Riding direction sensing method and system based on voice control instruction recognition and helmet

Abstract

The invention relates to the technical field of riding wearable equipment, and discloses a riding direction sensing method, system and helmet based on voice control instruction recognition, and the method comprises the steps: receiving a voice instruction of a rider through an embedded voice recognition module; the head motion sensing module detects and analyzes the motion trail and posture change of the head of a rider, monitors the orientation, rotation speed and head motion state of the head of the rider in real time, and senses and obtains head motion data of the head of the rider in real time; acquiring environment sensing data in real time through the environment sensing module, and feeding back the environment sensing data to the cloud navigation processing system; the cloud navigation processing system receives the voice instruction, the head motion data and the environment perception data for fusion processing, and calculates the current position, the driving direction and the target route of the rider; and the cloud navigation processing system generates a corresponding voice navigation instruction and feeds back a riding route planned in real time to the rider through the audio playing module, so that safer and more convenient riding experience is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of cycling wearable equipment, and particularly to a cycling direction sensing method, system and helmet based on voice control command recognition. Background Art

[0002] With the development of smart hardware and intelligent transportation systems, the safety and navigation needs of cyclists are increasingly valued. Especially for cyclists, obtaining real-time navigation information and maintaining safety during riding has become an important issue. Traditional cycling navigation systems mainly rely on visual navigation and manual operation. At present, many navigation systems use map displays, route instructions or prompts on mobile phone screens to guide cyclists. Such systems rely on the cyclist's eyes to focus on the screen of the mobile phone or other device, which may cause the cyclist to be distracted, thereby increasing the risk of accidents during riding. Especially when driving at high speeds or in complex traffic environments, excessive reliance on visual information not only affects reaction time, but may also distract the cyclist from the surrounding environment and increase the chance of accidents. Some navigation systems also require the rider to manually operate the device (for example, through a touch screen, buttons, etc.) to select a route, confirm instructions, or adjust navigation settings. This method also requires the rider to be distracted during riding, increasing the risk of accidents, especially when driving fast or frequently changing routes, the rider's hands need to be operated frequently and cannot focus on riding itself.

[0003] Therefore, a new solution is urgently needed for the cyclist's navigation system, which can achieve interference-free operation, real-time feedback, and provide effective navigation guidance without visual concentration or manual intervention, so as to solve the problems that most existing cycling navigation systems require cyclists to check the device screen or road signs, which distracts the cyclist and increases the risk of accidents; and existing cycling equipment requires cyclists to manually operate to confirm navigation instructions, which is inconvenient and affects the smoothness of the riding process. Summary of the invention

[0004] Based on this, in order to cope with these limitations, the purpose of the present invention is to propose a riding direction sensing method, system and helmet based on voice control command recognition, aiming to improve the navigation experience and riding safety during riding by integrating voice control command recognition and direction sensing functions. The core goal of this technical solution is to use voice commands to control the navigation function, combine the sensors in the helmet to monitor the rider's head movement in real time, and dynamically adjust the navigation commands, so as to achieve a safer and more convenient riding experience.

[0005] A riding direction sensing method based on voice control command recognition comprises the following steps:

[0006] Receive the rider's voice commands through the embedded voice recognition module;

[0007] The head movement sensing module detects and analyzes the movement trajectory and posture changes of the rider's head, monitors the rider's head direction, rotation speed and head movement status in real time, and senses and obtains the rider's head movement data in real time;

[0008] The environmental perception module obtains environmental perception data in real time and feeds voice commands, head movement data and environmental perception data back to the cloud navigation processing system;

[0009] The cloud-based navigation processing system receives voice commands, head movement data, and environmental perception data for fusion processing to calculate the rider’s current location, driving direction, and target route;

[0010] The cloud navigation processing system generates corresponding voice navigation instructions and feeds back the real-time planned riding route to the rider through the audio playback module;

[0011] If the actual cycling route deviates from the real-time planned cycling route, the cloud navigation processing system automatically adjusts the voice navigation instructions and provides updated navigation information through the audio playback module.

[0012] As a further solution of the present invention, the embedded voice recognition module includes a vehicle-mounted microphone or a microphone in a worn smart helmet, which is used to receive voice commands issued by the rider, wherein the voice commands include but are not limited to "turn left", "turn right", "go straight", "accelerate", "slow down", "stop", etc. The voice recognition module can efficiently and accurately recognize commands in a noisy environment.

[0013] As a further solution of the present invention, the head movement perception module includes:

[0014] Accelerometer: used to detect the linear acceleration of the head and obtain the movement of the head in different directions in space;

[0015] Gyroscope: used to detect the angular velocity of the head and measure the rotation speed and direction of the head;

[0016] Magnetometer: used to measure the azimuth (heading) of the head, to compensate for the drift of the gyroscope and to improve the accuracy of the head orientation.

[0017] As a further solution of the present invention, when the head motion sensing module detects and analyzes the motion trajectory and posture changes of the rider's head, the position, velocity and acceleration of the rider's head in three-dimensional space are calculated through the accelerometer and gyroscope data, including the following steps:

[0018] The linear acceleration data a(t) of the rider's head is obtained through an accelerometer;

[0019] a(t)=[αx (t),α y (t),α z (t)]

[0020] Represents the acceleration components of the head in the x, y, and z directions;

[0021] The angular velocity data ω(t) of the head is obtained through the gyroscope;

[0022] ω(t)=[ω x (t),ω y (t),ω z (t)]

[0023] represents the angular velocity of the head around the x, y, and z axes;

[0024] The displacement and velocity of the head are estimated by integrating the acceleration, where the head position update formula is:

[0025]

[0026] The head velocity update formula is:

[0027] v(t)=v(t-1)+α(t)·Δt

[0028] Where P(t) represents the position of the head, v(t) is the velocity of the head, a(t) is the acceleration, and Δt is the sampling time interval.

[0029] As a further solution of the present invention, when the head motion sensing module detects and analyzes the movement trajectory and posture change of the rider's head, the head posture is calculated by fusing the data of the accelerometer, gyroscope and magnetometer. The accelerometer provides angle information with the earth's gravity field to estimate the tilt angle of the head in a stationary state. The gyroscope provides continuous angular velocity data to track the rotation of the head in real time. The synthesized head orientation θ(t) is obtained by the following formula:

[0030] θ(t)=θ(t-1)+∫ω(t)dt

[0031] Where ω(t) is the angular velocity measured by the gyroscope and θ(t) is the orientation angle of the head.

[0032] As a further solution of the present invention, when the head movement perception module detects and analyzes the movement trajectory and posture change of the rider's head, it also includes adaptively adjusting the weights of the head movement and the external command according to the rider's actual movement state in combination with the head orientation and the external command, wherein the dynamic weight β(t) is set, then:

[0033] θ d (t) = β(t)·θ h(t)+(1-β(t))·θ v (t)

[0034] Among them, β(t) is the weight coefficient related to the head movement state.

[0035] As a further solution of the present invention, the environmental perception module includes a camera and an environmental noise monitor installed on the helmet, as well as a vehicle-mounted GPS and radar, which are used to obtain real-time surrounding environmental information such as road obstacles, traffic signals, obstacle distances, and weather conditions, and generate environmental perception data during riding.

[0036] As a further solution of the present invention, the cloud navigation processing system receives and integrates the rider's voice command, head movement data, and environmental perception data, including the following steps:

[0037] Receive and analyze the rider's voice commands and identify the rider's intentions;

[0038] The current riding direction is calibrated using the head motion data including the head orientation, rotation speed and head motion state provided by the head motion sensing module;

[0039] Combined with environmental perception data, dynamically evaluate road conditions and traffic signals, and correct the riding path;

[0040] Based on voice commands, head movement data, and environmental perception data, path planning is used to calculate the optimal cycling route and provide real-time navigation instructions.

[0041] As a further solution of the present invention, the cloud navigation processing system dynamically calculates the rider's current position, driving direction, and target route, and adjusts the navigation instructions according to the path deviation. The current position is calculated based on the fusion of GPS data and head movement data, and the current position is updated:

[0042] P(t)={x(t),y(t)}

[0043] Where P(t) is the current position, expressed as a two-dimensional coordinate point {x(t), y(t)}, x(t) is the horizontal coordinate position at time t, indicating the cyclist's eastward position on the map; y(t) is the vertical coordinate position at time t, indicating the cyclist's northward position on the map;

[0044] The calculation of the driving direction is based on the weighted average of the head orientation and the voice command to calculate the cyclist's driving direction:

[0045] θ d (t) = β·θ h (t)+(1-β)·θ v (t)

[0046] Among them, θd (t) is the final driving direction at time t, θ h (t) is the head orientation angle at time t, θ v (t) is the voice command direction at time t, β is the weight coefficient for balancing the influence of head orientation and voice command, and its value range is [0,1]. β determines the weight of head orientation and voice command in the final driving direction. When the head orientation is consistent with the voice command direction, β is larger; otherwise, the weight of the voice command direction is higher.

[0047] A riding direction sensing system based on voice control command recognition, comprising:

[0048] Voice recognition module: used to receive the rider's voice commands in real time and identify the rider's operating intentions (such as "turn left", "turn right", "continue straight", etc.); the voice recognition module can convert the rider's voice signal into processable digital commands and transmit them to the subsequent processing unit, supporting the recognition and processing of multiple voice commands and adapting to noise interference in different riding environments;

[0049] Head motion sensing module: A sensor that integrates an accelerometer, gyroscope, and magnetometer to detect and analyze the movement trajectory and posture changes of the rider's head in real time, and estimate the rider's head orientation, rotation speed, and movement state through sensor data; the head motion sensing module synthesizes acceleration, angular velocity, and magnetic information through sensor fusion technology to calculate the head's spatial position and movement direction in real time;

[0050] Environmental perception module: acquires real-time perception data of the surrounding environment through integrated external environmental sensors; provides current environmental information, such as road conditions, traffic signals, obstacles, etc., to assist the navigation processing system in making more accurate driving decisions;

[0051] Cloud navigation processing system: used to receive voice commands, head movement data and environmental perception data, perform data fusion and intelligent processing, calculate the rider's current position, driving direction and target route through path planning; adjust navigation strategy according to the rider's real-time situation and generate personalized voice navigation instructions; if the rider deviates from the planned route, the cloud navigation processing system will automatically adjust the route and generate new navigation instructions;

[0052] Audio playback module: used to play the voice navigation instructions generated by the cloud navigation processing system to guide the rider to perform the correct navigation operations. It supports real-time audio feedback so that the rider can maintain a clear understanding of the direction and route during riding. The volume can be adjusted to adapt to different riding environments (such as noisy urban environments or quiet rural roads);

[0053] Data communication interface: used for efficient data communication between modules and cloud systems, ensuring timely data transmission and processing, supporting wireless communication technologies such as Bluetooth and Wi-Fi, and realizing connection with smart phones, cloud servers and other devices.

[0054] A helmet, comprising the following components:

[0055] Helmet body: Made of light and strong materials (such as ABS or carbon fiber), it provides physical protection for the rider's head. The design is ergonomic to ensure comfortable and stable wearing. It has a good ventilation and heat dissipation system to keep the wearer comfortable.

[0056] Speech recognition module integration: It is an embedded speech recognition module that interacts through the rider's voice commands. The speech recognition module integrates a microphone and a speech processing chip, which can capture the rider's voice signals in real time, recognize riding commands through algorithms, and feed back voice commands to the rider through built-in speakers or externally connected headphones.

[0057] Head motion sensing sensor: It integrates an accelerometer, gyroscope and magnetometer to detect the movement state, direction, rotation speed, etc. of the head in real time. Through these sensor data, it monitors the rider's head posture changes in real time, calculates the head direction and rotation speed, and transmits the data to the cloud navigation system for processing.

[0058] Wireless communication module: supports Bluetooth or Wi-Fi communication, and is used to exchange data with other devices (such as smartphones, cloud navigation systems), ensuring that the helmet can connect to the rider's device and cloud system in real time to transmit navigation instructions and status information.

[0059] Battery and power management system: including a high-efficiency battery built into the helmet, which is used to power the voice recognition module, sensor and communication module. The power management system ensures the stable operation of each module and supports long-term use.

[0060] Audio output device: The helmet has built-in audio equipment, including headphones and speakers, which are used to play voice navigation instructions.

[0061] Safety warning system: used to remind riders to pay attention to surrounding traffic conditions (such as vehicles coming from behind, obstacles ahead, etc.) through vibration or sound, thereby enhancing riders' safety, especially in complex urban traffic environments.

[0062] Smart control panel: An intelligent control panel is integrated on the surface of the helmet, allowing riders to manually adjust voice control settings, navigation parameters, etc. when they stop riding. The control panel can display current navigation information, head movement status and other data.

[0063] Compared with the prior art, the riding direction sensing method, system and helmet based on voice control command recognition proposed in the present invention have the following beneficial effects:

[0064] 1. Through voice control command recognition, riding safety is enhanced, the driver's attention is maintained, and accidents caused by operational interference are reduced. The present invention uses a voice control system integrated into the helmet, and the rider can adjust the riding direction in real time through voice commands. For example, use commands such as "turn left" or "turn right" to guide the riding path. This technology can effectively reduce the situation where riders make improper turns due to distraction, violate traffic regulations or ignore emergencies, and improve riding safety. Riders do not need to distract themselves to check the route or operate the equipment. Voice prompts can ensure that riders focus on road conditions, thereby reducing accidents caused by operational interference.

[0065] 2. The convenience of riding is improved through voice interaction and hands-free operation. Since the traditional direction adjustment method requires manual operation, such as adjusting the handlebars or navigating with a mobile phone, the present invention is a voice-controlled direction sensing system that allows riders to operate only through simple voice commands without manual intervention, thereby improving the convenience and comfort of riding. Users can interact with the system through voice and check the weather, road conditions or riding health in real time. Such system integration can enhance the intelligent riding experience and reduce dependence on external devices.

[0066] 3. Improve riding efficiency through route planning and navigation optimization, as well as multi-scenario adaptability. By combining the voice control system with GPS positioning technology, the present invention allows riders to obtain real-time route planning, traffic conditions, cycling route adjustment and other information through voice commands to avoid getting lost or taking the wrong path. The voice control command system can adapt to different environments, such as noisy city streets or quiet country roads, and relies on accurate voice recognition technology to effectively improve the direction sensing and navigation accuracy during riding.

[0067] 4. Improve user experience through personalized adjustment and feedback voice prompts. Based on the user's voice characteristics and voice habits, the system of the present invention can automatically optimize recognition accuracy to ensure that instructions can be accurately responded to even in different environments or riding postures. The system of the present invention will not only give voice feedback based on the riding direction, but also provide voice reminders, such as reminding that there are traffic lights, obstacles or road construction ahead. Enhance the rider's perception of the environment and further improve the user experience.

[0068] 5. Intelligent helmet design is achieved through the integrated design of built-in sensors and control modules. The smart helmet of the present invention can have a built-in direction sensing module, which can identify the direction of the rider's head movement through the sensing device in the helmet and determine the current riding direction in combination with voice commands. The helmet can respond to the rider's movements and commands in real time and optimize the riding path. The system of the present invention can integrate voice control command recognition with other functions of the helmet (such as anti-collision sensors, voice navigation, smart calls, etc.) to form a comprehensive riding assistance system, reduce dependence on other equipment, and provide integrated riding support.

[0069] 6. Support smart cycling ecology through data collection and analysis. The system of the present invention can collect cycling data, analyze the cycling status in real time, and make intelligent adjustments and optimizations based on factors such as the rider's habits and the cycling environment. For example, when it is detected that the rider's movement direction deviates from the expected trajectory, the system can automatically adjust and inform the correct direction through voice to further enhance the cycling experience. The system of the present invention can also be combined with sensors in smart watches or smart helmets to monitor the rider's physiological data, such as heart rate, exercise intensity, etc., to provide data support to help riders adjust their cycling plans and avoid excessive exercise.

[0070] In summary, the riding direction sensing method, system and helmet based on voice control command recognition of the present invention can effectively improve the safety, convenience, efficiency and overall experience of riders. Combining advanced voice recognition, direction sensing, intelligent navigation and other technologies, an integrated and efficient riding assistance system is created, which can not only improve the riding experience, but also promote the development of the concept of green travel. The realization of this innovative technology not only brings a smarter riding experience to riders, but also makes positive contributions to future smart travel and traffic safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0072] in:

[0073] Figure 1 The figure is a flow chart of a riding direction sensing method based on voice control command recognition according to an embodiment of the present invention.

[0074] Figure 2 The present invention is a flow chart of calculating the position, velocity and acceleration of a rider's head in three-dimensional space in a riding direction sensing method based on voice control command recognition in an embodiment of the present invention.

[0075] Figure 3 The present invention is a flowchart of receiving and fusing the rider's voice commands, head movement data, and environmental perception data in a riding direction sensing method based on voice control command recognition in an embodiment of the present invention. DETAILED DESCRIPTION

[0076] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] The existing cycling navigation system requires the rider to check the device screen or road signs, which causes the rider's attention to be distracted and increases the risk of accidents. The existing cycling equipment requires the rider to manually operate to confirm the navigation instructions, which is inconvenient and affects the fluency of the riding process. The present invention proposes a cycling direction sensing method, system and helmet based on voice control command recognition. Through the voice control command recognition system, the rider is prevented from frequently operating the device during the riding process, thereby reducing the cycling accidents caused by distraction caused by operating the device and enhancing the safety of the rider; through the audio playback device integrated in the helmet, the rider can hear the navigation instructions and the surrounding environment sound through headphones or built-in speakers, ensuring that the information transmission during the riding process is accurate and timely, and does not interfere with the rider's line of sight and two-hand operation; using sensors such as gyroscopes and accelerometers, the rider's head movement is monitored in real time, the rider's driving direction is accurately calculated through direction sensing technology, and intelligent navigation decisions are made in combination with voice commands; through voice recognition technology, the rider can control the navigation system through voice commands (such as "turn left", "turn right", "stop", etc.), ensuring simple and fast operation, and ensuring that the rider's navigation needs in complex environments are met.

[0078] See also Figure 1 As shown, an embodiment of the present invention provides a riding direction sensing method based on voice control command recognition, the method comprising the following steps:

[0079] Step S10: receiving the rider's voice command through the embedded voice recognition module.

[0080] In this step, the embedded voice recognition module includes a vehicle-mounted microphone or a microphone in a worn smart helmet, which is used to receive voice commands issued by the rider, wherein the voice commands include but are not limited to "turn left", "turn right", "go straight", "accelerate", "slow down", "stop", etc. The voice recognition module can efficiently and accurately recognize commands in a noisy environment.

[0081] Step S20: Detect and analyze the movement trajectory and posture changes of the rider's head through the head movement sensing module, monitor the direction, rotation speed and head movement status of the rider's head in real time, and obtain the head movement data of the rider's head in real time.

[0082] In this step, the head motion perception module includes:

[0083] Accelerometer: used to detect the linear acceleration of the head and obtain the movement of the head in different directions in space;

[0084] Gyroscope: used to detect the angular velocity of the head and measure the rotation speed and direction of the head;

[0085] Magnetometer: used to measure the azimuth (heading) of the head, to compensate for the drift of the gyroscope and to improve the accuracy of the head orientation.

[0086] In this embodiment, see Figure 2 As shown, when the head motion sensing module detects and analyzes the motion trajectory and posture changes of the rider's head, it calculates the position, speed and acceleration of the rider's head in three-dimensional space through the accelerometer and gyroscope data, including the following steps:

[0087] Step S201, obtaining linear acceleration data a(t) of the rider's head through an accelerometer;

[0088] a(t)=[α x (t), α y (t), α z (t)]

[0089] Represents the acceleration components of the head in the x, y, and z directions;

[0090] Step S202, obtaining angular velocity data ω(t) of the head through a gyroscope;

[0091] ω(t)=[ω x (t),ω y (t),ω z (t)]

[0092] represents the angular velocity of the head around the x, y, and z axes;

[0093] Step S203: Estimate the displacement and velocity of the head by integrating the acceleration, wherein the head position update formula is:

[0094]

[0095] The head velocity update formula is:

[0096] v(t)=v(t-1)+α(t)·Δt

[0097] Among them, P(t) represents the position of the head at time t, P(t-1) represents the position of the head at time t-1, v(t) represents the velocity of the head at time t, v(t-1) represents the velocity of the head at time t-1, a(t) represents the acceleration at time t, and Δt is the sampling time interval.

[0098] In this embodiment, when the head motion sensing module detects and analyzes the movement trajectory and posture changes of the rider's head, the head posture is calculated by fusing the data of the accelerometer, gyroscope and magnetometer. The accelerometer provides angle information with the earth's gravity field to estimate the tilt angle of the head in a stationary state. The gyroscope provides continuous angular velocity data to track the rotation of the head in real time. The synthesized head orientation θ(t) is obtained by the following formula:

[0099] θ(t)=θ(t-1)+∫ω(t)dt

[0100] Wherein, ω(t) is the angular velocity measured by the gyroscope, θ(t) is the orientation angle of the head at time t, and θ(t-1) is the orientation angle of the head at time t-1.

[0101] When the head motion perception module detects and analyzes the motion trajectory and posture changes of the rider's head, it also includes adaptively adjusting the weights of the head motion and the external command according to the rider's actual motion state in combination with the head orientation and the external command. The dynamic weight β(t) is set, then:

[0102] θ d (t) = β(t)·θ h (t)+(1-α(t))·θ v (t)

[0103] Among them, θ d (t) is the final driving direction at time t, θ h (t) is the head orientation angle at time t, θ v (t) is the voice command direction at time t, and β(t) is the weight coefficient related to the head movement state.

[0104] Step S30: Acquire environmental perception data in real time through the environmental perception module, and feed back the voice command, head movement data and environmental perception data to the cloud navigation processing system.

[0105] In this step, the environmental perception module includes a camera and an environmental noise monitor installed on the helmet, as well as a vehicle-mounted GPS (Global Positioning System) and radar, which are used to obtain real-time surrounding environmental information such as road obstacles, traffic signals, obstacle distances, and weather conditions, and generate environmental perception data during riding.

[0106] Step S40: The cloud navigation processing system receives the voice command, the head movement data, and the environmental perception data for fusion processing to calculate the rider's current position, driving direction, and target route.

[0107] In this step, see Figure 3 As shown, the cloud navigation processing system receives and integrates the rider's voice command, head movement data, and environmental perception data, including the following steps:

[0108] Step S401, receiving and analyzing the rider's voice command, and identifying the rider's intention;

[0109] Step S402: calibrate the current riding direction using the head motion data including the head orientation, rotation speed and head motion state provided by the head motion sensing module;

[0110] Step S403: Combine environmental perception data to dynamically evaluate road conditions and traffic signals and correct the riding path;

[0111] Step S404: Based on the voice instructions, head movement data, and environmental perception data, use path planning to calculate the optimal cycling route and provide real-time navigation instructions.

[0112] In this embodiment, the cloud navigation processing system dynamically calculates the rider's current position, driving direction, and target route, and adjusts the navigation instructions according to the path deviation. The current position is calculated based on the fusion of GPS data and head movement data, and the current position is updated:

[0113] P(t)={x(t),y(t)}

[0114] Where P(t) is the current position, expressed as a two-dimensional coordinate point {x(t), y(t)}, x(t) is the horizontal coordinate position at time t, indicating the cyclist's eastward position on the map; y(t) is the vertical coordinate position at time t, indicating the cyclist's northward position on the map;

[0115] The calculation of the driving direction is based on the weighted average of the head orientation and the voice command to calculate the cyclist's driving direction:

[0116] θ d (t) = β·θ h (t)+(1-β)·θv (t)

[0117] Among them, θ d (t) is the final driving direction at time t, θ h (t) is the head orientation angle at time t, θ v (t) is the voice command direction at time t, β is the weight coefficient for balancing the influence of head orientation and voice command, and its value range is [0,1]. β determines the weight of head orientation and voice command in the final driving direction. When the head orientation is consistent with the voice command direction, β is larger; otherwise, the weight of the voice command direction is higher.

[0118] Step S50: The cloud navigation processing system generates corresponding voice navigation instructions and feeds back the real-time planned riding route to the rider through the audio playback module.

[0119] Step S60: If the actual riding route deviates from the real-time planned riding route, the cloud navigation processing system automatically adjusts the voice navigation instructions and provides updated navigation information through the audio playback module.

[0120] In this step, through the riding direction sensing method based on voice control command recognition provided by the present invention, the rider can focus on riding itself during riding, without being distracted by operating the navigation device, thereby greatly improving the safety of riding. In addition, the method of the present invention can intelligently feedback navigation instructions, ensuring that the rider can still accurately and timely obtain navigation guidance in a complex riding environment, greatly improving the riding experience.

[0121] The riding direction sensing method based on voice control command recognition of the present invention combines the voice control system with GPS positioning technology, so that riders can obtain real-time path planning, traffic conditions, riding route adjustment and other information through voice commands to avoid getting lost or taking the wrong path. The voice control command system can adapt to different environments, such as noisy city streets or quiet country roads, and relies on accurate voice recognition technology to effectively improve the accuracy of direction sensing and navigation during riding.

[0122] In one embodiment, the present invention further provides a riding direction sensing system based on voice control command recognition, comprising:

[0123] Voice recognition module: used to receive the rider's voice commands in real time and identify the rider's operating intentions (such as "turn left", "turn right", "continue straight", etc.); the voice recognition module can convert the rider's voice signal into processable digital commands and transmit them to the subsequent processing unit, supporting the recognition and processing of multiple voice commands and adapting to noise interference in different riding environments;

[0124] Head motion sensing module: A sensor that integrates an accelerometer, gyroscope, and magnetometer to detect and analyze the movement trajectory and posture changes of the rider's head in real time, and estimate the rider's head orientation, rotation speed, and movement state through sensor data; the head motion sensing module synthesizes acceleration, angular velocity, and magnetic information through sensor fusion technology to calculate the head's spatial position and movement direction in real time;

[0125] Environmental perception module: acquires real-time perception data of the surrounding environment through integrated external environmental sensors; provides current environmental information, such as road conditions, traffic signals, obstacles, etc., to assist the navigation processing system in making more accurate driving decisions;

[0126] Cloud navigation processing system: used to receive voice commands, head movement data and environmental perception data, perform data fusion and intelligent processing, calculate the rider's current position, driving direction and target route through path planning; adjust navigation strategy according to the rider's real-time situation and generate personalized voice navigation instructions; if the rider deviates from the planned route, the cloud navigation processing system will automatically adjust the route and generate new navigation instructions;

[0127] Audio playback module: used to play the voice navigation instructions generated by the cloud navigation processing system to guide the rider to perform the correct navigation operations. It supports real-time audio feedback so that the rider can maintain a clear understanding of the direction and route during riding. The volume can be adjusted to adapt to different riding environments (such as noisy urban environments or quiet rural roads);

[0128] Data communication interface: used for efficient data communication between modules and cloud systems, ensuring timely data transmission and processing, supporting wireless communication technologies such as Bluetooth and Wi-Fi, and realizing connection with smart phones, cloud servers and other devices.

[0129] Since traditional direction adjustment methods require manual operation, such as adjusting the handlebars or using mobile phone navigation, the present invention is a voice-controlled direction sensing system that allows riders to operate with simple voice commands without manual intervention, thus improving the convenience and comfort of riding. Users can interact with the system through voice to query weather, road conditions or riding health in real time. Such system integration can enhance the intelligent riding experience and reduce dependence on external devices.

[0130] Based on the user's voice characteristics and speech habits, the system can automatically optimize recognition accuracy to ensure that instructions can be accurately responded to even in different environments or riding postures. The system of the present invention not only gives voice feedback based on the riding direction, but also provides voice reminders, such as reminding that there are traffic lights, obstacles or road construction ahead. It enhances the rider's perception of the environment and further improves the user experience.

[0131] The system of the present invention can collect riding data, analyze riding status in real time, and make intelligent adjustments and optimizations based on factors such as the rider's habits and riding environment. For example, when it is detected that the rider's movement direction deviates from the expected trajectory, the system can automatically adjust and inform the correct direction through voice, further improving the riding experience. The system of the present invention can also be combined with sensors in smart watches or smart helmets to monitor the rider's physiological data, such as heart rate, exercise intensity, etc., to provide data support to help riders adjust their riding plans and avoid excessive exercise.

[0132] Through the above detailed steps and code examples, the riding direction sensing system based on voice control command recognition of the present invention is used to execute the steps of the riding direction sensing method based on voice control command recognition in the above embodiment, which will not be repeated here.

[0133] In one embodiment, a helmet is provided, comprising the following components:

[0134] Helmet body: Made of light and strong materials (such as ABS or carbon fiber), it provides physical protection for the rider's head. The design is ergonomic to ensure comfortable and stable wearing. It has a good ventilation and heat dissipation system to keep the wearer comfortable.

[0135] Speech recognition module integration: It is an embedded speech recognition module that interacts through the rider's voice commands. The speech recognition module integrates a microphone and a speech processing chip, which can capture the rider's voice signals in real time, recognize riding commands through algorithms, and feed back voice commands to the rider through built-in speakers or externally connected headphones.

[0136] Head motion sensing sensor: It integrates an accelerometer, gyroscope and magnetometer to detect the movement state, direction, rotation speed, etc. of the head in real time. Through these sensor data, it monitors the rider's head posture changes in real time, calculates the head direction and rotation speed, and transmits the data to the cloud navigation system for processing.

[0137] Wireless communication module: supports Bluetooth or Wi-Fi (mobile hotspot) communication, used to exchange data with other devices (such as smartphones, cloud navigation systems), ensuring that the helmet can connect to the rider's device and cloud system in real time to transmit navigation instructions and status information.

[0138] Battery and power management system: including a high-efficiency battery built into the helmet, which is used to power the voice recognition module, sensor and communication module. The power management system ensures the stable operation of each module and supports long-term use.

[0139] Audio output device: The helmet has built-in audio equipment, including headphones and speakers, which are used to play voice navigation instructions.

[0140] Safety warning system: used to remind riders to pay attention to surrounding traffic conditions (such as vehicles coming from behind, obstacles ahead, etc.) through vibration or sound, thereby enhancing riders' safety, especially in complex urban traffic environments.

[0141] Smart control panel: An intelligent control panel is integrated on the surface of the helmet, allowing riders to manually adjust voice control settings, navigation parameters, etc. when they stop riding. The control panel can display current navigation information, head movement status and other data.

[0142] The present invention uses a voice control system integrated into the helmet, so riders can adjust the riding direction in real time through voice commands. For example, use commands such as "turn left" or "turn right" to guide the riding path. This technology can effectively reduce the situation where riders make improper turns due to distraction, violate traffic regulations or ignore emergencies, and improve riding safety. Riders do not need to distract themselves to check the route or operate the equipment. Voice prompts can ensure that riders focus on the road conditions, thereby reducing accidents caused by operational interference.

[0143] The smart helmet of the present invention can have a built-in direction sensing module, which can identify the direction of the rider's head movement through the sensing device in the helmet and determine the current riding direction in combination with voice commands. The helmet can respond to the rider's movements and commands in real time and optimize the riding path. The system of the present invention can integrate voice control command recognition with other functions of the helmet (such as anti-collision sensors, voice navigation, smart calls, etc.) to form an all-round riding assistance system, reduce dependence on other equipment, and provide integrated riding support.

[0144] In summary, the riding direction sensing method, system and helmet based on voice control command recognition of the present invention can effectively improve the safety, convenience, efficiency and overall experience of riders. Combining advanced voice recognition, direction sensing, intelligent navigation and other technologies, an integrated and efficient riding assistance system is created, which can not only improve the riding experience, but also promote the development of the concept of green travel. The realization of this innovative technology not only brings a smarter riding experience to riders, but also makes positive contributions to future smart travel and traffic safety.

[0145] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0146] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A riding direction sensing method based on voice control command recognition, characterized in that: The method comprises the following steps: Receive the rider's voice commands through the embedded voice recognition module; The head movement sensing module detects and analyzes the movement trajectory and posture changes of the rider's head, monitors the rider's head direction, rotation speed and head movement status in real time, and senses and obtains the rider's head movement data in real time; The environmental perception module obtains environmental perception data in real time and feeds voice commands, head movement data and environmental perception data back to the cloud navigation processing system; The cloud-based navigation processing system receives voice commands, head movement data, and environmental perception data for fusion processing to calculate the rider’s current location, driving direction, and target route; The cloud navigation processing system generates corresponding voice navigation instructions and feeds back the real-time planned riding route to the rider through the audio playback module; If the actual cycling route deviates from the real-time planned cycling route, the cloud navigation processing system automatically adjusts the voice navigation instructions and provides updated navigation information through the audio playback module.

2. The riding direction sensing method based on voice control command recognition according to claim 1 is characterized in that: The embedded voice recognition module includes a microphone on the vehicle or in a microphone in a wearable smart helmet, which is used to receive voice commands from the rider.

3. The riding direction sensing method based on voice control command recognition according to claim 1 is characterized in that: The head motion perception module includes: Accelerometer: used to detect the linear acceleration of the head and obtain the movement of the head in different directions in space; Gyroscope: used to detect the angular velocity of the head and measure the rotation speed and direction of the head; Magnetometer: Used to measure the azimuth of the head orientation.

4. The riding direction sensing method based on voice control command recognition according to claim 3 is characterized in that: When the head motion sensing module detects and analyzes the movement trajectory and posture changes of the rider's head, it calculates the position, speed and acceleration of the rider's head in three-dimensional space through the accelerometer and gyroscope data, including the following steps: The linear acceleration data a(t) of the rider's head is obtained through an accelerometer; a(t)=[a x (t), a y (t), a z (t)] Represents the acceleration components of the head in the x, y, and z directions; The angular velocity data ω(t) of the head is obtained through the gyroscope; ω(t)=[ω x (t),ω y (t),ω z (t)] represents the angular velocity of the head around the x, y, and z axes; The displacement and velocity of the head are estimated by integrating the acceleration, where the head position update formula is: The head velocity update formula is: v(t)=v(t-1)+α(t)·Δt Where P(t) represents the position of the head, v(t) is the velocity of the head, a(t) is the acceleration, and Δt is the sampling time interval.

5. The riding direction sensing method based on voice control command recognition according to claim 4 is characterized in that: When the head motion sensing module detects and analyzes the movement trajectory and posture changes of the rider's head, it calculates the head posture by fusing the data of the accelerometer, gyroscope and magnetometer. The accelerometer provides the angle information with the earth's gravity field to estimate the tilt angle of the head in a static state. The gyroscope provides continuous angular velocity data to track the rotation of the head in real time. The synthesized head orientation θ(t) is obtained by the following formula: θ(t)=θ(t-1)+∫ω(t)dt Where ω(t) is the angular velocity measured by the gyroscope and θ(t) is the orientation angle of the head.

6. The riding direction sensing method based on voice control command recognition according to claim 1 is characterized in that: The environmental perception module includes a camera and environmental noise monitor installed on the helmet, as well as a vehicle-mounted GPS and radar, which are used to obtain real-time surrounding environmental information such as road obstacles, traffic signals, obstacle distances, and weather conditions, and generate environmental perception data while riding.

7. The riding direction sensing method based on voice control command recognition according to claim 6 is characterized in that: The cloud navigation processing system receives and integrates the rider's voice commands, head movement data, and environmental perception data, including the following steps: Receive and analyze the rider's voice commands and identify the rider's intentions; The current riding direction is calibrated using the head motion data including the head orientation, rotation speed and head motion state provided by the head motion sensing module; Combined with environmental perception data, dynamically evaluate road conditions and traffic signals, and correct the riding path; Based on voice commands, head movement data, and environmental perception data, path planning is used to calculate the optimal cycling route and provide real-time navigation instructions.

8. The riding direction sensing method based on voice control command recognition according to claim 7 is characterized in that: The cloud-based navigation processing system dynamically calculates the rider's current position, driving direction, and target route, and adjusts navigation instructions based on path deviation. The current position is calculated based on the fusion of GPS data and head movement data, and the current position is updated: P(t)={x(t),y(t)} Where P(t) is the current position, expressed as a two-dimensional coordinate point {x(t), y(t)}, x(t) is the horizontal coordinate position at time t, indicating the cyclist's eastward position on the map; y(t) is the vertical coordinate position at time t, indicating the cyclist's northward position on the map; The calculation of the driving direction is based on the weighted average of the head orientation and the voice command to calculate the cyclist's driving direction: i d (t)=β·θ h (t)+(1-β)·θ v (t) Among them, θ d (t) is the final driving direction at time t, θ h (t) is the head orientation angle at time t, θ v (t) is the direction of the voice command at time t, β is the weight coefficient for balancing the influence of head orientation and voice command, and its value range is [0, 1].

9. A riding direction sensing system based on voice control command recognition, characterized in that: The system is used to execute the riding direction sensing method based on voice control command recognition as described in any one of claims 1 to 8, comprising: Voice recognition module: used to receive the rider's voice commands in real time and identify the rider's operating intentions; Head motion sensing module: A sensor that integrates an accelerometer, gyroscope, and magnetometer to detect and analyze the movement trajectory and posture changes of the rider's head in real time, and estimate the rider's head orientation, rotation speed, and movement status through sensor data; Environmental perception module: acquires the perception data of the surrounding environment in real time through the integrated external environmental sensors; Cloud navigation processing system: used to receive voice commands, head movement data and environmental perception data, perform data fusion and intelligent processing, calculate the rider's current position, driving direction and target route through path planning; adjust navigation strategy according to the rider's real-time situation and generate personalized voice navigation instructions; if the rider deviates from the planned route, the cloud navigation processing system will automatically adjust the route and generate new navigation instructions; Audio playback module: used to play the voice navigation instructions generated by the cloud navigation processing system, guide the rider to perform the correct navigation operations, and support real-time audio feedback; Data communication interface: used for efficient data communication between modules and cloud systems to ensure timely transmission and processing of data.

10. A helmet, characterized in that: A helmet for executing the riding direction sensing method based on voice control command recognition as claimed in any one of claims 1 to 8, comprising: Helmet body: used to provide physical protection for the rider's head; Speech recognition module integration: It is an embedded speech recognition module that interacts with the rider’s voice commands. The speech recognition module integrates a microphone and a speech processing chip to capture the rider’s voice signals in real time, recognize riding commands, and feed back the voice commands to the rider through the built-in speaker or externally connected headphones. Head motion sensing sensor: It integrates an accelerometer, gyroscope and magnetometer to detect the movement state, direction and rotation speed of the head in real time, monitor the rider's head posture changes in real time, calculate the head direction and rotation speed, and transmit the data to the cloud navigation system for processing; Wireless communication module: supports Bluetooth or Wi-Fi communication for data exchange; Battery and power management system: including high-efficiency batteries built into the helmet to power the voice recognition module, sensors and communication modules; Audio output device: The helmet has built-in audio equipment, including headphones and speakers, for playing voice navigation instructions; Smart Control Panel: An intelligent control panel is integrated on the surface of the helmet, allowing riders to manually adjust voice control settings and navigation parameters when they stop riding.

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