Earthwork construction intelligent scheduling system based on infrastructure project

Abstract

The invention discloses an earthwork construction intelligent scheduling system based on infrastructure engineering, and belongs to the technical field of earthwork scheduling. Comprising a high-precision construction data acquisition module, a space-time knowledge graph module, a dynamic construction environment evaluation module, an intelligent prediction module, a construction scheduling module, a dynamic path planning optimization module and a construction strategy dynamic adjustment module. The intelligent prediction module predicts the influence of environmental factors on construction in the construction process according to the space-time relation information of the space-time knowledge graph and the construction environment dynamic evaluation result, and the construction scheduling module generates the optimal construction scheduling scheme according to the prediction result, so that construction tasks and resource allocation can be planned in advance; the construction strategy dynamic adjustment module performs construction strategy dynamic adjustment according to the feedback construction scheduling information in combination with the construction environment dynamic evaluation result, so that the construction scheduling execution condition and the environment change can be analyzed in real time, the construction strategy is adjusted timely and flexibly, and the construction efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of earthwork engineering scheduling, and specifically refers to an intelligent scheduling system for earthwork construction based on infrastructure engineering. Background Art

[0002] In the field of infrastructure construction, efficient management of earthwork construction is the key to ensuring the smooth progress of the project. The traditional scheduling method that relies on manual experience can no longer meet the needs of the current project scale and complexity.

[0003] However, there are still certain defects in the existing intelligent earthwork engineering scheduling. The existing intelligent earthwork engineering scheduling is only based on static construction plans and fixed resource allocation for construction scheduling, and cannot make intelligent predictions and adaptive adjustments according to the dynamic changes of the construction environment. It only relies on single-dimensional data or simple historical data for prediction, resulting in insufficient comprehensive and accurate predictions of construction environment factors, and cannot adjust the prediction model and results in real time according to environmental changes. It is difficult to adapt to the complex and changeable construction environment, and cannot adjust the scheduling plan in time according to the actual situation during the construction process, so it is impossible to effectively deal with the uncertainty and risks in the construction process. For this reason, an intelligent scheduling system for earthwork construction based on infrastructure projects is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent scheduling system for earthwork construction based on infrastructure projects to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an intelligent scheduling system for earthwork construction based on infrastructure engineering, comprising a high-precision construction data acquisition module, a spatiotemporal knowledge graph module, a dynamic construction environment assessment module, an intelligent prediction module, a construction scheduling module, a dynamic path planning optimization module and a construction strategy dynamic adjustment module;

[0006] The high-precision construction data acquisition module is used to obtain and pre-process the construction environment data in real time and with high precision through the Internet of Things devices;

[0007] The spatiotemporal knowledge graph module is used to model and store the relationship between real-time construction environment data in the spatiotemporal dimension to construct a spatiotemporal knowledge graph;

[0008] The dynamic construction environment assessment module is used to dynamically assess the construction environment based on real-time high-precision construction environment data and spatiotemporal relationship information of the spatiotemporal knowledge graph;

[0009] The intelligent prediction module is used to predict the impact of environmental factors on construction during the construction process based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic evaluation results of the construction environment;

[0010] The construction scheduling module is used to generate the optimal construction scheduling plan according to the intelligent prediction results and to provide real-time feedback on the construction scheduling information;

[0011] The dynamic path planning optimization module is used to dynamically generate the optimal driving path of the construction equipment according to the formulated optimal construction scheduling plan;

[0012] The construction strategy dynamic adjustment module is used to dynamically adjust the construction strategy according to the feedback construction scheduling information combined with the dynamic evaluation results of the construction environment.

[0013] The high-precision construction data acquisition module is wirelessly connected to the dynamic construction environment assessment module and the spatiotemporal knowledge graph module, the spatiotemporal knowledge graph is wirelessly connected to the dynamic construction environment assessment module and the intelligent prediction module, the dynamic construction environment assessment module is wirelessly connected to the intelligent prediction module, the intelligent prediction module is wirelessly connected to the construction scheduling module, the construction scheduling module is wirelessly connected to the dynamic path planning optimization module, and the construction strategy dynamic adjustment module is wirelessly connected to the construction adjustment module and the dynamic construction environment assessment module.

[0014] The spatiotemporal knowledge graph module is constructed based on the relationship between the real-time construction environment data in the spatiotemporal dimension, and the spatiotemporal knowledge graph is constructed to obtain the high-precision construction data preprocessed by the high-precision construction data acquisition module. The high-precision construction data obtained includes time series data, spatial coordinate data and attribute data. The spatiotemporal series data is , each Corresponding to a specific time point and construction data, the spatial coordinate data is , each Represents the location coordinates of the construction site, and the attribute data is , each Represents the attribute values ​​of equipment status and construction material quantity;

[0015] Based on the pre-processed high-precision construction data, let the function f(t) represent the construction activity characteristics at any given time point t, and build a time dimension model. The implementation formula is:

[0016] ,

[0017] In the formula, Indicates time point The attribute value of Indicates the time when the construction activity occurs. Indicates the trend of construction activities over time;

[0018] According to the spatial coordinate data P, the distance matrix between different entities is calculated, and the spatial dimension modeling implementation formula is constructed as follows:

[0019] ,

[0020] In the formula, represents the Euclidean distance between entity j and entity k, and Respectively represent the geographical location coordinates of entities j and k at the construction site.

[0021] The spatiotemporal knowledge graph module captures the spatiotemporal associations between different entities according to the time dimension and the space dimension, and the implementation formula is:

[0022] ,

[0023] In the formula, represents the strength of association between entities j and k, Represents the correlation between two entities in the time dimension, Indicates the degree of similarity between two entities in space. and The coefficients represent the temporal correlation and spatial similarity respectively.

[0024] Assume that the spatiotemporal knowledge graph is G=(V, E), where V represents the node set, E represents the edge set, and each node Corresponding to a construction entity, the edge Connect two nodes and add them according to the weight of each edge represents the association strength between node j and node k, expressed as , based on the association strength between all nodes and edge weights, the final knowledge graph G=(V, E) is constructed.

[0025] The spatiotemporal knowledge graph module uses time dimension modeling, space dimension modeling and spatiotemporal association formulas between entities to comprehensively capture the spatiotemporal relationship between different entities. The graph can analyze the resource shortage problem caused by the concentration of construction equipment in certain areas within a specific time period, providing a basis for optimizing resource allocation.

[0026] Among them, the dynamic construction environment assessment module dynamically assesses the construction environment based on the spatiotemporal relationship information of the real-time high-precision construction environment data and the spatiotemporal knowledge graph; obtains the real-time high-precision construction environment data and the spatiotemporal relationship information of the spatiotemporal knowledge graph to conduct construction environment assessment, and the implementation formula is:

[0027] ,

[0028] In the formula, represents the construction environment assessment value at time t and spatial coordinate P, Represents the current time t and the time when the construction activity occurs The time correlation between Indicates the current space coordinate P and construction coordinate The spatial correlation between represents the impact of the association strength between node i and node k on the environmental evaluation, Indicates time point The attribute value of .

[0029] The dynamic construction environment assessment module dynamically assesses the construction environment based on real-time high-precision construction environment data and the spatiotemporal relationship information of the spatiotemporal knowledge graph, which can more comprehensively and in real time reflect the changes in the construction environment and accurately assess the impact of environmental factors on construction.

[0030] The intelligent prediction module predicts the impact of environmental factors on construction during the construction process based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic evaluation results of the construction environment; and construction environment assessment value To make a prediction, the implementation formula is:

[0031] ,

[0032] In the formula, represents the predicted value of future construction impact at time t and spatial coordinate P, represents the weight factor, Indicates the impact of the evaluation values ​​of spatial coordinates and time points on the prediction results, Represents the impact of interactions between nodes on future construction activities.

[0033] The intelligent prediction module makes predictions based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic assessment results of the construction environment, predicts potential risks and changing trends in advance, and thus adjusts the construction plan in advance.

[0034] Among them, the construction scheduling module generates the optimal construction scheduling plan according to the intelligent prediction results, and feeds back the construction scheduling information in real time; receives the predicted value of the impact of the future construction environment from the intelligent prediction module, and integrates the historical construction data information, sets the scheduling constraints, and decomposes the overall construction task into multiple subtasks, determines the priority and time window of each subtask according to the intelligent prediction results, and automatically matches the most appropriate resource combination according to the task requirements and the available resources in the resource library through the ant colony algorithm, automatically generates a detailed scheduling plan according to the task allocation results and resource combinations, and monitors the execution of the scheduling plan in real time for feedback.

[0035] The construction scheduling module generates the optimal construction scheduling plan based on the intelligent prediction results and feeds back the construction scheduling information in real time. By introducing the intelligent prediction results, the scheduling plan can be adjusted in time according to the actual situation during the construction process, the optimal allocation of resources can be achieved, and the construction efficiency can be improved.

[0036] Among them, the dynamic path planning optimization module dynamically generates the optimal driving path of the construction equipment according to the formulated optimal construction scheduling plan; obtains the latest construction scheduling plan from the construction scheduling module, including the time schedule, location information and required resources of each construction task, and automatically generates the optimal path execution instructions in combination with the obstacles and risk points in the construction three-dimensional real-scene model, sends the optimal path execution instructions to the equipment for execution, and monitors the equipment execution status in real time. If multiple feasible paths are generated, a risk assessment is performed on each candidate path, potential risk points are identified, and the driving path is adjusted and optimized.

[0037] Among them, the construction strategy dynamic adjustment module dynamically adjusts the construction strategy according to the feedback construction scheduling information combined with the dynamic evaluation results of the construction environment; compares and analyzes the feedback construction scheduling information with the formulated scheduling plan, analyzes the deviation between the construction progress and the scheduling plan progress, and evaluates the impact of environmental factors on the construction process according to the dynamic evaluation results of the construction environment. The construction strategy is dynamically adjusted according to the construction scheduling plan, environmental evaluation results and current construction conditions, and the adjusted construction strategy is evaluated, and the evaluated construction strategy is fed back to the construction scheduling module for scheduling.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. The present invention predicts the impact of environmental factors on construction during the construction process based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic evaluation results of the construction environment through the intelligent prediction module. The construction scheduling module generates the optimal construction scheduling plan based on the prediction results, which can plan construction tasks and resource allocation in advance, reduce uncertainty and risks in the construction process, and improve construction efficiency;

[0040] 2. The present invention dynamically evaluates the construction environment based on real-time high-precision construction environment data and the spatiotemporal relationship information of the spatiotemporal knowledge graph, which can more comprehensively and real-timely reflect the changes in the construction environment and accurately evaluate the impact of environmental factors on construction;

[0041] 3. The present invention generates the optimal construction scheduling plan based on the intelligent prediction results, and feeds back the construction scheduling information in real time. By integrating historical construction data information and setting scheduling constraints, the overall construction task is decomposed into multiple subtasks, and the most appropriate resource combination is automatically matched. It can optimize resource allocation and adjust the scheduling plan in time according to the actual situation during the construction process, so as to achieve the optimal allocation of resources and improve construction efficiency.

[0042] 4. The present invention dynamically adjusts the construction strategy according to the feedback of construction scheduling information combined with the dynamic evaluation results of the construction environment through the construction strategy dynamic adjustment module, which can analyze the execution of construction scheduling and environmental changes in real time, adjust the construction strategy in a timely and flexible manner, and improve construction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a structural schematic diagram of an intelligent scheduling system for earthwork construction based on infrastructure engineering of the present invention;

[0044] Figure 2 This is a flow chart of the operation of the spatiotemporal knowledge graph module of the intelligent scheduling system for earthwork construction based on infrastructure engineering of the present invention;

[0045] Figure 3 This is a flow chart of the operation of a construction scheduling module of an intelligent scheduling system for earthwork construction based on infrastructure engineering of the present invention;

[0046] Figure 4 This is an operation flow chart of the construction strategy dynamic adjustment module of the intelligent scheduling system for earthwork construction based on infrastructure projects of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Example

[0049] See also Figure 1-Figure 4 As shown, the present invention provides a technical solution: including a high-precision construction data acquisition module, a spatiotemporal knowledge graph module, a dynamic construction environment assessment module, an intelligent prediction module, a construction scheduling module, a dynamic path planning optimization module and a construction strategy dynamic adjustment module;

[0050] The high-precision construction data acquisition module is used to obtain and pre-process the construction environment data in real time and with high precision through the Internet of Things devices;

[0051] The spatiotemporal knowledge graph module is used to model and store the relationship between real-time construction environment data in the spatiotemporal dimension to construct a spatiotemporal knowledge graph;

[0052] The dynamic construction environment assessment module is used to dynamically assess the construction environment based on real-time high-precision construction environment data and spatiotemporal relationship information of the spatiotemporal knowledge graph;

[0053] The intelligent prediction module is used to predict the impact of environmental factors on construction during the construction process based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic evaluation results of the construction environment;

[0054] The construction scheduling module is used to generate the optimal construction scheduling plan according to the intelligent prediction results and to provide real-time feedback on the construction scheduling information;

[0055] The dynamic path planning optimization module is used to dynamically generate the optimal driving path of the construction equipment according to the formulated optimal construction scheduling plan;

[0056] The construction strategy dynamic adjustment module is used to dynamically adjust the construction strategy according to the feedback construction scheduling information combined with the dynamic evaluation results of the construction environment.

[0057] The high-precision construction data acquisition module is wirelessly connected to the dynamic construction environment assessment module and the spatiotemporal knowledge graph module, the spatiotemporal knowledge graph is wirelessly connected to the dynamic construction environment assessment module and the intelligent prediction module, the dynamic construction environment assessment module is wirelessly connected to the intelligent prediction module, the intelligent prediction module is wirelessly connected to the construction scheduling module, the construction scheduling module is wirelessly connected to the dynamic path planning optimization module, and the construction strategy dynamic adjustment module is wirelessly connected to the construction adjustment module and the dynamic construction environment assessment module.

[0058] The spatiotemporal knowledge graph module is constructed based on the relationship between the real-time construction environment data in the spatiotemporal dimension, and the spatiotemporal knowledge graph is constructed to obtain the high-precision construction data preprocessed by the high-precision construction data acquisition module. The high-precision construction data obtained includes time series data, spatial coordinate data and attribute data. The spatiotemporal series data is , each Corresponding to a specific time point and construction data, the spatial coordinate data is , each Represents the location coordinates of the construction site, and the attribute data is , each Represents the attribute values ​​of equipment status and construction material quantity;

[0059] Based on the pre-processed high-precision construction data, let the function f(t) represent the construction activity characteristics at any given time point t, and build a time dimension model. The implementation formula is:

[0060] ,

[0061] In the formula, Indicates time point The attribute value of Indicates the time when the construction activity occurs. Indicates the trend of construction activities over time;

[0062] According to the spatial coordinate data P, the distance matrix between different entities is calculated, and the spatial dimension modeling implementation formula is constructed as follows:

[0063] ,

[0064] In the formula, represents the Euclidean distance between entity j and entity k, and Respectively represent the geographical location coordinates of entities j and k at the construction site.

[0065] The spatiotemporal knowledge graph module captures the spatiotemporal associations between different entities according to the time dimension and the space dimension, and the implementation formula is:

[0066] ,

[0067] In the formula, represents the strength of association between entities j and k, Represents the correlation between two entities in the time dimension, Indicates the degree of similarity between two entities in space. and The coefficients represent the temporal correlation and spatial similarity respectively.

[0068] Assume that the spatiotemporal knowledge graph is G=(V, E), where V represents the node set, E represents the edge set, and each node Corresponding to a construction entity, the edge Connect two nodes and add them according to the weight of each edge represents the association strength between node j and node k, expressed as , based on the association strength between all nodes and edge weights, the final knowledge graph G=(V, E) is constructed.

[0069] The spatiotemporal knowledge graph module uses time dimension modeling, space dimension modeling and spatiotemporal association formulas between entities to comprehensively capture the spatiotemporal relationship between different entities. The graph can analyze the resource shortage problem caused by the concentration of construction equipment in certain areas within a specific time period, providing a basis for optimizing resource allocation.

[0070] Among them, the dynamic construction environment assessment module dynamically assesses the construction environment based on the spatiotemporal relationship information of the real-time high-precision construction environment data and the spatiotemporal knowledge graph; obtains the real-time high-precision construction environment data and the spatiotemporal relationship information of the spatiotemporal knowledge graph to conduct construction environment assessment, and the implementation formula is:

[0071] ,

[0072] In the formula, represents the construction environment assessment value at time t and spatial coordinate P, Represents the current time t and the time when the construction activity occurs The time correlation between Indicates the current space coordinate P and construction coordinate The spatial correlation between represents the impact of the association strength between node i and node k on the environmental evaluation, Indicates time point The attribute value of .

[0073] The dynamic construction environment assessment module dynamically assesses the construction environment based on real-time high-precision construction environment data and the spatiotemporal relationship information of the spatiotemporal knowledge graph, which can more comprehensively and in real time reflect the changes in the construction environment and accurately assess the impact of environmental factors on construction.

[0074] The intelligent prediction module predicts the impact of environmental factors on construction during the construction process based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic evaluation results of the construction environment; and construction environment assessment value To make a prediction, the implementation formula is:

[0075] ,

[0076] In the formula, represents the predicted value of future construction impact at time t and spatial coordinate P, represents the weight factor, Indicates the impact of the evaluation values ​​of spatial coordinates and time points on the prediction results, Represents the impact of interactions between nodes on future construction activities.

[0077] The intelligent prediction module makes predictions based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic assessment results of the construction environment, predicts potential risks and changing trends in advance, and thus adjusts the construction plan in advance.

[0078] Among them, the construction scheduling module generates the optimal construction scheduling plan according to the intelligent prediction results, and feeds back the construction scheduling information in real time; receives the predicted value of the impact of the future construction environment from the intelligent prediction module, and integrates the historical construction data information, sets the scheduling constraints, and decomposes the overall construction task into multiple subtasks, determines the priority and time window of each subtask according to the intelligent prediction results, and automatically matches the most appropriate resource combination according to the task requirements and the available resources in the resource library through the ant colony algorithm, automatically generates a detailed scheduling plan according to the task allocation results and resource combinations, and monitors the execution of the scheduling plan in real time for feedback.

[0079] The construction scheduling module generates the optimal construction scheduling plan based on the intelligent prediction results and feeds back the construction scheduling information in real time. By introducing the intelligent prediction results, the scheduling plan can be adjusted in time according to the actual situation during the construction process, the optimal allocation of resources can be achieved, and the construction efficiency can be improved.

[0080] Among them, the dynamic path planning optimization module dynamically generates the optimal driving path of the construction equipment according to the formulated optimal construction scheduling plan; obtains the latest construction scheduling plan from the construction scheduling module, including the time schedule, location information and required resources of each construction task, and automatically generates the optimal path execution instructions in combination with the obstacles and risk points in the construction three-dimensional real-scene model, sends the optimal path execution instructions to the equipment for execution, and monitors the equipment execution status in real time. If multiple feasible paths are generated, a risk assessment is performed on each candidate path, potential risk points are identified, and the driving path is adjusted and optimized.

[0081] Among them, the construction strategy dynamic adjustment module dynamically adjusts the construction strategy according to the feedback construction scheduling information combined with the dynamic evaluation results of the construction environment; compares and analyzes the feedback construction scheduling information with the formulated scheduling plan, analyzes the deviation between the construction progress and the scheduling plan progress, and evaluates the impact of environmental factors on the construction process according to the dynamic evaluation results of the construction environment. The construction strategy is dynamically adjusted according to the construction scheduling plan, environmental evaluation results and current construction conditions, and the adjusted construction strategy is evaluated, and the evaluated construction strategy is fed back to the construction scheduling module for scheduling.

[0082] Working principle: The construction environment data, including time series data, spatial coordinate data and attribute data, are collected in real time and with high precision through the Internet of Things devices. The collected construction environment data is preliminarily preprocessed. The spatiotemporal knowledge graph module obtains the high-precision construction data preprocessed by the high-precision construction data collection module, and models are built from the time and space dimensions respectively. The construction activity characteristics at any given time point are represented by functions. The time dimension model is constructed by combining the attribute values ​​at the time point, the time when the construction activity occurs, and the change trend of the construction activity over time. The development law and change trend of the construction activity over time are analyzed. The distance matrix between different entities is calculated based on the spatial coordinate data. The spatial distance between entities is determined using the Euclidean distance formula, thereby constructing a model of the spatial dimension and clarifying the spatial position relationship of each entity at the construction site. Based on the models of the time dimension and the space dimension, the spatiotemporal correlation strength between different entities is calculated. Considering the time correlation and spatial similarity, the comprehensive correlation strength between entities is obtained. The construction entity is taken as a node, and the association between entities is taken as an edge. The spatiotemporal knowledge graph is constructed according to the weight of each edge, and various information in the construction process is structured and stored and represented in the form of a knowledge graph.

[0083] The dynamic construction environment assessment module calculates the construction environment assessment values ​​at different times and spatial locations based on the real-time high-precision construction environment data and the spatiotemporal relationship information of the spatiotemporal knowledge graph, taking into account the temporal correlation between the current time and the time of the construction activity, the spatial correlation between the current spatial coordinates and the construction coordinates, the correlation strength between nodes, and the attribute values ​​at time points, and dynamically evaluates the construction environment. The intelligent prediction module predicts the impact of environmental factors on the construction during the construction process based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic evaluation results of the construction environment. By comprehensively analyzing the impact of the evaluation values ​​of spatial coordinates and time points on the prediction results, the impact of the interaction between nodes on future construction activities, and other factors, the predicted values ​​of future construction impacts at different times and spatial locations are calculated. The construction scheduling module receives the predicted values ​​of future construction impacts from the intelligent prediction module, integrates historical construction data information, sets scheduling constraints, decomposes the overall construction task into multiple subtasks, and determines the priority and Time window, automatically match the most suitable resource combination through ant colony algorithm, automatically generate detailed scheduling plan according to task allocation results and resource combination, and monitor the execution of scheduling plan in real time for feedback. The dynamic path planning optimization module obtains the latest construction scheduling plan from the construction scheduling module, and automatically generates the optimal path execution instruction in combination with obstacles and risk points in the construction 3D real-life model, sends the optimal path execution instruction to the equipment for execution, and monitors the equipment execution status in real time. If multiple feasible paths are generated, each candidate path is risk assessed and the driving path is adjusted and optimized. The construction strategy dynamic adjustment module compares and analyzes the feedback construction scheduling information with the formulated scheduling plan, analyzes the deviation between the construction progress and the scheduling plan progress, and evaluates the impact of environmental factors on the construction process according to the dynamic evaluation results of the construction environment. The construction strategy is dynamically adjusted according to the construction scheduling plan, environmental evaluation results and current construction conditions, and the adjusted construction strategy is evaluated, and the evaluated construction strategy is fed back to the construction scheduling module for scheduling.

[0084] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0085] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. The intelligent dispatching system for earthwork construction based on infrastructure projects is characterized by: It includes high-precision construction data acquisition module, spatiotemporal knowledge graph module, dynamic construction environment assessment module, intelligent prediction module, construction scheduling module, dynamic path planning optimization module and construction strategy dynamic adjustment module; The high-precision construction data acquisition module is used to obtain and pre-process the construction environment data in real time and with high precision through the Internet of Things devices; The spatiotemporal knowledge graph module is used to model and store the relationship between real-time construction environment data in the spatiotemporal dimension to construct a spatiotemporal knowledge graph; The dynamic construction environment assessment module is used to dynamically assess the construction environment based on real-time high-precision construction environment data and spatiotemporal relationship information of the spatiotemporal knowledge graph; The intelligent prediction module is used to predict the impact of environmental factors on construction during the construction process based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic evaluation results of the construction environment; The construction scheduling module is used to generate the optimal construction scheduling plan according to the intelligent prediction results and to provide real-time feedback on the construction scheduling information; The dynamic path planning optimization module is used to dynamically generate the optimal driving path of the construction equipment according to the formulated optimal construction scheduling plan; The construction strategy dynamic adjustment module is used to dynamically adjust the construction strategy according to the feedback construction scheduling information combined with the dynamic evaluation results of the construction environment.

2. The intelligent scheduling system for earthwork construction based on infrastructure engineering according to claim 1 is characterized by: The spatiotemporal knowledge graph module models and stores the relationship between the real-time construction environment data in the spatiotemporal dimension to construct a spatiotemporal knowledge graph; obtains the high-precision construction data preprocessed by the high-precision construction data acquisition module, and assumes that the acquired high-precision construction data includes time series data, spatial coordinate data and attribute data, and the spatiotemporal series data is , each Corresponding to a time point and construction data, the spatial coordinate data is , each Represents the location coordinates of the construction site, and the attribute data is , each Represents the attribute values ​​of equipment status and construction material quantity; Based on the pre-processed high-precision construction data, let the function f(t) represent the construction activity characteristics at any given time point t, and build a time dimension model. The implementation formula is: ， In the formula, Indicates time point The attribute value of Indicates the time when the construction activity occurs. Indicates the trend of construction activities over time; According to the spatial coordinate data, the distance matrix between different entities is calculated and the spatial dimension modeling implementation formula is constructed as follows: ， In the formula, represents the Euclidean distance between entity j and entity k, and Respectively represent the geographical location coordinates of entities j and k at the construction site.

3. The intelligent scheduling system for earthwork construction based on infrastructure engineering according to claim 2 is characterized by: The spatiotemporal knowledge graph module captures the spatiotemporal associations between different entities based on the time dimension and the space dimension. The implementation formula is: ， In the formula, represents the strength of association between entities j and k, Represents the correlation between two entities in the time dimension, Indicates the degree of similarity between two entities in space. and The coefficients represent the temporal correlation and spatial similarity respectively.

4. The intelligent scheduling system for earthwork construction based on infrastructure engineering according to claim 3 is characterized by: Suppose the spatiotemporal knowledge graph is G=(V, E), where V represents the node set, E represents the edge set, and each node Corresponding to a construction entity, the edge Connect two nodes and add them according to the weight of each edge represents the association strength between node j and node k, expressed as , based on the association strength between all nodes and edge weights, the final knowledge graph G=(V, E) is constructed.

5. The intelligent scheduling system for earthwork construction based on infrastructure engineering according to claim 1 is characterized by: The dynamic construction environment assessment module dynamically assesses the construction environment based on the real-time high-precision construction environment data and the spatiotemporal relationship information of the spatiotemporal knowledge graph; obtains the real-time high-precision construction environment data and the spatiotemporal relationship information of the spatiotemporal knowledge graph to conduct construction environment assessment, and the implementation formula is: ， In the formula, represents the construction environment assessment value at time t and spatial coordinate P, Represents the current time t and the time when the construction activity occurs The time correlation between Indicates the current space coordinate P and construction coordinate The spatial correlation between represents the impact of the association strength between node i and node k on the environmental evaluation, Indicates time point The attribute value of .

6. The intelligent scheduling system for earthwork construction based on infrastructure engineering according to claim 1 is characterized by: The intelligent prediction module predicts the impact of environmental factors on construction during the construction process based on the spatiotemporal relationship information of the spatiotemporal knowledge graph and the dynamic evaluation results of the construction environment; and construction environment assessment value To make a prediction, the implementation formula is: ， In the formula, represents the predicted value of future construction impact at time t and spatial coordinate P, represents the weight factor, Indicates the impact of the evaluation values ​​of spatial coordinates and time points on the prediction results, Represents the impact of interactions between nodes on future construction activities.

7. The intelligent scheduling system for earthwork construction based on infrastructure engineering according to claim 1 is characterized by: The construction scheduling module generates the optimal construction scheduling plan according to the intelligent prediction results, and feeds back the construction scheduling information in real time; receives the predicted value of the impact of the future construction environment from the intelligent prediction module, integrates the historical construction data information, sets the scheduling constraints, and decomposes the overall construction task into multiple subtasks, determines the priority and time window of each subtask according to the intelligent prediction results, automatically matches the most appropriate resource combination according to the task requirements and the available resources in the resource library through the ant colony algorithm, automatically generates a detailed scheduling plan according to the task allocation results and the resource combination, and monitors the execution of the scheduling plan in real time for feedback.

8. The intelligent scheduling system for earthwork construction based on infrastructure engineering according to claim 1 is characterized by: The dynamic path planning optimization module dynamically generates the optimal driving path for the construction equipment according to the formulated optimal construction scheduling plan; obtains the latest construction scheduling plan from the construction scheduling module, including the time schedule, location information and required resources of each construction task, and automatically generates the optimal path execution instructions in combination with the obstacles and risk points in the three-dimensional construction real-life model, sends the optimal path execution instructions to the equipment for execution, and monitors the execution status of the equipment in real time. If multiple feasible paths are generated, a risk assessment is performed on each candidate path, potential risk points are identified, and the driving path is adjusted and optimized.

9. The intelligent scheduling system for earthwork construction based on infrastructure engineering according to claim 1 is characterized by: The construction strategy dynamic adjustment module dynamically adjusts the construction strategy according to the feedback construction scheduling information combined with the dynamic evaluation results of the construction environment; compares and analyzes the feedback construction scheduling information with the formulated scheduling plan, analyzes the deviation between the construction progress and the scheduling plan progress, and evaluates the impact of environmental factors on the construction process according to the dynamic evaluation results of the construction environment. The construction strategy is dynamically adjusted according to the construction scheduling plan, environmental evaluation results and current construction conditions, and the adjusted construction strategy is evaluated, and the evaluated construction strategy is fed back to the construction scheduling module for scheduling.

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