Intelligent guardrail remote monitoring method and device based on Internet of Things, and medium

Abstract

The invention discloses an intelligent guardrail remote monitoring method and device based on the Internet of Things, and a medium, belongs to the technical field of intelligent guardrails, and aims to solve the problems that an existing highway guardrail is difficult to monitor abnormities, the abnormal conditions of the guardrail cannot be grasped in time, follow-up driving vehicles are difficult to remind in time, secondary safety accidents are easily caused, and the like. And safety traffic management is not facilitated. The method comprises the following steps: performing section division on a high-speed network in a target expressway area, and deploying a preset guardrail sensor in a high-speed guardrail section of the high-speed network section; through the guardrail management platform, data monitoring processing related to the position, time and frequency is carried out on vibration abnormal data in the abnormal data, and first early warning information is obtained; performing space-time comparison processing on inclination abnormal data in the abnormal data to determine second early warning information; and carrying out guardrail abnormal mode identification on displacement abnormal data in the abnormal data, and determining third early 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, and play a very important role in traffic protection. When a traffic accident occurs, guardrails are often hit. Drivers are very likely to lose control of their vehicles and hit guardrails due to fatigue, speeding or emergencies.

[0003] When an abnormality occurs in a highway guardrail, if it is not handled in time, it may cause a secondary accident or affect traffic conditions. Traditional guardrails have problems such as being unable to be notified and handled in time after an abnormality occurs. In addition, it is difficult to automatically realize intelligent monitoring and abnormal warning of guardrails. When an abnormality occurs in the guardrail, it is impossible to respond quickly and remind the rear vehicle of safety hazards, which is not conducive to the safety of highway traffic and is prone to secondary safety accidents, causing a lot of trouble to the management capabilities of highway safety operations. Summary of the invention

[0004] The embodiments of the present application provide a remote monitoring method, device and medium for an intelligent guardrail based on the Internet of Things, which are used to solve the following technical problems: the existing abnormal monitoring of high-speed guardrails is relatively difficult, and it is impossible to grasp the abnormal conditions of the guardrails in time, 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 present application embodiment adopts 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 high-speed network in the target highway area into sections, and deploying a preset guardrail sensor in the high-speed guardrail section of the high-speed 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; according to the first warning information, performing spatiotemporal comparison processing on the tilt abnormal data in the abnormal data to determine a second warning information; according to 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; based on the first warning information, the second warning information and the third warning information, generating a guardrail alarm information.

[0007] By deploying sensors on the high-speed guardrail, the embodiment of the present application can monitor the vibration, tilt and displacement of the guardrail in real time to ensure seamless monitoring of the guardrail status. It is possible to collect abnormal data of the guardrail, including vibration, tilt and displacement data, and perform data analysis and processing through the guardrail management platform. Simultaneous monitoring of multiple parameters such as vibration, tilt and displacement can provide a more comprehensive status assessment, which helps to more accurately identify potential safety hazards. Through data monitoring and processing, the system can generate early warning information, including the relevant location, time and frequency information of the vibration abnormal data, to improve the timeliness and accuracy of the early warning. The time-space comparison processing of the tilt abnormal data can help determine the time and space range of the abnormality, which helps to quickly locate the problem area. Through the guardrail abnormal pattern recognition, the displacement abnormal data can be deeply analyzed to determine the specific abnormal situation of the guardrail, such as whether displacement or displacement occurs. Combined with the first, second and third warning information, the system can generate comprehensive guardrail alarm information to provide decision support for maintenance personnel. By timely identifying guardrail abnormalities, preventive measures can be taken in advance to reduce the risk of traffic accidents and improve the level of road safety. By early detection and prevention of guardrail problems, the frequency and cost of emergency maintenance can be reduced. 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 implementation, the expressway network in the target expressway area is divided into sections, and the preset guardrail sensors are deployed in the expressway guardrail sections of the expressway network sections, specifically including: 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 the normal expressway network sections within the monitoring threshold range and the extra-long expressway network sections beyond the monitoring threshold range; wherein the monitoring threshold range is the sensing threshold range of the guardrail sensor; based on the monitoring threshold range, dividing the extra-long expressway network sections into sections according to the relevant interval length parameters to determine the 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; through wireless communication technology, sending the abnormal data, the spatiotemporal data and the abnormal high-speed network segment to the guardrail management platform; wherein the guardrail management platform is a cloud platform and is used for data storage, processing and analysis.

[0010] In a feasible implementation manner, the guardrail management platform is used to monitor and process 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 a number of the 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 a number of the vibration data into high-speed network segments according to a 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 degree query on the abnormal high-speed network segment in the guardrail management platform under the combination of the two to obtain the vibration abnormality guardrail center segment; based on the vibration abnormality guardrail center segment, determining the vibration radiation guardrail associated segment; collecting the first vibration frequency of the vibration abnormality guardrail center segment and the second vibration frequency of the vibration radiation guardrail associated segment; generating the first warning information according to the vibration abnormality 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, a time-space comparison processing is performed on the tilt abnormal data in the abnormal data to determine the second warning information, which specifically includes: if the guardrail management platform recognizes the first warning information, the existence of tilt abnormal 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 abnormal guardrail section is identified and determined; wherein the tilt abnormal guardrail section is included in the vibration abnormal 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 tilted abnormal guardrail section with the non-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 guardrail abnormal pattern recognition is performed on the displacement abnormal data in the abnormal data to determine the third warning information, specifically including: if the high-speed guardrail section positions in the displacement abnormal data belong to the abnormal high-speed guardrail sections in the first warning information and the second warning information, then the displacement abnormal data is determined as the associated displacement abnormal 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 abnormal pattern recognition is performed on the associated displacement abnormal data 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 mode is identified for 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 mode is determined as a dangerous car 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 less than or equal to the first tilt preset threshold 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 implementation, based on the first warning information, the second warning information and the third warning information, a guardrail alarm information is generated, 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 device of the normal high-speed network section; and the high-risk guardrail alarm information is displayed as a priority on the top 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 as described in any of the above embodiments.

[0016] In 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 a terminal, the terminal executes a remote monitoring method for a smart guardrail based on the Internet of Things as described in any of the above-mentioned embodiments.

[0017] The present application provides a remote monitoring method, device and medium for intelligent guardrail based on the Internet of Things. Compared with the prior art, the embodiments of the present application have the following beneficial technical effects:

[0018] 1. By deploying sensors on high-speed guardrails, the vibration, tilt and displacement of the guardrails can be monitored in real time to ensure seamless monitoring of the guardrail status.

[0019] 2. Capable of collecting abnormal data of guardrails, including vibration, tilt and displacement data, and performing 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 the 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 occurs.

[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 timely identifying guardrail anomalies, preventive measures can be taken in advance to reduce the risk of traffic accidents and improve the level of 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 technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, 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 diagram of the structure of an intelligent guardrail remote monitoring device based on the Internet of Things 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 technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work 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, 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. The guardrail sensors include: vibration sensors, tilt sensors, and displacement sensors.

[0035] Specifically, firstly, the highway network in the target highway area is segmented according to the continuous sections of the highway guardrails, that is, some are guardrails, some are walls, and some are discontinuous forks, etc., to obtain the highway network sections. Among them, the highway network sections include the continuous sections of all highway guardrails in the target highway area.

[0036] Furthermore, the high-speed network sections are classified according to the interval length parameters to determine the normal high-speed network sections within the monitoring threshold range and the extra-long high-speed network sections beyond 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 super-long high-speed network section is segmented under the relevant interval length parameters to determine the segmented high-speed network section.

[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 to 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 IoT technologies such as sensor networks and wireless communications to transmit monitoring data to the central monitoring system.

[0041] In one embodiment, by dividing the extra-long 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. By ensuring that all highway guardrails are within the monitoring range, 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 inspections and maintenance work. For complex areas such as discontinuous intersections, segmented monitoring can better understand traffic patterns and optimize traffic management strategies. In the event of an abnormality, 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, firstly, the guardrail sensor is used to collect abnormal data and corresponding spatiotemporal data, wherein the spatiotemporal data 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, the abnormal data, spatiotemporal data and abnormal high-speed network segments are sent to the guardrail management platform through wireless communication technology. The guardrail management platform is a cloud platform and is used 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 abnormal condition, the corresponding spatiotemporal data is collected at the same time, including the specific time node and geographical location where the abnormality occurs. The data collected by the sensor contains time node and geographical location information, which are 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 in real time to the guardrail management platform. 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 respond quickly 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 abnormality occurs, which helps to quickly locate and solve the problem. Integrating abnormal data and spatiotemporal data provides maintenance personnel with more comprehensive information for problem diagnosis and decision-making. Since abnormal information can be quickly sent to the guardrail management platform, maintenance personnel can take action more quickly to 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 the recording of historical abnormal data, which is convenient for trend analysis and long-term maintenance planning.

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

[0049] Specifically, firstly, the time parameters in a number of vibration abnormal 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 processed to divide the high-speed network sections, and the vibration data of the section position parameters of the same abnormal high-speed network section are determined.

[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 guardrail center section with abnormal vibration.

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

[0053] Furthermore, it is also necessary to collect the first vibration frequency of the central section of the vibration abnormality 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 abnormal vibration data is classified according to a preset time interval, such as data every 5 minutes or every hour.

[0056] In one embodiment, the vibration abnormal data that appears continuously within the same time interval is first determined to analyze its time pattern. Then, according to the monitoring threshold range, the position parameters in the vibration data are processed and the data is divided into the corresponding high-speed network section. Then the vibration data in the same abnormal high-speed network section is determined to analyze the vibration pattern of the section. Then the classified continuous time parameter vibration data and section position parameter vibration data are input into the guardrail management platform. The platform is used to perform a matching query to find the central section of the vibration abnormal guardrail, that is, the area where the vibration is most concentrated or most significant. Based on the central section of the vibration abnormal guardrail, the vibration radiation guardrail associated sections related thereto are determined, which may also be affected by the vibration. The first vibration frequency of the central section of the vibration abnormal guardrail and the second vibration frequency of the vibration radiation guardrail associated section are collected. The vibration frequency data helps to understand the nature and impact range of the vibration source. Finally, the first warning information is generated by combining the central section of the vibration abnormal guardrail, the vibration radiation guardrail associated section, the first vibration frequency and the second vibration frequency. The warning information may include the severity of the vibration abnormality, possible causes, impact range and recommended countermeasures.

[0057] As a feasible implementation method, the specific area where the vibration anomaly occurs can be accurately located by classifying and processing the time parameters and location parameters. Classifying the data according to the time interval and location parameters helps to analyze more efficiently. By identifying the sections associated with the vibration radiation guardrail, the impact range and potential risks of the vibration anomaly can be fully evaluated. Generating early warning information can help maintenance personnel understand the vibration anomaly in a timely manner and take preventive measures. Based on the vibration frequency data, maintenance strategies can be better formulated to prioritize high-risk areas.

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

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

[0060] Further, according to the time difference of the vibration frequency between the first vibration frequency and the second vibration frequency in the first warning information, and based on the first position coordinate of the center section of the vibration abnormal guardrail and the second position coordinate of the vibration radiation guardrail associated section, the associated position of the tilted abnormal guardrail section is estimated to obtain the tilted associated guardrail section. 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.

[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 information, the guardrail management platform analyzes the data of the vibration abnormal guardrail center section and the vibration radiation guardrail associated section to identify whether there is an abnormal tilt. By analyzing the sensor data, it is then determined which guardrail sections are tilted, and these abnormal tilt guardrail sections are included in the vibration abnormal guardrail center section and / or the vibration radiation guardrail associated section. Then the time difference between the first vibration frequency and the second vibration frequency is calculated, which helps to determine the propagation speed and impact range of the vibration. The position of the non-tilted abnormal guardrail section is estimated using the first position coordinates of the vibration abnormal guardrail center section and the second position coordinates of the vibration radiation guardrail associated section. These non-tilted abnormal guardrail sections may be other abnormal guardrail sections that are associated with the tilt abnormal guardrail section after vibration and / or fracture. For the identified abnormal tilt guardrail section, a sensor or image analysis technology is used to measure the abnormal tilt angle of the guardrail. Then based on the abnormal tilt guardrail section, the tilt associated guardrail section and the abnormal tilt angle, a second warning information is generated. 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 tilt anomalies, the platform can more comprehensively assess the safety status of the guardrail and improve the accuracy of early warnings. The generation of second warning information enables maintenance personnel to respond quickly to tilt anomalies and reduce potential safety risks. By associating position estimation, the location of the guardrail section without tilt anomalies can be more accurately determined, which helps to concentrate resources for repair. By identifying abnormal tilt angles, the degree of damage to the guardrail can be assessed, so that maintenance work can be scheduled more effectively.

[0064] S105. According to the first warning information and the second warning information, a guardrail abnormal pattern is identified for the displacement abnormal data in the abnormal data to determine the 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 abnormal 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 abnormal pattern recognition is performed on the associated displacement abnormal 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 as 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 inclination angle in the second warning information is less than or equal to the first inclination 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 as 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 inclination angle in the second warning information is greater than the first inclination preset threshold, and the abnormal displacement distance is greater than the first displacement preset threshold, the guardrail abnormal mode is determined as an ultra-dangerous accident guardrail abnormal mode.

[0072] In one embodiment, first, the displacement abnormality data is analyzed to check whether the position of the high-speed guardrail section is consistent with the abnormal high-speed guardrail section marked in the first warning information and the second warning information. If consistent, these displacement abnormality data are determined as the associated displacement abnormality data under the influence of the first warning information and the second warning information. Then, the associated displacement abnormality data is measured using a displacement sensor to calculate the abnormal displacement distance. The abnormal displacement distance refers to the movement distance of the guardrail relative to the normal position, which is an important indicator for evaluating the stability of the guardrail. Combining the first warning information, the second warning information and the calculated abnormal displacement distance, the associated displacement abnormality data is pattern recognized. Then the third warning information is identified, which reflects the abnormal state of the guardrail and its potential accident risk. According to the preset threshold and the data in the warning information, the guardrail abnormal pattern is classified. According to different combinations of vibration frequency, tilt angle and displacement distance, the guardrail abnormal pattern is divided into different levels, from dangerous car accidents to super-dangerous accidents. That is, by combining the displacement abnormality data with the warning information, the abnormal state of the guardrail and the potential accident risk can be more accurately evaluated. The generation of the third warning information enables maintenance personnel to respond quickly and take corresponding 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 as 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 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, the high-risk guardrail alarm information can be visualized through the visualization equipment in the normal high-speed network section, and the high-risk guardrail alarm information can be displayed on the top with priority through the guardrail management platform.

[0078] In addition, the present application also provides a remote monitoring device for intelligent guardrails 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 high-speed network in the target high-speed area is divided into sections, and the preset guardrail sensors are deployed in the high-speed guardrail sections of the high-speed network sections; wherein the guardrail sensors include: vibration sensors, tilt sensors and displacement sensors;

[0081] 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;

[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, performing a time-space comparison process 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 recognition is performed 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] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description 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 as the 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 may be provided as methods, systems, or computer program products. Therefore, the present application may 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 may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include 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 generate 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] The 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. The memory is an example of a computer-readable medium.

[0091] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. 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 disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape 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 temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

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

[0093] The above is only 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 changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present application should be included in the scope of the claims of the present application.

Claims

1. A remote monitoring method for intelligent guardrail based on the Internet of Things, characterized in that: The method comprises: The high-speed network in the target high-speed area is divided into sections, and preset guardrail sensors are deployed in the high-speed guardrail section of the high-speed network section; 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; Through the guardrail management platform, data monitoring and processing on the position, time and frequency of the vibration abnormal data in the abnormal data are performed to obtain first warning information; According to the first warning information, performing a spatiotemporal comparison process on the tilted abnormal data in the abnormal data to determine the second warning information; According to 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 third warning information; Guardrail alarm information is generated based on the first warning information, the second warning information and the third warning information.

2. According to the method of remote monitoring of intelligent guardrail based on Internet of Things in claim 1, it is 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: According to the continuous sections of the highway guardrails, the highway network in the target highway area is segmented to obtain the highway network section; wherein the highway network section includes the continuous sections of all highway guardrails in the target highway area; Classifying the high-speed network sections according to the interval length parameters, and determining the normal high-speed network sections within the monitoring threshold range and the extra-long high-speed network sections beyond 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 section; The guardrail sensors are respectively deployed to the normal expressway network section and the segmented expressway network section, so that all expressway guardrails in the target expressway area are within an overall controllable monitoring range.

3. The method for remote monitoring of intelligent guardrails based on the Internet of Things according to claim 1 is characterized in that: Transmitting the abnormal data collected by the guardrail sensor to the guardrail management platform specifically includes: The abnormal data and the corresponding spatiotemporal data are collected by 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; 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 intelligent guardrails based on the Internet of Things according to claim 1 is characterized in that: Through the guardrail management platform, the vibration abnormal data in the abnormal data is monitored and processed in terms of location, time and frequency to obtain first warning information, which specifically includes: According to a preset time interval, classify and process the time parameters in the plurality of vibration abnormal data to determine the continuous time parameter vibration data in the same time interval; According to the monitoring threshold range, the position parameters in the 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; The continuous time parameter vibration data and the section position parameter vibration data are used as query data, and a matching degree query is performed on the abnormal high-speed network section in the guardrail management platform under the combination of the two to obtain the guardrail center section with abnormal vibration; Based on the central section of the vibration abnormal guardrail, determining the vibration radiation guardrail associated section; Collecting the first vibration frequency of the central section of the vibration abnormality guardrail and the second vibration frequency of the associated section of the vibration radiation guardrail; The first warning information is generated according to the vibration abnormality guardrail central 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 is characterized in that: According to the first warning information, performing a spatiotemporal comparison process 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 abnormal tilt data for the vibration abnormal guardrail center section and the vibration radiation guardrail associated section in the first warning information, and identifies and determines the abnormal tilt guardrail section; wherein the abnormal tilt guardrail section is included in the vibration abnormal guardrail center section and / or the vibration radiation guardrail associated section; According to the time difference of the vibration frequency between the first vibration frequency and the second vibration frequency in the first warning information, and based on the first position coordinate of the central section of the vibration abnormal guardrail and the second position coordinate of the vibration radiation guardrail associated section, the associated position of the tilted abnormal guardrail section with the non-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; Identifying an abnormal inclination angle of a guardrail in the abnormally inclined guardrail section; Based on the abnormally tilted guardrail section, the tilt-associated guardrail section and the abnormal tilt angle, second warning information is generated.

6. The method for remote monitoring of intelligent guardrails based on the Internet of Things according to claim 1 is characterized in that: According to the first warning information and the second warning information, the guardrail abnormal pattern recognition is performed on the displacement abnormal 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, the abnormal displacement data is determined as the 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 abnormal pattern recognition is performed on the associated displacement abnormal data to determine the third warning information.

7. The method for remote monitoring of intelligent guardrails based on the Internet of Things according to claim 6 is characterized in that: Based on the first warning information, the second warning information and the abnormal displacement distance, the guardrail abnormal pattern recognition is performed 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, the guardrail abnormal mode is determined as a dangerous car 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 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; 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 inclination angle in the second warning information is greater than the first inclination preset threshold, and the abnormal displacement distance is greater than the first displacement preset threshold, the guardrail abnormal mode is determined as an ultra-dangerous accident guardrail abnormal mode.

8. The method for remote monitoring of intelligent guardrails based on the Internet of Things according to claim 1 is 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 as 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 as 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 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 displayed at the top with priority through the guardrail management platform.

9. 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 1-8.

10. 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 which 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 1-8.

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