Cycling fall warning method, device, equipment and storage medium

Abstract

The present application relates to the field of early warning monitoring technology, and discloses an early warning method, device, equipment and storage medium for a fall while riding. The method includes: monitoring the target rider through a GNSS positioning module to obtain a first riding speed, monitoring the target rider through a riding to obtain a second riding speed and acceleration data; when the communication state of the GNSS positioning module is normal, real-time monitoring of the first riding speed; when the acceleration data meets the first threshold interval, threshold analysis is performed on the first riding speed, and riding posture analysis is performed on the target rider to obtain riding posture data; when the first riding speed meets the preset second threshold interval and the riding posture data is an abnormal riding posture, an alarm tone is played to the target rider through a speaker module, and the target rider's operation data is collected in real time; when the target rider's operation data is not collected, a distress data is sent to a remote server, and the distress data is sent to multiple riders in the target area.

Description

Technical Field

[0001] The present application relates to the field of early warning monitoring, and in particular to an early warning method, device, equipment and storage medium for a cycling fall. Background Art

[0002] Cycling has become increasingly popular in recent years, and accidental injuries caused by falls have also increased year by year. After a rider falls, their physical activities may be hindered or they may even lose consciousness, making it impossible for them to contact help on their own, resulting in missing the best time for help. Some cycling equipment (motorcycles, helmets, etc.) monitors the impact through acceleration sensors to determine whether the rider has fallen, and sends a distress message with location information through a mobile terminal.

[0003] In the prior art, whether a rider falls is generally determined only through an acceleration sensor, and the judgment condition is single. When riders ride in a team, when a rider falls, it is impossible to promptly alert other riders in the group. The distress message can only be sent through the mobile terminal. If the connection with the mobile terminal is disconnected, the distress message cannot be sent normally. Summary of the invention

[0004] The present application provides a method, device, equipment and storage medium for early warning of a cycling fall, which are used to improve the timeliness and accuracy of early warning of a cycling fall.

[0005] In a first aspect, the present application provides a method for early warning of a rider falling down, the method comprising: S1, monitoring a target rider's riding at a preset frequency through a GNSS positioning module to obtain a first riding speed, and at the same time, monitoring the target rider's riding at the preset frequency through a six-axis inertial measurement unit module to obtain a second riding speed and acceleration data;

[0006] S2. monitoring the communication status of the GNSS positioning module in real time, and when the communication status of the GNSS positioning module is normal, monitoring the first riding speed in real time;

[0007] S3, analyzing the acceleration data, extracting the acceleration data corresponding to the first riding speed, and when the acceleration data meets the preset first threshold interval, executing step S4; when the acceleration data does not meet the preset first threshold interval, repeating steps S1 to S3;

[0008] S4, within a preset time zone, performing a threshold analysis on the first riding speed, and at the same time, performing a riding posture analysis on the target rider to obtain riding posture data; when the first riding speed meets a preset second threshold interval and the riding posture data is an abnormal riding posture, playing an alarm tone to the target rider through a speaker module, and at the same time, collecting the operation data of the target rider in real time; when the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, repeating steps S1 to S4;

[0009] S5. When the operation data of the target rider is not collected, the distress data is sent to a preset remote server, and the distress data is sent to multiple riders in the target area through the Mesh network, wherein the distress data includes the location information of the target rider.

[0010] In combination with the first aspect, in a first implementation of the first aspect of the present application, the present invention further includes:

[0011] When the communication state of the GNSS positioning module is abnormal, real-time monitoring of the second riding speed is performed;

[0012] Analyze the acceleration data, and when the acceleration data meets the preset first threshold interval, execute step S4; when the acceleration data does not meet the preset first threshold interval, repeat steps S1 to S3;

[0013] In a preset time zone, a threshold analysis is performed on the second riding speed, and at the same time, a riding posture analysis is performed on the target rider to obtain riding posture data. When the second riding speed meets the preset second threshold interval and the riding posture data is an abnormal riding posture, an alarm tone is played to the target rider through a speaker module, and at the same time, the operation data of the target rider is collected in real time. When the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, steps S1 to S4 are repeated.

[0014] When the operation data of the target rider is not collected, distress data is sent to a preset remote server, wherein the distress data includes the location information of the target rider, and the distress data is broadcast to multiple riders in the target area through a preset Mesh network.

[0015] In combination with the first aspect, in a second implementation of the first aspect of the present application, step S4 includes:

[0016] In a preset time zone, a threshold analysis is performed on the first riding speed, and at the same time, a riding posture analysis is performed on the target rider to obtain riding posture data, and when the first riding speed meets a preset second threshold interval, forward tilt angle data, backward tilt angle data, and left and right tilt angle data of the target rider collected by the six-axis inertial measurement unit module are extracted;

[0017] The riding posture of the target rider is analyzed according to the forward tilt angle data, the rearward tilt angle data and the left and right tilt angle data to obtain riding posture data. When the riding posture data is an abnormal riding posture, an alarm tone is played to the target rider through a speaker module. At the same time, the operation data of the target rider is collected in real time. When the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, steps S1 to S4 are repeated.

[0018] In combination with the first aspect, in a third implementation of the first aspect of the present application, the performing riding posture analysis on the target rider according to the forward tilt angle data, the rearward tilt angle data, and the left and right tilt angle data to obtain the riding posture data includes:

[0019] The left and right tilt angle data, the rear tilt angle data and the front tilt angle data are analyzed simultaneously, and the riding posture data is determined to be an abnormal riding posture, including one or more of the following situations: the left and right tilt angle data exceeds a preset first angle threshold, the forward tilt angle data exceeds a preset second angle threshold, and the rear tilt angle data exceeds a preset third angle threshold.

[0020] In combination with the first aspect, in a fourth implementation method of the first aspect of the present application, it also includes: when the riding posture data is a normal riding posture and the first riding speed meets the preset second threshold interval, repeating steps S1 to S4.

[0021] In combination with the first aspect, in a fifth implementation of the first aspect of the present application, the present invention further includes:

[0022] When the operation data of the target rider is collected, steps S1 to S5 are repeatedly executed.

[0023] In combination with the first aspect, in a sixth implementation of the first aspect of the present application, step S5 includes:

[0024] When the operation data of the target rider is not collected, the distress data is sent to the preset remote server, wherein the distress data is sent to the preset remote server in the following manner:

[0025] Connect directly to a remote server via a WiFi hotspot through a preset WiFi module and send distress data to the remote server, or,

[0026] The mobile phone APP is connected through a preset Bluetooth module, the remote server is connected through the mobile phone APP, and distress data is sent to the remote server, wherein the distress data includes the location information of the target rider, and the distress data is broadcast to multiple riders in the target area through a preset Mesh network.

[0027] In a second aspect, the present application provides a warning device for a rider falling down, the warning device for a rider falling down comprising:

[0028] An acquisition module is used to monitor the riding of a target rider at a preset frequency through a GNSS positioning module to obtain a first riding speed, and at the same time, monitor the riding of the target rider at the preset frequency through a six-axis inertial measurement unit module to obtain a second riding speed and acceleration data;

[0029] A monitoring module, used for monitoring the communication status of the GNSS positioning module in real time, and when the communication status of the GNSS positioning module is normal, monitoring the first riding speed in real time;

[0030] A solution module, used for analyzing the acceleration data, and executing step S4 when the acceleration data meets the preset first threshold interval, and repeating steps S1 to S3 when the acceleration data does not meet the preset first threshold interval;

[0031] a playing module, configured to perform a threshold analysis on the first riding speed within a preset time zone, and simultaneously perform a riding posture analysis on the target rider to obtain riding posture data; when the first riding speed meets a preset second threshold interval and the riding posture data is an abnormal riding posture, an alarm tone is played to the target rider through a speaker module, and at the same time, operation data of the target rider is collected in real time; when the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, steps S1 to S4 are repeatedly executed;

[0032] The early warning module is used to send distress data to a preset remote server when the operation data of the target rider is not collected, and to send distress data to multiple riders in the target area through the Mesh network, wherein the distress data includes the location information of the target rider.

[0033] A third aspect of the present application provides a cycling fall warning device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory to enable the cycling fall warning device to execute the above-mentioned cycling fall warning method.

[0034] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned method for early warning of a cycling fall.

[0035] In the technical solution provided by the present application, by monitoring the changes in the rider's riding speed and riding posture, it is comprehensively judged whether the rider has fallen, thereby improving the detection accuracy. Before sending a distress message, the current rider is informed by broadcasting a prompt tone, and other riders in the group are alerted. The current rider can actively cancel the broadcast and the alarm. By sending distress messages through multiple channels such as mobile phones, WIFI, and Mesh, the rider's riding situation can be comprehensively monitored based on the data of the GNSS and six-axis inertial measurement unit modules, and whether the rider has fallen can be identified more efficiently and accurately. When the rider falls, it is promptly broadcast to the rider and other members of the team are alerted. If the alarm is not canceled, a distress message is sent through mobile phones, WIFI, and Mesh, which can improve the timeliness and accuracy of the warning of riding falls. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0037] Figure 1 A schematic diagram of an embodiment of a method for early warning of a fall while riding a bicycle in an embodiment of the present application;

[0038] Figure 2 This is a schematic diagram of an embodiment of a warning device for a rider falling in an embodiment of the present application. DETAILED DESCRIPTION

[0039] The embodiments of the present application provide a method, device, equipment and storage medium for early warning of a fall while riding. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0040] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 In the embodiment of the present application, an embodiment of the early warning method for a fall while riding a bicycle includes:

[0041] S1. Using a GNSS positioning module, the target rider is monitored at a preset frequency to obtain a first riding speed. At the same time, using a six-axis inertial measurement unit module, the target rider is monitored at a preset frequency to obtain a second riding speed and acceleration data.

[0042] S2. monitoring the communication status of the GNSS positioning module in real time. When the communication status of the GNSS positioning module is normal, monitoring the first riding speed in real time.

[0043] S3, analyzing the acceleration data, and when the acceleration data meets the preset first threshold interval, executing step S4, and when the acceleration data does not meet the preset first threshold interval, repeating steps S1 to S3;

[0044] In this step, the first threshold interval is 1.3g~2g, where g is the unit of acceleration and the specific value is 9.8m / .

[0045] S4, within a preset time zone, performing a threshold analysis on the first riding speed, and at the same time, performing a riding posture analysis on the target rider to obtain riding posture data; when the first riding speed meets the preset second threshold interval and the riding posture data is an abnormal riding posture, playing an alarm tone to the target rider through the speaker module, and at the same time, collecting the operation data of the target rider in real time; when the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, repeating steps S1 to S4;

[0046] In this step, the preset time interval is 2s to 6s.

[0047] S5. When the operation data of the target rider is not collected, the distress data is sent to a preset remote server, and the distress data is sent to multiple riders in the target area through the Mesh network, wherein the distress data includes the location information of the target rider.

[0048] It is understandable that the execution subject of the present application can be a warning device for riding a fall, or a terminal or a server, which is not limited here. The embodiment of the present application is described by taking the server as the execution subject as an example.

[0049] In this embodiment, it should be noted that when the target rider is monitored for riding according to a preset frequency and the first riding speed is obtained, the preset frequency is 1Hz~10Hz. The first step is to use the GNSS positioning module to regularly monitor the first riding speed of the target rider. At the same time, the six-axis inertial measurement unit module also detects another set of riding data according to the same preset frequency, which is the second riding speed and acceleration data. These two speed measurement systems act as backups for each other, ensuring the continuity and accuracy of rider speed monitoring. Suppose in an open environment, a rider is performing daily training, and his riding path is tracked and the speed is measured by the GNSS module. At the same time, the six-axis inertial measurement unit module is used as an auxiliary to provide speed and posture data to improve the robustness of the system.

[0050] Among them, the communication status of the GNSS positioning module is monitored in real time. When the communication is normal, the first riding speed is tracked in real time to confirm whether the rider's motion state is stable. If the GNSS communication status is abnormal, the second riding speed data will be automatically used as the main source of speed monitoring. For example, when the weather is clear and the communication conditions are good, GNSS data will be the main force for speed monitoring, and the second riding speed will be an auxiliary verification. Furthermore, when the rider's speed enters the preset speed range, the role of the six-axis inertial measurement unit module becomes crucial. It needs to solve the current posture and obtain important posture data such as pitch angle, roll angle and yaw angle. Imagine that the rider speeds up during the downhill process. At this time, the six-axis inertial measurement unit module will closely monitor the slight changes in the rider's posture to determine whether it has entered a dangerous posture. When the posture data of the rider is monitored to show abnormalities, such as a sudden increase in pitch or roll angle, it will be determined that a fall accident has occurred or may occur, and an alarm tone will be played through the speaker module to warn the rider to take immediate measures.

[0051] If no operation data of the rider is collected after the emergency warning is triggered, it may mean that the rider is no longer able to control the situation by himself, and may lose consciousness or be unable to take action due to a fall. In this case, the pre-installed WIFI module will immediately send distress data to the remote server and send distress voice to other riders in the target area, which immediately initiates the rescue operation. At the same time, the real-time broadcast of distress data through the built-in Mesh network module can not only cover areas that WIFI may not cover, but also ensure that rescue information can be accurately delivered even in an unstable network environment.

[0052] For example, if a rider is training on a mountain bike trail, the speaker will immediately sound an alarm if it detects a sudden change in speed and abnormal posture when the rider is going down a steep slope. If the rider fails to respond in time due to panic, technical errors or any other reasons, the emergency procedure will be triggered quickly without detecting any operation data, asking nearby riders and remote rescue units to intervene. The rescue signal is broadcast through the Mesh network, ensuring that even in possible WiFi blind spots such as valleys, the rescue request can be received by nearby riders or search and rescue teams, and they can gather at the accident site as soon as possible for rescue.

[0053] In an embodiment of the present application, by monitoring the changes in the rider's riding speed and riding posture, it is comprehensively judged whether the rider has fallen, thereby improving the detection accuracy. Before sending a distress message, the current rider is informed by broadcasting a prompt tone, and other riders in the group are alerted. The current rider can actively cancel the broadcast and the alert. By sending distress messages through multiple channels such as mobile phones, WIFI, and Mesh, the rider's riding situation can be comprehensively monitored based on the data of the GNSS and six-axis inertial measurement unit modules, and whether the rider has fallen can be more efficiently and accurately identified. When the rider falls, it is promptly broadcast to the rider and alerts other members of the team. If the alarm is not canceled, a distress message is sent through mobile phones, WIFI, and Mesh, which can improve the timeliness and accuracy of the early warning of riding falls.

[0054] In a specific embodiment, the early warning method for a fall while riding a bicycle may further include the following steps:

[0055] (1) When the communication status of the GNSS positioning module is abnormal, the second riding speed is monitored in real time;

[0056] (2) analyzing the acceleration data. When the acceleration data satisfies a preset first threshold interval, executing step S4. When the acceleration data does not satisfy the preset first threshold interval, repeating steps S1 to S3.

[0057] (3) within a preset time zone, a threshold analysis is performed on the second riding speed, and at the same time, a riding posture analysis is performed on the target rider to obtain riding posture data. When the second riding speed meets the preset second threshold interval and the riding posture data is an abnormal riding posture, an alarm tone is played to the target rider through the speaker module. At the same time, the operation data of the target rider is collected in real time. When the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, steps S1 to S4 are repeated.

[0058] (4) When the operation data of the target rider is not collected, the rescue data is sent to a preset remote server, where the rescue data includes the location information of the target rider, and the rescue data is broadcast to multiple riders in the target area through a preset Mesh network.

[0059] In a specific embodiment, the process of executing step S4 may specifically include the following steps:

[0060] (1) within a preset time zone, a threshold analysis is performed on a first riding speed, and at the same time, a riding posture analysis is performed on a target rider to obtain riding posture data, and when the first riding speed meets a preset second threshold interval, forward tilt angle data, rearward tilt angle data, and left and right tilt angle data of the target rider collected by a six-axis inertial measurement unit module are extracted;

[0061] (2) The riding posture of the target rider is analyzed according to the forward tilt angle data, the rearward tilt angle data, and the left and right tilt angle data to obtain riding posture data. When the riding posture data is an abnormal riding posture, an alarm tone is played to the target rider through the speaker module. At the same time, the operation data of the target rider is collected in real time. When the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, steps S1 to S4 are repeated.

[0062] Specifically, when the first riding speed is detected to change to a preset speed range, the riding fall warning method of the present invention collects three-axis angular velocity data of the target rider through a six-axis inertial measurement unit module to obtain first angular velocity data, second angular velocity data and third angular velocity data. The six-axis inertial measurement unit module is a device that combines a three-axis gyroscope and a three-axis accelerometer;

[0063] In the disclosed embodiment, the second threshold interval is the judgment standard of the first riding speed, and its value is 0m / s~3m / s. At the same time, it is judged whether the rider is riding abnormally. If the front and rear tilt angles and the left and right tilt angles are beyond the normal range, it is judged that there is a risk of falling. For example, in the above mountain biking example, if the rider's rolling angle exceeds the normal value, it is judged that the rider may be in the process of falling, and the warning is immediately activated to issue a warning to the rider, and take timely measures to reduce possible injuries.

[0064] In a specific embodiment, the process of performing a riding posture analysis on the target rider according to the forward tilt angle data, the rearward tilt angle data, and the left and right tilt angle data to obtain the riding posture data may specifically include the following steps:

[0065] At the same time, the left and right tilt angle data, the rear tilt angle data and the forward tilt angle data are analyzed to determine that the riding posture data is an abnormal riding posture, including one or more of the following situations: the left and right tilt angle data exceeds a preset first angle threshold, the rear tilt angle data exceeds a preset second angle threshold, and the rear tilt angle data exceeds a preset third angle threshold.

[0066] It should be noted that, in a possible embodiment of the present disclosure, the first angle threshold is 20°~45°, the second angle threshold is 10°~20°, and the third angle threshold is 40°~90°.

[0067] In a specific embodiment, the method for early warning of a fall while riding may further specifically include the following steps: when the riding posture data is a normal riding posture and the first riding speed meets a preset second threshold range, steps S1 to S4 are repeated.

[0068] In this embodiment, when the riding speed does not meet the threshold value of 0 m / s to 3 m / s or the riding posture is normal within the preset time interval, steps S1 to S5 are repeatedly executed.

[0069] In a specific embodiment, the method for early warning of a rider fall may further specifically include the following steps: when the operation data of the target rider is collected, steps S1 to S5 are repeatedly executed.

[0070] In a specific embodiment, the process of executing step S5 may specifically include the following steps:

[0071] (1) When the operation data of the target rider is not collected, the distress data is sent to a preset remote server, wherein the distress data is sent to the preset remote server in the following manner:

[0072] (2) Use the pre-installed WiFi module to directly connect to the remote server through the WiFi hotspot and send distress data to the remote server, or,

[0073] (3) Connect to the mobile phone APP through the preset Bluetooth module, connect to the remote server through the mobile phone APP, and send distress data to the remote server, where the distress data includes the location information of the target rider, and broadcast the distress data to multiple riders in the target area through the preset Mesh network.

[0074] Specifically, when the emergency response mechanism finds that the target rider cannot perform normal operations due to some uncontrollable factors, it will start sending the distress data. First, the WIFI module pre-installed on the rider's device will automatically send distress data to the pre-configured remote server without collecting the rider's operation data. After receiving this signal, the server will immediately start the rescue program and notify the rescue team members. This design is very in line with the actual needs of mountain biking, because in areas far away from the city and with poor signal coverage, timely rescue request transmission is crucial. Identify the riders in the target area. This is done by analyzing the devices identified in the WIFI network, which can detect and confirm other rider devices in the area. When the riders are confirmed, after obtaining the device information of each rider, the specific signal transmission channel of each device will be matched. After that, voice distress information will be sent to these riders through the corresponding signal transmission channel. In order to ensure that the distress data can be transmitted when the WIFI signal cannot be covered, the distress data is also broadcast in real time through the pre-installed Mesh network module. Due to its multi-hop transmission characteristics, the Mesh network is particularly suitable for complex terrain and large-scale coverage. Even in areas without direct WIFI connection, distress data can be matched with each rider's signal transmission channel through the network built between devices, and based on each rider's signal transmission channel, the WIFI module can send distress voice to multiple riders in the target area. At the same time, the distress data is broadcast in real time through the preset Mesh network module.

[0075] The above describes the early warning method for a rider falling down in the embodiment of the present application. The following describes the early warning device for a rider falling down in the embodiment of the present application. Figure 2 In the embodiment of the present application, an early warning device for a fall while riding a bicycle comprises:

[0076] The acquisition module 201 is used to monitor the riding of the target rider at a preset frequency through the GNSS positioning module to obtain a first riding speed, and at the same time, monitor the riding of the target rider at a preset frequency through the six-axis inertial measurement unit module to obtain a second riding speed and acceleration data;

[0077] A monitoring module 202 is used to monitor the communication status of the GNSS positioning module in real time, and when the communication status of the GNSS positioning module is normal, monitor the first riding speed in real time;

[0078] A solution module 203 is used to analyze the acceleration data, and when the acceleration data meets the preset first threshold interval, execute step S4, and when the acceleration data does not meet the preset first threshold interval, repeat steps S1 to S3;

[0079] The playing module 204 is used to perform a threshold analysis on the first riding speed within a preset time zone, and at the same time, perform a riding posture analysis on the target rider to obtain riding posture data. When the first riding speed meets a preset second threshold interval and the riding posture data is an abnormal riding posture, an alarm tone is played to the target rider through a speaker module, and at the same time, the operation data of the target rider is collected in real time. When the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, steps S1 to S4 are repeated;

[0080] The early warning module 205 is used to send distress data to a preset remote server when the operation data of the target rider is not collected, and to send distress data to multiple riders in the target area through the Mesh network, wherein the distress data includes the location information of the target rider.

[0081] Through the coordinated cooperation of the above components, the changes in the rider's riding speed and riding posture are monitored to comprehensively judge whether the rider has fallen, thereby improving the accuracy of detection. Before sending a distress message, the current rider is informed by broadcasting a prompt tone, and other riders in the group are alerted. The current rider can actively cancel the broadcast and alarm. Sending distress messages through multiple channels such as mobile phones, WIFI and Mesh can comprehensively monitor the rider's riding situation based on the data of GNSS and six-axis inertial measurement unit modules, and more efficiently and accurately identify whether the rider has fallen. When the rider falls, it is promptly reported to the rider and other members of the team are alerted. If the alarm is not canceled, a distress message is sent through mobile phones, WIFI and Mesh, which can improve the timeliness and accuracy of the warning of riding falls.

[0082] The present application also provides a riding fall warning device, which includes a memory and a processor. The memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor executes the steps of the riding fall warning method in the above-mentioned embodiments.

[0083] The present application also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the method for early warning of a fall while riding a bicycle.

[0084] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0085] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for early warning of a fall while riding, characterized in that: The early warning method for riding a fall comprises: S1. Using a GNSS positioning module, the target rider is monitored for riding at a preset frequency to obtain a first riding speed. Meanwhile, using a six-axis inertial measurement unit module, the target rider is monitored for riding at the preset frequency to obtain a second riding speed and acceleration data. S2. monitoring the communication status of the GNSS positioning module in real time, and when the communication status of the GNSS positioning module is normal, monitoring the first riding speed in real time; S3, analyzing the acceleration data, and when the acceleration data meets the preset first threshold interval, executing step S4, and when the acceleration data does not meet the preset first threshold interval, repeating steps S1 to S3; S4, within a preset time zone, performing a threshold analysis on the first riding speed, and at the same time, performing a riding posture analysis on the target rider to obtain riding posture data; when the first riding speed meets a preset second threshold interval and the riding posture data is an abnormal riding posture, playing an alarm tone to the target rider through a speaker module, and at the same time, collecting the operation data of the target rider in real time; when the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, repeating steps S1 to S4; S5. When the operation data of the target rider is not collected, send the distress data to the preset remote server, and send the distress data to multiple riders in the target area through the Mesh network, wherein the distress data includes the location information of the target rider; When the communication state of the GNSS positioning module is abnormal, real-time monitoring of the second riding speed is performed; The acceleration data is analyzed, and when the acceleration data meets the preset first threshold interval, the following steps are performed: within a preset time zone, the second riding speed is threshold analyzed, and at the same time, the riding posture analysis of the target rider is performed to obtain riding posture data; when the second riding speed meets the preset second threshold interval and the riding posture data is an abnormal riding posture, an alarm prompt sound is played to the target rider through a speaker module, and at the same time, the operation data of the target rider is collected in real time; when the second riding speed does not meet the preset second threshold interval or the riding posture data is normal, steps S1 to S3 are repeated; when the operation data of the target rider is not collected, distress data is sent to a preset remote server, wherein the distress data includes the location information of the target rider, and the distress data is broadcast to multiple riders in the target area through a preset Mesh network; when the acceleration data does not meet the preset first threshold interval, steps S1 to S3 are repeated.

2. The method for early warning of a fall while riding a bicycle according to claim 1, characterized in that: Step S4 includes: In a preset time zone, a threshold analysis is performed on the first riding speed, and at the same time, a riding posture analysis is performed on the target rider to obtain riding posture data, and when the first riding speed meets a preset second threshold interval, forward tilt angle data, backward tilt angle data, and left and right tilt angle data of the target rider collected by the six-axis inertial measurement unit module are extracted; The riding posture of the target rider is analyzed according to the forward tilt angle data, the rearward tilt angle data and the left and right tilt angle data to obtain riding posture data. When the riding posture data is an abnormal riding posture, an alarm tone is played to the target rider through a speaker module. At the same time, the operation data of the target rider is collected in real time. When the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, steps S1 to S4 are repeated.

3. The method for early warning of a fall while riding a bicycle according to claim 2, characterized in that: The performing riding posture analysis on the target rider according to the forward tilt angle data, the rearward tilt angle data and the left and right tilt angle data to obtain riding posture data includes: The left and right tilt angle data, the rear tilt angle data and the front tilt angle data are analyzed simultaneously, and the riding posture data is determined to be an abnormal riding posture, including one or more of the following situations: the left and right tilt angle data exceeds a preset first angle threshold, the forward tilt angle data exceeds a preset second angle threshold, and the rear tilt angle data exceeds a preset third angle threshold.

4. The method for early warning of a fall while riding a bicycle according to claim 1, characterized in that: Also includes: When the operation data of the target rider is collected, steps S1 to S5 are repeatedly executed.

5. The method for early warning of a fall while riding a bicycle according to claim 1, characterized in that: Step S5 includes: When the operation data of the target rider is not collected, the distress data is sent to the preset remote server, wherein the distress data is sent to the preset remote server in the following manner: Connect directly to a remote server via a WiFi hotspot through a preset WiFi module and send distress data to the remote server, or, The mobile phone APP is connected through a preset Bluetooth module, the remote server is connected through the mobile phone APP, and distress data is sent to the remote server, wherein the distress data includes the location information of the target rider, and the distress data is broadcast to multiple riders in the target area through a preset Mesh network.

6. A warning device for a rider falling down, characterized in that: Used to implement the early warning method for a rider falling down as claimed in claim 1, the early warning device for a rider falling down comprises: An acquisition module is used to monitor the riding of a target rider at a preset frequency through a GNSS positioning module to obtain a first riding speed, and at the same time, monitor the riding of the target rider at the preset frequency through a six-axis inertial measurement unit module to obtain a second riding speed and acceleration data; A monitoring module, used for monitoring the communication status of the GNSS positioning module in real time, and when the communication status of the GNSS positioning module is normal, monitoring the first riding speed in real time; A solution module analyzes the acceleration data, and when the acceleration data meets a preset first threshold interval, executes step S4, and when the acceleration data does not meet the preset first threshold interval, repeats steps S1 to S3; a playing module, configured to perform a threshold analysis on the first riding speed within a preset time zone, and simultaneously perform a riding posture analysis on the target rider to obtain riding posture data; when the first riding speed meets a preset second threshold interval and the riding posture data is an abnormal riding posture, an alarm tone is played to the target rider through a speaker module, and at the same time, operation data of the target rider is collected in real time; when the first riding speed does not meet the preset second threshold interval or the riding posture data is normal, steps S1 to S4 are repeatedly executed; The early warning module is used to send distress data to a preset remote server when the operation data of the target rider is not collected, and to send distress data to multiple riders in the target area through the Mesh network, wherein the distress data includes the location information of the target rider.

7. A warning device for a fall while riding, characterized in that: The riding fall warning device comprises: a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the riding fall warning device to execute the riding fall warning method as described in any one of claims 1-5.

8. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the method for early warning of a fall while riding a bicycle as described in any one of claims 1 to 5 is implemented.

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