System

Abstract

An object of a system according to an embodiment is to improve safety during driving.SOLUTION: A system according to an embodiment includes a driving situation analysis unit, a conversation unit, a feedback unit, a state monitoring unit, and an emergency handling unit. The driving situation analysis unit analyzes the driving situation in real time. The conversation unit performs a conversation with the driver based on the driving situation analyzed by the driving situation analysis unit. The feedback unit records the advice or warning provided by the conversation unit and provides feedback after the end of driving. The state monitoring unit monitors the state of the driver and issues a warning when an abnormality is detected. The emergency response unit performs an appropriate response at the time of emergency.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] With conventional technology, it is difficult to ensure safety while driving in real time, and appropriate responses according to the driver's condition are required.

[0005] The system according to the embodiment aims to improve safety during driving. [Means for solving the problem]

[0006] The system according to the embodiment includes a driving situation analysis unit, a conversation unit, a feedback unit, a status monitoring unit, and an emergency response unit. The driving situation analysis unit analyzes the driving situation in real time. The conversation unit converses with the driver based on the driving situation analyzed by the driving situation analysis unit. The feedback unit records advice or warnings provided by the conversation unit and provides feedback after the driving is completed. The status monitoring unit monitors the driver's status and issues a warning if an abnormality is detected. The emergency response unit takes appropriate action in an emergency. [Effects of the Invention]

[0007] The system according to the embodiment can improve safety while driving. [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 AI ​​dash cam system according to the embodiment of the present invention is a system that analyzes driving conditions in real time, converses with the driver, and provides appropriate advice and warnings to help the driver drive safely. As a result, the AI ​​dash cam system supports safe driving in real time and reduces the risk of accidents.

[0029] The AI ​​dashcam system according to the embodiment includes a driving situation analysis unit, a conversation unit, a feedback unit, a status monitoring unit, and an emergency response unit. The driving situation analysis unit analyzes the driving situation in real time. For example, the driving situation analysis unit analyzes the distance to the vehicle ahead, the speed, the status of road signs and traffic lights, etc. using the vehicle's cameras and sensors. The driving situation analysis unit also analyzes the driving situation using the generation AI based on the images and data acquired from the vehicle's cameras and sensors. The conversation unit engages in conversation with the driver based on the driving situation analyzed by the driving situation analysis unit. For example, the conversation unit issues instructions to the driver in the form of, for example, "You are too close to the vehicle ahead. Please maintain a safe distance" or "You are exceeding the speed limit. Please slow down." The conversation unit analyzes the driver's voice instructions and questions and generates appropriate responses. The feedback unit records the advice or warnings provided by the conversation unit and provides feedback after the drive is completed. For example, the feedback unit may advise the driver, for example, "You braked a lot during your drive today. Try to drive more smoothly next time." The state monitoring unit monitors the driver's state and issues a warning if an abnormality is detected. For example, if the driver is feeling drowsy or distracted, the state monitoring unit may issue a warning, for example, "You seem to be feeling drowsy. Please take a break." The emergency response unit takes appropriate action in an emergency. For example, if an accident occurs, the emergency response unit may issue instructions to the driver, for example, "An accident has occurred. Call the police and an ambulance immediately," and take the necessary action. As a result, the AI ​​drive recorder system according to the embodiment can support safe driving in real time and reduce the risk of accidents.

[0030] The driving situation analysis unit can also integrate external data on weather or traffic volume to perform more accurate analysis. For example, when an AI dashcam analyzes driving conditions, the driving situation analysis unit acquires weather data in real time and provides appropriate advice to the driver, taking into account weather conditions such as rain or snow. For example, in rainy weather, the unit may issue instructions such as, "The road is slippery, so please slow down." The driving situation analysis unit also acquires traffic volume data in real time and suggests the optimal route to the driver, taking into account traffic congestion and other conditions. For example, the unit provides information to the driver such as, "The road ahead is congested. We suggest a detour route." The driving situation analysis unit also acquires road construction and accident information in real time to alert the driver. For example, the unit warns the driver with, "Road construction is underway ahead. Please proceed with caution." This integration of external data enables more accurate analysis of driving conditions.

[0031] The driving situation analysis unit can refer to past driving data, learn the driver's driving patterns, and provide individually optimized advice. The driving situation analysis unit, for example, analyzes past driving data and learns the driver's driving patterns. For example, it analyzes the frequency of sudden braking and sudden acceleration, and provides the driver with advice such as, "You brake a lot, so try to drive more smoothly." The driving situation analysis unit also predicts the driver's reaction to specific driving situations based on the driver's past driving history and provides advance advice. For example, it warns the driver by warning the driver that "You have frequently exceeded the speed limit in this section in the past, so please be careful." The driving situation analysis unit also provides individually optimized advice based on the driver's driving style. For example, if the driver regularly uses expressways, it can provide advice focusing on safe driving on expressways. This allows the system to learn the driver's driving patterns and provide individually optimized advice.

[0032] The driving situation analysis unit can also share data from other vehicles to realize cooperative driving. For example, the driving situation analysis unit acquires data from other vehicles in real time to realize cooperative driving. For example, if a vehicle ahead suddenly brakes, it issues a warning to the following vehicle, such as, "The vehicle ahead has suddenly braked. Please be careful." The driving situation analysis unit also adjusts the distance and speed between vehicles through communication with other vehicles. For example, if the vehicle ahead decelerates, it issues an instruction to the following vehicle, such as, "The vehicle ahead is decelerating. Please maintain a safe distance between vehicles." The driving situation analysis unit also suggests the optimal timing for lane changes and overtaking based on the position information of other vehicles. For example, it provides information to the driver in the form of, "There is no vehicle in the left lane, so you can change lanes." This allows the sharing of data from other vehicles to realize cooperative driving.

[0033] The driving situation analysis unit can integrate the driver's health data and provide advice according to their health condition. For example, the driving situation analysis unit acquires the driver's heart rate and blood pressure data in real time and provides advice according to their health condition. For example, if the driver's heart rate increases, the unit issues instructions such as, "Your heart rate is increasing. Take a deep breath and relax." The driving situation analysis unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, the unit encourages the driver to take a break by saying, "You've been driving for a long time. Let's take a break." The driving situation analysis unit can also provide advice to adjust the driver's posture and body movements while driving according to the driver's health condition. For example, the unit issues instructions such as, "Your posture is poor. Drive with your back straight." This allows the driver's health data to be integrated and advice according to their health condition can be provided.

[0034] The conversation unit can refer to the driver's past conversation history and provide individually optimized advice. For example, the conversation unit analyzes the driver's past conversation history and provides individually optimized advice. For example, if a driver has been warned about speeding in the past, the conversation unit issues an instruction such as, "You are exceeding the speed limit. Please slow down." The conversation unit also learns the driver's preferences and habits based on the driver's past questions and instructions and provides individually optimized advice. For example, the conversation unit confirms with the driver by asking, "You chose the same route last time. Would you like to take the same route this time?" The conversation unit also provides advice tailored to the driver's driving style based on the driver's past conversation history. For example, if the driver tends to brake suddenly, the conversation unit issues an instruction such as, "You brake suddenly a lot, so try to drive more smoothly." This makes it possible to refer to the driver's past conversation history and provide individually optimized advice.

[0035] The conversation unit can also cooperate with drivers of other vehicles to realize cooperative driving. For example, if a vehicle ahead suddenly brakes, it warns the following vehicle, saying, "The vehicle ahead has suddenly braked. Please be careful." The conversation unit also adjusts the distance and speed between vehicles through communication with other vehicles. For example, if the vehicle ahead decelerates, it issues an instruction to the following vehicle, saying, "The vehicle ahead is slowing down. Please maintain a safe distance between vehicles." The conversation unit also suggests optimal timing for lane changes and overtaking based on the position information of other vehicles. For example, it provides information to the driver in the form of, "There are no vehicles in the left lane, so you can change lanes." This allows cooperation with drivers of other vehicles to realize cooperative driving.

[0036] The conversation unit can integrate the driver's health data and provide advice according to their health condition. For example, the conversation unit can acquire the driver's heart rate and blood pressure data in real time and provide advice according to their health condition. For example, if the driver's heart rate increases, the conversation unit can issue instructions such as, "Your heart rate is increasing. Take a deep breath and relax." The conversation unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, the conversation unit can urge the driver to take a break by saying, "You've been driving for a long time. Let's take a break." The conversation unit can also provide advice to adjust the driver's posture and body movements while driving according to the driver's health condition. For example, the conversation unit can issue instructions such as, "Your posture is poor. Drive with your back straight." This allows the conversation unit to integrate the driver's health data and provide advice according to their health condition.

[0037] The feedback unit can integrate the driver's health data and provide feedback based on the driver's health status. For example, the feedback unit records heart rate and blood pressure data while driving and provides feedback based on the driver's health status after the drive is completed. For example, the feedback unit may provide advice such as, "It seems your heart rate was high during today's drive. Try to relax and drive more next time." The feedback unit also integrates the driver's driving history and health data to evaluate the driver's health status. For example, if fatigue due to long driving is observed, the feedback unit may provide feedback such as, "Long driving hours have a negative impact on your health, so take regular breaks." The feedback unit may also evaluate the driver's driving style based on the health data and suggest improvements based on the driver's health status. For example, the feedback unit may provide advice such as, "Frequent sudden braking increases your heart rate, so try to drive more smoothly." This allows the driver's health data to be integrated and feedback based on the driver's health status to be provided.

[0038] The feedback unit can integrate the driver's eye tracking data and provide feedback based on their eye movements. For example, the feedback unit records the eye tracking data while driving and provides feedback based on their eye movements after the drive is completed. For example, the feedback unit can provide advice such as, "It seems that your eyes were not focused on the road ahead today. Next time, keep your eyes on the road ahead while driving." The feedback unit can also analyze the driver's eye tracking patterns and evaluate their driving style based on the eye tracking data. For example, if the driver tends to look away in a particular section, the feedback unit can provide feedback such as, "Make sure to pay particular attention to the road ahead while driving in this section." The feedback unit can also suggest improvements based on the driver's eye movements based on the eye tracking data. For example, the feedback unit can provide advice such as, "Frequent eye movements cause distractions, so try to focus more on the road ahead while driving." This allows the feedback unit to integrate the driver's eye tracking data and provide feedback based on their eye movements.

[0039] The feedback unit can also share data from other vehicles and evaluate cooperative driving. The feedback unit, for example, shares driving data from other vehicles and evaluates cooperative driving. For example, based on the distance between the vehicle and the vehicle in front, it provides feedback such as "the vehicle distance was maintained appropriately." The feedback unit also evaluates cooperative driving through communication with other vehicles. For example, when the vehicle in front suddenly brakes, it evaluates whether the following vehicle responded appropriately and provides feedback such as "the vehicle responded appropriately to the sudden braking." The feedback unit also evaluates cooperative driving based on position information from other vehicles. For example, it provides feedback to the driver in the form of "the positional relationship with other vehicles was maintained appropriately." This allows data from other vehicles to be shared and cooperative driving to be evaluated.

[0040] The feedback unit can share the driving history with insurance companies and provide discounts on insurance premiums based on an evaluation of safe driving. For example, the feedback unit can share the driving history with insurance companies and provide discounts on insurance premiums based on an evaluation of safe driving. For example, the feedback unit can notify the driver in a form such as, "Your insurance premium discount will be applied because you rarely braked or accelerated suddenly." The feedback unit can also work with insurance companies to set evaluation criteria for safe driving. For example, the feedback unit can provide information to the driver in a form such as, "If you obey the speed limit and maintain an appropriate distance between vehicles, you will receive a discount on insurance premiums." The feedback unit can also build a system that evaluates safe driving based on the driving history and provides discounts on insurance premiums. For example, the feedback unit can notify the driver in a form such as, "Your insurance premium discount will be applied because your safety driving evaluation was high based on your driving history over the past year." This allows the driving history to be shared with insurance companies and insurance premium discounts to be provided based on an evaluation of safe driving.

[0041] The condition monitoring unit can integrate the driver's health data and provide warnings based on the driver's health condition. For example, the condition monitoring unit acquires the driver's heart rate and blood pressure data in real time and provides warnings based on the driver's health condition. For example, if the driver's heart rate increases, the unit issues a warning such as, "Your heart rate is increasing. Take a deep breath and relax." The condition monitoring unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, the unit can urge the driver to take a break by saying, "You've been driving for a long time. Let's take a break." The condition monitoring unit can also provide advice to adjust the driver's posture and body movements while driving according to the driver's health condition. For example, the unit issues a warning such as, "Your posture is poor. Drive with your back straight." This allows the driver's health data to be integrated and warnings to be provided based on the driver's health condition.

[0042] The state monitoring unit can integrate the driver's eye tracking data and provide warnings based on eye movement. For example, the state monitoring unit acquires eye tracking data while driving in real time and provides warnings based on eye movement. For example, if the driver's eyes are not focused on the road ahead, the state monitoring unit issues a warning such as "Keep your eyes firmly on the road ahead while driving." The state monitoring unit also analyzes the driver's eye pattern based on the eye tracking data and provides warnings based on eye movement. For example, if the driver's eyes move frequently, the state monitoring unit issues a warning such as "Your eyes are moving frequently. Please concentrate on the road ahead while driving." The state monitoring unit also suggests improvements based on the driver's eye movement based on the eye tracking data. For example, the state monitoring unit issues a warning such as "Frequent eye movement will distract you, so please concentrate more on the road ahead while driving." In this way, the state monitoring unit can integrate the driver's eye tracking data and provide warnings based on eye movement.

[0043] The status monitoring unit can also cooperate with drivers of other vehicles to realize cooperative driving. For example, if a vehicle ahead suddenly brakes, it issues a warning to the following vehicle, such as, "The vehicle ahead has suddenly braked. Please be careful." The status monitoring unit also adjusts the distance and speed between vehicles through communication with other vehicles. For example, if the vehicle ahead decelerates, it issues an instruction to the following vehicle, such as, "The vehicle ahead is decelerating. Please maintain a safe distance between vehicles." The status monitoring unit also suggests optimal timing for lane changes and overtaking based on the position information of other vehicles. For example, it provides information to the driver in the form of, "There are no vehicles in the left lane, so you can change lanes." This allows cooperation with drivers of other vehicles to realize cooperative driving.

[0044] The condition monitoring unit can integrate the driver's health data and provide warnings based on the driver's health condition. For example, the condition monitoring unit acquires the driver's heart rate and blood pressure data in real time and provides warnings based on the driver's health condition. For example, if the driver's heart rate increases, the unit issues a warning such as, "Your heart rate is increasing. Take a deep breath and relax." The condition monitoring unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, the unit can urge the driver to take a break by saying, "You've been driving for a long time. Let's take a break." The condition monitoring unit can also provide advice to adjust the driver's posture and body movements while driving according to the driver's health condition. For example, the unit issues a warning such as, "Your posture is poor. Drive with your back straight." This allows the driver's health data to be integrated and warnings to be provided based on the driver's health condition.

[0045] The emergency response department can integrate the driver's health data and provide responses based on their health condition. For example, in an emergency, the emergency response department can obtain the driver's heart rate and blood pressure data in real time and provide responses based on their health condition. For example, if the driver's heart rate suddenly rises, the department can issue instructions such as, "Your heart rate is rising. Take a deep breath and relax." The emergency response department can also provide appropriate responses based on the driver's health data in an emergency. For example, if the driver loses consciousness, the department can issue instructions such as, "The driver has lost consciousness. Call an ambulance immediately." The emergency response department can also provide responses based on the driver's health condition in an emergency. For example, if the driver panics, the department can issue instructions such as, "Take a deep breath and relax" to calm the driver. This allows the emergency response department to integrate the driver's health data and provide responses based on their health condition.

[0046] The emergency response unit can also share data from other vehicles and coordinate emergency responses. For example, in an emergency, the emergency response unit acquires data from other vehicles in real time and coordinates emergency responses. For example, if a vehicle ahead has an accident, it issues a warning to following vehicles such as, "An accident has occurred ahead. Please be careful." The emergency response unit also coordinates emergency responses through communication with other vehicles. For example, if a vehicle ahead suddenly brakes, it issues instructions such as, "The vehicle ahead has suddenly braked. Please be careful," so that following vehicles can respond appropriately. The emergency response unit also coordinates emergency responses based on the position information of other vehicles. For example, it provides information to the driver in the form of, "An accident has occurred ahead. Please move to the left lane." This allows data from other vehicles to be shared and emergency responses to be coordinated.

[0047] The emergency response unit can also cooperate with drivers of other vehicles to coordinate emergency responses. The emergency response unit cooperates with drivers of other vehicles to coordinate emergency responses. For example, if a vehicle ahead has an accident, the emergency response unit issues a warning to following vehicles such as, "An accident has occurred ahead. Please be careful." The emergency response unit also cooperates with other vehicles to coordinate emergency responses through communication with other vehicles. For example, if a vehicle ahead suddenly brakes, the emergency response unit issues an instruction such as, "The vehicle ahead has suddenly braked. Please be careful," so that following vehicles can respond appropriately. The emergency response unit also cooperates with emergency responses based on the position information of other vehicles. For example, the emergency response unit provides information to drivers in the form of, "An accident has occurred ahead. Please move to the left lane." This allows the emergency response to be coordinated with drivers of other vehicles to coordinate emergency responses.

[0048] The emergency response department can integrate the driver's health data and provide responses based on their health condition. For example, in an emergency, the emergency response department can obtain the driver's heart rate and blood pressure data in real time and provide responses based on their health condition. For example, if the driver's heart rate suddenly rises, the department can issue instructions such as, "Your heart rate is rising. Take a deep breath and relax." The emergency response department can also provide appropriate responses based on the driver's health data in an emergency. For example, if the driver loses consciousness, the department can issue instructions such as, "The driver has lost consciousness. Call an ambulance immediately." The emergency response department can also provide responses based on the driver's health condition in an emergency. For example, if the driver panics, the department can issue instructions such as, "Take a deep breath and relax" to calm the driver. This allows the emergency response department to integrate the driver's health data and provide responses based on their health condition.

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

[0050] The driving situation analysis unit can also provide advice to optimize fuel efficiency based on the driver's driving style. For example, fuel efficiency can be improved by instructing the driver to avoid sudden acceleration and braking. The driving situation analysis unit can also suggest optimal routes for eco-driving. For example, it can suggest routes that avoid traffic jams or routes with fewer traffic lights. Furthermore, the driving situation analysis unit can monitor the vehicle's maintenance status and provide maintenance advice to maintain fuel efficiency. For example, it can issue instructions such as, "Your tire pressure is low. Please adjust the tire pressure to the appropriate level." This allows the driver to optimize fuel efficiency and drive in an environmentally friendly manner.

[0051] The driving situation analysis unit can also evaluate the driver's driving skills and provide a training program to improve those skills. For example, it can evaluate the driver's driving technique and suggest training for specific skills. The driving situation analysis unit can also provide an individually optimized training program based on the driver's driving skills. For example, it can suggest training for braking operation for a driver who frequently brakes suddenly. Furthermore, the driving situation analysis unit can monitor the improvement of the driver's driving skills and provide feedback on the progress. For example, it can provide feedback in the form of, "Your braking operation has improved. Please continue to drive smoothly." This allows the driver to improve their driving skills and achieve safe driving.

[0052] The driving situation analysis unit can also provide advice to optimize vehicle performance based on the driver's driving style. For example, it can improve vehicle performance by instructing the driver to optimize engine speed or gear selection. The driving situation analysis unit can also provide maintenance advice to maintain vehicle performance. For example, it can issue an instruction such as, "It's almost time to change your engine oil. Please change it." Furthermore, the driving situation analysis unit can analyze vehicle performance data and provide the driver with advice to improve performance. For example, it can issue advice such as, "Keeping the engine speed at an appropriate level will improve fuel efficiency." This allows the driver to optimize vehicle performance and achieve a comfortable drive.

[0053] The driving situation analysis unit can also share data with other vehicles and provide advice to achieve cooperative driving. For example, if a vehicle ahead suddenly brakes, it can warn the following vehicle by saying, "The vehicle ahead has suddenly braked. Please be careful." The driving situation analysis unit can also provide advice on adjusting the distance between vehicles and speed through communication with other vehicles. For example, if the vehicle ahead decelerates, it can instruct the following vehicle by saying, "The vehicle ahead is slowing down. Please maintain a safe distance between vehicles." Furthermore, the driving situation analysis unit can suggest optimal timing for lane changes and overtaking based on the position information of other vehicles. For example, it can provide information to the driver in the form of, "There is no vehicle in the left lane, so you can change lanes." This allows the sharing of data with other vehicles and the realization of cooperative driving.

[0054] The driving situation analysis unit can also integrate the driver's health data and suggest adjustments to driving style based on their health condition. For example, it can evaluate the driver's health condition based on heart rate and blood pressure data and suggest an appropriate driving style. The driving situation analysis unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, it can urge the driver to take a break by saying, "You've been driving for a long time. Let's take a break." Furthermore, the driving situation analysis unit can provide advice on adjusting posture and body movements while driving based on the driver's health condition. For example, it can issue instructions such as, "Your posture is poor. Drive with your back straight." This makes it possible to integrate the driver's health data and suggest adjustments to driving style based on their health condition.

[0055] The conversation unit can also refer to the driver's past conversation history and provide individually optimized advice. For example, if a driver has been warned about speeding in the past, the conversation unit can issue an instruction such as, "You're exceeding the speed limit. Please slow down." The conversation unit can also learn the driver's preferences and habits based on the driver's past questions and instructions and provide individually optimized advice. For example, the conversation unit can confirm with the driver, "You chose the same route last time. Would you like to take the same route this time?" Furthermore, the conversation unit can provide advice tailored to the driver's driving style based on the driver's past conversation history. For example, if the driver tends to brake suddenly, the conversation unit can issue an instruction such as, "You brake suddenly a lot, so try to drive more smoothly." This makes it possible to provide individually optimized advice by referring to the driver's past conversation history.

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

[0057] Step 1: The driving situation analysis unit analyzes the driving situation in real time. For example, it uses the vehicle's cameras and sensors to analyze the distance to the vehicle ahead, speed, road signs, traffic light status, etc. The generation AI also analyzes the driving situation based on the images and data acquired from the vehicle's cameras and sensors. Step 2: The conversation unit converses with the driver based on the driving situation analyzed by the driving situation analysis unit. For example, it issues instructions to the driver such as, "You are too close to the vehicle ahead. Please maintain a safe distance," or "You are exceeding the speed limit. Please slow down." The generation AI analyzes the driver's voice instructions and questions and generates an appropriate response. Step 3: The feedback unit records the advice or warning provided by the conversation unit and provides feedback after the driving is completed. For example, it may give advice to the driver in the form of, "You braked a lot during today's driving. Try to drive more smoothly next time." Step 4: The condition monitoring unit monitors the driver's condition and issues a warning if an abnormality is detected. For example, if the driver is feeling drowsy or distracted, the unit issues a warning such as, "You seem to be feeling drowsy. Please take a break." Step 5: The emergency response department takes appropriate action in the event of an emergency. For example, if an accident occurs, they will issue instructions to the driver, such as "An accident has occurred. Call the police and an ambulance immediately," and take the necessary action.

[0058] (Example 2) The AI ​​dash cam system according to the embodiment of the present invention is a system that analyzes driving conditions in real time, converses with the driver, and provides appropriate advice and warnings to help the driver drive safely. As a result, the AI ​​dash cam system supports safe driving in real time and reduces the risk of accidents.

[0059] The AI ​​dashcam system according to the embodiment includes a driving situation analysis unit, a conversation unit, a feedback unit, a status monitoring unit, and an emergency response unit. The driving situation analysis unit analyzes the driving situation in real time. For example, the driving situation analysis unit analyzes the distance to the vehicle ahead, the speed, the status of road signs and traffic lights, etc. using the vehicle's cameras and sensors. The driving situation analysis unit also analyzes the driving situation using the generation AI based on the images and data acquired from the vehicle's cameras and sensors. The conversation unit engages in conversation with the driver based on the driving situation analyzed by the driving situation analysis unit. For example, the conversation unit issues instructions to the driver in the form of, for example, "You are too close to the vehicle ahead. Please maintain a safe distance" or "You are exceeding the speed limit. Please slow down." The conversation unit analyzes the driver's voice instructions and questions and generates appropriate responses. The feedback unit records the advice or warnings provided by the conversation unit and provides feedback after the drive is completed. For example, the feedback unit may advise the driver, for example, "You braked a lot during your drive today. Try to drive more smoothly next time." The state monitoring unit monitors the driver's state and issues a warning if an abnormality is detected. For example, if the driver is feeling drowsy or distracted, the state monitoring unit may issue a warning, for example, "You seem to be feeling drowsy. Please take a break." The emergency response unit takes appropriate action in an emergency. For example, if an accident occurs, the emergency response unit may issue instructions to the driver, for example, "An accident has occurred. Call the police and an ambulance immediately," and take the necessary action. As a result, the AI ​​drive recorder system according to the embodiment can support safe driving in real time and reduce the risk of accidents.

[0060] The driving situation analysis unit can also integrate external data on weather or traffic volume to perform more accurate analysis. For example, when an AI dashcam analyzes driving conditions, the driving situation analysis unit acquires weather data in real time and provides appropriate advice to the driver, taking into account weather conditions such as rain or snow. For example, in rainy weather, the unit may issue instructions such as, "The road is slippery, so please slow down." The driving situation analysis unit also acquires traffic volume data in real time and suggests the optimal route to the driver, taking into account traffic congestion and other conditions. For example, the unit provides information to the driver such as, "The road ahead is congested. We suggest a detour route." The driving situation analysis unit also acquires road construction and accident information in real time to alert the driver. For example, the unit warns the driver with, "Road construction is underway ahead. Please proceed with caution." This integration of external data enables more accurate analysis of driving conditions.

[0061] The driving situation analysis unit can refer to past driving data, learn the driver's driving patterns, and provide individually optimized advice. The driving situation analysis unit, for example, analyzes past driving data and learns the driver's driving patterns. For example, it analyzes the frequency of sudden braking and sudden acceleration, and provides the driver with advice such as, "You brake a lot, so try to drive more smoothly." The driving situation analysis unit also predicts the driver's reaction to specific driving situations based on the driver's past driving history and provides advance advice. For example, it warns the driver by warning the driver that "You have frequently exceeded the speed limit in this section in the past, so please be careful." The driving situation analysis unit also provides individually optimized advice based on the driver's driving style. For example, if the driver regularly uses expressways, it can provide advice focusing on safe driving on expressways. This allows the system to learn the driver's driving patterns and provide individually optimized advice.

[0062] The driving situation analysis unit uses the emotion estimation function to analyze the driver's emotional state and can provide advice encouraging relaxation if stress or impatience is observed. The driving situation analysis unit, for example, analyzes the driver's facial expressions and voice to detect signs of stress or impatience. For example, if the driver's voice tone becomes higher or the driver's face looks tense, the unit provides advice such as "Please drive in a relaxed manner." The driving situation analysis unit also analyzes the driver's heart rate and breathing data to evaluate the driver's stress level. For example, if the driver's heart rate rises sharply, the unit encourages the driver to relax by saying, "Take a deep breath and relax." The driving situation analysis unit also provides relaxing music or audio guidance according to the driver's emotional state. For example, if the driver is feeling stressed, relaxing music can be played to calm the driver. This allows the system to analyze the driver's emotional state and provide advice encouraging relaxation.

[0063] The driving situation analysis unit can also share data from other vehicles to realize cooperative driving. For example, the driving situation analysis unit acquires data from other vehicles in real time to realize cooperative driving. For example, if a vehicle ahead suddenly brakes, it issues a warning to the following vehicle, such as, "The vehicle ahead has suddenly braked. Please be careful." The driving situation analysis unit also adjusts the distance and speed between vehicles through communication with other vehicles. For example, if the vehicle ahead decelerates, it issues an instruction to the following vehicle, such as, "The vehicle ahead is decelerating. Please maintain a safe distance between vehicles." The driving situation analysis unit also suggests the optimal timing for lane changes and overtaking based on the position information of other vehicles. For example, it provides information to the driver in the form of, "There is no vehicle in the left lane, so you can change lanes." This allows the sharing of data from other vehicles to realize cooperative driving.

[0064] The driving situation analysis unit can integrate the driver's health data and provide advice according to their health condition. For example, the driving situation analysis unit acquires the driver's heart rate and blood pressure data in real time and provides advice according to their health condition. For example, if the driver's heart rate increases, the unit issues instructions such as, "Your heart rate is increasing. Take a deep breath and relax." The driving situation analysis unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, the unit encourages the driver to take a break by saying, "You've been driving for a long time. Let's take a break." The driving situation analysis unit can also provide advice to adjust the driver's posture and body movements while driving according to the driver's health condition. For example, the unit issues instructions such as, "Your posture is poor. Drive with your back straight." This allows the driver's health data to be integrated and advice according to their health condition can be provided.

[0065] The driving situation analysis unit uses the emotion estimation function to provide music and audio guidance according to the driver's emotional state, thereby promoting relaxation while driving. The driving situation analysis unit, for example, analyzes the driver's emotional state and provides music with a relaxing effect. For example, if the driver is feeling stressed, classical music with a relaxing effect is played. The driving situation analysis unit also provides audio guidance to encourage relaxation according to the driver's emotional state. For example, if the driver is feeling anxious, audio guidance such as "Take a deep breath and relax" is played. The driving situation analysis unit also monitors the driver's emotional state in real time and provides content with a relaxing effect at an appropriate time. For example, if the driver is tense, natural sounds with a relaxing effect are played. In this way, music and audio guidance according to the driver's emotional state are provided, promoting relaxation.

[0066] The conversation unit can refer to the driver's past conversation history and provide individually optimized advice. For example, the conversation unit analyzes the driver's past conversation history and provides individually optimized advice. For example, if a driver has been warned about speeding in the past, the conversation unit issues an instruction such as, "You are exceeding the speed limit. Please slow down." The conversation unit also learns the driver's preferences and habits based on the driver's past questions and instructions and provides individually optimized advice. For example, the conversation unit confirms with the driver by asking, "You chose the same route last time. Would you like to take the same route this time?" The conversation unit also provides advice tailored to the driver's driving style based on the driver's past conversation history. For example, if the driver tends to brake suddenly, the conversation unit issues an instruction such as, "You brake suddenly a lot, so try to drive more smoothly." This makes it possible to refer to the driver's past conversation history and provide individually optimized advice.

[0067] The conversation unit can analyze the tone and speed of the driver's voice and provide advice according to their emotional state. For example, the conversation unit analyzes the tone and speed of the driver's voice and provides advice according to their emotional state. For example, if the driver's voice gets higher or faster, the conversation unit issues instructions such as "Drive relaxed." The conversation unit also evaluates the driver's emotional state based on the tone and speed of the driver's voice and provides appropriate advice. For example, if the driver is feeling impatient, the conversation unit encourages the driver to relax by saying, "Drive slowly and without rushing." The conversation unit also monitors the tone and speed of the driver's voice in real time and provides advice according to their emotional state. For example, if the driver's voice gets lower or they speak more slowly, the conversation unit issues instructions such as, "You seem to be feeling drowsy. Take a break." This makes it possible to analyze the tone and speed of the driver's voice and provide advice according to their emotional state.

[0068] The conversation unit uses the emotion estimation function to analyze the driver's emotional state and can provide advice encouraging relaxation if stress or impatience is observed. The conversation unit, for example, analyzes the driver's facial expressions and voice to detect signs of stress or impatience. For example, if the driver's voice tone becomes higher or their face looks tense, the conversation unit provides advice such as "Please drive in a relaxed state." The conversation unit also analyzes the driver's heart rate and breathing data to evaluate their stress level. For example, if their heart rate rises sharply, the conversation unit encourages the driver to relax by saying, "Take a deep breath and relax." The conversation unit also provides relaxing music or audio guidance according to the driver's emotional state. For example, if the driver is feeling stressed, relaxing music can be played to calm the driver. This makes it possible to analyze the driver's emotional state and provide advice encouraging relaxation.

[0069] The conversation unit can also cooperate with drivers of other vehicles to realize cooperative driving. For example, if a vehicle ahead suddenly brakes, it warns the following vehicle, saying, "The vehicle ahead has suddenly braked. Please be careful." The conversation unit also adjusts the distance and speed between vehicles through communication with other vehicles. For example, if the vehicle ahead decelerates, it issues an instruction to the following vehicle, saying, "The vehicle ahead is slowing down. Please maintain a safe distance between vehicles." The conversation unit also suggests optimal timing for lane changes and overtaking based on the position information of other vehicles. For example, it provides information to the driver in the form of, "There are no vehicles in the left lane, so you can change lanes." This allows cooperation with drivers of other vehicles to realize cooperative driving.

[0070] The conversation unit can integrate the driver's health data and provide advice according to their health condition. For example, the conversation unit can acquire the driver's heart rate and blood pressure data in real time and provide advice according to their health condition. For example, if the driver's heart rate increases, the conversation unit can issue instructions such as, "Your heart rate is increasing. Take a deep breath and relax." The conversation unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, the conversation unit can urge the driver to take a break by saying, "You've been driving for a long time. Let's take a break." The conversation unit can also provide advice to adjust the driver's posture and body movements while driving according to the driver's health condition. For example, the conversation unit can issue instructions such as, "Your posture is poor. Drive with your back straight." This allows the conversation unit to integrate the driver's health data and provide advice according to their health condition.

[0071] The conversation unit uses the emotion estimation function to provide music and audio guidance that correspond to the driver's emotional state, thereby promoting relaxation while driving. The conversation unit, for example, analyzes the driver's emotional state and provides music with a relaxing effect. For example, if the driver is feeling stressed, it plays classical music that has a relaxing effect. The conversation unit also provides audio guidance that encourages relaxation according to the driver's emotional state. For example, if the driver is feeling anxious, it plays audio guidance such as "Take a deep breath and relax." The conversation unit also monitors the driver's emotional state in real time and provides content with a relaxing effect at an appropriate time. For example, if the driver is tense, it plays natural sounds that have a relaxing effect. In this way, music and audio guidance that correspond to the driver's emotional state can be provided, promoting relaxation.

[0072] The feedback unit can also record the driver's emotional state and provide feedback based on the emotion. For example, the feedback unit records the driver's emotional state while driving and provides feedback based on the emotion after the drive is completed. For example, the feedback unit may provide advice such as, "Today's drive was stressful. Next time, drive more relaxed." The feedback unit also integrates the driving history and emotional data to analyze the driver's emotional patterns. For example, if stress tends to increase in a particular section, the feedback unit provides feedback such as, "Drive especially carefully in this section." The feedback unit also evaluates the driver's driving style based on the emotional data and suggests improvements based on the emotion. For example, the feedback unit may provide advice such as, "Frequent sudden braking increases stress, so try to drive more smoothly." This makes it possible to record the driver's emotional state and provide feedback based on the emotion.

[0073] The feedback unit can integrate the driver's health data and provide feedback based on the driver's health status. For example, the feedback unit records heart rate and blood pressure data while driving and provides feedback based on the driver's health status after the drive is completed. For example, the feedback unit may provide advice such as, "It seems your heart rate was high during today's drive. Try to relax and drive more next time." The feedback unit also integrates the driver's driving history and health data to evaluate the driver's health status. For example, if fatigue due to long driving is observed, the feedback unit may provide feedback such as, "Long driving hours have a negative impact on your health, so take regular breaks." The feedback unit may also evaluate the driver's driving style based on the health data and suggest improvements based on the driver's health status. For example, the feedback unit may provide advice such as, "Frequent sudden braking increases your heart rate, so try to drive more smoothly." This allows the driver's health data to be integrated and feedback based on the driver's health status to be provided.

[0074] The feedback unit can integrate the driver's eye tracking data and provide feedback based on their eye movements. For example, the feedback unit records the eye tracking data while driving and provides feedback based on their eye movements after the drive is completed. For example, the feedback unit can provide advice such as, "It seems that your eyes were not focused on the road ahead today. Next time, keep your eyes on the road ahead while driving." The feedback unit can also analyze the driver's eye tracking patterns and evaluate their driving style based on the eye tracking data. For example, if the driver tends to look away in a particular section, the feedback unit can provide feedback such as, "Make sure to pay particular attention to the road ahead while driving in this section." The feedback unit can also suggest improvements based on the driver's eye movements based on the eye tracking data. For example, the feedback unit can provide advice such as, "Frequent eye movements cause distractions, so try to focus more on the road ahead while driving." This allows the feedback unit to integrate the driver's eye tracking data and provide feedback based on their eye movements.

[0075] The feedback unit can also share data from other vehicles and evaluate cooperative driving. The feedback unit, for example, shares driving data from other vehicles and evaluates cooperative driving. For example, based on the distance between the vehicle and the vehicle in front, it provides feedback such as "the vehicle distance was maintained appropriately." The feedback unit also evaluates cooperative driving through communication with other vehicles. For example, when the vehicle in front suddenly brakes, it evaluates whether the following vehicle responded appropriately and provides feedback such as "the vehicle responded appropriately to the sudden braking." The feedback unit also evaluates cooperative driving based on position information from other vehicles. For example, it provides feedback to the driver in the form of "the positional relationship with other vehicles was maintained appropriately." This allows data from other vehicles to be shared and cooperative driving to be evaluated.

[0076] The feedback unit can share the driving history with insurance companies and provide discounts on insurance premiums based on an evaluation of safe driving. For example, the feedback unit can share the driving history with insurance companies and provide discounts on insurance premiums based on an evaluation of safe driving. For example, the feedback unit can notify the driver in a form such as, "Your insurance premium discount will be applied because you rarely braked or accelerated suddenly." The feedback unit can also work with insurance companies to set evaluation criteria for safe driving. For example, the feedback unit can provide information to the driver in a form such as, "If you obey the speed limit and maintain an appropriate distance between vehicles, you will receive a discount on insurance premiums." The feedback unit can also build a system that evaluates safe driving based on the driving history and provides discounts on insurance premiums. For example, the feedback unit can notify the driver in a form such as, "Your insurance premium discount will be applied because your safety driving evaluation was high based on your driving history over the past year." This allows the driving history to be shared with insurance companies and insurance premium discounts to be provided based on an evaluation of safe driving.

[0077] The feedback unit can use the emotion estimation function to provide a driving evaluation based on the driver's emotional state and provide emotion-based feedback. The feedback unit, for example, records the driver's emotional state during driving and provides emotion-based feedback after the drive is completed. For example, the feedback unit provides advice such as, "It seems that today's drive was stressful. Next time, drive more relaxed." The feedback unit also evaluates the driver's driving style based on the emotion data and suggests improvements based on the emotion. For example, the feedback unit provides advice such as, "Frequent sudden braking increases stress, so try to drive more smoothly." The feedback unit also analyzes the driver's emotional patterns based on the emotion data and evaluates the driving style. For example, if stress tends to increase in a specific section, the feedback unit provides feedback such as, "Drive especially carefully in this section." This makes it possible to provide a driving evaluation based on the driver's emotional state and provide emotion-based feedback.

[0078] The condition monitoring unit can integrate the driver's health data and provide warnings based on the driver's health condition. For example, the condition monitoring unit acquires the driver's heart rate and blood pressure data in real time and provides warnings based on the driver's health condition. For example, if the driver's heart rate increases, the unit issues a warning such as, "Your heart rate is increasing. Take a deep breath and relax." The condition monitoring unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, the unit can urge the driver to take a break by saying, "You've been driving for a long time. Let's take a break." The condition monitoring unit can also provide advice to adjust the driver's posture and body movements while driving according to the driver's health condition. For example, the unit issues a warning such as, "Your posture is poor. Drive with your back straight." This allows the driver's health data to be integrated and warnings to be provided based on the driver's health condition.

[0079] The state monitoring unit can integrate the driver's eye tracking data and provide warnings based on eye movement. For example, the state monitoring unit acquires eye tracking data while driving in real time and provides warnings based on eye movement. For example, if the driver's eyes are not focused on the road ahead, the state monitoring unit issues a warning such as "Keep your eyes firmly on the road ahead while driving." The state monitoring unit also analyzes the driver's eye pattern based on the eye tracking data and provides warnings based on eye movement. For example, if the driver's eyes move frequently, the state monitoring unit issues a warning such as "Your eyes are moving frequently. Please concentrate on the road ahead while driving." The state monitoring unit also suggests improvements based on the driver's eye movement based on the eye tracking data. For example, the state monitoring unit issues a warning such as "Frequent eye movement will distract you, so please concentrate more on the road ahead while driving." In this way, the state monitoring unit can integrate the driver's eye tracking data and provide warnings based on eye movement.

[0080] The state monitoring unit uses the emotion estimation function to analyze the driver's emotional state and can provide a warning encouraging the driver to relax if stress or impatience is observed. The state monitoring unit, for example, analyzes the driver's facial expressions and voice to detect signs of stress or impatience. For example, if the driver's voice tone becomes higher or the driver's face looks tense, a warning such as "Please drive while relaxing" is provided. The state monitoring unit also analyzes the driver's heart rate and breathing data to evaluate the driver's stress level. For example, if the driver's heart rate rises sharply, a warning encouraging the driver to relax is provided, such as "Take a deep breath and relax." The state monitoring unit also provides relaxing music or audio guidance according to the driver's emotional state. For example, if the driver is feeling stressed, relaxing music can be played to calm the driver. This makes it possible to analyze the driver's emotional state and provide a warning encouraging the driver to relax.

[0081] The status monitoring unit can also cooperate with drivers of other vehicles to realize cooperative driving. For example, if a vehicle ahead suddenly brakes, it issues a warning to the following vehicle, such as, "The vehicle ahead has suddenly braked. Please be careful." The status monitoring unit also adjusts the distance and speed between vehicles through communication with other vehicles. For example, if the vehicle ahead decelerates, it issues an instruction to the following vehicle, such as, "The vehicle ahead is decelerating. Please maintain a safe distance between vehicles." The status monitoring unit also suggests optimal timing for lane changes and overtaking based on the position information of other vehicles. For example, it provides information to the driver in the form of, "There are no vehicles in the left lane, so you can change lanes." This allows cooperation with drivers of other vehicles to realize cooperative driving.

[0082] The condition monitoring unit can integrate the driver's health data and provide warnings based on the driver's health condition. For example, the condition monitoring unit acquires the driver's heart rate and blood pressure data in real time and provides warnings based on the driver's health condition. For example, if the driver's heart rate increases, the unit issues a warning such as, "Your heart rate is increasing. Take a deep breath and relax." The condition monitoring unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, the unit can urge the driver to take a break by saying, "You've been driving for a long time. Let's take a break." The condition monitoring unit can also provide advice to adjust the driver's posture and body movements while driving according to the driver's health condition. For example, the unit issues a warning such as, "Your posture is poor. Drive with your back straight." This allows the driver's health data to be integrated and warnings to be provided based on the driver's health condition.

[0083] The state monitoring unit uses the emotion estimation function to provide music and audio guidance according to the driver's emotional state, thereby promoting relaxation while driving. The state monitoring unit, for example, analyzes the driver's emotional state and provides music with a relaxing effect. For example, if the driver is feeling stressed, classical music with a relaxing effect is played. The state monitoring unit also provides audio guidance to encourage relaxation according to the driver's emotional state. For example, if the driver is feeling anxious, audio guidance such as "Take a deep breath and relax" is played. The state monitoring unit also monitors the driver's emotional state in real time and provides content with a relaxing effect at an appropriate time. For example, if the driver is tense, natural sounds with a relaxing effect are played. In this way, music and audio guidance according to the driver's emotional state are provided, promoting relaxation.

[0084] The emergency response department can integrate the driver's health data and provide responses based on their health condition. For example, in an emergency, the emergency response department can obtain the driver's heart rate and blood pressure data in real time and provide responses based on their health condition. For example, if the driver's heart rate suddenly rises, the department can issue instructions such as, "Your heart rate is rising. Take a deep breath and relax." The emergency response department can also provide appropriate responses based on the driver's health data in an emergency. For example, if the driver loses consciousness, the department can issue instructions such as, "The driver has lost consciousness. Call an ambulance immediately." The emergency response department can also provide responses based on the driver's health condition in an emergency. For example, if the driver panics, the department can issue instructions such as, "Take a deep breath and relax" to calm the driver. This allows the emergency response department to integrate the driver's health data and provide responses based on their health condition.

[0085] The emergency response unit can also share data from other vehicles and coordinate emergency responses. For example, in an emergency, the emergency response unit acquires data from other vehicles in real time and coordinates emergency responses. For example, if a vehicle ahead has an accident, it issues a warning to following vehicles such as, "An accident has occurred ahead. Please be careful." The emergency response unit also coordinates emergency responses through communication with other vehicles. For example, if a vehicle ahead suddenly brakes, it issues instructions such as, "The vehicle ahead has suddenly braked. Please be careful," so that following vehicles can respond appropriately. The emergency response unit also coordinates emergency responses based on the position information of other vehicles. For example, it provides information to the driver in the form of, "An accident has occurred ahead. Please move to the left lane." This allows data from other vehicles to be shared and emergency responses to be coordinated.

[0086] The emergency response unit can use the emotion estimation function to analyze the driver's emotional state and provide a response that encourages the driver to relax so as not to panic. For example, the emergency response unit can analyze the driver's facial expressions and voice in an emergency and provide a response that encourages the driver to relax so as not to panic. For example, if the driver's voice tone becomes higher or the driver's face looks tense, the emergency response unit can issue instructions such as "Please drive relaxed." The emergency response unit can also analyze the driver's heart rate and breathing data in an emergency and provide a response that encourages the driver to relax so as not to panic. For example, if the driver's heart rate rises sharply, the emergency response unit can issue instructions such as "Take a deep breath and relax." The emergency response unit can also provide relaxing music or audio guidance according to the driver's emotional state in an emergency. For example, if the driver is in a panic, relaxing music can be played to calm the driver. In this way, the driver's emotional state can be analyzed and a response that encourages the driver to relax so as not to panic can be provided.

[0087] The emergency response unit can also cooperate with drivers of other vehicles to coordinate emergency responses. The emergency response unit cooperates with drivers of other vehicles to coordinate emergency responses. For example, if a vehicle ahead has an accident, the emergency response unit issues a warning to following vehicles such as, "An accident has occurred ahead. Please be careful." The emergency response unit also cooperates with other vehicles to coordinate emergency responses through communication with other vehicles. For example, if a vehicle ahead suddenly brakes, the emergency response unit issues an instruction such as, "The vehicle ahead has suddenly braked. Please be careful," so that following vehicles can respond appropriately. The emergency response unit also cooperates with emergency responses based on the position information of other vehicles. For example, the emergency response unit provides information to drivers in the form of, "An accident has occurred ahead. Please move to the left lane." This allows the emergency response to be coordinated with drivers of other vehicles to coordinate emergency responses.

[0088] The emergency response department can integrate the driver's health data and provide responses based on their health condition. For example, in an emergency, the emergency response department can obtain the driver's heart rate and blood pressure data in real time and provide responses based on their health condition. For example, if the driver's heart rate suddenly rises, the department can issue instructions such as, "Your heart rate is rising. Take a deep breath and relax." The emergency response department can also provide appropriate responses based on the driver's health data in an emergency. For example, if the driver loses consciousness, the department can issue instructions such as, "The driver has lost consciousness. Call an ambulance immediately." The emergency response department can also provide responses based on the driver's health condition in an emergency. For example, if the driver panics, the department can issue instructions such as, "Take a deep breath and relax" to calm the driver. This allows the emergency response department to integrate the driver's health data and provide responses based on their health condition.

[0089] The emergency response unit uses the emotion estimation function to provide music and audio guidance according to the driver's emotional state, thereby promoting relaxation in emergencies. For example, the emergency response unit analyzes the driver's emotional state in an emergency and provides music with a relaxing effect. For example, if the driver is in a panic, classical music with a relaxing effect is played. The emergency response unit also provides audio guidance to encourage relaxation according to the driver's emotional state in an emergency. For example, if the driver is anxious, audio guidance such as "Take a deep breath and relax" is played. The emergency response unit also monitors the driver's emotional state in real time in an emergency and provides content with a relaxing effect at an appropriate time. For example, if the driver is nervous, natural sounds with a relaxing effect are played. In this way, music and audio guidance according to the driver's emotional state can be provided to promote relaxation in emergencies.

[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 driving situation analysis unit can also provide advice to optimize fuel efficiency based on the driver's driving style. For example, fuel efficiency can be improved by instructing the driver to avoid sudden acceleration and braking. The driving situation analysis unit can also suggest optimal routes for eco-driving. For example, it can suggest routes that avoid traffic jams or routes with fewer traffic lights. Furthermore, the driving situation analysis unit can monitor the vehicle's maintenance status and provide maintenance advice to maintain fuel efficiency. For example, it can issue instructions such as, "Your tire pressure is low. Please adjust the tire pressure to the appropriate level." This allows the driver to optimize fuel efficiency and drive in an environmentally friendly manner.

[0092] The driving situation analysis unit can also evaluate the driver's driving skills and provide a training program to improve those skills. For example, it can evaluate the driver's driving technique and suggest training for specific skills. The driving situation analysis unit can also provide an individually optimized training program based on the driver's driving skills. For example, it can suggest training for braking operation for a driver who frequently brakes suddenly. Furthermore, the driving situation analysis unit can monitor the improvement of the driver's driving skills and provide feedback on the progress. For example, it can provide feedback in the form of, "Your braking operation has improved. Please continue to drive smoothly." This allows the driver to improve their driving skills and achieve safe driving.

[0093] The driving situation analysis unit can also provide advice to optimize vehicle performance based on the driver's driving style. For example, it can improve vehicle performance by instructing the driver to optimize engine speed or gear selection. The driving situation analysis unit can also provide maintenance advice to maintain vehicle performance. For example, it can issue an instruction such as, "It's almost time to change your engine oil. Please change it." Furthermore, the driving situation analysis unit can analyze vehicle performance data and provide the driver with advice to improve performance. For example, it can issue advice such as, "Keeping the engine speed at an appropriate level will improve fuel efficiency." This allows the driver to optimize vehicle performance and achieve a comfortable drive.

[0094] The driving situation analysis unit can also use the emotion estimation function to provide advice to adjust the driver's driving style based on the driver's emotional state. For example, if the driver is feeling stressed, it can suggest a driving style that has a relaxing effect. The driving situation analysis unit can also suggest taking a break while driving based on the driver's emotional state. For example, it can encourage the driver to take a break by saying, "You're feeling stressed. Let's take a break." Furthermore, the driving situation analysis unit can monitor the driver's emotional state and provide advice that has a relaxing effect at the appropriate time. For example, it can encourage the driver to take a deep breath and relax. This allows the driver to achieve a driving style that suits their emotional state and drive with less stress.

[0095] The driving situation analysis unit can also share data with other vehicles and provide advice to achieve cooperative driving. For example, if a vehicle ahead suddenly brakes, it can warn the following vehicle by saying, "The vehicle ahead has suddenly braked. Please be careful." The driving situation analysis unit can also provide advice on adjusting the distance between vehicles and speed through communication with other vehicles. For example, if the vehicle ahead decelerates, it can instruct the following vehicle by saying, "The vehicle ahead is slowing down. Please maintain a safe distance between vehicles." Furthermore, the driving situation analysis unit can suggest optimal timing for lane changes and overtaking based on the position information of other vehicles. For example, it can provide information to the driver in the form of, "There is no vehicle in the left lane, so you can change lanes." This allows the sharing of data with other vehicles and the realization of cooperative driving.

[0096] The driving situation analysis unit can also integrate the driver's health data and suggest adjustments to driving style based on their health condition. For example, it can evaluate the driver's health condition based on heart rate and blood pressure data and suggest an appropriate driving style. The driving situation analysis unit can also predict fatigue due to long driving hours based on the driver's health data and encourage the driver to take a break. For example, it can urge the driver to take a break by saying, "You've been driving for a long time. Let's take a break." Furthermore, the driving situation analysis unit can provide advice on adjusting posture and body movements while driving based on the driver's health condition. For example, it can issue instructions such as, "Your posture is poor. Drive with your back straight." This makes it possible to integrate the driver's health data and suggest adjustments to driving style based on their health condition.

[0097] The driving situation analysis unit can also use the emotion estimation function to provide advice to promote relaxation while driving based on the driver's emotional state. For example, if the driver is feeling stressed, it can provide relaxing music. The driving situation analysis unit can also provide audio guidance to promote relaxation depending on the driver's emotional state. For example, if the driver is feeling anxious, it can play audio guidance such as "Take a deep breath and relax." Furthermore, the driving situation analysis unit can monitor the driver's emotional state in real time and provide content with a relaxing effect at the appropriate time. For example, if the driver is feeling tense, it can play natural sounds with a relaxing effect. This makes it possible to promote relaxation while driving based on the driver's emotional state.

[0098] The conversation unit can also refer to the driver's past conversation history and provide individually optimized advice. For example, if a driver has been warned about speeding in the past, the conversation unit can issue an instruction such as, "You're exceeding the speed limit. Please slow down." The conversation unit can also learn the driver's preferences and habits based on the driver's past questions and instructions and provide individually optimized advice. For example, the conversation unit can confirm with the driver, "You chose the same route last time. Would you like to take the same route this time?" Furthermore, the conversation unit can provide advice tailored to the driver's driving style based on the driver's past conversation history. For example, if the driver tends to brake suddenly, the conversation unit can issue an instruction such as, "You brake suddenly a lot, so try to drive more smoothly." This makes it possible to provide individually optimized advice by referring to the driver's past conversation history.

[0099] The conversation unit can also analyze the tone and speed of the driver's voice and provide advice according to their emotional state. For example, if the driver's voice gets higher or they start speaking faster, the conversation unit can issue instructions such as "Drive relaxed." The conversation unit can also evaluate the driver's emotional state based on the tone and speed of the driver's voice and provide appropriate advice. For example, if the driver seems impatient, the conversation unit can encourage the driver to relax by saying, "Drive slowly and without rushing." Furthermore, the conversation unit can monitor the driver's tone and speed of voice in real time and provide advice according to their emotional state. For example, if the driver's voice gets lower or they start speaking slowly, the conversation unit can issue instructions such as, "You seem to be feeling drowsy. Take a break." This makes it possible to analyze the tone and speed of the driver's voice and provide advice according to their emotional state.

[0100] The conversation unit can use its emotion estimation function to analyze the driver's emotional state and provide advice encouraging relaxation if stress or impatience is observed. For example, it can analyze the driver's facial expressions and voice to detect signs of stress or impatience. For example, if the driver's voice tone becomes higher or their face looks tense, it can provide advice such as "Please drive relaxed." The conversation unit can also analyze the driver's heart rate and breathing data to evaluate their stress level. For example, if their heart rate rises sharply, it can encourage the driver to relax by saying, "Take a deep breath and relax." Furthermore, the conversation unit can provide relaxing music or audio guidance depending on the driver's emotional state. For example, if the driver is feeling stressed, it can play relaxing music to calm the driver. This makes it possible to analyze the driver's emotional state and provide advice encouraging relaxation.

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

[0102] Step 1: The driving situation analysis unit analyzes the driving situation in real time. For example, it uses the vehicle's cameras and sensors to analyze the distance to the vehicle ahead, speed, road signs, traffic light status, etc. The generation AI also analyzes the driving situation based on the images and data acquired from the vehicle's cameras and sensors. Step 2: The conversation unit converses with the driver based on the driving situation analyzed by the driving situation analysis unit. For example, it issues instructions to the driver such as, "You are too close to the vehicle ahead. Please maintain a safe distance," or "You are exceeding the speed limit. Please slow down." The generation AI analyzes the driver's voice instructions and questions and generates an appropriate response. Step 3: The feedback unit records the advice or warning provided by the conversation unit and provides feedback after the driving is completed. For example, it may give advice to the driver in the form of, "You braked a lot during today's driving. Try to drive more smoothly next time." Step 4: The condition monitoring unit monitors the driver's condition and issues a warning if an abnormality is detected. For example, if the driver is feeling drowsy or distracted, the unit issues a warning such as, "You seem to be feeling drowsy. Please take a break." Step 5: The emergency response department takes appropriate action in the event of an emergency. For example, if an accident occurs, they will issue instructions to the driver, such as "An accident has occurred. Call the police and an ambulance immediately," and take the necessary action.

[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 (registered trademark) (Internet search engine).<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 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.

[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 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.

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

[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 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.

[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 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.

[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. a driving situation analysis unit that analyzes driving situations in real time; a conversation unit that converses with the driver based on the driving situation analyzed by the driving situation analysis unit; a feedback unit that records the advice or warning provided by the conversation unit and provides feedback after driving is completed; a state monitoring unit that monitors the state of the driver and issues a warning when an abnormality is detected; and an emergency response department that takes appropriate action in the event of an emergency. A system characterized by:

2. The driving situation analysis unit Integrate external weather or traffic data for more accurate analysis 2. The system of claim 1.

3. The driving situation analysis unit It references past driving data, learns the driver's driving patterns, and provides personalized advice 2. The system of claim 1.

4. The driving situation analysis unit Analyzes the driver's emotional state and provides advice to encourage relaxation if stress or impatience is detected 2. The system of claim 1.

5. The driving situation analysis unit Sharing data from other vehicles to achieve cooperative driving 2. The system of claim 1.

6. The driving situation analysis unit Integrates driver health data and provides advice based on health status 2. The system of claim 1.

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