Road traffic public security checkpoint monitoring system

Abstract

The invention relates to the technical field of smart cities, in particular to a road traffic public security checkpoint monitoring system, which comprises a vehicle detection module, a processing module, a transmission module and a central management module, and is characterized in that the processing module is connected with the vehicle detection module, and the transmission module is connected with the processing module and the central management module; and the vehicle detection module realizes accurate detection of the vehicle. The processing module improves image quality, high image definition and stability and ensures the stability and reliability of the system, the transmission module ensures real-time transmission of vehicle information and encrypts transmission data, and the center management module quickly processes and analyzes mass vehicle data and extracts valuable traffic management information, so that the traffic management system is provided with a real-time monitoring module and a real-time monitoring module. By introducing technologies such as radar, a sensor and video detection, the dependence on a ground induction coil is reduced, the complexity of construction and maintenance is reduced, more accurate vehicle detection information is provided, and the occurrence of false alarm and missing alarm conditions is reduced.

Description

Technical Field

[0001] The present invention relates to the field of smart city technology, and in particular to a road traffic security checkpoint monitoring system. Background Art

[0002] The road traffic security checkpoint monitoring system is an important part of smart city traffic management. It refers to a monitoring system that relies on specific places on the road, such as toll booths, traffic or security checkpoints, to photograph, record and process all pedestrians or motor vehicles passing through the checkpoint.

[0003] The existing publication number CN111899522A discloses a road traffic security checkpoint monitoring system, in which the vehicle detection unit includes a detection host and a ground sensor coil, the shooting unit includes a feature camera and a panoramic camera; the image acquisition management unit includes an industrial control computer and a video capture card, and the control software installed on the industrial control computer includes image acquisition processing software, video detection software and remote management software; the central management unit includes a data communication control machine, a central control computer and a monitoring station. The system is used for all-weather real-time detection and recording of vehicles in security checkpoints. It can automatically identify the license plate, color and other features of vehicles passing through the intersection, verify the legal identity of the vehicle, automatically check the blacklist library, and issue real-time alarms for speeding vehicles, illegal overtaking, and vehicles driving in the wrong direction, quickly correct traffic violations, and quickly solve traffic accident escapes and motor vehicle theft and robbery cases, providing important technical means and evidence.

[0004] However, the above-mentioned road traffic security checkpoint monitoring system uses ground sensing coils for vehicle detection, which has the limitations of complex construction, high maintenance costs, and limited detection range. Summary of the invention

[0005] The purpose of the present invention is to provide a road traffic security checkpoint monitoring system, which solves the problems of the existing road traffic security checkpoint monitoring system using ground sensing coils for vehicle detection, which has the limitations of complex construction, high maintenance cost and limited detection range.

[0006] To achieve the above-mentioned object, the present invention provides a road traffic security checkpoint monitoring system, comprising a vehicle detection module, a processing module, a transmission module and a central management module, wherein the processing module is connected to the vehicle detection module, and the transmission module is connected to the processing module and the central management module respectively;

[0007] The vehicle detection module is used to detect vehicles and obtain vehicle data by using radar and video fusion detection technology and combining sensors;

[0008] The processing module is used to obtain video data, process the video data using image enhancement and denoising technology, and introduce redundancy design and fault tolerance mechanism to ensure the stability and reliability of the system;

[0009] The transmission module is used to transmit the processed data and encrypt the transmitted data;

[0010] The central management module is used to receive data and process and analyze vehicle data using cloud computing and big data technologies.

[0011] Wherein, the vehicle detection module includes a radar unit, a camera unit and a sensor unit, and the radar unit, the camera unit and the sensor unit are respectively connected to the processing module;

[0012] The radar unit is used to measure the vehicle speed;

[0013] The camera unit is used to collect vehicle images and video data;

[0014] The sensing unit is used to collect additional vehicle detection information under specific circumstances through infrared and microwave sensors.

[0015] Wherein, the processing module includes an automatic fill light unit and an enhanced denoising unit, the automatic fill light unit is connected to the camera unit, and the enhanced denoising unit is connected to the camera unit;

[0016] The automatic fill light unit is used to detect the ambient light intensity through a photosensitive sensor, automatically adjust the brightness and color temperature of the fill light, and automatically fill light under low light conditions;

[0017] The enhancement denoising unit is used to improve the quality of the image by adjusting the grayscale distribution, contrast and edge details of the image, and to remove noise in the image by spatial domain filtering, frequency domain filtering, wavelet denoising or a deep learning-based method.

[0018] Wherein, the processing module also includes a redundant fault-tolerant unit;

[0019] The redundant fault-tolerant unit is used to adopt a dual-machine hot standby or multi-machine backup strategy to quickly switch to a backup device or module when a device or module fails, and adopt an automatic fault switching, error retransmission or timeout retransmission mechanism to automatically switch to a backup path or retransmit data when a system failure occurs.

[0020] Wherein, the central management module includes a distribution unit and a calculation unit, the distribution unit is connected to the transmission module, and the calculation unit is connected to the distribution unit;

[0021] The distribution unit is used to distribute the data processing tasks to multiple processing nodes;

[0022] The computing unit is used to process and analyze vehicle data using cloud computing and big data technologies.

[0023] Wherein, the central management module further includes a storage unit and an analysis unit, the storage unit is connected to the calculation unit, and the analysis unit is connected to the storage unit;

[0024] The storage unit is used to store vehicle data and process and analyze the data;

[0025] The analysis unit is used to perform in-depth analysis and mining on the stored data to extract valuable traffic management information.

[0026] Wherein, the central management module further includes a visualization unit and a backup unit, the visualization unit is connected to the analysis unit, and the backup unit is connected to the storage unit;

[0027] The visualization unit is used to visualize the data analysis results;

[0028] The backup unit is used to back up key data to an independent storage medium periodically or in real time.

[0029] The present invention discloses a road traffic security checkpoint monitoring system, wherein the vehicle detection module adopts radar and video fusion detection technology, combined with infrared and microwave sensors, to achieve accurate detection of vehicles. The processing module automatically fills in light under low light conditions to improve image quality, adopts image enhancement and denoising technology to improve image clarity and stability, and also introduces redundant design and fault-tolerant mechanism to ensure the stability and reliability of the system. The transmission module adopts a combination of wired and wireless to ensure real-time transmission of vehicle information. At the same time, the transmission data is encrypted and processed, and a secure transmission protocol is adopted to prevent the data from being intercepted or tampered with. The central management module adopts a distributed architecture design to disperse data processing, storage and other functions to multiple nodes, reduce the load pressure of a single node, and use cloud computing and big data technology to quickly process and analyze massive vehicle data, extract valuable traffic management information, and at the same time, establish independent data backup to ensure data integrity and availability. By introducing technologies such as radar, sensors and video detection, the dependence on ground sensing coils is reduced, the complexity of construction and maintenance is reduced, more accurate vehicle detection information is provided, the occurrence of false alarms and missed alarms is reduced, and the detection range is wider. Effectively solve the limitations of ground sensing coils in road traffic security checkpoint monitoring systems and improve the overall performance and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0031] Figure 1 It is a structural block diagram of the road traffic security checkpoint monitoring system of the first embodiment of the present invention.

[0032] Figure 2 It is a structural block diagram of a road traffic security checkpoint monitoring system according to a second embodiment of the present invention.

[0033] In the figure: 101-vehicle detection module, 102-processing module, 103-transmission module, 104-central management module, 105-radar unit, 106-camera unit, 107-sensing unit, 108-automatic fill light unit, 109-enhanced denoising unit, 110-redundant fault-tolerant unit, 111-distribution unit, 112-computing unit, 113-storage unit, 114-analysis unit, 115-visualization unit, 116-backup unit, 201-instruction module. DETAILED DESCRIPTION

[0034] Embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0035] The first embodiment of the present application is:

[0036] See also Figure 1 ,in, Figure 1 It is a structural block diagram of the road traffic security checkpoint monitoring system of the first embodiment of the present invention. The present invention provides a road traffic security checkpoint monitoring system: including a vehicle detection module 101, a processing module 102, a transmission module 103 and a central management module 104, the vehicle detection module 101 includes a radar unit 105, a camera unit 106 and a sensor unit 107, the processing module 102 includes an automatic fill light unit 108, an enhanced denoising unit 109 and a redundant fault-tolerant unit 110, and the central management module 104 includes a distribution unit 111, a calculation unit 112, a storage unit 113, an analysis unit 114, a visualization unit 115 and a backup unit 116. The above-mentioned solution solves the problem that the existing road traffic security checkpoint monitoring system uses ground sensing coils for vehicle detection, which has the limitations of complex construction, high maintenance cost and limited detection range. It can be understood that the above-mentioned solution can also be used to solve the problem of system stability.

[0037] According to this specific implementation, the processing module 102 is connected to the vehicle detection module 101, and the transmission module 103 is connected to the processing module 102 and the central management module 104 respectively;

[0038] The vehicle detection module 101 is used to detect vehicles and obtain vehicle data by using radar and video fusion detection technology and combining sensors;

[0039] The processing module 102 is used to obtain video data, and process the video data using image enhancement and denoising technology, and introduce redundancy design and fault tolerance mechanism to ensure the stability and reliability of the system;

[0040] The transmission module 103 is used to transmit the processed data and encrypt the transmitted data;

[0041] The central management module 104 is used to receive data and process and analyze vehicle data using cloud computing and big data technologies.

[0042] The vehicle detection module 101 uses a radar speed meter combined with a high-definition camera to detect vehicles. The radar provides accurate speed measurement, while the camera provides vehicle images and video data. This fusion technology can reduce the reliance on ground sensor coils and improve the accuracy and stability of detection. Infrared and microwave sensors are used as auxiliary detection means to provide additional vehicle detection information in specific environments, such as haze, rain and snow, to enhance the robustness of the system. During the image acquisition process, the processing module 102 uses image enhancement and denoising algorithms to improve the clarity and stability of the image and reduce noise interference, and introduces redundant design and fault-tolerant mechanisms, such as dual-machine hot standby and automatic fault switching, to ensure the stability and reliability of the system. The transmission module 103 builds an efficient and stable data transmission network to ensure the real-time transmission of vehicle information, including the use of a combination of wired and wireless methods to improve the flexibility and reliability of data transmission, encrypt the transmitted data to ensure the security of the data during transmission, and at the same time, use a secure transmission protocol to prevent the data from being intercepted or tampered with. The central management module 104 adopts a distributed architecture to disperse data processing, storage and other functions to multiple nodes, reduce the load pressure of a single node, improve the overall performance and stability of the system, and use cloud computing and big data technology to quickly process and analyze massive vehicle data. Through data mining and intelligent analysis, valuable traffic management information is extracted to provide decision-making support for traffic management departments, establish independent data backup, and ensure data integrity and availability in the event of an accident.

[0043] Wherein, the radar unit 105, the camera unit 106 and the sensor unit 107 are respectively connected to the processing module 102;

[0044] The radar unit 105 is used to measure the vehicle speed;

[0045] The camera unit 106 is used to collect vehicle images and video data;

[0046] The sensing unit 107 is used to collect additional vehicle detection information in a specific environment through infrared and microwave sensors.

[0047] The radar unit 105 uses a radar speedometer to provide accurate speed measurement, the camera unit 106 uses a high-definition camera to collect vehicle images and video data, and the sensor unit 107 uses infrared and microwave sensors as auxiliary detection means to provide additional vehicle detection information in specific environments, such as haze, rain and snow, to enhance the robustness of the system.

[0048] Secondly, the automatic fill light unit 108 is connected to the camera unit 106, and the enhancement and denoising unit 109 is connected to the camera unit 106;

[0049] The automatic fill light unit 108 is used to detect the ambient light intensity through a photosensitive sensor, automatically adjust the brightness and color temperature of the fill light, and automatically fill light under low light conditions;

[0050] The enhancement and denoising unit 109 is used to improve the quality of the image by adjusting the grayscale distribution, contrast and edge details of the image, and to remove noise in the image by spatial domain filtering, frequency domain filtering, wavelet denoising or deep learning-based methods.

[0051] The automatic fill light unit 108 detects the ambient light intensity through a photosensitive sensor, and automatically adjusts the brightness and color temperature of the fill light to achieve the best fill light effect, thereby automatically filling light under low light conditions, improving image brightness, and reducing the loss of dark details. The enhanced denoising unit 109 adopts histogram equalization, grayscale transformation, filtering enhancement, etc., and improves the overall quality of the image by adjusting the grayscale distribution, contrast, edge details, etc. of the image, improving the visual effect of the image, making the image clearer, the color more vivid, and the contrast more moderate. And adopts spatial domain filtering, such as mean filtering, median filtering, frequency domain filtering, wavelet denoising, denoising based on deep learning, etc., to remove different types of noise such as additive noise and multiplicative noise in the image, remove the noise in the image, and reduce the interference of noise on image quality.

[0052] At the same time, the redundant fault-tolerant unit 110 is used to adopt a dual-machine hot standby or multi-machine backup strategy to quickly switch to a backup device or module when a device or module fails, and to adopt an automatic fault switching, error retransmission or timeout retransmission mechanism to automatically switch to a backup path or retransmit data when a system failure occurs.

[0053] The redundant fault-tolerant unit 110 adopts strategies such as dual-machine hot standby and multi-machine backup to ensure that when a certain device or module fails, it can quickly switch to the backup device or module to ensure the continuous operation of the system, improve the stability and reliability of the system, and prevent the whole system from being paralyzed due to a single point failure. And adopt mechanisms such as automatic fault switching, error retransmission, timeout retransmission, etc., when the system fails, it automatically switches to the backup path or retransmits data to ensure the integrity of the data and the stability of the system. When the system fails, it can automatically detect, diagnose and take corresponding recovery measures to reduce the impact of the failure on the system. Among them, in the redundant fault-tolerant mechanism, the specific calculation process involves the evaluation of indicators such as fault detection time, fault recovery time, and data loss rate. These evaluations are usually statistically analyzed based on the actual operation data and historical fault records of the system. For example, in the redundant design of dual-machine hot standby, the switching time between the two devices can be calculated, that is, the time from the failure of the main device to the time when the backup device takes over the work, and the amount of data loss that may be caused during the switching process. These data are obtained through simulation tests or actual operation data and are used to evaluate the redundant fault tolerance and reliability of the system.

[0054] In addition, the distribution unit 111 is connected to the transmission module 103, and the calculation unit 112 is connected to the distribution unit 111;

[0055] The distribution unit 111 is used to distribute the data processing tasks to multiple processing nodes;

[0056] The computing unit 112 is used to process and analyze vehicle data using cloud computing and big data technologies.

[0057] The storage unit 113 is connected to the calculation unit 112, and the analysis unit 114 is connected to the storage unit 113;

[0058] The storage unit 113 is used to store vehicle data and process and analyze the data;

[0059] The analysis unit 114 is used to perform in-depth analysis and mining on the stored data to extract valuable traffic management information.

[0060] The visualization unit 115 is connected to the analysis unit 114, and the backup unit 116 is connected to the storage unit 113;

[0061] The visualization unit 115 is used to visualize the data analysis results;

[0062] The backup unit 116 is used to back up key data to an independent storage medium periodically or in real time.

[0063] The distribution unit 111 is deployed on the computing unit 112, and the data processing tasks are dispersed to multiple processing nodes. Each node is responsible for processing a part of the data, thereby reducing the load pressure of a single node, improving the data processing efficiency, having high concurrent processing capabilities and scalability, and being able to dynamically increase or decrease processing nodes according to system requirements. The computing unit 112 decomposes the computing tasks into multiple subtasks through a distributed computing framework, and executes them simultaneously on multiple computing nodes, thereby significantly improving the processing speed, and using data mining and machine learning algorithms to conduct in-depth mining and analysis of vehicle data. By training machine learning models, the vehicle driving rules, traffic status prediction, and abnormal driving behavior identification can be discovered. These analysis results can provide a scientific basis for traffic management decisions. For application scenarios with high real-time requirements, such as traffic light control, emergency response, etc., real-time data stream processing technology is supported. By real-time processing and analysis of vehicle data, emergency situations such as traffic congestion and accidents can be discovered and responded to in a timely manner. The processed data, such as recognition results, analysis reports, etc., are transmitted to the storage unit 113 for subsequent analysis and query. The storage unit 113 uses redundant storage technology to ensure that data is not lost, supports fast read and write and query operations, and can expand storage capacity as the amount of data grows. The analysis unit 114 performs in-depth analysis and mining on the stored data to extract valuable traffic management information. It uses a variety of data analysis algorithms and models, such as cluster analysis, association rule mining, etc., to discover hidden patterns and trends in the data and provide support for decision-making. The visualization unit 115 provides decision support for the traffic management department based on the data analysis results, visualizes the data analysis results, and facilitates decision makers to quickly understand. It uses a variety of decision scenarios and models, such as traffic flow prediction, congestion warning, etc. The backup unit 116 regularly or in real time backs up key data to an independent storage medium to prevent data loss. In the event of a catastrophic event, it can quickly start the disaster recovery system and restore the normal operation of the system.

[0064] A road traffic security checkpoint monitoring system using this embodiment, the vehicle detection module 101 adopts radar and video fusion detection technology, combined with infrared and microwave sensors, to achieve accurate detection of vehicles. The processing module 102 automatically fills in light under low light conditions to improve image quality, adopts image enhancement and denoising technology to improve image clarity and stability, and also introduces redundant design and fault-tolerant mechanism to ensure the stability and reliability of the system. The transmission module 103 adopts a combination of wired and wireless methods to ensure real-time transmission of vehicle information. At the same time, the transmission data is encrypted and a secure transmission protocol is adopted to prevent the data from being intercepted or tampered with. The central management module 104 adopts a distributed architecture design to disperse data processing, storage and other functions to multiple nodes, reduce the load pressure of a single node, and use cloud computing and big data technology to quickly process and analyze massive vehicle data to extract valuable traffic management information. At the same time, an independent data backup is established to ensure the integrity and availability of the data. By introducing technologies such as radar, sensors and video detection, the reliance on ground-sensing coils is reduced, the complexity of construction and maintenance is reduced, more accurate vehicle detection information is provided, the occurrence of false alarms and missed alarms is reduced, and the detection range is wider. This effectively solves the limitations of ground-sensing coils in road traffic security checkpoint monitoring systems and improves the overall performance and reliability of the system.

[0065] The second embodiment of the present application is:

[0066] Based on the first embodiment, please refer to Figure 2 ,in, Figure 2 2 is a block diagram of a road traffic security checkpoint monitoring system according to a second embodiment of the present invention. The road traffic security checkpoint monitoring system according to this embodiment further includes an instruction module 201 .

[0067] According to this specific implementation, the instruction module 201 is respectively connected to the vehicle detection module 101, the processing module 102, the transmission module 103 and the central management module 104;

[0068] The instruction module 201 is used to provide a user access interface and a unified application portal for users to query, analyze and manage relevant data.

[0069] A road traffic security checkpoint monitoring system using this embodiment, the user access interface includes authentication and authorization: users need to pass identity authentication to access the system to ensure the security of the system and the privacy of data, and the system will allocate corresponding resource access rights according to the user's identity and authority. User interface: Provide an intuitive and friendly user interface so that users can easily understand and operate the system, wherein the user interface includes a command line interface, a graphical user interface or a hybrid interface to meet the needs of different users. Interaction mechanism: Support multiple interaction methods, such as keyboard input, mouse clicks, touch screen operations, etc., so that users can choose the appropriate interaction method according to their habits and preferences. The unified application portal includes single sign-on: users only need to log in once to access multiple application systems and resources, without having to repeatedly enter the user name and password in each system, which not only improves the user's work efficiency, but also enhances the security of the system. Application integration: Integrate multiple independent application systems through unified standards and interfaces to achieve data sharing and process collaboration. Users can seamlessly switch between different application systems in the unified application portal to complete cross-system business processes. Personalization customization: Support users to customize the portal according to their needs, such as adjusting the interface layout, setting common application shortcuts, etc., which helps to improve the user's experience and work efficiency. The instruction module 201 also provides powerful data query, analysis and management functions to meet the diverse needs of users for data. By providing a user access interface and a unified application portal, it provides users with a convenient, efficient and secure platform to query, analyze and manage relevant data, which not only improves the work efficiency and quality of users, but also provides strong support for the digital transformation of enterprises or organizations.

[0070] What is disclosed above is only one or more preferred embodiments of the present application, and cannot be used to limit the scope of rights of the present application. Ordinary technicians in this field can understand that all or part of the processes of implementing the above embodiments and equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A road traffic security checkpoint monitoring system, characterized in that: It includes a vehicle detection module, a processing module, a transmission module and a central management module, wherein the processing module is connected to the vehicle detection module, and the transmission module is connected to the processing module and the central management module respectively; The vehicle detection module is used to detect vehicles and obtain vehicle data by using radar and video fusion detection technology and combining sensors; The processing module is used to obtain video data, process the video data using image enhancement and denoising technology, and introduce redundancy design and fault tolerance mechanism to ensure the stability and reliability of the system; The transmission module is used to transmit the processed data and encrypt the transmitted data; The central management module is used to receive data and process and analyze vehicle data using cloud computing and big data technologies.

2. The road traffic security checkpoint monitoring system as claimed in claim 1, characterized in that: The vehicle detection module includes a radar unit, a camera unit and a sensor unit, and the radar unit, the camera unit and the sensor unit are respectively connected to the processing module; The radar unit is used to measure the vehicle speed; The camera unit is used to collect vehicle images and video data; The sensing unit is used to collect additional vehicle detection information under specific circumstances through infrared and microwave sensors.

3. The road traffic security checkpoint monitoring system as claimed in claim 2, characterized in that: The processing module includes an automatic fill light unit and an enhanced denoising unit, wherein the automatic fill light unit is connected to the camera unit, and the enhanced denoising unit is connected to the camera unit; The automatic fill light unit is used to detect the ambient light intensity through a photosensitive sensor, automatically adjust the brightness and color temperature of the fill light, and automatically fill light under low light conditions; The enhancement denoising unit is used to improve the quality of the image by adjusting the grayscale distribution, contrast and edge details of the image, and to remove noise in the image by spatial domain filtering, frequency domain filtering, wavelet denoising or a deep learning-based method.

4. The road traffic security checkpoint monitoring system as claimed in claim 3, characterized in that: The processing module also includes a redundant fault-tolerant unit; The redundant fault-tolerant unit is used to adopt a dual-machine hot standby or multi-machine backup strategy to quickly switch to a backup device or module when a device or module fails, and adopt an automatic fault switching, error retransmission or timeout retransmission mechanism to automatically switch to a backup path or retransmit data when a system failure occurs.

5. The road traffic security checkpoint monitoring system as claimed in claim 1, characterized in that: The central management module includes a distribution unit and a calculation unit, the distribution unit is connected to the transmission module, and the calculation unit is connected to the distribution unit; The distribution unit is used to distribute the data processing tasks to multiple processing nodes; The computing unit is used to process and analyze vehicle data using cloud computing and big data technologies.

6. The road traffic security checkpoint monitoring system as claimed in claim 5, characterized in that: The central management module further comprises a storage unit and an analysis unit, wherein the storage unit is connected to the calculation unit, and the analysis unit is connected to the storage unit; The storage unit is used to store vehicle data and process and analyze the data; The analysis unit is used to perform in-depth analysis and mining on the stored data to extract valuable traffic management information.

7. The road traffic security checkpoint monitoring system as claimed in claim 6, characterized in that: The central management module further includes a visualization unit and a backup unit, wherein the visualization unit is connected to the analysis unit, and the backup unit is connected to the storage unit; The visualization unit is used to visualize the data analysis results; The backup unit is used to back up key data to an independent storage medium periodically or in real time.

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