Bluetooth wireless communication method for controlling bicycle light groups

Abstract

This invention relates to the field of bicycle light group control technology, and discloses a method for controlling bicycle light groups via Bluetooth wireless communication. The method scans and identifies bicycle light devices using the Bluetooth protocol, collecting their unique identifiers, status, and location data. A dynamic topology management algorithm is used to divide the system into logical groups, each containing a master and slave devices. A dynamic communication link model is established based on device location and movement trends to predict signal transmission stability and generate control command sequences. An adaptive frequency hopping mechanism is also employed to optimize Bluetooth channel selection, and group configuration and control commands are updated in real time based on environmental data, dynamically adjusting the brightness mode and flashing frequency of each device. This invention improves the intelligence, communication reliability, and lighting safety of bicycle light group control, effectively solving many problems in existing bicycle light control technologies and providing cyclists with a better user experience.

Description

Technical Field

[0001] This invention relates to the field of bicycle light group control technology, specifically a method for controlling bicycle light groups via Bluetooth wireless communication. Background Technology

[0002] With the increasing popularity of cycling and the growing demand for nighttime riding, bicycle lights are being used more and more widely. In multi-person cycling scenarios, such as cycling club events and long-distance cycling groups, the need for coordinated control of bicycle lights is becoming increasingly prominent. Traditional bicycle lights are mostly controlled individually, making it impossible to achieve unified management and coordination of lights within a group, which causes many inconveniences in actual riding.

[0003] In terms of communication, early bicycle lights lacked effective communication methods, making it difficult for riders to control multiple lights simultaneously. Even when some products adopted simple wired connections, installation was cumbersome, limiting bicycle maneuverability and making them prone to damage in complex riding environments. With the development of wireless communication technology, some bicycle lights began to experiment with wireless communication. However, common wireless communication methods such as Wi-Fi suffer from high power consumption and limited number of connected devices, making them unsuitable for scenarios like bicycle lights where power consumption and device scalability are critical. While Bluetooth technology has seen some application, it has mostly been limited to simple one-to-one connection control, failing to fully leverage Bluetooth's advantages in multi-device connectivity and dynamic networking.

[0004] In terms of group management, existing bicycle lights lack a reasonable group division mechanism. During riding, the status of individual bicycle lights varies; some have sufficient power, while others have low power; some have strong signals, while others have weak signals. Due to the lack of effective group division and management, it is impossible to reasonably allocate tasks according to the actual situation of the equipment, resulting in low operating efficiency of the entire group. For example, when encountering complex road conditions and needing to quickly transmit light warning information, it cannot be guaranteed that the information can be accurately and timely conveyed to every light in the group.

[0005] In terms of brightness and flashing frequency control, traditional bicycle lights typically rely on manual operation for brightness adjustment, failing to automatically adjust based on ambient light intensity and riding conditions. When entering tunnels during the day or experiencing rapid changes in light at dusk, riders often lack the time to manually adjust the light brightness, compromising riding safety. Furthermore, there is no intelligent control function for flashing frequency based on vehicle movement, preventing timely and effective warning signals to the surrounding environment in special situations such as turning or slowing down.

[0006] Furthermore, existing bicycle light communication systems are relatively weak in resisting interference when dealing with complex cycling environments. Cities are rife with interference sources such as Bluetooth devices and Wi-Fi signals. During cycling, this interference can easily lead to communication interruptions or incorrect command transmissions between bicycle lights. For example, when passing through an area with strong signal interference, bicycle lights may exhibit abnormal brightness changes or fail to receive control commands, seriously affecting cycling safety and the normal operation of the lights. Summary of the Invention

[0007] The purpose of this invention is to provide a method for controlling bicycle light groups via Bluetooth wireless communication to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for controlling bicycle light groups via Bluetooth wireless communication, the method comprising:

[0009] Step S1: Scan and identify bicycle light devices within a preset range via Bluetooth protocol, and collect the device's unique identifier, current status information, and location data. The status information includes at least the brightness level, battery level, and communication signal strength.

[0010] Step S2: Based on the dynamic topology management algorithm, the identified bicycle light devices are divided into multiple logical groups. Each group contains at least one master control device and several slave devices. The master control device is responsible for the distribution and coordination of instructions within the group.

[0011] Step S3: Based on the location and movement trends of devices within the group, establish a dynamic communication link model, predict the signal transmission stability between devices within the group, and generate a group control command sequence.

[0012] Preferably, step S2 further includes:

[0013] Step S21: Set constraints for group division, including the maximum allowable communication distance between devices, the minimum remaining battery power threshold, and the signal strength threshold;

[0014] Step S22: Construct an adjacency matrix based on device location data, and select the device with the widest signal coverage and sufficient power as the master control device using a greedy algorithm;

[0015] Step S23: Assign a priority to each slave device. The priority is dynamically calculated based on the device's movement speed, remaining battery life, and signal stability.

[0016] Step S24: When a device is detected to be out of the group communication range or its power is below the threshold, the group reconstruction mechanism is triggered to reallocate the master device and update the slave device list.

[0017] Preferably, the establishment of the dynamic communication link model in step S3 includes:

[0018] Step S31: Predict the motion trajectory of each device in the group using a Kalman filter, and calculate the relative position changes between devices within the future time window;

[0019] Step S32: Estimate the link quality index based on the signal attenuation model, combined with data on distance between devices and environmental obstacles;

[0020] Step S33: If the link quality index is lower than the preset threshold, insert redundant instructions into the control instruction sequence and mark them as high-priority transmission tasks;

[0021] Step S34: Dynamically adjust the instruction transmission interval based on the link quality index to ensure that critical instructions are sent first.

[0022] Preferably, the method further includes:

[0023] Step S4: Optimize Bluetooth channel selection through an adaptive frequency hopping mechanism and adjust the communication frequency band based on real-time environmental interference data; the specific steps of the adaptive frequency hopping mechanism include:

[0024] Step S41: Monitor the intensity and distribution of interference sources in the current Bluetooth channel in real time and generate an interference spectrum diagram;

[0025] Step S42: Based on the interference spectrum, select the continuous idle channel with the lowest interference intensity as the candidate frequency band;

[0026] Step S43: Using time division multiplexing technology, the control command is divided into multiple data packets and transmitted alternately in different candidate frequency bands;

[0027] Step S44: If the channel quality continues to deteriorate, the emergency frequency hopping mode is triggered, and the system switches to a preset backup frequency band group.

[0028] Preferably, the method further includes:

[0029] Step S5: Based on device status information and external environment data, update group configuration and control commands in real time, and dynamically adjust the brightness mode and flicker frequency of each device to achieve coordinated control; specific steps include:

[0030] Step S51: Based on the ambient light intensity sensor data, divide the brightness level into multiple intervals and set a reference brightness value for each interval;

[0031] Step S52: Based on the relative positions of devices within the group, calculate the minimum safe brightness difference between the front and rear headlights to avoid visual interference;

[0032] Step S53: When a vehicle is detected to decelerate or turn suddenly, dynamically increase the flashing frequency of the corresponding headlights and synchronize it to all devices in the group;

[0033] Step S54: If the battery level of a device is lower than the threshold, its brightness level will be automatically reduced, and the main control device will be notified to reassign the lighting task.

[0034] Preferably, the priority calculation formula in step S23 is as follows:

[0035] P j =α·v j +β·e j +γ·s j

[0036] Among them, P j v is the priority value of device j. j Represents the speed of movement of device j, e j s represents the remaining battery percentage. j This represents the signal stability index, where α, β, and γ are dynamic weighting coefficients.

[0037] Preferably, the signal attenuation model in step S32 adopts the following formula:

[0038]

[0039] Among them, LQI ij Let L0 be the link quality index between device i and device j, L0 be the initial signal strength at the reference distance d0, and η be the path loss index. ij W is the distance between devices i and j. k is the attenuation coefficient of the k-th obstacle, and n is the total number of obstacles on the transmission path between devices.

[0040] Preferably, the switching strategy for the spare frequency band group in step S44 includes:

[0041] Step S441: Preset multiple non-overlapping frequency band groups and assign them different priorities;

[0042] Step S442: When the main frequency band group fails, attempt to switch in priority order until an available frequency band is found;

[0043] Step S443: After the switch is completed, broadcast the frequency band update command to all devices in the group and start the frequency band synchronization timer;

[0044] Step S444: If synchronization times out, forcibly disconnect unresponsive devices and trigger the group reconfiguration process.

[0045] Preferably, the method for calculating the minimum safe brightness difference in step S52 is as follows:

[0046] Step S521: Based on the persistence of vision of the human eye, set the threshold for the difference in brightness between the front and rear headlights;

[0047] Step S522: Dynamically adjust the threshold range based on device spacing and relative speed;

[0048] Step S523: If a conflict in the brightness of the headlights of multiple vehicles is detected, the main control device will intervene and redistribute the brightness levels.

[0049] Preferably, the adjustment strategy for the dynamic weighting coefficients includes:

[0050] Step S101: Initialize the baseline values ​​of α, β, and γ based on the number of devices in the group and the complexity of the environment;

[0051] Step S102: Monitor the rate of change of device status in real time. If the speed of movement or the power of a device drops suddenly, increase the corresponding weight coefficient.

[0052] Step S103: Optimize the weight combination using the gradient descent algorithm to achieve optimal group stability in priority allocation.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] The Bluetooth wireless communication-based bicycle light group control method proposed in this invention has several significant advantages. In terms of device management and communication, it scans and identifies bicycle light devices within a preset range using the Bluetooth protocol, collecting unique identifiers, current status information, and location data, enabling precise location and monitoring of each light's status. Based on a dynamic topology management algorithm, it divides logical groups, clearly defining the responsibilities of the master and slave devices, making instruction distribution and coordination within the group more efficient. This division method considers constraints such as the maximum allowable communication distance between devices, the minimum remaining battery threshold, and signal strength threshold, ensuring group stability. For example, in a multi-person cycling activity, even if some devices have low battery or weak signals, the system can ensure the normal operation of all lights in the group through reasonable group division and reallocation of the master device, avoiding the impact of individual device problems on the overall lighting effect.

[0055] The establishment of a dynamic communication link model further enhances communication reliability. By using a Kalman filter to predict the device's trajectory and combining it with a signal attenuation model to estimate the link quality index, signal transmission stability can be predicted in advance. When the link quality index falls below a preset threshold, redundant instructions are inserted and marked as high-priority transmission tasks, while the instruction transmission interval is dynamically adjusted based on the link quality. This is of great significance in actual cycling, for example, when passing through areas with strong signal interference or when the relative position of equipment changes rapidly, it ensures that control instructions are transmitted accurately and promptly, ensuring that the lights work as expected, avoiding lighting abnormalities caused by communication problems, and guaranteeing cycling safety.

[0056] The adaptive frequency hopping mechanism optimizes Bluetooth channel selection, significantly improving the system's anti-interference capability. It monitors the strength and distribution of interference sources in real time, selecting the continuously idle channels with the lowest interference intensity as candidate frequency bands, and employs time-division multiplexing technology to alternately transmit control commands across different candidate frequency bands. When channel quality continues to deteriorate, an emergency frequency hopping mode is triggered to switch to a preset backup frequency band group. Taking urban cycling scenarios as an example, when encountering interference from numerous Bluetooth devices and Wi-Fi signals, the system can quickly switch channels to maintain stable communication within the bicycle light group, preventing light malfunctions or abnormal brightness changes due to interference.

[0057] This invention achieves a high degree of intelligence in brightness and flashing frequency control. It divides brightness level ranges based on ambient light intensity sensor data and sets a baseline brightness value. The minimum safe brightness difference between the front and rear lights is calculated based on the relative positions of devices within the group, avoiding visual interference. When a vehicle is detected to be decelerating rapidly or turning, the flashing frequency of the corresponding light is dynamically increased and synchronized to all devices in the group. If a device's battery level falls below a critical value, its brightness level is automatically reduced, and the main control device is notified to reassign lighting tasks. During nighttime riding, the lights automatically adjust their brightness according to changes in ambient light, ensuring effective illumination while avoiding energy waste. When the vehicle turns, the lights in the turning direction flash rapidly, promptly alerting pedestrians and vehicles and reducing the risk of accidents.

[0058] This invention improves the intelligence level, communication reliability, anti-interference ability, and lighting safety and rationality of bicycle light groups through a series of innovative control methods, providing cyclists with a more convenient and safer riding experience. It has high practical value and market promotion potential. Attached Figure Description

[0059] Figure 1 This is a schematic diagram illustrating the working principle of the bicycle light group control device described in this invention.

[0060] Figure 2 This is a schematic diagram illustrating the working principle of a dynamic communication link model.

[0061] Figure 3A flowchart of the adaptive frequency hopping mechanism;

[0062] Figure 4 This is a flowchart for coordinated brightness control. Detailed Implementation

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0064] Please see Figures 1-4 This invention provides a technical solution: a method for controlling bicycle light groups via Bluetooth wireless communication, specifically including the following steps:

[0065] Step S1: Device Scanning and Information Collection: The system uses Bluetooth to scan bicycle light devices within a preset range. During scanning, a unique identifier is identified for each bicycle light device; this identifier acts like a "ID card" for accurately distinguishing different devices within the system. Simultaneously, the system collects the current status information of the devices. Brightness level represents the current luminous intensity of the bicycle light, battery level reflects the remaining power, and communication signal strength indicates the strength of signal transmission between devices. Furthermore, the system acquires the device's location data, which provides crucial information for subsequent group segmentation and communication link establishment.

[0066] Step S2: Logical Group Division: Based on the dynamic topology management algorithm, the identified bicycle light devices are divided into multiple logical groups. Each group contains at least one master control device and several slave devices. The master control device undertakes the key task of instruction distribution and coordination in the group, just like a leader in a team, responsible for directing and coordinating the work of other members.

[0067] Step S3: Dynamic Communication Link Establishment and Command Generation: Based on the location and movement trends of devices within the group, a dynamic communication link model is established. This model is used to predict the signal transmission stability between devices within the group. After comprehensively considering various factors, a group control command sequence is generated to ensure stable and reliable communication between devices within the group, while also achieving effective control of the bicycle lights.

[0068] The present invention will be further described below with reference to Examples 1 to 6:

[0069] Example 1:

[0070] In this embodiment, the specific process of group division is further described in detail.

[0071] Step S21: Set the constraints for group division. The maximum allowable communication distance between devices is an important indicator, as it limits the range within which devices can effectively communicate. For example, after extensive experiments and real-world application testing, the maximum allowable communication distance is set to 50 meters. Beyond this distance, the signal transmission quality between devices will severely degrade, failing to meet the requirements of group control. The minimum remaining battery power threshold is set to 20%. When a device's battery power falls below this threshold, its stability and functionality within the group will be affected, and it may be unable to execute commands normally. The signal strength threshold is set to -70dBm. Below this strength, the signal is easily interfered with, reducing communication reliability.

[0072] Proceed to step S22, constructing an adjacency matrix based on device location data. An adjacency matrix is ​​a mathematical model that clearly represents the connection relationships between devices. Assuming a scenario with five bicycle light devices, a 5×5 adjacency matrix is ​​constructed by acquiring their location data. In this matrix, the values ​​of the elements represent information such as whether a connection exists between two corresponding devices and the strength of that connection. Then, a greedy algorithm is used to select the device with the widest signal coverage and sufficient battery power as the master control device. The greedy algorithm prioritizes devices that are optimal under the current conditions. For example, among the five devices mentioned above, device 3's signal coverage reaches that of the other four devices, and its remaining battery power is 80%, far exceeding the minimum remaining battery power threshold; therefore, it is selected as the master control device.

[0073] Step S23: Assign a priority to each slave device. The priority is dynamically calculated based on the device's movement speed, remaining battery life, and signal stability. The calculation formula is:

[0074] P j =α·v j +β·e j +γ·s j

[0075] Among them, P j v represents the priority value of device j, which comprehensively reflects the device's importance within the group and its suitability for performing tasks. j This represents the speed of device j, measured in meters per second. Faster devices may exhibit greater dynamic changes within the group and have a greater impact on group control. j This indicates the remaining battery percentage. Devices with sufficient battery power can perform tasks more stably and will not malfunction due to insufficient power. jThis represents the signal stability index, which is derived by monitoring and analyzing fluctuations in the signals received and transmitted by the device. A higher index indicates a more stable signal. α, β, and γ are dynamic weighting coefficients that are adjusted according to different scenarios and requirements to balance the importance of various factors in priority calculation.

[0076] Step S24: When a device is detected to be out of the group's communication range or its battery level is below a threshold, the group reconfiguration mechanism is triggered. For example, during a ride, if device 5 is too far from other devices in the group, exceeding the maximum allowed communication distance of 50 meters, the system will detect that the device has left the group's communication range. The system will then reassign the master device. Assuming that after reassessment, device 2 has the best signal coverage and battery level at this time, it will be reselected as the master device, and the slave device list will be updated to ensure that the group can continue to operate stably.

[0077] Example 2:

[0078] This embodiment details the process of establishing the dynamic communication link model in step S3. Specifically, it includes:

[0079] Step S31: Predict the motion trajectory of each device within the group using a Kalman filter. The Kalman filter is a commonly used algorithm that can predict the future position of a device based on its current position and speed, combined with a mathematical model. For example, in a cycling group, each bicycle is constantly moving. The Kalman filter predicts the motion trajectory of each device. Taking device 1 as an example, based on its current speed and direction, as well as motion data from the past period, the Kalman filter can predict its position change within the next 10 seconds. By calculating the relative position changes between devices within the future time window, the trend of distance changes between devices can be understood.

[0080] Step S32: Based on the signal attenuation model, and combined with data on device distance and environmental obstacles, estimate the link quality index. The signal attenuation model uses the following formula:

[0081]

[0082] Among them, LQI ij Let Li be the link quality index between device i and device j, which comprehensively reflects the quality of the communication link between them. L0 is the initial signal strength at a reference distance d0. Assuming the reference distance d0 is 1 meter, the initial signal strength L0 measured at this distance is -50 dBm. η is the path loss index, which generally ranges from 2 to 4 depending on the environment and signal transmission characteristics; in this scenario, it is set to 3. ijLet W be the distance between devices i and j, for example, the distance between device 1 and device 2 is measured to be 10 meters. k Let W1 be the attenuation coefficient of the k-th obstacle. Assume there are two obstacles on the transmission path between device 1 and device 2: the attenuation coefficient W1 of obstacle 1 is 5dB, and the attenuation coefficient W2 of obstacle 2 is 3dB. Let n be the total number of obstacles on the transmission path between the devices, where n = 2. This formula can be used to calculate the link quality index between device 1 and device 2.

[0083] Step S33: If the link quality index is lower than a preset threshold, for example, -80dBm, when the calculated link quality index is lower than this threshold, redundant instructions are inserted into the control instruction sequence and marked as high-priority transmission tasks. This is to ensure that important instructions can be transmitted accurately even in cases of poor link quality.

[0084] Step S34: Dynamically adjust the command transmission interval based on the link quality index. When the link quality index is high, it indicates that the communication link is stable, and the command transmission interval can be appropriately increased to reduce resource consumption; when the link quality index is low, the command transmission interval is shortened to ensure that critical commands are sent first and improve communication reliability.

[0085] Example 3:

[0086] This embodiment details the process of optimizing Bluetooth channel selection using an adaptive frequency hopping mechanism. Specifically, it includes:

[0087] Step S41: Real-time monitoring of the strength and distribution of interference sources in the current Bluetooth channel. A dedicated monitoring module continuously collects signal data from the Bluetooth channel and analyzes the strength and distribution of interference sources. For example, in a complex urban environment, there may be multiple interference sources such as Bluetooth devices and Wi-Fi signals. The monitoring module processes the collected data to generate an interference spectrum diagram, which clearly shows the distribution of interference intensity in different frequency bands.

[0088] Step S42: Based on the interference spectrum map, select the continuous idle channel with the lowest interference intensity as the candidate frequency band. In the generated interference spectrum map, find the region with the lowest interference intensity. Assuming that analysis shows the 80-85MHz frequency band has the lowest interference intensity and is continuously idle, then select it as the candidate frequency band.

[0089] Step S43 involves employing time-division multiplexing (TDM) technology to divide control commands into multiple data packets, which are then transmitted alternately in different candidate frequency bands. TDM works by dividing time into smaller segments, each segment used to transmit data packets in a different candidate frequency band. For example, if control commands are divided into 10 data packets, data packet 1 is transmitted in candidate frequency band 1 during the first time period, data packet 2 is transmitted in candidate frequency band 2 during the second time period, and so on. This method improves the anti-interference capability of communication.

[0090] Step S44: If channel quality is detected to be continuously deteriorating, for example, if the interference intensity of a candidate frequency band continues to rise over a period of time, resulting in a serious decline in communication quality, then an emergency frequency hopping mode is triggered to switch to a preset backup frequency band group.

[0091] The switching strategy for the spare frequency band group includes the following steps:

[0092] Step S441: Preset multiple non-overlapping frequency band groups and assign them different priorities. Assume that 3 non-overlapping frequency band groups are preset, with frequency band group 1 having the highest priority, frequency band group 2 second, and frequency band group 3 the lowest.

[0093] Step S442: When the primary frequency band group fails, attempt to switch in priority order until an available frequency band is found. If the currently used primary frequency band group is severely interfered with and cannot communicate normally, the system will first try to switch to frequency band group 1. If frequency band group 1 is also unavailable, it will continue to try frequency band group 2, and so on.

[0094] In step S443, after the switch is completed, a frequency band update command is broadcast to all devices in the group, and a frequency band synchronization timer is started. This is to ensure that all devices in the group can switch to the new frequency band in a timely manner and maintain synchronization.

[0095] In step S444, if the synchronization times out, for example, if some devices do not respond to the frequency band update command within the set 10-second synchronization time, the unresponsive devices will be forcibly disconnected and the group reconstruction process will be triggered to ensure the normal operation of the group.

[0096] Example 4:

[0097] This embodiment details the process of dynamically adjusting the brightness mode and flicker frequency of each device by updating group configuration and control commands in real time based on device status information and external environmental data. Specifically, it includes:

[0098] Step S51: Based on the ambient light intensity sensor data, the brightness level is divided into multiple intervals, and a reference brightness value is set for each interval. For example, by measuring the ambient light intensity using the ambient light intensity sensor, when the light intensity is between 0-100 Lux, the brightness level is divided into a low brightness interval, and a reference brightness value of 50 lumens is set; when the light intensity is between 101-500 Lux, it is divided into a medium brightness interval, and a reference brightness value of 150 lumens is set; when the light intensity is greater than 500 Lux, it is divided into a high brightness interval, and a reference brightness value of 300 lumens is set.

[0099] Step S52: Based on the relative positions of devices within the group, calculate the minimum safe brightness difference between the front and rear headlights to avoid visual interference. The calculation method is as follows:

[0100] Step S521: Based on the persistence of vision characteristic of the human eye, set a threshold for the brightness difference between the front and rear headlights. The persistence of vision characteristic of the human eye refers to the ability of the human eye to retain the image of an object for a short period of time after it disappears. Based on relevant research and experiments, the threshold for the brightness difference between the front and rear headlights is set to 50 lumens.

[0101] Step S522: Dynamically adjust the threshold range based on device spacing and relative speed. For example, when the device spacing is small, the brightness difference threshold is appropriately reduced to avoid visual interference; when the relative speed is high, the brightness difference threshold is appropriately increased to improve the warning effect. Assuming the device spacing is 5 meters and the relative speed is 10 meters per second, the brightness difference threshold is calculated and adjusted to 60 lumens.

[0102] Step S523: If a conflict in the brightness of the headlights of multiple vehicles is detected, such as in a cycling group where multiple bicycles are riding side by side, the brightness of the headlights of each vehicle may interfere with each other. The main control device intervenes and redistributes the brightness levels to ensure that the headlights of each vehicle can function normally, while avoiding visual interference.

[0103] Step S53: When a vehicle is detected to be decelerating or turning suddenly, the flashing frequency of the corresponding headlight is dynamically increased and synchronized to all devices in the group. For example, when a vehicle turns left, the system detects the turning action through the vehicle's sensors and immediately increases the flashing frequency of the left headlight from 2 times per second to 5 times per second. This instruction is then synchronously sent to all devices in the group, causing the flashing frequency of the left headlights in the entire group to increase, thereby alerting surrounding vehicles and pedestrians.

[0104] Step S54: If the battery level of a device falls below a threshold (assuming the threshold is set to 10%), when a device's battery level is detected to be below this value, its brightness level is automatically reduced, and the main control device is notified to reassign lighting tasks. For example, if the battery level of device 4 drops to 8%, the system automatically adjusts its brightness level from high to low and sends a notification to the main control device. The main control device then reassigns lighting tasks based on the actual situation to ensure that the lighting effect of the entire group is not significantly affected.

[0105] Example 5:

[0106] This embodiment details the implementation of the dynamic weighting coefficients, specifically including:

[0107] Step S101: Initialize the baseline values ​​of α, β, and γ based on the number of devices in the group and the environmental complexity. Assuming a group containing 10 bicycle light devices with medium environmental complexity, after comprehensive consideration, initialize the baseline values ​​of α to 0.3, β to 0.3, and γ to 0.4. These baseline values ​​are set to ensure reasonable calculation of device priorities in the initial stage.

[0108] Step S102: Monitor the rate of change in device status in real time. For example, during cycling, the speed of device 7 suddenly drops from 15 meters per second to 5 meters per second, while the battery level also drops rapidly from 60% to 40%. After detecting these changes, the system increases the corresponding weighting coefficients. Due to the sudden drop in speed, the value of α is increased, assuming it is increased to 0.4; due to the sudden drop in battery level, the value of β is increased, assuming it is increased to 0.4, while keeping the value of γ unchanged.

[0109] Step S103 involves optimizing the weight combination using the gradient descent algorithm to achieve optimal group stability through priority allocation. Gradient descent is a commonly used optimization algorithm that continuously adjusts the weight coefficients to optimize the objective function (group stability in this scenario). During this process, the group stability index is continuously calculated, and the values ​​of α, β, and γ are adjusted according to the principles of gradient descent. For example, after multiple iterations, the final values ​​of α, β, and γ are determined to be 0.35, 0.35, and 0.3, at which point the priority allocation achieves optimal group stability. When calculating device priorities, formula P is still used. j =α·v j +β·e j +γ·s j By continuously optimizing the weighting coefficients, we can ensure that the calculation of device priorities is more reasonable, thereby improving the overall operating efficiency and stability of the group.

[0110] Example 6:

[0111] In practical scenarios, signal attenuation models are used when assessing the communication link quality between lighting devices in a group of lights. Assume a large outdoor lighting group scenario where lighting device M and device N need to communicate and work together. First, define the parameters in the signal attenuation model formula: the reference distance d0 is set to 1 meter, a baseline distance used to calibrate signal strength; the initial signal strength L0 at distance d0 is measured to be -50 dBm, representing the signal strength under ideal close-range conditions; the path loss exponent η, based on the signal propagation characteristics of this open outdoor area, is set to 2.5, reflecting the rate attenuation of the signal with increasing distance during propagation; and the distance d between device M and device N... MN The distance, measured using positioning technology, is 15 meters, which is one of the key factors affecting signal attenuation. Meanwhile, there are obstacles on the signal transmission path between devices M and N. Four obstacles were detected, labeled Obstacle 1, Obstacle 2, Obstacle 3, and Obstacle 4, with attenuation coefficients W1 of 3dB, W2 of 2.5dB, W3 of 2dB, and W4 of 1.5dB, i.e., n = 4.

[0112] Substitute these parameters into the signal attenuation model formula Link Quality Index (LQI) between computing device M and device N MN :

[0113] LQI MN = -50 - 10 × 2.5 × log 10 (15÷1)-(3+2.5+2+1.5)

[0114] = -50 - 25 × log 10 (15)-9

[0115] ≈-50-25×1.176-9

[0116] =-50-29.4-9

[0117] = -88.4dBm

[0118] Through such calculations, the link quality between devices M and N can be accurately assessed. If the calculated link quality index is lower than a preset threshold (assuming the preset threshold is -80dBm), the system will insert redundant instructions into the control instruction sequence according to relevant policies and mark them as high-priority transmission tasks. At the same time, the instruction transmission interval will be dynamically adjusted according to the link quality index to ensure the reliability of communication.

[0119] In terms of brightness control of headlight groups, the calculation method for the minimum safe brightness difference plays a crucial role. Taking a multi-vehicle nighttime driving scenario as an example, the headlights on the vehicles form a headlight group. First, in step S521, based on the persistence of vision characteristics of the human eye, a threshold for the brightness difference between the front and rear headlights is set. Through research and extensive practical testing, an initial threshold of 60 lumens is set. This is to ensure that, under normal driving conditions, the brightness difference between the front and rear headlights will not cause visual interference to the driver.

[0120] Next, step S522 is performed, dynamically adjusting the threshold range based on the device spacing and relative speed. Assume that at a certain moment, vehicle A and vehicle B are traveling on the same route, with vehicle A in front and vehicle B behind. Sensors measure a spacing of 10 meters between the two vehicles' lighting devices, and a relative speed of 5 meters per second. Based on relevant algorithms and empirical formulas, combined with the current spacing and speed data, the initial threshold is adjusted. Due to the small spacing and slow relative speed, to avoid visual interference, the threshold is appropriately reduced, calculated and adjusted to 50 lumens.

[0121] Next, in step S523, if a conflict in the brightness of headlights of multiple vehicles traveling side-by-side is detected—for example, in a road section where multiple vehicles are traveling side-by-side, the headlights of vehicles C, D, and E interfere with each other—the main control device intervenes. It collects the status and location information of each vehicle's headlights and reallocates the brightness levels. Based on factors such as the vehicle's direction of travel and ambient lighting conditions, the main control device adjusts the brightness of vehicle C's headlights from 300 lumens to 250 lumens, vehicle D's taillights from 200 lumens to 180 lumens, and vehicle E's headlights from 280 lumens to 230 lumens. This ensures that each vehicle's headlights can function properly for illumination and warning while avoiding visual interference and ensuring driving safety. In this way, the calculation method for the minimum safe brightness difference is effectively applied in practical applications to achieve reasonable control of the brightness of the headlight group, improving overall safety and functionality.

[0122] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0123] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for controlling bicycle light groups via Bluetooth wireless communication, characterized in that, Includes the following steps: Step S1: Scan and identify bicycle light devices within a preset range via Bluetooth protocol, and collect the device's unique identifier, current status information, and location data. The status information includes at least the brightness level, battery level, and communication signal strength. Step S2: Based on the dynamic topology management algorithm, the identified bicycle light devices are divided into multiple logical groups. Each group contains at least one master control device and several slave devices. The master control device is responsible for the distribution and coordination of instructions within the group. Step S3: Based on the location and movement trends of devices within the group, establish a dynamic communication link model, predict the signal transmission stability between devices within the group, and generate a group control command sequence.

2. The method for controlling bicycle light groups via Bluetooth wireless communication according to claim 1, characterized in that, Step S2 further includes: Step S21: Set constraints for group division, including the maximum allowable communication distance between devices, the minimum remaining battery power threshold, and the signal strength threshold; Step S22: Construct an adjacency matrix based on device location data, and select the device with the widest signal coverage and sufficient power as the master control device using a greedy algorithm; Step S23: Assign a priority to each slave device. The priority is dynamically calculated based on the device's movement speed, remaining battery life, and signal stability. Step S24: When a device is detected to be out of the group communication range or its power is below the threshold, the group reconstruction mechanism is triggered to reallocate the master device and update the slave device list.

3. The method for controlling bicycle light groups via Bluetooth wireless communication according to claim 1, characterized in that, The establishment of the dynamic communication link model in step S3 includes: Step S31: Predict the motion trajectory of each device in the group using a Kalman filter, and calculate the relative position changes between devices within the future time window; Step S32: Estimate the link quality index based on the signal attenuation model and combined with data on distance between devices and environmental obstacles; Step S33: If the link quality index is lower than the preset threshold, insert redundant instructions into the control instruction sequence and mark them as high-priority transmission tasks; Step S34: Dynamically adjust the instruction transmission interval based on the link quality index to ensure that critical instructions are sent first.

4. The method for controlling bicycle light groups via Bluetooth wireless communication according to claim 1, characterized in that, Also includes: Step S4: Optimize Bluetooth channel selection through adaptive frequency hopping mechanism and adjust communication frequency band based on real-time environmental interference data; The specific steps of the adaptive frequency hopping mechanism include: Step S41: Monitor the intensity and distribution of interference sources in the current Bluetooth channel in real time and generate an interference spectrum diagram; Step S42: Based on the interference spectrum, select the continuous idle channel with the lowest interference intensity as the candidate frequency band; Step S43: Using time division multiplexing technology, the control command is divided into multiple data packets and transmitted alternately in different candidate frequency bands; Step S44: If the channel quality continues to deteriorate, the emergency frequency hopping mode is triggered, and the system switches to a preset backup frequency band group.

5. The method for controlling bicycle light groups via Bluetooth wireless communication according to claim 1, characterized in that, Also includes: Step S5: Based on device status information and external environment data, update group configuration and control commands in real time, and dynamically adjust the brightness mode and flicker frequency of each device to achieve coordinated control; specific steps include: Step S51: Based on the ambient light intensity sensor data, divide the brightness level into multiple intervals and set a reference brightness value for each interval; Step S52: Based on the relative positions of devices within the group, calculate the minimum safe brightness difference between the front and rear headlights to avoid visual interference; Step S53: When a vehicle is detected to decelerate or turn suddenly, dynamically increase the flashing frequency of the corresponding headlights and synchronize it to all devices in the group; Step S54: If the battery level of a device is lower than the threshold, its brightness level will be automatically reduced, and the main control device will be notified to reassign the lighting task.

6. The method for controlling bicycle light groups via Bluetooth wireless communication according to claim 2, characterized in that, The formula for calculating the priority in step S23 is as follows: P j =α·v j +β·e j +γ·s j Among them, P j v is the priority value of device j. j Represents the speed of movement of device j, e j s represents the remaining battery percentage. j This represents the signal stability index, where α, β, and γ are dynamic weighting coefficients.

7. The method for controlling bicycle light groups via Bluetooth wireless communication according to claim 3, characterized in that, The signal attenuation model in step S32 uses the following formula: Among them, LQI ij Let L0 be the link quality index between device i and device j, L0 be the initial signal strength at the reference distance d0, and η be the path loss index. ij W is the distance between devices i and j. k is the attenuation coefficient of the k-th obstacle, and n is the total number of obstacles on the transmission path between devices.

8. The method for controlling bicycle light groups via Bluetooth wireless communication according to claim 4, characterized in that, The switching strategy for the spare frequency band group in step S44 includes: Step S441: Preset multiple non-overlapping frequency band groups and assign them different priorities; Step S442: When the main frequency band group fails, attempt to switch in priority order until an available frequency band is found; Step S443: After the switch is completed, broadcast the frequency band update command to all devices in the group and start the frequency band synchronization timer; Step S444: If synchronization times out, forcibly disconnect unresponsive devices and trigger the group reconfiguration process.

9. The method for controlling bicycle light groups via Bluetooth wireless communication according to claim 5, characterized in that, The method for calculating the minimum safe brightness difference in step S52 is as follows: Step S521: Based on the persistence of vision of the human eye, set the threshold for the difference in brightness between the front and rear headlights; Step S522: Dynamically adjust the threshold range based on device spacing and relative speed; Step S523: If a conflict in the brightness of the headlights of multiple vehicles is detected, the main control device will intervene and redistribute the brightness levels.

10. The method for controlling bicycle light groups via Bluetooth wireless communication according to claim 6, characterized in that, The adjustment strategy for the dynamic weighting coefficients includes: Step S101: Initialize the baseline values ​​of α, β, and γ based on the number of devices in the group and the complexity of the environment; Step S102: Monitor the rate of change of device status in real time. If the speed of movement or the power of a device drops suddenly, increase the corresponding weight coefficient. Step S103: Optimize the weight combination using the gradient descent algorithm to achieve optimal group stability in priority allocation.

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