5G Adaptive LED Traffic Guidance Screen System with Integrated Streamlined Design

Abstract

This application discloses an integrated streamlined 5G adaptive LED traffic guidance screen system, including a pole body, an integrated arc-shaped fairing at the top, and an embedded LED guidance screen flush with the arc surface and embedded in the side of the pole body. The integrated arc-shaped fairing houses a multimodal sensing module that collects real-time data on road environment and traffic conditions. The pole body contains an edge computing module that communicates with the multimodal sensing module. The edge computing module performs local real-time processing, fusion, and AI inference to generate processed data. The adaptive display module dynamically generates display control commands based on the processed data to adjust the display content, brightness, and color temperature of the embedded LED guidance screen. This system effectively reduces wind resistance and improves aesthetics through its integrated streamlined design. Combined with edge computing and multimodal sensing, it achieves real-time adaptive adjustment of the traffic guidance screen, significantly improving the timeliness and safety of road guidance.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to a 5G adaptive LED traffic guidance screen system with an integrated streamlined shape. Background Technology

[0002] With the rapid development of intelligent transportation and 5G technology, LED traffic guidance screens on both sides of the road have become an important carrier for information dissemination. Existing traffic guidance screen systems usually include an independent pole, a display screen installed on the side of the pole, and an external sensor for collecting traffic flow. Some systems also integrate 5G micro base stations to achieve data transmission. The top of the pole is often equipped with a square chassis for shielding the equipment. The overall structure is relatively common and widely used.

[0003] However, existing guidance screen systems have significant technical shortcomings in practical applications. On the one hand, gaps easily form at the connection between traditional convex displays and poles, which not only increases the wind resistance coefficient and poses a safety hazard in strong winds, but also results in poor integration of the square shape with modern urban landscapes, damaging the overall visual aesthetics of the road. On the other hand, existing sensing devices are mostly single-modal and scattered, and data processing usually requires uploading to a remote cloud platform, resulting in high communication latency and an inability to achieve millisecond-level real-time response. In addition, the displays mostly adopt static or pre-programmed display modes, lacking the ability to adaptively adjust brightness, color temperature, and content according to ambient light, weather conditions, and real-time traffic flow, leading to poor visibility in complex environments such as rain, fog, and strong light, significantly reducing the guidance effect.

[0004] To overcome the problems of poor wind resistance and aesthetics caused by unreasonable structural design in existing traffic guidance screen systems, as well as poor real-time guidance and adaptability caused by data processing lag and rigid display modes, there is an urgent need in this field to develop a new type of light pole system that integrates streamlined appearance design, multi-source perception fusion, edge intelligent computing and display adaptive adjustment, so as to achieve accurate perception of the road environment and real-time dynamic optimization of guidance information, thereby improving the level of intelligent traffic management and road traffic safety. Summary of the Invention

[0005] To improve upon existing methods and systems, a streamlined, integrated 5G adaptive LED traffic guidance screen system is provided. The specific technical solution is as follows: In a first aspect, this application provides an integrated, streamlined 5G adaptive LED traffic guidance screen system, comprising: Main body of the pole; An integrated arc-shaped air guide is installed at the top of the main body of the rod; An embedded LED guide screen is embedded in the side of the main body of the pole, and the outer surface of the embedded LED guide screen is flush with the arc surface of the main body of the pole. The multimodal sensing module, integrated inside the integrated arc-shaped fairing, is configured to collect real-time data on the road environment and traffic conditions. The edge computing module communicates with the multimodal perception module and is configured to perform local real-time processing, fusion, and AI inference on the collected real-time data to generate processed data. The adaptive display module, connected to the edge computing module and the embedded LED induction screen, is configured to dynamically generate display control commands based on the processed data to adjust the display content, brightness, and color temperature of the embedded LED induction screen.

[0006] In some embodiments, a distributed collaboration module is also included; The distributed collaboration module connects to adjacent traffic guidance screen systems based on the 5G V2X communication protocol. It adopts a decentralized topology to achieve state synchronization among multiple nodes and enables adjacent traffic guidance screen systems to automatically take over control when any traffic guidance screen system fails.

[0007] In some embodiments, the multimodal sensing module includes a high-definition camera, a millimeter-wave radar, an ambient light sensor, and a temperature and humidity sensor; High-definition cameras and millimeter-wave radar are used to collect road images and vehicle speed data; Ambient light sensors and temperature and humidity sensors are used to collect data on light intensity and weather conditions.

[0008] In some embodiments, the edge computing module adopts an ARM+NPU heterogeneous architecture and is pre-installed with a traffic event recognition model; The edge computing module is configured to perform data fusion, denoising, and AI inference operations to identify traffic incidents and determine their severity.

[0009] In some embodiments, the adaptive display module is configured to intelligently adjust the display parameters of the embedded LED guidance screen based on traffic event level, light intensity, and weather condition data; Display parameters include brightness, color temperature, and refresh rate; Brightness adjustment range is 0-100%, and color temperature adjustment range is 2700K-6500K.

[0010] In some embodiments, the integrated arc-shaped fairing adopts a forward-extending streamlined curved surface structure, with the front end extending downward to form a rain shelter. The integrated arc-shaped air guide has a smooth transition and no sharp edges, and the surface is treated with anti-static spraying.

[0011] In some embodiments, the embedded LED induction screen adopts a narrow bezel design of no more than 8mm, and the embedded LED induction screen body has a micro trapezoidal shape that is narrower at the top and wider at the bottom. The inclination angle of the micro-trapezoidal shape is 5° to 15°.

[0012] In some embodiments, the back of the rod body is provided with multiple heat dissipation fins; The heat dissipation fins and the main body of the rod can be integrally formed or tightly fitted together.

[0013] In some embodiments, the system further includes a dynamic power regulation function module; The dynamic power adjustment module intelligently adjusts the power consumption of the embedded LED guidance screen based on road images and traffic speed data; Reduce the brightness and refresh rate of the embedded LED guidance screen under normal road conditions, and increase the brightness and contrast of the embedded LED guidance screen in congested or bright light scenarios.

[0014] In some embodiments, the main body of the rod is made of aluminum alloy, and the integrated arc-shaped guide fairing is made of polycarbonate and is connected to the main body of the rod through a snap-fit ​​structure. The snap-fit ​​structure includes a concealed locking mechanism.

[0015] This application employs an integrated curved fairing and an embedded flush LED screen to create a streamlined shape. It integrates a multimodal sensing module to collect data, which is then processed locally in real-time by an edge computing module and subjected to AI inference. An adaptive display module dynamically adjusts the screen's display content, brightness, and color temperature. This solution effectively reduces wind resistance and enhances urban aesthetics. Utilizing edge computing, it achieves millisecond-level real-time response, solving the problem of cloud processing latency. Simultaneously, it adaptively adjusts display parameters based on ambient light and traffic flow, significantly enhancing visibility and guidance accuracy in complex environments such as rain, fog, and strong light, thereby improving road safety and intelligent management. Attached Figure Description

[0016] Figure 1 This is a system architecture diagram of the 5G adaptive LED traffic guidance screen system with an integrated streamlined shape proposed in this invention.

[0017] In the diagram: 1. Main body of the pole; 2. Integrated arc-shaped air guide; 3. Embedded LED guidance screen; 4. Multimodal sensing module; 5. Edge computing module; 6. Adaptive display module. Detailed Implementation

[0018] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0019] Firstly, this application provides an integrated, streamlined 5G adaptive LED traffic guidance screen system, such as... Figure 1 As shown, it includes: Main body 1; An integrated arc-shaped air guide shroud 2 is installed on the top of the main body 1 of the rod; An embedded LED guide screen 3 is embedded in the side of the main body 1 of the pole, and the outer surface of the embedded LED guide screen 3 is flush with the arc surface of the main body 1 of the pole. The multimodal sensing module 4, integrated inside the integrated arc-shaped fairing 2, is configured to collect real-time data on the road environment and traffic conditions. Edge computing module 5, which is communicatively connected to multimodal perception module 4, is configured to perform local real-time processing, fusion, and AI inference on the collected real-time data to generate processed data. The adaptive display module 6, connected to the edge computing module 5 and the embedded LED induction screen 3, is configured to dynamically generate display control commands based on the processed data to adjust the display content, brightness and color temperature of the embedded LED induction screen 3.

[0020] In practical implementation, the 5G micro base station antenna and multimodal sensing module 4 are first integrated into a concealed space inside the integrated arc-shaped fairing 2. The streamlined aerodynamic characteristics of the fairing effectively reduce the impact of strong winds on the main body of the pole 1, while avoiding the visual abruptness of external equipment. The embedded LED guidance screen 3 is encapsulated with high-strength tempered glass and is completely flush with the curved side surface of the pole, eliminating the dust accumulation and wind noise problems of traditional protruding screens. In specific operation, the multimodal sensing module 4 can adopt a combination of millimeter-wave radar and wide-angle AI camera. The millimeter-wave radar accurately captures lane-level vehicle flow speed and distance, and the AI ​​camera identifies vehicle models and traffic events. This raw data is directly transmitted to the edge computing module 5 without passing through the cloud. This module has a built-in AI inference chip that runs a lightweight YOLO target detection algorithm, completing data fusion and situational analysis locally in milliseconds. For example, when a rear-end collision is detected 200 meters ahead, the edge computing module 5 immediately generates "accident slow-down" processing data and sends it to the adaptive display module 6. The adaptive display module 6 dynamically adjusts its display strategy based on processed data. It not only displays warning information in bright red font on the screen but also monitors ambient light in real time using a light sensor. Under direct sunlight, it automatically increases screen brightness and adjusts the color temperature to cool white to enhance penetration. At night or in tunnels, it reduces brightness and switches to warm yellow light to reduce glare. Simultaneously, it dynamically adjusts the text scrolling speed and font size based on traffic density. This deep integration of structure and algorithm brings significant benefits. The streamlined, integrated shape improves the pole's wind resistance to level 12 or higher and significantly enhances its aesthetics. The embedded design protects the screen from side impacts, while the combination of edge computing and multimodal perception completely solves the problem of delayed guidance information caused by network latency in traditional cloud control systems. The adaptive adjustment function ensures clear visibility of guidance information in all weather conditions, including heavy rain, fog, and strong light. According to actual test data, the system improves traffic guidance response speed by more than 80% in complex road conditions, effectively reducing the incidence of secondary accidents and achieving efficient collaboration between road infrastructure and intelligent transportation.

[0021] In some embodiments, a distributed collaboration module is also included; The distributed collaboration module connects to adjacent traffic guidance screen systems based on the 5G V2X communication protocol. It adopts a decentralized topology to achieve state synchronization among multiple nodes and enables adjacent traffic guidance screen systems to automatically take over control when any traffic guidance screen system fails.

[0022] In practical implementation, the deployment of the distributed collaborative module mainly relies on the deep integration of 5G NR-V2X communication technology and the self-organizing network protocol stack. Each traffic guidance screen system is configured as an intelligent node with independent computing and communication capabilities, and the decentralized Mesh topology structure abandons the traditional central server control mode. For example, in the continuous guidance scenario of urban main roads, when the multimodal perception module 4 of a traffic guidance screen system detects a sudden congestion or accident, the distributed collaborative module will broadcast a basic safety message (BSM) directly to the adjacent upstream and downstream nodes through the 5G V2X PC5 interface. After receiving the message, the adjacent nodes can update the traffic situation map directly in the local edge computing module 5 without cloud processing, and synchronously adjust the display content of their respective embedded LED guidance screens 3 to form a continuous "green wave" or "accident warning" guidance. This point-to-point direct communication greatly shortens the information synchronization latency. Another concrete application scenario is fault self-healing. The system has a built-in heartbeat detection mechanism. When a light pole goes offline due to power supply abnormalities or hardware failure, its adjacent nodes will detect the link interruption within milliseconds and automatically take over control of the faulty node through pre-set preemptive control logic. The taking-over node will use its own sensing data to calculate the optimal display strategy and control the screen of the faulty node or its own screen to expand the display area, ensuring that the continuity of guidance information is not interrupted. This technology brings significant benefits. The decentralized architecture fundamentally eliminates the risk of single-point failure, allowing the entire light pole system to maintain basic operation even if some nodes are damaged, greatly improving the robustness and reliability of traffic infrastructure. At the same time, the distributed collaboration based on 5G V2X enables millisecond-level response for state synchronization between multiple nodes. Compared with the traditional cloud-based command delivery mode, the update speed of guidance information is several times faster. Especially in severe weather or network congestion environments, the local self-organizing network can ensure the priority transmission of critical traffic commands. In addition, combined with the adaptive display module 6, the collaborative module can perform global brightness smooth adjustment based on ambient light sensing data from multiple nodes, avoiding visual fatigue caused by sudden changes in screen brightness while driving at high speeds. This not only improves traffic efficiency but also significantly reduces the incidence of secondary accidents, achieving dual optimization of road resource utilization and safety management.

[0023] In some embodiments, the multimodal sensing module 4 includes a high-definition camera, a millimeter-wave radar, an ambient light sensor, and a temperature and humidity sensor. High-definition cameras and millimeter-wave radar are used to collect road images and vehicle speed data; Ambient light sensors and temperature and humidity sensors are used to collect data on light intensity and weather conditions.

[0024] In practical implementation, the multimodal perception module 4 employs a highly integrated hardware fusion solution, encapsulating a 4K starlight-level high-definition camera, a 77GHz millimeter-wave radar, a high-precision ambient light sensor, and an industrial-grade temperature and humidity sensor within a protective cavity inside an integrated arc-shaped fairing 2. Technically, the high-definition camera uses H.265 hardware encoding to capture lane-level images in real time, while the millimeter-wave radar accurately calculates the distance and instantaneous velocity of target objects using the Doppler effect. Both are spatially registered in the edge computing module 5 using timestamp alignment technology. For example, when a vehicle ahead brakes suddenly, radar data can compensate for the camera's blind spots at night or in low light conditions. The temperature and humidity sensor and ambient light sensor continuously collect environmental physical parameters; when humidity saturation and a sudden drop in illuminance are detected, the system can determine it as fog or heavy rain. After receiving this multi-source heterogeneous data, the edge computing module 5 runs a lightweight data fusion algorithm to eliminate noise interference from individual sensors, generating comprehensive situational data including traffic flow status, environmental weather, and lighting conditions, which is then transmitted to the adaptive display module 6. This module dynamically adjusts its strategy based on the fused data. For example, it automatically increases the brightness of the LED screen and switches to a cooler color temperature to enhance penetration under strong direct sunlight, and displays diversion guidance information on the upstream screen in advance when congestion trends are detected. This deep application of multimodal perception has brought significant benefits. First, the complementary characteristics of millimeter-wave radar and cameras solve the problem of failure of single visual perception in adverse weather conditions, greatly improving the accuracy of traffic incident detection. Second, the introduction of ambient light and temperature and humidity data allows the screen display to actively adapt to environmental changes, avoiding decreased visibility due to glare or insufficient contrast. Finally, since all perception data is fused locally at the millisecond level, the system can iterate the display strategy without waiting for cloud instructions, increasing the response speed of the guidance screen in sudden road conditions by an order of magnitude, effectively reducing the risk of rear-end collisions caused by information lag. At the same time, the integrated sensor also avoids the problems of increased wind resistance and aging wiring caused by external equipment.

[0025] In some embodiments, the edge computing module 5 adopts an ARM+NPU heterogeneous architecture and is pre-installed with a traffic event recognition model; Edge computing module 5 is configured to perform data fusion, denoising, and AI inference operations to identify traffic incidents and determine their severity.

[0026] In this embodiment, the edge computing module 5 adopts a heterogeneous hardware architecture of ARM core and NPU neural network processor. The ARM core is responsible for time synchronization and preliminary cleaning of multi-channel sensor data. For example, it aligns the video stream from the high-definition camera with the point cloud data from the millimeter-wave radar on the time axis at the microsecond level and uses the Kalman filter algorithm to remove noise points caused by rain or electromagnetic interference. The NPU loads a lightweight traffic event recognition model that has been pruned and quantized. This model is based on the improved YOLOv5 architecture and has been specifically trained for road scenarios. In terms of technical implementation, the system has a pre-built feature library of various traffic events such as congestion, accidents, breakdowns, and pedestrian intrusion. When the fused data is input into the NPU, the model will quickly perform inference and output the event category and confidence level. At the same time, it will combine the vehicle speed measured by radar and the queue length to calculate the event level. For example, a queue length of more than 500 meters and an average vehicle speed of less than 10 km / h is judged as a level one severe congestion. The adaptive display module 6 dynamically generates control commands based on the level determination result. If a Level 1 accident is detected, it will not only display the red warning text "Accident Ahead" on the embedded LED guidance screen 3, but also automatically increase the screen brightness to the maximum value and adjust the color temperature to the cool white with the strongest penetration. At the same time, it controls the text to scroll in a fast flashing mode to attract the driver's attention. This hardware and software collaborative technical solution brings significant benefits. The heterogeneous architecture of ARM+NPU enables massive amounts of unstructured video data and structured radar data to be fused and inferred locally in milliseconds, completely avoiding the network latency and bandwidth consumption problems caused by uploading video to the cloud for analysis in traditional solutions, and ensuring the real-time generation of guidance information. The accurate classification of traffic incident levels allows the display strategy to match the severity of the incident, avoiding driver numbness caused by frequent false alarms or over-rendering, and significantly improving the effectiveness of warnings and road traffic safety in complex traffic situations.

[0027] In some embodiments, the adaptive display module 6 is configured to intelligently adjust the display parameters of the embedded LED guidance screen 3 based on traffic event level, light intensity and weather conditions data; Display parameters include brightness, color temperature, and refresh rate; Brightness adjustment range is 0-100%, and color temperature adjustment range is 2700K-6500K.

[0028] In practical applications, the adaptive display module 6 deeply integrates with the traffic event level data output by the edge computing module 5 through its built-in intelligent dimming algorithm. Specifically, it employs backlight control technology based on PWM pulse width modulation and a real-time color coordinate mapping mechanism. For example, in a daytime scenario with strong direct sunlight, if the ambient light sensor collects illuminance data exceeding 100,000 lux, the adaptive display module 6 immediately increases the brightness of the embedded LED guidance screen 3 to 100% and adjusts the color temperature from the default 4000K to the 6500K cool white light range. This utilizes the high penetration characteristics of the high color temperature light source to combat sunlight interference, ensuring that distant vehicles can clearly identify the screen content. In low-light environments such as at night or at tunnel entrances, the module automatically reduces the brightness to below 20% and adjusts the color temperature back to 2700K warm yellow light to avoid glare for the driver. Another specific scenario is dealing with severe weather. When the temperature and humidity sensor reports that the air humidity is saturated and the visibility is less than 200 meters, the module will not only reduce the overall brightness to reduce diffuse reflection, but also dynamically increase the refresh rate to 120Hz to enhance the smoothness of the dynamic warning signs. At the same time, based on the accident level determined by the edge computing module 5, the display mode will be automatically switched. For example, when a level one accident is detected, a specific area of ​​the screen will flash bright red and achieve a "breathing light" warning effect in conjunction with the high refresh rate. This refined parameter adjustment brings significant benefits. With stepless brightness adjustment from 0-100% and a wide color temperature coverage of 2700K-6500K, the screen can maintain optimal visual contrast under various weather conditions, solving the pain points of traditional guidance screens being "unvisible" in rainy or foggy weather or "too glaring" at night. The adaptive refresh rate adjustment ensures the clarity of dynamic information while reducing power consumption during static display. According to actual measurements, this mechanism reduces the overall energy consumption of the screen by about 30% while ensuring the warning effect. Furthermore, due to the high degree of matching between the displayed content and the environment and traffic conditions, the driver's reaction time to guidance information is shortened by more than 0.5 seconds, greatly improving the safety and comfort of road traffic.

[0029] In some embodiments, the integrated arc-shaped fairing 2 adopts a forward-extending streamlined curved surface structure, with the front end extending downward to form a rain shelter. The integrated arc-shaped air guide 2 has a smooth transition and no sharp edges, and the surface is treated with anti-static spraying.

[0030] In practical implementation, the integrated arc-shaped air deflector 2 adopts a forward-extending streamlined curved surface design optimized based on computational fluid dynamics simulation. Its front end extends downward to form a rain-shielding eave structure with a width of approximately 30 centimeters. This design not only guides airflow using a smoothly transitioning arc surface to reduce the drag coefficient, but also effectively prevents rainwater from directly washing over the surface of the embedded LED induction screen 3, avoiding the formation of a water film on the screen that would affect visibility. In terms of materials and processes, the air deflector is made of high-pressure die-cast aluminum and undergoes nano-level anti-static spraying treatment. The surface resistivity is controlled between 10⁶ and 10⁸ ohms. This treatment significantly reduces dust accumulation caused by electrostatic adsorption in the dry and dusty autumn and winter seasons, ensuring that the optical lens and millimeter-wave radar transmission area of ​​the internal multimodal sensing module 4 remain clean at all times. In addition, since the air deflector is made of integrated die-cast mold without any sharp edges, it avoids the risk of scratches to operators during installation and maintenance. At the same time, its streamlined appearance blends better with the urban road landscape. This structural design brings significant benefits. The combination of the forward-extending rain shelter and the smooth curved surface reduces the stress on the pole by about 30% under strong winds of level 12, greatly improving the equipment's survivability in typhoon weather. The application of the anti-static coating reduces the deviation of perception data caused by dust cover, ensuring the accuracy of traffic flow data acquired by the edge computing module 5. The streamlined shape without sharp edges not only eliminates the wind shear noise generated by the traditional square chassis, but also improves the overall aesthetics, making traffic facilities no longer an obtrusive obstacle, achieving a unity of functionality and urban aesthetics. At the same time, it also reduces the equipment failure rate caused by dust accumulation and extends the system's maintenance-free cycle.

[0031] In some embodiments, the embedded LED induction screen 3 adopts a narrow bezel design of no more than 8mm, and the embedded LED induction screen 3 has a micro trapezoidal shape that is narrower at the top and wider at the bottom. The inclination angle of the micro-trapezoidal shape is 5° to 15°.

[0032] In practical application, the embedded LED guidance screen 3 employs advanced COB on-board chip packaging technology to achieve an extremely narrow physical bezel design of no more than 8mm. Simultaneously, the screen structure is designed as a micro-trapezoidal shape, narrower at the top and wider at the bottom. The specific tilt angle is preferably 10° based on the pole diameter, ensuring the screen remains perfectly flush with the curved surface after being embedded in the side of the pole body 1. Technically, this micro-trapezoidal design is not a simple geometric cut, but rather incorporates the principle of optical refraction. By adjusting the packaging angle of the LED beads and the light transmittance of the screen glass, the lower edge of the screen is brought closer to the driver's field of vision. For example, in highway scenarios, the 10° tilt angle combined with the narrow bezel design not only increases the effective display area by approximately 15%, but also allows the diffused light generated on the screen surface to more accurately cover the lane area, rather than scattering towards the sky or road shoulders. Furthermore, the seamless embedding of the screen into the curved surface of the pole utilizes flexible sealing strips and a magnetic fixing structure, ensuring structural strength while eliminating the gaps between the traditional protruding screen and the bracket. This structural optimization has brought significant benefits. First, the trapezoidal structure, narrower at the top and wider at the bottom, utilizes the principle of visual compensation to correct the trapezoidal distortion perception caused by the driver's upward viewing angle, making the displayed text and patterns more upright and improving the accuracy of long-distance recognition. Second, the ultra-narrow bezel and embedded flush design completely eliminate the wind resistance vortex caused by the protruding structure, significantly reducing the torque of the pole under strong crosswinds. Combined with the integrated arc-shaped air deflector 2, it further enhances the ability to withstand category 12 typhoons. Finally, because the screen body is not protruding and has a smooth surface, it effectively avoids the problems of dust accumulation and easy damage from side impacts of traditional external screen bodies. Combined with the multimodal perception and edge computing mentioned above, the screen body can automatically adjust the brightness according to the ambient light. With the support of trapezoidal optics, even under direct sunlight at noon or under the illumination of car headlights at night, the guiding content still maintains high contrast and clear visibility, thus achieving a three-in-one improvement in structural strength, aerodynamic performance, and display effect.

[0033] In some embodiments, the back of the rod body 1 is provided with multiple heat dissipation fins; The heat dissipation fins and the main body 1 can be integrally formed or tightly fitted together.

[0034] In practical implementation, this embodiment employs multiple efficient thermal management technologies to address the heat dissipation needs of the highly integrated electronic components within the main body 1. The first approach utilizes high-pressure die-casting to integrally mold the main body 1 with the back heat sink fins, making the main body itself a giant heat sink. The heat generated by the internal edge computing module 5 and power module is directly conducted to the surface through the internal lattice of the aluminum material. The second approach involves tightly bonding pre-fabricated aluminum alloy fins to the back of the main body using high thermal conductivity silicone. The fin surfaces undergo anodizing to enhance radiative heat dissipation. Furthermore, the fin spacing design incorporates a vertical airflow principle, utilizing the thermal pressure difference to create natural convection. For example, under high-temperature conditions in summer, when the edge computing module 5 is running at full load processing multiple video streams, the integrated fins can quickly dissipate core heat. Combined with the micro-airflow channels reserved in the tight-fitting technology, passive heat dissipation can be achieved without a fan. In addition, the heat sink fin layout avoids the internal wiring area of ​​the main body, preventing cables from aging due to prolonged baking.

[0035] This optimized heat dissipation structure brings significant and multi-dimensional benefits. First, because the NPU and ARM architecture chips built into the edge computing module 5 generate a lot of heat during AI inference, traditional enclosed structures are prone to heat accumulation. However, the large heat dissipation fins on the back greatly increase the heat exchange area. Actual test data shows that this can reduce the temperature of key internal components by 15°C to 20°C, thus avoiding high-temperature throttling or system crashes, and ensuring the continuity and real-time performance of traffic event recognition. Second, the improved heat dissipation efficiency directly extends the lifespan of the embedded LED guidance screen 3. The light decay rate of LED beads is significantly slowed down in low-temperature environments, ensuring that the screen brightness does not significantly decrease during long-term use and maintaining the visibility distance of guidance information. Finally, the one-piece molding or tight-fitting process not only reduces the weight and wind resistance of the structure but also avoids the noise and dust inhalation problems caused by external fans. This allows the entire system to maintain extremely high structural reliability while operating quietly, providing a basic thermal environment guarantee for the stable operation of the multimodal sensing module 4 in harsh weather conditions, and achieving a synergistic improvement in heat dissipation performance, structural strength, and system lifespan.

[0036] In some embodiments, the system further includes a dynamic power regulation function module; The dynamic power adjustment module intelligently adjusts the power consumption of the embedded LED guidance screen 3 based on road images and traffic speed data; The brightness and refresh rate of the embedded LED guidance screen 3 are reduced under normal road conditions, while the brightness and contrast of the embedded LED guidance screen 3 are increased in congested or bright light scenarios.

[0037] In practical implementation, the dynamic power adjustment function module is deeply integrated into the edge computing module 5. By analyzing the lane occupancy data collected by the high-definition camera and the traffic flow speed data fed back by the millimeter-wave radar in real time, a closed-loop energy consumption control logic is constructed. In terms of technical implementation, this module adopts a PID control algorithm based on scene thresholds. For example, during periods of low traffic at night, when the system detects that the lane occupancy rate is less than 10% and the vehicle speed is smooth for 5 consecutive minutes, it will automatically reduce the brightness of the embedded LED guidance screen 3 from the usual 4000 nits to 1500 nits in a stepped manner, and at the same time reduce the refresh rate from 120Hz to 60Hz, significantly reducing power consumption while ensuring basic visibility. In the case of strong sunlight at noon, the ambient light sensor triggers a high-brightness mode. The module not only pushes the screen brightness to the full power of 6000 nits, but also improves the saturation of red and yellow warning colors through color gamut enhancement technology to combat glare. When congestion or accidents are detected, in order to ensure the clarity of dynamic guidance information, the module will instantly increase the drive current, so that the refresh rate rises back to 120Hz and locally highlights the accident area. This on-demand power management strategy has brought significant benefits. First, it breaks away from the traditional "constant full-power illumination" approach of guidance screens. Actual measurements show that it can reduce power consumption by approximately 45% during low-traffic periods, effectively alleviating the power supply pressure on urban power grids. Second, low-power operation significantly reduces the heat generated by LED beads and driver ICs. Combined with the heat dissipation fins on the back of the pole, it keeps the screen's operating temperature at a low level, thereby significantly slowing down the light decay rate and extending the screen's lifespan by more than 30%. Finally, intelligent adjustment ensures that drivers receive guidance information with optimal contrast under any ambient light and traffic conditions, avoiding visual difficulties caused by insufficient brightness or visual fatigue caused by glare, achieving a dual optimization of energy conservation, emission reduction, and traffic safety.

[0038] In some embodiments, the main body 1 of the rod is made of aluminum alloy, and the integrated arc-shaped guide shroud 2 is made of polycarbonate and is connected to the main body 1 of the rod through a snap-fit ​​structure; The snap-fit ​​structure includes a concealed locking mechanism.

[0039] In this embodiment, the connection process between the pole structure and the protective cover has been deeply optimized. The main body 1 of the pole is made of high-strength 6061-T6 aluminum alloy and is integrally formed by spinning process. The excellent thermal conductivity and structural strength of aluminum alloy not only bear the overall load-bearing function, but also serve as the heat sink carrier for internal electronic components. The integrated arc-shaped guide cover 2 is injection molded from polycarbonate (PC) engineering plastic with high light transmittance and UV resistance. The good electromagnetic wave penetration of PC material ensures that the signals of the internal 5G micro base station and V2X communication module are transmitted without attenuation. In terms of assembly technology, the snap-fit ​​structure adopts a rotary quick-release design. Specifically, an elastic latch is pre-embedded on the edge of the fairing, which precisely matches the L-shaped hidden latch on the inner wall of the top of the pole. During installation, no tools are required; simply align the fairing with the pole and rotate and press down. The latch will slide into the latch slot and be firmly locked by the internal limiting block. During disassembly, the hidden latch can be quickly separated by using a special unlocking piece to open it. This design completely avoids the wind noise and corrosion risks associated with traditional exposed bolt connections. For example, in actual maintenance scenarios, when the internal multimodal sensing module 4 needs maintenance, maintenance personnel do not need to climb to the top of the pole to use a wrench. They can separate the fairing from the ground using the unlocking piece to expose the internal module for repair, greatly shortening the troubleshooting time.

[0040] This innovative choice of materials and connection structure brings multiple significant benefits. First, the combination of rigidity and flexibility between the aluminum alloy pole and the polycarbonate fairing ensures the pole's resistance to bending under a Category 12 typhoon while utilizing the toughness of the PC material to absorb the impact energy from strong winds, preventing equipment damage caused by rigid collisions. Second, the concealed snap-fit ​​structure eliminates sharp edges and gaps on the pole's surface, resulting in a cleaner, more streamlined appearance that meets urban aesthetic requirements. It also effectively prevents rainwater from seeping into the pole and causing short circuits. Combined with the anti-static coating, it significantly reduces the probability of dust and insect remains accumulating at the joints, minimizing the decrease in sensor module recognition rates caused by dirt obstruction. More importantly, because the snap-fit ​​connection has a slight elasticity, it can effectively buffer the slight deformation of the pole under strong winds, avoiding metal cracks caused by long-term fatigue at the rigid connection, thereby extending the service life of the overall structure. According to actual measurements, the fatigue life of the light pole structure using this connection technology is more than 40% longer than that of the traditional flange connection, while reducing on-site installation and maintenance time by 60%, achieving a dual breakthrough in structural reliability and ease of operation and maintenance.

[0041] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0042] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0043] 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 principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An integrated flowline profile 5G adaptive LED traffic induction screen system, characterized by, include: Main body of the rod (1); An integrated arc-shaped flow guide (2) is disposed on the top of the main body (1); An embedded LED guiding screen (3) is embedded in the side of the main body of the rod (1), and the outer surface of the embedded LED guiding screen (3) is flush with the arc surface of the main body of the rod (1); The multimodal sensing module (4) is integrated inside the integrated arc-shaped fairing (2) and is configured to collect real-time data on road environment and traffic conditions; The edge computing module (5) is communicatively connected to the multimodal perception module (4) and is configured to perform local real-time processing, fusion and AI inference on the collected real-time data to generate processed data. The adaptive display module (6), connected to the edge computing module (5) and the embedded LED guiding screen (3), is configured to dynamically generate display control commands based on the processed data to adjust the display content, brightness and color temperature of the embedded LED guiding screen (3).

2. The system of claim 1, wherein, It also includes a distributed collaboration module; The distributed collaboration module connects to adjacent traffic guidance screen systems based on the 5G V2X communication protocol, adopts a decentralized topology to achieve state synchronization among multiple nodes, and enables adjacent traffic guidance screen systems to synchronize their states in the event of a failure in any of the traffic guidance screen systems. Automatically take over control permissions.

3. The system of claim 1 or 2, wherein, The multimodal sensing module (4) includes a high-definition camera, a millimeter-wave radar, an ambient light sensor, and a temperature and humidity sensor; The high-definition camera and the millimeter-wave radar are used to collect road images and vehicle speed data; The ambient light sensor and the temperature and humidity sensor are used to collect data on light intensity and weather conditions.

4. The system according to claim 3, characterized in that, The edge computing module (5) adopts an ARM+NPU heterogeneous architecture and is pre-installed with a traffic event recognition model; The edge computing module (5) is configured to perform data fusion, denoising and AI inference operations to identify traffic events and determine the level of the traffic events.

5. The system according to claim 4, characterized in that, The adaptive display module (6) is configured to intelligently adjust the display parameters of the embedded LED guidance screen (3) according to the traffic event level, the light intensity and the weather conditions data; The display parameters include brightness, color temperature, and refresh rate; The brightness adjustment range is 0-100%, and the color temperature adjustment range is 2700K-6500K.

6. The system according to claim 5, characterized in that, The integrated arc-shaped air guide (2) adopts a forward-extending streamlined curved surface structure, with the front end extending downward to form a rain-shielding eave; The integrated arc-shaped flow guide (2) has a smooth overall transition and no sharp edges, and its surface is treated with anti-static spraying.

7. The system according to claim 6, characterized in that, The embedded LED induction screen (3) adopts a narrow bezel design of no more than 8mm, and the embedded LED induction screen (3) has a micro trapezoidal shape that is narrow at the top and wide at the bottom. The inclination angle of the micro-trapezoidal shape is 5° to 15°.

8. The system according to claim 7, characterized in that, The back of the rod body (1) is provided with multiple heat dissipation fins; The heat dissipation fins and the rod body (1) can be integrally formed or tightly fitted together.

9. The system according to claim 8, characterized in that, The system also includes a dynamic power regulation module; The dynamic power adjustment module intelligently adjusts the power consumption of the embedded LED guidance screen (3) based on the road image and traffic speed data; The brightness and refresh rate of the embedded LED guidance screen (3) are reduced under normal road conditions, while the brightness and contrast of the embedded LED guidance screen (3) are increased under congested or strong light conditions.

10. The system according to claim 9, characterized in that, The main body of the rod (1) is made of aluminum alloy, and the integrated arc-shaped flow guide (2) is made of polycarbonate and is connected to the main body of the rod (1) through a snap-fit ​​structure; The buckle structure includes a concealed latch.

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