Noise detection system

Abstract

The invention provides a noise detection system, which comprises a vehicle-mounted detection unit, a server and a mobile terminal, and is characterized in that whether whistling noise is generated around a deployed vehicle is detected through the vehicle-mounted detection unit deployed on the vehicle, and when the whistling noise around the deployed vehicle is detected, the server sends the whistling noise to the mobile terminal; the distance between the deployment vehicle and the whistling noise source vehicle is measured, the whistling noise source vehicle image is shot, the server identifies the whistling noise source vehicle according to the whistling noise source vehicle image, whistling noise source vehicle information is obtained, whistling noise event information is further generated, and the whistling noise event information is sent to the deployment vehicle. And the whistling noise event information is sent to a traffic law enforcement department, so that the violation whistling monitoring range is expanded, the violation whistling phenomenon is restrained, the civilized driving habit of a driver is cultivated, noise pollution is reduced, and the life quality of residents and the overall image of a city are improved.

Description

Technical Field

[0001] The invention relates to the technical field of traffic violation monitoring, and in particular to a noise detection system. Background Art

[0002] With the improvement of the living standards of urban residents and the rapid development of the automobile industry, the number of cars per capita has continued to rise, which has also generated a lot of traffic noise. Vehicle horns are one of the important sources of traffic noise. Long-term exposure to high noise environments may cause hearing loss, sleep disorders, cardiovascular diseases, anxiety and stress, and have a negative impact on the quality of life of residents around traffic roads. Frequent honking may also cause confusion among other drivers and pedestrians, increasing the risk of traffic accidents. At present, the traffic laws and regulations of many countries and regions have clearly stipulated that honking is prohibited in designated areas, and violators will face fines, deductions and other penalties. At present, the monitoring of illegal honking is mainly achieved by setting up acoustic cameras at traffic intersections and linking electronic eyes to identify and capture vehicles that honk illegally. However, due to equipment costs and data transmission issues, such systems can only be deployed in fixed locations on some important roads, making them difficult to be widely used. Summary of the invention

[0003] The purpose of the present invention is to provide a noise detection system, which can detect and capture illegal honking of horns through road vehicles participating in traffic, so as to further curb the phenomenon of illegal honking of horns.

[0004] To achieve the above object, the present invention provides a noise detection system, the system comprising:

[0005] The vehicle-mounted detection unit is deployed on the vehicle and is used to detect whether horn noise is generated around the deployed vehicle. When horn noise is detected around the vehicle, the distance between the deployed vehicle and the vehicle at the source of the horn noise is measured, an image of the vehicle at the source of the horn noise is taken, and the image of the vehicle at the source of the horn noise and the horn noise detection data are uploaded to the server;

[0006] The server is used to obtain an image of a vehicle that is a source of horn noise, identify the vehicle that is a source of horn noise, obtain information about the vehicle that is a source of horn noise, summarize the information about the vehicle that is a source of horn noise, the image of the vehicle that is a source of horn noise, and horn noise detection data into horn noise event information, and send the horn noise event information to a traffic law enforcement department;

[0007] The mobile terminal is used to view the vehicle images and horn noise detection data collected by the vehicle-mounted detection unit as the source of the horn noise, as well as the horn violation records of the deployed vehicles.

[0008] Furthermore, the vehicle-mounted detection unit includes:

[0009] A sound signal collection module, used to collect sound signals around the deployed vehicle;

[0010] A data transceiver module is used to transmit the sound signal collected by the sound signal collection module to the server and receive the noise direction information sent by the server;

[0011] The image acquisition module is used to acquire an image in the direction according to the source direction of the noise signal, obtain a noise source image, and send the noise source image to the server through the data transceiver module.

[0012] Furthermore, the server includes:

[0013] A signal classification module is used to input the sound signal collected by the sound signal collection module into the pre-trained first supervised learning algorithm for classification processing, and identify whether the sound signal contains a whistle noise signal;

[0014] A distance analysis module, for analyzing and determining the source direction of the whistle noise signal and its distance from the deployed vehicle when the signal classification module identifies that the sound signal contains a whistle noise signal, and sending the noise direction information including the source direction of the whistle noise signal to the vehicle-mounted detection unit;

[0015] An image analysis module is used to input the noise source image into the target detection algorithm for processing, and identify the vehicle information and license plate information in the noise source image;

[0016] A noise source confirmation module is used to input the identified vehicle information and noise signal into the pre-trained second supervised learning algorithm for processing, determine whether the identified vehicle information matches the noise signal, and if so, generate horn noise event information;

[0017] The violation record module is used to send the horn noise event information to the traffic law enforcement department.

[0018] Furthermore, the server includes a scheduling server and an edge server. The scheduling server is used to monitor the load of each edge server, receive sound signals, determine the unloading objects of the signal classification task and its subsequent tasks according to the load of each edge server and the distance between the edge server and the deployed vehicle, send the sound signal to the corresponding edge server according to the unloading object information, and send the unloading object information to the vehicle-mounted detection unit, so that the vehicle-mounted detection unit can establish communication with the corresponding edge server.

[0019] Furthermore, the data transceiver module is also used to send the vehicle information of the deployed vehicle to the server, and the noise source confirmation module is also used to input the vehicle information of the deployed vehicle into the pre-trained second supervised learning algorithm for processing, to determine whether the vehicle information of the deployed vehicle matches the noise signal, and if so, to generate corresponding horn noise event information.

[0020] Furthermore, the target detection algorithm uses the YOLOv8 algorithm to detect vehicle elements in the noise source image, and replaces the initial model detection head in the YOLOv8 algorithm with the DCNv4-Dyhead detection head.

[0021] Furthermore, before applying the target detection algorithm to process the noise source image, the target detection algorithm is subjected to model pruning.

[0022] Furthermore, the on-board detection unit also includes a positioning module, which is used to locate the real-time position of the deployed vehicle. The server also includes a no-honking section management module, which is used to update the no-honking section information and send the no-honking section information to the on-board detection unit. The positioning module is also used to determine whether the deployed vehicle is located in the no-honking section based on the real-time position of the deployed vehicle. If it is located in the no-honking section, the sound signal collection module is enabled, otherwise the sound signal collection module is disabled.

[0023] Furthermore, the mobile terminal includes:

[0024] A registration module, used for a user to register an account, bind the registered account to the vehicle-mounted detection unit, and upload the binding information of the account and the vehicle-mounted detection unit to the server;

[0025] The data viewing module is used to display the images of vehicles with horn noise sources and horn noise detection data collected by the vehicle detection unit bound to the account, as well as the illegal horn honking records of deployed vehicles;

[0026] Points management module, used by users to check account points and redeem items or services with account points;

[0027] The server is also used to manage the account points bound to the on-board detection unit that detects the horn noise according to the vehicle that generates the horn noise when the horn noise event information is received by the traffic law enforcement department.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The present invention provides a noise detection system, which detects whether horn noise is generated around the deployed vehicle through a vehicle-mounted detection unit deployed on the vehicle. When horn noise is detected around the deployed vehicle, the system measures the distance between the deployed vehicle and the vehicle at the source of the horn noise, and takes an image of the vehicle at the source of the horn noise. The server identifies the vehicle at the source of the horn noise based on the image of the vehicle at the source of the horn noise, obtains information about the vehicle at the source of the horn noise, further generates horn noise event information, and sends the horn noise event information to a traffic law enforcement department. The present invention monitors illegal horn events in the surrounding area through a large number of vehicles participating in road traffic, and can effectively expand the monitoring range of illegal horn events, curb the occurrence of illegal horn events, help cultivate drivers' civilized driving habits, reduce noise pollution, and improve the quality of life of residents and the overall image of the city. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 It is a schematic diagram of the overall structure of a noise detection system provided by an embodiment of the present invention.

[0032] Figure 2 It is a schematic diagram of the overall structure of the vehicle-mounted detection unit provided by an embodiment of the present invention.

[0033] Figure 3 It is a schematic diagram of the overall structure of a server provided by an embodiment of the present invention.

[0034] Figure 4 It is a schematic diagram of the overall structure of a mobile terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The enumerated embodiments are only used to explain the present invention and are not used to limit the scope of the present invention.

[0036] Reference Figure 1 This embodiment provides a noise pollution detection system, which includes a vehicle-mounted detection unit, a server and a mobile terminal, and the vehicle-mounted detection unit and the mobile terminal are respectively connected to the server for communication.

[0037] The vehicle-mounted detection unit is deployed on the vehicle to detect whether horn noise is generated around the deployed vehicle. When horn noise is detected around the vehicle, the distance between the deployed vehicle and the vehicle at the source of the horn noise is measured, and an image of the vehicle at the source of the horn noise is taken, and the image of the vehicle at the source of the horn noise and the horn noise detection data are uploaded to the server.

[0038] The server is used to obtain an image of the vehicle that is the source of the horn noise, identify the vehicle that is the source of the horn noise, obtain the vehicle information that is the source of the horn noise, summarize the vehicle information that is the source of the horn noise, the vehicle image that is the source of the horn noise, and the horn noise detection data into horn noise event information, and send the horn noise event to the traffic law enforcement department, so that the traffic law enforcement department can record the illegal horn honking according to the horn noise event, and punish and notify the relevant responsible persons.

[0039] For example, the vehicle information of the horn noise source includes but is not limited to the vehicle model, vehicle body color, license plate number, etc. The horn noise detection data includes but is not limited to the horn noise original signal, horn noise signal strength, etc.

[0040] The mobile terminal is used to view the vehicle images and horn noise detection data collected by the on-board detection unit, as well as the illegal horn honking records of deployed vehicles.

[0041] The system provided in this embodiment monitors the horn noise around the deployed vehicle by deploying an on-board detection unit on a vehicle that is a road traffic participant. When the horn noise is detected, the distance between the deployed vehicle and the vehicle at the source of the horn noise is measured, and an image of the vehicle at the source of the horn noise is taken. The server identifies the vehicle at the source of the horn noise based on the image of the vehicle at the source of the horn noise, obtains the vehicle information at the source of the horn noise, and further generates horn noise event information, which is sent to the traffic law enforcement department to punish and notify the relevant responsible persons, thereby expanding the monitoring scope of illegal horn honking and curbing the occurrence of illegal horn honking.

[0042] As a preferred embodiment, refer to Figure 2 The vehicle-mounted detection unit includes a sound signal acquisition module, a data transceiver module and an image acquisition module.

[0043] Among them, the sound signal collection module is used to collect sound signals around the deployed vehicle.

[0044] Exemplarily, the sound signal acquisition module can use airborne sonar. Airborne sonar is a technology that uses the characteristics of sound waves propagating in the air to detect and locate targets. Sound waves are emitted into the air through one or more speakers or sound wave transmitters. These sound waves can be continuous waves or pulse waves, and the frequency range can be from low frequency to ultrasonic waves. When the emitted sound waves encounter the target object, they will be reflected to form echoes, which carry information about the location, shape and material of the target object. The echoes are captured by one or more microphones or sound wave receivers. These receivers can be in array form to improve positioning accuracy and resolution. The received sound wave signal is processed, including filtering, amplification, digitization and other steps, and then the time delay, intensity and frequency change of the echo are analyzed by an algorithm to determine the location, distance and speed of the target.

[0045] The data transceiver module is used to transmit the sound signal collected by the sound signal collection module to the server, and receive the noise direction information sent by the server.

[0046] The image acquisition module is used to acquire an image in the direction according to the source direction of the noise signal, obtain a noise source image, and send the noise source image to the server through the data transceiver module.

[0047] In this embodiment, the sound signals around the deployed vehicle are first monitored by the on-board detection unit and transmitted to the server. The server determines the source direction of the sound signal based on the sound signal and feeds it back to the on-board detection unit. The on-board detection unit takes an image in this direction based on the noise direction information analyzed by the server and sends it to the server so that the server can identify the vehicle that generates the horn noise based on the image in the direction of the noise source. That is to say, the on-board detection unit mainly plays the role of data collection in this embodiment, while the server mainly plays the role of data analysis.

[0048] Corresponding to the above embodiment, refer to Figure 3 The server specifically includes a signal classification module, a distance analysis module, an image analysis module, a noise source confirmation module and a violation recording module.

[0049] Among them, the signal classification module is used to input the sound signal collected by the sound signal collection module into the pre-trained first supervised learning algorithm for classification processing, and identify whether the sound signal contains a whistle noise signal.

[0050] Supervised learning, also known as supervised machine learning, is a subcategory of machine learning and artificial intelligence. It is defined as the use of labeled data sets to train algorithms in order to classify data or accurately predict results. With the development of deep learning technology, many efficient algorithms have been proposed and applied to sound signal classification. In this embodiment, the first supervised learning algorithm can be implemented using a convolutional neural network, a recurrent neural network, or a residual network, which is not specifically limited in this embodiment.

[0051] The distance analysis module is used to determine the source direction of the whistle noise signal and its distance from the deployed vehicle through a preset algorithm analysis when the signal classification module identifies that the sound signal contains whistle noise, and send the noise direction information including the source direction of the whistle noise signal to the vehicle detection unit. If the sound signal does not contain whistle noise, the process is stopped and the signal classification module is left to find the whistle noise signal.

[0052] The image analysis module is used to input the noise source image into the target detection algorithm for processing and identify the vehicle information and license plate information in the noise source image.

[0053] Exemplarily, the vehicle information includes but is not limited to vehicle model, body color and other information.

[0054] The noise source confirmation module is used to input the identified vehicle information and noise signal into the pre-trained second supervised learning algorithm for processing, and determine whether the identified vehicle information matches the noise signal. If they match, it means that the vehicle identified in the noise source image is more likely to be the honking vehicle, and honking noise event information is generated on this basis; if they do not match, it means that the honking vehicle may not be captured in the noise source image, or the honking vehicle cannot be determined, and the process ends.

[0055] For example, the horn sounds of different car models in different environments and driving conditions can be pre-recorded to obtain diverse sample data, and the recorded audio data can be labeled with car model information. The labeled data can then be used to perform supervised learning training on the classification model, such as a support vector machine, random forest or deep learning model. After multiple iterations of training, the performance of the model is evaluated and verified to ensure the classification accuracy of the model. Finally, the model is deployed to the server to determine whether it matches the car model based on the noise signal to avoid misjudging the maker of the horn noise.

[0056] The violation record module is used to send the horn noise event information to the traffic law enforcement department.

[0057] Based on the foregoing embodiment, as another preferred implementation manner, the server includes a scheduling server and an edge server, the scheduling server is used to monitor the load of each edge server, receive sound signals, determine the unloading objects of the signal classification task and its subsequent tasks according to the load of each edge server and the distance between the edge server and the deployed vehicle, send the sound signal to the corresponding edge server according to the unloading object information, and send the unloading object information to the vehicle-mounted detection unit, so that the vehicle-mounted detection unit can establish communication with the corresponding edge server.

[0058] In this implementation, each edge server is set in a different area, and the scheduling server is not directly responsible for the specific data analysis task, but realizes the unloading scheduling of the computing task by monitoring the load of each edge server and the distance between it and the vehicle-mounted detection unit that uploads the sound signal. In principle, after receiving the sound signal, the scheduling server first determines the edge server with a smaller current load according to the real-time load of each edge server, and then finds the edge server with the shortest distance to the vehicle-mounted detection unit from these edge servers with smaller loads. Finally, by comprehensively considering the edge server load and transmission cost, the optimal edge server is selected to determine the unloading object of the signal classification task and its subsequent tasks. The unloading object information is the identification information and IP address of the edge server. After receiving the unloading object information, the vehicle-mounted detection unit directly communicates with the corresponding edge server to complete the execution of the signal classification task and subsequent tasks, without going through the scheduling server. By completing a series of tasks such as signal classification on the edge side, the data transmission rate and analysis efficiency can be effectively improved.

[0059] As another preferred implementation, the data transceiver module is also used to send the vehicle information of the deployed vehicle to the server, and the noise source confirmation module is also used to input the vehicle information of the deployed vehicle into a pre-trained second supervised learning algorithm for processing, to determine whether the vehicle information of the deployed vehicle matches the noise signal, and if so, to generate corresponding horn noise event information.

[0060] In this implementation, the noise source confirmation module will also match the vehicle information of the deployed vehicle with the noise signal to determine whether the horn noise is emitted by the deployed vehicle.

[0061] As another preferred implementation, the target detection algorithm uses the YOLOv8 algorithm to detect vehicle elements in the noise source image, and replaces the initial model detection head in the YOLOv8 algorithm with a DCNv4-Dyhead detection head.

[0062] YOLOv8 (You Only Look Once version 8) is the latest version of the YOLO series of target detection algorithms, which is well-known for its efficient and real-time target detection capabilities. YOLOv8 inherits the advantages of previous generations of YOLO algorithms and has made a number of improvements and optimizations to further improve detection performance and efficiency. DCNv4-DyHead is an advanced target detection architecture that combines Deformable Convolutional Networks (DCN) and Dynamic Head (DyHead). Through the deformable convolution and pooling operations of DCNv4, and the multi-stage feature enhancement and dynamic adjustment of DyHead, the architecture is able to perform well in handling scale changes and dense targets. This combination not only improves the performance of target detection, but also maintains a high efficiency, making it suitable for use in various application scenarios.

[0063] This implementation uses the DCNv4-Dyhead detection head to replace the initial detection head of the YOLOv8 model, which can effectively capture the spatial relationship between elements of different scales and shapes in the image, and enhance the learning ability of multi-scale features such as scale, position and deformation of moving vehicle images.

[0064] As a further preferred implementation, this embodiment performs model pruning processing on the target detection algorithm before applying the target detection algorithm to process the noise source image.

[0065] Model pruning is a technique in deep learning that aims to reduce the complexity of the model by removing unimportant parameters or structures in the model, thereby improving the computational efficiency and storage efficiency of the model. Model pruning can not only reduce the inference time and memory usage of the model, but also improve the generalization ability of the model in some cases. In this implementation, by pruning the target detection algorithm, the complexity of the target processing algorithm and the usage of computing resources are reduced, thereby reducing the demand on edge server performance.

[0066] As a preferred implementation, the on-board detection unit also includes a positioning module, which is used to locate the real-time position of the deployed vehicle. The server also includes a no-honking section management module, which is used to update the no-honking section information and send the no-honking section information to the on-board detection unit. The positioning module is also used to determine whether the deployed vehicle is located in the no-honking section based on the real-time position of the deployed vehicle. If it is located in the no-honking section, the sound signal collection module is enabled, otherwise the sound signal collection module is disabled.

[0067] In this implementation, the sound signal collection module is enabled only when the positioning module detects that the vehicle has moved to a no-honking section, to monitor whether the deployed vehicle or surrounding vehicles are honking in the no-honking section; otherwise, the sound signal collection module is disabled, thereby reducing energy consumption.

[0068] On the other hand, refer to Figure 4 , the mobile terminal comprises:

[0069] The registration module is used for users to register accounts, bind the registered accounts to the vehicle-mounted detection units, and upload the binding information between the accounts and the vehicle-mounted detection units to the server.

[0070] The data viewing module is used to display the vehicle images and horn noise detection data collected by the vehicle detection unit bound to the account, as well as the illegal horn honking records of the deployed vehicles.

[0071] The points management module is used for users to view account points and use account points to redeem items or services.

[0072] The server is also used to manage the account points bound to the on-board detection unit that detects the horn noise according to the vehicle that generates the horn noise when the horn noise event information is received by the traffic law enforcement department.

[0073] For example, when the vehicle that generates the horn noise is a vehicle other than a deployed vehicle, as a reward to the user, points are added to the user's account according to the preset scoring rules; if the vehicle that generates the horn noise is a deployed vehicle, points are deducted from the user's account according to the preset deduction rules, thereby encouraging the user to monitor the road horn noise situation with the deployed vehicle detection unit, while improving the user's environmental awareness and trying not to honk and create noise in urban areas.

[0074] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A noise detection system, characterized in that: The system comprises: The vehicle-mounted detection unit is deployed on the vehicle and is used to detect whether horn noise is generated around the deployed vehicle. When horn noise is detected around the vehicle, the distance between the deployed vehicle and the vehicle at the source of the horn noise is measured, an image of the vehicle at the source of the horn noise is taken, and the image of the vehicle at the source of the horn noise and the horn noise detection data are uploaded to the server; The server is used to obtain an image of a vehicle that is a source of horn noise, identify the vehicle that is a source of horn noise, obtain information about the vehicle that is a source of horn noise, summarize the information about the vehicle that is a source of horn noise, the image of the vehicle that is a source of horn noise, and horn noise detection data into horn noise event information, and send the horn noise event information to a traffic law enforcement department; The mobile terminal is used to view the vehicle images and horn noise detection data collected by the vehicle-mounted detection unit as the source of the horn noise, as well as the horn violation records of the deployed vehicles.

2. A noise detection system according to claim 1, characterized in that: The vehicle-mounted detection unit comprises: A sound signal collection module, used to collect sound signals around the deployed vehicle; A data transceiver module is used to transmit the sound signal collected by the sound signal collection module to the server and receive the noise direction information sent by the server; The image acquisition module is used to acquire an image in the direction according to the source direction of the noise signal, obtain a noise source image, and send the noise source image to the server through the data transceiver module.

3. A noise detection system according to claim 2, characterized in that: The server comprises: A signal classification module is used to input the sound signal collected by the sound signal collection module into the pre-trained first supervised learning algorithm for classification processing, and identify whether the sound signal contains a whistle noise signal; A distance analysis module, for analyzing and determining the source direction of the whistle noise signal and its distance from the deployed vehicle when the signal classification module identifies that the sound signal contains a whistle noise signal, and sending the noise direction information including the source direction of the whistle noise signal to the vehicle-mounted detection unit; An image analysis module is used to input the noise source image into the target detection algorithm for processing, and identify the vehicle information and license plate information in the noise source image; A noise source confirmation module is used to input the identified vehicle information and noise signal into the pre-trained second supervised learning algorithm for processing, determine whether the identified vehicle information matches the noise signal, and if so, generate horn noise event information; The violation record module is used to send the horn noise event information to the traffic law enforcement department.

4. A noise detection system according to claim 3, characterized in that: The server includes a scheduling server and an edge server. The scheduling server is used to monitor the load of each edge server, receive sound signals, determine the unloading objects of the signal classification task and its subsequent tasks according to the load of each edge server and the distance between the edge server and the deployed vehicle, send the sound signal to the corresponding edge server according to the unloading object information, and send the unloading object information to the vehicle-mounted detection unit, so that the vehicle-mounted detection unit can establish communication with the corresponding edge server.

5. A noise detection system according to claim 3, characterized in that: The data transceiver module is also used to send the vehicle information of the deployed vehicle to the server, and the noise source confirmation module is also used to input the vehicle information of the deployed vehicle into the pre-trained second supervised learning algorithm for processing, to determine whether the vehicle information of the deployed vehicle matches the noise signal, and if so, to generate corresponding horn noise event information.

6. A noise detection system according to claim 3, characterized in that: The target detection algorithm uses the YOLOv8 algorithm to detect vehicle elements in the noise source image, and replaces the initial model detection head in the YOLOv8 algorithm with the DCNv4-Dyhead detection head.

7. A noise detection system according to claim 6, characterized in that: Before applying the target detection algorithm to process the noise source image, the target detection algorithm is pruned.

8. A noise detection system according to claim 2, characterized in that: The on-board detection unit also includes a positioning module, which is used to locate the real-time position of the deployed vehicle. The server also includes a no-honking section management module, which is used to update the no-honking section information and send the no-honking section information to the on-board detection unit. The positioning module is also used to determine whether the deployed vehicle is located in the no-honking section based on the real-time position of the deployed vehicle. If it is located in the no-honking section, the sound signal collection module is enabled, otherwise the sound signal collection module is disabled.

9. A noise detection system according to claim 1, characterized in that: The mobile terminal comprises: A registration module, used for a user to register an account, bind the registered account to the vehicle-mounted detection unit, and upload the binding information between the account and the vehicle-mounted detection unit to the server; The data viewing module is used to display the images of vehicles with horn noise sources and horn noise detection data collected by the vehicle detection unit bound to the account, as well as the illegal horn honking records of deployed vehicles; Points management module, used by users to check account points and redeem items or services with account points; The server is also used to manage the account points bound to the on-board detection unit that detects the horn noise according to the vehicle that generates the horn noise when the horn noise event information is received by the traffic law enforcement department.

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