A rural sewage treatment planning system and method

Abstract

The application belongs to the technical field of rural sewage treatment, and discloses a rural sewage treatment planning system and method, which comprises a planning collection device, which is used for obtaining construction range information and process requirement information, performing plan analysis on the construction range information and the process requirement information, and obtaining engineering plan information; the engineering plan information comprises progress plan information and material requirement plan information; a construction collection device is used for obtaining construction real-time information and the engineering plan information, performing completion condition analysis on the construction real-time information according to the engineering plan information, and obtaining construction completion result information. The application can effectively manage the sewage project, improve the timeliness of engineering management, and make the construction range information fit the actual sewage generation condition and treatment demand of the rural area.

Description

TECHNICAL FIELD

[0001] The present application relates to the rural sewage treatment technical field, and particularly relates to a rural sewage treatment planning system and method. BACKGROUND

[0002] The quality management of sewage projects is a long-term overall process, and needs data analysis processing and statistics of all personnel in the whole process at various stages from the planning, surveying and designing, construction to the acceptance of the engineering project.

[0003] The current rural sewage treatment planning often relies on the subjective experience of decision makers or copies the sewage treatment strategies of cities, however, there are great differences between rural areas and towns in population distribution, land use types and the like, and the sources of sewage generation in rural areas are also quite different from those in towns; and rural areas often do not carry out much geological modification during construction like towns, so that the terrain changes in rural areas are much greater than those in towns, especially the terrain fluctuation in rural areas located in mountainous areas is more obvious, thereby bringing planning difficulties to sewage pipeline construction, and making the existing rural sewage treatment have a disconnection between planning and actual demand. In the construction process of sewage treatment projects, the complex and changeable factors of various project subjects, construction equipment and materials, construction technology methods and environment form a constraint to the quality management of various sewage project points. The traditional method of relying on manual information collection and analysis and statistics needs to consume a lot of manpower and resources, and since the amount of engineering project data is determined by the size of the engineering project, in the case of a large engineering project size, the current method of relying on manual data statistics cannot ensure the timeliness of data statistics of each engineering point, thereby affecting the subsequent execution efficiency. SUMMARY

[0004] In order to effectively manage the sewage projects and improve the timeliness of engineering management, the present application provides a rural sewage treatment planning system and method, which adopts the following technical solutions:

[0005] In a first aspect, the present application embodiment provides a rural sewage treatment planning system, comprising:

[0006] A planning collection device is configured to acquire construction range information and process requirement information, perform plan analysis on the construction range information and the process requirement information, and obtain engineering plan information; the engineering plan information comprises progress plan information and material requirement plan information;

[0007] A construction collection device is configured to acquire construction real-time information and the engineering plan information, perform completion analysis on the construction real-time information according to the engineering plan information, and obtain construction completion result information.

[0008] Further, the above planning collection device comprises:

[0009] The progress analysis module is configured to acquire task target information, perform task decomposition according to the construction range information and the task target information, and obtain task division information; perform time analysis according to the process requirement information and the task division information, and obtain progress plan information.

[0010] The material requirement analysis module is configured to perform requirement material analysis according to the progress plan information and the process requirement information, and obtain material requirement quantity information; match corresponding procurement scheduling information according to the material requirement quantity information, and obtain material requirement plan information.

[0011] Further, the construction acquisition device comprises:

[0012] The procurement information acquisition module is configured to acquire procurement real-time information and engineering plan information, check the procurement real-time information according to the engineering plan information, and obtain procurement completion result information.

[0013] The labor subcontracting acquisition module is configured to acquire labor subcontracting real-time information and engineering plan information, check the labor subcontracting real-time information according to the engineering plan information, and obtain labor subcontracting situation information.

[0014] Further, the system further comprises a planning generation device.

[0015] The planning generation device is configured to acquire geographical data and biological distribution data of a target rural area, generate a drainage pipeline plan and a sewage treatment site selection of the target rural area according to the geographical data and the biological distribution data, and put the same into the construction range information.

[0016] Further, the planning generation device comprises:

[0017] The data acquisition module is configured to acquire geographical data and biological distribution data of a target rural area.

[0018] The geographical data comprises meteorological and hydrological data, terrain elevation data, land type data and soil permeability data of the target rural area; and the biological distribution data comprises population distribution data and livestock distribution data.

[0019] The data processing module is configured to analyze the geographical data and the biological distribution data, and obtain a sewage load thermal map.

[0020] The load analysis module is configured to generate a drainage pipeline plan based on the geographical data and the sewage load thermal map.

[0021] The intelligent planning module is configured to determine a sewage treatment site selection based on the geographical data and the drainage pipeline plan.

[0022] Further, the data processing module is specifically configured to divide the target rural area into a plurality of grid units based on a preset size.

[0023] The land type data in the geographic data is one-hot encoded; sewage load features of each grid cell are extracted according to the terrain elevation data, biological distribution data and land type data; the sewage load features include neighborhood statistical features, terrain conduction features, land composition proportions, population equivalent and average soil permeability of the grid cell;

[0024] A sewage generation feature matrix is constructed according to a preset sewage coefficient and the sewage load features of each grid cell; the sewage generation feature matrix is input into a sewage load prediction model to obtain a sewage load thermal map.

[0025] Further, the data processing module is specifically configured to determine a lowest point elevation of the target rural area according to the terrain elevation data; the average elevation of each grid cell is subtracted from the lowest point elevation to obtain the drainage potential energy of each grid cell; the runoff accumulation of each grid cell is calculated according to the meteorological and hydrological data; and the drainage potential energy and the runoff accumulation are taken as the terrain conduction features of the grid cell.

[0026] Further, the load analysis module is specifically configured to determine a pollution sensitive area according to the land type data, and to exclude the grid cell in which the pollution sensitive area exists; a natural drainage path is obtained by analyzing the terrain elevation data using a mathematical elevation model and a D8 algorithm.

[0027] The high load unit and the medium load unit in each grid cell are determined according to the sewage load thermal map.

[0028] The high load unit that coincides with the natural drainage path is selected as a target trunk unit.

[0029] A drainage trunk line is constructed according to each target trunk unit and the natural drainage path.

[0030] Each medium load unit and each remaining high load unit is connected to the drainage trunk line to obtain a plurality of drainage branch lines; the drainage trunk line and each drainage branch line are taken as a drainage pipeline plan.

[0031] Further, the load analysis module is further configured to take the grid cell penetrated by the drainage pipeline as a to-be-laid unit.

[0032] The predicted flow of the to-be-laid unit is calculated according to a preset sewage coefficient and the sewage load features of the to-be-laid unit; and the pipeline diameter of the drainage pipeline in the to-be-laid unit is determined according to the Manning formula and the predicted flow.

[0033] Further, the intelligent planning module is specifically configured to take the preset number of grid units at the end of the main drainage line as the to-be-planned units; eliminate the to-be-planned units that do not meet the preset constraint conditions; the preset constraint conditions include an elevation difference constraint, a soil bearing capacity constraint, a soil average permeability constraint, and a road quantity constraint; determine at least one target planning unit in each to-be-planned unit based on a preset evaluation index, a preset index weight, and a GIS spatial analysis model, and take the target planning unit as the sewage treatment site selection.

[0034] Further, the data acquisition module is further configured to acquire detection results of multiple water quality detection points in the target rural area.

[0035] The data processing module is further configured to calculate sewage update weights of grid units in which the water quality monitoring points are located according to the detection results, and update the sewage load thermal map according to the sewage update weights.

[0036] Further, the planning generation device further includes a detection planning module.

[0037] The detection planning module is configured to determine coordinates of the water quality monitoring points according to the land type data.

[0038] Further, the planning generation device further includes a process recommendation module.

[0039] The process recommendation module is configured to calculate an elevation standard deviation of the target rural area according to the terrain elevation data, calculate a corrosion risk value according to the land type data and the soil permeability data, and generate process requirement information according to the elevation standard deviation and the corrosion risk value.

[0040] In a second aspect, an embodiment of the present application provides a rural sewage treatment planning method, including:

[0041] Obtaining construction range information and process requirement information; performing plan analysis on the construction range information and the process requirement information to obtain engineering plan information; the engineering plan information includes progress plan information and material requirement plan information;

[0042] Obtaining construction real-time information and engineering plan information;

[0043] Performing completion analysis on the construction real-time information according to the engineering plan information to obtain construction completion result information.

[0044] Further, the plan analysis on the construction range information and the process requirement information to obtain the engineering plan information includes:

[0045] Obtaining task target information;

[0046] Performing task decomposition according to the construction range information and the task target information to obtain task division information;

[0047] According to the process requirement information and the task division information, time analysis is performed to obtain progress plan information;

[0048] According to the progress plan information and the process requirement information, demand material analysis is performed to obtain material demand quantity information;

[0049] According to the material demand quantity information, corresponding procurement scheduling information is matched to obtain material demand plan information.

[0050] Further, the above-mentioned construction completion analysis according to the engineering plan information on the construction real-time information is performed to obtain construction completion result information, including:

[0051] Obtain procurement real-time information and engineering plan information;

[0052] According to the engineering plan information, the procurement real-time information is checked to obtain procurement completion result information;

[0053] Obtain labor subcontracting real-time information and engineering plan information;

[0054] According to the engineering plan information, the labor subcontracting real-time information is checked to obtain labor subcontracting situation information.

[0055] Further, the method further comprises:

[0056] Obtain geographical data and biological distribution data of the target rural area;

[0057] Among them, the geographical data includes meteorological and hydrological data, terrain elevation data, land type data and soil permeability data of the target rural area; the biological distribution data includes population distribution data and livestock distribution data;

[0058] Analyze the geographical data and the biological distribution data to obtain a sewage load thermal map;

[0059] Generate a drainage pipeline plan based on the geographical data and the sewage load thermal map;

[0060] Determine the sewage treatment site based on the geographical data and the drainage pipeline plan;

[0061] Put the drainage pipeline plan and the sewage treatment site into the construction range information.

[0062] Further, the above-mentioned analysis of the geographical data and the biological distribution data to obtain the sewage load thermal map comprises:

[0063] Divide the target rural area based on a preset size of a grid to obtain a plurality of grid units;

[0064] The land type data in the geographic data is one-hot encoded; sewage load features of each grid cell are extracted according to the terrain elevation data, the biological distribution data and the land type data; wherein, the sewage load features include neighborhood statistical features of the grid cell, terrain conduction features, land composition proportions, population equivalent and average soil permeability;

[0065] A sewage generation feature matrix is constructed according to the preset sewage coefficient and the sewage load features of each grid cell;

[0066] The sewage generation feature matrix is input into a sewage load prediction model to obtain a sewage load thermal map.

[0067] In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to execute the steps of the rural sewage treatment planning method according to any one of the above embodiments.

[0068] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, having a computer program stored thereon, and the computer program is executed by a processor to implement the steps of the rural sewage treatment planning method according to any one of the above embodiments.

[0069] Compared with the prior art, the technical scheme provided by the embodiments of the present application has at least the following beneficial effects:

[0070] The rural sewage treatment planning system provided by the embodiments of the present application obtains construction range information and process requirement information after project planning, analyzes the construction range information and the process requirement information, and processes to obtain engineering plan information, which can provide a reference for project planning personnel. In the case of executing the engineering plan information, the construction collection device obtains construction real-time information and analyzes the completion situation to obtain construction completion result information for the system operator to intuitively understand the construction situation. The planning collection device provides reference data for the completion situation analysis of the construction collection device, so that the sewage project can be effectively managed, and the timeliness of engineering management is improved. BRIEF DESCRIPTION OF DRAWINGS

[0071] Figure 1 A structural diagram of a rural sewage treatment planning system provided for an exemplary embodiment of the present application

[0072] Figure 2 A structural diagram of a planning generation device provided for an exemplary embodiment of the present application.

[0073] Figure 3 A flowchart of a rural sewage treatment planning method provided for an exemplary embodiment of the present application.

[0074] Figure 4 A flow chart of the construction scope information generation step provided for an exemplary embodiment of the present application.

[0075] Figure 5 A flow chart of the sewage load thermal map generation step provided for an exemplary embodiment of the present application.

[0076] Figure 6 A flow chart of the sewer pipeline plan generation step provided for an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0077] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application.

[0078] Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0079] Please refer to Figure 1 The embodiments of the present application provide a rural sewage treatment planning system, which comprises:

[0080] The planning acquisition device is configured to acquire construction scope information and process requirement information, perform plan analysis on the construction scope information and the process requirement information, and obtain engineering plan information; the engineering plan information comprises progress plan information and material requirement plan information.

[0081] The construction scope information comprises a sewer pipeline plan and sewage treatment site selection, and the process requirement information is usually determined according to the nature and design requirements of a project, and the process type used in construction, such as civil engineering process, electrical installation process, etc.

[0082] Specifically, the planning acquisition device comprises:

[0083] The progress analysis module is configured to acquire task target information, perform task decomposition according to the construction scope information and the task target information, and obtain task division information; perform time analysis according to the process requirement information and the task division information, and obtain the progress plan information.

[0084] In the implementation process, the application obtains the construction range information and the process requirement information, and performs plan analysis, specifically task decomposition and time analysis. First, the task target information needs to be obtained. The project task and target of task decomposition are obtained from the overall project task and target in the project planning, such as the total amount of engineering, phased tasks and delivery dates, and also include the requirements of resources and construction period, such as the availability of construction resources and the construction period requirements of the project. Then, according to the construction range and target, the overall project is divided into different construction tasks, and the sequence of each task is determined.

[0085] Specifically, first, various types of data related to the project can be obtained, including the target, task, resource demand, time arrangement, budget, etc. of the project. The data usually comes from project plans, inputs of team members, demand analysis reports, market research data, etc., that is, task target information. Through the integration of project management tools such as Jira, Trello, Microsoft Project, etc., the data can be automatically collected and sorted. Finally, the complex project target is converted into specific work tasks. Through preset rules and algorithms, the computer system automatically decomposes the top-level target according to certain logical rules, such as hierarchical and phased, and generates a work breakdown structure, that is, WBS. For example, based on the requirement document, the system automatically generates related subtasks, thereby completing task decomposition and obtaining task division information, such as the need to use reinforced concrete construction technology for a certain site and the need to use mechanical construction technology for another site. After determining the task division information, the corresponding process requirements are combined for each task division, so as to calculate the corresponding task time consumption. Based on the time and resources required for each task, the application embodiment combines engineering progress plan models such as Gantt chart, critical path method CPM or project review technology method PERT to prepare detailed engineering progress plans. The engineering progress plan is, for example, task A needs to be completed in 5 days, task B needs to be completed in 3 days, and task C depends on task B and is expected to start the next day after task B is completed.

[0086] The final engineering progress plan information specifically lists the specific start and end times of each task in the project, as well as the stages of the project. In one embodiment, the civil part of the project is completed in the first 30 days, the electrical installation is completed in the first 15-45 days, and the corresponding equipment is used for mechanical construction, and the final delivery date is the 90th day.

[0087] The material requirement analysis module is used to analyze the material requirements according to the progress plan information and the process requirement information, and obtain the material requirement quantity information; and match the corresponding procurement scheduling information according to the material requirement quantity information, and obtain the material requirement plan information.

[0088] Specifically, this application determines the type, specifications, and quantity of materials required for each task based on construction drawings and process requirements, and understands information such as the procurement cycle, supplier capacity, and inventory status of each material. First, material requirements are calculated. Based on the project schedule and the process requirements of each task, the quantity of materials required for each task is calculated. For example, a civil engineering task requires 50 tons of steel bars and 500 cubic meters of concrete, while an electrical task requires 1000 meters of cable and 500 sockets. Next, material procurement and scheduling are arranged. Based on the material requirements, the procurement and delivery times are scheduled to ensure timely arrival of materials during construction. This application's implementation combines material procurement cycles and supplier capabilities. For example, certain special materials need to be procured three months in advance, while regular materials can be procured in batches according to the construction schedule. After demand analysis, a material requirements plan is obtained, including the quantity, specifications, procurement time, and delivery plan for each material. For example, 50 tons of steel bars need to arrive on the 10th day of the project, and 500 cubic meters of concrete need to arrive on the 15th day.

[0089] The project schedule information determines the project's time nodes, task allocation, and duration; the material requirements plan arranges the procurement, supply, and distribution of materials based on the construction progress and task requirements. Together, these plans in this application embodiment provide detailed time and material arrangements for project implementation, helping to ensure the project is completed on time, efficiently, and in compliance with regulations.

[0090] The construction data acquisition device is used to obtain real-time construction information and project plan information. Based on the project plan information, it analyzes the completion status of the real-time construction information to obtain construction completion result information. The real-time construction information includes real-time procurement information and real-time labor subcontracting information. The construction completion result information includes procurement completion result information and labor subcontracting status information.

[0091] Specifically, the aforementioned construction data acquisition device includes:

[0092] The procurement information collection module is used to acquire real-time procurement information and project plan information, verify the real-time procurement information against the project plan information, and obtain the procurement completion result information.

[0093] Specifically, upon obtaining project plan information, it is necessary to verify the data or information uploaded by the operators. The real-time procurement information obtained in this embodiment includes procurement pricing, procurement contracts, purchase orders, arrival inspection, and procurement warehousing related information. The procurement pricing includes product pricing information. The procurement contract records detailed information about the procurement contract.

[0094] The purchase order is the generated purchase order details. The arrival inspection record is the result of inspection after the goods arrive. The purchase storage record is the information of the material entering the warehouse. The embodiment of the application counts whether the material has been satisfied according to the demand plan. The purchase situation of the material is judged by tracking the cumulative state of the ordered and un-ordered, the ordered and un-ordered, the arrived and un-arrived, and the stored and un-stored. The current purchase stage of the material is tracked. After comparison, if the price is determined, the material price is determined; if the contract is signed, the purchase contract is signed; if the order is placed, the purchase order is placed; if the goods arrive, the material arrives and is inspected; and if the goods are stored, the material is completed. The final purchase completion result information obtained by the embodiment of the application is the demand state and the purchase stage of each material, including whether the material has completed the steps of ordering, ordering, arrival and storage. The purchase progress summary helps to judge whether the material demand has been met, and provides a basis for subsequent purchase decision.

[0095] The labor subcontracting collection module is used to obtain labor subcontracting real-time information and engineering plan information, check the labor subcontracting real-time information according to the engineering plan information, and obtain labor subcontracting situation information.

[0096] Specifically, in the case of obtaining the engineering plan information, the data or information uploaded by the operator needs to be verified. The labor subcontracting real-time information obtained by the embodiment of the application includes subcontracting pricing, subcontracting contract, subcontracting measurement, subcontracting visa, and subcontracting completion settlement documents. Among them, the subcontracting pricing is the pricing and pricing situation of the subcontracting project; the subcontracting contract records the contract content signed with the subcontractor; the subcontracting measurement records the measurement data of the subcontracting project, including the engineering quantity; the subcontracting visa refers to the visa record of engineering changes or special circumstances in the subcontracting process; and the subcontracting completion settlement document records the settlement information after the completion of the subcontracting project.

[0097] According to the demand plan, the embodiment of the application needs to count the cumulative completed engineering quantity, including the completed and uncompleted work quantity under the subcontracting item; summarize the occurred visas, such as delay of construction period, change, etc., and calculate the influence on the engineering progress; count the final completed engineering quantity, that is, the overall completion situation of all subcontracting projects, and then analyze the material and labor cost.

[0098] The material and labor cost analysis specifically counts the types and quantities of materials consumed by the completed engineering quantity. Specifically, which raw materials are used in the engineering completion process and the quantity, and the number of labor workers and working hours involved in the project are calculated, including the working time of each type of work and the number of workers involved, and finally the labor subcontracting situation information is obtained.

[0099] The labor subcontracting information includes engineering quantity statistics, specifically showing the cumulative completed engineering quantity and visa conditions; includes material consumption and labor input, specifically and in detail listing the types and quantities of materials used in the subcontracting project, and the input conditions of labor workers; includes subcontracting settlement data, specifically generating final subcontracting settlement information according to the completion conditions and related documents.

[0100] It can be understood that, in order to cope with the complexity of the sewage project, the embodiments of the present application obtain the construction range information and process requirement information obtained after the project planning, analyze the construction range information and process requirement information, and process to obtain engineering plan information. The engineering plan information can provide a reference for project planning personnel, and in the case of execution according to the engineering plan information, the construction acquisition device obtains the construction real-time information and the completion condition analysis of the engineering plan information, and obtains the construction completion result information for the system operator to intuitively understand the construction situation. And the planning acquisition device provides reference data for the completion condition analysis of the construction acquisition device, reduces manual judgment and management, can more effectively cope with large data sewage projects, so that the sewage project can be effectively managed, and the effectiveness and timeliness of engineering management can be improved.

[0101] In some embodiments, referring to Figure 1 , the system further includes a planning generation device.

[0102] The above planning generation device is used to obtain geographical data and biological distribution data of a target rural area, generate a drainage pipeline plan and a sewage treatment site selection of the target rural area according to the geographical data and the biological distribution data, and put into the construction range information.

[0103] Specifically, referring to Figure 2 , the above planning generation device includes:

[0104] A data acquisition module is configured to obtain geographical data and biological distribution data of a target rural area.

[0105] The geographical data includes meteorological and hydrological data, terrain elevation data, land type data, and soil permeability data of the target rural area; and the biological distribution data includes population distribution data and livestock distribution data.

[0106] Specifically, the meteorological and hydrological data includes rainfall intensity (or rainfall) of the target rural area, and distribution, water storage and flow rate of rivers and lakes; the land type data is various land types (such as livestock land, agricultural land, residential land, forest, wasteland, etc.) owned by the target rural area; it is worth noting that the soil permeability data is added in the geographical data, because the land of the town is basically covered by cement or asphalt, and most of the rainfall is discharged through the constructed drainage pipe, while the modernization degree of the rural area is less than that of the town, and there are still a lot of bare land, and there are also a lot of farmland, which will make the rainfall directly penetrate the soil into the underground, so that the consideration weight of rainfall pollution in the rural sewage intelligence construction is less than that in the town.

[0107] Further, because the rainfall in the rural area directly penetrates the soil, the construction of the drainage pipe in the rural area also needs to consider the influence of water seepage and corrosion when selecting the laying depth and construction process, therefore, the soil permeability data is added to the sewage load analysis in the present application, which can make the sewage load analysis of the rural area more accurate, and the sewage treatment construction more practical.

[0108] The data processing module is used to analyze the geographical data and the biological distribution data to obtain a sewage load thermal map.

[0109] The data processing module divides the target rural area into grid units of a preset size, for example, 100m x 100m, for the rural area in the mountainous area with scattered distribution, the preset size can be set larger, for example, 300m x 300m or 500m x 500m, and the generated sewage load thermal map includes the sewage load value of each grid unit.

[0110] Specifically, unlike the land types of the town which are concentrated in factories, commerce and residence, the sewage load of the town generally presents a trend of spreading around the core of the city center and industrial center, the land types of the rural area are various and scattered, the sewage source is not concentrated, and the drainage flow direction is greatly affected by the change of terrain, therefore, the grid unit is used for division and analysis, which can fully consider the sewage generation of different areas of the rural area, and realize accurate sewage treatment planning.

[0111] The load analysis module is used to generate a drainage pipe plan based on the geographical data and the sewage load thermal map.

[0112] The intelligent planning module is used to determine the sewage treatment site based on the geographical data and the drainage pipe plan.

[0113] The planning generation device provided by the above embodiment collects geographical data and biological distribution data of the rural area through the data collection module; it is worth noting that one of the main differences between rural and urban areas is that rural areas can have various livestock farms, so the sewage load cannot be simply considered based on population distribution, and the livestock factor also needs to be considered; at the same time, considering that the water use intensity of rural areas is much lower than that of urban areas, the data processing module of the present application generates a sewage load heat map in combination with the geographical and biological distribution data of the rural area to clearly define the sewage load of different regions in the rural area; finally, the load analysis module and the intelligent planning module determine the drainage pipeline plan and the sewage treatment site based on the geographical data and the sewage load heat map of the rural area; the planning generation device of the present application fully considers the differences between rural and urban areas, so that the drainage pipeline plan and the sewage treatment site determined based on the geographical data and the biological distribution data of the rural area can well meet the actual sewage generation situation and treatment needs of the rural area.

[0114] In some embodiments, the data processing module is specifically configured to divide the target rural area into a plurality of grid units based on a preset size; perform one-hot encoding on the land type data in the geographical data; extract sewage load features of each grid unit according to the terrain elevation data, the biological distribution data and the land type data; the sewage load features include neighborhood statistical features, terrain conduction features, land composition proportions, population equivalents and average soil permeability of the grid unit.

[0115] The one-hot encoding is a technique for converting categorical variables into a numerical form that can be understood by machine learning algorithms. The land type data is different from the terrain elevation and biological distribution data in that its content is not a vector or a number, but a categorical label represented by text. Directly using these categorical labels for calculation may introduce misleading numerical relationships for the machine learning model. One-hot encoding can clearly represent the differences between different land types without introducing any numerical partial order relationships. This allows the subsequent sewage load prediction model to more accurately understand and process these features, thereby improving the accuracy of predicting sewage load.

[0116] Specifically, in the sewage load features, the calculation formula of the population equivalent is:

[0117] Resident population + ∑(livestock number x preset conversion population coefficient)

[0118] The livestock number includes the number of animals related to human activities such as livestock breeding and pet breeding in the grid unit, which can be considered as quantifying human activities and livestock pollution as "population equivalent" in the present application.

[0119] The calculation of the average soil permeability is relatively simple, that is, the soil permeability of each place in the grid unit is averaged, and the integral or area weight method can be used to calculate it.

[0120] The calculation of the land composition proportion is also relatively simple, that is, the area proportion of each land type and the area of the entire grid cell.

[0121] The neighborhood statistical features of the grid cell with coordinates (x, y) can be calculated through a 3x3 neighborhood window.

[0122]

[0123] wherein w i,j is a preset distance attenuation weight, the greater the distance, the smaller the weight, for example, the weight of the center grid (i and j are both 0) = 0.3, the weight of the adjacent grid (i or j is 0) = 0.2, and the weight of the diagonal grid (i and j are both not 0) = 0.1; d x+i,y+j is the population equivalent of the grid cell with coordinates (x+i, y+j), and a is a preset sewage coefficient, with a unit of m 3 / person·day.

[0124] It should be noted that the neighborhood statistical features are introduced in the present application, considering the slight mobility of the population in rural areas and the diffusion and transmission of sewage between adjacent grid cells due to land seepage, thereby further improving the prediction accuracy of the sewage load.

[0125] The data processing module is further configured to determine a lowest point elevation of the target rural area according to the terrain elevation data; subtract the lowest point elevation from the average elevation of each grid cell to obtain a drainage potential of each grid cell; and calculate a runoff accumulation of each grid cell according to the meteorological and hydrological data, and take the drainage potential and the runoff accumulation as the topographic conduction features of the grid cell.

[0126] Specifically, the drainage potential = grid average elevation - downstream lowest point elevation, and the runoff accumulation = catchment area calculated by the flow direction algorithm x rainfall intensity. The calculation of the runoff accumulation is recorded in many geographical related documents, and will not be repeated here.

[0127] Then, the data processing module constructs a sewage generation feature matrix according to the preset sewage coefficient and the sewage load features of each grid cell; inputs the sewage generation feature matrix into the sewage load prediction model to obtain a sewage load thermal map.

[0128] wherein the preset sewage coefficient is multiplied by the population equivalent of the grid cell to obtain the sewage production equivalent of the corresponding grid cell, and the sewage production equivalent, the neighborhood statistical features, the topographic conduction features, the land composition proportion and the average soil permeability of each grid cell are taken as the matrix elements of the grid cell and put into the sewage generation feature matrix; that is, the row and column of the sewage generation feature matrix are consistent with the row and column of the divided grid cells, and each matrix element is the feature data of the corresponding grid cell.

[0129] Specifically, the sewage load prediction model can be trained by using a machine learning model. In the specific application process, a random forest model is used, but this is not limited here. Support vector machines, graph convolution networks, and other models can also be used.

[0130] Further, after the sewage load prediction model outputs the predicted sewage load value of each grid cell, the predicted sewage load value can be subjected to Kriging interpolation to achieve smoothing processing, thereby obtaining a sewage load thermal map.

[0131] The above embodiment designs a feature extraction algorithm according to the characteristics of sewage generation in rural areas, and then predicts the sewage load value of each grid cell according to the extracted sewage load characteristics, thereby improving the prediction accuracy of the sewage load.

[0132] In some embodiments, the load analysis module is specifically configured to perform the following steps:

[0133] In step S031, a sewage-sensitive area is determined according to land type data, and grid cells in the sewage-sensitive area are removed.

[0134] Specifically, for rural areas, there are some sensitive areas that cannot be built with sewage treatment facilities, such as farmland (sewage will affect crops), wasteland (low development level, difficulty in maintaining drainage pipes), water sources, protected areas, and the like. Therefore, the grid cells containing these sensitive areas are first removed to avoid temporary changes to the construction plan during construction.

[0135] In step S032, a natural drainage path is obtained by analyzing the terrain elevation data by using a mathematical elevation model and a D8 algorithm.

[0136] Specifically, the analysis of the natural drainage path is also a common process in the field of geology, and details are not described here.

[0137] However, it should be noted that although the analysis algorithm of the natural drainage path is not the innovation of the present application, the improvement point of the present application is to apply the analysis algorithm to the rural sewage treatment planning. This is a manifestation of the present application that fully considers that the terrain change in rural areas is greater than that in urban areas, and is an operation that can reduce the number of pump stations for rural sewage treatment and reduce the cost of sewage treatment.

[0138] In step S033, high-load cells and medium-load cells in each grid cell are determined according to the sewage load thermal map.

[0139] Specifically, according to the sewage load value of each grid unit in the sewage load thermal diagram, the top 10% or the top 20% of the grid units are ranked from large to small, the last 20% or 30% of the grid units are ranked as low load units, and the remaining grid units are ranked as medium load units. In addition to the ranking method, a natural breakpoint method, an equal interval classification method or a threshold judgment method can be used to determine the high load units and the medium load units.

[0140] Step S034, screening the high load units coinciding with the natural drainage path as the target trunk units.

[0141] Specifically, since the rural sewage treatment planning needs to consider the construction cost, the application simultaneously considers the natural drainage path and the high load units, so that the sewage can flow as much as possible by using the gravitational potential energy while ensuring that the areas with large sewage load can be quickly drained, reducing the construction of pump stations on the trunk line, thereby reducing the construction cost.

[0142] Step S035, constructing a drainage trunk line according to each target trunk unit and the natural drainage path.

[0143] Specifically, if the target trunk units cannot be connected into a line, the trunk line at the disconnected part is preferably coincided with the natural drainage path. In the specific implementation process, it is found that since the area of a single rural area is generally small, the drainage trunk line planned by the above algorithm basically does not exist a too large winding or curve.

[0144] If there are extremely rare cases of large rural areas or a small number of high load units, each target trunk unit can be directly connected into a line (directly connected in the middle), to obtain a first trunk line, and the number of pump stations required on the first trunk line is obtained according to the terrain elevation data; the method of step S35 is used to construct a second trunk line and the corresponding number of pump stations, the construction cost is calculated according to the length of the trunk line and the number of pump stations, and the trunk line with the lowest cost is selected as the drainage trunk line.

[0145] Step S036, connecting each medium load unit and each remaining high load unit to the drainage trunk line to obtain a plurality of drainage branch lines; the drainage trunk line and each drainage branch line are used as a drainage pipeline plan.

[0146] The above embodiment combines the terrain elevation data to obtain the natural drainage path of the target rural area, and combines the natural drainage path and the high load units with high sewage treatment demand to determine the drainage trunk line, thereby reducing the construction cost while ensuring to meet the drainage demand.

[0147] In some embodiments, the load analysis module is further configured to: take the grid cell through which the drainage pipeline runs as a to-be-laid cell; calculate a predicted flow of the to-be-laid cell according to a preset sewage coefficient and sewage load characteristics of the to-be-laid cell; and determine a pipeline diameter of the drainage pipeline in the to-be-laid cell according to the Manning formula and the predicted flow.

[0148] Specifically, the predicted flow can be obtained by multiplying the preset sewage coefficient and the population equivalent, and then adding a product of a catchment area (a pipeline cross-sectional area, which is calculated from a pipeline radius) and a runoff coefficient (a preset value).

[0149] The Manning formula is specifically used in an iteration process.

[0150]

[0151] wherein Q is the predicted flow, n is the Manning coefficient (depending on the material used for the drainage pipeline, 0.013 for a concrete pipeline and 0.009 for a plastic pipeline), A is the flow area, D is the pipeline diameter, μ is the fullness, generally taken as 0.6-0.8, R is the hydraulic radius, and S is the slope of the to-be-laid cell, which can be directly obtained from the terrain elevation data.

[0152] Specifically, in the iteration process, Q, S, n, an initial pipeline diameter D0 and an initial flow rate v are input.

[0153] Then, the Chezy coefficient C is calculated.

[0154]

[0155] The actual flow rate is calculated.

[0156]

[0157] It is determined whether an absolute value of a difference between the actual flow rate and the initial flow rate is less than a preset error (generally taken as 5%), if not, the pipeline diameter is adjusted and the above steps are re-executed, and if yes, the current pipeline diameter is taken as the pipeline diameter of the to-be-laid cell.

[0158] The above embodiments can accurately calculate the optimal pipeline diameter of the to-be-laid cell to meet the sewage flow based on the sewage load characteristics of the to-be-laid cell, and reduce the cost of pipeline materials while realizing sewage transmission.

[0159] In some embodiments, the intelligent planning module is specifically configured to perform the following steps:

[0160] In step S041, a preset number of grid cells located at the end of the drainage main line are taken as to-be-planned cells.

[0161] In step S042, the to-be-planned cells that do not meet the preset constraint conditions are removed.

[0162] The preset constraint conditions can include an elevation difference constraint, a soil bearing capacity constraint, a soil average permeability constraint, and a road quantity constraint. That is, in determining the location of the sewage treatment plant, first, the land blocks that do not meet the requirements for building the plant are excluded.

[0163] Specifically, the elevation difference constraint is that the slope of the unit to be planned cannot be higher than a threshold (5%), otherwise the cost of filling and digging is too high; the soil bearing capacity constraint is that the soil bearing capacity of the unit to be planned needs to be greater than a certain threshold (100 kPa) to meet the foundation requirements of the structure; the soil average permeability constraint is that the soil average permeability of the unit to be planned needs to be less than a certain threshold to reduce the risk of leakage; and the road quantity constraint is that the roads contained in the unit to be planned need to be greater than a certain threshold to facilitate construction and maintenance.

[0164] In step S043, at least one target planning unit is determined in each unit to be planned based on the preset evaluation index, the preset index weight, and the GIS spatial analysis model, and the target planning unit is taken as the sewage treatment location.

[0165] The preset evaluation index and the preset index weight are required data for the GIS spatial analysis model to analyze, for example, the weight of construction cost is 30%, the weight of operation efficiency is 20%, and the like.

[0166] The GIS spatial analysis model will calculate the cost grid, AHP decision, and the like according to these evaluation indexes and corresponding weights, and finally determine the optimal unit to be planned that meets these evaluation indexes as the target planning unit.

[0167] In some embodiments, the data acquisition module is also configured to acquire detection results of multiple water quality detection points in the target rural area.

[0168] The data processing module is also configured to calculate sewage update weights of grid cells where the water quality monitoring points are located according to the detection results, and update the sewage load heat map according to the sewage update weights.

[0169] Specifically, the detection results are compared horizontally to obtain the severity of each detection result as the sewage update weight, and the sewage load value and the sewage update weight of the corresponding grid cell are used to update the sewage load heat map.

[0170] The above embodiments further update the sewage load values in the sewage load heat map according to the acquired water quality detection results after generating the sewage load heat map, so that the sewage treatment demand expressed by the sewage load heat map is more accurate.

[0171] In some embodiments, the system further includes a detection planning module.

[0172] The detection planning module is configured to determine the coordinates of each water quality monitoring point according to the land type data.

[0173] Specifically, the detection planning module determines the land composition proportion according to the land type data, and regards a grid unit with a proportion of a certain type exceeding a certain preset threshold as a coordinate unit of a water quality monitoring point.

[0174] For example, a grid unit with a proportion of livestock land exceeding 1 / 3 needs to set a water quality monitoring point at a downstream position.

[0175] In some embodiments, the system further comprises a process recommendation module.

[0176] The process recommendation module is configured to calculate an elevation standard deviation of the target rural area according to the terrain elevation data, calculate a corrosion risk value according to the land type data and the soil permeability data, and generate process recommendation information according to the elevation standard deviation and the corrosion risk value.

[0177] The corrosion risk value can be calculated by using a quantitative analysis method such as fault tree analysis (FTA).

[0178] Specifically, the process recommendation module is configured to include a process recommendation table, and different elevation standard deviations and corrosion risk values correspond to recommended process types. For example, in the case of a drainage pipe material process, a rural area with a large elevation standard deviation has many bends in the drainage pipe, so the pipe material is preferably a material with good ductility such as plastic. A high corrosion risk value indicates that the underground soil is humid and has a high oxygen content, so metal materials are prone to oxidation and should be avoided when laying pipes. A low corrosion risk value indicates that the soil is too dry, which may cause pipe settlement, so the pipe material needs to be selected to have a small density and a light weight.

[0179] See Figure 3 Another embodiment of the present application provides a rural sewage treatment planning method, comprising:

[0180] Step S11, obtaining construction range information and process requirement information.

[0181] Step S12, performing plan analysis on the construction range information and the process requirement information to obtain engineering plan information.

[0182] The engineering plan information includes progress plan information and material requirement plan information.

[0183] Step S13, obtaining construction real-time information and engineering plan information.

[0184] Step S14, performing completion analysis on the construction real-time information according to the engineering plan information to obtain construction completion result information.

[0185] In some embodiments, the above-mentioned plan analysis on the construction range information and the process requirement information to obtain the progress plan information and the material requirement plan information comprises:

[0186] Step S121, obtain task target information.

[0187] Step S122, perform task decomposition according to the construction range information and the task target information to obtain task division information.

[0188] Step S123, perform time analysis according to the process requirement information and the task division information to obtain progress plan information.

[0189] Step S124, perform demand material analysis according to the progress plan information and the process requirement information to obtain material demand quantity information.

[0190] Step S125, match corresponding procurement scheduling information according to the material demand quantity information to obtain material demand plan information.

[0191] In some embodiments, the above-mentioned completion analysis of the construction real-time information according to the engineering plan information to obtain construction completion result information includes:

[0192] Step S141, obtain procurement real-time information and engineering plan information.

[0193] Step S142, check the procurement real-time information according to the engineering plan information to obtain procurement completion result information.

[0194] Step S143, obtain labor subcontracting real-time information and engineering plan information.

[0195] Step S144, check the labor subcontracting real-time information according to the engineering plan information to obtain labor subcontracting situation information.

[0196] In some embodiments, referring to Figure 4 , the method further includes:

[0197] Step S01, obtain geographical data and biological distribution data of a target rural area.

[0198] The geographical data includes meteorological and hydrological data, terrain elevation data, land type data, and soil permeability data of the target rural area; and the biological distribution data includes population distribution data and livestock distribution data.

[0199] Step S02, analyze the geographical data and the biological distribution data to obtain a sewage load thermal map.

[0200] Step S03, generate a drainage pipeline plan map based on the geographical data and the sewage load thermal map.

[0201] Step S04, determine sewage treatment site selection based on the geographical data and the drainage pipeline plan map.

[0202] Step S05, put the sewer pipeline planning map and sewage treatment site selection into the construction range information.

[0203] Further, please refer to Figure 5 The above analysis of geographical data and biological distribution data obtains a sewage load thermal map, including:

[0204] Step S021, divide the target rural area based on a preset size of a grid to obtain a plurality of grid units.

[0205] Step S022, one-hot encoding is performed on the land type data in the geographical data.

[0206] Step S023, extracting sewage load characteristics of each grid unit according to the terrain elevation data, biological distribution data and land type data; wherein the sewage load characteristics include neighborhood statistical characteristics, terrain conduction characteristics, land composition proportion, population equivalent and average soil permeability of the grid unit.

[0207] Step S024, constructing a sewage generation feature matrix according to a preset sewage coefficient and the sewage load characteristics of each grid unit.

[0208] Step S025, inputting the sewage generation feature matrix into a sewage load prediction model to obtain a sewage load thermal map.

[0209] Further, the method further comprises:

[0210] Step S0231, determining the lowest point elevation of the target rural area according to the terrain elevation data.

[0211] Step S0232, subtracting the lowest point elevation from the average elevation of each grid unit to obtain the drainage potential energy of each grid unit.

[0212] Step S0233, calculating the runoff accumulation of each grid unit according to the meteorological and hydrological data.

[0213] Step S0234, taking the drainage potential energy and the runoff accumulation as the terrain conduction characteristics of the grid unit.

[0214] Further, please refer to Figure 6 The above generating a sewer pipeline planning map based on geographical data and a sewage load thermal map comprises:

[0215] Step S031, determining a sewage discharge sensitive area according to the land type data, and excluding the grid unit in which the sewage discharge sensitive area exists.

[0216] Step S032, analyzing the terrain elevation data by using a mathematical elevation model and a D8 algorithm to obtain a natural drainage path.

[0217] Step S033, determining high-load units and medium-load units in each grid unit according to the sewage load thermal map.

[0218] Step S034, screening high-load units coinciding with the natural drainage path as target trunk units.

[0219] Step S035, constructing a drainage trunk line according to each target trunk unit and the natural drainage path.

[0220] Step S036, connecting each medium-load unit and each remaining high-load unit to the drainage trunk line to obtain a plurality of drainage branch lines; taking the drainage trunk line and each drainage branch line as a drainage pipeline plan.

[0221] Further, the method further comprises:

[0222] Step S061, taking a grid unit penetrated by the drainage pipeline as a unit to be laid;

[0223] Step S062, calculating a predicted flow of the unit to be laid according to a preset sewage coefficient and a sewage load characteristic of the unit to be laid;

[0224] Step S063, determining a pipeline diameter of the drainage pipeline in the unit to be laid according to the Manning formula and the predicted flow.

[0225] Further, the above determining sewage treatment site based on geographic data and the drainage pipeline plan comprises:

[0226] Step S041, taking a preset number of grid units located at the end of the drainage trunk line as units to be planned.

[0227] Step S042, eliminating the units to be planned that do not meet preset constraint conditions; wherein, the preset constraint conditions include an elevation difference constraint, a soil bearing capacity constraint, a soil average permeability constraint and a road quantity constraint.

[0228] Step S043, determining at least one target planning unit in each unit to be planned based on a preset evaluation index, a preset index weight and a GIS spatial analysis model, and taking the target planning unit as a sewage treatment site.

[0229] Further, the method further comprises:

[0230] Step S071, collecting detection results of a plurality of water quality detection points in the target rural area.

[0231] Step S072, calculating a sewage update weight of a grid unit in which each water quality monitoring point is located according to each detection result.

[0232] Step S073, updating the sewage load thermal map according to each sewage update weight.

[0233] The specific limitation of the rural sewage treatment planning device provided in the embodiment can be referred to the embodiment of the rural sewage treatment planning method, which will not be repeated here.

[0234] The computer device provided in the embodiment can include a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with the external terminal through the network connection. The computer program is executed by the processor, so that the processor executes the steps of the rural sewage treatment planning method of any one of the above embodiments.

[0235] The working process, working details and technical effects of the computer device provided in the embodiment can be referred to the embodiment of the rural sewage treatment planning method, which will not be repeated here.

[0236] The computer readable storage medium provided in the embodiment stores a computer program, and the computer program is executed by the processor to realize the steps of the rural sewage treatment planning method of any one of the above embodiments. The computer readable storage medium refers to a carrier for storing data, which can include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash memory, a USB flash disk and / or a memory stick, etc. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices. The working process, working details and technical effects of the computer readable storage medium provided in the embodiment can be referred to the embodiment of the rural sewage treatment planning method, which will not be repeated here.

[0237] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, databases, or other media in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0238] The technical features of the above embodiments can be combined in any way. In order to make the description simple, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not exist, they should be considered as the scope of the present application.

[0239] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, some modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of the patent of the present application should be subject to the appended claims.

Claims

1. A rural sewage treatment planning system, characterized in that, include: A planning and data acquisition device is used to acquire construction scope information and process requirement information, perform planning analysis on the construction scope information and process requirement information, and obtain project planning information; the project planning information includes schedule planning information and material requirement planning information. The construction data acquisition device is used to acquire real-time construction information and project plan information, and to analyze the completion status of the real-time construction information based on the project plan information to obtain construction completion result information. A planning generation device is used to acquire geographical and biological distribution data of a target rural area, generate a drainage pipeline plan and sewage treatment site selection for the target rural area based on the geographical and biological distribution data, and incorporate the construction scope information. The planning generation device includes a data acquisition module, a data processing module, a load analysis module, and an intelligent planning module; The data acquisition module is used to acquire geographical and biological distribution data of the target rural area; The geographic data includes meteorological and hydrological data, topographic elevation data, land type data, and soil infiltration data for the target rural area; the biological distribution data includes population distribution data and livestock distribution data. The data processing module is used to divide the target rural area into multiple grid cells based on a preset size; perform unique heat encoding on the land type data in the geographic data; extract the wastewater load characteristics of each grid cell based on the topographic elevation data, the biological distribution data, and the land type data; the wastewater load characteristics include the neighborhood statistical characteristics, topographic transmission characteristics, land composition ratio, population equivalent, and average soil permeability of the grid cell; construct a wastewater generation feature matrix based on a preset wastewater coefficient and the wastewater load characteristics of each grid cell; input the wastewater generation feature matrix into a wastewater load prediction model to obtain a wastewater load heat map; specifically, determine the lowest point elevation of the target rural area based on the topographic elevation data; subtract the lowest point elevation from the average elevation of each grid cell to obtain the drainage potential energy of each grid cell; calculate the runoff accumulation of each grid cell based on the meteorological and hydrological data; and use the drainage potential energy and the runoff accumulation as the topographic transmission characteristics of the grid cell. The load analysis module is used to determine sewage-sensitive areas based on the land type data, and remove grid cells containing sewage-sensitive areas; analyze the terrain elevation data using a mathematical elevation model and the D8 algorithm to obtain natural drainage paths; determine high-load and medium-load units in each grid cell based on the sewage load heat map; select high-load units that overlap with the natural drainage paths as target trunk units; construct drainage trunk lines based on each target trunk unit and the natural drainage path; connect each medium-load unit and the remaining high-load units to the drainage trunk lines to obtain multiple drainage branches; and use the drainage trunk lines and each drainage branch line as a drainage pipeline plan. The intelligent planning module is used to determine the site selection for sewage treatment based on the geographic data and the drainage pipeline plan.

2. The rural sewage treatment planning system according to claim 1, characterized in that, The planning data acquisition device includes: The progress analysis module is used to obtain task objective information, decompose tasks based on construction scope information and task objective information to obtain task division information, and perform time analysis based on process requirements information and task division information to obtain progress plan information. The Material Requirements Analysis module is used to analyze the required materials based on the schedule information and process requirements information to obtain the material requirement quantity information; and to match the corresponding procurement scheduling information with the material requirement quantity information to obtain the material requirement plan information.

3. The rural sewage treatment planning system according to claim 1, characterized in that, The construction data acquisition device includes: The procurement information collection module is used to acquire real-time procurement information and project plan information, verify the real-time procurement information against the project plan information, and obtain procurement completion result information. The labor subcontracting data collection module is used to obtain real-time labor subcontracting information and project plan information, and to verify the real-time labor subcontracting information against the project plan information to obtain labor subcontracting status information.

4. The rural sewage treatment planning system according to claim 1, characterized in that, The load analysis module is also used to treat the grid cells through which the drainage pipes pass as the cells to be laid. The predicted flow rate of the unit to be laid is calculated based on the preset sewage coefficient and the sewage load characteristics of the unit to be laid; the pipe diameter of the drainage pipe in the unit to be laid is determined based on the Manning formula and the predicted flow rate.

5. The rural sewage treatment planning system according to claim 4, characterized in that, The intelligent planning module is specifically used to use a preset number of grid units located at the end of the main drainage line as units to be planned. Eliminate the planned units that do not meet the preset constraints; the preset constraints include elevation difference constraints, soil bearing capacity constraints, average soil permeability constraints, and road quantity constraints. Based on preset evaluation indicators, preset indicator weights, and a GIS spatial analysis model, at least one target planning unit is determined in each of the planned units, and the target planning unit is used as the site selection for the wastewater treatment.

6. The rural sewage treatment planning system according to claim 5, characterized in that, The data acquisition module is also used to collect the test results from multiple water quality monitoring points in the target rural area; The data processing module is also used to calculate the wastewater update weight of the grid unit where the corresponding water quality monitoring point is located based on each of the detection results, and update the wastewater load heat map based on each of the wastewater update weights.

7. The rural sewage treatment planning system according to claim 6, characterized in that, The planning generation device also includes a planning detection module, which is used to determine the coordinates of each water quality monitoring point based on land type data.

8. The rural sewage treatment planning system according to claim 1, characterized in that, The planning generation device also includes a process recommendation module, used to calculate the elevation standard deviation of the target rural area based on the terrain elevation data; Calculate the corrosion risk value based on the land type data and the soil permeability data; Process requirement information is generated based on the elevation standard deviation and the corrosion risk value.

9. A rural sewage treatment planning method, characterized in that, include: Obtain construction scope information and process requirements information; perform planning analysis on the construction scope information and process requirements information to obtain project plan information; wherein, the project plan information includes schedule plan information and material requirements plan information; Obtain real-time construction information and project plan information; Based on the project plan information, the real-time construction information is analyzed to obtain the construction completion result information; Obtain geographical and biological distribution data for the target rural area; The geographic data includes meteorological and hydrological data, topographic elevation data, land type data, and soil infiltration data for the target rural area; the biological distribution data includes population distribution data and livestock distribution data. The target rural area is divided into multiple grid cells based on a preset size grid. The land type data in the geographic data is uniquely encoded. The wastewater load characteristics of each grid cell are extracted based on the topographic elevation data, the biological distribution data, and the land type data. A wastewater generation feature matrix is ​​constructed based on a preset wastewater coefficient and the wastewater load characteristics of each grid cell. The wastewater generation feature matrix is ​​input into the wastewater load prediction model to obtain the wastewater load heat map. The wastewater load characteristics include the neighborhood statistical characteristics, topographic transmission characteristics, land composition ratio, population equivalent, and average soil permeability of the grid cells. Specifically, the lowest point elevation of the target rural area is determined based on the topographic elevation data; the average elevation of each grid cell is subtracted from the lowest point elevation to obtain the drainage potential energy of each grid cell; the runoff accumulation of each grid cell is calculated based on the meteorological and hydrological data; and the drainage potential energy and the runoff accumulation are used as the topographic transmission characteristics of the grid cells. Based on the land type data, sensitive areas for sewage discharge are identified, and grid cells containing such sensitive areas are removed. The topographic elevation data is analyzed using a mathematical elevation model and the D8 algorithm to obtain natural drainage paths. High-load and medium-load cells in each grid cell are determined based on the sewage load heat map. High-load cells that overlap with the natural drainage paths are selected as target trunk cells. A main drainage line is constructed based on each target trunk cell and the natural drainage path. Each medium-load cell and the remaining high-load cells are connected to the main drainage line to obtain multiple drainage branches. The main drainage line and each drainage branch form a drainage pipeline plan. Wastewater treatment site selection is determined based on geographic data and drainage pipeline planning maps; The drainage pipeline plan and sewage treatment site selection are included in the construction scope information.

10. The rural sewage treatment planning method according to claim 9, characterized in that, The aforementioned analysis of the construction scope information and process requirements information yields project plan information, including: Obtain task objective information; Based on the construction scope information and the task objective information, the task is decomposed to obtain task division information; Based on the process requirements information and the task allocation information, a time analysis is performed to obtain the schedule information; Based on the schedule information and the process requirements information, a material demand analysis is performed to obtain material demand information. Based on the material demand information, the corresponding procurement scheduling information is matched to obtain the material demand plan information.

11. The rural sewage treatment planning method according to claim 9, characterized in that, The process of analyzing the real-time construction information based on the project plan information to obtain construction completion result information includes: Obtain real-time procurement information and project planning information; The procurement results are obtained by verifying the real-time procurement information against the project plan information. Obtain real-time information on labor subcontracting and project plans; The labor subcontracting information is verified against the project plan information to obtain the labor subcontracting status information.

12. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the rural wastewater treatment planning method as described in any one of claims 9 to 11.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the rural wastewater treatment planning method as described in any one of claims 9 to 11.

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