Remote video monitoring method and system for road construction site

Abstract

The invention relates to the technical field of road construction remote monitoring, and particularly discloses a road construction site remote video monitoring method and system. According to the method, a construction site model is constructed; performing real-time video monitoring to obtain a plurality of real-time monitoring videos; obtaining a plurality of target appearance features; tracking and identifying a remote monitoring target, selecting a target monitoring video, and marking a target monitoring area; and creating a remote monitoring window, performing monitoring display on the target monitoring video, and performing regional highlight synchronous display on the construction site model. In a plurality of real-time monitoring videos, tracking identification of a remote monitoring target, selection of a target monitoring video, monitoring display of the target monitoring video and regional highlight synchronous display of a construction site model can be carried out, so that the monitoring video which is most critical and has the most reference value is automatically displayed for remote management personnel; and the target monitoring area can be synchronously displayed, so that the remote monitoring efficiency is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of remote monitoring for road construction, and particularly relates to a method and system for remote video monitoring of road construction sites. Background Art

[0002] Remote monitoring of road construction is a technology that uses remote communication means to conduct real-time monitoring and management of construction sites during road construction. It can collect images, videos, and various environmental parameters of the construction site in real time and transmit them to a designated monitoring center or the mobile devices of management personnel through the network.

[0003] In the prior art, a large number of monitoring cameras need to be deployed for road construction. At the same time, a large amount of different monitoring video data can be obtained. In remote monitoring, it is difficult for remote management personnel to simply and quickly view the most critical and valuable monitoring videos from them. Instead, they need to view each monitoring video one by one, which is time-consuming and laborious, seriously affecting the efficiency of remote monitoring. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a method and system for remote video monitoring of road construction sites, aiming to solve the problems raised in the background art.

[0005] To achieve the above purpose, the embodiments of the present invention provide the following technical solutions: A method for remote video monitoring of road construction sites, the method specifically includes the following steps: Obtain the basic on-site data of the road construction site and construct a construction site model; Determine multiple video monitoring areas in the road construction site, and conduct real-time video monitoring in the multiple video monitoring areas to obtain multiple real-time monitoring videos; Receive remote monitoring requirements, conduct target analysis, determine the remote monitoring target, and obtain multiple target appearance features of the remote monitoring target; Based on the multiple target appearance features, track and identify the remote monitoring target in the multiple real-time monitoring videos, select the target monitoring video, and mark the target monitoring area; Create a remote monitoring window, monitor and display the target monitoring video, and synchronously display area highlighting of the construction site model according to the target monitoring area.

[0006] As a further limitation of the technical solution of the embodiments of the present invention, the step of obtaining the basic on-site data of the road construction site and constructing a construction site model specifically includes the following steps: Obtain the construction planning information of the road construction; Analyze the construction planning information to determine the road construction site; Obtain the basic on-site data of the road construction site; Perform modeling processing on the basic on-site data, and construct a construction site model through cascaded convolution.

[0007] As a further limitation of the technical solution of the embodiment of the present invention, the determining of multiple video monitoring areas in the road construction site, performing real-time video monitoring in the multiple video monitoring areas, and obtaining multiple real-time monitoring videos specifically include the following steps: Determine multiple video monitoring areas in the road construction site, and generate area monitoring instructions; According to the area monitoring instructions, perform real-time video monitoring on the multiple video monitoring areas to obtain multiple real-time monitoring videos.

[0008] As a further limitation of the technical solution of the embodiment of the present invention, the receiving of remote monitoring requirements, performing target analysis, determining remote monitoring targets, and obtaining multiple target appearance features of the remote monitoring targets specifically include the following steps: Receive remote monitoring requirements; Perform target analysis on the remote monitoring requirements to determine remote monitoring targets; From a preset target database, obtain multiple target backup images of the remote monitoring targets; Perform feature recognition on the multiple target backup images to obtain multiple target appearance features. [[ID=X]]

[0009] As a further limitation of the technical solution of the embodiment of the present invention, the performing of tracking and recognition of remote monitoring targets in the multiple real-time monitoring videos based on the multiple target appearance features, selecting target monitoring videos, and marking target monitoring areas specifically include the following steps: Generate a tracking and recognition instruction; According to the tracking and recognition instruction, perform tracking and recognition of remote monitoring targets in the multiple real-time monitoring videos based on the multiple target appearance features, and select target monitoring videos; According to the target monitoring videos, mark the corresponding target monitoring areas from the multiple video monitoring areas.

[0010] As a further limitation of the technical solution of the embodiment of the present invention, the creating of a remote monitoring window, performing monitoring display on the target monitoring videos, and performing area highlighting and synchronous display on the construction site model according to the target monitoring areas specifically include the following steps: Create a remote monitoring window; In the remote monitoring window, perform monitoring display on the target monitoring videos; According to the target monitoring area, perform area highlighting processing on the construction site model to generate an area highlighted model; In the remote monitoring window, synchronously display the area highlighted model.

[0011] A remote video monitoring system for a road construction site, the system includes a site model construction unit, a real-time video monitoring unit, a monitoring target analysis unit, a target tracking and recognition unit, and a remote monitoring display unit, wherein: The site model construction unit is used to obtain the basic site data of the road construction site and construct a construction site model; The real-time video monitoring unit is used to determine multiple video monitoring areas in the road construction site, perform real-time video monitoring in the multiple video monitoring areas, and obtain multiple real-time monitoring videos; The monitoring target analysis unit is used to receive remote monitoring requirements, perform target analysis, determine remote monitoring targets, and obtain multiple target appearance features of the remote monitoring targets; The target tracking and recognition unit is used to perform tracking and recognition of remote monitoring targets in the multiple real-time monitoring videos based on the multiple target appearance features, select target monitoring videos, and mark target monitoring areas; The remote monitoring display unit is used to create a remote monitoring window, monitor and display the target monitoring videos, and perform area highlighting synchronization display on the construction site model according to the target monitoring area.

[0012] As a further limitation of the technical solution of the embodiment of the present invention, the site model construction unit specifically includes: The information acquisition module is used to acquire the construction planning information of the road construction; The information analysis module is used to analyze the construction planning information to determine the road construction site; The data acquisition module is used to acquire the basic site data of the road construction site; The model construction module is used to perform model processing on the basic site data and construct a construction site model through cascaded convolution.

[0013] As a further limitation of the technical solution of the embodiment of the present invention, the monitoring target analysis unit specifically includes: The requirement receiving module is used to receive remote monitoring requirements; The target analysis module is used to perform target analysis on the remote monitoring requirements to determine remote monitoring targets; The image acquisition module is used to acquire multiple target backup images of the remote monitoring targets from a preset target database; A feature recognition module for performing feature recognition on multiple target backup images to obtain multiple target appearance features.

[0014] As a further limitation of the technical solution of the embodiment of the present invention, the remote monitoring and display unit specifically includes: A window creation module for creating a remote monitoring window; A monitoring and display module for monitoring and displaying the target monitoring video in the remote monitoring window; A highlighting processing module for performing regional highlighting processing on the construction site model according to the target monitoring area to generate a regional highlighting model; A synchronous display module for synchronously displaying the regional highlighting model in the remote monitoring window.

[0015] Compared with the prior art, the beneficial effects of the present invention are: In the embodiment of the present invention, a construction site model is constructed; real-time video monitoring is performed to obtain multiple real-time monitoring videos; multiple target appearance features are obtained; tracking and recognition of remote monitoring targets are performed, a target monitoring video is selected, and a target monitoring area is marked; a remote monitoring window is created, the target monitoring video is monitored and displayed, and regional highlighting and synchronous display of the construction site model are performed. It is possible to perform tracking and recognition of remote monitoring targets in multiple real-time monitoring videos, select a target monitoring video, monitor and display the target monitoring video, and perform regional highlighting and synchronous display of the construction site model, thereby automatically displaying the most critical and most valuable monitoring video for remote managers, and being able to synchronously display the target monitoring area, greatly improving the efficiency of remote monitoring. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0017] Figure 1 Shows the flowchart of the method provided by the embodiment of the present invention.

[0018] Figure 2 Shows the flowchart of constructing the construction site model in the method provided by the embodiment of the present invention.

[0019] Figure 3 Shows the flowchart of obtaining multiple real-time monitoring videos in the method provided by the embodiment of the present invention.

[0020] Figure 4 Shows the flowchart of determining the remote monitoring target in the method provided by the embodiment of the present invention.

[0021] Figure 5 The flowchart for tracking and identifying a target in the method provided by an embodiment of the present invention is shown.

[0022] Figure 6 The flowchart for remotely monitoring and displaying a target in the method provided by an embodiment of the present invention is shown.

[0023] Figure 7 The application architecture diagram of the system provided by an embodiment of the present invention is shown.

[0024] Figure 8 The structural block diagram of the on-site model construction unit in the system provided by an embodiment of the present invention is shown.

[0025] Figure 9 The structural block diagram of the monitoring target analysis unit in the system provided by an embodiment of the present invention is shown.

[0026] Figure 10 The structural block diagram of the remote monitoring and display unit in the system provided by an embodiment of the present invention is shown. Detailed implementation manners

[0027] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0028] It can be understood that in the prior art, a large number of monitoring cameras need to be deployed for road construction. At the same time, a large amount of different monitoring video data can be obtained. In remote monitoring, it is difficult for remote managers to simply and quickly view the most critical and most valuable monitoring videos from them. Instead, they need to view each monitoring video one by one, which is time-consuming and laborious, and seriously affects the efficiency of remote monitoring.

[0029] To solve the above problems, the embodiments of the present invention obtain the basic on-site data of the road construction site and construct a construction site model; determine multiple video monitoring areas in the road construction site, perform real-time video monitoring in the multiple video monitoring areas to obtain multiple real-time monitoring videos; receive remote monitoring requirements, perform target analysis, determine remote monitoring targets, and obtain multiple target appearance features of the remote monitoring targets; based on the multiple target appearance features, perform tracking and recognition of the remote monitoring targets in the multiple real-time monitoring videos, select target monitoring videos, and mark target monitoring areas; create a remote monitoring window, monitor and display the target monitoring videos, and perform area highlighting and synchronous display of the construction site model according to the target monitoring areas. It can perform tracking and recognition of remote monitoring targets in multiple real-time monitoring videos, select target monitoring videos, monitor and display the target monitoring videos, and perform area highlighting and synchronous display of the construction site model, thereby automatically displaying the most critical and valuable monitoring videos for remote management personnel, and being able to synchronously display the target monitoring areas, greatly improving the efficiency of remote monitoring.

[0030] Figure 1 The flowchart of the method provided by the embodiments of the present invention is shown.

[0031] Specifically, a remote video monitoring method for a road construction site, the method specifically includes the following steps: Step S101, obtain the basic on-site data of the road construction site and construct a construction site model.

[0032] In the embodiments of the present invention, by obtaining the construction planning information of the road construction, through analyzing the construction planning information, determining the road construction site, and then obtaining the basic on-site data such as the map and BIM data of the road construction site, and further performing three-dimensional data extraction and model rendering processing on the basic on-site data to construct the construction site model of the road construction site.

[0033] Specifically, Figure 2 The flowchart of constructing the construction site model in the method provided by the embodiments of the present invention is shown.

[0034] Among them, in the preferred embodiment provided by the present invention, the obtaining the basic on-site data of the road construction site and constructing the construction site model specifically includes the following steps: Step S1011, obtain the construction planning information of the road construction; Step S1012, analyze the construction planning information to determine the road construction site; Step S1013, obtain the basic on-site data of the road construction site; Step S1014, perform model processing on the basic on-site data and construct the construction site model through cascaded convolution.

[0035] Specifically, the basic on-site data is modeled, and a construction site model is constructed through cascaded convolution. The specific steps are as follows: Receive the basic on-site data and perform noise filtering and format standardization processing to generate standardized data; adopt a spatial registration algorithm to align the video images and 3D laser point cloud coordinates in the standardized data to obtain spatio-temporally aligned structured data; Extract the mechanical motion trajectory, personnel focus heat map, and trimmed relative displacement amount from the spatio-temporally aligned structured data; based on the sliding time window mechanism, perform dynamic importance assessment on the mechanical motion trajectory, personnel focus heat map, and trimmed relative displacement amount, and update the weight value distribution map every preset period to obtain a three-dimensional weight matrix; Process the spatio-temporally aligned structured data and the three-dimensional weight matrix through a cascaded convolution architecture. The shallow network processes the infrared and visible light features in the spatio-temporally aligned structured data to capture minute visual features, and the deep network extracts macroscopic motion patterns, and finally obtains the output feature tensor; According to the illumination change at the construction site, combined with the output feature tensor, dynamically adjust the fusion ratio of the infrared and visible light features. For the image quality degradation caused by extreme weather, adopt an adversarial generative network for feature restoration compensation to obtain a feature map with enhanced environmental robustness; Use a graph neural network to construct a timestamped three-dimensional topological structure of the construction surface, and perform cross-modal fusion on the feature map with enhanced environmental robustness and the 3D laser point cloud coordinates to construct a four-dimensional spatio-temporal situation model; Compare the current four-dimensional spatio-temporal situation model with the historical four-dimensional spatio-temporal situation model to generate a feature offset report; based on the confidence level in the feature offset report, screen and construct an incremental training data set; use the incremental training data set to train the current four-dimensional spatio-temporal situation model, and obtain an optimized four-dimensional spatio-temporal situation model. After a preset number of iterations, obtain the final four-dimensional spatio-temporal situation model, and use the final four-dimensional spatio-temporal situation model as the construction site model.

[0036] Furthermore, the remote video monitoring method for the road construction site further includes the following steps: Step S102, determine multiple video monitoring areas in the road construction site, and perform real-time video monitoring in the multiple video monitoring areas to obtain multiple real-time monitoring videos.

[0037] In the embodiment of the present invention, by analyzing the basic on-site data, multiple video monitoring areas in the road construction site are determined, and then area monitoring instructions are generated. According to the area monitoring instructions, real-time video monitoring is performed on the multiple video monitoring areas to obtain real-time monitoring videos corresponding to the multiple video monitoring areas.

[0038] Specifically, Figure 3 Fig. 3 shows a flowchart of obtaining multiple real-time monitoring videos in the method provided by an embodiment of the present invention.

[0039] Among them, in a preferred embodiment provided by the present invention, determining multiple video monitoring areas in a road construction site, performing real-time video monitoring in the multiple video monitoring areas, and obtaining multiple real-time monitoring videos specifically include the following steps: Step S1021, determine multiple video monitoring areas in a road construction site and generate area monitoring instructions; Step S1022, according to the area monitoring instructions, perform real-time video monitoring on the multiple video monitoring areas to obtain multiple real-time monitoring videos.

[0040] Specifically, the specific steps for determining multiple video monitoring areas in a road construction site and generating area monitoring instructions are as follows: Obtain a historical construction accident report and a construction progress plan through basic on-site data; by analyzing the high-frequency risk points in the historical construction accident report and combining with the construction progress plan, establish a dynamic benchmark instruction template including area risk levels and operation type sensitivities; Link monitoring devices through the dynamic benchmark instruction template, perform three-dimensional coordinate calibration on key areas, and then eliminate visual blind spots caused by equipment occlusion through point cloud reconstruction to generate a monitoring area dataset; the monitoring area dataset includes the actual number of workers in each area, the activity trajectories of heavy machinery, the occurrence frequency of illegal operations, and the operation intensity; Determine high-risk scenario characteristics by analyzing the high-frequency risk points in the historical construction accident report; use a temporal convolutional neural network to analyze the correlation between the occurrence frequency of illegal operations and the operation intensity in each area of the monitoring area dataset, and at the same time fuse the high-risk scenario characteristics to generate a priority evaluation list; Obtain meteorological warning data through basic on-site data, and the meteorological warning data includes real-time wind speed monitoring values and rainfall intensity forecast parameters; according to the high-risk operation areas marked in the priority evaluation list, combine with the meteorological warning data to execute a hierarchical response strategy to generate a priority environment adaptive map; the priority environment adaptive map includes the monitoring accuracy of the construction operation area, the infrared coverage radius parameter in a rainstorm environment, and environmental sensitivity parameters; Based on the monitoring accuracy of the construction operation area and the infrared coverage radius parameter in a rainstorm environment, extract the effective monitoring area parameters of each area, and synchronously associate with the time window of the construction progress plan to generate a spatio-temporal coupling queue; the spatio-temporal coupling queue includes spatio-temporal association parameters and process sensitivity coefficients; Dynamically fuse the process sensitivity coefficient and the high-risk scenario characteristics based on spatio-temporal correlation parameters, and then combine the environment sensitivity parameters to generate area monitoring instructions.

[0041] Further, the remote video monitoring method for road construction sites further includes the following steps: Step S103, receive remote monitoring requirements, conduct target analysis, determine the remote monitoring target, and obtain multiple target appearance features of the remote monitoring target.

[0042] In an embodiment of the present invention, when a remote manager needs to perform remote monitoring management, receive the remote monitoring requirements of the remote manager, then conduct target analysis on the remote monitoring requirements, determine the remote monitoring target, and then match and obtain multiple target backup images of the remote monitoring target from a preset target database, and then perform feature recognition on the multiple target backup images to obtain multiple target appearance features.

[0043] It can be understood that the remote monitoring target can be construction workers, asphalt transport vehicles, tire rollers, vibratory rollers, graders, etc.

[0044] It can be understood that the types of feature recognition include color, shape, texture, etc.

[0045] Specifically, Figure 4 shows a flowchart for determining a remote monitoring target in the method provided by an embodiment of the present invention.

[0046] Among them, in a preferred embodiment provided by the present invention, the steps of receiving remote monitoring requirements, conducting target analysis, determining the remote monitoring target, and obtaining multiple target appearance features of the remote monitoring target specifically include the following steps: Step S1031, receive remote monitoring requirements; Step S1032, conduct target analysis on the remote monitoring requirements to determine the remote monitoring target; Step S1033, obtain multiple target backup images of the remote monitoring target from a preset target database; Step S1034, perform feature recognition on multiple target backup images to obtain multiple target appearance features.

[0047] Specifically, the steps of performing feature recognition on multiple target backup images to obtain multiple target appearance features are as follows: Determine a feature dimension classification template through a preset target database, read all target backup images, and for each target backup image, establish an analysis channel corresponding to the feature dimension classification template to generate a feature dimension initialization image; Use a deep learning model to perform layer-by-layer feature analysis on the initialized images of each feature dimension, generate quantization evaluation values on each feature dimension, and obtain an initial evaluation value table, where the initial evaluation value table contains multiple initial evaluation values; Determine the monitoring target category based on the monitoring requirements; perform correlation analysis on the initialized images of the feature dimension under the same feature dimension through the monitoring target category, calculate the numerical fluctuation law of the initial evaluation values in each feature channel among different images, and at the same time assign weights according to the strength of stability to generate the feature stability confidence; Obtain environmental parameters through the monitoring area dataset. The environmental parameters include light intensity and the concentration of airborne particulate matter. Process the environmental parameters through dynamic feature mapping to obtain dynamic environment compensation parameters; Combine the construction progress plan, analyze the value decay curve of the target backup images collected at different time periods, and determine the time compensation factor based on the value decay curve of the target backup images collected at different time periods; Obtain a feature template matching the current target backup image, and measure the Bhattacharyya distance distribution between the actually extracted features and the standard features item by item to obtain the feature benchmark comparison value; For each target backup image, non-linearly superimpose the initial evaluation value and the feature stability confidence, and then dynamically adjust the non-linearly superimposed result using the dynamic environment compensation parameter to obtain a multi-dimensional fusion feature vector; use the time compensation factor to perform weighted geometric average processing on all multi-dimensional fusion feature vectors to obtain a normalized feature vector; use the feature benchmark comparison value to perform difference compensation on the normalized feature vector to obtain a compensated feature vector; encode the compensated feature vector into a standardized format to obtain a standard feature vector; use the standard feature vector to obtain the target appearance feature.

[0048] Further, the remote video monitoring method for the road construction site further includes the following steps: Step S104, based on the multiple target appearance features, in the multiple real-time monitoring videos, perform tracking and recognition of the remote monitoring target, select the target monitoring video, and mark the target monitoring area.

[0049] In the embodiment of the present invention, by generating a tracking and recognition instruction, and then according to the tracking and recognition instruction, based on multiple target appearance features, perform feature matching and tracking and recognition of the remote monitoring target in multiple real-time monitoring videos, select the target monitoring video with the remote monitoring target from the multiple real-time monitoring videos, and mark the corresponding target monitoring area from the multiple video monitoring areas according to the target monitoring video.

[0050] Specifically, Figure 5 Shows the flowchart of performing target tracking and recognition in the method provided by the embodiment of the present invention.

[0051] Among them, in the preferred embodiment provided by the present invention, for tracking and identifying a remote monitoring target among multiple real-time monitoring videos based on the multiple target appearance features, selecting a target monitoring video, and marking a target monitoring area, the specific steps are as follows: Step S1041: Generate a tracking and identification instruction; Step S1042: According to the tracking and identification instruction, perform tracking and identification of the remote monitoring target among multiple real-time monitoring videos based on the multiple target appearance features, and select a target monitoring video; Step S1043: According to the target monitoring video, mark the corresponding target monitoring area from multiple video monitoring areas.

[0052] Specifically, according to the tracking and identification instruction, for tracking and identifying the remote monitoring target among multiple real-time monitoring videos based on the multiple target appearance features and selecting a target monitoring video, the specific steps are as follows: Obtain the environmental parameter values of the target monitoring point at every preset period. The environmental parameter values include dust concentration parameters and light intensity values; perform Gaussian filtering on the dust concentration parameters to obtain the processed dust concentration parameters; convert the light intensity values to obtain a standardized brightness coefficient; obtain a mapping relationship table based on the processed dust concentration parameters and the standardized brightness coefficient; Extract the key frames of each real-time monitoring video stream to obtain data vectors in the feature dimension; obtain standard features based on the feature dimension classification template; compare the data vectors in the feature dimension with the standard features dimension by dimension, and generate a multi-dimensional feature matching degree scoring matrix. In the feature matching degree scoring matrix, the matching degree scores correspond one-to-one with the environmental adjustment parameter values; Calculate the dynamic adjustment coefficients of each feature dimension under the current environmental parameter values through the mapping relationship table to obtain feature dynamic adjustment coefficients; use the feature dynamic adjustment coefficients to perform non-linear transformation on the matching degree scores to obtain environment-adaptive feature weights; Obtain the delay data from the acquisition to the processing completion by measuring each real-time monitoring video stream, and obtain a delay coefficient through the delay data; obtain an attenuation index through the regional hazard level; use the attenuation index to apply an exponential decay multiplication to the delay coefficient to obtain a delay compensation coefficient; Obtain the distance attenuation coefficient based on BIM data, the coordinates of the monitoring device, and the lens parameters of the monitoring device; use the multi-dimensional feature matching degree scoring matrix to non-linearly superimpose the feature matching degree scores of each dimension with the corresponding environment adaptation feature weights to obtain the feature matching degree score of the environmental impact; use the delay compensation coefficient to adjust the feature matching degree score of the environmental impact to generate the processed matching degree score; optimize the processed matching degree score through the distance attenuation coefficient to obtain the comprehensive matching degree score; Traverse all the comprehensive matching degree scores, and select the real-time monitoring video with the highest comprehensive matching degree score as the target monitoring video.

[0053] Furthermore, the remote video monitoring method for the road construction site further includes the following steps: Step S105, create a remote monitoring window, monitor and display the target monitoring video, and synchronously display the area highlighting of the construction site model according to the target monitoring area.

[0054] In the embodiment of the present invention, by creating a remote monitoring window, the remote monitoring window is equally divided into a monitoring sub-window A and a monitoring sub-window B. In the monitoring sub-window A of the remote monitoring window, the target monitoring video is monitored and displayed, and according to the spatial position of the target monitoring area in the road construction site, the area highlighting of the construction site model is performed to generate an area highlighting model. Then, in the monitoring sub-window B of the remote monitoring window, the area highlighting model is synchronously displayed, so that the remote management personnel can not only view the target monitoring video of the remote monitoring target, but also clearly understand the position of the remote monitoring target in the road construction site.

[0055] Specifically, Figure 6 The flowchart of the target remote monitoring display in the method provided by the embodiment of the present invention is shown.

[0056] Among them, in the preferred embodiment provided by the present invention, the step of creating a remote monitoring window, monitoring and displaying the target monitoring video, and synchronously displaying the area highlighting of the construction site model according to the target monitoring area specifically includes the following steps: Step S1051, create a remote monitoring window; Step S1052, in the remote monitoring window, monitor and display the target monitoring video; Step S1053, according to the target monitoring area, perform area highlighting on the construction site model to generate an area highlighting model; Step S1054, in the remote monitoring window, synchronously display the area highlighting model.

[0057] Furthermore, Figure 7Shows the application architecture diagram of the system provided by the embodiments of the present invention.

[0058] Among them, in another preferred embodiment provided by the present invention, a remote video monitoring system for road construction sites includes: A field model construction unit 101, configured to obtain the basic field data of the road construction site and construct a construction site model.

[0059] In the embodiments of the present invention, the field model construction unit 101 determines the road construction site by obtaining the construction planning information of the road construction and analyzing the construction planning information, then obtains the basic field data such as the map and BIM data of the road construction site, and further performs three-dimensional data extraction and model rendering processing on the basic field data to construct the construction site model of the road construction site.

[0060] Specifically, Figure 8 Shows the structural block diagram of the field model construction unit 101 in the system provided by the embodiments of the present invention.

[0061] Among them, in the preferred embodiment provided by the present invention, the field model construction unit 101 specifically includes: An information acquisition module 1011, configured to acquire the construction planning information of the road construction; An information analysis module 1012, configured to analyze the construction planning information to determine the road construction site; A data acquisition module 1013, configured to acquire the basic field data of the road construction site; A model construction module 1014, configured to perform model processing on the basic field data and construct a construction site model through cascaded convolution.

[0062] Furthermore, the remote video monitoring system for road construction sites further includes: A real-time video monitoring unit 102, configured to determine multiple video monitoring areas in the road construction site, perform real-time video monitoring in the multiple video monitoring areas, and acquire multiple real-time monitoring videos.

[0063] In the embodiments of the present invention, the real-time video monitoring unit 102 determines multiple video monitoring areas in the road construction site by analyzing the basic field data, then generates area monitoring instructions, and performs real-time video monitoring on the multiple video monitoring areas according to the area monitoring instructions to acquire the real-time monitoring videos corresponding to the multiple video monitoring areas.

[0064] A monitoring target analysis unit 103, configured to receive remote monitoring requirements, perform target analysis, determine remote monitoring targets, and acquire multiple target appearance features of the remote monitoring targets.

[0065] In an embodiment of the present invention, when a remote administrator needs to perform remote monitoring and management, the monitoring target analysis unit 103 receives the remote monitoring requirements of the remote administrator, then performs target analysis on the remote monitoring requirements to determine the remote monitoring target, and then matches and obtains multiple target backup images of the remote monitoring target from a preset target database, and further performs feature recognition on the multiple target backup images to obtain multiple target appearance features.

[0066] Specifically, Figure 9 FIG. shows a structural block diagram of the monitoring target analysis unit 103 in the system provided by the embodiment of the present invention.

[0067] Among them, in a preferred embodiment provided by the present invention, the monitoring target analysis unit 103 specifically includes: A requirement receiving module 1031, configured to receive remote monitoring requirements; A target analysis module 1032, configured to perform target analysis on the remote monitoring requirements to determine the remote monitoring target; An image acquisition module 1033, configured to obtain multiple target backup images of the remote monitoring target from a preset target database; A feature recognition module 1034, configured to perform feature recognition on the multiple target backup images to obtain multiple target appearance features.

[0068] Furthermore, the remote video monitoring system for road construction sites further includes: A target tracking and recognition unit 104, configured to perform tracking and recognition of the remote monitoring target in multiple real-time monitoring videos based on the multiple target appearance features, select a target monitoring video, and mark a target monitoring area.

[0069] In an embodiment of the present invention, the target tracking and recognition unit 104 generates a tracking and recognition instruction, and then, according to the tracking and recognition instruction, performs feature matching and tracking and recognition of the remote monitoring target in multiple real-time monitoring videos based on the multiple target appearance features, selects a target monitoring video with the remote monitoring target from the multiple real-time monitoring videos, and marks a corresponding target monitoring area from multiple video monitoring areas according to the target monitoring video.

[0070] A remote monitoring display unit 105, configured to create a remote monitoring window, monitor and display the target monitoring video, and perform area highlighting and synchronous display on the construction site model according to the target monitoring area.

[0071] In an embodiment of the present invention, the remote monitoring and display unit 105 creates a remote monitoring window, evenly divides the remote monitoring window into a monitoring sub-window A and a monitoring sub-window B. In the monitoring sub-window A of the remote monitoring window, the target monitoring video is monitored and displayed, and according to the spatial position of the target monitoring area at the road construction site, the construction site model is subjected to area highlighting processing to generate an area highlighted model. Furthermore, in the monitoring sub-window B of the remote monitoring window, the area highlighted model is synchronously displayed, so that the remote management personnel can not only view the target monitoring video of the remote monitoring target, but also clearly understand the position of the remote monitoring target at the road construction site.

[0072] Specifically, Figure 10 FIG. shows a structural block diagram of the remote monitoring and display unit 105 in the system provided by the embodiment of the present invention.

[0073] Among them, in the preferred embodiment provided by the present invention, the remote monitoring and display unit 105 specifically includes: A window creation module 1051, configured to create a remote monitoring window; A monitoring and display module 1052, configured to monitor and display the target monitoring video in the remote monitoring window; A highlighting processing module 1053, configured to perform area highlighting processing on the construction site model according to the target monitoring area to generate an area highlighted model; A synchronous display module 1054, configured to synchronously display the area highlighted model in the remote monitoring window.

[0074] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0075] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0076] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0077] The above embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention should be subject to the appended claims.

[0078] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A remote video monitoring method for road construction sites, characterized in that, The method specifically includes the following steps: Obtain the basic on-site data of the road construction site and construct a construction site model; Determine multiple video monitoring areas in the road construction site, and conduct real-time video monitoring in the multiple video monitoring areas to obtain multiple real-time monitoring videos; Receive remote monitoring requirements, conduct target analysis, determine remote monitoring targets, and obtain multiple target appearance features of the remote monitoring targets; Based on the multiple target appearance features, track and identify the remote monitoring targets in the multiple real-time monitoring videos, select target monitoring videos, and mark target monitoring areas; Create a remote monitoring window, monitor and display the target monitoring videos, and synchronously display the highlighted areas of the construction site model according to the target monitoring areas; The step of obtaining the basic on-site data of the road construction site and constructing a construction site model specifically includes the following steps: Obtain the construction planning information of the road construction; Analyze the construction planning information to determine the road construction site; Obtain the basic on-site data of the road construction site; Perform model processing on the basic on-site data, and construct a construction site model through cascaded convolution.

2. The remote video monitoring method for road construction sites according to claim 1, wherein, The step of performing model processing on the basic on-site data and constructing a construction site model through cascaded convolution is as follows: Receive the basic on-site data and perform noise filtering and format standardization processing to generate standardized data; use a spatial registration algorithm to align the video images and 3D laser point cloud coordinates in the standardized data to obtain spatio-temporally aligned structured data; Extract the mechanical motion trajectory, personnel focus heat map, and cropped relative displacement from the spatio-temporally aligned structured data; Based on the sliding time window mechanism, perform dynamic importance evaluation on the mechanical motion trajectory, personnel focus heat map, and cropped relative displacement, and update the weight value distribution map every preset period to obtain a three-dimensional weight matrix; Process the spatio-temporally aligned structured data and the three-dimensional weight matrix through a cascaded convolution architecture. The shallow network processes the infrared and visible light features in the spatio-temporally aligned structured data to capture tiny visual features, and the deep network extracts macroscopic motion patterns, and finally obtains the output feature tensor; According to the illumination change at the construction site, combine the output feature tensor to dynamically adjust the fusion ratio of the infrared and visible light features. For the image quality degradation caused by extreme weather, use an adversarial generative network for feature restoration compensation to obtain a feature map with enhanced environmental robustness; Use a graph neural network to construct a timestamped three-dimensional topological structure of the construction surface, and perform cross-modal fusion on the feature map with enhanced environmental robustness and the 3D laser point cloud coordinates to construct a four-dimensional spatio-temporal situation model; Compare the current four-dimensional spatio-temporal situation model with the historical four-dimensional spatio-temporal situation model to generate a feature offset report; Filter and construct an incremental training dataset based on the confidence in the feature offset report; use the incremental training dataset to train the current four-dimensional spatio-temporal situation model, and obtain an optimized four-dimensional spatio-temporal situation model. After a preset number of iterations, obtain the final four-dimensional spatio-temporal situation model, and use the final four-dimensional spatio-temporal situation model as the construction site model.

3. The remote video monitoring method for road construction sites according to claim 2, characterized in that, The determination of multiple video monitoring areas in the road construction site, and the real-time video monitoring in the multiple video monitoring areas to obtain multiple real-time monitoring videos specifically includes the following steps: Determine multiple video monitoring areas in the road construction site and generate area monitoring instructions; According to the area monitoring instructions, conduct real-time video monitoring on the multiple video monitoring areas to obtain multiple real-time monitoring videos.

4. The remote video monitoring method for road construction sites according to claim 3, characterized in that, Determine multiple video monitoring areas in the road construction site and generate area monitoring instructions. The specific steps are as follows: Obtain the historical construction accident report and the construction progress plan through the basic on-site data; By analyzing the high-frequency risk points in the historical construction accident report and combining the construction progress plan, establish a dynamic benchmark instruction template including the area risk level and the sensitivity of the operation type; Link the monitoring equipment through the dynamic benchmark instruction template, calibrate the three-dimensional coordinates of the key areas, and then eliminate the visual blind spots caused by equipment occlusion through point cloud reconstruction to generate a monitoring area dataset; The monitoring area dataset includes the actual number of workers in each area, the activity trajectory of heavy machinery, the frequency of illegal operations, and the operation intensity. Determine the high-risk scene features by analyzing the high-frequency risk points in the historical construction accident report; Use a temporal convolutional neural network to analyze the correlation between the frequency of illegal operations and the operation intensity in each area of the monitoring area dataset, and at the same time fuse the high-risk scene features to generate a priority evaluation list; Obtain meteorological warning data through the basic on-site data. The meteorological warning data includes the real-time wind speed monitoring value and the rainfall intensity forecast parameter; According to the high-risk operation areas marked in the priority evaluation list, combine the meteorological warning data to execute a hierarchical response strategy to generate a priority environment adaptive map; The priority environment adaptive map includes the monitoring accuracy of the construction operation area, the infrared coverage radius parameter in the rainstorm environment, and the environmental sensitivity parameter. Based on the monitoring accuracy of the construction operation area and the infrared coverage radius parameter in the rainstorm environment, extract the effective monitoring area parameters of each area, and synchronously associate the time window of the construction progress plan to generate a spatio-temporal coupling queue; The spatio-temporal coupling queue includes spatio-temporal correlation parameters and process sensitivity coefficients. Dynamically fuse the process sensitivity coefficient with the high-risk scene features based on the spatio-temporal correlation parameters, and then combine the environmental sensitivity parameters to generate area monitoring instructions.

5. The remote video monitoring method for road construction sites according to claim 4, wherein The reception of the remote monitoring requirement, the target analysis, the determination of the remote monitoring target, and the acquisition of multiple target appearance features of the remote monitoring target specifically include the following steps: Receive the remote monitoring requirement; Conduct target analysis on the remote monitoring requirement to determine the remote monitoring target; Obtain multiple target backup images of the remote monitoring target from the preset target database; Perform feature recognition on multiple target backup images to obtain multiple target appearance features.

6. The remote video monitoring method for road construction sites according to claim 5, wherein, Perform feature recognition on multiple target backup images to obtain multiple target appearance features. The specific steps are as follows: Determine the feature dimension classification template through a preset target database, read all target backup images, and for each target backup image, establish an analysis channel corresponding to the feature dimension classification template to generate a feature dimension initialization image; Use a deep learning model to perform layer-by-layer feature analysis on each feature dimension initialization image, generate quantization evaluation values on each feature dimension, and obtain an initial evaluation value table, where the initial evaluation value table contains multiple initial evaluation values; Determine the monitoring target category based on the monitoring requirements; perform correlation analysis on the feature dimension initialization images under the same feature dimension through the monitoring target category, calculate the numerical fluctuation law of the initial evaluation values in each feature channel among different images, and assign weights according to the strength of stability to generate a feature stability confidence level; Obtain environmental parameters through the monitoring area dataset. The environmental parameters include light intensity and the concentration of airborne particulate matter. Process the environmental parameters through dynamic feature mapping to obtain dynamic environmental compensation parameters; Combine the construction progress plan, analyze the value decay curve of the target backup images collected at different time periods, and determine the time compensation factor based on the value decay curve of the target backup images collected at different time periods; Obtain the feature template matching the current target backup image, and measure the Bhattacharyya distance distribution between the actually extracted features and the standard features item by item to obtain a feature reference comparison value; For each target backup image, perform non-linear superposition of the initial evaluation value and the feature stability confidence level, and then dynamically adjust the non-linear superposition result using the dynamic environmental compensation parameter to obtain a multi-dimensional fusion feature vector; perform weighted geometric average processing on all multi-dimensional fusion feature vectors using the time compensation factor to obtain a normalized feature vector; Perform difference compensation on the normalized feature vector using the feature reference comparison value to obtain a compensated feature vector; encode the compensated feature vector into a standardized format to obtain a standard feature vector; use the standard feature vector to obtain the target appearance feature.

7. The method for remotely monitoring a road construction site according to claim 6, wherein Based on the multiple target appearance features, in the multiple real-time monitoring videos, perform tracking and recognition of the remote monitoring target, select the target monitoring video, and mark the specific target monitoring area, which specifically includes the following steps: Generate a tracking and recognition instruction; According to the tracking and recognition instruction, based on the multiple target appearance features, perform tracking and recognition of the remote monitoring target in the multiple real-time monitoring videos, and select the target monitoring video; Based on the target monitoring video, mark the corresponding target monitoring area from the multiple video monitoring areas.

8. The method for remotely video monitoring of a road construction site according to claim 7, wherein According to the tracking and recognition instruction, based on the multiple target appearance features, perform tracking and recognition of the remote monitoring target in the multiple real-time monitoring videos, and select the target monitoring video. The specific steps are as follows: Obtain the environmental parameter values of the target monitoring point at preset intervals. The environmental parameter values include dust concentration parameters and light intensity values; perform Gaussian filtering on the dust concentration parameters to obtain the processed dust concentration parameters; convert the light intensity values to obtain the standardized brightness coefficient; obtain the mapping relationship table based on the processed dust concentration parameters and the standardized brightness coefficient; Extract the key frames of each real-time monitoring video stream to obtain data vectors of feature dimensions; obtain the standard features based on the feature dimension classification template; Compare the data vectors of feature dimensions with the standard features dimension by dimension and generate a multi-dimensional feature matching degree scoring matrix; Calculate the dynamic adjustment coefficients of each feature dimension under the current environmental parameter values through the mapping relationship table to obtain the feature dynamic adjustment coefficients; Use the feature dynamic adjustment coefficients to perform non-linear transformation on the matching degree scores to obtain the environment-adaptive feature weights; Obtain the delay data from the acquisition to the processing completion by measuring each real-time monitoring video stream, obtain the delay coefficient through the delay data; obtain the attenuation index through the regional hazard level; Apply exponential attenuation multiplication to the delay coefficient using the attenuation index to obtain the delay compensation coefficient; Obtain the distance attenuation coefficient based on the BIM data, the coordinates of the monitoring device, and the lens parameters of the monitoring device; use the multi-dimensional feature matching degree scoring matrix to non-linearly superimpose the feature matching degree scores of each dimension with the corresponding environment-adaptive feature weights to obtain the feature matching degree score of the environmental impact; Adjust the feature matching degree score of the environmental impact using the delay compensation coefficient to generate the processed matching degree score; optimize the processed matching degree score through the distance attenuation coefficient to obtain the comprehensive matching degree score; Traverse all the comprehensive matching degree scores and select the real-time monitoring video with the highest comprehensive matching degree score as the target monitoring video.

9. The method for remotely video monitoring of a road construction site according to claim 8, wherein, The creation of the remote monitoring window, the monitoring and display of the target monitoring video, and the regional highlighting synchronization display of the construction site model according to the target monitoring area specifically include the following steps: Create a remote monitoring window; In the remote monitoring window, monitor and display the target monitoring video; Perform regional highlighting processing on the construction site model according to the target monitoring area to generate a regional highlighting model; In the remote monitoring window, synchronously display the regional highlighting model.

10. A remote video monitoring system for road construction sites, characterized in that, [[ID= ​ ​ The monitoring target analysis unit is used to receive remote monitoring requirements, conduct target analysis, determine remote monitoring targets, and obtain multiple target appearance features of the remote monitoring targets; The target tracking and recognition unit is used to track and recognize remote monitoring targets in multiple real-time monitoring videos based on the multiple target appearance features, select target monitoring videos, and mark target monitoring areas; The remote monitoring display unit is used to create a remote monitoring window, monitor and display the target monitoring videos, and synchronously display area highlighting of the construction site model according to the target monitoring areas.

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