A road change detection system

Abstract

The present invention discloses a road change detection system, which relates to the field of data processing technology. The system includes an unmanned aerial vehicle, an infrared camera, a wireless communication module, a data collector and a data processing module; the infrared camera is installed on the unmanned aerial vehicle, and is used to obtain the infrared thermal imaging of the road surface of the target road when the unmanned aerial vehicle flies over the target road; the data collector is used to connect with the infrared camera through the wireless communication module, and transmit the infrared thermal imaging of the road surface to the data processing module; the data processing module is used to generate a road surface temperature distribution map of the target road according to the infrared thermal imaging of the road surface, and judge whether there is an abnormal temperature area on the target road according to the road surface temperature distribution map, and the abnormal temperature area is used to indicate that the target road has collapsed. The present invention can realize efficient and accurate detection of road collapse changes, and overcome the problems of large human resource requirements, low efficiency and unreliable accuracy of traditional methods.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a road change detection system. Background Art

[0002] Roads undergo many changes during use, including road collapse, cracks and fissures, potholes, fading and unclear road markings, and damage to ancillary facilities. These changes may affect the safety, durability, and driving comfort of the road. Among them, road collapse is the biggest risk to traffic safety.

[0003] Traditional methods of detecting whether there are changes in road pavement collapse usually rely on manual inspections, using simple tools such as geological radar or ground penetrating radar (GPR) to detect underground cavities and moisture accumulation, combined with physical inspections of the road surface, such as observing visible signs such as cracks and uneven settlement, and regular maintenance records to assess road conditions.

[0004] However, this method requires a lot of human resources, has low efficiency, and its detection accuracy is unreliable. Summary of the invention

[0005] In view of the above-mentioned technical problems and defects, the purpose of the present invention is to provide a road change detection system that can realize efficient and accurate detection of road collapse changes, overcoming the problems of large human resource requirements, low efficiency and unreliable accuracy of traditional manual patrol detection methods.

[0006] To achieve the above-mentioned purpose, the present invention provides a road change detection system, comprising an unmanned aerial vehicle, an infrared camera, a wireless communication module, a data collector and a data processing module; the infrared camera is installed on the unmanned aerial vehicle, and is used to obtain infrared thermal imaging of the road surface of the target road when the unmanned aerial vehicle flies over the target road; the data collector is used to connect to the infrared camera through the wireless communication module, and transmit the infrared thermal imaging of the road surface to the data processing module; the data processing module is used to generate a road surface temperature distribution map of the target road according to the infrared thermal imaging of the road surface, and determine whether there is a temperature abnormality area on the target road according to the road surface temperature distribution map, and the temperature abnormality area is used to infer the possibility of the existence of underground cavities on the target road, indicating that the target road has collapsed.

[0007] The present invention utilizes a drone equipped with an infrared camera, which can flexibly fly over the target road, quickly cover a large area, improve detection efficiency, and overcome the limitations of traditional manual detection. The infrared thermal imaging of the road surface obtained by the infrared camera can accurately reflect the temperature distribution of the road. By judging the temperature abnormality area, it can effectively detect the possible existence of cavities in the road and the risk of collapse. The cooperation of the data collector and the data processing module ensures the accurate transmission and efficient analysis of data, and timely generates the road surface temperature distribution map to provide a scientific basis for the road management department. This detection method has high accuracy and reliability, and can timely discover hidden dangers in the early stage of abnormal changes in the road, avoid potential safety accidents, ensure the safe passage of pedestrians and vehicles, reduce road maintenance costs, and improve the service life and service quality of the road.

[0008] In some embodiments, the system also includes a laser scanning module, which is installed on the drone and connected to the data collector through the wireless communication module. The laser scanning module is used to obtain three-dimensional road surface data of the target road. The data processing module is also used to determine whether the target road has collapsed based on the three-dimensional road surface data.

[0009] By adopting the technical solution of the above embodiment and adding a laser scanning module, the three-dimensional data of the road surface of the target road can be obtained. This allows the data processing module to determine whether the road has collapsed from the perspective of three-dimensional space. Compared with relying solely on infrared thermal imaging, there is an additional detection method, which improves the accuracy and reliability of the detection. The actual condition of the road can be more comprehensively grasped, providing a more accurate basis for timely maintenance measures, effectively preventing safety hazards caused by problems such as road collapse, and ensuring the safety of pedestrians and vehicles.

[0010] In some embodiments, the data processing module is specifically used to generate a current three-dimensional point cloud model of the target road based on the three-dimensional road surface data, and compare the current three-dimensional point cloud model with the historical three-dimensional point cloud model of the target road to determine whether the target road has collapsed.

[0011] By adopting the technical solution of the above embodiment, the data processing module generates the current 3D point cloud model based on the 3D road surface data and compares it with the historical model, which can intuitively discover the subtle changes in the road morphology. This method can accurately locate areas where collapse may occur and warn of potential risks in advance. At the same time, by comparing models from different periods, it is helpful to analyze the trend of road changes, provide data support for long-term road maintenance planning, and improve the scientificity and foresight of road management.

[0012] In some embodiments, the system also includes a camera module, which is arranged on the drone and connected to the data collector through the wireless communication module, and is used to capture the road surface image of the target road. The data processing module is used to determine whether there are potholes or cracks on the target road based on the road surface image.

[0013] By adopting the technical solution of the above embodiment, the camera module captures the road surface image, which provides an intuitive visual basis for judging the road condition. It can timely detect surface damage such as potholes and cracks to prevent these problems from further deteriorating and affecting road safety. It can also help road management departments quickly determine maintenance priorities, reasonably allocate resources, improve maintenance efficiency, ensure the smoothness and smoothness of the road, and improve driving comfort.

[0014] In some embodiments, the data processing module is further specifically used to determine whether the road traffic markings of the target road are clear based on the road image.

[0015] Adopting the technical solution of the above embodiment, judging whether the traffic markings are clear based on the road surface image is crucial to regulating traffic order. Clear traffic markings can guide vehicles and pedestrians to drive correctly and reduce the occurrence of traffic accidents. This function enables road management departments to promptly detect problems such as blurred markings and repair them, improve road safety and traffic efficiency, and provide a good road environment for traffic participants.

[0016] In some embodiments, the data processing module is further specifically used to determine whether the ancillary facilities of the target road are damaged based on the road surface image.

[0017] Adopting the technical solution of the above embodiment to determine whether the target road ancillary facilities are damaged helps to ensure the normal function of the ancillary facilities. Timely repair of damaged ancillary facilities can improve the overall service level of the road, such as ensuring normal lighting of street lamps to improve nighttime driving safety, repairing guardrails to prevent vehicles from running off the road, etc. At the same time, it can also extend the service life of the ancillary facilities and reduce maintenance costs.

[0018] In some embodiments, the system further includes a storage module connected to the data processing module.

[0019] With the technical solution of the above embodiment, the existence of the storage module provides the system with a data storage function. Various test data and analysis results can be saved, making it convenient to check historical data for comparative analysis at any time. This is of great significance for tracking the changing trend of road conditions, evaluating the effectiveness of maintenance measures, and providing reference for future road planning. In addition, the storage module can also ensure the security and traceability of data, and improve the stability and reliability of the system.

[0020] In some embodiments, the system further includes a display, which is connected to the data processing module and is used to display the infrared thermal imaging of the road surface or the three-dimensional road surface data of the target road.

[0021] By adopting the technical solution of the above embodiment, the display shows the infrared thermal imaging of the road surface or the three-dimensional data of the road surface, making the detection results more intuitive. The staff can quickly understand the temperature distribution and morphological changes of the road through the display without complicated data interpretation. This helps to improve work efficiency, find problems in time and take corresponding measures. At the same time, the intuitive display also makes it convenient to show the road conditions to relevant departments and the public, and enhance the transparency of road management.

[0022] In some embodiments, the system further includes a road management terminal, and the data processing module is used to send warning information to the road management terminal when it is determined that the target road has undergone a collapse change.

[0023] By adopting the technical solution of the above embodiment, when the data processing module determines that the target road has collapsed, it sends warning information to the road management end, which can achieve real-time warning. The road management department can respond quickly, arrange personnel to conduct on-site inspections and take emergency measures, such as setting up warning signs, blocking dangerous areas, etc., to prevent accidents. This greatly improves the timeliness and pertinence of road maintenance and protects the safety of people's lives and property.

[0024] In some embodiments, the data collector is also used to encrypt the infrared thermal imaging of the road surface or the three-dimensional data of the road surface of the target road.

[0025] By adopting the technical solution of the above embodiment, the data collector encrypts the road infrared thermal imaging or road three-dimensional data to ensure the security of data transmission. During the data transmission process, the data is prevented from being illegally stolen, tampered with or destroyed, ensuring the authenticity and integrity of the data. This is crucial for the stable operation of the road change detection system and the accuracy of road management decisions, and improves the reliability and trust of the system.

[0026] One or more technical solutions provided by the present invention have at least the following technical effects or advantages:

[0027] 1. Comprehensive and accurate detection of changes in road conditions: The present invention uses a variety of advanced technologies to achieve comprehensive and accurate detection of changes in road conditions. The drone is equipped with an infrared camera, a laser scanning module, and a camera module to obtain infrared thermal imaging of the road surface, three-dimensional data of the road surface, and road surface images, respectively. By analyzing these multi-dimensional data, the data processing module can accurately determine whether there are collapse changes, potholes or cracks on the road, whether the traffic markings are clear, and whether the ancillary facilities are damaged. For example, infrared thermal imaging of the road surface can detect areas with abnormal temperatures, suggesting that there may be potential collapse factors such as underground cavities; comparison of three-dimensional data of the road surface can intuitively reflect changes in road morphology and further confirm collapse conditions; and road surface images can clearly show specific problems on the road surface. This comprehensive and accurate detection method provides road management departments with detailed and accurate road condition information, which helps to take targeted maintenance measures in a timely manner to ensure the safety and normal use of roads.

[0028] 2. Real-time warning improves safety: When the data processing module determines that the target road has problems such as collapse, it will immediately send warning information to the road management end. This function greatly improves the safety of the road. The road management department can learn about the road problems at the first time, quickly arrange personnel to go to the site for inspection and evaluation, set up warning signs, block dangerous areas, prevent vehicles and pedestrians from entering by mistake, and avoid possible safety accidents. At the same time, a reasonable repair plan is formulated based on the warning information, and a construction team is organized to carry out emergency repairs to ensure that the road can resume normal traffic as soon as possible. The real-time warning mechanism makes road management more efficient and timely, effectively reduces road safety risks, and provides strong protection for the safety of life and property of the public.

[0029] 3. Data management and visualization improve efficiency: The storage module can save various test data and analysis results, which is convenient for road management departments to query and compare and analyze. This provides a historical basis for the long-term maintenance and management of roads, helps to track the changing trends of road conditions, and evaluate the effectiveness of maintenance measures. The setting of the display makes the test results more intuitive. The staff does not need to perform complex data interpretation. They can quickly obtain key information on road conditions by observing the images and models on the display. This data management and visualization method improves work efficiency and makes road management more scientific and efficient. At the same time, the data collector encrypts the data to ensure the security and reliability of data transmission, prevents data from being tampered with or stolen, and further enhances the stability and trust of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings herein are incorporated into and constitute a part of the specification, showing embodiments consistent with the present invention, and together with the specification, are used to explain the principles of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0031] Figure 1 is a schematic diagram of the architecture of a road change detection system according to an embodiment of the present invention;

[0032] Figure 2 is a schematic diagram of an application scenario of a road change detection system according to an embodiment of the present invention;

[0033] Figure 3 2 is a schematic diagram of the architecture of another road change detection system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The terms used in the following embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to be limiting of the present invention. As used in the specification of the present invention, the singular expressions "a", "a", "above", "the" and "this" are intended to also include plural expressions, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present invention refers to any or all possible combinations comprising one or more of the listed items.

[0035] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood as implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present invention, unless otherwise specified, the meaning of "plurality" is two or more.

[0036] It should also be noted that, unless otherwise clearly specified and limited, in the embodiments of the present invention, the terms such as "setting" and "connection" should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two components; it can be a wired communication connection or a wireless communication connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. The embodiments of the present invention are described in detail below.

[0037] The embodiment of the present invention provides a road change detection system, such as Figure 1 and 2As shown, it includes a drone 1, an infrared camera 2, a wireless communication module 3, a data collector 4 and a data processing module 5; the infrared camera 2 is installed on the drone 1, and is used to obtain the infrared thermal imaging of the road surface of the target road when the drone 1 flies over the target road; the data collector 4 is used to connect with the infrared camera 2 through the wireless communication module 3, and transmit the infrared thermal imaging of the road surface to the data processing module 5; the data processing module 5 is used to generate a road surface temperature distribution map of the target road according to the infrared thermal imaging of the road surface, and determine whether there is an abnormal temperature area in the target road according to the road surface temperature distribution map, and the abnormal temperature area is used to infer the possibility of the existence of underground cavities in the target road, indicating that the target road has collapsed.

[0038] In this embodiment, the infrared camera 2 mounted on the drone 1 obtains infrared thermal imaging of the road surface, and transmits the data to the data collector 4 through the wireless communication module 3. Finally, the data processing module 5 analyzes and generates a temperature distribution map to accurately identify the temperature abnormality area. This temperature anomaly represents the possibility of underground cavities under the road, which is a manifestation of road collapse changes. Therefore, this system can timely warn of potential collapse risks, provide key information for road maintenance and safety management, effectively prevent road collapse accidents, ensure driving safety, reduce economic losses, and improve the efficiency and pertinence of road maintenance. The implementation of this system has improved the intelligent level of road safety monitoring, which is of great practical significance for maintaining the stability and safety of transportation infrastructure.

[0039] In this embodiment, the infrared camera 2 uses infrared technology to capture infrared thermal images of the road surface of the target road, and provides the system with intuitive data on the health of the road by detecting subtle changes in the road surface temperature. Such data is crucial for identifying areas with abnormal temperatures, as these areas may indicate the presence of underground cavities under the road, indicating potential collapse risks.

[0040] The data collector 4 is connected to the infrared camera 2 through the wireless communication module 3, receives the road surface infrared thermal imaging data from the infrared camera 2 in real time, and transmits it to the data processing module 5. The efficient operation of the data collector 4 ensures the accuracy and real-time nature of the data, and provides reliable data support for the subsequent generation of temperature distribution maps and judgment of abnormal areas.

[0041] The wireless communication module 3 is a bridge connecting the infrared camera 2 and the data collector 4. It uses advanced wireless transmission technology, such as Wi-Fi, 4G / 5G or a dedicated wireless communication protocol, to ensure high-speed and stable data transmission between the UAV 1 and the ground station. This module may include a wireless transmitter and a receiver, which can maintain a stable data flow during the flight of the UAV 1, and maintain the continuity and reliability of communication even in complex urban environments or severe weather conditions. The design of the wireless communication module 3 takes into account anti-interference and data encryption to protect the security and integrity of data during transmission.

[0042] The data processing module 5 is the hardware core of the system, which is usually composed of high-performance computing devices, such as industrial-grade servers or dedicated data processing computers. These devices are equipped with processors (CPUs) and graphics processing units (GPUs) with sufficient computing power, which can quickly process and analyze a large amount of infrared thermal imaging data transmitted from the infrared camera 2. The data processing module 5 may also include some software algorithms, such as machine learning and deep learning models, for identifying and analyzing abnormal patterns in the road surface temperature distribution map, so as to determine whether there is a risk of collapse of the road.

[0043] In some embodiments, Figure 3 As shown, the system also includes a laser scanning module 6, which is installed on the drone 1 and connected to the data collector 4 through the wireless communication module 3. The laser scanning module 6 is used to obtain the three-dimensional road surface data of the target road. The data processing module 5 is also used to determine whether the target road has collapsed according to the three-dimensional road surface data.

[0044] This embodiment further integrates a laser scanning module 6, which is also installed on the drone 1 and works in conjunction with the wireless communication module 3 to achieve wireless connection with the data collector 4. The main function of the laser scanning module 6 is to obtain the three-dimensional road surface data of the target road, and accurately measure the ups and downs and shape changes of the road surface by emitting laser pulses and measuring the time it takes for them to reflect back. These three-dimensional data provide additional and more accurate spatial information for the data processing module 5, so that the system can not only detect temperature abnormalities through infrared thermal imaging, but also further determine whether the road has collapsed by analyzing the three-dimensional structural changes of the road surface.

[0045] The data processing module 5 uses infrared thermal imaging and 3D laser scanning data to conduct a comprehensive analysis of the physical state of the road surface, thereby more accurately identifying potential collapse areas and providing more comprehensive and accurate data support for road change detection and safety management. This multi-modal detection method combining infrared thermal imaging and 3D laser scanning greatly improves the accuracy and reliability of road change detection, which is of great significance for preventing road collapse accidents and protecting people's lives and property.

[0046] In some embodiments, the data processing module 5 is specifically used to generate a current three-dimensional point cloud model of the target road based on the three-dimensional road surface data, and compare the current three-dimensional point cloud model with the historical three-dimensional point cloud model of the target road to determine whether the target road has collapsed.

[0047] Specifically, the data processing module 5 first generates a current three-dimensional point cloud model of the target road using the precise measurement data obtained by the laser scanning module 6. The point cloud model is a three-dimensional spatial data composed of a large number of points, which can describe the geometric shape and spatial position of the road surface in detail. Then, the data processing module 5 compares and analyzes the current three-dimensional point cloud model with the historical three-dimensional point cloud model of the target road stored previously.

[0048] By comparing the three-dimensional data at two points in time, the data processing module 5 is able to identify any significant changes in the road surface, such as subsidence, bulge or other structural deformations, which are potential signs of road collapse.

[0049] This comparative analysis can reveal the evolution of road structure over time and provide strong data support for determining whether the road has collapsed. Through this high-precision three-dimensional data comparison, the data processing module 5 can accurately detect and warn of road collapse risks, thereby providing a scientific and timely decision-making basis for road maintenance and safety management.

[0050] In some embodiments, the data processing module 5 can also determine whether there is an abnormal temperature area on the target road based on the road surface temperature distribution map, and obtain a first collapse change confidence level; then the data processing module 5 determines whether the target road has a collapse change based on the three-dimensional road surface data, and obtains a second collapse change confidence level; finally, based on these two collapse change confidence levels, it is finally determined whether there is a collapse change on the target road.

[0051] Specifically, first, the data processing module 5 will set certain temperature anomaly standards. For example, an area whose temperature difference with the surrounding area exceeds a certain threshold is regarded as a temperature anomaly area. These temperature anomaly areas may indicate the existence of potential collapse factors such as underground cavities under the road. Then, a comprehensive evaluation is performed based on multiple factors such as the size, number, and degree of temperature difference of the temperature anomaly areas. If the temperature anomaly areas are large, the number is large, and the temperature difference is obvious, then the possibility of road collapse is relatively high, and the first collapse change confidence will increase accordingly; conversely, if the temperature anomaly areas are small, the number is small, and the temperature difference is not significant, then the first collapse change confidence will decrease. In this way, the data processing module 5 can derive a first collapse change confidence that reflects the possibility of collapse change of the target road based on the road surface temperature distribution map.

[0052] On the other hand, after receiving the three-dimensional road surface data, the data processing module 5 generates the current three-dimensional point cloud model of the target road based on these data. The data processing module 5 will retrieve the historical three-dimensional point cloud model of the target road and compare the current three-dimensional point cloud model with the historical three-dimensional point cloud model. During the comparison process, the main focus is on changes in the height, slope, flatness, etc. of the road. If it is found that the current model has a significant drop in height, a change in slope, or a deterioration in flatness compared to the historical model, it means that the road may have collapsed. Then, the data processing module 5 will perform a quantitative assessment based on the degree of change. For example, the greater the height drop, the more obvious the slope change, and the more serious the deterioration in flatness, the higher the possibility of collapse, and the second collapse change confidence will be correspondingly increased; conversely, if the change is small, then the second collapse change confidence will be reduced. In this way, the data processing module 5 can derive a second collapse change confidence that reflects the possibility of collapse of the target road based on the three-dimensional road surface data.

[0053] After obtaining the first collapse change confidence (based on the road surface temperature distribution map) and the second collapse change confidence (based on the road surface three-dimensional data), the data processing module 5 will combine the two confidences to finally determine whether the target road has a collapse change. The specific process is as follows:

[0054] First, different initial weights are assigned to the two confidence levels. Let the first collapse change confidence level be C1 and the initial weight be W1; let the second collapse change confidence level be C2 and the initial weight be W2. At the same time, a dynamic adjustment factor F is introduced. The value of F depends on the degree of difference between the two confidence levels (C1 and C2) and some specific attributes of the target road, such as the age of the road and the complexity of geological conditions. Specifically, the degree of difference D = |C1- C2| is calculated. If the value of D is large, it means that the two confidence levels are obviously different. At this time, the value of F will be reduced accordingly to reduce the influence of the confidence level with a large difference in the final calculation; if the difference is small, it means that the two confidence levels are relatively consistent, and the value of F will be appropriately increased to strengthen the joint effect of the two confidence levels.

[0055] Then, the comprehensive confidence is calculated using the following formula: Next, the two confidences are substituted into the comprehensive evaluation formula to calculate the comprehensive confidence. The comprehensive evaluation formula includes:

[0056] ;

[0057] in, Indicates that the dynamic adjustment factor F is exponentially calculated according to the square root of the difference degree D, so that the comprehensive confidence can be adjusted more delicately. If the difference between the first collapse change confidence and the second collapse change confidence is small, the square root value is also small, and the exponential operation has little effect on F. The comprehensive confidence is mainly determined by the initial weight and the values ​​of the two confidences; if the difference is large, the square root value is large, and the exponential operation will significantly reduce the value of F, thereby reducing the role of the confidence with large differences in the comprehensive calculation.

[0058] Finally, a comprehensive confidence threshold T is set. If the calculated comprehensive confidence C exceeds this threshold T, then it is judged that the target road has collapsed; if C is lower than this threshold, then it is judged that the target road does not have collapsed. At the same time, during the entire calculation process, the weights and thresholds can be dynamically adjusted according to new detection data and actual conditions to improve the accuracy and adaptability of the judgment.

[0059] In some embodiments, the system also includes a camera module 7, which is installed on the drone 1 and connected to the data collector 4 via the wireless communication module 3, and is used to capture the road surface image of the target road. The data processing module 5 is used to determine whether there are potholes or cracks on the target road based on the road surface image.

[0060] The camera module 7 is arranged on the drone 1, and can take comprehensive photos of the road surface of the target road from different angles and heights by means of the flexible flight capability of the drone 1. Through the wireless communication module 3, the camera module 7 can transmit the photographed road surface image to the data collector 4 in real time, and then the data collector 4 transmits the image data to the data processing module 5.

[0061] After receiving the road surface image, the data processing module 5 processes it using known image analysis techniques. First, the data processing module 5 preprocesses the image, including operations such as denoising and contrast enhancement, to improve the quality and clarity of the image. Then, through the feature extraction algorithm, various features in the road surface image, such as color, texture, shape, etc., are identified. For the judgment of potholes and cracks, the data processing module 5 will analyze the typical features of potholes and cracks in the image. For example, potholes usually appear as sunken areas on the road surface, the color may be different from the surrounding road surface, and the edges are more obvious; cracks appear as long and thin lines, which may have a specific direction and width.

[0062] The data processing module 5 will establish a judgment model based on these features, and determine whether there are potholes or cracks on the target road by comparing the features in the image with the known pothole and crack feature patterns. If the features in the image have a high degree of match with the feature patterns of potholes or cracks, then it can be determined that the target road has corresponding problems. This pothole and crack detection method based on road surface images can timely discover the damage of the road surface and provide an important basis for road maintenance and management.

[0063] In some embodiments, the data processing module 5 is further specifically configured to determine whether the road traffic markings of the target road are clear based on the road image.

[0064] Specifically, when the camera module 7 transmits the road image to the data collector 4 through the wireless communication module 3 and then reaches the data processing module 5, the data processing module 5 will first perform a series of pre-processing operations on the image, including adjusting the brightness, contrast and color balance of the image to optimize the image quality and make the traffic markings more prominent in the image.

[0065] Next, the data processing module 5 uses image recognition technology to analyze the characteristics of traffic markings. Traffic markings usually have specific features such as shape, color and width. For example, a white solid line is usually a continuous long strip with high brightness and a specific width range. Based on these features, the data processing module 5 searches and identifies the position and shape of traffic markings in the image.

[0066] Then, by comparing with the known clear traffic marking standards, the data processing module 5 evaluates the clarity of the traffic markings in the image. If the edges of the traffic markings are clear, the colors are bright, they are continuous, and the width meets the standards, then the traffic markings can be judged to be clear. On the contrary, if the traffic markings are blurred, the colors are dim, there are gaps, or the width is abnormal, it means that the traffic markings are not clear.

[0067] This method of judging the clarity of traffic markings through road surface images can promptly detect the wear and unclearness of traffic markings, provide an important reference for road traffic safety management, ensure that drivers can accurately identify road signs, and improve road driving safety.

[0068] In some embodiments, the data processing module 5 is further specifically used to determine whether the ancillary facilities of the target road are damaged based on the road surface image.

[0069] Among them, ancillary facilities include street lights, guardrails, traffic signs, drainage facilities, etc.

[0070] In this embodiment, when the road surface image is transmitted from the camera module 7 to the data collector 4 via the wireless communication module 3 and then reaches the data processing module 5, the data processing module 5 first performs detailed preprocessing on the image, including removing noise from the image, enhancing the contrast and sharpness of the image, etc., so as to present the details of the auxiliary facilities more clearly.

[0071] Next, the data processing module 5 uses a known image recognition algorithm to analyze the features of the ancillary facilities of the target road. Different ancillary facilities have their own unique features such as shape, color and texture. For example, road guardrails are usually long strips with specific colors and textures, and traffic signs have specific shapes and patterns. The data processing module 5 will locate and identify the position and form of the ancillary facilities in the image based on these features.

[0072] Then, by comparing with the standard features of the auxiliary facilities in the normal state, the data processing module 5 evaluates the condition of the auxiliary facilities in the image. If the auxiliary facilities are deformed, broken, rusted, severely faded or missing, it can be determined that the auxiliary facilities are damaged. For example, if the road guardrail is bent, deformed or broken, and the traffic signs are damaged, blurred or tilted, it indicates that the auxiliary facilities are damaged.

[0073] This method of judging the damage of ancillary facilities through road surface images can timely discover problems with road ancillary facilities, provide an important basis for road maintenance and management, ensure that the ancillary facilities can perform their functions normally, and ensure the safety and smoothness of the road.

[0074] In some embodiments, the system further includes a storage module 8 , which is connected to the data processing module 5 .

[0075] The storage module 8 provides the data storage function for the whole system. When various detection devices on the drone 1, such as the infrared camera 2, the laser scanning module 6 and the camera module 7, obtain the relevant data of the target road, the data collector 4 transmits the data to the data processing module 5 for analysis and processing. At the same time, the processed result data and the original collected data will also be saved by the storage module 8.

[0076] The storage module 8 can store various types of data such as road infrared thermal imaging, road three-dimensional data and road images. For road infrared thermal imaging data, the storage module 8 can record the temperature distribution of the target road at different time points, so as to conduct subsequent comparative analysis to determine whether there are abnormal temperature changes and possible collapse risks on the road. The storage of road three-dimensional data provides a historical basis for analyzing the morphological changes of the road. By comparing the three-dimensional point cloud models of different periods, it is possible to more accurately detect whether the road has collapsed. The storage of road images can not only be used to determine whether there are potholes, cracks and damage to ancillary facilities on the road, but also can be used as intuitive evidence to facilitate road management departments to conduct problem investigation and maintenance decisions.

[0077] In addition, the storage module 8 can also store various analysis results generated by the data processing module 5, such as the confidence of collapse change, the judgment result of traffic marking clarity, and the judgment of the damage of auxiliary facilities. These result data can provide detailed road condition information for road management departments, helping them to formulate reasonable maintenance plans and resource allocation plans. The existence of the storage module 8 ensures the security and traceability of system data, and provides a solid foundation for the continuous operation and continuous optimization of the road change detection system.

[0078] In some embodiments, the system further includes a display 9, which is connected to the data processing module 5 and is used to display infrared thermal imaging of the road surface or three-dimensional road surface data of the target road.

[0079] Among them, the display 9 can intuitively display the infrared thermal imaging of the road surface or the three-dimensional data of the road surface of the target road, which provides great convenience for road detection and management.

[0080] When the data processing module 5 receives the infrared thermal imaging data of the road surface collected by the infrared camera 2 on the drone 1, it will process and analyze the data to generate a road surface temperature distribution map. At this time, the display 9 can present the infrared thermal imaging of the road surface in the form of a clear image, so that the staff can intuitively observe the temperature distribution of different areas of the road. Through the thermal imaging image on the display 9, the temperature abnormal area can be identified at a glance, which provides an important visual basis for judging whether there is a collapse change on the road.

[0081] At the same time, the data processing module 5 processes the three-dimensional road surface data of the target road obtained by the laser scanning module 6 and generates visualization results such as a three-dimensional point cloud model. The display 9 can display these three-dimensional road surface data in a three-dimensional and realistic form, allowing the staff to observe the shape and structure of the road from different angles. This display method helps to more accurately determine whether the road has collapsed and has a more comprehensive understanding of the overall condition of the road.

[0082] The presence of the display 9 makes the road detection process more intuitive and efficient. The staff does not need to interpret complicated data, but can quickly obtain key information on road conditions by simply observing the images and models on the display 9, so as to take corresponding maintenance and management measures in time to ensure the safety and smoothness of the road.

[0083] In some embodiments, the system further includes a road management terminal 10, and the data processing module 5 is used to send warning information to the road management terminal 10 when it is determined that a collapse change occurs on the target road.

[0084] Among them, the road management terminal 10 is a terminal platform for receiving warning information about road collapse changes and other problems sent by the data processing module 5. It is used by the road management department to arrange inspections, maintenance and other measures in a timely manner to ensure road safety and normal use.

[0085] When the data processing module 5 determines that the target road has collapsed after analyzing various data, it will immediately send an early warning message to the road management terminal 10.

[0086] Once the data processing module 5 determines that the target road has a collapse risk by combining the first collapse change confidence obtained by the road surface temperature distribution map and the second collapse change confidence obtained by the road surface three-dimensional data, it will quickly start the early warning mechanism. The early warning information containing detailed information is sent to the road management terminal 10 through network communication and other means. The early warning information may include key contents such as the location of the collapse, possible severity, and analysis results of related data.

[0087] After the road management terminal 10 receives the warning information, the management personnel can take timely actions. They can quickly arrange personnel to go to the site for inspection and assessment, set up warning signs, and block dangerous areas to prevent vehicles and pedestrians from entering by mistake and avoid possible safety accidents. At the same time, according to the specific situation in the warning information, a reasonable repair plan is formulated, and a construction team is organized to carry out emergency repairs to ensure that the road can be restored to normal use as soon as possible.

[0088] Through the linkage between the data processing module 5 and the road management terminal 10, a response can be made immediately when a road collapse occurs, which greatly improves the efficiency and timeliness of road safety management and plays an important role in protecting the safety of public life and property and the normal passage of roads.

[0089] In some embodiments, the data collector 4 is also used to encrypt the road surface infrared thermal imaging or the three-dimensional road surface data of the target road.

[0090] Specifically, when the infrared camera 2 on the drone 1 obtains infrared thermal imaging data of the road surface, and the laser scanning module 6 obtains three-dimensional data of the road surface, these data will first be transmitted to the data collector 4. While receiving these data, the data collector 4 will start the encryption program.

[0091] The encryption process is designed to protect the security and integrity of the data. By using advanced encryption algorithms to encode and convert data, unauthorized personnel cannot easily obtain and interpret the data. This can prevent the data from being maliciously stolen, tampered with or destroyed during transmission. When the encrypted road infrared thermal imaging and road three-dimensional data are transmitted to the data processing module 5 through the wireless communication module 3, even if they are intercepted, they are difficult to crack, thereby ensuring the confidentiality of the data.

[0092] This encryption processing is crucial for the road change detection system. On the one hand, road infrared thermal imaging and road 3D data contain key information about road conditions, which is crucial for road safety assessment and maintenance decisions. If this data is leaked or tampered with, it may lead to wrong judgments and decisions, affecting the safety and normal use of the road. On the other hand, encryption processing also meets the requirements of modern data security management, protects the data rights and interests of road management departments and related stakeholders, and enhances the reliability and trust of the entire system.

[0093] The road change detection system of this embodiment is an efficient detection solution integrating multiple advanced technologies. The system mainly consists of a drone 1, an infrared camera 2, a laser scanning module 6, a camera module 7, a wireless communication module 3, a data collector 4, a data processing module 5, a storage module 8, a display 9 and a road management terminal 10.

[0094] As a platform for carrying detection equipment, drone 1 flies flexibly over the target road. Infrared camera 2 obtains infrared thermal imaging of the road surface, which is received by data collector 4 and transmitted to data processing module 5 to generate a road surface temperature distribution map to determine whether there is an abnormal temperature area, and then infer whether the road has collapsed. At the same time, laser scanning module 6 obtains three-dimensional data of the road surface, and data processing module 5 generates a current three-dimensional point cloud model and compares it with the historical model to obtain another confidence level about the collapse change. The comprehensive judgment of the two confidence levels improves the accuracy of collapse detection.

[0095] The camera module 7 takes images of the road surface, and the data processing module 5 can use this to determine whether there are potholes or cracks on the road, whether the traffic markings are clear, and whether the auxiliary facilities are damaged. The data collector 4 also encrypts the road surface infrared thermal imaging and road surface three-dimensional data to ensure safe data transmission. The storage module 8 is connected to the data processing module 5 to save various data and analysis results for subsequent query and comparison. The display 9 displays the road surface infrared thermal imaging or road surface three-dimensional data to make the detection results more intuitive. When the data processing module 5 determines that the road has collapsed, it will send an early warning message to the road management terminal 10 so that timely measures can be taken for maintenance and management.

[0096] In short, the system provides a comprehensive, efficient and accurate solution for road detection and management through functions such as multimodal detection, data encryption, visual display and real-time warning.

[0097] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A road change detection system, characterized in that: It includes a drone, an infrared camera, a wireless communication module, a data collector and a data processing module; The infrared camera is installed on the drone and is used to obtain infrared thermal imaging of the road surface of the target road when the drone flies over the target road; The data collector is used to connect to the infrared camera through the wireless communication module and transmit the road surface infrared thermal image to the data processing module; The data processing module is used to generate a road surface temperature distribution map of the target road according to the road surface infrared thermal imaging, and to determine whether there is a temperature abnormality area on the target road according to the road surface temperature distribution map, and to obtain a first collapse change confidence level, wherein the temperature abnormality area is used to infer the possibility of the existence of an underground cavity on the target road, indicating that a collapse change has occurred on the target road; The system further comprises a laser scanning module, which is mounted on the UAV and connected to the data collector via the wireless communication module. The laser scanning module is used to obtain the three-dimensional road surface data of the target road. The data processing module is also used to determine whether the target road has collapsed according to the three-dimensional road surface data, and to obtain a second collapse change confidence level. The data processing module is further used to calculate a comprehensive confidence by a comprehensive evaluation formula based on the first collapse change confidence and the second collapse change confidence, so as to determine whether the target road has a collapse change; The comprehensive evaluation formula includes: Wherein, C is the comprehensive confidence, C1 is the first collapse change confidence, C2 is the second collapse change confidence, W1 and W2 are initial weights, and F is a dynamic adjustment factor, which is determined based on the difference between C1 and C2, the age of the road, and the complexity of the geological conditions; if the comprehensive confidence C exceeds the set threshold T, it is determined that the target road has a collapse change; The system also includes a camera module, which is arranged on the drone and connected to the data collector via the wireless communication module, and is used to capture a road surface image of the target road. The data processing module is also used to determine whether there are potholes or cracks on the target road based on the road surface image.

2. The system according to claim 1, characterized in that The data processing module is specifically used to generate a current three-dimensional point cloud model of the target road based on the three-dimensional road surface data, and compare the current three-dimensional point cloud model with the historical three-dimensional point cloud model of the target road to determine whether the target road has collapsed.

3. The system according to claim 1, characterized in that The data processing module is also specifically used to determine whether the road traffic markings of the target road are clear according to the road image.

4. The system according to claim 1, characterized in that The data processing module is also specifically used to determine whether the auxiliary facilities of the target road are damaged according to the road surface image.

5. The system according to claim 1, characterized in that It also includes a storage module, which is connected to the data processing module.

6. The system according to claim 1, characterized in that It also includes a display, which is connected to the data processing module and is used to display the road surface infrared thermal imaging or the three-dimensional road surface data of the target road.

7. The system according to claim 1, characterized in that It also includes a road management terminal, and the data processing module is used to send early warning information to the road management terminal when it is determined that the target road has collapsed.

8. The system according to claim 1, characterized in that The data collector is also used to encrypt the road surface infrared thermal imaging or the three-dimensional road surface data of the target road.

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