Intelligent Scheduling System for Earthwork Construction Based on Infrastructure Projects

Abstract

The present invention discloses an intelligent scheduling system for earthwork construction based on infrastructure projects, belonging to the technical field of earthwork project scheduling. It includes a high-precision construction data acquisition module, a spatio-temporal knowledge graph module, a dynamic construction environment assessment module, an intelligent prediction module, a construction scheduling module, a dynamic path planning and optimization module, and a dynamic adjustment module for construction strategies. According to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the dynamic assessment results of the construction environment, the intelligent prediction module of the present invention predicts the impact of environmental factors on construction during the construction process. The construction scheduling module generates an optimal construction scheduling plan based on the prediction results, which can plan construction tasks and resource allocation in advance. Through the dynamic adjustment module for construction strategies, according to the feedback construction scheduling information and the dynamic assessment results of the construction environment, the construction strategies are dynamically adjusted, which can analyze the implementation of the construction scheduling and environmental changes in real time, and flexibly adjust the construction strategies in a timely manner to improve construction efficiency.

Description

Technical Field

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

[0002] In the field of infrastructure projects, the efficient management of earthwork construction is the key to ensuring the smooth progress of projects. The traditional scheduling method relying on manual experience has been difficult to meet the requirements of the current project scale and complexity.

[0003] However, there are still certain defects in the existing intelligent earthwork project scheduling. The existing intelligent earthwork project scheduling only conducts construction scheduling based on static construction plans and fixed resource configurations, and cannot perform intelligent prediction and adaptive adjustment according to the dynamic changes in the construction environment. It only relies on single-dimensional data or simple historical data for prediction, resulting in insufficient comprehensive and accurate prediction of construction environment factors, and cannot adjust the prediction model and results in real time according to the changes in the environment, making it difficult to adapt to the complex and changeable construction environment and unable to adjust the scheduling plan in a timely manner according to the actual situation during the construction process. Therefore, it is unable to effectively cope with the uncertainties and risks during 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 background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: An intelligent scheduling system for earthwork construction based on infrastructure projects, including a high-precision construction data acquisition module, a spatio-temporal knowledge graph module, a dynamic construction environment assessment module, an intelligent prediction module, a construction scheduling module, a dynamic path planning and optimization module, and a dynamic adjustment module for construction strategies;

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

[0007] The spatio-temporal knowledge graph module is used to model and store the relationships of real-time construction environment data in the spatio-temporal dimension to construct a spatio-temporal knowledge graph;

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

[0009] The intelligent prediction module is used to predict the impact of environmental factors on construction during the construction process according to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the results of the dynamic construction environment assessment;

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

[0011] The dynamic path planning and optimization module is used to dynamically generate the optimal driving path of 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 evaluation module and the spatio-temporal knowledge graph module. The spatio-temporal knowledge graph is wirelessly connected to the dynamic construction environment evaluation module and the intelligent prediction module. The dynamic construction environment evaluation 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 and optimization module. The construction strategy dynamic adjustment module is wirelessly connected to the construction adjustment module and the dynamic construction environment evaluation module.

[0014] Among them, the spatio-temporal knowledge graph module models and stores according to the relationship of the real-time construction environment data obtained in the spatio-temporal dimension, constructs a spatio-temporal knowledge graph, and obtains the high-precision construction data preprocessed by the high-precision construction data acquisition module. It is assumed that the obtained high-precision construction data includes time series data, spatial coordinate data, and attribute data. The spatio-temporal sequence data is , each corresponds to a specific time point and construction data. The spatial coordinate data is , each represents the location coordinates of the construction site. The attribute data is , each represents the attribute values of the equipment status and the quantity of construction materials;

[0015] According to the preprocessed high-precision construction data, let the function f(t) represent the characteristics of construction activities at any given time point t, and construct a time dimension model. The implementation formula is:

[0016] ,

[0017] In the formula, represents the attribute value at the time point , represents the occurrence time of the construction activity, represents the change trend of the construction activity over time;

[0018] According to the spatial coordinate data P, calculate the distance matrix between different entities, and construct a spatial dimension model. The implementation formula is:

[0019] ,

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

[0021] Among them, the spatio-temporal knowledge graph module captures the spatio-temporal correlations between different entities according to the time dimension and the space dimension, and the implementation formula is:

[0022] ,

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

[0024] Among them, let the spatio-temporal knowledge graph be G=(V, E), where V represents the set of nodes and E represents the set of edges. Each node corresponds to a construction entity, and the edge connects two nodes, and according to the weight of each edge, it represents the correlation strength between node j and node k, denoted as , and according to the correlation strength between all nodes and edge weights, the final knowledge graph G=(V, E) is constructed.

[0025] The spatio-temporal knowledge graph module uses time dimension modeling, space dimension modeling, and the spatio-temporal correlation formula between entities to comprehensively capture the spatio-temporal relationships between different entities. Through the graph, it can analyze the resource tension problem caused by the concentration of construction equipment in certain areas during a specific time period, providing a basis for optimizing resource allocation.

[0026] Among them, the dynamic construction environment evaluation module dynamically evaluates the construction environment according to the real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal knowledge graph; obtains the real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal knowledge graph for construction environment evaluation, and the implementation formula is:

[0027] ,

[0028] In the formula, represents the construction environment evaluation value at time t and spatial coordinate P, represents the current time t and the time The temporal correlation between represents the spatial correlation between the current spatial coordinate P and the construction coordinate and represents the impact of the association strength between node i and node k on the environmental assessment represents the property value of the time point .

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

[0030] Among them, the intelligent prediction module predicts the impact of environmental factors on construction during the construction process according to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the dynamic assessment results of the construction environment; according to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the construction environment assessment value for prediction, and the implementation formula is:

[0031] ,

[0032] In the formula, represents the predicted value of the future construction impact at time t and spatial coordinate P, represents the weight factor, represents the impact of the evaluation values of the spatial coordinate and time point on the prediction result, represents the impact of the interaction between nodes on future construction activities.

[0033] The intelligent prediction module makes predictions according to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the dynamic assessment results of the construction environment, anticipates potential risks and change trends in advance, and thus adjusts the construction plan in advance.

[0034] Among them, the construction scheduling module generates an optimal construction scheduling plan according to the intelligent prediction results and real-time feedbacks the construction scheduling information; receives the predicted values of the impact of the future construction environment of the intelligent prediction module, integrates the historical construction data information, sets the constraints of the scheduling, 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 suitable 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 assignment results and the resource combination, and real-time monitors the execution of the scheduling plan for feedback.

[0035] The construction scheduling module generates an optimal construction scheduling plan based on the intelligent prediction results and real-time feedbacks the construction scheduling information. By introducing the intelligent prediction results, it can adjust the scheduling plan in a timely manner according to the actual situation during the construction process, achieve the optimal allocation of resources, and improve the construction efficiency.

[0036] Among them, the dynamic path planning and optimization module dynamically generates the optimal driving path of construction equipment according to the formulated optimal construction scheduling plan; obtains the latest construction scheduling plan from the construction scheduling module, including the time arrangement, location information, and required resources of each construction task, combines the obstacles and risk points in the construction three-dimensional real-scene model to automatically generate the optimal path execution instruction, sends the optimal path execution instruction to the equipment for execution, and real-time monitors the equipment execution status. If multiple feasible paths are generated, 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 and the dynamic evaluation result 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, evaluates the impact of environmental factors on the construction process according to the dynamic evaluation result of the construction environment, dynamically adjusts the construction strategy according to the construction scheduling plan, environmental evaluation result, and current construction situation, and evaluates the adjusted construction strategy, and feeds back the evaluated construction strategy to the construction scheduling module for scheduling.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

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

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

[0041] 3. The present invention generates an optimal construction scheduling plan according to the intelligent prediction result and real-time feedbacks the construction scheduling information. By integrating the historical construction data information and the set scheduling constraints, the overall construction task is decomposed into multiple sub-tasks, and the most suitable resource combination is automatically matched, which can optimize the resource allocation, and adjust the scheduling plan in a timely manner according to the actual situation during the construction process, achieve the optimal allocation of resources, and improve the construction efficiency;

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

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

[0044] Figure 2 It is a flowchart of the operation of the spatio-temporal knowledge graph module of the earthwork construction intelligent scheduling system based on infrastructure projects of the present invention;

[0045] Figure 3 It is a flowchart of the operation of the construction scheduling module of the earthwork construction intelligent scheduling system based on infrastructure projects of the present invention;

[0046] Figure 4 It is a flowchart of the operation of the construction strategy dynamic adjustment module of the earthwork construction intelligent scheduling system based on infrastructure projects of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0048] Embodiment

[0049] Please refer to Figures 1-4 As shown, the present invention provides a technical solution: including a high-precision construction data acquisition module, a spatio-temporal knowledge graph module, a dynamic construction environment evaluation module, an intelligent prediction module, a construction scheduling module, a dynamic path planning and optimization module, and a construction strategy dynamic adjustment module;

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

[0051] The spatio-temporal knowledge graph module is used to model and store the relationship of the obtained real-time construction environment data in the spatio-temporal dimension, and construct a spatio-temporal knowledge graph;

[0052] The dynamic construction environment evaluation module is used to dynamically evaluate the construction environment according to the real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal 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 spatio-temporal relationship information of the spatio-temporal knowledge graph and the dynamic evaluation results of the construction environment;

[0054] The construction scheduling module is used to generate an 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 and optimization module is used to dynamically generate the optimal driving path of 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 and the dynamic evaluation results of the construction environment.

[0057] The high-precision construction data acquisition module is wirelessly connected to the dynamic construction environment evaluation module and the spatio-temporal knowledge graph module. The spatio-temporal knowledge graph is wirelessly connected to the dynamic construction environment evaluation module and the intelligent prediction module. The dynamic construction environment evaluation 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 and optimization module. The construction strategy dynamic adjustment module is wirelessly connected to the construction adjustment module and the dynamic construction environment evaluation module.

[0058] Among them, the spatio-temporal knowledge graph module models and stores the relationships of the acquired real-time construction environment data in the spatio-temporal dimension, constructs a spatio-temporal knowledge graph, and obtains the high-precision construction data preprocessed by the high-precision construction data acquisition module. It is assumed that the acquired high-precision construction data includes time series data, spatial coordinate data, and attribute data. The spatio-temporal sequence data is , each corresponds to a specific time point and construction data. The spatial coordinate data is , each represents the location coordinates of the construction site. The attribute data is , each represents the attribute values of equipment status and construction material quantity;

[0059] According to the preprocessed high-precision construction data, let the function f(t) represent the characteristics of construction activities at any given time point t, and construct a time dimension model. The implementation formula is:

[0060] ,

[0061] In the formula, represents the attribute value at time point , represents the occurrence time of construction activities, represents the change trend of construction activities over time;

[0062] Calculate the distance matrix between different entities based on the spatial coordinate data P, and the formula for constructing the spatial dimension modeling is 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 entity j and k at the construction site.

[0065] Among them, the spatio-temporal knowledge graph module captures the spatio-temporal associations between different entities according to the time dimension and the space dimension, and the implementation formula is as follows:

[0066] ,

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

[0068] Among them, let the spatio-temporal knowledge graph be G=(V, E), where V represents the set of nodes and E represents the set of edges. Each node corresponds to a construction entity, and the edge connects two nodes, and according to the weight of each edge, it represents the association strength between node j and node k, denoted as . According to the association strength between all nodes and edge weights, the final knowledge graph G=(V, E) is constructed.

[0069] The spatio-temporal knowledge graph module uses time dimension modeling, space dimension modeling, and the spatio-temporal association formula between entities to comprehensively capture the spatio-temporal relationships between different entities. Through the graph, it can analyze the resource tension problems caused by the concentration of construction equipment in certain areas during a specific period, providing a basis for optimizing resource allocation.

[0070] Among them, the dynamic construction environment assessment module dynamically assesses the construction environment according to the real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal knowledge graph; obtains the real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal knowledge graph for construction environment assessment, and the implementation formula is as follows:

[0071] ,

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

[0073] The dynamic construction environment evaluation module dynamically evaluates the construction environment based on real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal knowledge graph, and can more comprehensively and real-time reflect the changes in the construction environment, and accurately evaluate the impact of environmental factors on construction.

[0074] Among them, the intelligent prediction module predicts the impact of environmental factors on construction during the construction process according to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the dynamic evaluation result of the construction environment; according to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the construction environment evaluation value for prediction, and the implementation formula is:

[0075] ,

[0076] In the formula, represents the predicted value of the future construction impact at time t and spatial coordinate P, represents the weight factor, represents the impact of the evaluation values of the spatial coordinate and time point on the prediction result, represents the impact of the interaction between nodes on future construction activities.

[0077] The intelligent prediction module makes predictions according to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the dynamic evaluation result of the construction environment, anticipates potential risks and change trends in advance, and thus adjusts the construction plan in advance.

[0078] Among them, the construction scheduling module generates an optimal construction scheduling plan according to the intelligent prediction result and real-time feedbacks the construction scheduling information; receives the predicted value of the impact of the future construction environment of the intelligent prediction module, integrates the historical construction data information, sets the constraints of the scheduling, and decomposes the overall construction task into multiple subtasks, determines the priority and time window of each subtask according to the intelligent prediction result, automatically matches the most suitable 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 assignment result and the resource combination, and real-time monitors the execution of the scheduling plan for feedback.

[0079] The construction scheduling module generates an optimal construction scheduling plan based on the intelligent prediction results, and real-time feedbacks the construction scheduling information. By introducing the intelligent prediction results, it can adjust the scheduling plan in a timely manner according to the actual situation during the construction process, achieve the optimal allocation of resources, and improve the construction efficiency.

[0080] Among them, the dynamic path planning and optimization module dynamically generates the optimal driving path of construction equipment according to the formulated optimal construction scheduling plan; obtains the latest construction scheduling plan from the construction scheduling module, including the time arrangement, location information, and required resources of each construction task, combines the obstacles and risk points in the construction three-dimensional real-scene model to automatically generate the optimal path execution instruction, sends the optimal path execution instruction to the equipment for execution, and real-time monitors the equipment execution status. If multiple feasible paths are generated, 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 and the dynamic evaluation result 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, evaluates the impact of environmental factors on the construction process according to the dynamic evaluation result of the construction environment, dynamically adjusts the construction strategy according to the construction scheduling plan, environmental evaluation result, and current construction situation, and evaluates the adjusted construction strategy, and feeds back the evaluated construction strategy to the construction scheduling module for scheduling.

[0082] Working principle: The construction environment data is collected in real time and with high precision through Internet of Things devices, including time series data, spatial coordinate data, and attribute data. The collected construction environment data is preliminarily preprocessed. The spatio-temporal knowledge graph module obtains the high-precision construction data preprocessed by the high-precision construction data collection module, models from the time and space dimensions respectively, represents the characteristics of construction activities at any given time point through functions, combines the attribute values of the time point, the occurrence time of construction activities, and the change trend of construction activities over time to construct a model in the time dimension, analyzes the development law and change trend of construction activities in time, calculates the distance matrix between different entities according to the spatial coordinate data, uses the Euclidean distance formula to determine the spatial distance between entities, thereby constructing a model in the space dimension, clarifying the spatial position relationship of each entity at the construction site, calculates the spatio-temporal correlation intensity between different entities according to the models in the time and space dimensions, considers the time correlation and spatial similarity degree to obtain the comprehensive correlation intensity between entities, takes the construction entities as nodes and the correlations between entities as edges, constructs a spatio-temporal knowledge graph according to the weight of each edge, and structurally stores and represents various information in the construction process in the form of a knowledge graph;

[0083] The dynamic construction environment assessment module calculates the construction environment assessment values at different time and space positions based on real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal knowledge graph, comprehensively considering factors such as the time correlation between the current time and the time when the construction activity occurs, the spatial correlation between the current spatial coordinates and the construction coordinates, the association strength between nodes, and the attribute values of time points, to dynamically assess the construction environment. The intelligent prediction module predicts the impact of environmental factors on construction during the construction process based on the spatio-temporal relationship information of the spatio-temporal knowledge graph and the dynamic assessment results of the construction environment. By comprehensively analyzing factors such as the impact of the assessment values of spatial coordinates and time points on the prediction results and the impact of the interaction between nodes on future construction activities, it calculates the future construction impact prediction values at different time and space positions. The construction scheduling module receives the future construction impact prediction values from the intelligent prediction module, integrates historical construction data information, sets the constraints of the scheduling, decomposes the overall construction task into multiple sub-tasks, determines the priority and time window of each sub-task according to the intelligent prediction results, automatically matches the most suitable resource combination through the ant colony algorithm, automatically generates a detailed scheduling plan based on the task allocation results and resource combination, and monitors the execution status of the scheduling plan in real time for feedback. The dynamic path planning and optimization module obtains the latest construction scheduling plan from the construction scheduling module, combines the obstacles and risk points in the construction three-dimensional real-scene model, automatically generates the optimal path execution instruction, sends the optimal path execution instruction to the equipment for execution, and monitors the execution status of the equipment in real time. If multiple feasible paths are generated, it conducts a risk assessment on each candidate path and adjusts and optimizes the driving path. 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, evaluates the impact of environmental factors on the construction process based on the dynamic assessment results of the construction environment, dynamically adjusts the construction strategy according to the construction scheduling plan, environmental assessment results, and the current construction situation, evaluates the adjusted construction strategy, and feeds back the evaluated construction strategy to the construction scheduling module for scheduling.

[0084] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

[0085] The above describes the present invention and its implementation manners, and this description is not restrictive. What is shown in the drawings is only one of the implementation manners of the present invention, and the actual structure is not limited thereto. Generally speaking, if those of ordinary skill in the art are inspired by it and design similar structural manners and embodiments without creative efforts without departing from the purpose of the present invention, they should all fall within the protection scope of the present invention.

Claims

1. An intelligent dispatching system for earthwork construction based on infrastructure projects, characterized in that: It includes a high-precision construction data acquisition module, a spatio-temporal knowledge graph module, a dynamic construction environment assessment module, an intelligent prediction module, a construction scheduling module, a dynamic path planning and optimization module, and a dynamic construction strategy adjustment module; The high-precision construction data acquisition module is used to obtain construction environment data in real time with high precision through Internet of Things devices and perform preprocessing; The spatio-temporal knowledge graph module is used to model and store the relationships of the obtained real-time construction environment data in the spatio-temporal dimension, and construct a spatio-temporal knowledge graph; The dynamic construction environment assessment module is used to dynamically assess the construction environment according to the real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal knowledge graph; The intelligent prediction module is used to predict the impact of environmental factors on construction during the construction process according to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the results of the dynamic assessment of the construction environment; The construction scheduling module is used to generate an optimal construction scheduling plan according to the intelligent prediction results and real-time feedback the construction scheduling information; The dynamic path planning and optimization module is used to dynamically generate the optimal driving path of construction equipment according to the formulated optimal construction scheduling plan; The dynamic construction strategy adjustment module is used to dynamically adjust the construction strategy according to the feedback construction scheduling information combined with the results of the dynamic assessment of the construction environment; The spatio-temporal knowledge graph module models and stores the relationships of the acquired real-time construction environment data in the spatio-temporal dimension to construct a spatio-temporal knowledge graph; acquires the high-precision construction data preprocessed by the high-precision construction data acquisition module. Suppose the acquired high-precision construction data includes time series data, spatial coordinate data, and attribute data, and the spatio-temporal series data is , each corresponds to a time point and construction data, and 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 the equipment status and the quantity of construction materials; According to the preprocessed high-precision construction data, let the function f(t) represent the characteristics of construction activities at any given time point t, and construct a time dimension model. The implementation formula is: ， In the formula, represents the property value at the time point , indicates the time when the construction activity occurs, and represents the change trend of the construction activity over time; Calculate the distance matrix between different entities according to the spatial coordinate data, and construct a spatial dimension model. The implementation formula is: ， In the formula, represents the Euclidean distance between entity j and entity k, and represent the geographical location coordinates of entity j and k at the construction site, respectively; The spatio-temporal knowledge graph module captures the spatio-temporal associations between different entities according to the time dimension and the spatial dimension. The implementation formula is: ， In the formula, represents the association strength between entities j and k, represents the correlation between two entities in the time dimension, represents the degree of similarity between two entities in space, and represent the coefficients of time correlation and spatial similarity respectively; Let the spatio-temporal knowledge graph be G = (V, E), where V represents the set of nodes and E represents the set of edges. Each node corresponds to a construction entity, and the edge connects two nodes and represents the association strength between node j and node k according to the weight of each edge which is denoted as . Based on the association strength between all nodes and edge weights, the final knowledge graph G = (V, E) is constructed; The dynamic construction environment assessment module dynamically assesses the construction environment according to the real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal knowledge graph; obtains the real-time high-precision construction environment data and the spatio-temporal relationship information of the spatio-temporal knowledge graph for construction environment assessment. The implementation formula is: ， In the formula, represents the construction environment evaluation value at time t and spatial coordinate P, represents the time correlation between the current time t and the time when the construction activity occurs, represents the spatial correlation between the current spatial coordinate P and the construction coordinate at which the construction activity occurs, represents the impact of the association strength between node i and node k on the environment evaluation, represents the time point and its attribute value; The intelligent prediction module predicts the impact of environmental factors on construction during the construction process based on the spatio-temporal relationship information of the spatio-temporal knowledge graph and the dynamic evaluation results of the construction environment; according to the spatio-temporal relationship information of the spatio-temporal knowledge graph and the construction environment evaluation value to make predictions. The implementation formula is as follows: ， In the formula, represents the predicted value of the future construction impact at time t and spatial coordinate P, represents the weight factor, represents the impact of the evaluation values of spatial coordinates and time points on the prediction result, represents the impact of the interaction between nodes on future construction activities.

2. The intelligent dispatching system for earthwork construction based on infrastructure projects according to claim 1, wherein: The construction scheduling module generates an optimal construction scheduling plan according to the intelligent prediction results and real-time feedback the construction scheduling information; receives the predicted values of the impact of the future construction environment from the intelligent prediction module, integrates the historical construction data information, sets the constraints of the scheduling, 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 suitable 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 assignment results and the resource combination, and real-time monitors the execution of the scheduling plan for feedback.

3. The intelligent dispatching system for earthwork construction based on infrastructure projects according to claim 1, wherein: The dynamic path planning optimization module dynamically generates the optimal driving path of construction equipment according to the formulated optimal construction scheduling plan; obtains the latest construction scheduling plan from the construction scheduling module, including the time arrangement, location information, and required resources of each construction task, combines the obstacles and risk points in the construction three-dimensional real-scene model to automatically generate the optimal path execution instruction, 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, risk assessment is carried out on each candidate path, potential risk points are identified, and the driving path is adjusted and optimized.

4. The intelligent dispatching system for earthwork construction based on infrastructure projects according to claim 1, wherein: The construction strategy dynamic adjustment module dynamically adjusts the construction strategy according to the feedback construction scheduling information and the dynamic evaluation result 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, evaluates the impact of environmental factors on the construction process according to the dynamic evaluation result of the construction environment, dynamically adjusts the construction strategy according to the construction scheduling plan, environmental evaluation result, and current construction situation, evaluates the adjusted construction strategy, and feeds back the evaluated construction strategy to the construction scheduling module for scheduling.

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