CN115130881A - Road construction monitoring method and system based on big data - Google Patents
Road construction monitoring method and system based on big data Download PDFInfo
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- CN115130881A CN115130881A CN202210787491.3A CN202210787491A CN115130881A CN 115130881 A CN115130881 A CN 115130881A CN 202210787491 A CN202210787491 A CN 202210787491A CN 115130881 A CN115130881 A CN 115130881A
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- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
Abstract
The invention provides a road construction monitoring method and a system based on big data, which relate to the technical field of road engineering monitoring, and are characterized in that the road construction characteristic information is obtained by analyzing the obtained road construction monitoring video frame by frame, the road construction environment information is acquired by a sensor group, the construction equipment operation parameter information is acquired, the road construction characteristic information, the road construction environment information and the construction equipment operation parameter information are input into an adaptive road construction quality analysis model to obtain a road construction quality evaluation result, the difference value between the road construction quality evaluation result and a road construction quality standard is determined to be used as a construction quality excitation coefficient, and the control management of the road construction state is carried out on the basis of the construction quality excitation coefficient, thereby solving the problems that the road construction control method in the prior art is not intelligent enough and the analysis of the influence factors in the construction process is not deep enough, the technical problem that the road construction state cannot be optimally controlled is solved, and intelligent autonomous monitoring control of road construction is realized.
Description
Technical Field
The invention relates to the technical field of road engineering monitoring, in particular to a road construction monitoring method and system based on big data.
Background
Because daily trip and transportation work etc. all can not leave road traffic facility for demand degree to the traffic field is constantly improving, and simultaneously, the improvement of road use frequency further can influence the degree of wear of road, makes masses more and more high to the quality requirement of road.
Furthermore, multiple factors in the construction process of the road can influence the service life of the road to different degrees, so that the monitoring management of the road construction is the most important factor, and at present, the road construction is mainly constructed in sequence according to construction drawings.
At present, the existing road construction management and control method is not intelligent enough, and cannot carry out optimized management and control on the road construction state due to the fact that the influence factors are deeply analyzed in the construction process.
Disclosure of Invention
The application provides a road construction monitoring method and system based on big data, which are used for solving the technical problems that the existing road construction management and control method in the prior art is not intelligent enough, the analysis of influence factors in the construction process is not deep enough, and the road construction state cannot be optimally managed and controlled.
In view of the above problems, the present application provides a road construction monitoring method and system based on big data.
In a first aspect, the present application provides a road construction monitoring method based on big data, the method including: monitoring the road construction condition through a monitoring device to obtain a road construction monitoring video; analyzing the road construction monitoring video frame by frame to obtain road construction characteristic information; acquiring road construction environment information through a sensor group, wherein the road construction environment information comprises an environment temperature, an environment humidity and a construction position; obtaining operation parameter information of construction equipment; inputting the road construction characteristic information, the road construction environment information and the construction equipment operation parameter information into an adaptive road construction quality analysis model to obtain a road construction quality evaluation result; obtaining a road construction quality standard, and taking the difference value between the road construction quality evaluation result and the road construction quality standard as a construction quality excitation coefficient; and controlling and managing the road construction state based on the construction quality excitation coefficient.
In a second aspect, the present application provides a big data based road construction monitoring system, the system comprising: the construction monitoring module is used for monitoring the road construction condition through the monitoring device to obtain a road construction monitoring video; the video analysis module is used for analyzing the road construction monitoring video frame by frame to obtain road construction characteristic information; the system comprises an information acquisition module, a data processing module and a data processing module, wherein the information acquisition module is used for acquiring road construction environment information through a sensor group, and the road construction environment information comprises environment temperature, environment humidity and construction position; the operation parameter acquisition module is used for acquiring operation parameter information of the construction equipment; the model analysis module is used for inputting the road construction characteristic information, the road construction environment information and the construction equipment operation parameter information into an adaptive road construction quality analysis model to obtain a road construction quality evaluation result; the construction standard acquisition module is used for acquiring a road construction quality standard, and taking the difference value between the road construction quality evaluation result and the road construction quality standard as a construction quality excitation coefficient; and the state management module is used for controlling and managing the road construction state based on the construction quality excitation coefficient.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
according to the road construction monitoring method based on the big data, the monitoring device is used for monitoring the road construction condition to obtain the road construction monitoring video, and the road construction monitoring video is analyzed frame by frame to obtain the road construction characteristic information; acquiring road construction environment information through a sensor group, wherein the road construction environment information comprises an environment temperature, an environment humidity and a construction position; the method comprises the steps of obtaining construction equipment operation parameter information, further inputting the road construction characteristic information, the road construction environment information and the construction equipment operation parameter information into an adaptive road construction quality analysis model, obtaining a road construction quality evaluation result through model analysis simulation, obtaining a road construction quality standard, determining a difference value between the road construction quality evaluation result and the road construction quality standard as a construction quality excitation coefficient, and carrying out control management on a road construction state based on the construction quality excitation coefficient.
Drawings
FIG. 1 is a schematic flow chart of a road construction monitoring method based on big data provided by the present application;
FIG. 2 is a schematic diagram illustrating a road construction characteristic information acquisition process in a road construction monitoring method based on big data according to the present application;
FIG. 3 is a schematic diagram illustrating a process of obtaining a road construction quality evaluation result in a road construction monitoring method based on big data according to the present application;
fig. 4 is a schematic structural diagram of a road construction monitoring system based on big data according to the present application.
Description of reference numerals: the system comprises a construction monitoring module a, a video analysis module b, an information acquisition module c, an operation parameter acquisition module d, a model analysis module e, a construction standard acquisition module f and a state management module g.
Detailed Description
The application provides a road construction monitoring method based on big data, road construction characteristic information is extracted based on a road construction monitoring video, an adaptive road construction quality analysis model is constructed, model simulation analysis is carried out based on the road construction characteristic information, road construction environment information and construction equipment operation parameter information, a road construction quality evaluation result is obtained, mapping and checking are further carried out on the road construction quality standard, a construction quality excitation coefficient is obtained, and then control management is carried out on a road construction state, so that the technical problems that an existing road construction management and control method in the prior art is not intelligent enough, analysis on influence factors in the construction process is not deep enough, and optimization management and control cannot be carried out on the road construction state are solved.
Example one
As shown in fig. 1, the present application provides a road construction monitoring method based on big data, the method includes:
step S100: monitoring the road construction condition through a monitoring device to obtain a road construction monitoring video;
specifically, the road construction monitoring method based on big data, provided by the application, acquires road construction characteristic information, road construction environment information and construction equipment operation parameter information, further performs analysis simulation based on an adaptive road construction quality analysis model to acquire a road construction quality evaluation result, compares the road construction quality evaluation result with a road construction quality standard to determine a construction quality excitation coefficient, and further performs control and management of a road construction state, firstly monitors the road construction condition based on a monitoring device, collects corresponding real-time road construction monitoring videos which cover a plurality of construction steps and relevant details in a road construction process, exemplarily, can perform multi-angle monitoring on the construction condition to enable the collected construction monitoring videos to be complete and the corresponding information coverage degree to be more complete, the accuracy of information extraction analysis can be effectively improved, and a practical foundation is provided for the follow-up extraction of road construction information by performing the real-time acquisition of the road construction monitoring video.
Step S200: analyzing the road construction monitoring video frame by frame to obtain road construction characteristic information;
specifically, the road construction monitoring video is collected to obtain a multi-angle road construction monitoring video set, the road construction monitoring video is further subjected to frame-by-frame analysis, a plurality of specific video pictures are specifically analyzed, the road construction monitoring video set is further screened, repeated information pictures in the multi-angle road construction monitoring video set are abandoned, the rest pictures are subjected to time sequence integration processing, and on the basis, road construction characteristics are extracted, wherein the road construction characteristics comprise underground pipeline layout, supporting engineering, field arrangement and the like, the road construction characteristics of different construction positions and construction time periods have differences, the classification integration processing is carried out on the pictures, the road construction characteristic information is determined to be stored, the later extraction and calling are convenient, and the road construction monitoring video is subjected to frame-by-frame analysis, the integrity of information extraction can be effectively improved, and the final information analysis result is more accurate.
Step S300: acquiring road construction environment information through a sensor group, wherein the road construction environment information comprises an environment temperature, an environment humidity and a construction position;
specifically, the road construction environment information is collected based on a sensor group, the real-time environment temperature, the real-time environment humidity and the construction position in the road construction process are determined, the road construction process is influenced to a certain extent due to the change of environmental factors, illustratively, the operation of construction equipment and the state of workers are influenced by the fluctuation of the environment temperature, and the heat dissipation treatment of the construction equipment, the physical condition of constructors and the like need to be considered in a high-temperature state; the change of the environmental humidity can affect the soil humidity, the equipment running friction degree and the like; the difference of construction positions enables corresponding construction modes to be distinguished, building removal conditions, geological conditions and the like need to be considered, construction progress and construction quality are influenced by the influence factors, real-time environment temperature, real-time environment humidity and construction positions during road construction are collected, information integration processing is further conducted to obtain road construction environment information, and the road construction environment information is stored as road construction quality analysis conditions.
Step S400: obtaining operation parameter information of construction equipment;
specifically, the equipment types in the road construction process are collected, corresponding operation parameters of a plurality of construction equipment are obtained aiming at the construction equipment, the equipment operation parameters comprise equipment operation power, equipment accuracy, equipment size, operation adaptability and the like, the operation parameters of the same construction equipment are different for different external environments and construction progress, the operation parameters of the construction equipment are determined according to the real-time construction process, the obtained equipment operation parameters are classified and integrated based on the equipment types and the time sequence, and are stored as analysis bases of the road construction quality, so that the subsequent road construction quality analysis can be conveniently and directly called.
Step S500: inputting the road construction characteristic information, the road construction environment information and the construction equipment operation parameter information into an adaptive road construction quality analysis model to obtain a road construction quality evaluation result;
specifically, the road construction characteristic information, the road construction environment information and the manual equipment operation information are extracted and called to construct the adaptive road construction quality analysis model, the adaptive road construction quality analysis model is a model for respectively carrying out simulation analysis on the road construction characteristic information, the road construction environment information and the manual equipment operation information to determine the road construction quality, respectively carrying out information corresponding mapping on the road construction characteristic information, the road construction environment information and the manual equipment operation information based on time sequence, and further performing information grouping, further performing model simulation based on the adaptive road construction quality analysis model, acquiring a corresponding model simulation result as the road construction quality evaluation result, and further performing standard judgment on the road construction quality.
Step S600: obtaining a road construction quality standard, and taking the difference value between the road construction quality evaluation result and the road construction quality standard as a construction quality excitation coefficient;
step S700: and controlling and managing the road construction state based on the construction quality excitation coefficient.
Specifically, a road construction quality standard is obtained based on a big data platform, the road construction quality standard refers to a corresponding parameter index for measuring the road construction quality, information simulation is carried out according to the adaptive road construction quality analysis model, the road construction quality evaluation result is obtained, further, the road construction quality standard is used as the comparison information of the road construction quality evaluation result, the road construction quality standard and the road construction quality evaluation result are subjected to overlapped mapping of parameter information, wherein the road construction quality standard corresponds to the parameter information in the road construction quality evaluation result one by one, the difference value between corresponding information is determined and is determined as the construction quality excitation coefficient for storage, and the construction quality excitation coefficient expresses the difference of the road construction quality evaluation result to the road construction quality standard, and performing targeted adjustment on corresponding parameter information based on the construction quality excitation coefficient, and performing control management on the road construction state according to an adjustment result so as to optimize the road construction state.
Further, as shown in fig. 2, the step S200 of analyzing the road construction monitoring video frame by frame to obtain road construction characteristic information further includes:
step S210: performing meshing on each frame of the road construction monitoring video according to a preset size;
step S220: based on the road construction quality standard, presetting a convolution characteristic set;
step S230: performing traversal convolution calculation on the road construction monitoring video subjected to grid division according to the preset convolution feature set to obtain a convolution calculation result;
step S240: and acquiring the road construction characteristic information which accords with a preset convolution value range according to the convolution calculation result.
Specifically, the road construction monitoring video is obtained, the road construction monitoring video is further analyzed frame by frame, image picture extraction is carried out on the road construction video based on video frames, picture division size is preset, extracted image pictures are subjected to grid division based on the preset picture division size, a road construction quality standard is extracted and called according to a big data platform, a preset convolution feature set is obtained based on a convolution layer, the preset convolution feature set comprises the features of construction progress, road construction surface, structure, construction operation and the like, the preset convolution feature set refers to a limited range of convolution features under a standard condition, traversal convolution calculation is carried out on the road construction monitoring video aiming at the divided grids based on the preset convolution feature set to obtain a convolution calculation result, and the weight ratio of the convolution features corresponding to the preset convolution feature set in the road construction monitoring video is determined, further, analyzing and screening the convolution calculation result to determine road construction characteristic information which accords with a preset convolution value range, and further storing the road construction characteristic information as an index of road construction quality evaluation.
Further, as shown in fig. 3, step S500 of the present application further includes:
step S510: normalizing the road construction environment information and the construction equipment operation parameter information to obtain scalar road construction environment information and scalar construction equipment operation parameter information;
step S520: performing clustering integration on the road construction characteristic information, the scalar road construction environment information and the scalar construction equipment operation parameter information to obtain standard road construction characteristic information, standard road construction environment information and standard construction equipment operation parameter information;
step S530: and inputting the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information into the adaptive road construction quality analysis model for analysis.
Further, step S530 of the present application further includes:
step S531: adding data masks to the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information;
step S532: and inputting the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information added with the data mask into the adaptive road construction quality analysis model for training and analysis.
Specifically, the road construction environment information and the construction equipment operation parameter information are called, the parameter information is further normalized, the called original data is standardized to enable multiple indexes contained in the original data to be in the same order of magnitude, so that the scalar road construction environment and the scalar construction equipment operation parameter information are obtained, further, the road construction characteristic information, the scalar road construction environment information and the scalar construction equipment operation parameter information are subjected to clustering integration analysis, the parameter information is classified and integrated again based on the similarity of the internal structures of the information, the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information are obtained, and the information is further input into the adaptive road construction quality analysis model, and performing simulation analysis on corresponding information based on the adaptive road construction quality analysis model to obtain the road construction quality evaluation result, and providing a factual basis for performing optimization management on the road construction state.
Furthermore, the acquired standard road construction characteristic information, the acquired standard road construction environment information and the acquired standard construction equipment operation parameter information are called, data mask is added to the standard road construction characteristic information, binary data is adopted to express the parameter information, the operation state can be determined through bit operation, the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information after the data mask is added are subjected to parameter information training analysis in the adaptive road construction quality analysis model, a corresponding analysis result is acquired as a road construction quality evaluation result, and the road construction quality evaluation result is stored as comparison information, so that subsequent calling is facilitated to perform information correction between the road construction quality evaluation result and the road construction quality standard.
Further, in step S500 of the present application, the method further includes:
step S510-1: constructing a road construction quality analysis model base;
step S520-1: acquiring road construction attribute information;
step S530-1: and calling the adaptive road construction quality analysis model from the road construction quality analysis model library according to the road construction attribute information.
Specifically, the construction of the road construction quality analysis model base is carried out based on a big data platform, the road construction weight analysis model base comprises various types of road construction quality analysis models, the specific analysis simulation can be carried out aiming at various external conditions, the analysis accuracy of the models can be effectively ensured aiming at the dispersion of parameter data, the road construction attribute information is obtained, the road construction attribute information comprises the information of road type, construction mode, breadth and the like, model calling is carried out on the road construction quality analysis model base based on the road construction attribute information, the model with the highest matching degree is determined as the adaptive road construction quality analysis model by matching and checking with the road construction attribute information, the model is further called for simulation analysis, and corresponding matching can be carried out aiming at various construction road attribute information according to the road construction quality analysis model base, the accuracy of the model simulation result can be effectively improved.
Further, in the step S520-1 of obtaining the road construction attribute information, the method further includes:
step S521-1: acquiring basic information of road construction;
step S522-1: classifying the basic road construction information to obtain road construction classification characteristics;
step S523-1: and determining the road construction attribute information based on the road construction classification characteristics.
Specifically, basic information of road construction is collected, the basic information of road construction includes roadbed construction information, pavement construction information, operation information of construction machinery and the like, the obtained basic information of road construction is further identified and classified, corresponding classification results are obtained, and then classification features of road construction are extracted based on the classification results, the classification features of road construction refer to frames for representing type division of the basic information of road construction, information such as road type, construction mode and width of road construction is determined and stored as the attribute information of road construction, and further calling simulation of an adaptive model can be performed according to the attribute information of road construction.
Further, step S500 of the present application further includes:
step S510-2: obtaining a road construction material list;
step S520-2: detecting the material performance of each construction material in the road construction material list to obtain the qualification coefficient of the construction material;
step S530-2: and correcting the road construction quality evaluation result based on the construction material qualification coefficient.
Specifically, a material list of road construction is obtained, the material list of road construction comprises a plurality of building materials such as gravel, asphalt, lime, engineering polymer and the like, performance index standards of the plurality of materials in the material list of road construction are obtained, grading of material qualification coefficients is carried out, the material performance of the plurality of construction materials in the material list of road construction is further detected respectively, the material qualification coefficients are judged based on the performance index standards of corresponding materials, the obtained qualification coefficients of the plurality of materials are integrated to determine the construction material qualification coefficients, the evaluation result of road construction quality is corrected by taking the construction material qualification coefficients as a reference, and the deviation of the evaluation result of road construction quality caused by the performance factors of road construction materials is eliminated, the accuracy of the road construction quality evaluation result is improved.
Example two
Based on the same inventive concept as the road construction monitoring method based on big data in the foregoing embodiment, as shown in fig. 4, the present application provides a road construction monitoring system based on big data, the system includes:
the construction monitoring module a is used for monitoring the road construction condition through a monitoring device to obtain a road construction monitoring video;
the video analysis module b is used for analyzing the road construction monitoring video frame by frame to obtain road construction characteristic information;
the information acquisition module c is used for acquiring and obtaining road construction environment information through a sensor group, and the road construction environment information comprises environment temperature, environment humidity and construction position;
the operation parameter acquisition module d is used for acquiring operation parameter information of the construction equipment;
the model analysis module e is used for inputting the road construction characteristic information, the road construction environment information and the construction equipment operation parameter information into an adaptive road construction quality analysis model to obtain a road construction quality evaluation result;
the construction standard acquisition module f is used for acquiring a road construction quality standard, and taking the difference value between the road construction quality evaluation result and the road construction quality standard as a construction quality excitation coefficient;
and the state management module g is used for controlling and managing the road construction state based on the construction quality excitation coefficient.
Further, the system further comprises:
the size division module is used for carrying out grid division on each frame of the road construction monitoring video according to a preset size;
a convolution characteristic reservation module for reserving a convolution characteristic set based on the road construction quality standard;
the convolution calculation module is used for performing traversal convolution calculation on the road construction monitoring video subjected to grid division according to the preset convolution feature set to obtain a convolution calculation result;
and the construction characteristic acquisition module is used for acquiring the road construction characteristic information which accords with a preset convolution numerical range according to the convolution calculation result.
Further, the system further comprises:
the information processing module is used for carrying out normalization processing on the road construction environment information and the construction equipment operation parameter information to obtain scalar road construction environment information and scalar construction equipment operation parameter information;
the information integration module is used for carrying out clustering integration on the road construction characteristic information, the scalar road construction environment information and the scalar construction equipment operation parameter information to obtain standard road construction characteristic information, standard road construction environment information and standard construction equipment operation parameter information;
and the model analysis module is used for inputting the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information into the adaptive road construction quality analysis model for analysis.
Further, the system further comprises:
the data mask adding module is used for adding a data mask to the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information;
and the model training module is used for inputting the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information which are added with the data mask into the adaptive road construction quality analysis model for training and analysis.
Further, the system further comprises:
the model base construction module is used for constructing a road construction quality analysis model base;
the construction attribute acquisition module is used for acquiring road construction attribute information;
and the model calling module is used for calling the adaptive road construction quality analysis model from the road construction quality analysis model library according to the road construction attribute information.
Further, the system further comprises:
the construction information acquisition module is used for acquiring basic road construction information;
the information classification module is used for classifying the road construction basic information to obtain road construction classification characteristics;
an attribute information determination module to determine the road construction attribute information based on the road construction classification features.
Further, the system further comprises:
the system comprises a bill of material acquisition module, a bill of material acquisition module and a bill of material management module, wherein the bill of material acquisition module is used for acquiring a road construction bill of material;
the performance detection module is used for detecting the material performance of each construction material in the road construction material list to obtain the qualified coefficient of the construction material;
and the result correction module is used for correcting the road construction quality evaluation result based on the construction material qualified coefficient.
In the present specification, through the foregoing detailed description of the road construction monitoring method based on big data, it is clear to those skilled in the art that the road construction monitoring method and system based on big data in the present embodiment are known.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A road construction monitoring method based on big data is characterized by comprising the following steps:
monitoring the road construction condition through a monitoring device to obtain a road construction monitoring video;
analyzing the road construction monitoring video frame by frame to obtain road construction characteristic information;
acquiring road construction environment information through a sensor group, wherein the road construction environment information comprises an environment temperature, an environment humidity and a construction position;
obtaining operation parameter information of construction equipment;
inputting the road construction characteristic information, the road construction environment information and the construction equipment operation parameter information into an adaptive road construction quality analysis model to obtain a road construction quality evaluation result;
obtaining a road construction quality standard, and taking the difference value between the road construction quality evaluation result and the road construction quality standard as a construction quality excitation coefficient;
and controlling and managing the road construction state based on the construction quality excitation coefficient.
2. The method of claim 1, wherein the analyzing the road construction monitoring video frame by frame to obtain road construction characteristic information comprises:
performing meshing on each frame of the road construction monitoring video according to a preset size;
based on the road construction quality standard, presetting a convolution characteristic set;
performing traversal convolution calculation on the road construction monitoring video subjected to grid division according to the preset convolution feature set to obtain a convolution calculation result;
and acquiring the road construction characteristic information which accords with a preset convolution value range according to the convolution calculation result.
3. The method of claim 1, wherein the method comprises:
normalizing the road construction environment information and the construction equipment operation parameter information to obtain scalar road construction environment information and scalar construction equipment operation parameter information;
performing clustering integration on the road construction characteristic information, the scalar road construction environment information and the scalar construction equipment operation parameter information to obtain standard road construction characteristic information, standard road construction environment information and standard construction equipment operation parameter information;
and inputting the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information into the adaptive road construction quality analysis model for analysis.
4. The method of claim 3, wherein the method comprises:
adding data masks to the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information;
and inputting the standard road construction characteristic information, the standard road construction environment information and the standard construction equipment operation parameter information added with the data mask into the adaptive road construction quality analysis model for training and analysis.
5. The method of claim 1, wherein the method comprises:
constructing a road construction quality analysis model base;
acquiring road construction attribute information;
and calling the adaptive road construction quality analysis model from the road construction quality analysis model library according to the road construction attribute information.
6. The method of claim 5, wherein the obtaining road construction property information comprises:
acquiring basic information of road construction;
classifying the road construction basic information to obtain road construction classification characteristics;
and determining the road construction attribute information based on the road construction classification characteristics.
7. The method of claim 1, wherein the method comprises:
obtaining a road construction material list;
detecting the material performance of each construction material in the road construction material list to obtain the qualification coefficient of the construction material;
and correcting the road construction quality evaluation result based on the construction material qualification coefficient.
8. A big data based roadway construction monitoring system, the system comprising:
the construction monitoring module is used for monitoring the road construction condition through the monitoring device to obtain a road construction monitoring video;
the video analysis module is used for carrying out frame-by-frame analysis on the road construction monitoring video to obtain road construction characteristic information;
the system comprises an information acquisition module, a data processing module and a data processing module, wherein the information acquisition module is used for acquiring road construction environment information through a sensor group, and the road construction environment information comprises environment temperature, environment humidity and construction position;
the operation parameter acquisition module is used for acquiring operation parameter information of the construction equipment;
the model analysis module is used for inputting the road construction characteristic information, the road construction environment information and the construction equipment operation parameter information into an adaptive road construction quality analysis model to obtain a road construction quality evaluation result;
the construction standard acquisition module is used for acquiring a road construction quality standard, and taking the difference value between the road construction quality evaluation result and the road construction quality standard as a construction quality excitation coefficient;
and the state management module is used for controlling and managing the road construction state based on the construction quality excitation coefficient.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210787491.3A CN115130881A (en) | 2022-07-06 | 2022-07-06 | Road construction monitoring method and system based on big data |
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| CN202210787491.3A CN115130881A (en) | 2022-07-06 | 2022-07-06 | Road construction monitoring method and system based on big data |
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| CN115130881A true CN115130881A (en) | 2022-09-30 |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115452127A (en) * | 2022-11-11 | 2022-12-09 | 日照市计量科学研究院 | Gear hobbing machine main shaft vibration laser testing device |
| CN115796608A (en) * | 2023-02-06 | 2023-03-14 | 北京万赋互联网科技集团有限公司 | Building construction wind control management method and system based on portable interaction |
| CN116882709A (en) * | 2023-09-05 | 2023-10-13 | 深圳市睿拓新科技有限公司 | Road construction intelligent supervision method based on big data analysis and storage medium |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115452127A (en) * | 2022-11-11 | 2022-12-09 | 日照市计量科学研究院 | Gear hobbing machine main shaft vibration laser testing device |
| CN115452127B (en) * | 2022-11-11 | 2023-03-03 | 日照市计量科学研究院 | Gear hobbing machine main shaft vibration laser testing device |
| CN115796608A (en) * | 2023-02-06 | 2023-03-14 | 北京万赋互联网科技集团有限公司 | Building construction wind control management method and system based on portable interaction |
| CN116882709A (en) * | 2023-09-05 | 2023-10-13 | 深圳市睿拓新科技有限公司 | Road construction intelligent supervision method based on big data analysis and storage medium |
| CN116882709B (en) * | 2023-09-05 | 2023-12-01 | 深圳市睿拓新科技有限公司 | Road construction intelligent supervision method based on big data analysis and storage medium |
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