Traffic monitoring system based on millimeter wave technology and AI camera
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- SHENZHEN JAGUAR WAVE TECH LTD
- Filing Date
- 2025-06-16
- Publication Date
- 2026-06-30
Smart Images
Figure CN224437034U_ABST
Abstract
Description
Technical Field
[0001] This utility model belongs to the field of intelligent transportation technology, specifically relating to a traffic monitoring system based on millimeter wave technology and AI cameras. Background Technology
[0002] Traffic monitoring systems are comprehensive systems that use technological means to monitor, control, and manage traffic conditions in real time, playing a vital role in ensuring traffic safety, optimizing traffic flow, and improving road efficiency. As an important component of modern intelligent transportation systems, traffic monitoring systems achieve comprehensive monitoring, intelligent management, and efficient service of traffic through advanced technologies. They play an irreplaceable role in ensuring traffic safety, alleviating traffic congestion, improving traffic efficiency, and optimizing the allocation of traffic resources. With continuous technological advancements, traffic monitoring systems will develop towards greater intelligence, efficiency, safety, and environmental friendliness, bringing more convenience and benefits to people's travel and urban development.
[0003] Existing traffic monitoring systems mainly rely on 5G communication technology, which has the following problems:
[0004] (1) Insufficient 5G coverage: 5G signal coverage is poor in remote areas or complex terrain;
[0005] (2) High cost: The construction and maintenance costs of 5G infrastructure are high;
[0006] (3) Delay issues: In high-density traffic scenarios, 5G networks may experience delays and congestion. Utility Model Content
[0007] To address the shortcomings of existing technologies, this invention provides a traffic monitoring system based on millimeter-wave technology and AI cameras that features high-efficiency communication, low-cost deployment, and low latency.
[0008] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:
[0009] Traffic monitoring systems based on millimeter-wave technology and AI cameras are applied to 5G infrastructure and vehicle-to-vehicle communication, including:
[0010] AI camera module for real-time road condition monitoring;
[0011] An edge computing unit is located within the AI camera module. The edge computing unit is used to receive real-time data streams from the AI camera module. The edge computing unit is also used to enable AI model processing and data transmission.
[0012] A millimeter-wave communication module, connected to the edge computing unit and used for millimeter-wave signal transmission;
[0013] The vehicle network access module is connected to the millimeter-wave communication module. The vehicle network access module is used to realize real-time communication between the vehicle and 5G infrastructure through the millimeter-wave communication module.
[0014] The control center is connected to both the AI camera module and the vehicle network access module. The control center is used to receive and integrate data from the AI camera module, and it is also used to generate traffic management strategies.
[0015] Preferably, the AI camera module integrates a deep learning algorithm for target detection and behavior analysis.
[0016] Preferably, the millimeter-wave communication module uses the 60GHz frequency band.
[0017] By adopting the above technical solution, this utility model has the following beneficial effects:
[0018] (1) This utility model is equipped with a millimeter wave communication module, which can transmit millimeter wave signals. It provides high bandwidth and low latency communication capabilities to achieve efficient communication. Moreover, the use of millimeter wave signal transmission can reduce the dependence on 5G infrastructure and reduce construction and maintenance costs.
[0019] (2) This utility model is equipped with an AI camera module, a vehicle network access module and other structures. In specific use, the AI camera module can realize accurate target detection and behavior analysis, and the vehicle network access module can realize the collaboration between the vehicle and the 5G infrastructure.
[0020] In summary, this utility model has the advantages of high communication efficiency, low deployment cost, and low latency. Attached Figure Description
[0021] Figure 1 This is a system architecture diagram of this utility model;
[0022] Figure 2 This is the data flow diagram of this utility model;
[0023] Figure 3 This is a structural schematic diagram of the millimeter-wave communication module of this utility model. Detailed Implementation
[0024] The technical solution of this utility model will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of this utility model, but not all embodiments.
[0025] The components of the present invention embodiments described and shown in the accompanying drawings can typically be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention.
[0026] Based on the embodiments of this utility model, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this utility model.
[0027] In the description of this utility model, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings and are only for the convenience of describing this utility model and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this utility model. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.
[0028] In the description of this utility model, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this utility model based on the specific circumstances.
[0029] Example 1
[0030] In this embodiment, a traffic monitoring system based on millimeter wave technology and AI cameras is proposed. It is applied to 5G infrastructure and between vehicles. By combining AI visual analysis and millimeter wave communication technology and accessing the vehicle-to-everything (V2X) architecture, it achieves efficient and low-latency traffic monitoring and management.
[0031] like Figures 1-3As shown, in one embodiment of this utility model, the traffic monitoring system based on millimeter-wave technology and AI cameras includes an AI camera module, an edge computing unit, a millimeter-wave communication module, a vehicle network access module, and a control center. The AI camera module is used for real-time monitoring of road conditions and is deployed at key locations such as traffic intersections and highways. The AI camera module integrates deep learning algorithms for target detection and behavior analysis. It can analyze traffic scenes in real time, including identifying pedestrians, vehicles, abnormal events, and traffic signs, and can also perform specific behavior analysis, including violation detection and congestion warnings. The specific device model used can be Hikvision. The Weishi DS-2CE18T-ITX camera utilizes existing deep learning algorithms. An edge computing unit is integrated within the AI camera module. This edge computing unit receives real-time data streams from the AI camera module and is also used to enable AI model processing and data transmission. It handles local data processing and AI model inference, reducing data transmission volume and latency. Video streaming is typically achieved using RTSP or ONVIF protocols, with a possible device model being the NVIDIA Jetson AGX Orin. The edge computing unit performs object detection and data compression, further reducing data transmission volume. A millimeter-wave communication module is integrated with the edge computing unit. The system is interconnected and used for millimeter-wave signal transmission. The millimeter-wave communication module, including but not limited to, uses the 60GHz frequency band, supports point-to-point (P2P) and point-to-multipoint communication, and has a coverage range of 1-2 kilometers. It enhances signal directionality and anti-interference capabilities through beamforming technology. A specific device model used may be the Jaguar PTP6150 product, which may include a housing, mounting bracket, vent valve, grounding terminal, and waterproof connector. The vehicle network access module is connected to the millimeter-wave communication module. The vehicle network access module is used to achieve real-time communication between the vehicle and 5G infrastructure through the millimeter-wave communication module. The vehicle network access module transmits monitoring data to the vehicle's network (V2X) via millimeter waves. The V2X architecture supports real-time communication between vehicles and 5G infrastructure, as well as between vehicles themselves. Specifically, the device used can be the Huawei OceanConnect vehicle networking platform. The control center of this invention is connected to both the AI camera module and the vehicle networking access module. The control center receives and integrates data from the AI camera module and also generates traffic management strategies. It receives and integrates data from multiple AI cameras to generate traffic management strategies (such as traffic light control and route planning). It provides a visual interface and supports remote monitoring and management. A suitable device for this purpose is the Dell PowerEdge R740XD server.
[0032] This invention employs an AI vision data direct connection to the vehicle-mounted millimeter-wave system (i.e., the vehicle network access module achieves real-time communication between the vehicle and 5G infrastructure through the millimeter-wave communication module), achieving an end-to-end latency of <40ms and significantly improving transmission efficiency. Furthermore, the millimeter-wave communication module integrates a phased array antenna and utilizes hybrid beamforming technology, achieving beam alignment accuracy at the 0.1-degree level, ensuring link stability. This invention employs a three-level communication protocol stack: emergency data, enhanced data, and full data, with the addition of a dynamic bandwidth algorithm (DBA) to ensure zero loss of emergency data. Emergency data refers to data with extremely high real-time and reliability requirements during communication, such as emergency stop signals in industrial automation control and emergency vital sign data in telemedicine. Loss or delay of this data can lead to serious consequences, such as equipment damage or endangering lives. Therefore, the communication protocol stack assigns the highest priority to emergency data, ensuring it is processed and transmitted first. Enhanced data, whose importance and real-time requirements fall between those of emergency data and full data, is considered more important. This might include data that optimizes system performance or data that needs to be transmitted promptly in specific scenarios, but with a certain degree of delay is permissible. For example, in intelligent transportation systems, real-time traffic flow statistics play a crucial role in optimizing traffic signal control and can be considered augmented data. Full data refers to all relevant data in the system, including emergency data, augmented data, and other general data. It has the broadest scope but relatively lower real-time requirements. Taking an enterprise's information management system as an example, full data might include basic employee information and daily business transaction data. When resources are sufficient, full data will be transmitted as completely as possible. However, when resources are limited, it may be appropriately compressed or delayed based on strategies. Dynamic bandwidth algorithms are mechanisms that dynamically allocate network bandwidth resources based on real-time network conditions and data priorities. In systems employing a three-tier communication protocol stack, DBAs flexibly adjust bandwidth allocation according to the different needs of emergency data, augmented data, and full data. When emergency data appears in the network, the DBA immediately detects it and quickly allocates sufficient bandwidth to ensure its priority transmission, thereby achieving zero loss of emergency data. Even under conditions of limited network bandwidth, the transmission quality of urgent data will be ensured by temporarily reducing bandwidth allocation for enhanced and full data. For enhanced data, the DBA will allocate bandwidth reasonably based on the remaining network bandwidth and the transmission status of urgent data, striving to meet its requirements for real-time performance and data integrity.Full data, on the other hand, will be transmitted using the remaining bandwidth while ensuring the transmission of emergency and enhanced data. This invention, through the combination of this three-level communication protocol stack and dynamic bandwidth algorithm, can effectively manage and allocate network resources in complex network environments according to the importance and real-time requirements of different data. This ensures that critical emergency data is prioritized for processing and transmission, maximizing the protection of zero loss of emergency data, while also taking into account the transmission of enhanced and full data, thereby improving the performance and reliability of the entire communication system.
[0033] In a specific application, this invention deploys AI camera modules and millimeter-wave communication modules at key locations such as traffic intersections and highways. Each AI camera module integrates an edge computing unit and a millimeter-wave communication module. The AI camera module collects traffic scene data, processes it locally through the edge computing unit, and transmits the processed data to the control center or the vehicle-to-everything (V2X) architecture via the millimeter-wave communication module. The vehicle receives traffic monitoring data (such as congestion information and accident warnings) through the millimeter-wave communication module. The vehicle and 5G infrastructure share data in real time, optimizing driving routes and traffic management. The control center integrates multiple data sources, generates traffic management strategies, and monitors traffic status in real time through a visual interface. This invention's millimeter-wave transmission provides high-bandwidth, low-latency communication capabilities, replacing 5G communication while reducing reliance on 5G infrastructure, lowering construction and maintenance costs. The deployment cost per kilometer is only 35% of that of a 5G solution. It supports the upgrading of existing traffic facilities. The AI camera module achieves accurate target detection and behavior analysis, while edge computing and millimeter-wave transmission ensure low-latency data processing. Furthermore, the vehicle-to-everything (V2X) architecture enables collaboration between the vehicle and 5G infrastructure.
[0034] This embodiment does not impose any limitation on the shape, material, structure, etc. of this utility model. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of this utility model shall fall within the protection scope of this utility model.
Claims
1.A traffic monitoring system based on millimeter wave technology and AI camera, applied to 5G infrastructure and between vehicles, characterized in that, include: AI camera module for real-time road condition monitoring; An edge computing unit is located within the AI camera module. The edge computing unit is used to receive real-time data streams from the AI camera module. The edge computing unit is also used to enable AI model processing and data transmission. A millimeter-wave communication module, connected to the edge computing unit and used for millimeter-wave signal transmission; The vehicle network access module is connected to the millimeter-wave communication module. The vehicle network access module is used to realize real-time communication between the vehicle and 5G infrastructure through the millimeter-wave communication module. The control center is connected to both the AI camera module and the vehicle network access module. The control center is used to receive and integrate data from the AI camera module, and it is also used to generate traffic management strategies. 2.The millimeter wave technology and AI camera-based traffic monitoring system according to claim 1, characterized in that: The AI camera module integrates deep learning algorithms for object detection and behavior analysis. 3.The millimeter wave technology and AI camera-based traffic monitoring system according to claim 1, characterized in that: The millimeter-wave communication module uses the 60GHz frequency band.