Intelligent perception-based road construction progress accurate monitoring and scheduling method and system

Abstract

This invention belongs to the field of construction scheduling technology. It provides a method and system for precise monitoring and scheduling of road construction progress based on intelligent perception. The method includes: constructing a construction constraint table by analyzing construction drawings and a 3D information model; collecting engineering quantities and calculating progress deviation rates using a 3D point cloud registration algorithm; establishing unique identifiers for overlapping structural sub-units to construct progress traceability chains and networks; extracting cross-chain branch sub-chains based on resource intersection, spatial proximity ratio, and time window overlap ratio; and identifying resource competition points and urgent demand points through equipment reuse rate and collaborative urgency index. Resources are dynamically allocated by constructing a resource scheduling model. The system includes a constraint construction module, a deviation acquisition module, a progress traceability module, a scheduling analysis module, and a resource allocation module. This invention constructs a closed-loop scheme for construction monitoring and scheduling, improving the accuracy of construction progress control and resource utilization efficiency.

Description

Technical Field

[0001] This invention belongs to the field of construction scheduling technology, specifically a method and system for precise monitoring and scheduling of road construction progress based on intelligent sensing. Background Technology

[0002] Road construction is a core component of urban infrastructure development, and the scientific management of its progress and resource allocation directly impacts project quality, schedule, and cost. Traditional road construction management relies on manual inspections, two-dimensional drawing annotations, and experience-based scheduling, which has many shortcomings.

[0003] Existing technologies struggle to identify overlapping structures (such as the spatial overlap between the subgrade and the base course) and concealed structures (such as underground pipeline burial and pipeline crossings) in road construction. This makes it impossible to quantify the degree of spatial overlap (such as volume ratio and projected area) of overlapping structures, resulting in the absence of key monitoring nodes and potential quality hazards such as poor interlayer bonding. Furthermore, parameters such as the burial depth and soil cover type of concealed structures rely on manual recording and lack automated traceability methods, making it difficult to quickly locate the root cause when problems such as leakage or misalignment occur.

[0004] Existing construction management technologies lack the ability to automatically analyze the transmission path of deviations. A single schedule deviation may cause global impact through the logical chain of processes (such as delays in base course construction leading to delays in surface course paving). However, traditional methods are difficult to quickly locate related sub-units, resulting in high traceability costs. Existing technologies rely on manual experience for resource allocation (such as pavers and material transportation), lacking quantitative analysis of cross-regional and cross-process resource competition points (such as equipment reuse rate and work surface space conflicts). This can easily lead to idle equipment or imbalanced material supply, resulting in project delays and cost waste.

[0005] Therefore, the present invention provides a method and system for precise monitoring and scheduling of road construction progress based on intelligent sensing. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0007] The technical solution adopted by this invention to solve its technical problem is: a method and system for precise monitoring and scheduling of road construction progress based on intelligent sensing, the method comprising:

[0008] The engineering quantities of different levels of road construction were collected using a 3D point cloud registration algorithm, and the progress deviation rate was obtained by analyzing the construction deviation.

[0009] Obtain the schedule deviation ratio of overlapping structural sub-units and construct a road construction schedule traceability chain. By performing deviation transmission analysis on the overlapping structure of road construction, extract the schedule traceability sub-chain. Then, by combining the spatial coordinates and process logic of the three-dimensional information model, analyze the transmission relationship of the schedule traceability sub-chain through the association rule algorithm and construct a schedule traceability network.

[0010] Extract the cross-chain branch sub-chains of the progress tracking network, perform resource scheduling analysis on the cross-chain branch sub-chains, identify the resource competition points of the cross-chain branch sub-chains, perform collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chains.

[0011] Obtain construction scheduling resources for urgent needs, establish a resource allocation group, construct a resource scheduling model and input it into the resource allocation group to realize resource allocation for overlapping road construction structures.

[0012] Furthermore, road construction drawings and 3D information models are acquired, and explicit analysis of the construction drawings and 3D information models is performed through intelligent perception algorithms to identify overlapping and hidden structural units in the road construction process, extract construction characteristic parameters of overlapping and hidden structures, and construct a construction constraint table.

[0013] Furthermore, the method for conducting the construction deviation analysis is as follows:

[0014] Obtain the three-dimensional information model of all levels of road construction structure, and match the three-dimensional information model of the structure with the construction constraint table to obtain the matching road construction structure;

[0015] Obtain the construction quantities at different levels and their corresponding time windows, retrieve the time window for the current construction quantity from the construction constraint table, calculate the deviation ratio, and obtain the progress deviation ratio of the construction progress.

[0016] The hierarchical structure includes: surface structure, hidden structure, and overlapping structure.

[0017] Furthermore, the method for obtaining the construction quantities at different levels is as follows:

[0018] The construction volume of the road construction surface structure was collected using a 3D point cloud registration algorithm.

[0019] For concealed structures in road construction, the construction workload of concealed structures in road construction is determined by combining the burial depth and location in the construction constraint table.

[0020] To calculate the construction workload of overlapping structures in road construction, road construction data is obtained and verified using a three-dimensional information model.

[0021] Furthermore, the progress tracking network is constructed as follows:

[0022] The sub-units of overlapping structures with negative schedule deviation rates are obtained from the road construction progress traceability chain to obtain the schedule lag unit;

[0023] Based on the traceability chain of road construction, the schedule deviation rate of the adjacent sub-units of the schedule lagging unit is obtained downwards. The deviation ratio between the schedule deviation rate of the schedule lagging unit and the schedule deviation rate of the adjacent sub-unit is calculated to obtain the deviation transmission rate.

[0024] Based on the deviation transmission rate, the progress traceability sub-chain of multiple sub-units of the progress traceability chain is extracted, and the progress traceability sub-chain of all overlapping structures of road construction is obtained.

[0025] A correlation analysis is performed on all the progress traceability sub-chains of the structure, and the progress traceability sub-chains with correlation are connected through a branch structure to form a progress traceability network.

[0026] Furthermore, the method for obtaining the construction progress traceability chain is as follows:

[0027] Obtain the sub-units of each overlapping structure in road construction and establish a unique identification system;

[0028] The traceability chain for road construction is determined according to the construction sequence of each sub-unit of the overlapping structure;

[0029] Obtain the schedule deviation ratio of each sub-unit of the overlapping structure and couple it with the road construction schedule traceability chain to construct the road construction schedule traceability chain.

[0030] Furthermore, the method for identifying the resource contention points of the cross-chain branch sub-chains is as follows:

[0031] By constructing a graph structure for the progress tracking network, the directed edges of the overlapping sub-units represent the transmission relationships;

[0032] A sub-chain filtering algorithm is established based on sub-chain filtering conditions to extract cross-chain branch sub-chains from the graph structure of the progress tracking network.

[0033] Obtain the device reuse rate and time window overlap ratio within the overlap period between cross-chain branch sub-chains and adjacent cross-chain branch sub-chains, establish a resource competition analysis model, and identify resource competition points of cross-chain branch sub-chains.

[0034] Furthermore, the resource competition analysis model is established as follows:

[0035] The resource competition analysis model is established by obtaining the time window overlap duration, time window overlap ratio, and equipment reuse rate of the cross-chain branch sub-chain and its adjacent sub-chain.

[0036] A two-dimensional resource competition analysis model is established with the overlap ratio of time windows as the horizontal axis and the equipment reuse rate as the vertical axis.

[0037] Furthermore, the method for determining the urgent need points of the cross-chain branch sub-chains is as follows:

[0038] The effective reuse rate is obtained by effectively screening the equipment reuse rate of resource competition points within the overlapping time period.

[0039] The overlap ratio and effective reuse rate of the resource competition points in the time window are normalized respectively. The product of the normalized overlap ratio and the reciprocal of the effective reuse rate is then used to obtain the collaborative urgency index.

[0040] Based on the collaborative urgency index, all competing resource points are screened to obtain urgent demand points.

[0041] A road construction progress precision monitoring and scheduling system based on intelligent sensing includes the following modules:

[0042] Constraint Construction Module: Used to acquire road construction drawings and 3D information models, perform explicit analysis on the construction drawings and 3D information models through intelligent perception algorithms, identify overlapping and hidden structural units in the road construction process, extract construction feature parameters of overlapping and hidden structures, and construct a construction constraint table;

[0043] Deviation Acquisition Module: Utilizes a 3D point cloud registration algorithm to collect engineering quantities at different levels of road construction and performs construction deviation analysis to obtain the schedule deviation rate;

[0044] Progress tracking module: used to obtain the progress deviation ratio of overlapping structural sub-units and construct a road construction progress tracking chain. By performing deviation transmission analysis on the overlapping structure of road construction, the progress tracking sub-chain is extracted. Then, combined with the spatial coordinates and process logic of the three-dimensional information model, the transmission relationship of the progress tracking sub-chain is analyzed through the association rule algorithm to construct a progress tracking network.

[0045] Scheduling and Analysis Module: Used to extract cross-chain branch sub-chains of the progress tracking network, perform resource scheduling analysis on the cross-chain branch sub-chains, identify resource contention points of the cross-chain branch sub-chains, perform collaborative urgency analysis on the resource contention points, and determine the urgent demand points of the cross-chain branch sub-chains.

[0046] Resource allocation module: Acquire construction scheduling resources for urgent needs, establish resource allocation groups, construct resource scheduling models and input them into resource allocation groups to realize resource allocation for overlapping road construction structures.

[0047] The beneficial effects of this invention are as follows:

[0048] 1. Utilizing 3D information models and construction drawings, intelligently perceive overlapping (e.g., multi-layer paving structures) and concealed (e.g., underground pipelines) structural units in road construction, quantify the degree of spatial overlap (overlap volume ratio) and concealment level (cover thickness, burial depth), and construct a construction constraint table containing spatial, temporal, and material parameters to provide a structured data benchmark for quality control and quantity measurement; calibrate measured data through 3D point cloud registration algorithms to achieve quantity collection for surface, concealed, and overlapping structures; and calculate the progress deviation rate of surface, concealed, and overlapping layers based on the time window constraints of the construction constraint table, enabling real-time feedback on the difference between construction progress and the plan, providing data support for dynamic adjustments.

[0049] 2. By constructing a progress traceability chain through a unique identifier system and process logic, and using the deviation transmission rate as an indicator, a graph theory algorithm is used to extract progress traceability sub-chains. This facilitates the visualization of the path from a single deviation source to the global impact, shortening the problem localization time. Combining the spatial coordinates of the 3D model with the process logic, a progress traceability network is constructed through an association rule algorithm to identify deviation transmission patterns and support multi-level and cross-regional progress impact analysis. Based on multi-dimensional conditions such as resource intersection, spatial proximity ratio (work surface overlap), and time window overlap ratio, cross-chain branch sub-chains are automatically extracted to identify resource competition points with high equipment reuse rates and significant time window overlaps, thus locating scheduling bottlenecks.

[0050] 3. Construct a resource scheduling model using a genetic algorithm. With time and space constraints and total resource quantity as input, minimize the cost of construction delays or resource idleness, and output the optimal solutions such as equipment scheduling schedules and material transportation routes. Link the model with IoT data to dynamically correct it and achieve dynamic balance of construction scheduling resources. Attached Figure Description

[0051] The invention will now be further described with reference to the accompanying drawings.

[0052] Figure 1 This is a flowchart of the method for precise monitoring and scheduling of road construction progress based on intelligent sensing, as described in an embodiment of the present invention.

[0053] Figure 2 This is a flowchart illustrating the construction method of the road construction progress traceability chain as described in an embodiment of the present invention;

[0054] Figure 3 This is an architecture diagram of the intelligent sensing-based road construction progress precise monitoring and scheduling system module described in an embodiment of the present invention. Detailed Implementation

[0055] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0056] In road construction, concealed structures (such as underground pipelines) and overlapping structures (such as multi-layer paving layers) are difficult to identify using traditional management methods due to their hidden spatial locations and complex procedural logic. This can lead to problems such as difficulty in tracing quality hazards, large errors in quantity measurement, and delayed progress control. Ming utilizes technologies such as a lightweight 3D Information Modeling (BIM) engine, graph neural networks, and 3D point cloud registration to automatically identify these two types of structures and construct a construction constraint table containing spatiotemporal and material parameters. This enables data-driven processes from design analysis to resource scheduling, solving the technical bottlenecks of traditional methods in structural feature quantification, deviation tracing, and dynamic collaborative scheduling. It provides an intelligent solution for refined management of road construction.

[0057] Example 1

[0058] Please see Figure 1 As shown in the embodiment of the present invention, the method for precise monitoring and scheduling of road construction progress based on intelligent sensing includes the following steps:

[0059] Step 1: Obtain road construction drawings and 3D information models. Use intelligent perception algorithms to perform explicit analysis on the construction drawings and 3D information models to identify overlapping and hidden structural units in the road construction process, extract construction characteristic parameters of overlapping and hidden structures, and construct a construction constraint table.

[0060] The method of explicitly analyzing construction drawings and 3D information models using intelligent perception algorithms is as follows:

[0061] Preferably, the road construction drawings and three-dimensional information model (BIM) are loaded through the BIM lightweight engine, and the spatial coordinates, geometric dimensions, material properties and construction sequence constraints of each component in the model are extracted using IFC standard parsing technology to construct a three-dimensional semantic network containing structural layer relationships.

[0062] Using spatial Boolean operation algorithms, the spatial overlapping areas of multi-layer paving structures (such as subgrade and base course) are intelligently perceived. Combined with the process flow diagram in the construction organization design, the design location and burial depth of hidden structural units such as pipeline backfilling and underground pipeline intersections are identified.

[0063] For overlapping structures, the degree of overlap is quantified and key monitoring nodes are marked by calculating the proportion of the spatial overlap volume and projected area between components;

[0064] For concealed structures, concealed feature parameters such as soil cover thickness and wrapping material are extracted based on the design specifications. A multi-dimensional feature database containing "structure type - spatial location - concealment level" is established. Finally, the graph neural network (GNN) is used to realize the automatic identification and labeling of overlapping and concealed structural units, providing construction feature parameters and monitoring targets for the subsequent deployment of intelligent sensing systems.

[0065] The construction characteristic parameters include: spatial characteristic parameters, temporal characteristic parameters, and material characteristic parameters of overlapping and concealed structures;

[0066] It should be noted that the spatial characteristic parameters include: coordinates, dimensions, burial depth, and percentage of overlapping volume of the overlapping and concealed structures;

[0067] Time characteristic parameters include: start and end time of the process, time window constraints of the construction workload, interval between adjacent processes, and logical constraints of the process;

[0068] Material characteristic parameters include: component material, soil cover type, and compaction standard;

[0069] Construct a construction constraint table that includes construction characteristic parameters of overlapping and concealed structural units;

[0070] Understandably, the construction constraint table is used to link design parameters with construction process control indicators, providing a structured data benchmark for intelligent scheduling systems to perform process logic verification, resource allocation optimization, and schedule deviation analysis. This is beneficial for achieving quality control and quantity measurement of concealed and overlapping structures during construction.

[0071] Step 2: Use a 3D point cloud registration algorithm to collect the engineering quantities of different levels of road construction and perform construction deviation analysis to obtain the schedule deviation rate;

[0072] Obtain the three-dimensional information model of all levels of road construction structure, and match the three-dimensional information model of the structure with the construction constraint table to obtain the matching road construction structure;

[0073] The hierarchical structure includes: surface structure, hidden structure, and overlapping structure;

[0074] Based on matching the corresponding road construction structure, the construction volume of the road construction surface structure is collected by a 3D point cloud registration algorithm.

[0075] The methods for obtaining the construction quantities of concealed structures and overlapping structures are as follows:

[0076] S1. For the concealed structures in road construction, determine the construction quantity of the concealed structures in road construction by combining the burial depth and location in the construction constraint table.

[0077] For example, for concealed pipeline backfilling works, the design burial depth (H) is combined with the construction constraint table. d The pipe diameter (D) is connected to the coordinates of multiple RFID tag installation locations collected in real time, and the actual length (L) of the laid pipe is calculated based on the distance of the connection. r ), and obtain the density difference before and after compaction of the concealed structure. Through the formula: Obtain the construction volume V of pipeline backfilling hid ;

[0078] in, The design density is the density of the road construction design drawings, where π is the mathematical constant pi.

[0079] S2. For the construction volume of overlapping structures in road construction, obtain road construction data and combine it with three-dimensional information model verification and analysis to calculate the construction volume of overlapping structures.

[0080] The model validation analysis method is as follows:

[0081] S201: Calibrate the three-dimensional information model of the overlapping structure with the measured coordinates of the overlapping structure to determine the construction boundary of the overlapping structure;

[0082] Preferably, a 3D point cloud registration algorithm is used to unify the spatiotemporal reference of the overlapping structural coordinate data of the structural layer surface point cloud acquired by the laser scanner with the BIM model:

[0083] One method for unifying the spatiotemporal reference is to select or automatically identify the same feature points (such as the internal and external corners of the structural layer and the endpoints of the joints) in the model and the measured data, and establish an initial matching pair.

[0084] Then, based on the least squares method, the transformation parameters (translation, rotation, scaling) are optimized to transform the measured coordinates of the initial matching pair from the local coordinate system to the global coordinate system of the BIM model. After calibration, the construction boundary of the overlapping structure is extracted by the point cloud and the contour line of the model.

[0085] S202. Combine the construction boundaries of the overlapping structure to perform spatial intersection analysis on the three-dimensional information model and detect the geometric overlap range of the structural layers adjacent to the overlapping structure.

[0086] Preferably, the spatial analysis module of BIM software is used to take the calibrated construction boundary of the overlapping structure as the reference geometric entity and perform Boolean intersection operation with the three-dimensional model of the adjacent structural layer to obtain the geometric overlap range.

[0087] S203. Based on the geometric overlap range, calculate the volume of the overlapping layer to obtain the construction quantity of the overlapping structure;

[0088] The method for obtaining the construction schedule deviation rate is as follows:

[0089] Obtain time windows for different structural levels from the construction constraint table;

[0090] Based on the construction quantities of surface structure layers, hidden structures, and overlapping structures, as well as the corresponding time windows, the time windows for the construction quantities of the corresponding structural layers are obtained from the construction constraint table, and the deviation ratio is calculated to obtain the progress deviation ratio of the construction progress.

[0091] The technical solution of this embodiment is as follows: Obtain road construction drawings and a 3D information model; perform explicit analysis on the construction drawings and the 3D information model using an intelligent perception algorithm to determine overlapping and hidden structural units in the road construction process; extract construction characteristic parameters of overlapping and hidden structures to construct a construction constraint table; use a 3D point cloud registration algorithm to collect the engineering quantities of different layers of road construction structures and perform construction deviation analysis to obtain the progress deviation rate; based on the time window constraints of the construction constraint table, calculate the progress deviation rates of the surface layer, hidden layer, and overlapping layer, which can provide real-time feedback on the difference between the construction progress and the plan, providing data support for dynamic adjustment.

[0092] Example 2

[0093] like Figure 1 As shown, the method for precise monitoring and scheduling of road construction progress based on intelligent sensing also includes the following steps:

[0094] Step 3: Obtain the schedule deviation ratio of overlapping structural sub-units and construct a road construction schedule traceability chain. By performing deviation transmission analysis on the overlapping structure of road construction, extract the schedule traceability sub-chain. Then, by combining the spatial coordinates of the three-dimensional information model and the process logic, analyze the transmission relationship of the schedule traceability sub-chain through the association rule algorithm and construct a schedule traceability network.

[0095] like Figure 2 As shown, the road construction progress traceability chain is constructed as follows:

[0096] A1. Obtain the sub-units of each overlapping structure in road construction and establish a unique identification system;

[0097] It should be explained that each overlapping structure in road construction contains multiple sub-units;

[0098] Assign a global construction identifier to each sub-unit of the overlapping structure to establish a unique identification system;

[0099] A2. Determine the traceability chain for road construction according to the construction sequence of each sub-unit of the overlapping structure;

[0100] A3. Obtain the progress deviation ratio of each sub-unit of the overlapping structure and couple it with the road construction progress traceability chain to construct the road construction progress traceability chain.

[0101] For example, the base layer is divided into sub-units "JC-01" (K0+000-K0+500 segment) and "JC-02" (K0+500-K1+000 segment) according to construction sections, and the surface layer is divided into "MC-01" (corresponding to base layer JC-01 segment) and "MC-02" (corresponding to base layer JC-02 segment). A globally unique identifier such as "JC-01-20250520" and "MC-01-20250521" is assigned to each sub-unit to establish an identification system; according to the construction sequence "JC-000-K0+500-K0+500-K1+000-K1+000", the surface layer is divided into sub-units "JC-01-20250520" and "MC-01-20250521" to establish an identification system. The sequence of the traceability chain is determined by “1→JC-02→MC-01→MC-02”; if the progress deviation ratio of JC-01 is -15% (lagging), JC-02 is -10%, MC-01 is -8%, and MC-02 is -5%, the deviation ratio of each sub-unit is coupled with its sequence in the traceability chain to form a progress traceability chain containing “JC-01 (-15%) → JC-02 (-10%) → MC-01 (-8%) → MC-02 (-5%)”. The progress traceability chain reflects the transmission path of the deviation along the construction sequence.

[0102] Among them, the method for performing deviation transmission analysis on overlapping structures in road construction and extracting progress traceability sub-chains is as follows:

[0103] The sub-units of overlapping structures with negative schedule deviation rates are obtained from the road construction progress traceability chain to obtain the schedule lag unit;

[0104] Based on the traceability chain of road construction, the schedule deviation rate of the adjacent sub-units of the schedule lagging unit is obtained downwards. The deviation ratio between the schedule deviation rate of the schedule lagging unit and the schedule deviation rate of the adjacent sub-unit is calculated to obtain the deviation transmission rate.

[0105] Based on the deviation transmission rate, the progress traceability sub-chain of multiple sub-units of the progress traceability chain is extracted, and the progress traceability sub-chain of all overlapping structures of road construction is obtained.

[0106] Understandably, based on the deviation transmission rate, the progress traceability sub-chain is extracted. Taking the progress lag unit as the core, the process logic network is traversed through graph theory algorithm: First, the sub-units with direct influence are selected according to the value of the deviation transmission rate (such as β=1 indicating strong transmission). The construction timestamp, spatial coordinates and deviation data of the sub-unit are associated with its unique identifier. A directed acyclic graph is constructed according to the process sequence. The single influence path is extracted as the progress traceability sub-chain through depth-first search.

[0107] For all overlapping structure progress traceability sub-chains, it is necessary to first identify the overlapping structure type (such as base layer-surface layer overlap) through the 3D information model and construction constraint table, and then use the structure ID as the index to batch filter the sub-units belonging to this type, and aggregate them according to time window constraints and transmission relationships to generate a hierarchical progress traceability sub-chain set, so as to realize the visualization of the traceability path from a single deviation to the global impact.

[0108] The method for analyzing the propagation relationship of the progress tracking sub-chain using the association rule algorithm is as follows:

[0109] A correlation analysis is performed on all the progress traceability sub-chains of the structure, and the progress traceability sub-chains with correlation are connected through a branch structure to form a progress traceability network;

[0110] Those skilled in the art will understand that a sub-chain spatial index is constructed based on the spatial coordinates (such as mileage station number and structural layer elevation) of a three-dimensional information model, and physically associated sub-chain nodes are identified through geometric overlap detection (such as intersection and inclusion relationships).

[0111] Simultaneously, the temporal transmission relationship between sub-chains is extracted using the process logic of road construction (such as multiple sub-chains sharing the same immediate preceding process). The sub-chains are abstracted into directed edges (containing deviation transmission rate attributes) and sub-units are nodes (containing ID, type, and spatiotemporal coordinate attributes) using the Neo4j algorithm. The transmission mode of cross-schedule traceability sub-chains is analyzed using the Apriori association rule algorithm (such as the association rule of base layer lag → multi-segment surface layer synchronization delay).

[0112] Using a tree-like hybrid diagram as a branch structure, the project dynamically connects the progress traceability sub-chains with direct and indirect relationships, forming a multi-level progress traceability network that includes "deviation source - transmission path - scope of influence". The project also dynamically displays the chain reaction and its impact on road construction through a visualization engine.

[0113] It needs to be explained that the purpose of establishing a progress tracking network is:

[0114] Function 1: Locating the source of deviation: By using the directed connection of the progress traceability sub-chain (such as associating the sub-unit ID with the timestamp and deviation data), the unit with the lagging progress and its directly or indirectly affected downstream sub-units can be located, thus shortening the problem location time.

[0115] Function 2: Visualizing the transmission path: The tree-like hybrid diagram dynamically displays the "deviation source - transmission path - scope of impact", intuitively presenting the chain effect caused by spatial overlap (such as the overlap of adjacent work surfaces) and temporal logic (such as the delay of the preceding process), helping managers to predict the trend of risk spread;

[0116] Thirdly, it supports cross-chain collaborative analysis: by mining the transmission patterns across sub-chains through association rule algorithms (such as the correlation between the lag of multiple base layers and the synchronization delay of the surface layer), it provides "deviation transmission priority" data for the resource scheduling model, realizes the management upgrade from passive response to active prevention, and improves the intelligence and refinement of construction progress control.

[0117] Step 4: Extract the cross-chain branch sub-chains of the progress tracking network, perform resource scheduling analysis on the cross-chain branch sub-chains, identify the resource competition points of the cross-chain branch sub-chains, perform collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chains.

[0118] The method for extracting cross-chain branch sub-chains from the progress tracking network is as follows:

[0119] By constructing a graph structure for the progress tracking network, the directed edges of the overlapping sub-units represent the transmission relationships;

[0120] The transmission relationships include: the transmission order of different sub-units in the time dimension, the transmission relationship of spatial overlap of sub-units, the deviation transmission rate between different sub-units, and the process logic constraints between construction constraint tables;

[0121] A sub-chain filtering algorithm is established based on sub-chain filtering conditions to extract cross-chain branch sub-chains from the graph structure of the progress tracking network.

[0122] The subchain selection criteria include:

[0123] B1. There is resource overlap. Different progress tracking subchains have resource overlap, that is, different road construction equipment and materials are applied for by multiple progress tracking subchains.

[0124] For example, a road paver is used by multiple progress tracking subchains;

[0125] B2. The spatial proximity ratio is obtained by calculating the overlap of adjacent progress tracing sub-chain work surfaces with branch structures.

[0126] Preferably, by formula: Obtain the spatial proximity ratio S ratio ;

[0127] Among them, V a V b Let a and b represent the volumes of two adjacent progress tracking subchains, respectively. This indicates the overlap volume of adjacent progress tracking sub-chain operation surfaces;

[0128] B3. Calculate the degree of overlap of time window constraints between adjacent progress tracking subchains to obtain the time window overlap ratio;

[0129] Preferably, the time windows of adjacent progress tracking sub-chains are obtained, and the overlap ratio of the time windows is calculated to obtain the time window overlap ratio;

[0130] For example, the time window of the progress tracking sub-chain a is [T a_start T a_end The time window for the progress tracking subchain b is [T]. b_start Tb_end ];

[0131] Through the formula: Get the overlap duration T over ;

[0132] Through the formula: Obtain the overlap ratio T of the time window ratio ;

[0133] Those skilled in the art will understand that the base subchain screening algorithm achieves cross-chain branch subchain extraction through graph traversal, multi-dimensional conditional filtering, and cluster analysis: by traversing the graph structure of the progress tracking network, for each subchain node, the algorithm matches adjacent nodes with resource intersection (B1) through a hash table.

[0134] The spatial proximity ratio (B2) is obtained by calculating the ratio of the overlapping volume of adjacent node work surfaces to the total volume using the BIM spatial analysis interface. At the same time, the overlap duration ratio (B3) is obtained by parsing the time window field. By setting different thresholds (such as resource intersection ≥ 1 type, spatial proximity ratio > 10%, and time window overlap ratio > 20%), node pairs that meet the conditions are filtered. Finally, the label propagation algorithm (LPA) is used to cluster the filtered nodes to generate cross-chain branch subgraphs containing resource, spatial, and temporal associations, thereby realizing the automatic extraction of cross-chain branch subgraphs.

[0135] It should be explained that the role of identifying cross-chain sub-chains is to locate complex conflict scenarios caused by resource, spatial, and temporal relationships in road construction. By filtering sub-chain combinations with resource overlap (such as shared pavers), overlapping spatial work surfaces (such as overlapping adjacent construction sections), and overlapping time windows, the spatiotemporal conflict intensity of resource competition points (such as equipment reuse rate and time window overlap ratio) is quantified. This provides target objects for subsequent resource scheduling analysis, enabling the system to identify urgent needs that require priority coordination. Then, through the resource allocation model, the spatiotemporal allocation of equipment, materials, and manpower is optimized to avoid cross-process and cross-regional resource conflicts and idleness, improve the efficiency of construction resource utilization, and reduce the risk of construction delays.

[0136] The method for analyzing resource scheduling in cross-chain branch sub-chains and identifying resource contention points in these sub-chains is as follows:

[0137] Obtain the overlap duration T between cross-chain branch subchains and adjacent cross-chain branch subchains. over Based on the equipment reuse rate and time window overlap ratio within the chain, a resource competition analysis model is established to identify resource competition points in cross-chain branch sub-chains;

[0138] It should be explained that the equipment reuse rate is determined by calculating the ratio of the total time that the road construction equipment is occupied by each cross-chain branch sub-chain within the overlap period to the overlap period, reflecting the degree of reuse of the equipment within the overlap period;

[0139] The resource competition analysis model is established by obtaining the time window overlap duration T between the cross-chain branch sub-chain and its adjacent sub-chain. over Time window overlap ratio and equipment reuse rate:

[0140] A two-dimensional resource competition analysis model is established with the time window overlap ratio as the horizontal axis and the equipment reuse rate as the vertical axis. Threshold ranges for time windows and equipment reuse rates are set (e.g., time window overlap ratio > 50% and equipment reuse rate > 60%). Subchain combinations falling within the high threshold range are identified as resource competition points, indicating that there is a significant conflict between them in terms of time and equipment resources, and they need to be prioritized for coordinated scheduling.

[0141] The method for determining the urgent needs of cross-chain branch sub-chains by conducting collaborative urgency analysis on resource competition points is as follows:

[0142] The effective reuse rate of equipment at resource competition points within the overlapping time period is obtained by effectively screening the equipment reuse rate.

[0143] Understandably, when effectively filtering the equipment reuse rate of resource competition points within the overlapping time period, it is necessary to rely on real-time collected equipment status data from the Internet of Things (such as location trajectory and start / stop timestamps) to eliminate non-working periods of equipment (such as downtime due to malfunction or maintenance) and invalid occupation time. Only the time when the equipment is in operation and is actually called by the cross-chain branch sub-chain is retained. The effective reuse rate is calculated by "effective reuse rate = (total effective working time of equipment within the overlapping time period / overlapping time period)" to obtain the real equipment reuse efficiency index after eliminating the invalid occupation time, which provides a reliable basis for identifying the intensity of resource competition.

[0144] The overlap ratio and effective reuse rate of the resource competition points in the time window are normalized respectively. The product of the normalized overlap ratio and the reciprocal of the effective reuse rate is then used to obtain the collaborative urgency index.

[0145] Based on the collaborative urgency index, all competing resource points are screened to obtain urgent demand points;

[0146] Understandably, the collaboration urgency index is compared with a preset collaboration urgency range value, and competitive resource points that meet the preset collaboration urgency range value are selected as urgent demand points.

[0147] It should be noted that the physical meaning of the Collaboration Urgency Index lies in quantifying the comprehensive conflict intensity of cross-chain branch sub-chains in terms of time and resources. The higher the Collaboration Urgency Index value, the higher the urgency of resource competition and the higher the scheduling priority.

[0148] Time window overlap ratio: reflects the degree of overlap in construction time between sub-chains. The larger the value, the more significant the time conflict (such as multiple construction segments occupying the same equipment time window simultaneously).

[0149] The reciprocal of the effective reuse rate is inversely proportional to the actual utilization efficiency of equipment resources. The larger the value of the reciprocal of the effective reuse rate, the higher the proportion of idle or inefficient use of equipment during the overlapping period (such as frequent start-stop or waiting of equipment due to scheduling conflicts).

[0150] The Collaborative Urgency Index integrates spatiotemporal data through standardized dimensions, providing an intuitive basis for prioritizing resource scheduling models. This helps to pinpoint key bottlenecks such as "intense time conflicts and high equipment idling rates" and optimize resource allocation.

[0151] Step 5: Obtain construction scheduling resources for urgent needs, establish a resource allocation group, construct a resource scheduling model and input it into the resource allocation group to realize resource allocation for overlapping road construction structures;

[0152] The method for acquiring construction scheduling resources for urgent needs and establishing resource allocation groups is as follows:

[0153] Construction scheduling resources include: equipment resources, material resources, and construction personnel;

[0154] Construct resource allocation groups that include construction scheduling resources and overlapping time periods;

[0155] The method for constructing a resource scheduling model and inputting it into a resource allocation group to achieve resource allocation for overlapping structures in road construction is as follows:

[0156] Preferably, a resource scheduling model is constructed and input into the resource allocation group. The core constraints are time and space constraints, total resource quantity, and process logic. A genetic algorithm is used to take the equipment list (such as paver number and available time period), material requirements (such as sand and gravel quantity and supply time), and manpower teams (such as skill type and work shift) of the resource allocation group as input. The model solves the optimal solution that minimizes the construction period delay or resource idle cost and outputs a scheduling scheme that includes equipment scheduling timetable, material transportation route, and work team division. At the same time, the model parameters are dynamically corrected by linking the three-dimensional information model and real-time IoT data (such as equipment positioning trajectory and material inventory) to realize the dynamic allocation of resources for overlapping structures in road construction.

[0157] The technical solution of this embodiment is as follows: Obtain the progress deviation ratio of overlapping structural sub-units and construct a road construction progress traceability chain. Through deviation transmission analysis of the overlapping road construction structure, extract the progress traceability sub-chain. Then, combining the spatial coordinates and process logic of the three-dimensional information model, analyze the transmission relationship of the progress traceability sub-chain using an association rule algorithm to construct a progress traceability network. Extract the cross-chain branch sub-chains of the progress traceability network, perform resource scheduling analysis on the cross-chain branch sub-chains, identify resource competition points in the cross-chain branch sub-chains, conduct collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chains. Obtain the construction scheduling resources for the urgent demand points, establish a resource allocation group, construct a resource scheduling model, and input it into the resource allocation group to realize resource allocation for the overlapping road construction structure.

[0158] Example 3

[0159] like Figure 3 As shown, the road construction progress precision monitoring and scheduling system based on intelligent sensing includes the following modules:

[0160] Constraint Construction Module: Used to acquire road construction drawings and 3D information models, perform explicit analysis on the construction drawings and 3D information models through intelligent perception algorithms, identify overlapping and hidden structural units in the road construction process, extract construction feature parameters of overlapping and hidden structures, and construct a construction constraint table;

[0161] Deviation Acquisition Module: Utilizes a 3D point cloud registration algorithm to collect engineering quantities at different levels of road construction and performs construction deviation analysis to obtain the schedule deviation rate;

[0162] Progress tracking module: used to obtain the progress deviation ratio of overlapping structural sub-units and construct a road construction progress tracking chain. By performing deviation transmission analysis on the overlapping structure of road construction, the progress tracking sub-chain is extracted. Then, combined with the spatial coordinates and process logic of the three-dimensional information model, the transmission relationship of the progress tracking sub-chain is analyzed through the association rule algorithm to construct a progress tracking network.

[0163] Scheduling and Analysis Module: Used to extract cross-chain branch sub-chains of the progress tracking network, perform resource scheduling analysis on the cross-chain branch sub-chains, identify resource contention points of the cross-chain branch sub-chains, perform collaborative urgency analysis on the resource contention points, and determine the urgent demand points of the cross-chain branch sub-chains.

[0164] Resource allocation module: Acquire construction scheduling resources for urgent needs, establish resource allocation groups, construct resource scheduling models and input them into resource allocation groups to realize resource allocation for overlapping road construction structures.

[0165] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended technical solutions and their equivalents.

Claims

1. A method for precise monitoring and scheduling of road construction progress based on intelligent sensing, characterized by: Includes the following steps: The engineering quantities of different levels of road construction were collected using a 3D point cloud registration algorithm, and the progress deviation rate was obtained by analyzing the construction deviation. Obtain the schedule deviation ratio of overlapping structural sub-units and construct a road construction schedule traceability chain. By performing deviation transmission analysis on the overlapping structure of road construction, extract the schedule traceability sub-chain. Then, by combining the spatial coordinates and process logic of the three-dimensional information model, analyze the transmission relationship of the schedule traceability sub-chain through the association rule algorithm and construct a schedule traceability network. The progress tracking network is constructed as follows: The sub-units of overlapping structures with negative schedule deviation rates are obtained from the road construction progress traceability chain to obtain the schedule lag unit; Based on the traceability chain of road construction, the schedule deviation rate of the adjacent sub-units of the schedule lagging unit is obtained downwards. The deviation ratio between the schedule deviation rate of the schedule lagging unit and the schedule deviation rate of the adjacent sub-unit is calculated to obtain the deviation transmission rate. Based on the deviation transmission rate, the progress traceability sub-chain of multiple sub-units of the progress traceability chain is extracted, and the progress traceability sub-chain of all overlapping structures of road construction is obtained. A correlation analysis is performed on all the progress traceability sub-chains of the structure, and the progress traceability sub-chains with correlation are connected through a branch structure to form a progress traceability network; Extract the cross-chain branch sub-chains of the progress tracking network, perform resource scheduling analysis on the cross-chain branch sub-chains, identify the resource competition points of the cross-chain branch sub-chains, perform collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chains. The method for identifying the resource contention points of the cross-chain branch sub-chains is as follows: By constructing a graph structure for the progress tracking network, the directed edges of the overlapping sub-units represent the transmission relationships; A sub-chain filtering algorithm is established based on sub-chain filtering conditions to extract cross-chain branch sub-chains from the graph structure of the progress tracking network. Obtain the device reuse rate and time window overlap ratio within the overlap period between cross-chain branch sub-chains and adjacent cross-chain branch sub-chains, establish a resource competition analysis model, and identify resource competition points of cross-chain branch sub-chains; Obtain construction scheduling resources for urgent needs, establish a resource allocation group, construct a resource scheduling model and input it into the resource allocation group to realize resource allocation for overlapping road construction structures; The resource competition analysis model is established as follows: The resource competition analysis model is established by obtaining the time window overlap duration, time window overlap ratio, and equipment reuse rate of the cross-chain branch sub-chain and its adjacent sub-chain. A two-dimensional resource competition analysis model is established with the overlap ratio of time windows as the horizontal axis and the equipment reuse rate as the vertical axis.

2. The method for precise monitoring and scheduling of road construction progress based on intelligent sensing according to claim 1, characterized in that: Obtain road construction drawings and 3D information models, and use intelligent perception algorithms to perform explicit analysis on the construction drawings and 3D information models to identify overlapping and hidden structural units in the road construction process. Extract construction characteristic parameters of overlapping and hidden structures and construct a construction constraint table.

3. The method for precise monitoring and scheduling of road construction progress based on intelligent sensing according to claim 1, characterized in that: The method for performing the construction deviation analysis is as follows: Obtain the three-dimensional information model of all levels of road construction structure, and match the three-dimensional information model of the structure with the construction constraint table to obtain the matching road construction structure; Obtain the construction quantities at different levels and their corresponding time windows, retrieve the time window for the current construction quantity from the construction constraint table, calculate the deviation ratio, and obtain the progress deviation ratio of the construction progress. The hierarchical structure includes: surface structure, hidden structure, and overlapping structure.

4. The method for precise monitoring and scheduling of road construction progress based on intelligent sensing according to claim 3, characterized in that: The method for obtaining the construction quantities at different levels is as follows: The construction volume of the road construction surface structure was collected using a 3D point cloud registration algorithm. For concealed structures in road construction, the construction workload of concealed structures in road construction is determined by combining the burial depth and location in the construction constraint table. To calculate the construction workload of overlapping structures in road construction, road construction data is obtained and verified using a three-dimensional information model.

5. The method for precise monitoring and scheduling of road construction progress based on intelligent sensing according to claim 1, characterized in that: The construction progress traceability chain is obtained as follows: Obtain the sub-units of each overlapping structure in road construction and establish a unique identification system; The traceability chain for road construction is determined according to the construction sequence of each sub-unit of the overlapping structure; Obtain the schedule deviation ratio of each sub-unit of the overlapping structure and couple it with the road construction schedule traceability chain to construct the road construction schedule traceability chain.

6. The method for precise monitoring and scheduling of road construction progress based on intelligent sensing according to claim 1, characterized in that: The method for determining the urgent need points of the cross-chain branch sub-chain is as follows: The effective reuse rate of equipment at resource competition points within the overlapping time period is obtained by effectively screening the equipment reuse rate. The overlap ratio and effective reuse rate of the resource competition points in the time window are normalized respectively. The product of the normalized overlap ratio and the reciprocal of the effective reuse rate is then used to obtain the collaborative urgency index. Based on the collaborative urgency index, all competing resource points are screened to obtain urgent demand points.

7. A road construction progress precision monitoring and scheduling system based on intelligent sensing, used to implement the road construction progress precision monitoring and scheduling method according to any one of claims 1-6, characterized in that: Includes the following modules: Constraint Construction Module: Used to acquire road construction drawings and 3D information models, perform explicit analysis on the construction drawings and 3D information models through intelligent perception algorithms, identify overlapping and hidden structural units in the road construction process, extract construction feature parameters of overlapping and hidden structures, and construct a construction constraint table; Deviation Acquisition Module: Utilizes a 3D point cloud registration algorithm to collect engineering quantities at different levels of road construction and performs construction deviation analysis to obtain the schedule deviation rate; Progress tracking module: used to obtain the progress deviation ratio of overlapping structural sub-units and construct a road construction progress tracking chain. By performing deviation transmission analysis on the overlapping structure of road construction, the progress tracking sub-chain is extracted. Then, combined with the spatial coordinates and process logic of the three-dimensional information model, the transmission relationship of the progress tracking sub-chain is analyzed through the association rule algorithm to construct a progress tracking network. Scheduling and Analysis Module: Used to extract cross-chain branch sub-chains of the progress tracking network, perform resource scheduling analysis on the cross-chain branch sub-chains, identify resource contention points of the cross-chain branch sub-chains, perform collaborative urgency analysis on the resource contention points, and determine the urgent demand points of the cross-chain branch sub-chains. Resource allocation module: Acquire construction scheduling resources for urgent needs, establish resource allocation groups, construct resource scheduling models and input them into resource allocation groups to realize resource allocation for overlapping road construction structures.

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