Riding earphone low-delay distress early warning ad hoc network communication system and method

Abstract

The invention discloses a riding earphone low-delay distress early warning ad hoc network communication system and method, and relates to the technical field of motorcycle riding communication, and the system is characterized in that after an ad hoc network configuration module is started, a network is established, resource blocks are distributed, a resource pool is constructed, and rule parameters are configured; the multi-dimensional data acquisition and sharing module acquires, processes and shares various data; the signal fusion judgment module judges the effectiveness of the collision signal and outputs an early warning instruction; the resource scheduling low-delay transmission module allocates resources to realize differentiated transmission; a receiving end volume adjusting module analyzes the data and adaptively adjusts early warning volume output; by constructing a self-organizing wireless communication network and integrating multi-dimensional data, accurate transmission of collision signals is realized, false alarm and missing alarm are avoided, resource scheduling is optimized, data differentiation low-delay transmission, volume self-adaptive adjustment, anti-interference capability enhancement and convenience improvement are realized, the advantages in multiple aspects of safety early warning are obvious, and the method is suitable for popularization and application. And more comprehensive and practical safety protection is provided for riding groups.

Description

Technical Field

[0001] This invention relates to the field of motorcycle riding communication technology, specifically to a low-latency distress warning self-organizing network communication system and method for riding headsets. Background Technology

[0002] With the popularization of cycling and the continuous growth in demand for long-distance group rides, communication coordination and safety protection during cycling have become core issues of concern in the industry. As a high-speed mode of transportation, real-time information interaction between riders is directly related to the coordination of movement and the efficiency of risk avoidance, and is a key link in ensuring cycling safety. Against this backdrop, cycling headsets have gradually become core equipment for group rides. Their core functions revolve around voice communication, providing riders with basic information exchange support such as route coordination and road condition sharing. However, the complexity and uncertainty of the cycling environment make early warning and rapid response to sudden dangers an important development direction for cycling communication technology. Various emergencies that may be encountered during cycling place higher demands on the automation and immediacy of communication systems. How to achieve efficient transmission of distress information through technological innovation and build a proactive safety protection system has become the core driving force for upgrading cycling communication equipment.

[0003] Traditional cycling headsets are designed primarily for voice communication, only meeting the basic information exchange needs between cyclists. They have significant limitations in safety warnings and emergency responses. These devices lack automatic detection and warning mechanisms for sudden dangers, relying entirely on cyclists to manually initiate voice distress calls or warnings. When encountering danger, cyclists may be unable to initiate voice communication for help due to injury, high concentration on dealing with the danger, or loss of mobility, making it difficult for fellow cyclists to know about the danger. Furthermore, traditional devices lack dedicated emergency information transmission channels and clear priority for information transmission. Even if cyclists attempt to transmit warnings, delays in voice communication and environmental interference may result in untimely or incomplete information transmission. In addition, traditional technology does not consider the need for automated information transmission in emergency situations, lacking the ability to accurately identify and rapidly broadcast distress signals, and failing to provide proactive warnings. This leaves cyclists in a passive state in the face of sudden dangers, making it difficult to effectively avoid secondary accidents and resulting in a serious lack of safety assurance. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a low-latency, self-organizing network communication system and method for distress warning in cycling headphones. This system automatically builds a self-organizing wireless communication network, synchronously collects multi-dimensional data such as collision signals and cycling speed, accurately identifies hazards through a multi-node signal fusion and judgment mechanism, and achieves low-latency transmission of warning information based on three-level priority scheduling and anti-interference transmission technology. The receiving end can adaptively adjust the warning volume according to the cycling status to ensure clear information perception. This invention adds a dedicated data transmission channel, which can automatically trigger warning broadcasts without manual intervention, effectively improving the safety response efficiency of group cycling and building an active protection system for cyclists.

[0005] To solve the above-mentioned technical problems, this invention provides the following technical solution: On one hand, a low-latency distress warning self-organizing network communication system for cycling headphones, comprising: a self-organizing network configuration module: used to automatically establish a self-organizing wireless communication network after each headphone node is started, allocate dedicated distress data resource blocks to each node and construct a global warning resource pool, and synchronously configure three-level data scheduling priority rules, speed-volume association logic, and OFDM anti-interference modulation parameters; the distress data resource blocks allocated by the self-organizing network configuration module are independently divided according to node identifiers, and exclusively store distress-related data such as collision features and speed anomalies collected by each node, configure dedicated access permissions to prevent data confusion, and synchronously bind data encryption and local backup mechanisms; the global warning resource pool integrates the distress data resource block information of each node, constructs a resource index table to achieve fast retrieval, has a built-in dynamic resource scheduling mechanism to prioritize the response to warning data transmission needs, and synchronously configures resource status monitoring and redundant backup units to ensure resource availability; a multi-dimensional data acquisition and sharing module: based on the communication network established by the self-organizing network configuration module, it collects and processes collision signal features and real-time cycling speed. The system includes: a multi-node collision signal strength data acquisition and sharing module; a signal fusion judgment module; a resource scheduling low-latency transmission module; a receiving end volume adjustment module; and a receiving end volume adjustment module. The receiving end volume adjustment module receives and parses the data sent by the resource scheduling low-latency transmission module, processes it according to priority, and adaptively adjusts the warning volume output using a speed-warning linkage volume adaptive adjustment algorithm, combined with the locally stored real-time riding speed and the fusion confidence level output by the signal fusion judgment module. The receiving end receives collision signal strength data, sends collision feature data to adjacent nodes that meet the sharing conditions after verifying data integrity, and, after verifying data integrity, determines the validity of the collision signal using a multi-node collision signal dynamic fusion confidence level algorithm, combined with a preset threshold and a continuous frame verification mechanism.

[0006] Furthermore, in the self-organizing network configuration module, the specific method for building a self-organizing wireless communication network is as follows: nodes identify surrounding nodes of the same type through an active scanning mechanism, the scanning channels are scanned sequentially according to a preset channel sequence and distributed within a fixed frequency range, the network topology adopts a mesh structure, supports dynamic addition and removal of nodes, and optimizes node power consumption to extend standby time.

[0007] Furthermore, in the self-organizing network configuration module, the three-level data scheduling priority rules configured by the self-organizing network configuration module are as follows: the first priority is allocated to distress warning data, which occupies communication resources and is transmitted first; the second priority is allocated to node status data, which is transmitted second priority; the third priority is allocated to ordinary interactive data, which is transmitted on demand; the speed-volume association logic is as follows: the volume is adjusted in stages according to the real-time riding speed collected by the node, the base volume is maintained in the low speed range, and the volume increases linearly with the speed in the medium and high speed range to cancel the environmental noise, and the volume warning is triggered when speeding occurs; the OFDM anti-interference modulation parameters are configured as follows: 64 subcarriers are orthogonally distributed, the modulation method is QPSK, and the cyclic prefix length is set to 1 / 8 of the symbol period.

[0008] Furthermore, in the multi-dimensional data acquisition and sharing module: the collision signal characteristics are acquired by detecting changes in acceleration, and a valid collision signal is determined when the change in acceleration exceeds 5g; the real-time riding speed is acquired by obtaining instantaneous speed values, and an overspeed state is marked when the speed exceeds 60km / h; the distance between adjacent nodes is acquired by calculating the round-trip time of communication signals between nodes, and a close proximity is marked when the distance is less than 10 meters; the signal strength is acquired by detecting the amplitude of communication signals, and a weak signal state is marked when the signal strength is below -85dBm.

[0009] Furthermore, in the multi-dimensional data acquisition and sharing module, the specific process of sending collision feature data to adjacent nodes that meet the sharing conditions is as follows: First, the acquired and processed collision feature data is standardized and encapsulated, and the encapsulation content includes the collision signal peak value, duration, acquisition timestamp, and current node identifier; then, the CRC32 verification mechanism is used to complete the data integrity verification; after the verification is passed, adjacent nodes that simultaneously meet the following conditions are selected: signal strength is not lower than -65dBm, distance from the current node is not more than 300 meters, and the preset identity verification is passed and the transmission queue occupancy rate is less than 50%; the encapsulated collision feature data is sent to the selected nodes packet by packet according to the secondary data scheduling priority; during the transmission process, the link status is monitored in real time, and when the link is interrupted, it is automatically switched to the backup communication channel to continue transmission.

[0010] Furthermore, in the signal fusion determination module, the mathematical expression for the multi-node collision signal dynamic fusion confidence algorithm is: ;in, It is the confidence level of dynamic fusion of multi-node collision signals. The number of adjacent nodes participating in the fusion; For the first The signal strength weight of each node is given by the formula: ; The signal strength value of the i-th node; This represents the minimum signal strength. This represents the maximum signal strength. For the first Distance weights of each node; For the first The speed of each node is associated with a weight; For the first The peak value of the collision impact of each node; For the first The duration of the collision signal of each node; This is a global velocity correction factor; Real-time riding speed at the current node. For the first Real-time cycling speed of adjacent nodes; For the first The straight-line distance between the current node and each of its neighboring nodes; This represents the maximum value of the peak impact force during the collision. This represents the maximum duration of the collision signal. The weighting coefficient for the peak impact value during collision; This is the weighting coefficient for the duration of the collision signal.

[0011] Furthermore, in the signal fusion determination module, the specific process of determining the validity of collision signals by combining preset thresholds and continuous frame verification mechanisms is as follows: First, the signal peak value in the single-frame collision feature data is compared with a preset peak value threshold, and the signal duration is compared with a preset duration threshold. Valid single-frame data that simultaneously meets the requirements of a peak value not less than 15g and a duration not less than 20ms is selected. Then, continuous frame verification is performed on the valid single-frame data: In a continuous 10-frame data window based on the current frame, when the number of valid single-frame data is not less than 8 frames, the data window is determined to have passed continuous frame verification. For the data window that has passed continuous frame verification, the confidence value calculated by combining the multi-node collision signal dynamic fusion confidence algorithm is used. Compare with the preset reliability threshold of 0.8. If If the value is less than 0.8, the collision signal is deemed valid and a warning command is output; otherwise, the collision signal is deemed invalid.

[0012] Furthermore, in the resource scheduling and low-latency transmission module, the three-level priority preemption mechanism is as follows: Level 1 priority distress warning data has the highest resource preemption right, and can directly interrupt the transmission process of Level 2 and Level 3 priority data and occupy the allocated communication resources, releasing the resources after the transmission is completed; Level 2 priority node status data can only preempt the resources of Level 3 priority ordinary interactive data, and cannot interrupt the transmission of Level 1 priority data; Level 3 priority data occupies the remaining resources when there is no high-priority data transmission, and once a high-priority data request is detected, it immediately releases the resources and enters the waiting queue; Data of the same priority uses a round-robin scheduling mechanism to allocate resources, while the system monitors the resource occupancy status in real time.

[0013] Furthermore, in the receiving end processing and volume adjustment module, the mathematical expression for the speed-warning linkage volume adaptive adjustment algorithm is: ; ; ;in, This is the final output volume; Based on the basic volume, , Maximum volume; The volume increment is correlated with the speed. Increase the volume for alert linkage; This is the maximum volume setting. Real-time riding speed at the current node; Confidence level for dynamic fusion of multi-node collision signals; This is the floor function.

[0014] On the other hand, a low-latency distress warning self-organizing network communication method for cycling headphones is provided. The specific steps of this method are as follows: S100, self-organizing network construction and configuration: after each headphone node starts, it establishes a self-organizing wireless communication network, allocates distress data resource blocks, constructs a global warning resource pool, and configures three-level data scheduling priority rules, speed-volume association logic, and OFDM anti-interference modulation parameters; S200, multi-dimensional data acquisition and sharing: collect collision signal characteristics, real-time cycling speed, distance between adjacent nodes, and signal strength data, preprocess and encapsulate the collision feature data and verify its integrity, filter adjacent nodes that meet the conditions, and send data; S300, signal fusion judgment: receive and verify the collision feature data, and determine the validity of the collision signal and output a warning command after single-frame filtering, continuous frame verification, and confidence comparison; S400, scheduling low-latency transmission: dynamically allocate resources according to the valid warning command, start a three-level priority preemption mechanism, and combine OFDM modulation technology and simplified MAC layer protocol to achieve low-latency transmission; S500, receiver volume adjustment: receive and parse the data, process it according to priority, and adjust the warning volume output through a speed-warning linkage volume adaptive adjustment algorithm.

[0015] Compared with existing technologies, this low-latency distress warning self-organizing network communication system and method for cycling headsets has the following beneficial effects: First, by constructing a self-organizing wireless communication network and integrating multi-dimensional data acquisition and sharing mechanisms, this invention achieves accurate identification and rapid transmission of collision signals. It can automatically capture distress-related data without manual intervention. Through a multi-node signal fusion judgment mechanism, it ensures the accuracy of warning information and avoids false alarms or missed alarms. The data transmission channel runs parallel to voice communication and has a higher priority, ensuring that distress information can be delivered to surrounding nodes in a timely manner. This helps fellow riders to know the danger as soon as possible and take evasive measures quickly, effectively reducing the risk of secondary accidents. At the same time, it buys valuable rescue time for those in distress. This design solves the limitations of traditional cycling headsets that can only rely on voice communication and cannot effectively transmit warnings in distress. It shifts from passive communication to active safety protection, significantly improving the safety guarantee capability during cycling and making the safety defense line of cycling groups more solid when traveling in groups.

[0016] Second, this invention optimizes resource scheduling mechanisms and transmission protocols, combined with anti-interference modulation technology, to achieve differentiated low-latency transmission of data with different priorities, ensuring the timeliness and stability of warning information transmission. Simultaneously, based on real-time riding status and warning confidence level, the volume adaptive adjustment logic allows the receiving end to dynamically adjust the warning volume according to the actual scenario, ensuring clear perception of warning information in various riding environments, unaffected by environmental noise or riding speed. This design strengthens the anti-interference capability of the communication link and improves user convenience, providing a scenario-appropriate warning experience without manual operation. Compared to traditional cycling communication devices, it exhibits significant advantages in the comprehensiveness, timeliness, and adaptability of safety warnings, offering more comprehensive safety protection support for cyclists and making safety assurance for group riding more targeted and practical.

[0017] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0019] Figure 1 A flowchart illustrating the steps of a low-latency distress warning self-organizing network communication method for cycling headphones;

[0020] Figure 2 This is a schematic diagram of a low-latency distress warning self-organizing network communication system for cycling headphones. Detailed Implementation

[0021] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0022] Example 1:

[0023] Application scenario of a low-latency distress warning self-organizing network communication system for cycling headphones.

[0024] In urban cycling environments, when multiple headset nodes equipped with this system are activated simultaneously, the system's self-organizing network configuration module immediately begins operation. It actively scans nearby headset nodes of the same type, sequentially scanning channels within a fixed frequency range according to a preset sequence to build a mesh-like self-organizing wireless communication network. This supports the dynamic addition and removal of nodes, optimizes node power consumption, extends standby time, adapts to the need for flexible node additions and removals during cycling, and reduces power consumption. This module allocates an independent distress data resource block to each node, exclusively storing collision characteristics, speed anomalies, and other data collected by each node. It configures exclusive access permissions and binds data encryption and local backup mechanisms to ensure that each node's data is independent, unmixed, and securely traceable. Simultaneously, it integrates distress data resource block information from all nodes to construct a global early warning resource pool, establishing a resource index table for convenient and rapid retrieval. Combined with a dynamic resource scheduling mechanism, status monitoring, and redundant backup units, resource allocation is more efficient, prioritizing responses to early warning data transmission needs and ensuring stable resource availability. In addition, the module is also configured with a three-level data scheduling priority rule: the first level is for distress warning data, the second level is for node status data, and the third level is for normal interactive data, ensuring that emergency data is transmitted first; it is configured with speed-volume correlation logic, maintaining a baseline volume at low speeds, increasing the volume linearly with speed at medium and high speeds, and triggering a volume warning when speeding, so that warnings can be clearly perceived at different riding speeds; it is configured with OFDM anti-interference modulation parameters, using 64 subcarriers orthogonally distributed, QPSK modulation, and a cyclic prefix length of 1 / 8 symbol period, to improve the anti-interference capability of data transmission and reduce the impact of environmental interference on communication.

[0025] During system operation, the multi-dimensional data acquisition and sharing module continuously collects data based on the established communication network: it acquires collision signal characteristics by detecting changes in acceleration, and determines a valid collision signal when the change in acceleration exceeds 5g, accurately capturing real collision situations and avoiding false triggers; it acquires real-time riding speed by obtaining instantaneous speed values, and marks a speed exceeding 60km / h as speeding, promptly identifying dangerous riding speeds; it acquires the distance between adjacent nodes by calculating the round-trip time of communication signals between nodes, and marks nodes less than 10 meters apart as close neighbors, understanding the close-range distribution of surrounding nodes; and it acquires signal strength by detecting the amplitude of communication signals, and marks a weak signal state when the signal strength is below -85dBm, providing a basis for subsequent data transmission link selection. Next, the module standardizes and encapsulates the collected and processed collision feature data. The encapsulation includes the peak value of the collision signal, duration, collection timestamp, and current node identifier. Then, a CRC32 check mechanism is used to complete the data integrity verification to ensure that the transmitted data is free of missing or errors. After the verification is passed, neighboring nodes with a signal strength of not less than -65dBm, a distance of no more than 300 meters from the current node, and who have passed the preset authentication and have a transmission queue occupancy rate of less than 50% are selected. These conditions ensure that the data transmission link is stable, the range is reasonable, the identity is reliable, and the transmission efficiency is not low. The encapsulated collision feature data is sent to these nodes packet by packet according to the secondary data scheduling priority. During the transmission process, the link status is monitored in real time. If the link is interrupted, the system automatically switches to the backup communication channel to continue transmission to avoid data transmission interruption. At the same time, the speed data is stored locally to provide basic data support for subsequent volume adjustment.

[0026] After receiving the collision feature data sent by the multi-dimensional data acquisition and sharing module, the signal fusion judgment module first verifies the data integrity to ensure that subsequent judgments are based on complete and valid data. Then, it performs single-frame data filtering, comparing the signal peak value and signal duration in the single-frame collision feature data with preset peak value thresholds and preset duration thresholds, filtering out valid single-frame data with a peak value not less than 15g and a duration not less than 20ms to eliminate transient interference signals and improve judgment accuracy. Subsequently, a continuous frame verification mechanism is activated. In a continuous 10-frame data window based on the current frame, if the number of valid single-frame data is not less than 8 frames, the window is considered to have passed continuous frame verification, further filtering out accidental interference and ensuring the persistence and authenticity of the collision signal. For data windows that pass continuous frame verification, the multi-node collision signal dynamic fusion confidence algorithm is called to calculate the confidence value. The mathematical expression of the multi-node collision signal dynamic fusion confidence algorithm is: ;in, It is the confidence level of dynamic fusion of multi-node collision signals. The number of adjacent nodes participating in the fusion; For the first The signal strength weight of each node is given by the formula: ; The signal strength value of the i-th node; This represents the minimum signal strength. This represents the maximum signal strength. For the first Distance weights of each node; For the first The speed of each node is associated with a weight; For the first The peak value of the collision impact of each node; For the first The duration of the collision signal of each node; This is a global velocity correction factor; Real-time riding speed at the current node. For the first Real-time cycling speed of adjacent nodes; For the first The straight-line distance between the current node and each of its neighboring nodes; This represents the maximum value of the peak impact force during the collision. This represents the maximum duration of the collision signal. The weighting coefficient for the peak impact value during collision; The weighting coefficient for the duration of the collision signal is compared with a preset confidence threshold of 0.8. If the confidence value is less than 0.8, the collision signal is deemed valid and a warning command is output. The comprehensive use of multi-node data makes the collision determination more comprehensive and reliable, avoiding misjudgment or omission.

[0027] Upon receiving a valid early warning command, the low-latency transmission module for resource scheduling drives the global early warning resource pool to dynamically allocate resources to distressed nodes, initiating a three-tiered priority preemption mechanism: First-priority distress warning data directly interrupts the transmission of second- and third-priority data and occupies their allocated communication resources; resources are released upon completion of transmission, ensuring the most urgent warning data is transmitted first. Second-priority node status data can only preempt resources from third-priority ordinary interactive data, without interrupting first-priority data transmission, balancing node status monitoring and urgent early warning transmission needs. Third-priority data occupies remaining resources when no high-priority data is being transmitted; upon detecting a high-priority data request, resources are immediately released and the data enters a waiting queue. Data of the same priority uses a round-robin scheduling mechanism to allocate resources, and the system monitors resource occupancy status in real time to ensure reasonable resource allocation and prevent waste. Simultaneously, combining OFDM modulation technology and a simplified MAC layer protocol reduces data transmission latency, enabling differentiated low-latency transmission of data with different priorities, allowing early warning information to be delivered to relevant nodes quickly.

[0028] After receiving and parsing the warning data, the volume adjustment module at the receiving end processes the warning information according to priority: first, it uses the speed-warning linkage volume adaptive adjustment algorithm, combined with the locally stored real-time riding speed and fusion confidence, to calculate and adjust the output volume. The mathematical expression of the speed-warning linkage volume adaptive adjustment algorithm is: ; ; ;in, This is the final output volume; Based on the basic volume, , Maximum volume; The volume increment is correlated with the speed. Increase the volume for alert linkage; This is the maximum volume setting. Real-time riding speed at the current node; Confidence level for dynamic fusion of multi-node collision signals; The function rounds down: the base volume is set to 50% of the maximum volume to ensure the clarity of basic warnings; the speed-related volume increment is calculated based on real-time riding speed, automatically increasing the volume at medium to high speeds to counteract wind and environmental noise, and maintaining a clear and non-intrusive base volume at low speeds to ensure the warning information is clearly perceived; simultaneously, the voice broadcast function is activated, repeatedly broadcasting the preset warning voice "A collision has occurred between adjacent nodes, please take timely precautions" at the adjusted volume, with the broadcast frequency set to 3 times, ensuring that the rider clearly receives the danger information while avoiding interference from continuous broadcasts. Figure 2 As shown in the image, nearby cyclists, upon hearing the voice announcement, can immediately become aware of potential collision hazards ahead or at nearby nodes, allowing them to quickly take evasive action such as slowing down or avoiding the area. This effectively reduces the occurrence of secondary accidents, buys time for rescue of those in distress, and ensures the safety of their own cycling.

[0029] In summary, this low-latency distress warning self-organizing network communication system for cycling headsets, used in urban periphery cycling scenarios, rapidly establishes a mesh communication network through a self-organizing network configuration module. It allocates independent resource blocks and constructs a global warning resource pool, clearly defining data priorities and anti-interference parameters. A multi-dimensional data acquisition and sharing module accurately collects key data such as collision and speed, which is then transmitted in a targeted manner after standardized encapsulation and verification. A signal fusion and judgment module ensures accurate collision judgment through single-frame filtering, continuous frame verification, and a multi-node collision signal dynamic fusion confidence algorithm. A resource scheduling low-latency transmission module achieves rapid data transmission based on a priority preemption mechanism and related technologies. The receiving end volume adjustment module adapts to different scenarios through a speed-warning linked volume adaptive adjustment algorithm, ensuring timely, clear, and reliable warnings during cycling distress throughout the entire process.

[0030] Example 2:

[0031] Application scenarios of a low-latency distress warning self-organizing network communication method for cycling headphones.

[0032] In suburban cycling routes, multiple headset nodes need to achieve collaborative communication for distress warnings. This method employs a low-latency distress warning self-organizing network communication approach for cycling headsets. The specific implementation process is as follows: Figure 1 The following is stated:

[0033] S100 Self-Organizing Network Configuration: After each earphone node starts, it automatically establishes a self-organizing wireless communication network. Through an active scanning mechanism, it identifies nearby nodes of the same type, scanning channels sequentially within a fixed frequency range according to a preset channel sequence. This constructs a mesh network that supports dynamic node addition and removal, adapting to scenarios where nodes are scattered and may increase or decrease during suburban cycling. Node power consumption is optimized to extend standby time, meeting the needs of long-term suburban cycling. Simultaneously, each node is allocated an independent distress data resource block for dedicated storage of subsequent distress-related data such as collision characteristics and speed anomalies collected by each node. Dedicated access permissions are configured to prevent data confusion, and data encryption and local backup mechanisms are implemented to ensure data storage security and clear ownership. The distress data resource block information from all nodes is integrated to construct a global early warning resource pool. A resource index table is established for rapid retrieval, and a dynamic resource scheduling mechanism, resource status monitoring, and redundant backup units are configured to improve resource allocation efficiency and stability, ensuring that early warning data transmission needs are prioritized. In addition, a three-level data scheduling priority rule is configured simultaneously: the first level is allocated to distress warning data, the second level to node status data, and the third level to ordinary interactive data, clearly defining the data transmission priority order; speed-volume correlation logic is configured, maintaining a baseline volume at low speeds, linearly increasing the volume with speed at medium and high speeds, and triggering a volume warning when speeding, adapting to the warning perception needs at different riding speeds; OFDM anti-interference modulation parameters are configured, using 64 subcarriers orthogonally distributed, QPSK modulation, and a cyclic prefix length of 1 / 8 symbol period, enhancing the anti-interference capability of data transmission and coping with complex wireless environments in the suburbs.

[0034] S200, Multi-dimensional Data Acquisition and Sharing: Based on the established communication network, it continuously collects collision signal characteristics, real-time riding speed, distance to adjacent nodes, and signal strength data. Specifically, collision signal characteristics are acquired by detecting changes in acceleration; a change in acceleration exceeding 5g is considered a valid collision signal, accurately capturing real collision events. Real-time riding speed is acquired by obtaining instantaneous speed values; speeds exceeding 60km / h are marked as speeding, promptly identifying dangerous riding speeds. Distance to adjacent nodes is acquired by calculating the round-trip time of communication signals between nodes; distances less than 10 meters are marked as close proximity, providing insight into the close-range distribution of surrounding nodes. Signal strength is acquired by detecting the amplitude of communication signals; signal strength below -85dBm is marked as a weak signal, providing a reference for data transmission link selection. After preprocessing the collected collision feature data, it is standardized and encapsulated. The encapsulated content includes the peak value of the collision signal, duration, collection timestamp, and current node identifier to ensure a unified data format for easy parsing by the receiving end. Then, a CRC32 check mechanism is used to complete the data integrity verification to avoid incomplete data transmission affecting the judgment result. After the verification is passed, adjacent nodes with a signal strength of not less than -65dBm, a distance of no more than 300 meters from the current node, and who have passed the preset authentication and have a transmission queue occupancy rate of less than 50% are selected to ensure the stability, security, and efficiency of data transmission. The encapsulated collision feature data is sent to the selected nodes packet by packet according to the secondary data scheduling priority. During the transmission process, the link status is monitored in real time. If the link is interrupted, it automatically switches to the backup communication channel to continue transmission to ensure uninterrupted data transmission. At the same time, the speed data is stored locally to reserve data for subsequent volume adjustment.

[0035] S300, Signal Fusion Judgment: Receive collision feature data sent by adjacent nodes, first verify data integrity to ensure judgment is based on complete data; then perform single-frame data filtering, comparing the signal peak value and signal duration in the single-frame data with preset peak thresholds and preset duration thresholds, filtering out valid single-frame data with a peak value not less than 15g and a duration not less than 20ms, excluding invalid signals caused by slight interference; then start the continuous frame verification mechanism, in a continuous frame verification window of 10 consecutive frames based on the current frame, if the number of valid single-frame data is not less than 8 frames, the window is judged to have passed continuous frame verification, confirming the persistence of the collision signal and reducing false judgments caused by random factors; for data windows that have passed continuous frame verification, the confidence value is calculated using a multi-node collision signal dynamic fusion confidence algorithm. The mathematical expression of the multi-node collision signal dynamic fusion confidence algorithm is: ;in, It is the confidence level of dynamic fusion of multi-node collision signals. The number of adjacent nodes participating in the fusion; For the first The signal strength weight of each node is given by the formula: ; The signal strength value of the i-th node; This represents the minimum signal strength. This represents the maximum signal strength. For the first Distance weights of each node; For the first The speed of each node is associated with a weight; For the first The peak value of the collision impact of each node; For the first The duration of the collision signal of each node; This is a global velocity correction factor; Real-time riding speed at the current node. For the first Real-time cycling speed of adjacent nodes; For the first The straight-line distance between the current node and each of its neighboring nodes; This represents the maximum value of the peak impact force during the collision. This represents the maximum duration of the collision signal. The weighting coefficient for the peak impact value during collision; The weighting coefficient for the duration of the collision signal is used to comprehensively consider factors such as signal strength, distance, and speed of multiple nodes, making the judgment result more comprehensive and objective. The confidence value is compared with the preset confidence threshold of 0.8. If the confidence value is less than 0.8, the collision signal is determined to be valid and a warning command is output. Otherwise, the collision signal is determined to be invalid, accurately distinguishing between real collisions and false signals, and ensuring the reliability of the warning command.

[0036] S400, scheduling low-latency transmission: Based on valid early warning commands output by S300, it drives the global early warning resource pool to dynamically allocate communication resources to distressed nodes, achieving precise resource allocation and avoiding resource idleness or uneven distribution; it initiates a three-level priority preemption mechanism: Level 1 priority distress warning data has the highest resource preemption right, and can directly interrupt the transmission process of Level 2 and Level 3 priority data and occupy their allocated communication resources. After transmission is completed, the resources are released to ensure the priority transmission channel for emergency early warning data; Level 2 priority node status data can only preempt resources of Level 3 priority ordinary interactive data, and cannot interrupt Level 1 priority data transmission, balancing node status monitoring and emergency early warning needs; Level 3 priority data occupies remaining resources when there is no high-priority data transmission, and immediately releases resources and enters the waiting queue upon detecting a high-priority data request. Data of the same priority uses a round-robin scheduling mechanism to allocate resources, and the system monitors resource occupancy status in real time to ensure fair and efficient resource allocation. At the same time, combined with OFDM modulation technology and a simplified MAC layer protocol, it reduces protocol overhead and interference during data transmission, achieving differentiated low-latency transmission of data with different priorities, allowing early warning information to be quickly transmitted to relevant nodes, buying time for disaster avoidance.

[0037] S500, Receiver Volume Adjustment: Receives and parses the transmitted warning data, prioritizing the processing of the distress warning information. First, it uses a speed-warning-linked volume adaptive adjustment algorithm, combined with real-time local riding speed and fusion confidence, to adaptively adjust the warning volume output. The mathematical expression for the speed-warning-linked volume adaptive adjustment algorithm is: ; ; ;in, This is the final output volume; Based on the basic volume, , Maximum volume; The volume increment is correlated with the speed. Increase the volume for alert linkage; This is the maximum volume setting. Real-time riding speed at the current node; Confidence level for dynamic fusion of multi-node collision signals; To ensure the volume is adjusted to match the ambient noise level and collision risk at different riding speeds, a base volume is maintained during low-speed riding to avoid discomfort caused by excessive volume. Once the volume is adjusted, the voice broadcast module is immediately triggered, repeatedly broadcasting the warning message "Collision hazard ahead, please slow down and avoid it" at the current volume. The broadcast duration is controlled within 5 seconds to ensure that riders, while focused on riding, can quickly grasp the key hazard information and take timely evasive action, preventing chain accidents caused by failure to notice the hazard.

[0038] In summary, this low-latency distress warning self-organizing network communication method for cycling headphones achieves coordinated early warning in a step-by-step and orderly manner in suburban cycling scenarios. First, the self-organizing network is established and various parameters are configured, laying the foundation for subsequent communication. Then, multi-dimensional data is collected, encapsulated, and verified before being transmitted to eligible nodes. Next, the validity of collision signals is determined through multi-stage verification and algorithm calculation. Subsequently, resource scheduling and low-latency transmission mechanisms are activated to ensure priority transmission of warning data. Finally, the warning volume is adaptively adjusted. The entire method is complete and logically rigorous, fully integrating the characteristics of cycling scenarios. Through the precise execution of each step, it achieves low latency, high accuracy, and strong adaptability in distress warnings, providing strong protection for cycling safety.

[0039] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A low-latency distress warning self-organizing network communication system for cycling headphones, characterized in that, The system includes: Self-organizing network configuration module: used to automatically build a self-organizing wireless communication network after each earphone node is started, allocate dedicated distress data resource blocks to each node and build a global early warning resource pool, and simultaneously configure three-level data scheduling priority rules, speed-volume association logic and OFDM anti-interference modulation parameters. Multi-dimensional data acquisition and sharing module: Based on the communication network established by the self-organizing network configuration module, it collects and processes collision signal characteristics, real-time riding speed, distance between adjacent nodes and signal strength data, sends collision feature data to adjacent nodes that meet the sharing conditions, and stores speed data locally; Signal fusion determination module: It is used to receive collision feature data sent by the multi-dimensional data acquisition and sharing module. After verifying the integrity of the data, it uses a multi-node collision signal dynamic fusion confidence algorithm, combined with a preset threshold and a continuous frame verification mechanism, to determine the validity of the collision signal and output the corresponding warning command. Resource scheduling low-latency transmission module: Based on the valid early warning instructions output by the signal fusion judgment module, it drives the global early warning resource pool to dynamically allocate resources to distressed nodes, initiates a three-level priority preemption mechanism, and combines OFDM modulation technology with a simplified MAC layer protocol to achieve differentiated low-latency transmission of data with different priorities. Receiver volume adjustment module: Used to receive and parse the data sent by the resource scheduling low-latency transmission module, process it according to priority, and adaptively adjust the warning volume output by combining the real-time riding speed stored locally with the fusion confidence output by the signal fusion judgment module through the speed-warning linkage volume adaptive adjustment algorithm.

2. The low-latency distress warning self-organizing network communication system for cycling headphones according to claim 1, characterized in that, In the self-organizing network configuration module, the specific method for building a self-organizing wireless communication network is as follows: nodes identify surrounding nodes of the same type through an active scanning mechanism, the scanning channels are scanned sequentially according to a preset channel sequence and distributed in a fixed frequency range, the network topology adopts a mesh structure, supports dynamic addition and removal of nodes, and optimizes node power consumption to extend standby time.

3. The low-latency distress warning self-organizing network communication system for cycling headphones according to claim 1, characterized in that, In the self-organizing network configuration module, the three-level data scheduling priority rules configured by the self-organizing network configuration module are as follows: the first priority is allocated to distress warning data, which occupies communication resources and is transmitted first; the second priority is allocated to node status data, which is transmitted second priority; the third priority is allocated to ordinary interactive data, which is transmitted on demand; the speed-volume association logic is as follows: the volume is adjusted in stages according to the real-time riding speed collected by the node, the base volume is maintained in the low speed range, the volume increases linearly with the speed in the medium and high speed range to cancel the environmental noise, and the volume warning is triggered when the speed exceeds the limit; The OFDM anti-interference modulation parameters are configured as follows: 64 subcarriers are orthogonally distributed, QPSK modulation method is selected, and the cyclic prefix length is set to 1 / 8 of the symbol period.

4. The low-latency distress warning self-organizing network communication system for cycling headphones according to claim 1, characterized in that, In the multi-dimensional data acquisition and sharing module: the collision signal characteristics are acquired by detecting changes in acceleration, and a valid collision signal is determined when the change in acceleration exceeds 5g; the real-time riding speed is acquired by obtaining instantaneous speed values, and an overspeed state is marked when the speed exceeds 60km / h; the distance between adjacent nodes is acquired by calculating the round-trip time of communication signals between nodes, and a close proximity is marked when the distance is less than 10 meters; the signal strength is acquired by detecting the amplitude of communication signals, and a weak signal state is marked when the signal strength is lower than -85dBm.

5. A low-latency distress warning self-organizing network communication system for cycling headphones according to claim 1, characterized in that, In the multi-dimensional data acquisition and sharing module, the specific process of sending collision feature data to adjacent nodes that meet the sharing conditions is as follows: First, the acquired and processed collision feature data is standardized and encapsulated, and the encapsulation content includes the peak value of the collision signal, the duration, the acquisition timestamp, and the current node identifier; then, the CRC32 verification mechanism is used to complete the data integrity verification; after the verification is passed, adjacent nodes that simultaneously meet the following conditions are selected: the signal strength is not lower than -65dBm, the distance from the current node is not more than 300 meters, the preset identity verification is passed, and the transmission queue occupancy rate is less than 50%; the encapsulated collision feature data is sent to the selected nodes packet by packet according to the secondary data scheduling priority; during the transmission process, the link status is monitored in real time, and when the link is interrupted, it is automatically switched to the backup communication channel to continue transmission.

6. The low-latency distress warning self-organizing network communication system for cycling headphones according to claim 1, characterized in that, In the signal fusion determination module, the mathematical expression for the multi-node collision signal dynamic fusion confidence algorithm is: ;in, It is the confidence level of dynamic fusion of multi-node collision signals. The number of adjacent nodes participating in the fusion; For the first The signal strength weight of each node is given by the formula: ; The signal strength value of the i-th node; This represents the minimum signal strength. This represents the maximum signal strength. For the first Distance weights of each node; For the first The speed of each node is associated with a weight; For the first The peak value of the collision impact of each node; For the first The duration of the collision signal of each node; This is a global velocity correction factor; Real-time riding speed at the current node. For the first Real-time cycling speed of adjacent nodes; For the first The straight-line distance between the current node and each of its neighboring nodes; This represents the maximum value of the peak impact force during the collision. This represents the maximum duration of the collision signal. The weighting coefficient for the peak impact value during collision; This is the weighting factor for the duration of the collision signal.

7. A low-latency distress warning self-organizing network communication system for cycling headphones according to claim 1, characterized in that, In the signal fusion determination module, the specific process of determining the validity of collision signals by combining preset thresholds and continuous frame verification mechanisms is as follows: First, the signal peak value in the single-frame collision feature data is compared with the preset peak value threshold, and the signal duration is compared with the preset duration threshold. Valid single-frame data that simultaneously meets the requirements of a peak value not less than 15g and a duration not less than 20ms is selected. Then, continuous frame verification is performed on the valid single-frame data: In a continuous 10-frame data window based on the current frame, when the number of valid single-frame data is not less than 8 frames, the data window is determined to have passed continuous frame verification. For the data window that has passed continuous frame verification, the confidence value calculated by combining the multi-node collision signal dynamic fusion confidence algorithm is used. Compare with the preset reliability threshold of 0.

8. If If the value is less than 0.8, the collision signal is deemed valid and a warning command is output; otherwise, the collision signal is deemed invalid.

8. A low-latency distress warning self-organizing network communication system for cycling headphones according to claim 1, characterized in that, In the resource scheduling and low-latency transmission module, the three-level priority preemption mechanism is as follows: First-level priority distress warning data has the highest resource preemption right, and can directly interrupt the transmission process of second-level and third-level priority data and occupy the allocated communication resources, releasing the resources after the transmission is completed; second-level priority node status data can only preempt the resources of third-level priority ordinary interactive data, and cannot interrupt the transmission of first-level priority data; third-level priority data occupies the remaining resources when there is no high-priority data transmission, and once a high-priority data request is detected, it immediately releases the resources and enters the waiting queue; data of the same priority uses a round-robin scheduling mechanism to allocate resources, and the system monitors the resource occupancy status in real time.

9. A low-latency distress warning self-organizing network communication system for cycling headphones according to claim 1, characterized in that, In the receiving end processing and volume adjustment module, the mathematical expression of the speed-warning linkage volume adaptive adjustment algorithm is: ; ; ;in, This is the final output volume; Based on the basic volume, , Maximum volume; The volume increment is correlated with the speed. Increase the volume for alert linkage; This is the maximum volume setting. Real-time riding speed at the current node; Confidence level for dynamic fusion of multi-node collision signals; This is the floor function.

10. A low-latency distress warning self-organizing network communication method for cycling headsets, the method being applicable to the low-latency distress warning self-organizing network communication system for cycling headsets as described in any one of claims 1-9, characterized in that, The specific steps of this method are as follows: S100, self-organizing network configuration: After each earphone node starts up, it establishes a self-organizing wireless communication network, allocates distress data resource blocks, builds a global early warning resource pool, and configures three-level data scheduling priority rules, speed-volume association logic and OFDM anti-interference modulation parameters. S200, multi-dimensional data acquisition and sharing: collects collision signal characteristics, real-time riding speed, distance between adjacent nodes and signal strength data, preprocesses and encapsulates collision feature data and verifies its integrity, filters adjacent nodes that meet the conditions and sends the data; S300, Signal Fusion Determination: Receives and verifies collision feature data, and determines the validity of the collision signal and outputs a warning command after single-frame filtering, continuous frame verification and confidence comparison. S400, scheduling low-latency transmission: dynamically allocates resources based on valid early warning instructions, initiates a three-level priority preemption mechanism, and achieves low-latency transmission by combining OFDM modulation technology with a simplified MAC layer protocol; S500, receiver volume adjustment: Receives and parses data, processes it according to priority, and adjusts the warning volume output through a speed-warning linkage volume adaptive adjustment algorithm.

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