arrives at a mountain hut, the AI ​​camera performs facial recognition and simultaneously checks their health status, and if any abnormalities are detected, it notifies them via voice. For example, it displays a message such as, "Your temperature is high. Please take care of your health." In addition, the AI ​​camera's built-in health check function periodically checks the climber's health status at the same time as facial recognition, and sends a notification to their smartphone if any abnormalities are detected. In addition, when a climber arrives at a mountain hut, the health check function is activated, and if any abnormalities are detected, a warning message is displayed on a display installed in the hut. This allows the climber's health to be regularly checked and any abnormalities to be notified.

[0079] AI cameras can periodically check the condition of climbers' equipment and prompt them for necessary maintenance. For example, when a climber arrives at a mountain hut, the AI ​​camera performs facial recognition and simultaneously checks the condition of their equipment, and provides a voice message urging them to perform necessary maintenance. For example, it displays a message such as, "Part of your equipment is damaged. Please perform maintenance." In addition, the AI ​​camera's built-in equipment check function periodically checks the climber's equipment and simultaneously performs facial recognition and sends a message to their smartphone urging them to perform necessary maintenance. In addition, when a climber arrives at a mountain hut, the AI ​​camera's equipment check function is activated and a message urging them to perform necessary maintenance is displayed on a display installed in the hut. This allows the condition of climbers' equipment to be periodically checked and prompts them to perform necessary maintenance.

[0080] The AI ​​camera can use its emotion estimation function to assess a climber's stress level and provide advice on how to relax. For example, when a climber arrives at a mountain hut, the AI ​​camera's emotion estimation function activates simultaneously with facial recognition, assessing the climber's stress level and providing voice advice on how to relax. For example, it might display a message such as, "Take a deep breath and relax." The AI ​​camera's built-in emotion estimation function also analyzes the climber's facial expressions simultaneously with facial recognition, assessing the climber's stress level, and sending advice on how to relax to the climber's smartphone. The AI ​​camera's emotion estimation function also activates when the climber arrives at the mountain hut, assessing the climber's stress level, and displaying advice on how to relax on a display installed in the hut. This makes it possible to assess the climber's stress level and provide advice on how to relax.

[0081] AI cameras are installed at mountain huts and major access points to track climbers' movements in real time, enabling rapid response in emergencies. For example, when a climber arrives at a mountain hut, the AI ​​camera simultaneously tracks the climber's movements in real time using facial recognition, enabling rapid response in emergencies. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." In addition, the AI ​​camera's built-in tracking function simultaneously tracks the climber's movements in real time using facial recognition, enabling rapid response in emergencies. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." In addition, when a climber arrives at a mountain hut, the tracking function is activated, tracking the climber's movements in real time, enabling rapid response in emergencies. For example, it sends a message such as, "Mr. / Ms. XX is currently at XX location." This allows the AI ​​camera to track the climber's movements in real time, enabling rapid response in emergencies.

[0082] AI cameras can analyze climbers' behavior patterns and suggest optimal rest points and routes. For example, when a climber arrives at a mountain hut, the AI ​​camera performs facial recognition and simultaneously analyzes their behavior patterns to suggest optimal rest points and routes. For example, it displays a message such as, "The next rest point is point XX." The AI ​​camera's built-in behavior pattern analysis function also analyzes the climber's behavior patterns and suggests optimal rest points and routes. For example, it sends a message such as, "The next rest point is point XX" to a smartphone. When a climber arrives at a mountain hut, the AI ​​camera's behavior pattern analysis function is activated and suggests optimal rest points and routes. For example, it displays a message such as, "The next rest point is point XX" on a display installed in the hut. This allows the AI ​​camera to analyze climbers' behavior patterns and suggest optimal rest points and routes.

[0083] The AI ​​camera can use its emotion estimation function to display messages to maintain climbers' motivation. For example, when a climber arrives at a mountain hut, the AI ​​camera's emotion estimation function activates at the same time as facial recognition, providing an audio message to maintain motivation. For example, it displays a message such as, "You're almost at the summit! Keep up the great work!" The AI ​​camera's built-in emotion estimation function also analyzes the climber's facial expressions at the same time as facial recognition, and sends a message to their smartphone to maintain motivation. The AI ​​camera's emotion estimation function also activates when the climber arrives at the mountain hut, displaying a message to maintain motivation on a display installed in the hut. This makes it possible to display a message to maintain climbers' motivation.

[0084] The information providing unit cooperates with local governments to build a database that centrally manages information about climbers, enabling a rapid response. The information providing unit, for example, cooperates with local governments to build a database that centrally manages information about climbers, enabling a rapid response in emergencies. For example, the information providing unit updates climbers' climbing and descending information in real time. The information providing unit also cooperates with local governments to build a database that centrally manages information about climbers, ensuring the safety of climbers. For example, the information providing unit registers the health status and equipment status of climbers in the database. The information providing unit also cooperates with local governments to build a database that centrally manages information about climbers, enabling a rapid response. For example, the information providing unit tracks the location information of climbers in real time. This allows the building of a database that centrally manages information about climbers, enabling a rapid response.

[0085] The information providing unit can work with existing apps to monitor the climber's health condition and equipment status in real time and notify the climber if any abnormalities are found. For example, the information providing unit can work with existing apps to monitor the climber's health condition and equipment status in real time and notify the climber if any abnormalities are found. For example, the information providing unit can send a message such as, "Your body temperature is high. Please take care of your health." The information providing unit can also work with existing apps to monitor the climber's health condition and equipment status in real time and notify the climber's smartphone if any abnormalities are found. The information providing unit can also work with existing apps to monitor the climber's health condition and equipment status in real time and notify the local government if any abnormalities are found. This allows the climber's health condition and equipment status to be monitored in real time and notified the climber if any abnormalities are found.

[0086] The information providing unit can use the emotion estimation function to report the climber's emotional state to local governments and provide support as needed. The information providing unit, for example, works in conjunction with an existing app to monitor the climber's emotional state in real time and notify the local government if an abnormality is detected. For example, it sends a message such as, "The climber is nervous. Support is needed." The information providing unit can also use the emotion estimation function to report the climber's emotional state to local governments and provide support as needed. For example, it sends a message such as, "The climber is feeling anxious. Support is needed." The information providing unit can also work in conjunction with an existing app to monitor the climber's emotional state in real time and notify the local government if an abnormality is detected and provide support as needed. This makes it possible to report the climber's emotional state to local governments and provide support as needed.

[0087] The information providing unit, in cooperation with local governments, creates statistical data based on information about climbers, which can be used to improve mountain climbing safety. The information providing unit, for example, in cooperation with local governments, creates statistical data based on information about climbers, which can be used to improve mountain climbing safety. For example, the information providing unit compiles information about climbers' ascent and descent to create statistical data. The information providing unit also works with local governments to create statistical data based on information about climbers, which can be used to improve mountain climbing safety. For example, the information providing unit compiles information about the climbers' health and the condition of their equipment to create statistical data. The information providing unit also works with local governments to create statistical data based on information about climbers, which can be used to improve mountain climbing safety. For example, the information providing unit compiles information about the climbers' location to create statistical data. In this way, statistical data based on information about climbers can be created, which can be used to improve mountain climbing safety.

[0088] The information providing unit can work in conjunction with an existing app to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan. The information providing unit, for example, works in conjunction with an existing app to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan. For example, it sends a message such as, "For your next mountain climbing plan, we recommend the XX route." The information providing unit can also work in conjunction with an existing app to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan. For example, it sends a message such as, "For your next mountain climbing plan, we recommend the XX route." to a smartphone. The information providing unit can also work in conjunction with an existing app to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan. For example, it sends a message such as, "For your next mountain climbing plan, we recommend the XX route." to a local government. In this way, it is possible to analyze the behavioral patterns of climbers and propose an optimal mountain climbing plan.

[0089] The information providing unit can use the emotion estimation function to provide feedback based on the climber's emotional state and suggest improvements for the next climb. For example, the information providing unit can work with an existing app to monitor the climber's emotional state in real time and suggest improvements for the next climb. For example, the information providing unit can send a message such as, "The climber is nervous. Please prepare to relax next time." The information providing unit can also use the emotion estimation function to provide feedback based on the climber's emotional state and suggest improvements for the next climb. For example, the information providing unit can send a message such as, "The climber is feeling anxious. Please provide more support next time." The information providing unit can also work with an existing app to monitor the climber's emotional state in real time and suggest improvements for the next climb. For example, the information providing unit can send a message such as, "The climber is nervous. Please prepare to relax next time." to a local government. This makes it possible to provide feedback based on the climber's emotional state and suggest improvements for the next climb.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] The climber safety system can further include a weather information acquisition unit. The weather information acquisition unit can acquire current weather information when a climber enters the mountain and provide it to the climber. For example, when a climber arrives at the mountain entrance, the weather information acquisition unit acquires current weather information and displays a message such as, "The current weather is sunny. The temperature is 20 degrees." The weather information acquisition unit can also send a warning message if the weather suddenly changes while the climber is climbing. For example, it can display a message such as, "The weather is worsening. Please evacuate to a safe place." Furthermore, the weather information acquisition unit can also provide weather information when the climber descends the mountain, improving the safety of the descent. This allows climbers to obtain weather information in real time and climb safely.

[0092] The climber safety assurance system can further include an emergency communication unit. The emergency communication unit can quickly request rescue if a climber gets into an emergency. For example, if a climber gets lost, the emergency communication unit can automatically obtain location information and notify a rescue team. The emergency communication unit can also request rescue by having the climber manually press an emergency button. For example, it can send a message such as, "An emergency has occurred. Rescue is requested." Furthermore, the emergency communication unit can monitor the climber's health condition and automatically request rescue if an abnormality is detected. This allows climbers to respond quickly to emergencies and climb safely.

[0093] The climber safety assurance system can further include an energy management unit. The energy management unit can monitor the climber's energy consumption in real time and encourage appropriate energy replenishment. For example, after the climber has walked a certain distance, the energy management unit can display a message such as, "You need to replenish your energy. Please take a break." The energy management unit can also suggest the optimal timing for energy replenishment based on the climber's energy consumption. For example, it can display a message such as, "Please replenish your energy at the next rest point." Furthermore, the energy management unit can record the climber's energy consumption and use the information to plan the next climb. This allows the climber to replenish their energy appropriately and climb safely.

[0094] The climber safety system can further include a communication unit. The communication unit can support communication between climbers and promote information sharing. For example, when a climber arrives at a mountain hut, the communication unit can provide a chat function with other climbers to exchange information. In addition, if a climber becomes lost, the communication unit can request rescue from other climbers. For example, the communication unit can send a message such as, "I'm lost at location XX. Please help me." Furthermore, when a climber descends the mountain, the communication unit can share information about the descent with other climbers, improving safety. This supports communication between climbers and allows for safe climbing.

[0095] The climber safety system can further include an environmental monitoring unit. The environmental monitoring unit monitors the environmental conditions of the climbing route in real time and can issue a warning if an abnormality occurs. For example, if a climber experiences a sudden change in weather or a risk of a landslide while climbing, the environmental monitoring unit displays a message such as, "The weather is changing suddenly. Please evacuate to a safe location." The environmental monitoring unit can also record environmental data of the climbing route and use it to plan the next climb. For example, it can display a message such as, "A landslide occurred at point XX during the previous climb. Please be careful." Furthermore, the environmental monitoring unit can check the environmental conditions when the climber descends the mountain and support them in descending safely. This allows climbers to understand the environmental conditions in real time and climb safely.

[0096] The climber safety assurance system can further use an emotion estimation function to evaluate a climber's stress level and provide advice for relaxation. For example, when a climber arrives at a mountain hut, the emotion estimation function is activated simultaneously with facial recognition to evaluate the climber's stress level and provide audio advice for relaxation. For example, a message such as "Take a deep breath and relax" is displayed. The emotion estimation function can also analyze the climber's facial expression, evaluate the climber's stress level, and send advice for relaxation to the climber's smartphone. Furthermore, when the climber arrives at the mountain hut, the emotion estimation function can evaluate the climber's stress level and display advice for relaxation on a display installed in the hut. This makes it possible to evaluate the climber's stress level and provide advice for relaxation.

[0097] The climber safety assurance system can further use the emotion estimation function to display messages to maintain the climber's motivation. For example, when a climber arrives at a mountain hut, the emotion estimation function is activated at the same time as facial recognition to provide an audio message to maintain motivation. For example, a message such as "You're almost at the summit. Keep up the great work!" can be displayed. The emotion estimation function can also analyze the climber's facial expressions and send a message to their smartphone to maintain motivation. Furthermore, when the climber arrives at the hut, the emotion estimation function can display a message to maintain motivation on a display installed in the hut. This makes it possible to display a message to maintain the climber's motivation.

[0098] The climber safety assurance system can also use an emotion estimation function to report the climber's emotional state to family and friends and send encouraging messages as needed. For example, when a climber enters the mountain, the emotion estimation function is activated simultaneously with facial recognition to report the climber's emotional state to family and friends. For example, a message such as "Mr. / Ms. XX has entered the mountain. He / she seems a little nervous" is sent. The emotion estimation function can also analyze the climber's facial expressions and notify family and friends of the climber's emotional state. For example, a message such as "Mr. / Ms. XX has entered the mountain. He / she looks like he / she is having a lot of fun" is sent. Furthermore, the emotion estimation function can report the climber's emotional state to family and friends when the climber enters and descends the mountain and send encouraging messages as needed. This allows the climber's emotional state to be reported to family and friends and encouragement messages to be sent as needed.

[0099] The climber safety assurance system can further use the emotion estimation function to provide feedback based on the climber's emotional state and suggest improvements for the next climb. For example, by linking with an existing app, the system can monitor the climber's emotional state in real time and suggest improvements for the next climb. For example, it can send a message such as, "The climber is nervous. Please prepare to relax next time." The emotion estimation function can also provide feedback based on the climber's emotional state and suggest improvements for the next climb. For example, it can send a message such as, "The climber is feeling anxious. Please provide more support next time." The emotion estimation function can also monitor the climber's emotional state in real time and suggest improvements for the next climb. This makes it possible to provide feedback based on the climber's emotional state and suggest improvements for the next climb.

[0100] The climber safety assurance system can also use an emotion estimation function to evaluate a climber's sense of accomplishment and satisfaction and provide positive feedback. For example, when a climber arrives at the trailhead, the emotion estimation function is activated simultaneously with facial recognition, evaluating the climber's sense of accomplishment and satisfaction and providing positive feedback via voice. For example, a message such as "Thank you for your hard work! It was a great climb!" is displayed. The emotion estimation function can also analyze the climber's facial expressions, evaluate the climber's sense of accomplishment and satisfaction, and send positive feedback to the climber's smartphone. Furthermore, when the climber performs facial recognition at the trailhead, the emotion estimation function can evaluate the climber's sense of accomplishment and satisfaction and display positive feedback on a display installed at the trailhead. This makes it possible to evaluate the climber's sense of accomplishment and satisfaction and provide positive feedback.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The AI ​​camera recognizes the climber's face. For example, when a climber stands in front of the camera, the AI ​​camera performs facial recognition and recognizes the climber's face. Step 2: The facial recognition unit performs facial recognition based on the facial image captured by the AI ​​camera. For example, the facial recognition unit uses a deep learning-based facial recognition algorithm to recognize the climber's face. Step 3: The mountain entry notification submission unit automatically submits a mountain entry notification based on the climber's information authenticated by the face recognition unit. For example, the mountain entry notification submission unit submits the mountain entry notification by automatically submitting an online form. Step 4: The descending confirmation unit confirms the climber's descent based on the information of the climber authenticated by the face authentication unit. For example, the descending confirmation unit performs face authentication when the climber arrives at the descending entrance and confirms that the climber has descended. Step 5: The information providing unit provides the information acquired by the mountain entry notification submission unit and the mountain descent confirmation unit to family and friends. For example, the information providing unit sends a message saying "Mr. / Ms. XX has entered the mountain" along with a photo of the climber when he / she enters the mountain. Also, when he / she descends the mountain, the information providing unit sends a message saying "Mr. / Ms. XX has descended the mountain safely."

[0103] 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.

[0104] 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.

[0105] 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.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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 AI 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.

[0120] 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.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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 AI 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.

[0135] 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.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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).

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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 also 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 perform processing similar to that of the specific processing unit 290 using these models.

[0148] 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.

[0149] 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.

[0150] 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 AI 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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).

[0156] 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.

[0157] 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."

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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]

[0170] 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. AI cameras that recognize climbers' faces, a face authentication unit that performs face authentication based on a face image acquired by the AI ​​camera; a mountain entry notification submission unit that automatically submits a mountain entry notification based on the information of the climber authenticated by the face authentication unit; a descending confirmation unit that confirms the climber's descent based on the information of the climber authenticated by the face authentication unit; an information providing unit that provides the information acquired by the mountain entry notification submission unit and the mountain descent confirmation unit to family and friends. A system characterized by:

2. The face authentication unit At the same time as recognizing the climber's face, the system measures their heart rate and body temperature without contact and issues a warning if any abnormalities are detected.

2. The system of claim 1.

3. The face authentication unit Check the climber's equipment and notify them if any equipment is missing.

2. The system of claim 1.

4. The face authentication unit Detecting tension or anxiety in the climber and providing advice to help them relax 2. The system of claim 1.

5. The face authentication unit Provides an AI guide function to support the selection of climbing routes and suggests the best route for the climber.

2. The system of claim 1.

6. The face authentication unit Displaying the climber's past climbing history and providing advice based on past experience 2. The system of claim 1.

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