Intelligent monitoring method and system for sewage treatment

Abstract

The invention relates to the technical field of sewage treatment, in particular to an intelligent monitoring method and system for sewage treatment, and the method comprises the steps: obtaining the sewage discharge amount, water quality parameters and drainage point coordinates of a rainwater collection drainage node through a sensor, and carrying out the pretreatment; calculating the real-time load rate based on the real-time sewage discharge amount and the maximum pipeline design flow, analyzing the water quality difference between adjacent nodes and the water quality difference of the pipeline, calculating the path distance by combining the coordinates of the drainage point, comprehensively evaluating the discharge suitability index by adopting an exponential function, fusing the real-time load rate to form a comprehensive dynamic weight, and obtaining the optimal path by utilizing an A algorithm. Conflict is processed based on comprehensive dynamic weight, intelligent selection of drainage paths is achieved, and drainage network operation is optimized. According to the method, the water quality difference between the drainage nodes and the water quality difference of the pipelines are calculated, and the drainage path selection is optimized, so that the pollutant diffusion risk is reduced, and the sewage treatment efficiency and suitability are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sewage treatment. In particular, it relates to a sewage treatment intelligent monitoring method and system. BACKGROUND

[0002] A sponge city is a modern urban rainwater management concept that aims to absorb, infiltrate, and purify rainwater in a natural way, just like a sponge, so that the city can absorb and store rainwater during rainfall and release it when needed. This concept not only helps to alleviate urban waterlogging problems, but also effectively improves the urban ecological environment and promotes the sustainable use of water resources. In the construction of a sponge city, sewage treatment is a key link that is important for protecting the quality of the urban water environment and ecological balance.

[0003] Sewage treatment is an integral part of sponge city construction, and it directly affects the quality of the urban water environment and the health of the ecological system. Effective sewage treatment can reduce pollutant emissions, reduce pollution of natural water bodies, protect biodiversity, and also help improve the quality of life of urban residents. In addition, through reasonable sewage treatment and reuse, water resources can be recycled, alleviating the problem of urban water shortages.

[0004] However, existing sewage treatment systems still have some problems when faced with the requirements of sponge city construction. The existing technology has the defect that the pipeline connection is fixed and cannot be dynamically adjusted according to real-time load. This static topology limitation makes it difficult for the system to effectively respond to sudden changes in water volume. In addition, the existing system does not integrate water quality parameters and spatial location information, making the scheduling decision lack comprehensive data support. At the same time, manual analysis of sensor data is time-consuming and cannot meet the rapid response requirements of minute-level water volume mutations. SUMMARY

[0005] To solve the problem of how to achieve load balancing at each drainage point, dynamically optimize the discharge path from the drainage node to the target node, and reduce the comprehensive cost of sewage treatment, the present application provides solutions in the following aspects.

[0006] In a first aspect, an intelligent monitoring method for sewage treatment includes: acquiring sewage discharge parameters, water quality parameters, and drainage point coordinates at multiple rainwater collection and drainage nodes, and preprocessing, wherein the water quality parameters include node water quality parameters and pipeline water quality parameters; analyzing the real-time load rate of each drainage point based on the real-time sewage discharge and the designed maximum flow rate of the pipeline, calculating the water quality difference of the same water quality parameters between adjacent drainage nodes, and the pipeline water quality difference between the node water quality parameters of the drainage node and the water quality parameters of the connected pipeline, and calculating the path distance between adjacent drainage nodes based on the drainage point coordinates; comprehensively evaluating the discharge suitability index using an exponential function based on the water quality difference between adjacent drainage nodes, the pipeline water quality difference, and the path distance; fusing the real-time load rate and the discharge suitability index to form a comprehensive dynamic weight, and using the A algorithm to obtain the optimal path, and based on the comprehensive dynamic weight, processing the path conflict when multiple drainage nodes discharge simultaneously to achieve the selection of the drainage path of the drainage network.

[0007] The intelligent monitoring and dynamic optimization method significantly improves the efficiency and response capability of the sponge city sewage treatment system, ensures stable operation in the face of extreme conditions such as heavy rain, and effectively reduces the risk of pollutant diffusion and sewage treatment costs, while enhancing environmental protection, thereby achieving more sustainable and economically efficient urban water management.

[0008] Preferably, the calculation method of the real-time load rate includes: The product of the cross-sectional area of the drainage pipe and the maximum allowable flow rate is taken as the pipeline maximum flow rate, and the ratio of the real-time sewage discharge to the pipeline maximum flow rate is taken as the real-time load rate.

[0009] Preferably, the calculation of the water quality difference of the same water quality parameters at adjacent drainage nodes includes: Taking any drainage node as a target node, acquiring other nodes connected to the target node through the water pipe, calculating the square root of the sum of the differences between the water quality parameters of the target node and other nodes, and obtaining the water quality difference between the target node and other nodes.

[0010] By calculating the water quality difference between drainage nodes, the water quality similarity is quantitatively evaluated, and a smaller value indicates a higher water quality similarity. This helps to identify drainage paths with lower pollution diffusion risk and higher suitability, thereby enhancing the efficiency and effectiveness of sewage treatment and providing strong support for environmental protection, ensuring that the drainage system can be more intelligent and flexible to adapt to changing water quality conditions and treatment needs.

[0011] Preferably, the pipeline water quality difference includes: Taking any drainage node as the target node, the square root of the sum of the squares of the difference between the water quality parameters of the pipes connected to the target node and the water quality parameters of the target node is calculated to obtain the pipe water quality difference between the target node and the corresponding pipe.

[0012] By accurately calculating the water quality difference between the drainage node and the connected pipe, the optimization of the drainage path selection is realized. When the calculated water quality difference value is small, it indicates that the pipe water quality is highly consistent with the target node water quality, which helps to reduce the diffusion risk of pollutants in the drainage process and improve the suitability of the discharge path. This significantly improves the accuracy and efficiency of the sewage treatment system, while providing strong protection for environmental protection, ensuring that the system can flexibly adapt to changing water quality conditions and treatment needs.

[0013] Preferably, the calculation method of the discharge suitability index comprises: In response to the existence of multiple direct pipes between two drainage nodes, the product of the water quality difference, the preset distance weight coefficient and the path distance, and the pipe water quality difference is processed using a negative exponential function respectively, the obtained results are multiplied, and the maximum value is selected as the discharge suitability index; In response to the absence of multiple direct pipes between two drainage nodes, the product of the water quality difference and the product of the preset distance weight coefficient and the path distance is processed using a negative exponential function, and the discharge suitability index is obtained; In response to the absence of direct pipes between two drainage nodes, it indicates that the two drainage nodes cannot directly communicate drainage.

[0014] By accurately evaluating the suitability of different discharge paths in a complex drainage network, the path selection is optimized, the diffusion risk of pollutants is reduced, and the efficiency and environmental friendliness of the sewage treatment system are improved, ensuring that the system can intelligently adapt to different water quality conditions and treatment needs.

[0015] Preferably, the A algorithm based on the comprehensive dynamic weight uses A algorithm to obtain the optimal path, comprising the steps of: establishing a drainage network graph, wherein each drainage point is defined as a node in the graph, the connection between the drainage points is defined as an edge in the graph, and the weight of each edge is determined based on the comprehensive dynamic weight, and A the starting point and the end point of the algorithm; Using the comprehensive dynamic weight of each edge as a factor affecting the Euclidean distance, a heuristic function is constructed to estimate the shortest path cost from any node to the end point, and the optimal path is obtained.

[0016] In response to the plurality of paths passing through one or more same nodes at the same time, the cumulative comprehensive dynamic weight of the starting point of each path and the conflict node is calculated, the path corresponding to the maximum cumulative comprehensive weight is selected to pass through the conflict node preferentially, the pipeline occupation is marked, the conflict node is removed from the available node set, re-distribution is performed, the discharge suitability index and the comprehensive dynamic weight are recalculated, the path is re-planned, and the efficiency and stability of system operation are ensured.

[0017] In a second aspect, an intelligent sewage treatment monitoring system includes a processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement the above-described intelligent sewage treatment monitoring method.

[0018] The present application has the following effects: 1. The present application calculates the water quality difference between drainage nodes and the water quality difference of the pipeline, and the system can identify a discharge path with higher water quality matching degree. Selecting a path with high water quality matching degree for discharge can reduce the risk of pollutant diffusion when sewage is mixed, improve discharge suitability, reduce the difficulty of sewage treatment caused by water quality mismatch, make the treatment process more efficient, reduce treatment cost, optimize the discharge path, reduce the load of the sewage treatment plant, and improve the overall treatment efficiency.

[0019] 2. The Euclidean distance reflected by the comprehensive dynamic weight can more accurately estimate the path cost from any node to the end point. This cost includes not only the physical distance, but also the water quality difference and real-time load rate, thereby providing a more comprehensive path cost evaluation. By selecting the path with the lowest cost, the operation cost of sewage treatment and transportation can be reduced, and cost-effectiveness maximization is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 is a method flowchart of steps S1-S4 in the sewage treatment intelligent monitoring method of an embodiment of the present application.

[0021] Figure 2 is a structural block diagram of the sewage treatment intelligent monitoring system of an embodiment of the present application. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments of the present application.

[0023] Specific implementation scenarios: In the control of sponge city sewage treatment, there are multiple key nodes and pipelines that collectively affect the entire sewage treatment system. Collection points typically include: rainwater collection points, initial rainwater collection points, industrial area sewage collection points, and other collection points.

[0024] Rainwater collection points are facilities designed to collect natural rainfall and transport it to the drainage pipeline network. They are distributed throughout various areas of the city, such as streets, squares, parks, rooftops, and parking lots. Their primary function is to collect rainwater, reduce pre- runoff, alleviate urban waterlogging, and protect the city's drainage system. They cover various open areas in the city, collect relatively clean rainwater with low pollutant concentrations, and transport it to the drainage pipeline network. However, during heavy rain, the water volume at these nodes increases dramatically, causing a sudden increase in pipeline load rates and triggering local overloading or even blockage, affecting the normal operation of the drainage system.

[0025] Initial rainwater collection points are facilities specifically designed to collect rainwater formed during the initial stage of rainfall. These rainwaters typically contain high concentrations of pollutants. Initial rainwater collection points are mainly distributed in low-lying areas of the city or at the entrances of the drainage system to quickly collect initial rainwater. Since initial rainwater is formed by washing the ground and carrying a large amount of pollutants such as chemical oxygen demand (COD), suspended solids (SS), heavy metals, and oils, it needs to be pretreated. Pretreatment methods include sedimentation, filtration, and biological treatment, aiming to reduce pollutant concentrations and reduce the amount of high-concentration pollutants entering the drainage system. This not only helps to reduce the impact on sewage treatment plants but also effectively protects the water environment.

[0026] Industrial area sewage collection points are located within industrial areas, near factory drainage outlets or centralized drainage systems, and are primarily responsible for collecting industrial wastewater containing harmful substances such as heavy metals (e.g., lead, copper, zinc), organic solvents, chemical oxygen demand (COD), and biochemical oxygen demand (BOD). These wastewaters need to be treated deeply, including chemical, physical, and biological treatment, to ensure that the concentration of harmful substances meets the discharge standards, thereby reducing environmental pollution and improving the efficiency of sewage treatment plants.

[0027] During heavy rain, the water volume at rainwater collection points and initial rainwater collection points increases dramatically, which may cause a sudden increase in pipeline load rates and affect the normal operation of the drainage system. Therefore, intelligent monitoring systems are needed to dynamically adjust discharge paths to avoid overloading and blockage.

[0028] Industrial area sewage collection points contain specific harmful substances, and special attention should be paid to the selection of discharge paths to reduce environmental impact.

[0029] A drainage network graph is constructed for each region, with each node representing a drainage point and each edge representing a pipe connection between nodes. The weight of each edge is determined by a comprehensive dynamic weight that takes into account factors such as water quality differences, path distances, and real-time load rates. In this way, the drainage network graph can reflect the structure and operating status of the entire wastewater treatment system.

[0030] Referring to Figure 1 , a wastewater treatment intelligent monitoring method includes steps S1-S4, as follows: S1: Obtain wastewater discharge parameters, water quality parameters, and drainage point coordinates at multiple rainwater collection and drainage nodes, and preprocess, wherein the water quality parameters include node water quality parameters and pipe water quality parameters.

[0031] Deploy a multi-parameter real-time sensor network at the rainwater collection and drainage nodes to collect real-time wastewater discharge (unit: m³ / s), water quality parameters (such as pollutant concentrations such as COD, TN, TP, etc., unit: mg / L), and drainage point GPS coordinates (latitude and longitude), with a water quality parameter sampling frequency of 1 time / second.

[0032] If there are multiple directly connected pipes between nodes, then deploy a supplementary sensor network at the key points of the pipes to obtain the real-time pollutant concentration of the pipe segment between the corresponding drainage nodes (the first node to the second node) at a sampling frequency of 1 time / second. When the sensors within the pipe cannot work normally or the data is unavailable, then use the real-time pollutant concentration at the corresponding nodes within the pipe segment as an approximation of the pollutant concentration within the pipe.

[0033] Preprocess the water quality parameters, execute a data cleaning program to identify and eliminate invalid data or outliers caused by sensor failure or external interference, ensuring the accuracy and reliability of the input data. Standardize the valid water quality parameter data to eliminate the incommensurability between different water quality parameters due to different dimensions, ensuring that each parameter has a consistent measurement standard in subsequent analysis.

[0034] Obtain the pipe design maximum flow , the pipe connection topology relationship, stored in the form of an adjacency matrix, with the initial weight of the adjacency matrix set as the geographical distance of the pipe, and the edge weight value dynamically updated through the real-time load rate.

[0035] ​S2: Based on the real-time sewage discharge and maximum pipeline design flow of each drainage point, analyze the real-time load rate of each drainage point, calculate the water quality difference of the same water quality parameters between adjacent drainage nodes, and the pipeline water quality difference between the node water quality parameters of the drainage node and the water quality parameters of the connected pipeline. Based on the coordinates of the drainage point, calculate the path distance between adjacent drainage nodes.

[0036] The product of the cross-sectional area of ​​the drainage pipe and the maximum allowable flow velocity is taken as the maximum flow rate of the pipe, and the ratio of the real-time sewage discharge to the maximum flow rate of the pipe is taken as the real-time load rate.

[0037] Specifically, the real-time load rate satisfies the following relationship: ; In the formula, Indicates real-time load rate. This indicates the real-time flow rate within the pipeline. Indicates the maximum design flow rate of the pipeline. Indicates the pipe diameter (m). This indicates the maximum permissible flow rate.

[0038] It should be noted that, The cross-sectional area of ​​the pipe, the flow rate It is the volume passing through the cross-section of the pipe per unit time. The maximum velocity of fluid flowing in the pipe is determined by design standards or safety requirements to prevent the fluid in the pipe from causing excessive pressure or wear on the pipe.

[0039] Taking any drainage node as the target node, obtain other nodes connected to the target node through water pipes, calculate the square root of the sum of squares of the differences in water quality parameters between the target node and other nodes, and obtain the water quality differences between the target node and other nodes.

[0040] Specifically, the differences in water quality parameters at adjacent drainage nodes satisfy the following relationship: ; In the formula, Indicates the first The node and the first Differences in water quality at each node with the same water quality parameters Indicates the number of water quality types. Indicates the first At the node, the first Water quality parameters, It is the first At the node, the first Water quality parameters, with a total of [number] nodes Water quality parameters, among which, The smaller the value, the smaller the difference in water quality.

[0041] Taking any drainage node as the target node, calculate the square root of the sum of the squares of the differences between the water quality parameters of the pipes connected to the target node and the water quality parameters of the target node, and obtain the pipe water quality difference between the target node and the corresponding pipe.

[0042] ; In the formula, Indicates the relationship with the first The water quality differences in the pipes connected to each node are related to the first node. Differences in pipeline water quality parameters at individual nodes; The smaller the value, the more likely it is to be the first... The pollutant concentration at the node is similar to that at the first node. The node and the first The smaller the difference in pollutant concentration between pipeline nodes, the lower the risk of pollutant diffusion when wastewater mixes, and the more suitable the discharge. Indicates the number of water quality types. Indicates the first in the pipeline Water quality parameters, Indicates the first At the node, the first Water quality parameters.

[0043] To further optimize the selection of drainage paths, the system considers the possibility of multiple pipes between two adjacent drainage nodes. Specifically, the system determines which pipe best matches the drainage node in terms of water quality based on the differences between the calculated water quality parameters of the drainage node and the water quality parameters of each pipe, thus selecting a more suitable discharge path. This process ensures that the selected path is closest to the drainage node in terms of water quality, thereby reducing the risk of pollutant diffusion during wastewater mixing and improving the suitability of discharge.

[0044] Choosing a pipeline with water quality parameters consistent with those of the drainage node as the discharge path can reduce the risk of pollutant diffusion when sewage mixes, and ensure the stability of water quality along the discharge path. Selecting the most suitable pipeline can ensure that the sewage discharge path is closest to the drainage node in terms of water quality, thereby improving the suitability of discharge and reducing the cumbersome operations required for subsequent sewage treatment. Specifically, choosing a pipeline with the smallest water quality difference as the discharge path can effectively reduce the risk of pollutant diffusion, ensure the stable operation of the system, and improve the operating efficiency of the entire sewage treatment system.

[0045] S3: An appropriate discharge index is obtained by comprehensively evaluating the differences in water quality at adjacent drainage nodes, differences in water quality in pipelines, and path distance using an exponential function.

[0046] In response to the existence of multiple direct-connection pipes between two drainage nodes, the negative exponential function is applied to the water quality difference, the product of the preset distance weight coefficient and the path distance, and the pipe water quality difference. The results are then multiplied, and the maximum value is selected as the discharge suitability index. In response to the absence of multiple direct pipes between two drainage nodes, the product of water quality differences and the preset distance weighting coefficient with the path distance is processed using a negative exponential function and then multiplied to obtain the discharge suitability index. If there is no direct connection between two drainage nodes, it means that the two drainage nodes cannot communicate with each other for drainage.

[0047] Specifically, the emission suitability index satisfies the following relationship: ; ; In the formula, Indicates the first The node to the first The emission suitability index of each node, Indicates the first The node and the first Differences in water quality at each node with the same water quality parameters This represents the distance weighting coefficient, used for adjustment. The weighting is determined through calibration using historical data, with a value range of 0.001-0.01 and a default value of 0.002, balancing the effects of distance and water quality. Indicates the first The node and the first Path distance between nodes Indicates the relationship with the first The water quality differences in the pipes connected to each node are related to the first node. Differences in pipeline water quality parameters at individual nodes; Represented by natural numbers An exponential function with base 0. This represents the maximum value function.

[0048] In other words, the most suitable discharge path is selected to improve wastewater treatment efficiency and reduce the risk of pollutant diffusion. The discharge path is dynamically adjusted based on real-time data to adapt to fluctuations in water quality and quantity. By selecting a suitable discharge path, the load balance of the drainage system can be achieved to avoid overload. By optimizing the discharge path, wastewater treatment costs can be reduced.

[0049] S4: Integrate real-time load rate and emissions suitability index to form a comprehensive dynamic weight, and use A based on the comprehensive dynamic weight. The algorithm obtains the optimal path. In response to the conflict between the optimal paths when multiple drainage nodes discharge simultaneously, it handles the path conflict when multiple nodes discharge based on comprehensive dynamic weights, thereby realizing the selection of drainage path in the drainage network.

[0050] Construct a drainage network diagram, where each drainage point is defined as a node in the diagram, and the pipe connections between drainage points are defined as edges. The weight of each edge is determined based on a comprehensive dynamic weight. Determine A. The start and end points of the algorithm; By using the combined dynamic weight of each edge as a factor affecting the Euclidean distance, a heuristic function is constructed to estimate the shortest path cost from any node to the destination and obtain the optimal path.

[0051] In response to multiple paths passing through one or more of the same nodes simultaneously, the cumulative dynamic weight of the starting point of each path and the conflicting node is calculated. The path with the largest cumulative dynamic weight is selected to pass through the conflicting node first, and the pipeline is marked as occupied. The conflicting node is removed from the set of available nodes and redistributed. The emission suitability index and the cumulative dynamic weight are recalculated, and the path is replanned to ensure the efficiency and stability of the system operation.

[0052] This invention also provides an intelligent monitoring system for wastewater treatment. For example... Figure 2 As shown, the system includes a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a wastewater treatment intelligent monitoring method according to the first aspect of the present invention. The system also includes other components well-known to those skilled in the art, such as a communication bus and a communication interface. Their configurations and functions are known in the art and will not be described further here.

[0053] It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept, and these all fall within the scope of protection of this invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A method for intelligent monitoring of wastewater treatment, characterized in that, include: The wastewater discharge volume parameters, water quality parameters, and drainage point coordinates at multiple rainwater collection and drainage nodes are obtained and pre-processed. The water quality parameters include node water quality parameters and pipeline water quality parameters. Based on the real-time sewage discharge and pipeline design maximum flow rate of each drainage point, analyze the real-time load rate of each drainage point, calculate the water quality difference of the same water quality parameters between adjacent drainage nodes, and the pipeline water quality difference between the node water quality parameters of the drainage node and the water quality parameters of the connected pipeline. Based on the coordinates of the drainage point, calculate the path distance between adjacent drainage nodes. An appropriate discharge index is obtained by comprehensively evaluating the differences in water quality at adjacent drainage nodes, differences in water quality in pipelines, and path distance using an exponential function. By integrating real-time load rate and emissions suitability index to form a comprehensive dynamic weight, A is used based on this comprehensive dynamic weight. The algorithm obtains the optimal path. In response to the conflict between the optimal paths when multiple drainage nodes discharge simultaneously, it handles the path conflict when multiple nodes discharge based on comprehensive dynamic weights, thereby realizing the selection of drainage path in the drainage network.

2. The intelligent monitoring method for wastewater treatment according to claim 1, characterized in that, The calculation method for the real-time load rate includes: The product of the cross-sectional area of ​​the drainage pipe and the maximum allowable flow velocity is taken as the maximum flow rate of the pipe, and the ratio of the real-time sewage discharge to the maximum flow rate of the pipe is taken as the real-time load rate.

3. The intelligent monitoring method for wastewater treatment according to claim 1, characterized in that, The calculation of water quality differences with the same water quality parameters at adjacent drainage nodes includes: Taking any drainage node as the target node, obtain other nodes connected to the target node through water pipes, calculate the square root of the sum of squares of the differences in water quality parameters between the target node and other nodes, and obtain the water quality differences between the target node and other nodes.

4. The intelligent monitoring method for wastewater treatment according to claim 1, characterized in that, The differences in water quality in the pipeline include: Taking any drainage node as the target node, calculate the square root of the sum of the squares of the differences between the water quality parameters of the pipes connected to the target node and the water quality parameters of the target node, and obtain the pipe water quality difference between the target node and the corresponding pipe.

5. The intelligent monitoring method for wastewater treatment according to claim 1, characterized in that, The calculation method for the emission suitability index includes: In response to the existence of multiple direct-connection pipes between two drainage nodes, the negative exponential function is applied to the water quality difference, the product of the preset distance weight coefficient and the path distance, and the pipe water quality difference. The results are then multiplied, and the maximum value is selected as the discharge suitability index. In response to the absence of multiple direct pipes between two drainage nodes, the product of water quality differences and the preset distance weighting coefficient with the path distance is processed using a negative exponential function and then multiplied to obtain the discharge suitability index. If there is no direct connection between two drainage nodes, it means that the two drainage nodes cannot communicate with each other for drainage.

6. The intelligent monitoring method for wastewater treatment according to claim 1, characterized in that, The use of A based on comprehensive dynamic weights The algorithm for finding the optimal path includes the following steps: Construct a drainage network diagram, where each drainage point is defined as a node in the diagram, and the pipe connections between drainage points are defined as edges. The weight of each edge is determined based on a comprehensive dynamic weight. Determine A. The start and end points of the algorithm; By using the combined dynamic weight of each edge as a factor affecting the Euclidean distance, a heuristic function is constructed to estimate the shortest path cost from any node to the destination and obtain the optimal path.

7. The intelligent monitoring method for wastewater treatment according to claim 1, characterized in that, The method for handling path conflicts during multi-node drainage based on comprehensive dynamic weights includes: In response to multiple paths passing through one or more of the same nodes simultaneously, the cumulative dynamic weight of the starting point of each path and the conflicting node is calculated. The path with the largest cumulative dynamic weight is selected to pass through the conflicting node first, and the pipeline is marked as occupied. The conflicting node is removed from the set of available nodes and redistributed. The emission suitability index and the cumulative dynamic weight are recalculated, and the path is replanned to ensure the efficiency and stability of the system operation.

8. A wastewater treatment intelligent monitoring system, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement the intelligent monitoring method for wastewater treatment according to any one of claims 1-7.

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