A remote monitoring method, device and medium for intelligent guardrail based on the Internet of Things

Abstract

The present invention discloses a remote monitoring method, device, and medium for intelligent guardrails based on the Internet of Things. The method belongs to the field of smart guardrail technology and is used to solve the technical problems that the existing abnormal monitoring of highway guardrails is difficult, the abnormal conditions of the guardrails cannot be grasped in time, and it is difficult to promptly alert subsequent vehicles, which easily causes secondary safety accidents and is not conducive to safe traffic management. The method includes: dividing the highway network in the target highway area into sections, and deploying preset guardrail sensors in the highway guardrail section of the highway network section; through the guardrail management platform, monitoring and processing the data related to the position, time, and frequency of the vibration abnormal data in the abnormal data to obtain the first warning information; performing spatiotemporal comparison processing on the tilt abnormal data in the abnormal data to determine the second warning information; and performing guardrail abnormal pattern recognition on the displacement abnormal data in the abnormal data to determine the third warning information.

Description

Technical Field

[0001] The present application relates to the field of smart guardrails, and in particular to a remote monitoring method, device and medium for smart guardrails based on the Internet of Things. Background Art

[0002] Guardrails are the most basic traffic protection facilities on highways and urban roads, playing a vital role in traffic prevention. During traffic accidents, guardrail collisions are common, as drivers can easily lose control and collide with guardrails due to fatigue, speeding, or unexpected circumstances.

[0003] If an abnormality occurs with a highway guardrail, it can lead to a secondary accident or disrupt traffic flow if not addressed promptly. Traditional guardrails suffer from a problem where an abnormality is not immediately detected or addressed. Furthermore, automated intelligent monitoring and abnormality warnings for the guardrail are difficult to implement. When an abnormality occurs, there's no way to quickly respond and alert following vehicles to potential safety hazards. This compromises highway safety, easily leading to secondary accidents and significantly impacting highway safety management capabilities. Summary of the Invention

[0004] The embodiments of the present application provide a remote monitoring method, device and medium for intelligent guardrails based on the Internet of Things, which are used to solve the following technical problems: the existing abnormal monitoring of highway guardrails is relatively difficult, and it is impossible to grasp the abnormal conditions of the guardrails in a timely manner, and it is difficult to promptly remind subsequent vehicles, which can easily cause secondary safety accidents and is not conducive to safe traffic management.

[0005] The embodiments of this application adopt the following technical solutions:

[0006] On the one hand, an embodiment of the present application provides a remote monitoring method for an intelligent guardrail based on the Internet of Things, comprising: dividing the highway network in the target highway area into sections, and deploying preset guardrail sensors in the highway guardrail section of the highway network section; wherein the guardrail sensor comprises: a vibration sensor, a tilt sensor, and a displacement sensor; transmitting the abnormal data collected by the guardrail sensor to a guardrail management platform; wherein the abnormal data comprises: vibration abnormal data, tilt abnormal data, and displacement abnormal data; through the guardrail management platform, performing data monitoring and processing on the position, time, and frequency of the vibration abnormal data in the abnormal data to obtain a first warning information; based on the first warning information, performing spatiotemporal comparison processing on the tilt abnormal data in the abnormal data to determine a second warning information; based on the first warning information and the second warning information, performing guardrail abnormal pattern recognition on the displacement abnormal data in the abnormal data to determine a third warning information; generating a guardrail alarm information based on the first warning information, the second warning information, and the third warning information.

[0007] By deploying sensors on highway guardrails, the present embodiment enables real-time monitoring of guardrail vibration, tilt, and displacement, ensuring seamless monitoring of guardrail status. Guardrail anomaly data, including vibration, tilt, and displacement, is collected and analyzed and processed via the guardrail management platform. Simultaneous monitoring of multiple parameters, including vibration, tilt, and displacement, provides a more comprehensive status assessment, helping to more accurately identify potential safety hazards. Through data monitoring and processing, the system generates early warning information, including the location, time, and frequency of vibration anomaly data, improving the timeliness and accuracy of early warnings. Spatiotemporal comparison of tilt anomaly data helps determine the time and spatial range of the anomaly, facilitating rapid location of the problem area. Guardrail anomaly pattern recognition enables in-depth analysis of displacement anomaly data to determine the specific anomaly condition of the guardrail, such as whether it has shifted or displaced. Combining the first, second, and third warning information, the system generates comprehensive guardrail alarm information to provide decision support for maintenance personnel. By promptly identifying guardrail anomalies, preventive measures can be taken to reduce the risk of traffic accidents and improve road safety. Early detection and prevention of guardrail problems can reduce the frequency and cost of emergency maintenance. Automated monitoring and analysis systems can reduce the workload of maintenance personnel and improve the efficiency and accuracy of maintenance work.

[0008] In a feasible embodiment, the expressway network in the target expressway area is divided into sections, and preset guardrail sensors are deployed in the expressway guardrail sections of the expressway network sections, specifically comprising: dividing the expressway network in the target expressway area into sections according to the continuous sections of the expressway guardrails to obtain the expressway network sections; wherein the expressway network sections include the continuous sections of all expressway guardrails in the target expressway area; classifying the expressway network sections according to the relevant interval length parameters to determine normal expressway network sections within the monitoring threshold range and extra-long expressway network sections outside the monitoring threshold range; wherein the monitoring threshold range is the sensing threshold range of the guardrail sensor; based on the monitoring threshold range, segmenting the extra-long expressway network sections according to the relevant interval length parameters to determine segmented expressway network sections; and deploying the guardrail sensors to the normal expressway network sections and the segmented expressway network sections respectively, so that all expressway guardrails in the target expressway area are within the overall controllable monitoring range.

[0009] In a feasible implementation, the abnormal data collected by the guardrail sensor is transmitted to the guardrail management platform, specifically including: collecting the abnormal data and corresponding spatiotemporal data through the guardrail sensor; wherein the spatiotemporal data includes: time node data and geographic location data; based on the time node data and the geographic location data, determining the abnormal high-speed network segment corresponding to the abnormal data; and sending the abnormal data, the spatiotemporal data and the abnormal high-speed network segment to the guardrail management platform through wireless communication technology; wherein the guardrail management platform is a cloud platform and is used for data storage, processing and analysis.

[0010] In a feasible embodiment, the guardrail management platform monitors and processes the position, time and frequency data of the vibration abnormality data in the abnormal data to obtain the first warning information, which specifically includes: classifying and processing the time parameters in several vibration abnormality data according to a preset time interval to determine the continuous time parameter vibration data in the same time interval; dividing the position parameters in several vibration data into high-speed network segments according to the monitoring threshold range to determine the segment position parameter vibration data of the same abnormal high-speed network segment; using the continuous time parameter vibration data and the segment position parameter vibration data as query data, performing a matching query on the abnormal high-speed network segment in the guardrail management platform under the combination of the two to obtain the vibration abnormal guardrail center segment; determining the vibration radiation guardrail associated segment based on the vibration abnormal guardrail center segment; collecting the first vibration frequency of the vibration abnormal guardrail center segment and the second vibration frequency of the vibration radiation guardrail associated segment; generating the first warning information according to the vibration abnormal guardrail center segment, the vibration radiation guardrail associated segment, the first vibration frequency and the second vibration frequency.

[0011] In a feasible implementation manner, according to the first warning information, the tilt abnormality data in the abnormal data is subjected to time-space comparison processing to determine the second warning information, specifically including: if the guardrail management platform recognizes the first warning information, the presence of tilt abnormality data is identified for the vibration abnormal guardrail center section and the vibration radiation guardrail associated section in the first warning information, and the tilt abnormality guardrail section is identified and determined; wherein, the tilt abnormality guardrail section is included in the vibration abnormality guardrail center section and / or the vibration radiation guardrail associated section; according to the first vibration frequency and the second vibration frequency in the first warning information, The time difference of the vibration frequencies between the frequencies is calculated, and based on the first position coordinate of the central section of the vibration abnormal guardrail and the second position coordinate of the associated section of the vibration radiation guardrail, the associated position of the non-tilted abnormal guardrail section of the tilted abnormal guardrail section is estimated to obtain the tilted associated guardrail section; wherein, the non-tilted abnormal guardrail section is an abnormal guardrail section that is associated with the tilted abnormal guardrail section when vibration and / or fracture occurs; the abnormal tilt angle of the guardrail in the tilted abnormal guardrail section is identified; based on the tilted abnormal guardrail section, the tilted associated guardrail section and the abnormal tilt angle, a second warning information is generated.

[0012] In a feasible implementation manner, based on the first warning information and the second warning information, the displacement abnormality data in the abnormal data is subjected to guardrail abnormality pattern recognition to determine the third warning information, specifically including: if the high-speed guardrail section positions in the displacement abnormality data all belong to the abnormal high-speed guardrail sections in the first warning information and the second warning information, then the displacement abnormality data is determined as the associated displacement abnormality data under the influence of the first warning information and the second warning information; through the displacement sensor, the displacement parameters of the associated displacement abnormal data are calculated to obtain the abnormal displacement distance; based on the first warning information, the second warning information and the abnormal displacement distance, the guardrail abnormality pattern of the associated displacement abnormal data is recognized to determine the third warning information.

[0013] In a feasible implementation manner, based on the first warning information, the second warning information and the abnormal displacement distance, the guardrail abnormal pattern is identified on the associated displacement abnormal data to determine the third warning information, specifically including: if the first vibration frequency in the first warning information is less than or equal to the first vibration preset threshold, and the abnormal tilt angle in the second warning information is less than or equal to the first tilt preset threshold, and the abnormal displacement distance is less than or equal to the first displacement preset threshold, then the guardrail abnormal pattern is determined to be a dangerous car accident guardrail abnormal pattern; if the first vibration frequency in the first warning information is greater than the first vibration preset threshold, and the abnormal tilt angle in the second warning information is less than or equal to the first tilt preset threshold, then the guardrail abnormal pattern is determined to be a dangerous car accident guardrail abnormal pattern. threshold, and the abnormal displacement distance is less than or equal to the first displacement preset threshold, the guardrail abnormal mode is determined as a dangerous scratch guardrail abnormal mode; if the first vibration frequency in the first warning information is greater than the first vibration preset threshold, and the abnormal tilt angle in the second warning information is greater than the first tilt preset threshold, and the abnormal displacement distance is less than or equal to the first displacement preset threshold, the guardrail abnormal mode is determined as a high-risk accident guardrail abnormal mode; if the first vibration frequency in the first warning information is greater than the first vibration preset threshold, and the abnormal tilt angle in the second warning information is greater than the first tilt preset threshold, and the abnormal displacement distance is greater than the first displacement preset threshold, the guardrail abnormal mode is determined as a super-dangerous accident guardrail abnormal mode.

[0014] In a feasible embodiment, a guardrail alarm information is generated based on the first warning information, the second warning information and the third warning information, specifically including: if only the first warning information exists on the guardrail management platform, the guardrail alarm information is determined as low-risk guardrail alarm information, and the low-risk guardrail alarm information is stored in a log; if the first warning information and the second warning information exist on the guardrail management platform, the guardrail alarm information is determined as medium-risk guardrail alarm information, and based on the location information of the abnormal high-speed network section, a road maintenance plan is generated and sent to the mobile device of the patrol personnel; if the first warning information, the second warning information and the third warning information exist on the guardrail management platform, the guardrail alarm information is determined as high-risk guardrail alarm information; and the high-risk guardrail alarm information is sent to a normal high-speed network section adjacent to the abnormal high-speed network section; the high-risk guardrail alarm information is visualized through the visualization equipment of the normal high-speed network section; and the high-risk guardrail alarm information is prioritized for top display through the guardrail management platform.

[0015] In the second aspect, an embodiment of the present application also provides a remote monitoring device for a smart guardrail based on the Internet of Things, the device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, so that the at least one processor can execute a remote monitoring method for a smart guardrail based on the Internet of Things described in any of the above embodiments.

[0016] On the third aspect, an embodiment of the present application also provides a non-volatile computer storage medium, characterized in that the storage medium is a non-volatile computer-readable storage medium, and the non-volatile computer-readable storage medium stores at least one program, each of which includes instructions, and when the instructions are executed by the terminal, the terminal executes a remote monitoring method for an intelligent guardrail based on the Internet of Things described in any of the above embodiments.

[0017] This application provides a method, device, and medium for remote monitoring of smart guardrails based on the Internet of Things. Compared with the existing technology, the embodiments of this application have the following beneficial technical effects:

[0018] 1. By deploying sensors on highway guardrails, the vibration, tilt, and displacement of the guardrails can be monitored in real time, ensuring seamless monitoring of the guardrail status.

[0019] 2. Able to collect abnormal data of guardrails, including vibration, tilt and displacement data, and perform data analysis and processing through the guardrail management platform.

[0020] 3. Simultaneous monitoring of multiple parameters such as vibration, tilt and displacement can provide a more comprehensive status assessment and help identify potential safety hazards more accurately.

[0021] 4. Through data monitoring and processing, the system can generate early warning information, including the relevant location, time and frequency information of abnormal vibration data, to improve the timeliness and accuracy of early warning.

[0022] 5. Temporal and spatial comparison of tilt anomaly data can help determine the time and spatial scope of the anomaly and help quickly locate the problem area.

[0023] 6. Through guardrail abnormal pattern recognition, the displacement abnormality data can be deeply analyzed to determine the specific abnormal situation of the guardrail, such as whether displacement or shift has occurred.

[0024] 7. Combining the first, second and third warning information, the system can generate comprehensive guardrail alarm information to provide decision support for maintenance personnel.

[0025] 8. By promptly identifying guardrail anomalies, preventive measures can be taken in advance to reduce the risk of traffic accidents and improve road safety.

[0026] 9. By detecting and preventing guardrail problems early, the frequency and cost of emergency maintenance can be reduced.

[0027] 10. Automated monitoring and analysis systems can reduce the workload of maintenance personnel and improve the efficiency and accuracy of maintenance work. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments described in the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0029] Figure 1 A flow chart of a remote monitoring method for an intelligent guardrail based on the Internet of Things provided in an embodiment of the present application;

[0030] Figure 2 A schematic diagram of a guardrail sensor installation provided in an embodiment of the present application;

[0031] Figure 3 A schematic structural diagram of an IoT-based smart guardrail remote monitoring device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the technical solutions in this application, the following will clearly and completely describe the technical solutions in the embodiments of this application in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0033] The present application embodiment provides a remote monitoring method for intelligent guardrails based on the Internet of Things, such as Figure 1 As shown, the remote monitoring method of the intelligent guardrail based on the Internet of Things specifically includes steps S101-S106:

[0034] S101: Divide the highway network in the target highway area into sections, and deploy preset guardrail sensors in the highway guardrail sections of the highway network sections. The guardrail sensors include vibration sensors, tilt sensors, and displacement sensors.

[0035] Specifically, the highway network in the target highway area is first divided into sections based on the continuous sections of highway guardrails, that is, some are guardrails, some are walls, and some are discontinuous intersections, to obtain highway network segments. The highway network segments include the continuous sections of all highway guardrails in the target highway area.

[0036] Furthermore, the high-speed network segments are classified based on their length parameters to identify normal high-speed network segments within a monitoring threshold range and overlong high-speed network segments exceeding the monitoring threshold range. The monitoring threshold range is the sensing threshold range of the guardrail sensor.

[0037] Furthermore, based on the monitoring threshold range, the ultra-long high-speed network section is segmented under relevant interval length parameters to determine the segmented high-speed network sections.

[0038] Further, Figure 2 A schematic diagram of a guardrail sensor installation provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, guardrail sensors are deployed in normal highway network sections and segmented highway network sections respectively, so that all highway guardrails in the target highway area are within the overall controllable monitoring range.

[0039] In one embodiment, Figure 2 As shown, the guardrail sensor includes: a vibration sensor, a tilt sensor and a displacement sensor. The vibration sensor is used to collect vibration abnormality data, the tilt sensor is used to collect tilt abnormality data, and the displacement sensor is used to collect displacement abnormality data.

[0040] As a feasible implementation method, a field survey is conducted on the target highway area to identify different types of sections such as guardrails, walls, and discontinuous intersections. Based on these characteristics, the highway is divided into multiple continuous sections, each of which contains guardrails within a certain range. Each highway network section is measured and its length is recorded. According to the preset monitoring threshold range (i.e. the sensing threshold range of the guardrail sensor), the sections are divided into two categories: normal length and overlong. For overlong sections, they are segmented according to the interval length parameters to ensure that each section is within the monitoring threshold range. When segmenting, factors such as traffic flow and accident rate should be considered to optimize the layout of monitoring points. Ensure that all highway guardrails are included in the overall controllable monitoring range, including all normal lengths and overlong sections that have been segmented. Use Internet of Things technologies, such as sensor networks and wireless communications, to transmit monitoring data to the central monitoring system.

[0041] In one embodiment, by dividing the overlong sections into segments, sensors and monitoring resources can be allocated more effectively, thereby improving the efficiency of monitoring. The classification processing of monitoring thresholds helps to reasonably allocate the number of sensors and avoid waste of resources. It ensures that all highway guardrails are within the monitoring range, so that potential safety risks can be discovered and responded to in a timely manner. Through segmented monitoring, sections that require maintenance can be located more accurately, reducing unnecessary inspection and maintenance work. For complex areas such as discontinuous intersections, segmented monitoring can better understand traffic patterns and thus optimize traffic management strategies. In the event of an anomaly, due to the clear monitoring range, it is possible to respond quickly and take corresponding measures to reduce the probability of accidents. Through effective monitoring and management, the user experience of the highway can be improved and traffic delays caused by guardrail problems can be reduced.

[0042] S102: Transmitting abnormal data collected by the guardrail sensor to the guardrail management platform, wherein the abnormal data includes vibration abnormal data, tilt abnormal data, and displacement abnormal data.

[0043] Specifically, guardrail sensors are used to collect abnormal data and corresponding spatiotemporal data, which includes time node data and geographic location data.

[0044] Furthermore, based on the time node data and the geographic location data, the abnormal high-speed network section corresponding to the abnormal data is determined.

[0045] Furthermore, through wireless communication technology, abnormal data, spatiotemporal data, and abnormal high-speed network segments are sent to the guardrail management platform, which is a cloud platform for data storage, processing, and analysis.

[0046] In one embodiment, guardrail sensors are installed on the guardrails of the highway. These sensors can detect abnormal conditions of the guardrails, such as vibration, tilt or displacement. When the sensor detects an abnormality, it also collects corresponding spatiotemporal data, including the specific time node and geographic location where the abnormality occurred. The data collected by the sensor contains time node and geographic location information, which is used to determine the specific location and time of the abnormal event. By analyzing these spatiotemporal data, the high-speed network section where the abnormality occurs can be accurately located. Wireless communication technology (such as 4G / 5G, LoRa, NB-IoT, etc.) is used to transmit the collected abnormal data, spatiotemporal data and the determined abnormal section information to the guardrail management platform in real time. The guardrail management platform is a cloud platform that is responsible for data storage, processing and analysis.

[0047] As a feasible implementation method, by collecting and transmitting data in real time, the system can quickly respond to abnormal conditions of the guardrail, improving the real-time nature of monitoring. Combined with spatiotemporal data, the system can accurately identify the location where the anomaly occurs, helping to quickly locate and solve the problem. Integrating abnormal data and spatiotemporal data provides maintenance personnel with more comprehensive information, facilitating problem diagnosis and decision-making. Since abnormal information can be quickly sent to the guardrail management platform, maintenance personnel can take action more quickly and reduce potential traffic safety risks. By centrally storing and analyzing data, the guardrail management platform can help optimize resource allocation and reduce unnecessary inspections and maintenance work. The data storage function of the cloud platform allows for the recording of historical abnormal data, facilitating trend analysis and long-term maintenance planning.

[0048] S103: Using the guardrail management platform, the vibration abnormality data in the abnormal data is monitored and processed with respect to location, time, and frequency to obtain first warning information.

[0049] Specifically, first, time parameters in a plurality of vibration abnormality data are classified and processed according to a preset time interval, and continuous time parameter vibration data in the same time interval is determined.

[0050] Furthermore, according to the monitoring threshold range, the position parameters in the plurality of vibration data are divided into high-speed network sections to determine the section position parameter vibration data of the same abnormal high-speed network section.

[0051] Furthermore, the continuous time parameter vibration data and the section position parameter vibration data are used as query data, and a matching query is performed on the abnormal high-speed network section in the guardrail management platform under the combination of the two to obtain the center section of the guardrail with abnormal vibration.

[0052] Furthermore, based on the center section of the vibration abnormal guardrail, the vibration radiation guardrail associated section is determined.

[0053] Furthermore, it is also necessary to collect the first vibration frequency of the central section of the vibration abnormal guardrail and the second vibration frequency of the associated section of the vibration radiation guardrail.

[0054] Furthermore, a first warning message is generated based on the vibration abnormal guardrail center section, the vibration radiation guardrail associated section, the first vibration frequency and the second vibration frequency.

[0055] In one embodiment, the collected vibration abnormality data is classified according to a preset time interval, such as data every 5 minutes or every hour.

[0056] In one embodiment, abnormal vibration data that occurs continuously within the same time interval is first identified to analyze its temporal pattern. Position parameters in the vibration data are then processed based on monitoring thresholds to group the data into corresponding high-speed network segments. Vibration data within the same abnormal high-speed network segment is then identified to analyze the vibration pattern within that segment. The classified continuous time parameter vibration data and segment position parameter vibration data are then input into the guardrail management platform. The platform then performs a matching query to identify the central segment of the guardrail with the abnormal vibration, i.e., the area with the most concentrated or significant vibration. Based on the central segment of the guardrail with the abnormal vibration, associated vibration radiation guardrail segments are identified, which may also be affected by the vibration. The first vibration frequency of the central segment of the guardrail with the abnormal vibration and the second vibration frequency of the associated vibration radiation guardrail segments are collected. This vibration frequency data helps understand the nature of the vibration source and the scope of impact. Finally, a first warning message is generated by combining the central segment of the guardrail with the abnormal vibration, the associated vibration radiation guardrail segments, the first vibration frequency, and the second vibration frequency. This warning message may include the severity of the vibration anomaly, possible causes, scope of impact, and recommended countermeasures.

[0057] As a feasible implementation method, the classification and processing of time and location parameters can precisely locate the specific area where vibration anomalies occur. Sorting data by time interval and location parameters facilitates more efficient analysis. By identifying sections associated with vibration radiation guardrails, the impact range and potential risks of vibration anomalies can be comprehensively assessed. Generating early warning information helps maintenance personnel promptly understand vibration anomalies and take preventive measures. Vibration frequency data can be used to better formulate maintenance strategies and prioritize high-risk areas.

[0058] S104: Based on the first warning information, perform spatiotemporal comparison processing on the tilted abnormal data in the abnormal data to determine second warning information.

[0059] Specifically, if the guardrail management platform recognizes the first warning information, it will identify the presence of tilt abnormality data in the vibration abnormality guardrail center section and the vibration radiation guardrail associated section in the first warning information, and identify and determine the tilt abnormality guardrail section. The tilt abnormality guardrail section is included in the vibration abnormality guardrail center section and / or the vibration radiation guardrail associated section.

[0060] Furthermore, based on the time difference between the first and second vibration frequencies in the first warning information, and based on the first position coordinates of the center section of the abnormally vibrating guardrail and the second position coordinates of the associated section of the vibration-radiating guardrail, the associated position of the abnormally tilted guardrail section is estimated with respect to the non-abnormally tilted guardrail section, thereby obtaining the associated guardrail section. The non-abnormally tilted guardrail section is an abnormal guardrail section that is associated with the abnormally tilted guardrail section when vibrating and / or breaking occurs.

[0061] Furthermore, it is also necessary to identify the abnormal tilt angle of the guardrail in the abnormal tilt guardrail section. Then, based on the abnormal tilt guardrail section, the tilt-associated guardrail section, and the abnormal tilt angle, a second warning information is generated.

[0062] In one embodiment, after receiving the first warning message, the guardrail management platform analyzes the data of the abnormally vibrating guardrail center section and the vibration-radiating guardrail associated sections to identify any tilt anomalies. By analyzing the sensor data, it then determines which guardrail sections are tilted. These abnormally tilted guardrail sections are contained within the abnormally vibrating guardrail center section and / or the vibration-radiating guardrail associated sections. The time difference between the first and second vibration frequencies is then calculated, which helps determine the vibration's propagation speed and impact range. The first position coordinates of the abnormally vibrating guardrail center section and the second position coordinates of the vibration-radiating guardrail associated sections are used to estimate the positions of the abnormally tilted guardrail sections. These abnormally tilted guardrail sections may be other abnormal guardrail sections that are associated with the abnormally tilted guardrail section after vibration and / or fracture. For the identified abnormally tilted guardrail sections, sensors or image analysis technology are used to measure the abnormal tilt angle of the guardrail. A second warning message is then generated based on the abnormally tilted guardrail sections, the associated tilted guardrail sections, and the abnormal tilt angle. At the same time, the second warning information may also include the severity of the tilt, possible causes, scope of impact, and recommended emergency response measures.

[0063] As a feasible implementation, by identifying abnormal tilt, the platform can more comprehensively assess the safety status of the guardrail and improve the accuracy of early warnings. The generation of a secondary early warning message enables maintenance personnel to quickly respond to the tilt anomaly, mitigating potential safety risks. By correlating position estimates, the location of the guardrail sections without abnormal tilt can be more accurately determined, helping to focus resources for repairs. By identifying abnormal tilt angles, the extent of guardrail damage can be assessed, allowing for more efficient scheduling of maintenance work.

[0064] S105 , performing guardrail abnormality pattern recognition on the displacement abnormality data in the abnormal data according to the first warning information and the second warning information, and determining third warning information.

[0065] Specifically, if the highway guardrail section positions in the displacement abnormality data belong to the abnormal highway guardrail sections in the first warning information and the second warning information, the displacement abnormality data is determined as the associated displacement abnormality data under the influence of the first warning information and the second warning information.

[0066] Furthermore, the displacement sensor is used to calculate the displacement parameters of the associated displacement anomaly data to obtain the abnormal displacement distance.

[0067] Furthermore, based on the first warning information, the second warning information and the abnormal displacement distance, guardrail abnormality pattern recognition is performed on the associated displacement abnormality data to determine the third warning information.

[0068] As a feasible implementation method, if the first vibration frequency in the first warning information is less than or equal to the first vibration preset threshold, and the abnormal tilt angle in the second warning information is less than or equal to the first tilt preset threshold, and the abnormal displacement distance is less than or equal to the first displacement preset threshold, then the guardrail abnormal mode is determined to be a dangerous car accident guardrail abnormal mode.

[0069] If the first vibration frequency in the first warning information is greater than the first vibration preset threshold, and the abnormal tilt angle in the second warning information is less than or equal to the first tilt preset threshold, and the abnormal displacement distance is less than or equal to the first displacement preset threshold, the guardrail abnormal mode is determined as a dangerous scratch guardrail abnormal mode.

[0070] If the first vibration frequency in the first warning information is greater than the first vibration preset threshold, and the abnormal tilt angle in the second warning information is greater than the first tilt preset threshold, and the abnormal displacement distance is less than or equal to the first displacement preset threshold, the guardrail abnormal mode is determined to be a high-risk accident guardrail abnormal mode.

[0071] If the first vibration frequency in the first warning information is greater than the first vibration preset threshold, and the abnormal tilt angle in the second warning information is greater than the first tilt preset threshold, and the abnormal displacement distance is greater than the first displacement preset threshold, the guardrail abnormal mode is determined to be an ultra-dangerous accident guardrail abnormal mode.

[0072] In one embodiment, the abnormal displacement data is first analyzed to check whether the position of the highway guardrail section matches the abnormal highway guardrail section identified in the first and second warning messages. If so, the abnormal displacement data is identified as correlated abnormal displacement data influenced by the first and second warning messages. Next, a displacement sensor is used to measure the correlated abnormal displacement data and calculate the abnormal displacement distance. The abnormal displacement distance refers to the distance the guardrail has moved relative to its normal position and is an important indicator for assessing guardrail stability. Pattern recognition is performed on the correlated abnormal displacement data by combining the first and second warning messages with the calculated abnormal displacement distance. Third warning information is then identified, reflecting the abnormal condition of the guardrail and its potential accident risk. Guardrail abnormality patterns are classified based on preset thresholds and the data in the warning message. Based on different combinations of vibration frequency, tilt angle, and displacement distance, guardrail abnormality patterns are classified into different levels, ranging from dangerous accidents to extremely dangerous accidents. In other words, by combining the abnormal displacement data with the warning information, the abnormal condition of the guardrail and the potential accident risk can be more accurately assessed. The generation of the third warning information enables maintenance personnel to respond quickly and take appropriate preventive measures.

[0073] S106. Generate guardrail alarm information based on the first warning information, the second warning information, and the third warning information.

[0074] Specifically, if only the first warning information exists on the guardrail management platform, the guardrail alarm information is determined to be low-risk guardrail alarm information, and the low-risk guardrail alarm information is stored in a log.

[0075] If the guardrail management platform has the first warning information and the second warning information, the guardrail alarm information will be determined as medium-risk guardrail alarm information, and based on the location information of the abnormal high-speed network section, a road maintenance plan will be generated and sent to the mobile device of the patrol personnel.

[0076] If the guardrail management platform has the first warning information, the second warning information, and the third warning information, the guardrail alarm information is determined as a high-risk guardrail alarm information, and the high-risk guardrail alarm information is sent to the normal high-speed network section adjacent to the abnormal high-speed network section.

[0077] Furthermore, high-risk guardrail alarm information can be visualized through visualization equipment in normal high-speed network sections, and high-risk guardrail alarm information can be prioritized and displayed at the top through the guardrail management platform.

[0078] In addition, the present application also provides an intelligent guardrail remote monitoring device based on the Internet of Things, such as Figure 3 As shown, the smart guardrail remote monitoring device 300 based on the Internet of Things specifically includes:

[0079] At least one processor 301. And a memory 302 in communication with the at least one processor 301. The memory 302 stores instructions that can be executed by the at least one processor 301, so that the at least one processor 301 can execute:

[0080] The highway network in the target highway area is divided into sections, and preset guardrail sensors are deployed in the highway guardrail sections of the highway network sections; wherein the guardrail sensors include: vibration sensors, tilt sensors, and displacement sensors;

[0081] Transmitting abnormal data collected by the guardrail sensor to the guardrail management platform; wherein the abnormal data includes: vibration abnormal data, tilt abnormal data and displacement abnormal data;

[0082] Through the guardrail management platform, the abnormal vibration data in the abnormal data is monitored and processed in terms of location, time and frequency to obtain the first warning information;

[0083] According to the first warning information, a temporal and spatial comparison process is performed on the tilted abnormal data in the abnormal data to determine the second warning information;

[0084] According to the first warning information and the second warning information, the guardrail abnormal pattern is identified on the displacement abnormal data in the abnormal data to determine the third warning information;

[0085] Based on the first warning information, the second warning information and the third warning information, a guardrail alarm information is generated.

[0086] The various embodiments in this application are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the device and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simple. For relevant parts, refer to the descriptions of the method embodiments.

[0087] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0088] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0089] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0090] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0091] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0092] The foregoing description describes specific embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0093] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the embodiments of the present application may have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included within the scope of the claims of the present application.

Claims

1. A remote monitoring method for intelligent guardrails based on the Internet of Things, characterized in that: The method comprises: The highway network in the target highway area is divided into sections, and preset guardrail sensors are deployed in the highway guardrail sections of the highway network sections; wherein the guardrail sensors include: vibration sensors, tilt sensors, and displacement sensors; Transmitting the abnormal data collected by the guardrail sensor to the guardrail management platform; wherein the abnormal data includes: vibration abnormal data, tilt abnormal data and displacement abnormal data; By means of the guardrail management platform, data monitoring and processing of the position, time and frequency of the vibration abnormality data in the abnormal data are performed to obtain first warning information; According to the first warning information, performing spatiotemporal comparison processing on the tilted abnormal data in the abnormal data to determine the second warning information specifically includes: If the guardrail management platform recognizes the first warning information, it identifies the presence of tilt abnormality data for the vibration abnormality guardrail center section and the vibration radiation guardrail associated section in the first warning information, and identifies and determines the tilt abnormality guardrail section; wherein the tilt abnormality guardrail section is included in the vibration abnormality guardrail center section and / or the vibration radiation guardrail associated section; According to the time difference between the first vibration frequency and the second vibration frequency in the first warning information, and based on the first position coordinates of the center section of the vibration abnormal guardrail and the second position coordinates of the vibration radiation guardrail associated section, the associated position of the tilted abnormal guardrail section with respect to the non-tilted abnormal guardrail section is estimated to obtain a tilted associated guardrail section; wherein the non-tilted abnormal guardrail section is an abnormal guardrail section that is associated with the tilted abnormal guardrail section when vibration and / or fracture occurs; Identifying an abnormal inclination angle of a guardrail in the abnormally inclined guardrail section; generating second warning information based on the abnormally tilted guardrail section, the tilt-associated guardrail section, and the abnormal tilt angle; performing guardrail abnormality pattern recognition on the displacement abnormality data in the abnormal data according to the first warning information and the second warning information to determine third warning information; Guardrail alarm information is generated based on the first warning information, the second warning information and the third warning information.

2. The method for remote monitoring of an intelligent guardrail based on the Internet of Things according to claim 1, characterized in that: The highway network in the target highway area is divided into sections, and the preset guardrail sensors are deployed in the highway guardrail sections of the highway network sections, including: Dividing the highway network in the target highway area into sections according to the continuous sections of the highway guardrails to obtain the highway network sections; wherein the highway network sections include the continuous sections of all highway guardrails in the target highway area; Classifying the high-speed network segments based on the interval length parameters to determine normal high-speed network segments within a monitoring threshold range and extra-long high-speed network segments exceeding the monitoring threshold range; wherein the monitoring threshold range is the sensing threshold range of the guardrail sensor; Based on the monitoring threshold range, the ultra-long high-speed network section is segmented under the relevant interval length parameters to determine the segmented high-speed network sections; The guardrail sensors are respectively deployed in the normal highway network section and the segmented highway network section, so that all highway guardrails in the target highway area are within the overall controllable monitoring range.

3. The method for remote monitoring of an intelligent guardrail based on the Internet of Things according to claim 1, characterized in that: Transmitting the abnormal data collected by the guardrail sensor to the guardrail management platform, specifically including: The guardrail sensor collects the abnormal data and corresponding spatiotemporal data; wherein the spatiotemporal data includes: time node data and geographic location data; Determining, based on the time node data and the geographic location data, an abnormal high-speed network segment corresponding to the abnormal data; The abnormal data, the spatiotemporal data and the abnormal high-speed network segment are sent to the guardrail management platform through wireless communication technology; wherein, the guardrail management platform is a cloud platform and is used for data storage, processing and analysis.

4. The method for remote monitoring of an intelligent guardrail based on the Internet of Things according to claim 1, characterized in that: The guardrail management platform monitors and processes the position, time, and frequency of the abnormal vibration data in the abnormal data to obtain first warning information, specifically including: Classifying and processing the time parameters in the plurality of vibration abnormality data according to a preset time interval to determine continuous time parameter vibration data within the same time interval; According to the monitoring threshold range, the position parameters in the plurality of vibration data are divided into high-speed network sections to determine the section position parameter vibration data of the same abnormal high-speed network section; Using the continuous time parameter vibration data and the segment position parameter vibration data as query data, a matching query is performed on the abnormal high-speed network segment in the guardrail management platform under the combination of the two to obtain the guardrail center segment with abnormal vibration; Based on the central section of the vibration abnormal guardrail, determining the vibration radiation guardrail associated section; Collecting a first vibration frequency of a central section of the vibration abnormality guardrail and a second vibration frequency of an associated section of the vibration radiation guardrail; The first warning information is generated according to the vibration abnormality guardrail center section, the vibration radiation guardrail associated section, the first vibration frequency and the second vibration frequency.

5. The method for remote monitoring of intelligent guardrails based on the Internet of Things according to claim 1, characterized in that: According to the first warning information and the second warning information, the guardrail abnormality pattern is identified on the displacement abnormality data in the abnormal data to determine the third warning information, specifically including: If the highway guardrail section positions in the abnormal displacement data all belong to the abnormal highway guardrail sections in the first warning information and the second warning information, then the abnormal displacement data is determined to be associated abnormal displacement data under the influence of the first warning information and the second warning information; By using the displacement sensor, the displacement parameter of the associated displacement abnormal data is calculated to obtain the abnormal displacement distance; Based on the first warning information, the second warning information and the abnormal displacement distance, guardrail abnormality pattern recognition is performed on the associated displacement abnormality data to determine the third warning information.

6. The method for remote monitoring of an intelligent guardrail based on the Internet of Things according to claim 5, characterized in that: Based on the first warning information, the second warning information, and the abnormal displacement distance, performing guardrail abnormality pattern recognition on the associated displacement abnormality data to determine the third warning information specifically includes: If the first vibration frequency in the first warning information is less than or equal to a first vibration preset threshold, and the abnormal tilt angle in the second warning information is less than or equal to a first tilt preset threshold, and the abnormal displacement distance is less than or equal to a first displacement preset threshold, then the guardrail abnormality mode is determined to be a dangerous car accident guardrail abnormality mode; If the first vibration frequency in the first warning information is greater than a first preset vibration threshold, and the abnormal tilt angle in the second warning information is less than or equal to the first preset tilt threshold, and the abnormal displacement distance is less than or equal to the first preset displacement threshold, then the guardrail abnormality mode is determined to be a dangerous guardrail scratch abnormality mode; If the first vibration frequency in the first warning information is greater than the first vibration preset threshold, and the abnormal tilt angle in the second warning information is greater than the first tilt preset threshold, and the abnormal displacement distance is less than or equal to the first displacement preset threshold, then the guardrail abnormality mode is determined to be a high-risk accident guardrail abnormality mode; If the first vibration frequency in the first warning information is greater than the first vibration preset threshold, and the abnormal tilt angle in the second warning information is greater than the first tilt preset threshold, and the abnormal displacement distance is greater than the first displacement preset threshold, the guardrail abnormal mode is determined to be an ultra-dangerous accident guardrail abnormal mode.

7. The method for remote monitoring of an intelligent guardrail based on the Internet of Things according to claim 1, characterized in that: Generating guardrail alarm information based on the first warning information, the second warning information, and the third warning information specifically includes: If the guardrail management platform only has the first warning information, the guardrail alarm information is determined to be low-risk guardrail alarm information, and the low-risk guardrail alarm information is stored in a log; If the guardrail management platform has the first warning information and the second warning information, the guardrail alarm information is determined to be a medium-risk guardrail alarm information, and a road maintenance plan is generated based on the location information of the abnormal high-speed network section and sent to the mobile device of the inspection personnel; If the guardrail management platform has the first warning information, the second warning information, and the third warning information, the guardrail alarm information is determined to be high-risk guardrail alarm information; and the high-risk guardrail alarm information is sent to a normal high-speed network segment adjacent to the abnormal high-speed network segment; The high-risk guardrail alarm information is visualized through the visualization equipment of the normal high-speed network section; and the high-risk guardrail alarm information is prioritized and displayed at the top through the guardrail management platform.

8. An intelligent guardrail remote monitoring device based on the Internet of Things, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, so that the at least one processor can execute the remote monitoring method of the smart guardrail based on the Internet of Things according to any one of claims 1-7.

9. A non-volatile computer storage medium, characterized in that The storage medium is a non-volatile computer-readable storage medium, which stores at least one program. Each of the programs includes instructions. When the instructions are executed by the terminal, the terminal executes the remote monitoring method of the smart guardrail based on the Internet of Things according to any one of claims 1 to 7.

Images